Final Environmental Assessment for the Military Family Housing Privatization Initiative Columbus Air Force Base, Mississippi

DTIC Science & Technology

2005-05-03

daily trips are applied to the following factors depending on the corresponding years. Year 2005 through 2009: VOCE = .016 * Trips NOxE = .015...Trips PM10E = .0022 * Trips COE = .262 * Trips Year 2010 and beyond: VOCE = .012 * Trips NOxE = .013 * Trips PM10E = .0022 * Trips COE...262 * Trips To convert from pounds per day to tons per year: VOC (tons/yr) = VOCE * DPYII/2000 NOx (tons/yr) = NOxE * DPYII/2000 PM10 (tons/yr

Event-based prospective memory in mildly and severely autistic children.

PubMed

Sheppard, Daniel P; Kvavilashvili, Lia; Ryder, Nuala

2016-01-01

There is a growing body of research into the development of prospective memory (PM) in typically developing children but research is limited in autistic children (Aut) and rarely includes children with more severe symptoms. This study is the first to specifically compare event-based PM in severely autistic children to mildly autistic and typically developing children. Fourteen mildly autistic children and 14 severely autistic children, aged 5-13 years, were matched for educational attainment with 26 typically developing children aged 5-6 years. Three PM tasks and a retrospective memory task were administered. Results showed that severely autistic children performed less well than typically developing children on two PM tasks but mildly autistic children did not differ from either group. No group differences were found on the most motivating (a toy reward) task. The findings suggest naturalistic tasks and motivation are important factors in PM success in severely autistic children and highlights the need to consider the heterogeneity of autism and symptom severity in relation to performance on event-based PM tasks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Emissions Reduction Policies and Recent Trends in Southern California’s Ambient Air Quality

PubMed Central

Lurmann, Fred; Gilliland, Frank

2017-01-01

To assess accountability and effectiveness of air regulatory policies, we reviewed over 20 years of monitoring data, emissions estimates, and regulatory policies across several Southern California communities participating in a long-term study of children’s health. Between 1994 and 2011, air quality improved for NO2 and PM2.5 in virtually all the monitored communities. Average NO2 declined 28% to 53%, and PM2.5 decreased 13% to 54%. Year-to-year PM2.5 variability at lower-pollution sites was large compared to changes in long-term trends. PM10 and O3 decreases were largest in communities that were initially among the most polluted. Trends in annual average NO2, PM2.5, and PM10 concentrations in higher pollution communities were generally consistent with NOx, ROG, SOx, PM2.5, and PM10 emissions decreases. Reductions observed at one of the higher PM2.5 sites, Mira Loma, was generally within the range expected from reductions observed in ROG, NOx, SOx, and PM2.5 emissions. Despite a 38% increase in regional motor vehicle activity, vigorous economic growth, and a 30% population increase, total estimated emissions of NOx, ROG, SOx, PM2.5, and PM10 decreased by 54%, 65%, 40%, 21%, and 15%, respectively, during the 20-year time period. Emission control strategies in California have achieved dramatic reductions in ambient NO2, O3, PM2.5, and PM10. However, additional reductions will still be needed to achieve current health-based clean air standards. PMID:25947128

Emissions reduction policies and recent trends in Southern California's ambient air quality.

PubMed

Lurmann, Fred; Avol, Ed; Gilliland, Frank

2015-03-01

To assess accountability and effectiveness of air regulatory policies, we reviewed more than 20 years of monitoring data, emissions estimates, and regulatory policies across several southern California communities participating in a long-term study of children's health. Between 1994 and 2011, air quality improved for NO2 and PM2.5 in virtually all the monitored communities. Average NO2 declined 28% to 53%, and PM2.5 decreased 13% to 54%. Year-to-year PM2.5 variability at lower pollution sites was large compared to changes in long-term trends. PM10 and O3 decreases were largest in communities that were initially among the most polluted. Trends in annual average NO2, PM2.5, and PM10 concentrations in higher pollution communities were generally consistent with NOx, ROG, SOx, PM2.5, and PM10 emissions decreases. Reductions observed at one of the higher PM2.5 sites, Mira Loma, were generally within the range expected from reductions observed in ROG, NOx, SOx, and PM2.5 emissions. Despite a 38% increase in regional motor vehicle activity, vigorous economic growth, and a 30% population increase, total estimated emissions of NOx, ROG, SOx, PM2.5, and PM10 decreased by 54%, 65%, 40%, 21%, and 15%, respectively, during the 20-year time period. Emission control strategies in California have achieved dramatic reductions in ambient NO2, O3, PM2.5, and PM10. However, additional reductions will still be needed to achieve current health-based clean air standards. For many cities facing the challenge of reducing air pollution to meet health-based standards, the emission control policies and pollution reduction programs adopted in southern California should serve as an example of the potential success of aggressive, comprehensive, and integrated approaches. Policies targeting on-road mobile emissions were the single most important element for observed improvements in the Los Angeles region. However, overall program success was the result of a much broader approach designed to achieve emission reductions across all major pollutants and emissions categories.

EXPOSURE ASSESSMENT FROM THE NERL RESEARCH TRIANGLE PARK PARTICULATE MATTER PANEL STUDY

EPA Science Inventory

The U.S. Environmental Protection Agency performed a particulate matter (PM) exposure assessment based on data from the National Exposure Research Laboratory (NERL) Research Triangle Park (RTP) Particulate Matter (PM) Panel Study. This study was a one-year investigation of PM ...

Final Environmental Assessment: To Relocate Air Force Explosive Ordnance Disposal Administrative Complex at Eglin Air Force Base

DTIC Science & Technology

2006-10-01

Trips PM10E = .0022 * Trips COE = .262 * Trips Year 2010 and beyond: VOCE = .012 * Trips NOxE = .013 * Trips PM10E = .0022 * Trips COE...Air Force Base, Florida To convert from pounds per day to tons per year: VOC (tons/yr) = VOCE * DPYII/2000 NOx (tons/yr) = NOxE * DPYII/2000

Environmental Assessment for the Construction of a Three-Bay Multi-Aircraft Hangar Tinker Air Force Base, Oklahoma

DTIC Science & Technology

2008-01-01

Years 2005 through 2009: VOCE = .016 * Trips NOxE = .015 * Trips PM10E = .0022 * Trips COE = .262 * Trips Appendix A: Air Quality January 2008...Final EA for the Construction of a Three-Bay Multi-Aircraft Hangar Page A-9 Tinker Air Force Base, Oklahoma Years 2010 and beyond: VOCE = .012...Trips NOxE = .013 * Trips PM10E = .0022 * Trips COE = .262 * Trips To convert from pounds per day to tons per year: VOC (tons/year) = VOCE

78 FR 14020 - Approval and Promulgation of Air Quality Implementation Plans; Delaware; the 2002 Base Year...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-04

... X ), volatile organic compounds (VOCs), PM 2.5 , coarse particles (PM 10 ), ammonia (NH 3 ), and... particles (PM 10 ), ammonia (NH 3 ), and sulfur dioxide (SO 2 ). [FR Doc. 2013-04810 Filed 3-1-13; 8:45 am...

Final Environmental Assessment for the Military Family Housing Privatization Initiative

DTIC Science & Technology

2006-09-01

Year 2005 through 2009: VOCE = .016 * Trips NOxE = .015 * Trips PM10E = .0022 * Trips COE = .262 * Trips Appendix A Additional Materials Final...Environmental Assessment Page A-39 Military Family Housing Privatization Initiative Robins Air Force Base, Georgia Year 2010 and beyond: VOCE ...yr) = VOCE * DPYII/2000 NOx (tons/yr) = NOxE * DPYII/2000 PM10 (tons/yr) = PM10E * DPYII/2000 CO (tons/yr) = COE * DPYII/2000 Where: Area of

Effects of drinking patterns on prospective memory performance in college students.

PubMed

Zamroziewicz, Marta; Raskin, Sarah A; Tennen, Howard; Austad, Carol S; Wood, Rebecca M; Fallahi, Carolyn R; Dager, Alecia D; Sawyer, Broderick; Leen, Samantha; Pearlson, Godfrey D

2017-02-01

Traditional college students are at a critical juncture in the development of prospective memory (PM). Their brains are vulnerable to the effects of alcohol. There were 123 third and fourth year college students, 19-23 years old, who completed the Self-Rating Effects of Alcohol (SREA), Modified Timeline Follow-back (TFLB), Brief Young Adult Alcohol Consequences Scale (BYAACS), and Alcohol Effects Questionnaire (AEQ) once per month on a secure online database, as reported elsewhere (Dager et al., 2013). Data from the 6 months immediately before memory testing were averaged. In a single testing session participants were administered the Mini International Neuropsychiatric Interview-Diagnostic and Statistical Manual for Mental Disorders-Fourth Edition-Text Revision (MINI-DSM-IV-TR), measures of PM (event-based and time-based), and retrospective memory (RM). Based on the average score of six consecutive monthly responses to the SREA, TLFB, and AEQ, students were classified as nondrinkers, light drinkers, or heavy drinkers (as defined previously; Dager et al., 2013). Alcohol-induced amnesia (blackout) was measured with the BYAACS. We found a relationship between these alcohol use classifications and time-based PM, such that participants who were classified as heavier drinkers were more likely to forget to perform the time-based PM task. We also found that self-reported alcohol-induced amnesia (blackouts) during the month immediately preceding memory testing was associated with lower performance on the event-based PM task. Participants' ability to recall the RM tasks suggested the PM items were successfully encoded even when they were not carried out, and we observed no relationship between alcohol use and RM performance. Heavy alcohol use in college students may be related to impairments in PM. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Characteristics of particulate matter and heterogeneous traffic in the urban area of India

NASA Astrophysics Data System (ADS)

Srimuruganandam, B.; Shiva Nagendra, S. M.

2011-06-01

This paper presents the characteristics of particulate matter (PM) mass concentrations (PM 10, PM 2.5 and PM 1) emitted from heterogeneous traffic in Chennai city during monsoon, winter and summer seasons of the year 2007-2009. The heterogeneous traffic characteristics at the study region indicated dominance of 2-wheelers (58%) followed by the 4-wheelers (29%), 3-wheelers (7%), light commercial vehicle (LCV = 2%) and heavy commercial vehicle (HCV = 4%). The vintage analysis of vehicles showed that 11, 24, 35 and 30% of the total vehicles were 15, 10, 5 and <5 years old vehicles, respectively (75% of LCV and 70% of HCV were older than 10 years and 82% of 2W, 85% of 3W, 79% of 4W were less than 10 years old). The travel demand on weekdays at the study site revealed that 60% of the traffic in the morning peak hours was due to school and office trips and 40% was due to the business trips. During the weekends the peak rush hours traffic was dominated by travel demand (90%) due to tourists and pleasure trips. At study region, the PM 10 comprised a large fraction of PM 2.5 (56% of PM 2.5 and 44% of PM 1), while PM 2.5 comprised a large proportion of PM 1 (81%). The estimated PM 2.5/PM 10 ratios for monsoon, winter and summer seasons were ranged between 0.44-0.62, 0.66-0.76 and 0.62-0.73, respectively. The high PM 2.5/PM 10 ratios ( R2 = 0.92-0.98) during peak hour indicated significant contribution from the vehicular emissions. Further, it was found that the PM 10, PM 2.5 and PM 1 concentrations at the study site followed similar trend of 2W, 3W, 4W and HCV during morning peak hour traffic. The analysis of 24-hr average PM 10, PM 2.5 and PM 1 concentrations showed maximum during monsoon (188.75 ± 71.75, 83.91 ± 33.18, 65.81 ± 28.47 μg/m 3) and winter (134.58 ± 64.55, 72.95 ± 39.27, 59.00 ± 31.15 μg/m 3) and minimum during summer (75.96 ± 43.15, 42.16 ± 19.76, 31.40 ± 16.05 μg/m 3) seasons. The 24-hr average PM 10 and PM 2.5 indicated maximum violations of Indian national ambient air quality standards (NAAQS for PM 10 = 100 μg/m 3 and PM 2.5 = 60 μg/m 3) during winter and monsoon seasons and minimum during summer season. Further, PM 10 and PM 2.5 concentrations were well above the prescribed 24-hr average world health organization (WHO) standards (PM 10 = 50 μg/m 3; PM 2.5 = 25 μg/m 3). The PM chemical characterization indicated the dominance of soil based crustal elements (74%) - Al, Ca, Fe and Mg, salt based components (16%)-Na and K, and the other trace elements (10%) such as B, Ba, Cd, Co, Cr, Cu, Ga, Mn, Mo, Ni, Pb, Rb, Se, Sr, Te, V and Zn. The percentage composition of different group of elements indicates traffic as the main source of PM emission at the study site. The ion analysis showed presence of more anions (36-82%) than the cations (18-64%). SO 42- and Mg 2+ were major constituents.

Disability-adjusted life years and economic cost assessment of the health effects related to PM2.5 and PM10 pollution in Mumbai and Delhi, in India from 1991 to 2015.

PubMed

Maji, Kamal Jyoti; Dikshit, Anil Kumar; Deshpande, Ashok

2017-02-01

Particulate air pollution is becoming a serious public health concern in urban cities in India due to air pollution-related health effects associated with disability-adjusted life years (DALYs) and economic loss. To obtain the quantitative result of health impact of particulate matter (PM) in most populated Mumbai City and most polluted Delhi City in India, an epidemiology-based exposure-response function has been used to calculate the attributable number of mortality and morbidity cases from 1991 to 2015 in a 5-year interval and the subsequent DALYs, and economic cost is estimated of the health damage based on unit values of the health outcomes. Here, we report the attributable number of mortality due to PM 10 in Mumbai and Delhi increased to 32,014 and 48,651 in 2015 compared with 19,291 and 19,716 in year 1995. And annual average mortality due to PM 2.5 in Mumbai and Delhi was 10,880 and 10,900. Premature cerebrovascular disease (CEV), ischemic heart disease (IHD), and chronic obstructive pulmonary disease (COPD) causes are about 35.3, 33.3, and 22.9% of PM 2.5 -attributable mortalities. Total DALYs due to PM10 increased from 0.34 million to 0.51 million in Mumbai and 0.34 million to 0.75 million in Delhi from average year 1995 to 2015. Among all health outcomes, mortality and chronic bronchitis shared about 95% of the total DALYs. Due to PM 10 , the estimated total economic cost at constant price year 2005 US$ increased from 2680.87 million to 4269.60 million for Mumbai City and 2714.10 million to 6394.74 million for Delhi City, from 1995 to 2015, and the total amount accounting about 1.01% of India's gross domestic product (GDP). A crucial presumption is that in 2030, PM 10 levels would have to decline by 44% (Mumbai) and 67% (Delhi) absolutely to maintain the same health outcomes in year 2015 levels. The results will help policy makers from pollution control board for further cost-benefit analyses of air pollution management programs in Mumbai and Delhi.

Identifying PM2.5 and PM0.1 sources for epidemiological studies in California.

PubMed

Hu, Jianlin; Zhang, Hongliang; Chen, Shuhua; Ying, Qi; Wiedinmyer, Christine; Vandenberghe, Francois; Kleeman, Michael J

2014-05-06

The University of California-Davis_Primary (UCD_P) model was applied to simultaneously track ∼ 900 source contributions to primary particulate matter (PM) in California for seven continuous years (January 1st, 2000 to December 31st, 2006). Predicted source contributions to primary PM2.5 mass, PM1.8 elemental carbon (EC), PM1.8 organic carbon (OC), PM0.1 EC, and PM0.1 OC were in general agreement with the results from previous source apportionment studies using receptor-based techniques. All sources were further subjected to a constraint check based on model performance for PM trace elemental composition. A total of 151 PM2.5 sources and 71 PM0.1 sources contained PM elements that were predicted at concentrations in general agreement with measured values at nearby monitoring sites. Significant spatial heterogeneity was predicted among the 151 PM2.5 and 71 PM0.1 source concentrations, and significantly different seasonal profiles were predicted for PM2.5 and PM0.1 in central California vs southern California. Population-weighted concentrations of PM emitted from various sources calculated using the UCD_P model spatial information differed from the central monitor estimates by up to 77% for primary PM2.5 mass and 148% for PM2.5 EC because the central monitor concentration is not representative of exposure for nearby population. The results from the UCD_P model provide enhanced source apportionment information for epidemiological studies to examine the relationship between health effects and concentrations of primary PM from individual sources.

The association between ambient inhalable particulate matter and the disease burden of respiratory disease: An ecological study based on ten-year time series data in Tianjin, China.

PubMed

Zeng, Qiang; Wu, Ziting; Jiang, Guohong; Wu, Xiaoyin; Li, Pei; Ni, Yang; Xiong, Xiuqin; Wang, Xinyan; Parasat; Li, Guoxing; Pan, Xiaochuan

2017-08-01

There is limited evidence available worldwide about the quantitative relationship between particulate matter with an aerodynamic diameter of less than 10µm (PM 10 ) and years of life lost (YLL) caused by respiratory diseases (RD), especially regarding long-term time series data. We investigated the quantitative exposure-response association between PM 10 and the disease burden of RD. We obtained the daily concentration of ambient pollutants (PM 10 , nitrogen dioxide and sulphur dioxide), temperature and relative humidity data, as well as the death monitoring data from 2001 to 2010 in Tianjin. Then, a time series database was built after the daily YLL of RD was calculated. We applied a generalized additive model (GAM) to estimate the burden of PM 10 on daily YLL of RD and to determine the effect (the increase of daily YLL) of every 10μg/m 3 increase in PM 10 on health. We found that every 10μg/m 3 increase in PM 10 was associated with the greatest increase in YLL of 0.84 (95% CI: 0.45, 1.23) years at a 2-day (current day and previous day, lag01) moving average PM 10 concentration for RD. The association between PM 10 and YLL was stronger in females and the elderly (≥65 years of age). The association between PM 10 and YLL of RD differed according to district. These findings also provide new epidemiological evidence for respiratory disease prevention. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison of physician referral and insurance claims data-based risk prediction as approaches to identify patients for care management in primary care: an observational study.

PubMed

Freund, Tobias; Gondan, Matthias; Rochon, Justine; Peters-Klimm, Frank; Campbell, Stephen; Wensing, Michel; Szecsenyi, Joachim

2013-10-20

Primary care-based care management (CM) could reduce hospital admissions in high-risk patients. Identification of patients most likely to benefit is needed as resources for CM are limited. This study aimed to compare hospitalization and mortality rates of patients identified for CM either by treating primary care physicians (PCPs) or predictive modelling software for hospitalization risk (PM). In 2009, a cohort of 6,026 beneficiaries of a German statutory health insurance served as a sample for patient identification for CM by PCPs or commercial PM (CSSG 0.8, Verisk Health). The resulting samples were compared regarding hospitalization and mortality rates in 2010 and in the two year period before patient selection. No CM-intervention was delivered until the end of 2010 and PCPs were blinded for the assessment of hospitalization rates. In 2010, hospitalization rates of PM-identified patients were 80% higher compared to PCP-identified patients. Mortality rates were also 8% higher in PM-identified patients if compared to PCP-identified patients (10% vs. 2%). The hospitalization rate of patients independently identified by both PM and PCPs was numerically between PM- and PCP-identified patients. Time trend between 2007 and 2010 showed decreasing hospitalization rates in PM-identified patients (-15% per year) compared to increasing rates in PCP-identified patients (+34% per year). PM identified patients with higher hospitalization and mortality rates compared to PCP-referred patients. But the latter showed increasing hospitalization rates over time thereby suggesting that PCPs may be able to predict future deterioration in patients with relatively good current health status. These patients may most likely benefit from preventive services like CM.

The effects of HIV disease and older age on laboratory-based, naturalistic, and self-perceived symptoms of prospective memory: does retrieval cue type and delay interval matter?

PubMed

Avci, G; Loft, S; Sheppard, D P; Woods, S P

2016-11-01

There is a rising prevalence of older HIV+ adults who are at risk of deficits in higher order neurocognitive functions and associated problems in everyday functioning. The current study applied multiprocess theory to examine the effects of HIV and aging on measures of laboratory-based, naturalistic, and self-perceived symptoms of prospective memory (PM). Participants included 125 Younger (48 with HIV, age = 32 ± 4.6 years) and 189 Older (112 with HIV, age = 56 ± 4.9 years) adults. Controlling for global neurocognitive functioning, mood, and other demographics, older age and HIV had independent effects on long-delay time-based PM in the laboratory, whereas on a naturalistic PM task older HIV- adults performed better than older HIV+ adults and younger persons. In line with the naturalistic findings, older age, but not HIV, was associated with a relative sparing of self-perceived PM failures in daily life across longer delay self-cued intervals. Findings suggest that, even in relatively younger aging cohorts, the effects of HIV and older age on PM can vary across PM delay intervals by the strategic demands of the retrieval cue type, are expressed differently in the laboratory and in daily life, and are independent of other higher order neurocognitive functions (e.g., retrospective memory).

The Effects of HIV Disease and Older Age on Laboratory-based, Naturalistic, and Self-Perceived Symptoms of Prospective Memory: Does Retrieval Cue Type and Delay Interval Matter?

PubMed Central

Avci, G.; Loft, S.; Sheppard, D.P.; Woods, S.P.

2016-01-01

There is a rising prevalence of older HIV+ adults who are at risk of deficits in higher-order neurocognitive functions and associated problems in everyday functioning. The current study applied Multiprocess Theory to examine the effects of HIV and aging on measures of laboratory-based, naturalistic, and self-perceived symptoms of prospective memory (PM). Participants included 125 Younger (48 with HIV, age = 32±4.6 years) and 189 Older (112 with HIV, age = 56±4.9 years) adults. Controlling for global neurocognitive functioning, mood, and other demographics, older age and HIV had independent effects on long-delay time-based PM in the laboratory, whereas on a naturalistic PM task older HIV− adults performed better than older HIV+ adults and younger persons. In line with the naturalistic findings, older age, but not HIV, was associated with a relative sparing of self-perceived PM failures in daily life across longer delay self-cued intervals. Findings suggest that, even in relatively younger aging cohorts, the effects of HIV and older age on PM can vary across PM delay intervals by the strategic demands of the retrieval cue type, are expressed differently in the laboratory and in daily life, and are independent of other higher-order neurocognitive functions (e.g., retrospective memory). PMID:27002287

Spatial Analysis of Ambient PM2.5 Exposure and Bladder Cancer Mortality in Taiwan

PubMed Central

Yeh, Hsin-Ling; Hsu, Shang-Wei; Chang, Yu-Chia; Chan, Ta-Chien; Tsou, Hui-Chen; Chang, Yen-Chen; Chiang, Po-Huang

2017-01-01

Fine particulate matter (PM2.5) is an air pollutant that is receiving intense regulatory attention in Taiwan. In previous studies, the effect of air pollution on bladder cancer has been explored. This study was conducted to elucidate the effect of atmospheric PM2.5 and other local risk factors on bladder cancer mortality based on available 13-year mortality data. Geographically weighted regression (GWR) was applied to estimate and interpret the spatial variability of the relationships between bladder cancer mortality and ambient PM2.5 concentrations, and other variables were covariates used to adjust for the effect of PM2.5. After applying a GWR model, the concentration of ambient PM2.5 showed a positive correlation with bladder cancer mortality in males in northern Taiwan and females in most of the townships in Taiwan. This is the first time PM2.5 has been identified as a risk factor for bladder cancer based on the statistical evidence provided by GWR analysis. PMID:28489042

Final Environmental Assessment for the Okaloosa Regional Airport Expansion at Eglin Air Force Base, FL

DTIC Science & Technology

2006-06-01

construction Total daily trips are then applied to the following factors depending on the corresponding years. Year 2005 through 2009: VOCE ...016 * Trips NOxE = .015 * Trips PM10E = .0022 * Trips COE = .262 * Trips Year 2010 and beyond: VOCE = .012 * Trips NOxE = .013 * Trips PM10E...0022 * Trips COE = .262 * Trips To convert from pounds per day to tons per year: VOC (tons/yr) = VOCE * DPYII/2000 Nox (tons/yr) = NOxE

Prospective memory functioning among ecstasy/polydrug users: evidence from the Cambridge Prospective Memory Test (CAMPROMPT).

PubMed

Hadjiefthyvoulou, Florentia; Fisk, John E; Montgomery, Catharine; Bridges, Nikola

2011-06-01

Prospective memory (PM) deficits in recreational drug users have been documented in recent years. However, the assessment of PM has largely been restricted to self-reported measures that fail to capture the distinction between event-based and time-based PM. The aim of the present study is to address this limitation. Extending our previous research, we augmented the range laboratory measures of PM by employing the CAMPROMPT test battery to investigate the impact of illicit drug use on prospective remembering in a sample of cannabis only, ecstasy/polydrug and non-users of illicit drugs, separating event and time-based PM performance. We also administered measures of executive function and retrospective memory in order to establish whether ecstasy/polydrug deficits in PM were mediated by group differences in these processes. Ecstasy/polydrug users performed significantly worse on both event and time-based prospective memory tasks in comparison to both cannabis only and non-user groups. Furthermore, it was found that across the whole sample, better retrospective memory and executive functioning was associated with superior PM performance. Nevertheless, this association did not mediate the drug-related effects that were observed. Consistent with our previous study, recreational use of cocaine was linked to PM deficits. PM deficits have again been found among ecstasy/polydrug users, which appear to be unrelated to group differences in executive function and retrospective memory. However, the possibility that these are attributable to cocaine use cannot be excluded.

MAIAC-based long-term spatiotemporal trends of PM2.5 in Beijing, China.

PubMed

Liang, Fengchao; Xiao, Qingyang; Wang, Yujie; Lyapustin, Alexei; Li, Guoxing; Gu, Dongfeng; Pan, Xiaochuan; Liu, Yang

2018-03-01

Satellite-driven statistical models have been proven to be able to provide spatially resolved PM 2.5 estimates worldwide. The North China Plain has been suffering from severe PM 2.5 pollution in recent years. An accurate assessment of the spatiotemporal characteristics of PM 2.5 levels in this region is crucial to design effective air pollution control policy. Our objective is to estimate daily PM 2.5 concentrations at 1km spatial resolution from 2004 to 2014 in Beijing and its surrounding areas using the Multi-angle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD). A high-performance three-stage model was developed with AOD, meteorological, demographic and land use variables as predictors, which includes a custom-designed PM 2.5 gap-filling method. The 11-year average annual coverage increased from 177days to 279days and annual PM 2.5 prediction error decreased from 14.1μg/m 3 to 8.3μg/m 3 after gap-filling techniques were applied. Results show that the 11-year overall mean of predicted PM 2.5 was 67.1μg/m 3 in our study domain. The cross-validation R 2 value of our model is 0.82 in 2013 and 0.79 in 2014. In addition, the models predicted historical PM 2.5 concentrations with relatively high accuracy at the seasonal and annual levels (R 2 ranged from 0.78 to 0.86). Our long-term PM 2.5 prediction filled the gaps left by ground monitors, which would be beneficial to PM 2.5 related epidemiological studies in Beijing. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantifying Future PM2.5 and Associated Health Effects Due to Changes in US Wildfires

NASA Astrophysics Data System (ADS)

Pierce, J. R.; Val Martin, M.; Ford, B.; Zelasky, S.; Heald, C. L.; Li, F.; Lawrence, D. M.; Fischer, E. V.

2017-12-01

Fine particulate matter (PM2.5) from landscape fires has been shown to adversely affect visibility, air quality and and health across the US. Fire activity is strongly related to climate and human activities. Predictions based on climate scenarios and future land cover projections that consider socioeconomic development suggest that fire activity will rise dramatically over the next decades. As PM2.5 is associated with increased mortality and morbidity rates, increases in emissions from landscape fires may alter the health burden on the US population. Here we present an analysis of the changes in future wildfire activity and consequences for PM2.5 and health over the US from 2000 to 2100. We employ the global Community Earth System Model (CESM) with the IPCC RCP projections. Within CESM, we use a process-based global fire parameterization to project future climate-driven and human-caused fire emissions. From these simulations, we determine the current and future impact on PM2.5 concentrations and visibility for different regions of the US, and we also calculate the mortality attributable to PM2.5 and wildfire-specific PM2.5 using existing concentration-response functions. Results show that although total PM2.5 concentrations in the US are projected to be similar in 2100 as in 2000, the dominant source of PM2.5 will change. Under the RCP8.5 climate projection and SSP3 population projection, non-fire emissions (mostly anthropogenic) are projected to decrease, but PM2.5 from CONUS and non-US wildfires is projected to increase from approximately 20% of all PM2.5 in 2000 to 80% of all PM2.5 in 2100. Furthermore, although the US population is expected to decline between 2000 and 2100, the mortality attributable to wildfire smoke is expected to increase from 25,000 deaths per year in 2000 to 75,000 deaths per year in 2100.

The mortality impacts of fine particles in France.

PubMed

Pascal, Mathilde; de Crouy Chanel, Perrine; Wagner, Vérène; Corso, Magali; Tillier, Claude; Bentayeb, Malek; Blanchard, Myriam; Cochet, Amandine; Pascal, Laurence; Host, Sabine; Goria, Sarah; Le Tertre, Alain; Chatignoux, Edouard; Ung, Aymeric; Beaudeau, Pascal; Medina, Sylvia

2016-11-15

Worldwide, air pollution has become a main environmental cause of premature mortality. This burden is largely due to fine particles. Recent cohort studies have confirmed the health risks associated with chronic exposure to PM2.5 for European and French populations. We assessed the mortality impact of PM2.5 in continental France using these new results. Based on a meta-analysis of French and European cohorts, we computed a shrunken estimate of PM2.5-mortality relationship for the French population (RR 1.15 [1.05:1.25] for a 10μg/m(3) increase in PM2.5). This RR was applied to PM2.5 annual concentrations estimated at a fine spatial scale, using a classical health impacts assessment method. The health benefits associated with alternative scenarios of improving air quality were computed for 36,219 French municipalities for 2007-2008. 9% of the total mortality in continental France is attributable to anthropogenic PM2.5. This represents >48,000 deaths per year, and 950,000years of life lost per year, more than half occurring in urban areas larger than 100,000 inhabitants. If none of the municipalities exceeded the World Health Organization guideline value for PM2.5 (10μg/m(3)), the total mortality could be decreased by 3%, corresponding to 400,000years of life saved per year. Results were consistent with previous estimates of the long-term mortality impacts of fine particles in France. These findings show that further actions to improve air quality in France would substantially improve health. Copyright © 2016 Elsevier B.V. All rights reserved.

78 FR 22423 - Approval and Promulgation of Air Quality Implementation Plans; West Virginia; The 2002 Base Year...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-16

... (PM 10 ), nitrogen oxides (NO X ), volatile organic compounds (VOC), ammonia (NH 3 ), and sulfur... , coarse particles (PM 10 ), ammonia (NH 3 ), and sulfur dioxide (SO 2 ). [FR Doc. 2013-08835 Filed 4-15-13...

Long-term prospective memory impairment following mild traumatic brain injury with loss of consciousness: findings from the Canadian Longitudinal Study on Aging.

PubMed

Bedard, Marc; Taler, Vanessa; Steffener, Jason

2017-12-18

We aimed to examine the extent to which loss of consciousness (LOC) following mild traumatic brain injury (mTBI) may be associated with impairments in time- and event-based prospective memory (PM). PM is thought to involve executive processes and be subserved by prefrontal regions. Neuroimaging research suggests alterations to these areas of the brain several years after mTBI, particularly if LOC was experienced. However, it remains unclear whether impairments in time- or event-based functioning may persist more than a year after mTBI, and what the link with duration of LOC may be. Analyses were run on data from the Canadian Longitudinal Study on Aging, a nationwide study on health and aging involving individuals between the ages of 45-85. The present study consisted of 1937 participants who experienced mTBI more than 12 months prior, of whom 1146 reported spending less than 1 min unconscious, and 791 had LOC between 1 and 20 min, and 13,525 cognitively healthy adults. Participants were administered the Miami Prospective Memory Test, and tests of retrospective memory and executive functioning. Both mTBI groups were impaired in time-based PM relative to people with no history of TBI. Time- and event-based impairments were predicted by older age, and executive dysfunction among those who spent more time unconscious. Those with mTBI with LOC may experience impairments in PM, particularly in conditions of high demand on executive processes (time-based PM). Implications for interventions aimed at ameliorating PM among those who have experienced mTBI are discussed.

77 FR 73924 - Approval and Promulgation of Air Quality Implementation Plans; West Virginia; The 2002 Base Year...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-12

... particles (PM 10 ), ammonia (NH 3 ) and sulfur dioxide (SO 2 ). EPA has reviewed the results, procedures and... , coarse particles (PM 10 ), ammonia (NH 3 ) and sulfur dioxide (SO 2 ). [FR Doc. 2012-29893 Filed 12-11-12...

Final Environmental Assessment: For Construction of an Addition to the Joint Strike Fighter Reprogramming Facility, Building 614, on Eglin Air Force Base, Florida

DTIC Science & Technology

2007-01-01

VOCE = .016 * Trips NOxE = .015 * Trips PM10E = .0022 * Trips COE = .262 * Trips Year 2010 and beyond: VOCE = .012 * Trips NOxE = .013...Trips PM10E = .0022 * Trips COE = .262 * Trips E = emissions To convert from pounds per day to tons per year: VOC (tons/yr) = VOCE * DPYII/2000 lbs

The impact of age, ongoing task difficulty, and cue salience on preschoolers' prospective memory performance: the role of executive function.

PubMed

Mahy, Caitlin E V; Moses, Louis J; Kliegel, Matthias

2014-11-01

The current study examined the impact of age, ongoing task (OT) difficulty, and cue salience on 4- and 5-year-old children's prospective memory (PM) and also explored the relation between individual differences in executive function (working memory, inhibition, and shifting) and PM. OT difficulty and cue salience are predicted to affect the detection of PM cues based on the multiprocess framework, yet neither has been thoroughly investigated in young children. OT difficulty was manipulated by requiring children to sort cards according to the size of pictured items (easy) or by opposite size (difficult), and cue salience was manipulated by placing a red border around half of the target cues (salient) and no border around the other cues (non-salient). The 5-year-olds outperformed the 4-year-olds on the PM task, and salient PM cues resulted in better PM cues compared with non-salient cues. There was no main effect of OT difficulty, and the interaction between cue salience and OT difficulty was not significant. However, a planned comparison revealed that the combination of non-salient cues and a difficult OT resulted in significantly worse PM performance than that in all of the other conditions. Inhibition accounted for significant variance in PM performance for non-salient cues and for marginally significant variance for salient cues. Furthermore, individual differences in inhibition fully mediated the effect of age on PM performance. Results are discussed in the context of the multiprocess framework and with reference to preschoolers' difficulty with the executive demands of dividing attention between the OT and PM task. Copyright © 2014 Elsevier Inc. All rights reserved.

Effect of Exhaust- and Nonexhaust-Related Components of Particulate Matter on Long-Term Survival After Stroke.

PubMed

Desikan, Anita; Crichton, Siobhan; Hoang, Uy; Barratt, Benjamin; Beevers, Sean D; Kelly, Frank J; Wolfe, Charles D A

2016-12-01

Outdoor air pollution represents a potentially modifiable risk factor for stroke. We examined the link between ambient pollution and mortality up to 5 years poststroke, especially for pollutants associated with vehicle exhaust. Data from the South London Stroke Register, a population-based register covering an urban, multiethnic population, were used. Hazard ratios (HR) for a 1 interquartile range increase in particulate matter <2.5 µm diameter (PM 2.5 ) and PM <10 µm (PM 10 ) were estimated poststroke using Cox regression, overall and broken down into exhaust and nonexhaust components. Analysis was stratified for ischemic and hemorrhagic strokes and was further broken down by Oxford Community Stroke Project classification. The hazard of death associated with PM 2.5 up to 5 years after stroke was significantly elevated (P=0.006) for all strokes (HR=1.28; 95% confidence interval [CI], 1.08-1.53) and ischemic strokes (HR, 1.32; 95% CI, 1.08-1.62). Within ischemic subtypes, PM 2.5 pollution increased mortality risk for total anterior circulation infarcts by 2-fold (HR, 2.01; 95% CI, 1.17-3.48; P=0.012) and by 78% for lacunar infarcts (HR, 1.78; 95% CI, 1.18-2.66; P=0.006). PM 10 pollution was associated with 45% increased mortality risk for lacunar infarct strokes (HR, 1.45; 95% CI, 1.06-2.00; P=0.022). Separating PM 2.5 and PM 10 into exhaust and nonexhaust components did not show increased mortality. Exposure to certain outdoor PM pollution, particularly PM 2.5 , increased mortality risk poststroke up to 5 years after the initial stroke. © 2016 American Heart Association, Inc.

Particulate matter pollution in the megacities of the Pearl River Delta, China - a systematic literature review and health risk assessment.

PubMed

Jahn, Heiko J; Schneider, Alexandra; Breitner, Susanne; Eissner, Romy; Wendisch, Manfred; Krämer, Alexander

2011-07-01

The exposure to ambient particulate matter (PM) pollution is a major threat to public health. Chinese megacities are coined by high levels of PM. Our aims were to examine the concentration levels of PM in megacities (Guangzhou, Hong Kong, and Shenzhen) of the Pearl River Delta (PRD), South China; to compare the results with international and national air quality guidelines; and to assess the health impact in terms of possible reductions in premature deaths due to PM reduction. The Medline(®) data base was used to identify published studies (systematic literature search). Based on our appraisal criteria 13 studies remained in the analysis. Additionally, publicly available data were extracted from data sources provided by municipal authorities of the cities under study. PM data reported in μg/m(3) were abstracted from single studies and municipal reports. If possible, the PM data were stratified for season of data collection (summer/winter half-year) and simple means were calculated for cities, seasons and months. Based on the abstracted data, a health impact assessment (HIA) was done in order to estimate potential preventable premature deaths due to PM pollution in the cities. Almost all PM data exceeded national and international air quality guidelines. Our HIA showed that in Guangzhou ten thousands of premature deaths could be prevented if the PM burden was reduced to these air quality limit values. We identified no suitable epidemiological study reporting PM according to our study protocol. Further epidemiological studies should be carried out to more precisely determine the spatial distribution of PM-related health risks in PRD. Environmental protection measures and public health interventions are required to reduce burden of PM-related diseases in PRD. Copyright © 2011 Elsevier GmbH. All rights reserved.

Final Environmental Assessment for Construction of a Precision Measurement Equipment Laboratory Facility on Eglin Air Force Base, FL

DTIC Science & Technology

2006-10-01

daily trips are then applied to the following factors depending on the corresponding years. Year 2005 through 2009: VOCE = .016 * Trips NOxE...015 * Trips PM10E = .0022 * Trips COE = .262 * Trips Year 2010 and beyond: VOCE = .012 * Trips NOxE = .013 * Trips PM10E = .0022 * Trips COE...262 * Trips E = emissions To convert from pounds per day to tons per year: VOC (tons/yr) = VOCE * DPYII/2000 lbs/ton NOx (tons/yr) = NOxE * DPYII

Polycyclic aromatic hydrocarbons (PAHs) in atmospheric PM2.5 and PM10 at a coal-based industrial city: Implication for PAH control at industrial agglomeration regions, China

NASA Astrophysics Data System (ADS)

Wu, Di; Wang, Zongshuang; Chen, Jianhua; Kong, Shaofei; Fu, Xiao; Deng, Hongbing; Shao, Guofan; Wu, Gang

2014-11-01

Eighteen polycyclic aromatic hydrocarbons (PAHs) in PM2.5 and PM10 are identified and quantified at five sites of E'erduosi in 2005 by GC-MS. Total PAH concentrations in PM2.5 and PM10 are in the ranges of 0.58-145.01 ng m- 3 and 5.80-180.32 ng m- 3 for the five sites, decreasing as coal-chemical base site (ZGE) > heavy industrial site (QPJ) > residential site with heavy traffic (DS) > suburban site surrounded by grassland (HJQ) > background site (QGN) for both PM2.5 and PM10. PAH concentrations in the coal-chemical base site are 250 and 31.1 times of those in the background site. Flu, Pyr, Chr, BbF, BeP, IND and BghiP are abundant for the coal-chemical base site, totally accounting for 75% of the PAH concentrations. 4, 5 and 6 rings PAHs are dominant, accounting for 88.9-94.2% and 90.5-94.1% of PAHs in PM2.5 and PM10, respectively. Combustion-derived PAH concentrations cover 42%-84% and 75%-82% of PAHs in PM2.5 and PM10, indicating large amounts of combustion sources existed for them in E'erduosi. PAH compositions between PM2.5 and PM10 are quite different from each other for sites with few human activities (HJQ and QGN) by coefficient of divergence analysis. Results obtained from principal component analysis and diagnostic ratios indicate that coal combustion, vehicle emission, wood combustion and industrial processes are the main sources for PAHs in E'erduosi. According to BaP equivalent concentration, the potential health risk of PAHs in PM2.5 at the two industrial sites ZGE and QPJ are 537 and 460 times of those for the background site. And they are 4.3 and 3.7 times of those for the residential site. The potential PAH pollution in particles at other industrial agglomeration regions that occurred in China in recent years should be paid attention by the local government.

Use of Satellite Observations for Long-Term Exposure Assessment of Global Concentrations of Fine Particulate Matter

PubMed Central

Martin, Randall V.; Brauer, Michael; Boys, Brian L.

2014-01-01

Background: More than a decade of satellite observations offers global information about the trend and magnitude of human exposure to fine particulate matter (PM2.5). Objective: In this study, we developed improved global exposure estimates of ambient PM2.5 mass and trend using PM2.5 concentrations inferred from multiple satellite instruments. Methods: We combined three satellite-derived PM2.5 sources to produce global PM2.5 estimates at about 10 km × 10 km from 1998 through 2012. For each source, we related total column retrievals of aerosol optical depth to near-ground PM2.5 using the GEOS–Chem chemical transport model to represent local aerosol optical properties and vertical profiles. We collected 210 global ground-based PM2.5 observations from the literature to evaluate our satellite-based estimates with values measured in areas other than North America and Europe. Results: We estimated that global population-weighted ambient PM2.5 concentrations increased 0.55 μg/m3/year (95% CI: 0.43, 0.67) (2.1%/year; 95% CI: 1.6, 2.6) from 1998 through 2012. Increasing PM2.5 in some developing regions drove this global change, despite decreasing PM2.5 in some developed regions. The estimated proportion of the population of East Asia living above the World Health Organization (WHO) Interim Target-1 of 35 μg/m3 increased from 51% in 1998–2000 to 70% in 2010–2012. In contrast, the North American proportion above the WHO Air Quality Guideline of 10 μg/m3 fell from 62% in 1998–2000 to 19% in 2010–2012. We found significant agreement between satellite-derived estimates and ground-based measurements outside North America and Europe (r = 0.81; n = 210; slope = 0.68). The low bias in satellite-derived estimates suggests that true global concentrations could be even greater. Conclusions: Satellite observations provide insight into global long-term changes in ambient PM2.5 concentrations. Satellite-derived estimates and ground-based PM2.5 observations from this study are available for public use. Citation: van Donkelaar A, Martin RV, Brauer M, Boys BL. 2015. Use of satellite observations for long-term exposure assessment of global concentrations of fine particulate matter. Environ Health Perspect 123:135–143; http://dx.doi.org/10.1289/ehp.1408646 PMID:25343779

77 FR 31262 - Approval and Promulgation of Implementation Plans; Kentucky; Louisville; Fine Particulate Matter...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-25

... Promulgation of Implementation Plans; Kentucky; Louisville; Fine Particulate Matter 2002 Base Year Emissions... approve the fine particulate matter (PM 2.5 ) 2002 base year emissions inventory, portion of the State...), a reasonable further progress (RFP) plan, contingency measures, a 2002 base year emissions inventory...

77 FR 45532 - Approval and Promulgation of Implementation Plans; Michigan; Detroit-Ann Arbor Nonattainment Area...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-01

... 2005 Base Year Emissions Inventory AGENCY: Environmental Protection Agency (EPA). ACTION: Proposed rule. SUMMARY: EPA is proposing to approve the fine particulate matter (PM 2.5 ) 2005 base year emissions...) plan, contingency measures, a 2005 base year emissions inventory and other planning SIP revisions...

Prenatal Particulate Air Pollution and Asthma Onset in Urban Children. Identifying Sensitive Windows and Sex Differences.

PubMed

Hsu, Hsiao-Hsien Leon; Chiu, Yueh-Hsiu Mathilda; Coull, Brent A; Kloog, Itai; Schwartz, Joel; Lee, Alison; Wright, Robert O; Wright, Rosalind J

2015-11-01

The influence of particulate air pollution on respiratory health starts in utero. Fetal lung growth and structural development occurs in stages; thus, effects on postnatal respiratory disorders may differ based on timing of exposure. We implemented an innovative method to identify sensitive windows for effects of prenatal exposure to particulate matter with a diameter less than or equal to 2.5 μm (PM2.5) on children's asthma development in an urban pregnancy cohort. Analyses included 736 full-term (≥37 wk) children. Each mother's daily PM2.5 exposure was estimated over gestation using a validated satellite-based spatiotemporal resolved model. Using distributed lag models, we examined associations between weekly averaged PM2.5 levels over pregnancy and physician-diagnosed asthma in children by age 6 years. Effect modification by sex was also examined. Most mothers were ethnic minorities (54% Hispanic, 30% black), had 12 or fewer years of education (66%), and did not smoke in pregnancy (80%). In the sample as a whole, distributed lag models adjusting for child age, sex, and maternal factors (education, race and ethnicity, smoking, stress, atopy, prepregnancy obesity) showed that increased PM2.5 exposure levels at 16-25 weeks gestation were significantly associated with early childhood asthma development. An interaction between PM2.5 and sex was significant (P = 0.01) with sex-stratified analyses showing that the association exists only for boys. Higher prenatal PM2.5 exposure at midgestation was associated with asthma development by age 6 years in boys. Methods to better characterize vulnerable windows may provide insight into underlying mechanisms.

77 FR 72966 - Approval and Promulgation of Air Quality Implementation Plans; Maryland; The 2002 Base Year...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-07

... (VOCs), PM 2.5 , coarse particles (PM 10 ), ammonia (NH 3 ), and sulfur dioxide (SO 2 ). EPA has... ), ammonia (NH 3 ), and sulfur dioxide (SO 2 ). [FR Doc. 2012-29611 Filed 12-6-12; 8:45 am] BILLING CODE 6560...

Predicting daily PM2.5 concentrations in Texas using high-resolution satellite aerosol optical depth.

PubMed

Zhang, Xueying; Chu, Yiyi; Wang, Yuxuan; Zhang, Kai

2018-08-01

The regulatory monitoring data of particulate matter with an aerodynamic diameter <2.5μm (PM 2.5 ) in Texas have limited spatial and temporal coverage. The purpose of this study is to estimate the ground-level PM 2.5 concentrations on a daily basis using satellite-retrieved Aerosol Optical Depth (AOD) in the state of Texas. We obtained the AOD values at 1-km resolution generated through the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm based on the images retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellites. We then developed mixed-effects models based on AODs, land use features, geographic characteristics, and weather conditions, and the day-specific as well as site-specific random effects to estimate the PM 2.5 concentrations (μg/m 3 ) in the state of Texas during the period 2008-2013. The mixed-effects models' performance was evaluated using the coefficient of determination (R 2 ) and square root of the mean squared prediction error (RMSPE) from ten-fold cross-validation, which randomly selected 90% of the observations for training purpose and 10% of the observations for assessing the models' true prediction ability. Mixed-effects regression models showed good prediction performance (R 2 values from 10-fold cross validation: 0.63-0.69). The model performance varied by regions and study years, and the East region of Texas, and year of 2009 presented relatively higher prediction precision (R 2 : 0.62 for the East region; R 2 : 0.69 for the year of 2009). The PM 2.5 concentrations generated through our developed models at 1-km grid cells in the state of Texas showed a decreasing trend from 2008 to 2013 and a higher reduction of predicted PM 2.5 in more polluted areas. Our findings suggest that mixed-effects regression models developed based on MAIAC AOD are a feasible approach to predict ground-level PM 2.5 in Texas. Predicted PM 2.5 concentrations at the 1-km resolution on a daily basis can be used for epidemiological studies to investigate short- and long-term health impact of PM 2.5 in Texas. Copyright © 2017 Elsevier B.V. All rights reserved.

Differential focal and nonfocal prospective memory accuracy in a demographically diverse group of nondemented community-dwelling older adults.

PubMed

Chi, Susan Y; Rabin, Laura A; Aronov, Avner; Fogel, Joshua; Kapoor, Ashu; Wang, Cuiling

2014-11-01

Although prospective memory (PM) is compromised in mild cognitive impairment (MCI), it is unclear which specific cognitive processes underlie these PM difficulties. We investigated older adults' performance on a computerized event-based focal versus nonfocal PM task that made varying demands on the amount of attentional control required to support intention retrieval. Participants were nondemented individuals (mean age=81.8 years; female=66.1%) enrolled in a community-based longitudinal study, including those with amnestic MCI (aMCI), nonamnestic MCI (naMCI), subjective cognitive decline (SCD), and healthy controls (HC). Participants included in the primary analysis (n=189) completed the PM task and recalled and/or recognized both focal and nonfocal PM cues presented in the task. Participants and their informants also completed a questionnaire assessing everyday PM failures. Relative to HC, those with aMCI and naMCI were significantly impaired in focal PM accuracy (p<.05). In a follow-up analysis that included 13 additional participants who successfully recalled and/or recognized at least one of the two PM cues, the naMCI group showed deficits in nonfocal PM accuracy (p<.05). There was a significant negative correlation between informant reports of PM difficulties and nonfocal PM accuracy (p<.01). PM failures in aMCI may be primarily related to impairment of spontaneous retrieval processes associated with the medial temporal lobe system, while PM failures in naMCI potentially indicate additional deficits in executive control functions and prefrontal systems. The observed focal versus nonfocal PM performance profiles in aMCI and naMCI may constitute specific behavioral markers of PM decline that result from compromise of separate neurocognitive systems.

77 FR 45956 - Approval and Promulgation of Implementation Plans; Kentucky; Louisville; Fine Particulate Matter...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-02

... Promulgation of Implementation Plans; Kentucky; Louisville; Fine Particulate Matter 2002 Base Year Emissions... action to approve the 1997 annual fine particulate matter (PM 2.5 ) 2002 base year emissions inventory... 45957

77 FR 6529 - Approval and Promulgation of Implementation Plans; Alabama, Georgia, and Tennessee: Chattanooga...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-08

...; Particulate Matter 2002 Base Year Emissions Inventory AGENCY: Environmental Protection Agency (EPA). ACTION: Proposed rule. SUMMARY: EPA is proposing to approve the fine particulate matter (PM 2.5 ) 2002 base year...

Implementing the US air quality standard for PM2.5 worldwide can prevent millions of premature deaths per year.

PubMed

Giannadaki, Despina; Lelieveld, Jos; Pozzer, Andrea

2016-08-23

Air pollution by fine aerosol particles is among the leading causes of poor health and premature mortality worldwide. The growing awareness of this issue has led several countries to implement air pollution legislation. However, populations in large parts of the world are still exposed to high levels of ambient particulate pollution. The main aim of this work is to evaluate the potential impact of implementing current air quality standards for fine particulate matter (PM2.5) in the European Union (EU), United States (US) and other countries where PM2.5 levels are high. We use a high-resolution global atmospheric chemistry model combined with epidemiological concentration response functions to investigate premature mortality attributable to PM2.5 in adults ≥30 years and children <5 years. We perform sensitivity studies to estimate the reductions in mortality that could be achieved if the PM2.5 air quality standards of the EU and US and other national standards would be implemented worldwide. We estimate the global premature mortality by PM2.5 at 3.15 million/year in 2010. China is the leading country with about 1.33 million, followed by India with 575 thousand and Pakistan with 105 thousand per year. For the 28 EU member states we estimate 173 thousand and for the United States 52 thousand premature deaths in 2010. Based on sensitivity analysis, applying worldwide the EU annual mean standard of 25 μg/m(3) for PM2.5 could reduce global premature mortality due to PM2.5 exposure by 17 %; while within the EU the effect is negligible. With the 2012 revised US standard of 12 μg/m(3) premature mortality by PM2.5 could drop by 46 % worldwide; 4 % in the US and 20 % in the EU, 69 % in China, 49 % in India and 36 % in Pakistan. These estimates take into consideration that about 22 % of the global PM2.5 related mortality cannot be avoided due to the contribution of natural PM2.5 sources, mainly airborne desert dust and PM2.5 from wild fires. Our results reflect the need to adopt stricter limits for annual mean PM2.5 levels globally, like the US standard of 12 μg/m(3) or an even lower limit to substantially reduce premature mortality in most of the world.

Comparison of Satellite Data with Ground-Based Measurements for Assessing Local Distributions of PM2.5 in Northeast Mexico.

NASA Astrophysics Data System (ADS)

Carmona, J.; Mendoza, A.; Lozano, D.; Gupta, P.; Mejia, G.; Rios, J.; Hernández, I.

2017-12-01

Estimating ground-level PM2.5 from satellite-derived Aerosol Optical Depth (AOD) through statistical models is a promising method to evaluate the spatial and temporal distribution of PM2.5 in regions where there are no or few ground-based observations, i.e. Latin America. Although PM concentrations are most accurately measured using ground-based instrumentation, the spatial coverage is too sparse to determine local and regional variations in PM. AOD satellite data offer the opportunity to overcome the spatial limitation of ground-based measurements. However, estimating PM surface concentrations from AOD satellite data is challenging, since multiple factors can affect the relationship between the total-column of AOD and the surface-concentration of PM. In this study, an Assembled Multiple Linear Regression Model (MLR) and a Neural Network Model (NN) were performed to estimate the relationship between the AOD and ground-concentrations of PM2.5 within the Monterrey Metropolitan Area (MMA). The MMA is located in northeast Mexico and is the third most populated urban area in the country. Episodes of high PM pollution levels are frequent throughout the year at the MMA. Daily averages of meteorological and air quality parameters were determined from data recorded at 5 monitoring sites of the MMA air quality monitoring network. Daily AOD data were retrieved from the MODIS sensor onboard the Aqua satellite. Overall, the best performance of the models was obtained using an AOD at 550 µm from the MYD04_3k product in combination with Temperature, Relative Humidity, Wind Speed and Wind Direction ground-based data. For the MLR performed, a correlation coefficient of R 0.6 and % bias of -6% were obtained. The NN showed a better performance than the MLR, with a correlation coefficient of R 0.75 and % bias -4%. The results obtained confirmed that satellite-derived AOD in combination with meteorological fields may allow to estimate PM2.5 local distributions.

Associations between long-term exposure to chemical constituents of fine particulate matter (PM2.5) and mortality in Medicare enrollees in the eastern United States.

PubMed

Chung, Yeonseung; Dominici, Francesca; Wang, Yun; Coull, Brent A; Bell, Michelle L

2015-05-01

Several epidemiological studies have reported that long-term exposure to fine particulate matter (PM2.5) is associated with higher mortality. Evidence regarding contributions of PM2.5 constituents is inconclusive. We assembled a data set of 12.5 million Medicare enrollees (≥ 65 years of age) to determine which PM2.5 constituents are a) associated with mortality controlling for previous-year PM2.5 total mass (main effect); and b) elevated in locations exhibiting stronger associations between previous-year PM2.5 and mortality (effect modification). For 518 PM2.5 monitoring locations (eastern United States, 2000-2006), we calculated monthly mortality rates, monthly long-term (previous 1-year average) PM2.5, and 7-year averages (2000-2006) of major PM2.5 constituents [elemental carbon (EC), organic carbon matter (OCM), sulfate (SO42-), silicon (Si), nitrate (NO3-), and sodium (Na)] and community-level variables. We applied a Bayesian hierarchical model to estimate location-specific mortality rates associated with previous-year PM2.5 (model level 1) and identify constituents that contributed to the spatial variability of mortality, and constituents that modified associations between previous-year PM2.5 and mortality (model level 2), controlling for community-level confounders. One-standard deviation (SD) increases in 7-year average EC, Si, and NO3- concentrations were associated with 1.3% [95% posterior interval (PI): 0.3, 2.2], 1.4% (95% PI: 0.6, 2.4), and 1.2% (95% PI: 0.4, 2.1) increases in monthly mortality, controlling for previous-year PM2.5. Associations between previous-year PM2.5 and mortality were stronger in combination with 1-SD increases in SO42- and Na. Long-term exposures to PM2.5 and several constituents were associated with mortality in the elderly population of the eastern United States. Moreover, some constituents increased the association between long-term exposure to PM2.5 and mortality. These results provide new evidence that chemical composition can partly explain the differential toxicity of PM2.5.

Year-long simulation of gaseous and particulate air pollutants in India

NASA Astrophysics Data System (ADS)

Kota, Sri Harsha; Guo, Hao; Myllyvirta, Lauri; Hu, Jianlin; Sahu, Shovan Kumar; Garaga, Rajyalakshmi; Ying, Qi; Gao, Aifang; Dahiya, Sunil; Wang, Yuan; Zhang, Hongliang

2018-05-01

Severe pollution events occur frequently in India but few studies have investigated the characteristics, sources, and control strategies for the whole country. A year-long simulation was carried out in India to provide detailed information of spatial and temporal distribution of gas species and particulate matter (PM). The concentrations of O3, NO2, SO2, CO, as well as PM2.5 and its components in 2015 were predicted using Weather Research Forecasting (WRF) and the Community Multiscale Air Quality (CMAQ) models. Model performance was validated against available observations from ground based national ambient air quality monitoring stations in major cities. Model performance of O3 does not always meet the criteria suggested by the US Environmental Protection Agency (EPA) but that of PM2.5 meets suggested criteria by previous studies. The performance of model was better on days with high O3 and PM2.5 levels. Concentrations of PM2.5, NO2, CO and SO2 were highest in the Indo-Gangetic region, including northern and eastern India. PM2.5 concentrations were higher during winter and lower during monsoon season. Winter nitrate concentrations were 160-230% higher than yearly average. In contrast, the fraction of sulfate in total PM2.5 was maximum in monsoon and least in winter, due to decrease in temperature and solar radiation intensity in winter. Except in southern India, where sulfate was the major component of PM2.5, primary organic aerosol (POA) fraction in PM2.5 was highest in all regions of the country. Fractions of secondary components were higher on bad days than on good days in these cities, indicating the importance of control of precursors for secondary pollutants in India.

Airborne particulate matter from primarily geologic, non-industrial sources at levels below National Ambient Air Quality Standards is associated with outpatient visits for asthma and quick-relief medication prescriptions among children less than 20 years old enrolled in Medicaid in Anchorage, Alaska.

PubMed

Chimonas, Marc-Andre R; Gessner, Bradford D

2007-03-01

In Anchorage, Alaska, particulates with aerodynamic diameter < or = 10 micro m (PM(10)) arise primarily from natural, geologic sources, and particulates with aerodynamic diameter < or = 2.5 micro m (PM(2.5)) arise primarily from automobile emissions. The current study used a population-based time-series analysis design to evaluate the effects of daily and weekly PM(10) and PM(2.5) on respiratory health outcomes among children <20 years of age residing in Anchorage enrolled in Medicaid. All generated estimating equations models were adjusted for season, year, weekends, temperature, wind speed, and precipitation. Relative to the days with PM(10) mass concentration < or = 13 micro g/m(3), a significant 9.3% increase (RR: 1.093, 95% CI: 1.004-1.191) in the rate of outpatient visits for asthma occurred during days with PM(10) of 20-33 micro g/m(3). No further dose-response occurred for days with PM(10) > or = 34 micro g/m(3). A significant 18.1% increase (RR: 1.181, 95% CI: 1.010-1.381) in the rate of quick-relief medication prescriptions occurred during days with PM(10) of 34-60 micro g/m(3), and a 28.8% increase (RR: 1.288, 95% CI: 1.026-1.619) occurred during days with PM(10) > or = 61 micro g/m(3). Similar results for outpatient asthma visits and quick-relief medication occurred in weekly models. There were no significant associations with PM(2.5) in either daily or weekly models. These subtle but statistically significant associations suggest that non-industrial, geologic sources of PM(10) may have measurable health effects at levels below current national standards.

77 FR 60339 - Approval and Promulgation of Air Quality Implementation Plans; Pennsylvania; The 2002 Base Year...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-03

... Promulgation of Air Quality Implementation Plans; Pennsylvania; The 2002 Base Year Inventory for the Pittsburgh... particulate matter (PM 2.5 ) 2002 base year emissions inventory portion of the Pennsylvania State... Valley, PA nonattainment area (hereafter referred to as the Area). The emissions inventory is part of the...

77 FR 1873 - Approval and Promulgation of Implementation Plans; Georgia; Rome; Fine Particulate Matter 2002...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-12

...] Approval and Promulgation of Implementation Plans; Georgia; Rome; Fine Particulate Matter 2002 Base Year... is taking direct final action to approve the fine particulate matter (PM 2.5 ) 2002 base year... progress (RFP) plan, contingency measures, a 2002 base year emissions inventory and other planning SIP...

77 FR 66547 - Approval and Promulgation of Implementation Plans; Michigan; Detroit-Ann Arbor Nonattainment Area...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-06

... 2005 Base Year Emissions Inventory AGENCY: Environmental Protection Agency (EPA). ACTION: Final rule. SUMMARY: EPA is approving the fine particulate matter (PM 2.5 ) 2005 base year emissions inventory, a... 2005 base year emissions inventory for the Detroit-Ann Arbor area. EPA did not receive any comments...

77 FR 12487 - Approval and Promulgation of Implementation Plans; Georgia; Atlanta; Fine Particulate Matter 2002...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-01

...] Approval and Promulgation of Implementation Plans; Georgia; Atlanta; Fine Particulate Matter 2002 Base Year... is taking direct final action to approve the fine particulate matter (PM 2.5 ) 2002 base year... progress (RFP) plan, contingency measures, a 2002 base year emissions inventory and other planning SIP...

77 FR 12724 - Approval and Promulgation of Implementation Plans; Georgia; Macon; Fine Particulate Matter 2002...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-02

...] Approval and Promulgation of Implementation Plans; Georgia; Macon; Fine Particulate Matter 2002 Base Year... is taking direct final action to approve the fine particulate matter (PM 2.5 ) 2002 base year... progress (RFP) plan, contingency measures, a 2002 base year emissions inventory and other planning SIP...

Data Recording in Performance Management: Trouble With the Logics

ERIC Educational Resources Information Center

Groth Andersson, Signe; Denvall, Verner

2017-01-01

In recent years, performance management (PM) has become a buzzword in public sector organizations. Well-functioning PM systems rely on valid performance data, but critics point out that conflicting rationale or logic among professional staff in recording information can undermine the quality of the data. Based on a case study of social service…

A Virtual Week study of prospective memory function in autism spectrum disorders.

PubMed

Henry, Julie D; Terrett, Gill; Altgassen, Mareike; Raponi-Saunders, Sandra; Ballhausen, Nicola; Schnitzspahn, Katharina M; Rendell, Peter G

2014-11-01

Prospective memory (PM) refers to the implementation of delayed intentions, a cognitive ability that plays a critical role in daily life because of its involvement in goal-directed behavior and consequently the development and maintenance of independence. Emerging evidence indicates that PM may be disrupted in autism spectrum disorders (ASDs), potentially contributing to the functional difficulties that characterize this group. However, the degree, nature, and specificity of ASD-related impairment remains poorly understood. In the current study, children between 8 and 12 years of age who were diagnosed with ASDs (n=30) were compared with typically developing children (n=30) on a child-appropriate version of the Virtual Week board game. This measure provides an opportunity to investigate the different sorts of PM failures that occur. The ASD group showed significant PM impairment on measures of time-based (but not event-based) prospective remembering. However, only a subtle difference emerged between regular and irregular PM tasks, and group differences were consistent across these tasks. Because regular and irregular tasks differentially load retrospective memory, these data imply that the PM difficulties seen in ASDs may primarily reflect a monitoring deficit and not an encoding and memory storage deficit. PM performance was poorer under conditions of high ongoing task absorption, but the magnitude of this effect did not vary as a function of group. In both groups, time-based (but not event-based) PM difficulties were associated with functional outcomes in daily life, but only an inconsistent association with executive control emerged. Copyright © 2014 Elsevier Inc. All rights reserved.

Short-term population-based non-linear concentration-response associations between fine particulate matter and respiratory diseases in Taipei (Taiwan): a spatiotemporal analysis.

PubMed

Yu, Hwa-Lung; Chien, Lung-Chang

2016-01-01

Fine particulate matter <2.5 μm (PM2.5) has been associated with human health issues; however, findings regarding the influence of PM2.5 on respiratory disease remain inconsistent. The short-term, population-based association between the respiratory clinic visits of children and PM2.5 exposure levels were investigated by considering both the spatiotemporal distributions of ambient pollution and clinic visit data. We applied a spatiotemporal structured additive regression model to examine the concentration-response (C-R) association between children's respiratory clinic visits and PM2.5 concentrations. This analysis was separately performed on three respiratory disease categories that were selected from the Taiwanese National Health Insurance database, which includes 41 districts in the Taipei area of Taiwan from 2005 to 2007. The findings reveal a non-linear C-R pattern of PM2.5, particularly in acute respiratory infections. However, a PM2.5 increase at relatively lower levels can elevate the same-day respiratory health risks of both preschool children (<6 years old) and schoolchildren (6-14 years old). In preschool children, same-day health risks rise when concentrations increase from 0.76 to 7.44 μg/m(3), and in schoolchildren, same-day health risks rise when concentrations increase from 0.76 to 7.52 μg/m(3). Changes in PM2.5 levels generally exhibited no significant association with same-day respiratory risks, except in instances where PM2.5 levels are extremely high, and these occurrences do exhibit a significant positive influence on respiratory health that is especially notable in schoolchildren. A significant high relative rate of respiratory clinic visits are concentrated in highly populated areas. We highlight the non-linearity of the respiratory health effects of PM2.5 on children to investigate this population-based association. The C-R relationship in this study can provide a highly valuable alternative for assessing the effects of ambient air pollution on human health.

Impact of Particulate Matter Exposure and Surrounding "Greenness" on Chronic Absenteeism in Massachusetts Public Schools.

PubMed

MacNaughton, Piers; Eitland, Erika; Kloog, Itai; Schwartz, Joel; Allen, Joseph

2017-02-20

Chronic absenteeism is associated with poorer academic performance and higher attrition in kindergarten to 12th grade (K-12) schools. In prior research, students who were chronically absent generally had fewer employment opportunities and worse health after graduation. We examined the impact that environmental factors surrounding schools have on chronic absenteeism. We estimated the greenness (Normalized Difference Vegetation Index (NDVI)) and fine particulate matter air pollution (PM 2.5 ) within 250 m and 1000 m respectively of each public school in Massachusetts during the 2012-2013 academic year using satellite-based data. We modeled chronic absenteeism rates in the same year as a function of PM 2.5 and NDVI, controlling for race and household income. Among the 1772 public schools in Massachusetts, a 0.15 increase in NDVI during the academic year was associated with a 2.6% ( p value < 0.0001) reduction in chronic absenteeism rates, and a 1 μg/m³ increase in PM 2.5 during the academic year was associated with a 1.58% ( p value < 0.0001) increase in chronic absenteeism rates. Based on these percentage changes in chronic absenteeism, a 0.15 increase in NDVI and 1 μg/m³ increase in PM 2.5 correspond to 25,837 fewer students and 15,852 more students chronically absent each year in Massachusetts respectively. These environmental impacts on absenteeism reinforce the need to protect green spaces and reduce air pollution around schools.

Impact of Particulate Matter Exposure and Surrounding “Greenness” on Chronic Absenteeism in Massachusetts Public Schools

PubMed Central

MacNaughton, Piers; Eitland, Erika; Kloog, Itai; Schwartz, Joel; Allen, Joseph

2017-01-01

Chronic absenteeism is associated with poorer academic performance and higher attrition in kindergarten to 12th grade (K-12) schools. In prior research, students who were chronically absent generally had fewer employment opportunities and worse health after graduation. We examined the impact that environmental factors surrounding schools have on chronic absenteeism. We estimated the greenness (Normalized Difference Vegetation Index (NDVI)) and fine particulate matter air pollution (PM2.5) within 250 m and 1000 m respectively of each public school in Massachusetts during the 2012–2013 academic year using satellite-based data. We modeled chronic absenteeism rates in the same year as a function of PM2.5 and NDVI, controlling for race and household income. Among the 1772 public schools in Massachusetts, a 0.15 increase in NDVI during the academic year was associated with a 2.6% (p value < 0.0001) reduction in chronic absenteeism rates, and a 1 μg/m3 increase in PM2.5 during the academic year was associated with a 1.58% (p value < 0.0001) increase in chronic absenteeism rates. Based on these percentage changes in chronic absenteeism, a 0.15 increase in NDVI and 1 μg/m3 increase in PM2.5 correspond to 25,837 fewer students and 15,852 more students chronically absent each year in Massachusetts respectively. These environmental impacts on absenteeism reinforce the need to protect green spaces and reduce air pollution around schools. PMID:28230752

Remote sensing of PM2.5 from ground-based optical measurements

NASA Astrophysics Data System (ADS)

Li, S.; Joseph, E.; Min, Q.

2014-12-01

Remote sensing of particulate matter concentration with aerodynamic diameter smaller than 2.5 um(PM2.5) by using ground-based optical measurements of aerosols is investigated based on 6 years of hourly average measurements of aerosol optical properties, PM2.5, ceilometer backscatter coefficients and meteorological factors from Howard University Beltsville Campus facility (HUBC). The accuracy of quantitative retrieval of PM2.5 using aerosol optical depth (AOD) is limited due to changes in aerosol size distribution and vertical distribution. In this study, ceilometer backscatter coefficients are used to provide vertical information of aerosol. It is found that the PM2.5-AOD ratio can vary largely for different aerosol vertical distributions. The ratio is also sensitive to mode parameters of bimodal lognormal aerosol size distribution when the geometric mean radius for the fine mode is small. Using two Angstrom exponents calculated at three wavelengths of 415, 500, 860nm are found better representing aerosol size distributions than only using one Angstrom exponent. A regression model is proposed to assess the impacts of different factors on the retrieval of PM2.5. Compared to a simple linear regression model, the new model combining AOD and ceilometer backscatter can prominently improve the fitting of PM2.5. The contribution of further introducing Angstrom coefficients is apparent. Using combined measurements of AOD, ceilometer backscatter, Angstrom coefficients and meteorological parameters in the regression model can get a correlation coefficient of 0.79 between fitted and expected PM2.5.

Advanced source apportionment of carbonaceous aerosols by coupling offline AMS and radiocarbon size-segregated measurements over a nearly 2-year period

NASA Astrophysics Data System (ADS)

Vlachou, Athanasia; Daellenbach, Kaspar R.; Bozzetti, Carlo; Chazeau, Benjamin; Salazar, Gary A.; Szidat, Soenke; Jaffrezo, Jean-Luc; Hueglin, Christoph; Baltensperger, Urs; El Haddad, Imad; Prévôt, André S. H.

2018-05-01

Carbonaceous aerosols are related to adverse human health effects. Therefore, identification of their sources and analysis of their chemical composition is important. The offline AMS (aerosol mass spectrometer) technique offers quantitative separation of organic aerosol (OA) factors which can be related to major OA sources, either primary or secondary. While primary OA can be more clearly separated into sources, secondary (SOA) source apportionment is more challenging because different sources - anthropogenic or natural, fossil or non-fossil - can yield similar highly oxygenated mass spectra. Radiocarbon measurements provide unequivocal separation between fossil and non-fossil sources of carbon. Here we coupled these two offline methods and analysed the OA and organic carbon (OC) of different size fractions (particulate matter below 10 and 2.5 µm - PM10 and PM2.5, respectively) from the Alpine valley of Magadino (Switzerland) during the years 2013 and 2014 (219 samples). The combination of the techniques gave further insight into the characteristics of secondary OC (SOC) which was rather based on the type of SOC precursor and not on the volatility or the oxidation state of OC, as typically considered. Out of the primary sources separated in this study, biomass burning OC was the dominant one in winter, with average concentrations of 5.36 ± 2.64 µg m-3 for PM10 and 3.83 ± 1.81 µg m-3 for PM2.5, indicating that wood combustion particles were predominantly generated in the fine mode. The additional information from the size-segregated measurements revealed a primary sulfur-containing factor, mainly fossil, detected in the coarse size fraction and related to non-exhaust traffic emissions with a yearly average PM10 (PM2.5) concentration of 0.20 ± 0.24 µg m-3 (0.05 ± 0.04 µg m-3). A primary biological OC (PBOC) was also detected in the coarse mode peaking in spring and summer with a yearly average PM10 (PM2.5) concentration of 0.79 ± 0.31 µg m-3 (0.24 ± 0.20 µg m-3). The secondary OC was separated into two oxygenated, non-fossil OC factors which were identified based on their seasonal variability (i.e. summer and winter oxygenated organic carbon, OOC) and a third anthropogenic OOC factor which correlated with fossil OC mainly peaking in winter and spring, contributing on average 13 % ± 7 % (10 % ± 9 %) to the total OC in PM10 (PM2.5). The winter OOC was also connected to anthropogenic sources, contributing on average 13 % ± 13 % (6 % ± 6 %) to the total OC in PM10 (PM2.5). The summer OOC (SOOC), stemming from oxidation of biogenic emissions, was more pronounced in the fine mode, contributing on average 43 % ± 12 % (75 % ± 44 %) to the total OC in PM10 (PM2.5). In total the non-fossil OC significantly dominated the fossil OC throughout all seasons, by contributing on average 75 % ± 24 % to the total OC. The results also suggested that during the cold period the prevailing source was residential biomass burning while during the warm period primary biological sources and secondary organic aerosol from the oxidation of biogenic emissions became important. However, SOC was also formed by aged fossil fuel combustion emissions not only in summer but also during the rest of the year.

CARDIOVASCULAR MORTALITY IN PHOENIX: PM1 IS A BETTER INDICATOR THAN PM2.5.

EPA Science Inventory

EPA has obtained a 3-year database of particulate matter (PM) in Phoenix, AZ from 1995 - 1997 that includes elemental analysis by XRF of daily PM2.5. During this time period PM1 and PM2.5 TEOMs were run simultaneously for about 7 months during two periods of the year. Regressio...

77 FR 73313 - Approval and Promulgation of Air Quality Implementation Plans; Maryland; The 2002 Base Year...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-10

... Promulgation of Air Quality Implementation Plans; Maryland; The 2002 Base Year Inventory for the Baltimore, MD... approve the fine particulate matter (PM 2.5 ) 2002 base year emissions inventory portion of the State of... Department of the Environment (MDE), on June 6, 2008 for Baltimore, Maryland. The emissions inventory is part...

Spatial and Interspecies Patterns of PM2.5 at Three Sites in the Pearl River Delta, China: One-Year Observations

NASA Astrophysics Data System (ADS)

Yu, J.; Lau, A. K.; Wu, C.; Ng, W.; Yuan, Z.; Wu, D.

2009-12-01

The Pearl River Delta (PRD) is among the most economically fast-developing regions in China. The region has been experiencing increasing levels of particulate matter (PM) pollution. In an effort of establishing long-term trend in chemical characteristics of PM2.5 and understanding PM sources important at regional scale, filter-based samples have been collected at three sites in the PRD concurrently in one-in-six-day schedule since August 2007. We here report observation results of PM2.5 over one-year period (August 2007-June 2008). The three sites include an urban downtown location in Guangzhou, Nansha, a rural receptor site at the mouth of the Pearl River, and Tsuen Wan, an urban background site in Hong Kong. Guangzhou recorded the highest annual average PM2.5 concentration of 78.2 μgm-3, followed by Nansha (65.9 μgm-3) and Tsuen Wan (42.8 μgm-3). Organic matter (OM) and sulfate are the top two constituents, accounting for ~70% of PM2.5 mass. The annual average nitrate contributions were similar at GZ and NS (~13%), but lower at TW (~7%). Inter-site correlations of PM2.5 and major constituents indicate that GZ strongly influenced ambient PM2.5 levels at NS, but GZ’s influence on TW was much reduced. Sulfate, ammonium, and OM showed strong regional characteristics. To the contrary, EC at the three sites had no correlations, suggesting a dominating local origin. Examples of high PM2.5 episodes are also analyzed to identify the conditions conducive for high PM.

Accessory papillary muscles and papillary muscle hypertrophy are associated with sudden cardiac arrest of unknown cause.

PubMed

Uhm, Jae-Sun; Youn, Jong-Chan; Lee, Hye-Jeong; Park, Junbeom; Park, Jin-Kyu; Shim, Chi Young; Hong, Geu-Ru; Joung, Boyoung; Pak, Hui-Nam; Lee, Moon-Hyoung

2015-10-15

The present study was performed for elucidating the associations between the morphology of the papillary muscles (PMs) and sudden cardiac arrest (SCA). We retrospectively reviewed history, laboratory data, electrocardiography, echocardiography, coronary angiography, and cardiac CT/MRI for 190 patients with SCA. The prevalence of accessory PMs and PM hypertrophy in patients with SCA of unknown cause was compared with that in patients with SCA of known causes and 98 age- and sex-matched patients without SCA. An accessory PM was defined as a PM with origins separated from the anterolateral and posteromedial PMs, or a PM that branched into two or three bellies at the base of the anterolateral or posteromedial PM. PM hypertrophy was defined as at least one of the two PMs having a diameter of ≥1.1cm. In 49 patients (age 49.9±15.9years; 38 men) the cause of SCA was unknown, whereas 141 (age 54.2±16.6years; 121 men) had a known cause. The prevalence of accessory PMs was significantly higher in the unknown-cause group than in the known-cause group (24.5% and 7.8%, respectively; p=0.002) or the no-SCA group (7.1%, p=0.003). The same was true for PM hypertrophy (unknown-cause 12.2%, known-cause 2.1%, p=0.010; no SCA group 1.0%, p=0.006). By logistic regression, accessory PM and PM hypertrophy were independently associated with sudden cardiac arrest of unknown cause. An accessory PM and PM hypertrophy are associated with SCA of unknown cause. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Association between Long-Term Exposure to Particulate Matter Air Pollution and Mortality in a South Korean National Cohort: Comparison across Different Exposure Assessment Approaches

PubMed Central

Kim, Sun-Young; Kim, Ho

2017-01-01

Increasing numbers of cohort studies have reported that long-term exposure to ambient particulate matter is associated with mortality. However, there has been little evidence from Asian countries. We aimed to explore the association between long-term exposure to particulate matter with a diameter ≤10 µm (PM10) and mortality in South Korea, using a nationwide population-based cohort and an improved exposure assessment (EA) incorporating time-varying concentrations and residential addresses (EA1). We also compared the association across different EA approaches. We used information from 275,337 people who underwent health screening from 2002 to 2006 and who had follow-up data for 12 years in the National Health Insurance Service-National Sample Cohort. Individual exposures were computed as 5-year averages using predicted residential district-specific annual-average PM10 concentrations for 2002–2006. We estimated hazard ratios (HRs) of non-accidental and five cause-specific mortalities per 10 µg/m3 increase in PM10 using the Cox proportional hazards model. Then, we compared the association of EA1 with three other approaches based on time-varying concentrations and/or addresses: predictions in each year and addresses at baseline (EA2); predictions at baseline and addresses in each year (EA3); and predictions and addresses at baseline (EA4). We found a marginal association between long-term PM10 and non-accidental mortality. The HRs of five cause-specific mortalities were mostly higher than that of non-accidental mortality, but statistically insignificant. In the comparison between EA approaches, the HRs of EA1 were similar to those of EA2 but higher than EA3 and EA4. Our findings confirmed the association between long-term exposure to PM10 and mortality based on a population-representative cohort in South Korea, and suggested the importance of assessing individual exposure incorporating air pollution changes over time. PMID:28946613

[Improvement of Air Quality During APEC in Beijing in 2014].

PubMed

Cheng, Nian-liang; Li, Yun-ting; Zhang, Da-wei; Chen, Tian; Li, Ling-jun; Li, Jin; Jiang, Lei

2016-01-15

Variations of air quality, meteorological conditions and the effect of pollution control measures on particle matter concentrations in Beijing were all analyzed during APEC (from 1st to 12th in November) in 2014 based on the atmospheric pollutant monitoring data, monitoring components of PM2.5, meteorological and remote sensing data and CMB model. The results showed that the average concentrations of PM2.5, PM10, SO2, NO2 were 43,62,8,46 [g.m respectively during APEC and the average concentrations of PM2.5, PM10, SO2, NO2 were decreased by 45%, 43%, 64% and 31% compared to those in the same period of the last 5 years (PM2. was the average of the last 2 years); the concentrations of PM25 at different sites were decreased by 27.4%-35.5%; the concentrations of PM2.5 in the center of city and northern mountainous areas were the lowest, which dropped by 30%-45% compared to those in the same period of the last 5 years while in the southern area the decrement was below 25%; the main component SO4(2-), the substance of the crust, and NO3- were decreased by 50%, 76%, 35% respectively compared to those in the same period in 2013 and the chemical mass balance (CMB) model analysis results indicated that contributions of coal boiler, dust, motor vehicle were 2%, 7%, 30% respectively during APEC; air pollution control measures (coal, dust and traffic management) had a significant effect on reducing pollutant emissions and the pollutant emissions control reduced the concentration peak and delayed the accumulation speed.

PM trend study for the 1998 - 2012 period: Impact of Transport and Petroleum-based Fuels in Santiago Chile

NASA Astrophysics Data System (ADS)

Castillo, M. A.; Jhun, I.; Moreno, F.; Oyola, P.; Koutrakis, P.

2013-05-01

Santiago is the capital city of Chile and the combination of adverse climatic and geographical conditions, a continuously growing vehicle fleet, and an increasing number of industries, has made Santiago one of the most polluted cities in South America, and has been declared saturated zone for PM10 since 1996. Although there have been important reductions in the PM emissions due the implementation of the "Atmospheric Prevention and Decontamination Plan for the Metropolitan Region" (PPDA) however the efforts have not been enough to meet the actual standards. Currently is approved a standard for PM2.5, where the annual average is 20 μg/m3 and daily average 24 hr is 50 μg/m3. One of the PM2.5 sources are the traffic emission and one of the measures targeted in PPDA has been to regulate this source. In the last 20 years two of the main interventions have been the elimination of Lead in gasoline (2001) and the steadily reduced diesel sulfur content from 5,000 to 50 ppm. In this study we analyzed 14 years of PM2.5 mass and species concentration time's series, from April 1998 to August 2012, elemental chemical analysis was made for approximately 60% of samples using XRF technique at DRI Lab (USA). One of the objectives is evaluate the impact of fuel-related interventions and petroleum-based fuels (PBFs) sales. When was analyzed de lead concentration we found that is present in the environment despite of that was eliminated of gasoline 20 years ago. We analyzed the impact of diesel sulfur on ambient sulfur content, and was constructed a model to verify the relationship between ambient sulfur and diesel sulfur content after controlling for other covariates. The relation between ambient concentration and diesel content sulfur is linear, when the reduction of sulfur in diesel was from 1500 to 50 ppm the concentration decreased from 1.59 to 1.08 μg/m3. To determinate the impact of PBFs sales (gasoline, kerosene, petroleum) on PM2.5 concentration, we estimated PM2.5 regression model for PBF sales. In PM2.5 trend was observed an increase in 2005-2008 period ; when the PBF sales were included in the regression model, the concentration of PM2.5 was mitigated (2005-2008), this results indicates that if the PBF sales not had risen in this period the concentration of PM2.5 would not have increased as much.

The effects of components of fine particulate air pollution on mortality in california: results from CALFINE.

PubMed

Ostro, Bart; Feng, Wen-Ying; Broadwin, Rachel; Green, Shelley; Lipsett, Michael

2007-01-01

Several epidemiologic studies provide evidence of an association between daily mortality and particulate matter < 2.5 pm in diameter (PM2.5). Little is known, however, about the relative effects of PM2.5 constituents. We examined associations between 19 PM2.5 components and daily mortality in six California counties. We obtained daily data from 2000 to 2003 on mortality and PM2.5 mass and components, including elemental and organic carbon (EC and OC), nitrates, sulfates, and various metals. We examined associations of PM2.5 and its constituents with daily counts of several mortality categories: all-cause, cardiovascular, respiratory, and mortality age > 65 years. Poisson regressions incorporating natural splines were used to control for time-varying covariates. Effect estimates were determined for each component in each county and then combined using a random-effects model. PM2.5 mass and several constituents were associated with multiple mortality categories, especially cardiovascular deaths. For example, for a 3-day lag, the latter increased by 1.6, 2.1, 1.6, and 1.5% for PM2.5, EC, OC, and nitrates based on interquartile ranges of 14.6, 0.8, 4.6, and 5.5 pg/m(3), respectively. Stronger associations were observed between mortality and additional pollutants, including sulfates and several metals, during the cool season. This multicounty analysis adds to the growing body of evidence linking PM2.5 with mortality and indicates that excess risks may vary among specific PM2.5 components. Therefore, the use of regression coefficients based on PM2.5 mass may underestimate associations with some PM2.5 components. Also, our findings support the hypothesis that combustion-associated pollutants are particularly important in California.

Mortality due to Vegetation Fire–Originated PM2.5 Exposure in Europe—Assessment for the Years 2005 and 2008

PubMed Central

Kollanus, Virpi; Prank, Marje; Gens, Alexandra; Soares, Joana; Vira, Julius; Kukkonen, Jaakko; Sofiev, Mikhail; Salonen, Raimo O.; Lanki, Timo

2016-01-01

Background: Vegetation fires can release substantial quantities of fine particles (PM2.5), which are harmful to health. The fire smoke may be transported over long distances and can cause adverse health effects over wide areas. Objective: We aimed to assess annual mortality attributable to short-term exposures to vegetation fire–originated PM2.5 in different regions of Europe. Methods: PM2.5 emissions from vegetation fires in Europe in 2005 and 2008 were evaluated based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data on fire radiative power. Atmospheric transport of the emissions was modeled using the System for Integrated modeLling of Atmospheric coMposition (SILAM) chemical transport model. Mortality impacts were estimated for 27 European countries based on a) modeled daily PM2.5 concentrations and b) population data, both presented in a 50 × 50 km2 spatial grid; c) an exposure–response function for short-term PM2.5 exposure and daily nonaccidental mortality; and d) country-level data for background mortality risk. Results: In the 27 countries overall, an estimated 1,483 and 1,080 premature deaths were attributable to the vegetation fire–originated PM2.5 in 2005 and 2008, respectively. Estimated impacts were highest in southern and eastern Europe. However, all countries were affected by fire-originated PM2.5, and even the lower concentrations in western and northern Europe contributed substantially (~ 30%) to the overall estimate of attributable mortality. Conclusions: Our assessment suggests that air pollution caused by PM2.5 released from vegetation fires is a notable risk factor for public health in Europe. Moreover, the risk can be expected to increase in the future as climate change proceeds. This factor should be taken into consideration when evaluating the overall health and socioeconomic impacts of these fires. Citation: Kollanus V, Prank M, Gens A, Soares J, Vira J, Kukkonen J, Sofiev M, Salonen RO, Lanki T. 2017. Mortality due to vegetation fire–originated PM2.5 exposure in Europe—assessment for the years 2005 and 2008. Environ Health Perspect 125:30–37; http://dx.doi.org/10.1289/EHP194 PMID:27472655

Mortality due to Vegetation Fire-Originated PM2.5 Exposure in Europe-Assessment for the Years 2005 and 2008.

PubMed

Kollanus, Virpi; Prank, Marje; Gens, Alexandra; Soares, Joana; Vira, Julius; Kukkonen, Jaakko; Sofiev, Mikhail; Salonen, Raimo O; Lanki, Timo

2017-01-01

Vegetation fires can release substantial quantities of fine particles (PM2.5), which are harmful to health. The fire smoke may be transported over long distances and can cause adverse health effects over wide areas. We aimed to assess annual mortality attributable to short-term exposures to vegetation fire-originated PM2.5 in different regions of Europe. PM2.5 emissions from vegetation fires in Europe in 2005 and 2008 were evaluated based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data on fire radiative power. Atmospheric transport of the emissions was modeled using the System for Integrated modeLling of Atmospheric coMposition (SILAM) chemical transport model. Mortality impacts were estimated for 27 European countries based on a) modeled daily PM2.5 concentrations and b) population data, both presented in a 50 × 50 km2 spatial grid; c) an exposure-response function for short-term PM2.5 exposure and daily nonaccidental mortality; and d) country-level data for background mortality risk. In the 27 countries overall, an estimated 1,483 and 1,080 premature deaths were attributable to the vegetation fire-originated PM2.5 in 2005 and 2008, respectively. Estimated impacts were highest in southern and eastern Europe. However, all countries were affected by fire-originated PM2.5, and even the lower concentrations in western and northern Europe contributed substantially (~ 30%) to the overall estimate of attributable mortality. Our assessment suggests that air pollution caused by PM2.5 released from vegetation fires is a notable risk factor for public health in Europe. Moreover, the risk can be expected to increase in the future as climate change proceeds. This factor should be taken into consideration when evaluating the overall health and socioeconomic impacts of these fires. Citation: Kollanus V, Prank M, Gens A, Soares J, Vira J, Kukkonen J, Sofiev M, Salonen RO, Lanki T. 2017. Mortality due to vegetation fire-originated PM2.5 exposure in Europe-assessment for the years 2005 and 2008. Environ Health Perspect 125:30-37; http://dx.doi.org/10.1289/EHP194.

Metamemory prediction accuracy for simple prospective and retrospective memory tasks in 5-year-old children.

PubMed

Kvavilashvili, Lia; Ford, Ruth M

2014-11-01

It is well documented that young children greatly overestimate their performance on tests of retrospective memory (RM), but the current investigation is the first to examine children's prediction accuracy for prospective memory (PM). Three studies were conducted, each testing a different group of 5-year-olds. In Study 1 (N=46), participants were asked to predict their success in a simple event-based PM task (remembering to convey a message to a toy mole if they encountered a particular picture during a picture-naming activity). Before naming the pictures, children listened to either a reminder story or a neutral story. Results showed that children were highly accurate in their PM predictions (78% accuracy) and that the reminder story appeared to benefit PM only in children who predicted they would remember the PM response. In Study 2 (N=80), children showed high PM prediction accuracy (69%) regardless of whether the cue was specific or general and despite typical overoptimism regarding their performance on a 10-item RM task using item-by-item prediction. Study 3 (N=35) showed that children were prone to overestimate RM even when asked about their ability to recall a single item-the mole's unusual name. In light of these findings, we consider possible reasons for children's impressive PM prediction accuracy, including the potential involvement of future thinking in performance predictions and PM. Copyright © 2014 Elsevier Inc. All rights reserved.

Association of PM2.5 with sleep-disordered breathing from a population-based study in Northern Taiwan urban areas.

PubMed

Shen, Yen-Ling; Liu, Wen-Te; Lee, Kang-Yun; Chuang, Hsiao-Chi; Chen, Hua-Wei; Chuang, Kai-Jen

2018-02-01

Recent studies suggest that exposure to air pollution might be associated with severity of sleep-disordered breathing (SDB). However, the association between air pollution exposure, especially particulate matter with aerodynamic diameters <= 2.5 μm (PM 2.5 ), and SDB is still unclear. We collected 4312 participants' data from the Taipei Medical University Hospital's Sleep Center and air pollution data from the Taiwan Environmental Protection Administration. Associations of particulate matter with aerodynamic diameters <=10 μm (PM 10 ), PM 2.5 , nitrogen dioxide (NO 2 ), ozone (O 3 ) and sulfur dioxide (SO 2 ) with apnea-hypopnea index (AHI) and oxygen desaturation index (ODI) were investigated by generalized additive models. We found that an interquartile range (IQR) increase in 1-year mean PM 2.5 (3.4 μg/m 3 ) and NO 2 (2.7 ppb) was associated with a 4.7% and 3.6% increase in AHI, respectively. We also observed the association of an IQR increase in 1-year mean PM 2.5 with a 2.5% increase in ODI. The similar pattern was found in the association of daily mean PM 2.5 exposure with increased AHI. Moreover, participants showed significant AHI and ODI responses to air pollution levels in spring and winter. We concluded that exposure to PM 2.5 was associated with SDB. Effects of air pollution on AHI and ODI were significant in spring and winter. Copyright © 2017 Elsevier Ltd. All rights reserved.

Combined use of land use regression and BenMAP for estimating public health benefits of reducing PM2.5 in Tianjin, China

NASA Astrophysics Data System (ADS)

Chen, Li; Shi, Mengshuang; Li, Suhuan; Bai, Zhipeng; Wang, Zhongliang

2017-03-01

To assess the public health benefits of reducing PM2.5 in Tianjin, we created an annual air quality surface with a land use regression (LUR) model conducted at a high spatial resolution (1 km). The predictors included in the final model were population density, road length within a 1000 m buffer, industrial land area within a 2000m buffer and distance to the coast. The fitting R2 and the leave-one-out-cross-validation (LOOCV) R2 of the PM2.5 LUR models were 0.78 and 0.73, respectively, suggesting that the predicted PM2.5 concentrations fitted well with the measured values for the entire year. Daily air quality surfaces were established based on historic concentration data and interpolation method. We evaluated avoided cases of mortality and morbidity in Tianjin, assuming achievement of China's current air quality daily and annual standards (No. GB3095-2012). Reducing the daily average PM2.5 to the daily Class II standard (75 μg/m3), the avoided emergency department visits, the deaths for cardiovascular disease and the deaths for respiratory disease are 85,000 (95% confidence interval (CI), 17,000-150,000), 2000 (95% CI, 920-3100) and 280 (95% CI, 94-460) per year respectively, and the monetary values are 23-42 million yuan, 180-4800 million yuan and 25-670 million yuan per year in 2015 yuan year respectively. Reducing the annual average PM2.5 to the annual Class II standard (35 μg/m3), the avoided emergency department visits, the deaths for cardiovascular disease and the deaths for respiratory disease are 59,000 (95% CI, 12,000-110,000), 1400 (95% CI, 640-2100) and 200 (95% CI, 66-320) per year respectively, and the monetary values are 16-29 million yuan, 130 to 3400 million yuan and 18 to 480 million yuan per year in 2015 yuan year respectively.

EVALUATING TEMPORAL AND SPATIAL O3 AND PM2.5 PATTERNS SIMULATED DURING AN ANNUAL CMAS APPLICATION OVER THE CONTINENTAL U.S.

EPA Science Inventory

Over the next several years, grid-based photochemical models such as the Community Multiscale Air Quality (CMAQ) model and REMSAD will be used by regulatory agencies to design emission control strategies aimed at meeting and maintaining the NAAQS for O3 and PM2.5. The evaluation ...

[Air Quality Characteristics in Beijing During Spring Festival in 2015].

PubMed

Cheng, Nian-liang; Chen, Tian; Zhang, Da-wei; Li, Yun-ting; Sun, Feng; Wei, Qiang; Liu, Jia-lin; Liu, Bao-xian; Sun, Rui-wen

2015-09-01

To analyze the impacts of emissions from fireworks on the air quality, monitoring data of PM2.5, PM10, SO2, NO2 chemical compositions of PM2.5 of automatic air quality stations in Beijing during Spring Festival(February 18th-24th) in 2015 were investigated. Moreover, we also estimated the fireworks on the New Year's Eve produced based on the ratio of PM.5 to CO. Analysis results showed that the concentrations of PM2.5, PM10, SO2, NO2 during 2015 Spring Festival was 116. 85, 184.71, 22. 14, and 36. 27 µg.m-3 respectively, which raised 52. 61%, 92. 41%, - 40. 15%, - 0.46% respectively compared to the same period in 2014; the concentration peaks of PM2.5, PM10, SO2, NO2 at 1 : 00 am on 19th was 412. 69, 541. 63, 152. 73, 51. 09 µg.m-3, respectively, which was increased 19. 02%, 14. 37%, 76. 57%, 11. 35% compared to that of 2014; the concentration peaks at dense population area were significantly higher than that in other districts; fireworks had great influence on the chemical compositions of PM2.5 especially on the concentrations of chloride ion, potassium ion, magnesian ion, which were 18. 85, 66. 72, and 70. 10 times than that in 2013-2014; fireworks resulted in severe air pollution in a short time and the estimated fireworks on the New Year's Eve was approximately 2. 13 x 10(5) kg of PM2.5. Reduction of pollutants during Spring Festival had a positive significant impact on air quality in Beijing.

On-road particulate emission measurement

NASA Astrophysics Data System (ADS)

Mazzoleni, Claudio

Particulate matter (PM) suspended in the atmosphere has harmful health effects, contributes to visibility impairment, and affects atmospheric radiative transfer, thereby contributing to global change. Vehicles contribute substantially to the ambient PM concentration in urban areas, yet the fraction of ambient PM originating from vehicle emissions is poorly characterized because suitable measurement methods have not been available. This dissertation describes the development and the use of a new vehicle emission remote sensing system (VERSS) for the on-road measurement of PM emission factors for vehicles. The PM VERSS measures PM by ultraviolet backscattering and transmission. PM backscattering and transmission mass efficiencies have been calculated from Mie theory based on an homogeneous spherical model for gasoline particles and on a two-layers, spherical model for diesel particles. The VERSS was used in a large-scale study in Las Vegas, NV. A commercial gaseous VERSS was used for the measurement of gaseous emission factors (i.e., carbon monoxide, hydrocarbons, and nitrogen oxide). Speed and acceleration were also measured for each vehicle. A video image of each vehicle's rear license plate was acquired and license plate numbers were matched with the Clark County department of motor vehicle database to retrieve vehicle information such as model year, vehicle weight category and engine ignition type. PM VERSS has precisely estimated PM fleet average emission factors and clearly shown the dependence of PM emission factors on vehicle model year. Under mostly hot-stabilized operation, diesel vehicle PM emission factors are about 25 times higher than those of gasoline vehicles. Furthermore, the fleet frequency distributions of PM emission factors are highly skewed, meaning that most of the fleet emission factor is accounted for by a small portion of the fleet. The PM VERSS can measure PM emission factors for these high emitting vehicles on an individual basis. PM emission factors measured during this study are comparable to results of previous studies. Gaseous emissions in Las Vegas are similar to those in other urban areas in the United States. For individual vehicles, the pollutants do not correlate well with each other, however averaged data clearly show functional relationships.

Assessment of personal and community-level exposures to particulate matter among children with asthma in Detroit, Michigan, as part of Community Action Against Asthma (CAAA).

PubMed Central

Keeler, Gerald J; Dvonch, Timothy; Yip, Fuyuen Y; Parker, Edith A; Isreal, Barbara A; Marsik, Frank J; Morishita, Masako; Barres, James A; Robins, Thomas G; Brakefield-Caldwell, Wilma; Sam, Mathew

2002-01-01

We report on the research conducted by the Community Action Against Asthma (CAAA) in Detroit, Michigan, to evaluate personal and community-level exposures to particulate matter (PM) among children with asthma living in an urban environment. CAAA is a community-based participatory research collaboration among academia, health agencies, and community-based organizations. CAAA investigates the effects of environmental exposures on the residents of Detroit through a participatory process that engages participants from the affected communities in all aspects of the design and conduct of the research; disseminates the results to all parties involved; and uses the research results to design, in collaboration with all partners, interventions to reduce the identified environmental exposures. The CAAA PM exposure assessment includes four seasonal measurement campaigns each year that are conducted for a 2-week duration each season. In each seasonal measurement period, daily ambient measurements of PM2.5 and PM10 (particulate matter with a mass median aerodynamic diameter less than 2.5 microm and 10 microm, respectively) are collected at two elementary schools in the eastside and southwest communities of Detroit. Concurrently, indoor measurements of PM2.5 and PM10 are made at the schools as well as inside the homes of a subset of 20 children with asthma. Daily personal exposure measurements of PM10 are also collected for these 20 children with asthma. Results from the first five seasonal assessment periods reveal that mean personal PM10 (68.4 39.2 microg/m(3)) and indoor home PM10 (52.2 30.6 microg/m(3)) exposures are significantly greater (p < 0.05) than the outdoor PM10 concentrations (25.8 11.8 microg/m(3)). The same was also found for PM2.5 (indoor PM2.5 = 34.4 21.7 microg/m(3); outdoor PM2.5 = 15.6 8.2 microg/m(3)). In addition, significant differences (p < 0.05) in community-level exposure to both PM10 and PM2.5 are observed between the two Detroit communities (southwest PM10 = 28.9 14.4 microg/m(3)), PM2.5 = 17.0 9.3 microg/m(3); eastside PM10 = 23.8 12.1 microg/m(3), PM2.5 = 15.5 9.0 microg/m(3). The increased levels in the southwest Detroit community are likely due to the proximity to heavy industrial pollutant point sources and interstate motorways. Trace element characterization of filter samples collected over the 2-year period will allow a more complete assessment of the PM components. When combined with other project measures, including concurrent seasonal twice-daily peak expiratory flow and forced expiratory volume at 1 sec and daily asthma symptom and medication dairies for 300 children with asthma living in the two Detroit communities, these data will allow not only investigations into the sources of PM in the Detroit airshed with regard to PM exposure assessment but also the role of air pollutants in exacerbation of childhood asthma. PMID:11929726

The Effects of Plastic Film Mulching on Maize Growth and Water Use in Dry and Rainy Years in Northeast China

PubMed Central

Xu, Jie; Li, Congfeng; Liu, Huitao; Zhou, Peilu; Tao, Zhiqiang; Wang, Pu; Meng, Qingfeng; Zhao, Ming

2015-01-01

Plastic film mulching (PM) has been widely used to improve maize (Zea mays L.) yields and water use efficiency (WUE) in Northeast China, but the effects of PM in a changing climate characterized by highly variable precipitation are not well understood. Six site-year field experiments were conducted in the dry and rainy years to investigate the effects of PM on maize growth, grain yield, and WUE in Northeast China. Compared to crops grown without PM treatment (control, CK), PM significantly increased the grain yield by 15-26% in the dry years, but no significant yield increase was observed in the rainy years. Yield increase in the dry years was mainly due to a large increase in dry matter accumulation pre-silking compared to the CK, which resulted from a greater dry matter accumulation rate due to the higher topsoil temperature and water content. As a result, the WUE of the crops that underwent PM (3.27 kg m-3) treatment was also increased by around 16% compared to the CK, although the overall evapotranspiration was similar between the two treatments. In the rainy years, due to frequent precipitation and scant sunshine, the topsoil temperature and water content in the field that received PM treatment was improved only at some stages and failed to cause higher dry matter accumulation, except at the 8th leaf stage. Consequently, the grain yield and WUE were not improved by PM in the rainy years. In addition, we found that PM caused leaf senescence at the late growth stage in both dry and rainy years. Therefore, in practice, PM should be applied cautiously, especially when in-season precipitation is taken into account. PMID:25970582

Multi-year objective analyses of warm season ground-level ozone and PM2.5 over North America using real-time observations and Canadian operational air quality models

NASA Astrophysics Data System (ADS)

Robichaud, A.; Ménard, R.

2014-02-01

Multi-year objective analyses (OA) on a high spatiotemporal resolution for the warm season period (1 May to 31 October) for ground-level ozone and for fine particulate matter (diameter less than 2.5 microns (PM2.5)) are presented. The OA used in this study combines model outputs from the Canadian air quality forecast suite with US and Canadian observations from various air quality surface monitoring networks. The analyses are based on an optimal interpolation (OI) with capabilities for adaptive error statistics for ozone and PM2.5 and an explicit bias correction scheme for the PM2.5 analyses. The estimation of error statistics has been computed using a modified version of the Hollingsworth-Lönnberg (H-L) method. The error statistics are "tuned" using a χ2 (chi-square) diagnostic, a semi-empirical procedure that provides significantly better verification than without tuning. Successful cross-validation experiments were performed with an OA setup using 90% of data observations to build the objective analyses and with the remainder left out as an independent set of data for verification purposes. Furthermore, comparisons with other external sources of information (global models and PM2.5 satellite surface-derived or ground-based measurements) show reasonable agreement. The multi-year analyses obtained provide relatively high precision with an absolute yearly averaged systematic error of less than 0.6 ppbv (parts per billion by volume) and 0.7 μg m-3 (micrograms per cubic meter) for ozone and PM2.5, respectively, and a random error generally less than 9 ppbv for ozone and under 12 μg m-3 for PM2.5. This paper focuses on two applications: (1) presenting long-term averages of OA and analysis increments as a form of summer climatology; and (2) analyzing long-term (decadal) trends and inter-annual fluctuations using OA outputs. The results show that high percentiles of ozone and PM2.5 were both following a general decreasing trend in North America, with the eastern part of the United States showing the most widespread decrease, likely due to more effective pollution controls. Some locations, however, exhibited an increasing trend in the mean ozone and PM2.5, such as the northwestern part of North America (northwest US and Alberta). Conversely, the low percentiles are generally rising for ozone, which may be linked to the intercontinental transport of increased emissions from emerging countries. After removing the decadal trend, the inter-annual fluctuations of the high percentiles are largely explained by the temperature fluctuations for ozone and to a lesser extent by precipitation fluctuations for PM2.5. More interesting is the economic short-term change (as expressed by the variation of the US gross domestic product growth rate), which explains 37% of the total variance of inter-annual fluctuations of PM2.5 and 15% in the case of ozone.

76 FR 10817 - Approval and Promulgation of Implementation Plans; State of Nevada; PM-10; Determinations...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-28

... meter ([micro]g/m\\3\\) with no more than one expected exceedance per year. The annual primary PM-10... contains three consecutive years of complete, quality-assured and certified PM-10 data for the 1999-2001... consecutive years of complete, quality-assured and certified PM-10 data for the 2007-2009 period, the most...

40 CFR Appendix N to Part 50 - Interpretation of the National Ambient Air Quality Standards for PM2.5

Code of Federal Regulations, 2014 CFR

2014-07-01

... series of daily values represents the 98th percentile for that year. Creditable samples include daily... measured (or averaged from hourly measurements in AQS) from midnight to midnight (local standard time) from... design value (DV) or a 24-hour PM2.5 NAAQS DV to determine if those metrics, which are judged to be based...

AIRUSE-LIFE +: estimation of natural source contributions to urban ambient air PM10 and PM2. 5 concentrations in southern Europe - implications to compliance with limit values

NASA Astrophysics Data System (ADS)

Diapouli, Evangelia; Manousakas, Manousos I.; Vratolis, Stergios; Vasilatou, Vasiliki; Pateraki, Stella; Bairachtari, Kyriaki A.; Querol, Xavier; Amato, Fulvio; Alastuey, Andrés; Karanasiou, Angeliki A.; Lucarelli, Franco; Nava, Silvia; Calzolai, Giulia; Gianelle, Vorne L.; Colombi, Cristina; Alves, Célia; Custódio, Danilo; Pio, Casimiro; Spyrou, Christos; Kallos, George B.; Eleftheriadis, Konstantinos

2017-03-01

The contribution of natural sources to ambient air particulate matter (PM) concentrations is often not considered; however, it may be significant for certain areas and during specific periods of the year. In the framework of the AIRUSE-LIFE+ project, state-of-the-art methods have been employed for assessing the contribution of major natural sources (African dust, sea salt and forest fires) to PM concentrations, in southern European urban areas. 24 h measurements of PM10 and PM2. 5 mass and chemical composition were performed over the course of a year in five cities: Porto, Barcelona, Milan, Florence and Athens. Net African dust and sea-salt concentrations were calculated based on the methodologies proposed by the EC (SEC 2011/208). The contribution of uncontrolled forest fires was calculated through receptor modelling. Sensitivity analysis with respect to the calculation of African dust was also performed, in order to identify major parameters affecting the estimated net dust concentrations. African dust contribution to PM concentrations was more pronounced in the eastern Mediterranean, with the mean annual relative contribution to PM10 decreasing from 21 % in Athens, to 5 % in Florence, and around 2 % in Milan, Barcelona and Porto. The respective contribution to PM2. 5 was calculated equal to 14 % in Athens and from 1.3 to 2.4 % in all other cities. High seasonal variability of contributions was observed, with dust transport events occurring at different periods in the western and eastern Mediterranean basin. Sea salt was mostly related to the coarse mode and also exhibited significant seasonal variability. Sea-salt concentrations were highest in Porto, with average relative contributions equal to 12.3 % for PM10. Contributions from uncontrolled forest fires were quantified only for Porto and were low on an annual basis (1.4 and 1.9 % to PM10 and PM2. 5, respectively); nevertheless, contributions were greatly increased during events, reaching 20 and 22 % of 24 h PM10 and PM2. 5 concentrations, respectively.

Use of visual range measurements to predict fine particulate matter exposures in Southwest Asia and Afghanistan.

PubMed

Masri, Shahir; Garshick, Eric; Hart, Jaime; Bouhamra, Walid; Koutrakis, Petros

2017-01-01

Military personnel deployed to Southwest Asia and Afghanistan were exposed to high levels of ambient particulate matter (PM). However, quantitative ambient exposure data for conducting health studies are limited due to a lack of PM monitoring stations. Since visual range (VR) is proportional to particle light extinction, VR can serve as a surrogate for PM 2.5 (particulate matter with an aerodynamic diameter ≤2.5 µm) concentrations. We used data on VR, relative humidity (RH), and PM 2.5 ground measurements collected in Kuwait from years 2004-2005 to establish the relationship between PM 2.5 and VR. Model validation obtained by regressing trimester average PM 2.5 predictions against PM 2.5 measurements in Kuwait produced an r 2 value of 0.84. Cross validation of urban and rural sites in Kuwait also revealed good model fit. We applied this relationship to location-specific visibility data at 104 regional sites between years 2000-2012 to estimate monthly average PM 2.5 concentrations. Monthly averages at sites in Iraq, Afghanistan, United Arab Emirates, Kuwait, Djibouti, and Qatar ranged from 10 to 365 µg/m3 during this period, while site averages ranged from 22 to 80 µg/m3, indicating considerable spatial and temporal heterogeneity in ambient PM 2.5 across these regions. These data support the use of historical visibility data to estimate location-specific PM 2.5 concentrations for application in epidemiological studies. This study demonstrates the ability to use airport visibility to estimate PM 2.5 concentrations in Southwest Asian and Afghanistan. This supports the use of historical and ongoing visibility data to estimate PM 2.5 exposure in this region of the world, where PM exposure information is otherwise scarce. This is of high utility to epidemiologists investigating the relationship between chronic exposure to PM 2.5 and respiratory diseases among deployed military personnel stationed at various military bases throughout the region. Such information will enable the drafting of improved policies relating to military health.

33 CFR 165.939 - Safety Zones; Annual Fireworks Events in the Captain of the Port Buffalo Zone.

Code of Federal Regulations, 2011 CFR

2011-07-01

... effective from 9 p.m. to 10 p.m. on July 1 of each year. (3) French Festival Fireworks, Cape Vincent, NY—(i... 10:30 p.m. on the first weekend of July each year. (5) Celebrate Baldwinsville Fireworks.... to 10 p.m. on the third weekend of September each year. (6) Island Festival Fireworks Display...

[Research on Kalman interpolation prediction model based on micro-region PM2.5 concentration].

PubMed

Wang, Wei; Zheng, Bin; Chen, Binlin; An, Yaoming; Jiang, Xiaoming; Li, Zhangyong

2018-02-01

In recent years, the pollution problem of particulate matter, especially PM2.5, is becoming more and more serious, which has attracted many people's attention from all over the world. In this paper, a Kalman prediction model combined with cubic spline interpolation is proposed, which is applied to predict the concentration of PM2.5 in the micro-regional environment of campus, and to realize interpolation simulation diagram of concentration of PM2.5 and simulate the spatial distribution of PM2.5. The experiment data are based on the environmental information monitoring system which has been set up by our laboratory. And the predicted and actual values of PM2.5 concentration data have been checked by the way of Wilcoxon signed-rank test. We find that the value of bilateral progressive significance probability was 0.527, which is much greater than the significant level α = 0.05. The mean absolute error (MEA) of Kalman prediction model was 1.8 μg/m 3 , the average relative error (MER) was 6%, and the correlation coefficient R was 0.87. Thus, the Kalman prediction model has a better effect on the prediction of concentration of PM2.5 than those of the back propagation (BP) prediction and support vector machine (SVM) prediction. In addition, with the combination of Kalman prediction model and the spline interpolation method, the spatial distribution and local pollution characteristics of PM2.5 can be simulated.

New insight into PM2.5 pollution patterns in Beijing based on one-year measurement of chemical compositions.

PubMed

Tan, Tianyi; Hu, Min; Li, Mengren; Guo, Qingfeng; Wu, Yusheng; Fang, Xin; Gu, Fangting; Wang, Yu; Wu, Zhijun

2018-04-15

In recent years, air pollution has become a major concern in China, especially in the capital city of Beijing. Haze events occur in Beijing over all four seasons, exhibiting distinct characteristics. In this study, the typical evolution patterns of atmospheric particulate matter with a diameter of less than 2.5μm (PM 2.5 ) in each season were illustrated by episode-based analysis. In addition, a novel method was developed to elucidate the driving species of pollution, which is the largest contributor to the incremental PM 2.5 (ΔPM 2.5 ), not PM 2.5 . This method revealed a temporal variation of the driving species throughout the year: nitrate-driven spring, sulfate-driven summer, nitrate-driven early fall, and organic matters (OM)-driven late fall and winter. These results suggested that primary organic particles or volatile organic compounds emissions were dominant in the heating season due to residential heating, while NOx and SO 2 emissions dominated in the other seasons. Besides, nitrate formation seemed more significant than sulfate formation during severe pollution episodes. It was also found that the pollution formation mechanism in the winter showed some unique features in comparison with the other seasons: aqueous reactions were more important in the winter, while multiple pathways coexisted in the other seasons. Furthermore, this study confirmed that the PM 2.5 in Beijing was moderately acidic despite a fully neutralized system. In addition, the acidity variation during pollution episodes displayed different patterns between seasons and was driven by both the variation of aerosol water and chemical compositions. These results provide a new perspective to understand the characteristics and mechanisms of aerosol pollution in Beijing. However, more accurate measurements are necessary for effective air pollution control that depends on the seasonal variation of fine particle formation in Beijing and the surrounding areas. Copyright © 2017 Elsevier B.V. All rights reserved.

A full year evaluation of the CALIOPE-EU air quality modeling system over Europe for 2004

NASA Astrophysics Data System (ADS)

Pay, M. T.; Piot, M.; Jorba, O.; Gassó, S.; Gonçalves, M.; Basart, S.; Dabdub, D.; Jiménez-Guerrero, P.; Baldasano, J. M.

The CALIOPE-EU high-resolution air quality modeling system, namely WRF-ARW/HERMES-EMEP/CMAQ/BSC-DREAM8b, is developed and applied to Europe (12 km × 12 km, 1 h). The model performances are tested in terms of air quality levels and dynamics reproducibility on a yearly basis. The present work describes a quantitative evaluation of gas phase species (O 3, NO 2 and SO 2) and particulate matter (PM2.5 and PM10) against ground-based measurements from the EMEP (European Monitoring and Evaluation Programme) network for the year 2004. The evaluation is based on statistics. Simulated O 3 achieves satisfactory performances for both daily mean and daily maximum concentrations, especially in summer, with annual mean correlations of 0.66 and 0.69, respectively. Mean normalized errors are comprised within the recommendations proposed by the United States Environmental Protection Agency (US-EPA). The general trends and daily variations of primary pollutants (NO 2 and SO 2) are satisfactory. Daily mean concentrations of NO 2 correlate well with observations (annual correlation r = 0.67) but tend to be underestimated. For SO 2, mean concentrations are well simulated (mean bias = 0.5 μg m -3) with relatively high annual mean correlation ( r = 0.60), although peaks are generally overestimated. The dynamics of PM2.5 and PM10 is well reproduced (0.49 < r < 0.62), but mean concentrations remain systematically underestimated. Deficiencies in particulate matter source characterization are discussed. Also, the spatially distributed statistics and the general patterns for each pollutant over Europe are examined. The model performances are compared with other European studies. While O 3 statistics generally remain lower than those obtained by the other considered studies, statistics for NO 2, SO 2, PM2.5 and PM10 present higher scores than most models.

Long-term exposure to ambient particulate matter (PM2.5) is associated with platelet counts in adults.

PubMed

Zhang, Zilong; Chan, Ta-Chien; Guo, Cui; Chang, Ly-Yun; Lin, Changqing; Chuang, Yuan Chieh; Jiang, Wun Kai; Ho, Kin Fai; Tam, Tony; Woo, Kam S; Lau, Alexis K H; Lao, Xiang Qian

2018-05-09

The prothrombotic effects of particulate matter (PM) may underlie the association of air pollution with increased risks of cardiovascular disease. This study aimed to investigate the association between long-term exposure to PM with an aerodynamic diameter ≤2.5 μm (PM 2.5 ) and platelet counts, a marker of coagulation profiles. The study participants were from a cohort consisting of 362,396 Taiwanese adults who participated in a standard medical examination program between 2001 and 2014. Platelet counts were measured through Complete Blood Count tests. A satellite-based spatio-temporal model was used to estimate 2-year average ambient PM 2.5 concentration at each participant's address. Mixed-effects linear regression models were used to investigate the association between PM 2.5 exposure and platelet counts. This analysis included 175,959 men with 396,248 observations and 186,437 women with 397,877 observations. Every 10-μg/m 3 increment in the 2-year average PM 2.5 was associated with increases of 0.42% (95% CI: 0.38%, 0.47%) and 0.49% (95% CI: 0.44%, 0.54%) in platelet counts in men and women, respectively. A series of sensitivity analyses, including an analysis in participants free of cardiometabolic disorders, confirmed the robustness of the observed associations. Baseline data analyses showed that every 10-μg/m 3 increment in PM 2.5 was associated with higher risk of 17% and 14% of having elevated platelet counts (≥90th percentile) in men and women, respectively. Long-term exposure to PM 2.5 appears to be associated with increased platelet counts, indicating potential adverse effects on blood coagulability. Copyright © 2018 Elsevier Ltd. All rights reserved.

Poverty and child (0-14 years) mortality in the USA and other Western countries as an indicator of "how well a country meets the needs of its children" (UNICEF).

PubMed

Pritchard, Colin; Williams, Richard

2011-01-01

Children's (0-14 years) mortality rates in the USA and 19 Western countries (WCs) were examined in the context of a nation-specific measure of relative poverty and the Gross Domestic Product Health Expenditure (GDPHE) of countries to compare the effectiveness and efficiency of health care systems "to meet the needs of its children" (UNICEF). World Health Organisation child mortality rates per million were analysed for 1979-1981 and 2003-2005 to determine any significant differences between the USA and the other WCs over these periods. Child mortality rates are correlated with all countries GDPHE and 'relative poverty', defined by 'Income Inequalities', i.e., the gap between top and bottom 20% of incomes. Outputs: The mortality rate of every country fell substantially ranging from falls of 46% in the USA to 78% in Portugal. The highest current mortality rates are: USA, 2436 per million (pm), New Zealand 2105 pm, Portugal 1929 pm, Canada 1877 pm and the UK 1834 pm; the lowest are: Japan 1073 pm and Sweden 1075 pm, Finland 1193 pm and Norway 1200 pm. A total of 16 countries rates fell significantly more than the USA over these periods. Inputs: The USA had the greatest GDPHE and widest Income Inequality gap. There was no significant correlation between GDPHE and mortality but highly significant correlations with children's deaths and income inequalities. The five widest income inequality countries had the six worst rates, the narrowest four had the lowest. Despite major improvements in every WC, based upon financial inputs and child mortality outputs, the USA health care system appears the least efficient and effective in "meeting the needs of its children".

Modelling street level PM10 concentrations across Europe: source apportionment and possible futures

NASA Astrophysics Data System (ADS)

Kiesewetter, G.; Borken-Kleefeld, J.; Schöpp, W.; Heyes, C.; Thunis, P.; Bessagnet, B.; Terrenoire, E.; Fagerli, H.; Nyiri, A.; Amann, M.

2015-02-01

Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter <10 μm) limit values at individual air quality monitoring stations reporting to the AirBase database. The modelling approach relies on a combination of bottom up modelling of emissions, simplified atmospheric chemistry and dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80% of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period 2000-2008 to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are largely eliminated in a scenario applying the best available emission control technologies to the maximal technically feasible extent.

Modelling street level PM10 concentrations across Europe: source apportionment and possible futures

NASA Astrophysics Data System (ADS)

Kiesewetter, G.; Borken-Kleefeld, J.; Schöpp, W.; Heyes, C.; Thunis, P.; Bessagnet, B.; Terrenoire, E.; Amann, M.

2014-07-01

Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter < 10 μm) limit values at individual air quality monitoring stations reporting to the AirBase database. The modelling approach relies on a combination of bottom up modelling of emissions, simplified atmospheric chemistry and dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80% of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period 2000-2008 to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are largely eliminated in a scenario applying the best available emission control technologies to the maximal technically feasible extent.

A Global Perspective of Fine Particulate Matter Pollution and Its Health Effects.

PubMed

Mukherjee, Arideep; Agrawal, Madhoolika

Fine particulate matter (PM) in the ambient air is implicated in a variety of human health issues throughout the globe. Regulation of fine PM in the atmosphere requires information on the dimension of the problem with respect to variations in concentrations and sources. To understand the current status of fine particles in the atmosphere and their potential harmful health effects in different regions of the world this review article was prepared based on peer-reviewed scientific papers, scientific reports, and database from government organizations published after the year 2000 to evaluate the global scenario of the PM 2.5 (particles <2.5 μm in aerodynamic diameter), its exceedance of national and international standards, sources, mechanism of toxicity, and harmful health effects of PM 2.5 and its components. PM 2.5 levels and exceedances of national and international standards were several times higher in Asian countries, while levels in Europe and USA were mostly well below the respective standards. Vehicular traffic has a significant influence on PM 2.5 levels in urban areas; followed by combustion activities (biomass, industrial, and waste burning) and road dust. In urban atmosphere, fine particles are mostly associated with different health effects with old aged people, pregnant women, and more so children being the most susceptible ones. Fine PM chemical constituents severely effect health due to their carcinogenic or mutagenic nature. Most of the research indicated an exceedance of fine PM level of the standards with a diverse array of health effects based on PM 2.5 chemical constituents. Emission reduction policies with epidemiological studies are needed to understand the benefits of sustainable control measures for fine PM mitigation.

75 FR 33562 - Approval and Promulgation of Implementation Plans and Designations of Areas for Air Quality...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-14

...EPA is proposing to determine that the Birmingham, Alabama, nonattainment area for the 2006 24-hour fine particulate matter (PM2.5) National Ambient Air Quality Standard (NAAQS) has attained the 2006 24-hour PM2.5 NAAQS. This proposed determination is based upon complete, quality assured, quality controlled, and certified ambient air monitoring data for the years 2007-2009 showing that this area has monitored attainment of the 2006 24-hour PM2.5 NAAQS. If this proposed determination is made final, the requirement for the State of Alabama to submit an attainment demonstration and associated reasonably available control measures (RACM), reasonable further progress (RFP) plan, contingency measures, and other planning State Implementation Plans (SIPs) related to attainment of the 2006 24-hour PM2.5 standard for the Birmingham, Alabama, PM2.5 nonattainment area, shall be suspended for as long as this area continues to meet the 2006 24-hour PM2.5 NAAQS.

Real-time chemical characterization of atmospheric particulate matter in China: A review

NASA Astrophysics Data System (ADS)

Li, Yong Jie; Sun, Yele; Zhang, Qi; Li, Xue; Li, Mei; Zhou, Zhen; Chan, Chak K.

2017-06-01

Atmospheric particulate matter (PM) pollution has become a major health threat accompanying the rapid economic development in China. For decades, filter-based offline chemical analyses have been the most widely adopted means to investigate PM and have provided much information for understanding this type of pollution in China. However, offline analyses have low time resolutions and the chemical information thus obtained fail to reflect the dynamic nature of the sources and the rapid processes leading to the severe PM pollution in China. In recent years, advances in real-time PM chemical characterization have created a new paradigm for PM studies in China. In this review, we summarize those advances, focusing on the most widely used mass spectrometric and ion chromatographic techniques. We describe the findings from those studies in terms of spatiotemporal variabilities, degree of neutralization and oxygenation, source apportionment, secondary formation, as well as collocated measurements of the chemical and physical (hygroscopic and optical) properties of PM. We also highlight the new insights gained from those findings and suggest future directions for further advancing our understanding of PM pollution in China via real-time chemical characterization.

AUPHEP—Austrian Project on Health Effects of Particulates—general overview

NASA Astrophysics Data System (ADS)

Hauck, H.; Berner, A.; Frischer, T.; Gomiscek, B.; Kundi, M.; Neuberger, M.; Puxbaum, H.; Preining, O.; Auphep-Team

AUPHEP was started in 1999 as a 5 years program to investigate the situation of the atmospheric aerosol with respect to effects on human health. At four different sites in Austria (3 urban and one rural site) an extended monitoring program was conducted for PM 1, PM 2.5 and PM 10 as well as particle number concentration for 12 months each. Beside continuous measurements using TEOM and beta attenuation high-volume sampling of PM 2.5 and PM 10 provided samples for chemical analyses of various ions, heavy metals and organic compounds. Furthermore, carbonaceous material (TC, EC, OC) year round and PAHs on selected days were analyzed. From collocated public monitoring stations also pollutant gases (SO 2, NO, NO 2, O 3, CO) and meteorological components are available. In winter and summer campaigns aerosol size spectra including chemical components were measured for at least one week each. All data are collected in a project data base (CD-ROM). While extensive data analysis will be presented in following papers, some general results are presented within this paper: annual averages for PM 1 are between 10 and 20 μg m -3, for PM 2.5 between 15 and 26 mg m -3 and for PM 10 between 20 and 38 μg m -3. Number concentrations are between 10,000 and 30,000 cm -3. Urban concentrations are usually higher in winter, rural concentrations in summer. PM 2.5 is in average around 70% of PM 10, for PM 1 this fraction is about 57%. Several studies on health effects are included in this project: a cross-sectional study on preschool and school children regarding lung function measurements and questionnaires about respiratory impairment in the surrounding area of the monitoring sites as well as time series studies on mortality and respiratory morbidity on the general population.

An improved geographically weighted regression model for PM2.5 concentration estimation in large areas

NASA Astrophysics Data System (ADS)

Zhai, Liang; Li, Shuang; Zou, Bin; Sang, Huiyong; Fang, Xin; Xu, Shan

2018-05-01

Considering the spatial non-stationary contributions of environment variables to PM2.5 variations, the geographically weighted regression (GWR) modeling method has been using to estimate PM2.5 concentrations widely. However, most of the GWR models in reported studies so far were established based on the screened predictors through pretreatment correlation analysis, and this process might cause the omissions of factors really driving PM2.5 variations. This study therefore developed a best subsets regression (BSR) enhanced principal component analysis-GWR (PCA-GWR) modeling approach to estimate PM2.5 concentration by fully considering all the potential variables' contributions simultaneously. The performance comparison experiment between PCA-GWR and regular GWR was conducted in the Beijing-Tianjin-Hebei (BTH) region over a one-year-period. Results indicated that the PCA-GWR modeling outperforms the regular GWR modeling with obvious higher model fitting- and cross-validation based adjusted R2 and lower RMSE. Meanwhile, the distribution map of PM2.5 concentration from PCA-GWR modeling also clearly depicts more spatial variation details in contrast to the one from regular GWR modeling. It can be concluded that the BSR enhanced PCA-GWR modeling could be a reliable way for effective air pollution concentration estimation in the coming future by involving all the potential predictor variables' contributions to PM2.5 variations.

Changes in soil parameters under continuous plastic mulching in strawberry cultivation

NASA Astrophysics Data System (ADS)

Muñoz, Katherine; Diehl, Dörte; Scopchanova, Sirma; Schaumann, Gabriele E.

2016-04-01

Plastic mulching (PM) is a widely used practice in modern agriculture because they generate conditions for optimal yield rates and quality. However, information about long-term effects of PC on soil quality parameters is scarce. The aim of this study is to compare the effect of three different mulching managements on soil quality parameters. Sampling and methodology: Three different managements were studied: Organic mulching (OM), 2-years PM and 4-years PM. Soil samples were collected from irrigated fields in 0-5, 5-10 and 10-30 cm depths and analyzed for water content (WC), pH, dissolved organic carbon (DOC), total soil carbon (Ctot) and cation exchange capacity (CECeff). Results and discussion: Mulching management has an influence on soil parameters. The magnitude of the effects is influenced by the type (organic agriculture practice vs. plastic mulching practice) and duration of the mulching. PM modified the water distribution through the soil column. WC values at the root zone were in average 10% higher compared to those measured at the topsoil. Under OM, the WC was lower than under PM. The pH was mainly influenced by the duration of the managements with slightly higher values after 4 than after 2-years PM. Under PM, aqueous extracts of the topsoil (0-5 cm depth) contained in average with 8.5±1.8 mg/L higher DOC than in 10-30 cm depth with 5.6±0.5 mg/L, which may indicate a mobilization of organic components in the upper layers. After 4-years PM, Ctot values were slightly higher than after 2-years PM and after OM. Surprisingly, after 4-years PM, CECeff values were with 138 - 157 mmolc/kg almost 2-fold higher than after 2-years PM and OM which had with 74 - 102 mmolc/kg comparable CECeff values. Long-term PM resulted in changes of soil pH and slightly increased Ctot which probably enhanced the CECeff of the soil. However, further investigations of the effect of PM on stability of soil organic matter and microbial community structure are needed.

77 FR 31200 - Revision to the South Coast Air Quality Management District Portion of the California State...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-25

.... Comment 1: CSE's first comment provides an overview of the reasonable further progress (RFP) and base year... year (i.e. pre-1997) emissions credits for particulate matter of 10 microns or less (PM 10 ) and sulfur... base- year requirement.'') [Footnote omitted] CSE's basis for concluding the 2003 AQMP is not ``valid...

The public health benefits of insulation retrofits in existing housing in the United States

PubMed Central

Levy, Jonathan I; Nishioka, Yurika; Spengler, John D

2003-01-01

Background Methodological limitations make it difficult to quantify the public health benefits of energy efficiency programs. To address this issue, we developed a risk-based model to estimate the health benefits associated with marginal energy usage reductions and applied the model to a hypothetical case study of insulation retrofits in single-family homes in the United States. Methods We modeled energy savings with a regression model that extrapolated findings from an energy simulation program. Reductions of fine particulate matter (PM2.5) emissions and particle precursors (SO2 and NOx) were quantified using fuel-specific emission factors and marginal electricity analyses. Estimates of population exposure per unit emissions, varying by location and source type, were extrapolated from past dispersion model runs. Concentration-response functions for morbidity and mortality from PM2.5 were derived from the epidemiological literature, and economic values were assigned to health outcomes based on willingness to pay studies. Results In total, the insulation retrofits would save 800 TBTU (8 × 1014 British Thermal Units) per year across 46 million homes, resulting in 3,100 fewer tons of PM2.5, 100,000 fewer tons of NOx, and 190,000 fewer tons of SO2 per year. These emission reductions are associated with outcomes including 240 fewer deaths, 6,500 fewer asthma attacks, and 110,000 fewer restricted activity days per year. At a state level, the health benefits per unit energy savings vary by an order of magnitude, illustrating that multiple factors (including population patterns and energy sources) influence health benefit estimates. The health benefits correspond to $1.3 billion per year in externalities averted, compared with $5.9 billion per year in economic savings. Conclusion In spite of significant uncertainties related to the interpretation of PM2.5 health effects and other dimensions of the model, our analysis demonstrates that a risk-based methodology is viable for national-level energy efficiency programs. PMID:12740041

Health effects caused by primary fine particulate matter (PM2.5) emitted from buses in the Helsinki metropolitan area, Finland.

PubMed

Tainio, Marko; Tuomisto, Jouni T; Hänninen, Otto; Aarnio, Päivi; Koistinen, Kimmo J; Jantunen, Matti J; Pekkanen, Juha

2005-02-01

Fine particle (PM(2.5)) emissions from traffic have been associated with premature mortality. The current work compares PM(2.5)-induced mortality in alternative public bus transportation strategies as being considered by the Helsinki Metropolitan Area Council, Finland. The current bus fleet and transportation volume is compared to four alternative hypothetical bus fleet strategies for the year 2020: (1) the current bus fleet for 2020 traffic volume, (2) modern diesel buses without particle traps, (3) diesel buses with particle traps, and (4) buses using natural gas engines. The average population PM(2.5) exposure level attributable to the bus emissions was determined for the 1996-1997 situation using PM(2.5) exposure measurements including elemental composition from the EXPOLIS-Helsinki study and similar element-based source apportionment of ambient PM(2.5) concentrations observed in the ULTRA study. Average population exposure to particles originating from the bus traffic in the year 2020 is assumed to be proportional to the bus emissions in each strategy. Associated mortality was calculated using dose-response relationships from two large cohort studies on PM(2.5) mortality from the United States. Estimated number of deaths per year (90% confidence intervals in parenthesis) associated with primary PM(2.5) emissions from buses in Helsinki Metropolitan Area in 2020 were 18 (0-55), 9 (0-27), 4 (0-14), and 3 (0-8) for the strategies 1-4, respectively. The relative differences in the associated mortalities for the alternative strategies are substantial, but the number of deaths in the lowest alternative, the gas buses, is only marginally lower than what would be achieved by diesel engines equipped with particle trap technology. The dose-response relationship and the emission factors were identified as the main sources of uncertainty in the model.

Longitudinal Analysis of Particulate Air Pollutants and Adolescent Delinquent Behavior in Southern California.

PubMed

Younan, Diana; Tuvblad, Catherine; Franklin, Meredith; Lurmann, Fred; Li, Lianfa; Wu, Jun; Berhane, Kiros; Baker, Laura A; Chen, Jiu-Chiuan

2017-12-13

Animal experiments and cross-sectional human studies have linked particulate matter (PM) with increased behavioral problems. We conducted a longitudinal study to examine whether the trajectories of delinquent behavior are affected by PM 2.5 (PM with aerodynamic diameter ≤ 2.5 μm) exposures before and during adolescence. We used the parent-reported Child Behavior Checklist at age 9-18 with repeated measures every ~2-3 years (up to 4 behavioral assessments) on 682 children from the Risk Factors for Antisocial Behavior Study conducted in a multi-ethnic cohort of twins born in 1990-1995. Based on prospectively-collected residential addresses and a spatiotemporal model of ambient air concentrations in Southern California, monthly PM 2.5 estimates were aggregated to represent long-term (1-, 2-, 3-year average) exposures preceding baseline and cumulative average exposure until the last assessment. Multilevel mixed-effects models were used to examine the association between PM 2.5 exposure and individual trajectories of delinquent behavior, adjusting for within-family/within-individual correlations and potential confounders. We also examined whether psychosocial factors modified this association. The results sμggest that PM 2.5 exposure at baseline and cumulative exposure during follow-up was significantly associated (p < 0.05) with increased delinquent behavior. The estimated effect sizes (per interquartile increase of PM 2.5 by 3.12-5.18 μg/m 3 ) were equivalent to the difference in delinquency scores between adolescents who are 3.5-4 years apart in age. The adverse effect was stronger in families with unfavorable parent-to-child relationships, increased parental stress or maternal depressive symptoms. Overall, these findings sμggest long-term PM 2.5 exposure may increase delinquent behavior of urban-dwelling adolescents, with the resulting neurotoxic effect aggravated by psychosocial adversities.

Distinct and shared cognitive functions mediate event- and time-based prospective memory impairment in normal ageing

PubMed Central

Gonneaud, Julie; Kalpouzos, Grégoria; Bon, Laetitia; Viader, Fausto; Eustache, Francis; Desgranges, Béatrice

2011-01-01

Prospective memory (PM) is the ability to remember to perform an action at a specific point in the future. Regarded as multidimensional, PM involves several cognitive functions that are known to be impaired in normal aging. In the present study, we set out to investigate the cognitive correlates of PM impairment in normal aging. Manipulating cognitive load, we assessed event- and time-based PM, as well as several cognitive functions, including executive functions, working memory and retrospective episodic memory, in healthy subjects covering the entire adulthood. We found that normal aging was characterized by PM decline in all conditions and that event-based PM was more sensitive to the effects of aging than time-based PM. Whatever the conditions, PM was linked to inhibition and processing speed. However, while event-based PM was mainly mediated by binding and retrospective memory processes, time-based PM was mainly related to inhibition. The only distinction between high- and low-load PM cognitive correlates lays in an additional, but marginal, correlation between updating and the high-load PM condition. The association of distinct cognitive functions, as well as shared mechanisms with event- and time-based PM confirms that each type of PM relies on a different set of processes. PMID:21678154

Intraurban Variation of Fine Particle Elemental Concentrations in New York City.

PubMed

Ito, Kazuhiko; Johnson, Sarah; Kheirbek, Iyad; Clougherty, Jane; Pezeshki, Grant; Ross, Zev; Eisl, Holger; Matte, Thomas D

2016-07-19

Few past studies have collected and analyzed within-city variation of fine particulate matter (PM2.5) elements. We developed land-use regression (LUR) models to characterize spatial variation of 15 PM2.5 elements collected at 150 street-level locations in New York City during December 2008-November 2009: aluminum, bromine, calcium, copper, iron, potassium, manganese, sodium, nickel, lead, sulfur, silicon, titanium, vanadium, and zinc. Summer- and winter-only data available at 99 locations in the subsequent 3 years, up to November 2012, were analyzed to examine variation of LUR results across years. Spatial variation of each element was modeled in LUR including six major emission indicators: boilers burning residual oil; traffic density; industrial structures; construction/demolition (these four indicators in buffers of 50 to 1000 m), commercial cooking based on a dispersion model; and ship traffic based on inverse distance to navigation path weighted by associated port berth volume. All the elements except sodium were associated with at least one source, with R(2) ranging from 0.2 to 0.8. Strong source-element associations, persistent across years, were found for residual oil burning (nickel, zinc), near-road traffic (copper, iron, and titanium), and ship traffic (vanadium). These emission source indicators were also significant and consistent predictors of PM2.5 concentrations across years.

77 FR 50446 - Approval and Promulgation of Implementation Plans; Tennessee; Knoxville; Fine Particulate Matter...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-21

... ENVIRONMENTAL PROTECTION AGENCY 40 CFR Part 52 [EPA-R04-OAR-2010-0153(b); FRL-9717-4] Approval and Promulgation of Implementation Plans; Tennessee; Knoxville; Fine Particulate Matter 2002 Base Year Emissions... approve the 1997 annual fine particulate matter (PM 2.5 ) 2002 base year emissions inventory portion of...

An overview of PM-10 base year emissions inventories

DOT National Transportation Integrated Search

1999-01-01

This report provides an overview of the Long Term Pavement Performance (LTPP) program's analysis program. Specifically, it outlines the analysis projects that will be undertaken by the Federal Highway Administration in fiscal years 1999 and 2000 and ...

Monetary Incentive Effects on Event-Based Prospective Memory Three Months after Traumatic Brain Injury in Children

PubMed Central

Pedroza, Claudia; Chapman, Sandra B.; Cook, Lori G.; Vásquez, Ana C.; Levin, Harvey S.

2011-01-01

Information regarding the remediation of event-based prospective memory (EB-PM) impairments following pediatric traumatic brain injury (TBI) is scarce. Addressing this, two levels of monetary incentives were used to improve EB-PM in children ages 7 to 16 years with orthopedic injuries (OI, n = 51), or moderate (n = 25), and severe (n = 39) TBI at approximately three months postinjury. The EB-PM task consisted of the child giving a specific verbal response to a verbal cue from the examiner while performing a battery of neuropsychological measures (ongoing task). Significant effects were found for Age-at-Test, Motivation Condition, Period, and Group. Within-group analyses indicated OI and moderate TBI groups performed significantly better under the high-versus low-incentive condition, but the severe TBI group demonstrated no significant improvement. These results indicate EB-PM can be significantly improved at three months postinjury in children with moderate, but not severe, TBI. PMID:21347945

Purpose, Processes, Partnerships, and Products: 4Ps to advance Participatory Socio-Environmental Modeling

NASA Astrophysics Data System (ADS)

Gray, S. G.; Voinov, A. A.; Jordan, R.; Paolisso, M.

2016-12-01

Model-based reasoning is a basic part of human understanding, decision-making, and communication. Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding environmental change since stakeholders often hold valuable knowledge about socio-environmental dynamics and since collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four dimensional framework that includes reporting on dimensions of: (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of environmental changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of environmental policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.

Residential particulate matter and distance to roadways in relation to mammographic density: results from the Nurses' Health Studies.

PubMed

DuPre, Natalie C; Hart, Jaime E; Bertrand, Kimberly A; Kraft, Peter; Laden, Francine; Tamimi, Rulla M

2017-11-23

High mammographic density is a strong, well-established breast cancer risk factor. Three studies conducted in various smaller geographic settings reported inconsistent findings between air pollution and mammographic density. We assessed whether particulate matter (PM) exposures (PM 2.5 , PM 2.5-10 , and PM 10 ) and distance to roadways were associated with mammographic density among women residing across the United States. The Nurses' Health Studies are prospective cohorts for whom a subset has screening mammograms from the 1990s (interquartile range 1990-1999). PM was estimated using spatio-temporal models linked to residential addresses. Among 3258 women (average age at mammogram 52.7 years), we performed multivariable linear regression to assess associations between square-root-transformed mammographic density and PM within 1 and 3 years before the mammogram. For linear regression estimates of PM in relation to untransformed mammographic density outcomes, bootstrapped robust standard errors are used to calculate 95% confidence intervals (CIs). Analyses were stratified by menopausal status and region of residence. Recent PM and distance to roadways were not associated with mammographic density in premenopausal women (PM 2.5 within 3 years before mammogram β = 0.05, 95% CI -0.16, 0.27; PM 2.5-10 β = 0, 95%, CI -0.15, 0.16; PM 10 β = 0.02, 95% CI -0.10, 0.13) and postmenopausal women (PM 2.5 within 3 years before mammogram β = -0.05, 95% CI -0.27, 0.17; PM 2.5-10 β = -0.01, 95% CI -0.16, 0.14; PM 10 β = -0.02, 95% CI -0.13, 0.09). Largely null associations were observed within regions. Suggestive associations were observed among postmenopausal women in the Northeast (n = 745), where a 10-μg/m 3 increase in PM 2.5 within 3 years before the mammogram was associated with 3.4 percentage points higher percent mammographic density (95% CI -0.5, 7.3). These findings do not support that recent PM or roadway exposures influence mammographic density. Although PM was largely not associated with mammographic density, we cannot rule out the role of PM during earlier exposure time windows and possible associations among northeastern postmenopausal women.

SU43. The Effect of Implementation Intention on Different Types of Prospective Memory Performance in Patients With Schizophrenia

PubMed Central

Wang, Ya; Liu, Lu-lu; Gan, Ming-yuan; Tan, Shu-ping; Shum, David; Chan, Raymond

2017-01-01

Abstract Background: Prospective memory (PM) refers to remembering to execute a planned intention in the future, which can been divided as event-based PM (focal, nonfocal) and time-based PM according to the nature of the cue. Focal event-based PM, where the ongoing task requires processing of the characteristics of PM cues, has been found to be benefited from implementation intention (II, ie, an encoding strategy in the format of “if I see X, then I will do Y”). However, to date, it is unclear whether implementation intention can produce a positive effect on nonfocal event-based PM (where the ongoing task is irrelevant with the PM cues) and time-based PM. Moreover, patients with schizophrenia (SCZ) were found to have impairments in these types of PM, and few studies have been conducted to examine the effect of II on these types of PM. This study investigated whether (and how) implementation intention can improve nonfocal event-based PM and time-based PM performance in patients with SCZ. Methods: Forty-two patients with SCZ and 42 healthy control participants were administered both computerized nonfocal event-based PM task and time-based PM task. Patients and healthy controls were further randomly allocated to implementation intention condition (N = 21) and typical instruction condition (N = 21). Results: Patients with SCZ in the implementation intention group showed higher PM accuracy than the typical instruction group in both nonfocal event-based PM task (0.51 ± 0.32 vs 0.19 ± 0.29, t(40) = 3.39, P = .002) and time-based PM task (0.72 ± 0.31 vs 0.39 ± 0.40, t(40) = 2.98, P = .005). Similarly, healthy controls in the II group also showed better PM performance than the typical instruction group in both tasks (all P’s < 0.05). Time check frequency of time-based PM task in the II group of all the participants was significantly higher than the typical instruction group. Conclusion: Implementation intention is an effective strategy for improving different types of PM performance in patients with schizophrenia and can be applied for clinical settings.

Timeline trend profile and seasonal variations in nicotine present in ambient PM10 samples: A four year investigation from Delhi region, India

NASA Astrophysics Data System (ADS)

Yadav, Shweta; Tandon, Ankit; Attri, Arun K.

2014-12-01

The detection of nicotine, an organic tracer for Environmental Tobacco Smoke (ETS), in the collected PM10 samples from Delhi region's ambient environment, in a appropriately designed investigation was initiated over four years (2006-2009) to: (1) Comprehend seasonal and inter-annual variations in the nicotine present in PM10; (2) Extract regression based linear trend profile manifested by nicotine in PM10; (3) Determine the non-linear trend timeline from the nicotine data, and compare it with the obtained linear trend; (4) Suggest the possible use of the designed experiment and analysis to have a qualitative appraisal of Tobacco Smoking activity in the sampling region. The PM10 samples were collected in a monthly time-series sequence at a known receptor site. Quantitative estimates of nicotine (ng m-3) were made by using a Thermal Desorption Gas Chromatography Mass Spectrometry (TD-GC/MS). The annual average concentrations of nicotine (ng m-3) were 516 ± 302 (2008) > 494 ± 301 (2009) > 438 ± 250 (2007) > 325 ± 149 (2006). The estimated linear trend of 5.4 ng m-3 month-1 corresponded to 16.3% per annum increase in the PM10 associated nicotine. The industrial production of India's tobacco index normalized to Delhi region's consumption, pegged an increase at 10.5% per annum over this period.

Operational model evaluation for particulate matter in Europe and North America in the context of AQMEII

NASA Astrophysics Data System (ADS)

Solazzo, Efisio; Bianconi, Roberto; Pirovano, Guido; Matthias, Volker; Vautard, Robert; Moran, Michael D.; Wyat Appel, K.; Bessagnet, Bertrand; Brandt, Jørgen; Christensen, Jesper H.; Chemel, Charles; Coll, Isabelle; Ferreira, Joana; Forkel, Renate; Francis, Xavier V.; Grell, Georg; Grossi, Paola; Hansen, Ayoe B.; Miranda, Ana Isabel; Nopmongcol, Uarporn; Prank, Marje; Sartelet, Karine N.; Schaap, Martijn; Silver, Jeremy D.; Sokhi, Ranjeet S.; Vira, Julius; Werhahn, Johannes; Wolke, Ralf; Yarwood, Greg; Zhang, Junhua; Rao, S. Trivikrama; Galmarini, Stefano

2012-06-01

Ten state-of-the-science regional air quality (AQ) modeling systems have been applied to continental-scale domains in North America and Europe for full-year simulations of 2006 in the context of Air Quality Model Evaluation International Initiative (AQMEII), whose main goals are model inter-comparison and evaluation. Standardised modeling outputs from each group have been shared on the web-distributed ENSEMBLE system, which allows statistical and ensemble analyses to be performed. In this study, the one-year model simulations are inter-compared and evaluated with a large set of observations for ground-level particulate matter (PM10 and PM2.5) and its chemical components. Modeled concentrations of gaseous PM precursors, SO2 and NO2, have also been evaluated against observational data for both continents. Furthermore, modeled deposition (dry and wet) and emissions of several species relevant to PM are also inter-compared. The unprecedented scale of the exercise (two continents, one full year, fifteen modeling groups) allows for a detailed description of AQ model skill and uncertainty with respect to PM. Analyses of PM10 yearly time series and mean diurnal cycle show a large underestimation throughout the year for the AQ models included in AQMEII. The possible causes of PM bias, including errors in the emissions and meteorological inputs (e.g., wind speed and precipitation), and the calculated deposition are investigated. Further analysis of the coarse PM components, PM2.5 and its major components (SO4, NH4, NO3, elemental carbon), have also been performed, and the model performance for each component evaluated against measurements. Finally, the ability of the models to capture high PM concentrations has been evaluated by examining two separate PM2.5 episodes in Europe and North America. A large variability among models in predicting emissions, deposition, and concentration of PM and its precursors during the episodes has been found. Major challenges still remain with regards to identifying and eliminating the sources of PM bias in the models. Although PM2.5 was found to be much better estimated by the models than PM10, no model was found to consistently match the observations for all locations throughout the entire year.

Comparison of Remote Sensing and Fixed-Site Monitoring Approaches for Examining Air Pollution and Health in a National Study Population

NASA Technical Reports Server (NTRS)

Prud'homme, Genevieve; Dobbin, Nina A.; Sun, Liu; Burnet, Richard T.; Martin, Randall V.; Davidson, Andrew; Cakmak, Sabit; Villeneuve, Paul J.; Lamsal, Lok N.; vanDonkelaar, Aaron;

The relationship of respiratory and cardiovascular hospital admissions to the southern California wildfires of 2003.

PubMed

Delfino, R J; Brummel, S; Wu, J; Stern, H; Ostro, B; Lipsett, M; Winer, A; Street, D H; Zhang, L; Tjoa, T; Gillen, D L

2009-03-01

There is limited information on the public health impact of wildfires. The relationship of cardiorespiratory hospital admissions (n = 40 856) to wildfire-related particulate matter (PM(2.5)) during catastrophic wildfires in southern California in October 2003 was evaluated. Zip code level PM(2.5) concentrations were estimated using spatial interpolations from measured PM(2.5), light extinction, meteorological conditions, and smoke information from MODIS satellite images at 250 m resolution. Generalised estimating equations for Poisson data were used to assess the relationship between daily admissions and PM(2.5), adjusted for weather, fungal spores (associated with asthma), weekend, zip code-level population and sociodemographics. Associations of 2-day average PM(2.5) with respiratory admissions were stronger during than before or after the fires. Average increases of 70 microg/m(3) PM(2.5) during heavy smoke conditions compared with PM(2.5) in the pre-wildfire period were associated with 34% increases in asthma admissions. The strongest wildfire-related PM(2.5) associations were for people ages 65-99 years (10.1% increase per 10 microg/m(3) PM(2.5), 95% CI 3.0% to 17.8%) and ages 0-4 years (8.3%, 95% CI 2.2% to 14.9%) followed by ages 20-64 years (4.1%, 95% CI -0.5% to 9.0%). There were no PM(2.5)-asthma associations in children ages 5-18 years, although their admission rates significantly increased after the fires. Per 10 microg/m(3) wildfire-related PM(2.5), acute bronchitis admissions across all ages increased by 9.6% (95% CI 1.8% to 17.9%), chronic obstructive pulmonary disease admissions for ages 20-64 years by 6.9% (95% CI 0.9% to 13.1%), and pneumonia admissions for ages 5-18 years by 6.4% (95% CI -1.0% to 14.2%). Acute bronchitis and pneumonia admissions also increased after the fires. There was limited evidence of a small impact of wildfire-related PM(2.5) on cardiovascular admissions. Wildfire-related PM(2.5) led to increased respiratory hospital admissions, especially asthma, suggesting that better preventive measures are required to reduce morbidity among vulnerable populations.

Comparative analysis of specialization in palliative medicine processes within the World Health Organization European region.

PubMed

Centeno, Carlos; Bolognesi, Deborah; Biasco, Guido

2015-05-01

Palliative medicine (PM), still in the development phase, is a new, growing specialty aimed at caring for both oncology and non-oncology patients. There is still confusion about the training offered in the various European PM certification programs. To provide a detailed, comparative update and analysis of the PM certification process in Europe, including the different training approaches and their main features. Experts from each country completed an online survey addressing historical background, program name, training requirements, length of time in training, characteristic and content, official certifying institution, effectiveness of accreditation, and 2013 workforce capacity. We prepared a comparative analysis of the data provided. In 2014, 18 of 53 European countries had official programs on specialization in PM (POSPM): Czech Republic, Denmark, Finland, France, Georgia, Germany, Hungary, Ireland, Israel, Italy, Latvia, Malta, Norway, Poland, Portugal, Romania, Slovakia, and the U.K. Ten of these programs were begun in the last five years. The PM is recognized as a "specialty," "subspecialty," or "special area of competence," with no substantial differences between the last two designations. The certification contains the term "palliative medicine" in most countries. Clinical training varies, with one to two years being the most frequent duration. There is a clear trend toward establishing the POSPM as a mandatory condition for obtaining a clinical PM position in countries' respective health systems. PM is growing as a specialization field in Europe. Processes leading to certification are generally long and require substantial clinical training. The POSPM education plans are heterogeneous. The European Association for Palliative Care should commit to establishing common learning standards, leading to additional European-based recognition of expertise in PM. Copyright © 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Increment of ambient exposure to fine particles and the reduced human fertility rate in China, 2000-2010.

PubMed

Xue, Tao; Zhu, Tong

2018-06-13

Epidemiological and toxicological studies suggest that exposure to ambient fine particles (PM 2.5 ) can reduce human reproductive capacity. We previously reported, based on spatial epidemiology, that higher levels of PM 2.5 exposure were associated with a lower fertility rate (FR) in China. However, that study was limited by a lack of temporal variation. Using first-difference regression, we linked temporal changes in FR and PM 2.5 with adjustment for ecological covariates across 2806 counties in China during 2000-2010. Next, we performed a sensitivity analysis of the variation in the PM 2.5 -FR association according to (1) geographic region, (2) indicators of the level of development, and (3) PM 2.5 concentrations. Also, we quantified the reduction in the FR attributable to ambient PM 2.5 in China for the first time. The FR decreased by 3.3% (1.2%, 5.3%) for each 10 μg/m 3 increment in PM 2.5 . The association varied significantly among the geographic regions, but not with the level of development. Nonlinearity analysis suggested a linear exposure-response function with an effect threshold of ~8 μg/m 3 . We also found that comparing to the 2000 scenario, increment of PM 2.5 in 2010 might result in a reduction of 2.50 (2.44, 2.60) infants per 1000 women aged 15-44 years per year in China. Our results confirm the statistical association between ambient particles and FR and suggest that poor air quality may contribute to childlessness in China. Copyright © 2018 Elsevier B.V. All rights reserved.

Ambient particulate matter and lung function growth in Chinese children.

PubMed

Roy, Ananya; Hu, Wei; Wei, Fusheng; Korn, Leo; Chapman, Robert S; Zhang, Junfeng Jim

2012-05-01

Exposure to particulate matter (PM) has been associated with deficits in lung function growth among children in Western countries. However, few studies have explored this association in developing countries, where PM levels are often substantially higher. Children (n = 3273) 6-12 years of age were recruited from 8 schools in 4 Chinese cities. The lung function parameters of forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV1) were measured using computerized spirometers twice a year for up to 3 years (1993-1996). Dichotomous samplers placed in each schoolyard were used to measure PM2.5 and PM10 (PM with diameter ≤ 2.5 μm and ≤ 10 μm, respectively). Multivariable generalized estimating equations were used to examine the association between the quarterly average PM levels and lung function growth during the period of follow-up. Annual average PM2.5 and PM10 levels in the 4 cities ranged from 57 to 158 μg/m and 95 to 268 μg/m, respectively. In multivariable models, an increase of 10 μg/m of PM2.5 was associated with decreases of 2.7 mL FEV1 (95% confidence interval = -3.5 to -2.0), 3.5 mL FVC (-4.3 to -2.7), 1.4 mL/year FEV1 growth (-1.8 to -0.9), and 1.5 mL/year FVC growth (-2.0 to -1.0). Similar results were seen with PM10 exposure. Exposure to ambient particulate matter was associated with decreased growth in lung function among Chinese children.

Research on the optimization of air quality monitoring station layout based on spatial grid statistical analysis method.

PubMed

Li, Tianxin; Zhou, Xing Chen; Ikhumhen, Harrison Odion; Difei, An

2018-05-01

In recent years, with the significant increase in urban development, it has become necessary to optimize the current air monitoring stations to reflect the quality of air in the environment. Highlighting the spatial representation of some air monitoring stations using Beijing's regional air monitoring station data from 2012 to 2014, the monthly mean particulate matter concentration (PM10) in the region was calculated and through the IDW interpolation method and spatial grid statistical method using GIS, the spatial distribution of PM10 concentration in the whole region was deduced. The spatial distribution variation of districts in Beijing using the gridding model was performed, and through the 3-year spatial analysis, PM10 concentration data including the variation and spatial overlay (1.5 km × 1.5 km cell resolution grid), the spatial distribution result obtained showed that the total PM10 concentration frequency variation exceeded the standard. It is very important to optimize the layout of the existing air monitoring stations by combining the concentration distribution of air pollutants with the spatial region using GIS.

New evidence on the impact of sustained exposure to air pollution on life expectancy from China’s Huai River Policy

PubMed Central

Ebenstein, Avraham; Fan, Maoyong; Greenstone, Michael; He, Guojun; Zhou, Maigeng

2017-01-01

This paper finds that a 10-μg/m3 increase in airborne particulate matter [particulate matter smaller than 10 μm (PM10)] reduces life expectancy by 0.64 years (95% confidence interval = 0.21–1.07). This estimate is derived from quasiexperimental variation in PM10 generated by China’s Huai River Policy, which provides free or heavily subsidized coal for indoor heating during the winter to cities north of the Huai River but not to those to the south. The findings are derived from a regression discontinuity design based on distance from the Huai River, and they are robust to using parametric and nonparametric estimation methods, different kernel types and bandwidth sizes, and adjustment for a rich set of demographic and behavioral covariates. Furthermore, the shorter lifespans are almost entirely caused by elevated rates of cardiorespiratory mortality, suggesting that PM10 is the causal factor. The estimates imply that bringing all of China into compliance with its Class I standards for PM10 would save 3.7 billion life-years. PMID:28893980

Health effects of ambient levels of respirable particulate matter (PM) on healthy, young-adult population

NASA Astrophysics Data System (ADS)

Shaughnessy, William J.; Venigalla, Mohan M.; Trump, David

2015-12-01

There is an absence of studies that define the relationship between ambient particulate matter (PM) levels and adverse health outcomes among the young and healthy adult sub-group. In this research, the relationship between exposures to ambient levels of PM in the 10 micron (PM10) and 2.5 micron (PM2.5) size fractions and health outcomes in members of the healthy, young-adult subgroup who are 18-39 years of age was examined. Active duty military personnel populations at three strategically selected military bases in the United States were used as a surrogate to the control group. Health outcome data, which consists of the number of diagnoses for each of nine International Classification of Diseases, 9th Revision (ICD-9) categories related to respiratory illness, were derived from outpatient visits at each of the three military bases. Data on ambient concentrations of particulate matter, specifically PM10 and PM2.5, were obtained for these sites. The health outcome data were correlated and regressed with the PM10 and PM2.5 data, and other air quality and weather-related data on a daily and weekly basis for the period 1998 to 2004. Results indicate that at Fort Bliss, which is a US Environmental Protection Agency designated non-attainment area for PM10, a statistically significant association exists between the weekly-averaged number of adverse health effects in the young and healthy adult population and the corresponding weekly-average ambient PM10 concentration. A least squares regression analysis was performed on the Fort Bliss data sets indicated that the health outcome data is related to several environmental parameters in addition to PM10. Overall, the analysis estimates a .6% increase in the weekly rate of emergency room visits for upper respiratory infections for every 10 μg/m3 increase in the weekly-averaged PM10 concentration above the mean. The findings support the development of policy and guidance opportunities that can be developed to mitigate exposures to particulate matter.

77 FR 12769 - Approval and Promulgation of Implementation Plans; Georgia; Macon; Fine Particulate Matter 2002...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-02

... ENVIRONMENTAL PROTECTION AGENCY 40 CFR Part 52 [EPA-R04-OAR-2011-0850-201154(b); FRL-9639-7] Approval and Promulgation of Implementation Plans; Georgia; Macon; Fine Particulate Matter 2002 Base Year... proposing to approve the fine particulate matter (PM 2.5 ) 2002 base year emissions inventory, portion of...

77 FR 12526 - Approval and Promulgation of Implementation Plans; Georgia; Atlanta; Fine Particulate Matter 2002...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-01

... ENVIRONMENTAL PROTECTION AGENCY 40 CFR Part 52 [EPA-R04-OAR-2012-0050-201207(b); FRL-9639-3] Approval and Promulgation of Implementation Plans; Georgia; Atlanta; Fine Particulate Matter 2002 Base Year... proposing to approve the fine particulate matter (PM 2.5 ) 2002 base year emissions inventory, portion of...

Spatiotemporal air pollution exposure assessment for a Canadian population-based lung cancer case-control study

PubMed Central

2012-01-01

Background Few epidemiological studies of air pollution have used residential histories to develop long-term retrospective exposure estimates for multiple ambient air pollutants and vehicle and industrial emissions. We present such an exposure assessment for a Canadian population-based lung cancer case-control study of 8353 individuals using self-reported residential histories from 1975 to 1994. We also examine the implications of disregarding and/or improperly accounting for residential mobility in long-term exposure assessments. Methods National spatial surfaces of ambient air pollution were compiled from recent satellite-based estimates (for PM2.5 and NO2) and a chemical transport model (for O3). The surfaces were adjusted with historical annual air pollution monitoring data, using either spatiotemporal interpolation or linear regression. Model evaluation was conducted using an independent ten percent subset of monitoring data per year. Proximity to major roads, incorporating a temporal weighting factor based on Canadian mobile-source emission estimates, was used to estimate exposure to vehicle emissions. A comprehensive inventory of geocoded industries was used to estimate proximity to major and minor industrial emissions. Results Calibration of the national PM2.5 surface using annual spatiotemporal interpolation predicted historical PM2.5 measurement data best (R2 = 0.51), while linear regression incorporating the national surfaces, a time-trend and population density best predicted historical concentrations of NO2 (R2 = 0.38) and O3 (R2 = 0.56). Applying the models to study participants residential histories between 1975 and 1994 resulted in mean PM2.5, NO2 and O3 exposures of 11.3 μg/m3 (SD = 2.6), 17.7 ppb (4.1), and 26.4 ppb (3.4) respectively. On average, individuals lived within 300 m of a highway for 2.9 years (15% of exposure-years) and within 3 km of a major industrial emitter for 6.4 years (32% of exposure-years). Approximately 50% of individuals were classified into a different PM2.5, NO2 and O3 exposure quintile when using study entry postal codes and spatial pollution surfaces, in comparison to exposures derived from residential histories and spatiotemporal air pollution models. Recall bias was also present for self-reported residential histories prior to 1975, with cases recalling older residences more often than controls. Conclusions We demonstrate a flexible exposure assessment approach for estimating historical air pollution concentrations over large geographical areas and time-periods. In addition, we highlight the importance of including residential histories in long-term exposure assessments. For submission to: Environmental Health PMID:22475580

Short-term Elevation of Fine Particulate Matter Air Pollution and Acute Lower Respiratory Infection.

PubMed

Horne, Benjamin D; Joy, Elizabeth A; Hofmann, Michelle G; Gesteland, Per H; Cannon, John B; Lefler, Jacob S; Blagev, Denitza P; Korgenski, E Kent; Torosyan, Natalie; Hansen, Grant I; Kartchner, David; Pope Iii, C Arden

2018-04-13

Nearly 60% of U.S. children live in counties with PM2.5 concentrations above air quality standards. Understanding the relationship between ambient air pollution exposure and health outcomes informs actions to reduce exposure and disease risk. To evaluate the association between ambient PM2.5 levels and healthcare encounters for acute lower respiratory infection (ALRI). Using an observational case-crossover design, subjects (N=146,397) were studied if they had an ALRI diagnosis and resided on Utah's Wasatch Front. PM2.5 air pollution concentrations were measured using community-based air quality monitors between 1999 and 2016. Odds ratios (OR) for ALRI healthcare encounters were calculated after stratification by ages 0-2, 3-17, and 18+ years. Approximately 77% (n=112,467) of subjects were 0-2 years of age. The odds of ALRI encounter for these young children increased within 1 week of elevated PM2.5 and peaked after 3 weeks with a cumulative 28-day OR= 1.15 per +10 μg/m3 (95% CI= 1.12, 1.19). ALRI encounters with diagnosed and laboratory-confirmed RSV and influenza increased following elevated ambient PM2.5 levels. Similar elevated odds for ALRI were also observed for older children, although the number of events and precision of estimates were much lower. In this large sample of urban/suburban patients, short-term exposure to elevated PM2.5 air pollution was associated with greater healthcare utilization for ALRI in both young children, older children, and adults. Further exploration is needed of causal interactions between PM2.5 and ALRI.

Parent ratings of working memory are uniquely related to performance-based measures of secondary memory but not primary memory.

PubMed

Ralph, Kathryn J; Gibson, Bradley S; Gondoli, Dawn M

2018-03-06

Existing evidence suggests that performance- and rating-based measures of working memory (WM) correlate poorly. Although some researchers have interpreted this evidence as suggesting that these measures may be assessing distinct cognitive constructs, another possibility is that rating-based measures are related to some but not all theoretically motivated performance-based measures. The current study distinguished between performance-based measures of primary memory (PM) and secondary memory (SM), and examined the relation between each of these components of WM and parent-ratings on the WM subscale of the Behavior Rating Inventory of Executive Function (BRIEF-WM). Because SM and BRIEF-WM scores have both been associated with group differences in attention-deficit/hyperactivity disorder (ADHD), it was hypothesized that SM scores would be uniquely related to parent-rated BRIEF-WM scores. Participants were a sample of 77 adolescents with and without an ADHD diagnosis, aged 11 to 15 years, from a midwestern school district. Participant scores on verbal and spatial immediate free recall tasks were used to estimate both PM and SM capacities. Partial correlation analyses were used to evaluate the extent to which estimates of PM and SM were uniquely related parent-rated BRIEF-WM scores. Both verbal and spatial SM scores were significantly related to parent-rated BRIEF-WM scores, when corresponding PM scores were controlled. Higher verbal and spatial SM scores were associated with less frequent parent-report of WM-related failures in their child's everyday life. However, neither verbal nor spatial PM scores significantly related to parent-rated BRIEF-WM scores, when corresponding SM scores were controlled. The current study suggested that previously observed low correlations between performance- and rating-based measures of WM may result from use of performance-based WM measures that do not capture the unique contributions of PM and SM components of WM.

The practice and earnings of preventive medicine physicians.

PubMed

Salive, M E

1992-01-01

A shortage of preventive medicine (PM) physicians exists in the United States. Researchers know little about these physicians' earnings and practice characteristics. The American College of Preventive Medicine (ACPM) mailed a survey to all self-identified PM physicians on the American Medical Association (AMA) Physician Masterfile. A total of 3,771 (54%) responded; respondents' sex and region of residence were typical for PM physicians in general, with a slight excess of older physicians and those reporting board certification. A total of 2,664 (71%) were working full time, with median earnings of $85,000 (mean $90,000). Among full-time physicians, relatively higher earnings were associated with the following characteristics: male sex; age 45 to 64 years; major source of income from clinical, business, or industrial sources, rather than governmental or academic; and PM board certification. Full-time PM physicians earned much less than office-based private practitioners in several primary care specialties in 1989. The gap in earnings between PM specialists in government positions and those in the private sector is also substantial. Both disparities may require creative solutions.

Spatiotemporal Patterns of Ground Monitored PM2.5 Concentrations in China in Recent Years

PubMed Central

Li, Junming; Han, Xiulan; Li, Xiao; Yang, Jianping; Li, Xuejiao

2018-01-01

This paper firstly explores the space-time evolution of city-level PM2.5 concentrations showed a very significant seasonal cycle type fluctuation during the period between 13 May 2014 and 30 May 2017. The period from October to April following each year was a heavy pollution period, whereas the phase from April to October of the current year was part of a light pollution period. The average monthly PM2.5 concentrations in mainland China based on ground monitoring, employing a descriptive statistics method and a Bayesian spatiotemporal hierarchy model. Daily and weekly average PM2.5 concentrations in 338 cities in mainland China presented no significant spatial difference during the severe pollution period but a large spatial difference during light pollution periods. The severe PM2.5 pollution areas were mainly distributed in the Beijing-Tianjin-Hebei urban agglomeration in the North China Plain during the beginning of each autumn-winter season (September), spreading to the Northeast Plains after October, then later continuing to spread to other cities in mainland China, eventually covering most cities. PM2.5 pollution in China appeared to be a cyclic characteristic of first spreading and then centralizing in the space in two spring-summer seasons, and showed an obvious process of first diffusing then transferring to shrinkage alternation during the spring-summer season of 2015, but showed no obvious diffusion during the spring-summer season of 2016, maintaining a stable spatial structure after the shrinkage in June, as well as being more concentrated. The heavily polluted areas are continuously and steadily concentrated in East China, Central China and Xinjiang Province. PMID:29324671

Traffic-related air pollution, particulate matter, and autism.

PubMed

Volk, Heather E; Lurmann, Fred; Penfold, Bryan; Hertz-Picciotto, Irva; McConnell, Rob

2013-01-01

Autism is a heterogeneous disorder with genetic and environmental factors likely contributing to its origins. Examination of hazardous pollutants has suggested the importance of air toxics in the etiology of autism, yet little research has examined its association with local levels of air pollution using residence-specific exposure assignments. To examine the relationship between traffic-related air pollution, air quality, and autism. This population-based case-control study includes data obtained from children with autism and control children with typical development who were enrolled in the Childhood Autism Risks from Genetics and the Environment study in California. The mother's address from the birth certificate and addresses reported from a residential history questionnaire were used to estimate exposure for each trimester of pregnancy and first year of life. Traffic-related air pollution was assigned to each location using a line-source air-quality dispersion model. Regional air pollutant measures were based on the Environmental Protection Agency's Air Quality System data. Logistic regression models compared estimated and measured pollutant levels for children with autism and for control children with typical development. Case-control study from California. A total of 279 children with autism and a total of 245 control children with typical development. Crude and multivariable adjusted odds ratios (AORs) for autism. Children with autism were more likely to live at residences that had the highest quartile of exposure to traffic-related air pollution, during gestation (AOR, 1.98 [95% CI, 1.20-3.31]) and during the first year of life (AOR, 3.10 [95% CI, 1.76-5.57]), compared with control children. Regional exposure measures of nitrogen dioxide and particulate matter less than 2.5 and 10 μm in diameter (PM2.5 and PM10) were also associated with autism during gestation (exposure to nitrogen dioxide: AOR, 1.81 [95% CI, 1.37-3.09]; exposure to PM2.5: AOR, 2.08 [95% CI, 1.93-2.25]; exposure to PM10: AOR, 2.17 [95% CI, 1.49-3.16) and during the first year of life (exposure to nitrogen dioxide: AOR, 2.06 [95% CI, 1.37-3.09]; exposure to PM2.5: AOR, 2.12 [95% CI, 1.45-3.10]; exposure to PM10: AOR, 2.14 [95% CI, 1.46-3.12]). All regional pollutant estimates were scaled to twice the standard deviation of the distribution for all pregnancy estimates. Exposure to traffic-related air pollution, nitrogen dioxide, PM2.5, and PM10 during pregnancy and during the first year of life was associated with autism. Further epidemiological and toxicological examinations of likely biological pathways will help determine whether these associations are causal.

In-Plume Emission Test Stand 2: emission factors for 10- to 100-kW U.S. military generators.

PubMed

Zhu, Dongzi; Nussbaum, Nicholas J; Kuhns, Hampden D; Chang, M-C Oliver; Sodeman, David; Uppapalli, Sebastian; Moosmüller, Hans; Chow, Judith C; Watson, John G

2009-12-01

Although emissions of air pollutants from some military tactical equipment are not subject to the emissions standards, local communities near military bases must conform to the National Ambient Air Quality Standards. Military diesel generators are widely used in training. A portable in-plume system was used to measure fuel-based emission factors (EFs) for particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), and hydrocarbons (HCs) for 30-, 60-, and 100-kW generators at five load levels and for cold starts. It was found that EFs depend on multiple parameters including engine size, engine load, unit age, and total running hours. The average CO EF of generators tested was 5% lower, and the average NOx EF was 63% lower than AP-42 estimates; average PM EF was 80% less than the AP-42 estimates. A 2002 model-year 60-kW engine produced 25% less PM than a 1995 engine of the same family with similar running hours. CO EFs decrease with increasing engine load, NOx EFs increase up to mid-loads and decrease slightly at high loads, PM EFs increase with loads for 30- and 60-kW engines. CO and PM have higher EFs and NOx has a lower EF during cold starts than during hot-stabilized operation. PM chemical source profiles were also examined.

Relationship Between Fine-Particle Pollution and the Urban Heat Island in Beijing, China: Observational Evidence

NASA Astrophysics Data System (ADS)

Zheng, Zuofang; Ren, Guoyu; Wang, Hong; Dou, Junxia; Gao, Zhiqiu; Duan, Chunfeng; Li, Yubin; Ngarukiyimana, Jean Paul; Zhao, Chun; Cao, Chang; Jiang, Mei; Yang, Yuanjian

2018-05-01

Urbanization has led to a significant urban heat island (UHI) effect in Beijing in recent years. At the same time, air pollution caused by a large number of fine particles significantly influences the atmospheric environment, urban climate, and human health. The distribution of fine particulate matter (PM 2.5 ) concentration and its relationship with the UHI effect in the Beijing area are analyzed based on station-observed hourly data from 2012 to 2016. We conclude that, (1) in the last five years, the surface concentrations of PM 2.5 averaged for urban and rural sites in and around Beijing are 63.2 and 40.7 µg m-3, respectively, with significant differences between urban and rural sites (ΔPM 2.5 ) at the seasonal, monthly and daily scales observed; (2) there is a large correlation between ΔPM 2.5 and the UHI intensity defined as the differences in the mean (ΔT ave ), minimum (ΔT min ), and maximum (ΔT max ) temperatures between urban and rural sites. The correlation between ΔPM 2.5 and ΔT min (ΔT max ) is the highest (lowest); (3) a Granger causality analysis further shows that ΔPM 2.5 and ΔT min are most correlated for a lag of 1-2 days, while the correlation between ΔPM 2.5 and ΔT ave is lower; there is no causal relationship between ΔPM 2.5 and ΔT max ; (4) a case analysis shows that downwards shortwave radiation at the surface decreases with an increase in PM 2.5 concentration, leading to a weaker UHI intensity during the daytime. During the night, the outgoing longwave radiation from the surface decreases due to the presence of daytime pollutants, the net effect of which is a slower cooling rate during the night in cities than in the suburbs, leading to a larger ΔT min .

Remote sensing of PM2.5 during cloudy and nighttime periods using ceilometer backscatter

NASA Astrophysics Data System (ADS)

Li, Siwei; Joseph, Everette; Min, Qilong; Yin, Bangsheng; Sakai, Ricardo; Payne, Megan K.

2017-06-01

Monitoring PM2.5 (particulate matter with aerodynamic diameter d ≤ 2.5 µm) mass concentration has become of more importance recently because of the negative impacts of fine particles on human health. However, monitoring PM2.5 during cloudy and nighttime periods is difficult since nearly all the passive instruments used for aerosol remote sensing are not able to measure aerosol optical depth (AOD) under either cloudy or nighttime conditions. In this study, an empirical model based on the regression between PM2.5 and the near-surface backscatter measured by ceilometers was developed and tested using 6 years of data (2006 to 2011) from the Howard University Beltsville Campus (HUBC) site. The empirical model can explain ˜ 56, ˜ 34 and ˜ 42 % of the variability in the hourly average PM2.5 during daytime clear, daytime cloudy and nighttime periods, respectively. Meteorological conditions and seasons were found to influence the relationship between PM2.5 mass concentration and the surface backscatter. Overall the model can explain ˜ 48 % of the variability in the hourly average PM2.5 at the HUBC site when considering the seasonal variation. The model also was tested using 4 years of data (2012 to 2015) from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, which was geographically and climatologically different from the HUBC site. The results show that the empirical model can explain ˜ 66 and ˜ 82 % of the variability in the daily average PM2.5 at the ARM SGP site and HUBC site, respectively. The findings of this study illustrate the strong need for ceilometer data in air quality monitoring under cloudy and nighttime conditions. Since ceilometers are used broadly over the world, they may provide an important supplemental source of information of aerosols to determine surface PM2.5 concentrations.

Long- and short-term exposure to PM2.5 and mortality: using novel exposure models.

PubMed

Kloog, Itai; Ridgway, Bill; Koutrakis, Petros; Coull, Brent A; Schwartz, Joel D

2013-07-01

Many studies have reported associations between ambient particulate matter (PM) and adverse health effects, focused on either short-term (acute) or long-term (chronic) PM exposures. For chronic effects, the studied cohorts have rarely been representative of the population. We present a novel exposure model combining satellite aerosol optical depth and land-use data to investigate both the long- and short-term effects of PM2.5 exposures on population mortality in Massachusetts, United States, for the years 2000-2008. All deaths were geocoded. We performed two separate analyses: a time-series analysis (for short-term exposure) where counts in each geographic grid cell were regressed against cell-specific short-term PM2.5 exposure, temperature, socioeconomic data, lung cancer rates (as a surrogate for smoking), and a spline of time (to control for season and trends). In addition, for long-term exposure, we performed a relative incidence analysis using two long-term exposure metrics: regional 10 × 10 km PM2.5 predictions and local deviations from the cell average based on land use within 50 m of the residence. We tested whether these predicted the proportion of deaths from PM-related causes (cardiovascular and respiratory diseases). For short-term exposure, we found that for every 10-µg/m increase in PM 2.5 exposure there was a 2.8% increase in PM-related mortality (95% confidence interval [CI] = 2.0-3.5). For the long-term exposure at the grid cell level, we found an odds ratio (OR) for every 10-µg/m increase in long-term PM2.5 exposure of 1.6 (CI = 1.5-1.8) for particle-related diseases. Local PM2.5 had an OR of 1.4 (CI = 1.3-1.5), which was independent of and additive to the grid cell effect. We have developed a novel PM2.5 exposure model based on remote sensing data to assess both short- and long-term human exposures. Our approach allows us to gain spatial resolution in acute effects and an assessment of long-term effects in the entire population rather than a selective sample from urban locations.

Evaluating strategies to reduce urban air pollution

NASA Astrophysics Data System (ADS)

Duque, L.; Relvas, H.; Silveira, C.; Ferreira, J.; Monteiro, A.; Gama, C.; Rafael, S.; Freitas, S.; Borrego, C.; Miranda, A. I.

2016-02-01

During the last years, specific air quality problems have been detected in the urban area of Porto (Portugal). Both PM10 and NO2 limit values have been surpassed in several air quality monitoring stations and, following the European legislation requirements, Air Quality Plans were designed and implemented to reduce those levels. In this sense, measures to decrease PM10 and NO2 emissions have been selected, these mainly related to the traffic sector, but also regarding the industrial and residential combustion sectors. The main objective of this study is to investigate the efficiency of these reduction measures with regard to the improvement of PM10 and NO2 concentration levels over the Porto urban region using a numerical modelling tool - The Air Pollution Model (TAPM). TAPM was applied over the study region, for a simulation domain of 80 × 80 km2 with a spatial resolution of 1 × 1 km2. The entire year of 2012 was simulated and set as the base year for the analysis of the impacts of the selected measures. Taking into account the main activity sectors, four main scenarios have been defined and simulated, with focus on: (1) hybrid cars; (2) a Low Emission Zone (LEZ); (3) fireplaces and (4) industry. The modelling results indicate that measures to reduce PM10 should be focused on residential combustion (fireplaces) and industrial activity and for NO2 the strategy should be based on the traffic sector. The implementation of all the defined scenarios will allow a total maximum reduction of 4.5% on the levels of both pollutants.

Regression trees modeling and forecasting of PM10 air pollution in urban areas

NASA Astrophysics Data System (ADS)

Stoimenova, M.; Voynikova, D.; Ivanov, A.; Gocheva-Ilieva, S.; Iliev, I.

2017-10-01

Fine particulate matter (PM10) air pollution is a serious problem affecting the health of the population in many Bulgarian cities. As an example, the object of this study is the pollution with PM10 of the town of Pleven, Northern Bulgaria. The measured concentrations of this air pollutant for this city consistently exceeded the permissible limits set by European and national legislation. Based on data for the last 6 years (2011-2016), the analysis shows that this applies both to the daily limit of 50 micrograms per cubic meter and the allowable number of daily concentration exceedances to 35 per year. Also, the average annual concentration of PM10 exceeded the prescribed norm of no more than 40 micrograms per cubic meter. The aim of this work is to build high performance mathematical models for effective prediction and forecasting the level of PM10 pollution. The study was conducted with the powerful flexible data mining technique Classification and Regression Trees (CART). The values of PM10 were fitted with respect to meteorological data such as maximum and minimum air temperature, relative humidity, wind speed and direction and others, as well as with time and autoregressive variables. As a result the obtained CART models demonstrate high predictive ability and fit the actual data with up to 80%. The best models were applied for forecasting the level pollution for 3 to 7 days ahead. An interpretation of the modeling results is presented.

Purpose, processes, partnerships, and products: four Ps to advance participatory socio-environmental modeling

USGS Publications Warehouse

Gray, Steven; Voinov, Alexey; Paolisso, Michael; Jordan, Rebecca; BenDor, Todd; Bommel, Pierre; Glynn, Pierre D.; Hedelin, Beatrice; Hubacek, Klaus; Introne, Josh; Kolagani, Nagesh; Laursen, Bethany; Prell, Christina; Schmitt-Olabisi, Laura; Singer, Alison; Sterling, Eleanor J.; Zellner, Moira

2018-01-01

Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human–environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.

Purpose, processes, partnerships, and products: four Ps to advance participatory socio-environmental modeling.

PubMed

Gray, Steven; Voinov, Alexey; Paolisso, Michael; Jordan, Rebecca; BenDor, Todd; Bommel, Pierre; Glynn, Pierre; Hedelin, Beatrice; Hubacek, Klaus; Introne, Josh; Kolagani, Nagesh; Laursen, Bethany; Prell, Christina; Schmitt Olabisi, Laura; Singer, Alison; Sterling, Eleanor; Zellner, Moira

2018-01-01

Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM. © 2017 by the Ecological Society of America.

Air pollution-related health and climate benefits of clean cookstove programs in Mozambique

NASA Astrophysics Data System (ADS)

Anenberg, Susan C.; Henze, Daven K.; Lacey, Forrest; Irfan, Ans; Kinney, Patrick; Kleiman, Gary; Pillarisetti, Ajay

2017-02-01

Approximately 95% of households in Mozambique burn solid fuels for cooking, contributing to elevated indoor and outdoor fine particulate matter (PM2.5) concentrations and subsequent health and climate impacts. Little is known about the potential health and climate benefits of various approaches for expanding the use of cleaner stoves and fuels in Mozambique. We use state-of-the-science methods to provide a first-order estimation of potential air pollution-related health and climate benefits of four illustrative scenarios in which traditional cooking fires and stoves are displaced by cleaner and more efficient technologies. For rural areas, we find that a 10% increase in the number of households using forced draft wood-burning stoves could achieve >2.5 times more health benefits from reduced PM2.5 exposure (200 avoided premature deaths and 14 000 avoided disability adjusted life years, DALYs, over a three-year project lifetime) compared to natural draft stoves in the same households, assuming 70% of households use the new technology for both cases. Expanding use of LPG stoves to 10% of households in five major cities is estimated to avoid 160 premature deaths and 11 000 DALYs from reduced PM2.5 exposure for a three-year intervention, assuming 60% of households use the new stove. Advanced charcoal stoves would achieve ∽80% of the PM2.5-related health benefits of LPG stoves. Approximately 2%-5% additional health benefits would result from reduced ambient PM2.5, depending on the scenario. Although climate impacts are uncertain, we estimate that all scenarios would reduce expected climate change-related temperature increases from continued solid fuel use by 4%-6% over the next century. All results are based on an assumed adjustment factor of 0.8 to convert from laboratory-based emission reduction measurements to exposure reductions, which could be optimistic in reality given potential for continued use of the traditional stove. We conclude that cleaner cooking stoves in Mozambique can achieve health and climate benefits, though both are uncertain and local information about baseline and intervention PM2.5 exposure levels are needed.

[Surgical treatment of pediatric pulmonary metastases].

PubMed

Costa Borrás, E; Ferrís i Tortajada, J; Jovaní Casano, C; Segarra Llido, V; Bermúdez Cortés, M; Cañete Nieto, A; Velázquez Terrón, J

1998-07-01

We comment and update the surgical treatment for pulmonary metastases (PM) within a multidisciplinary approach for paediatric cancer. We analyse patients with PM who have been operated between 1976-1996. Scientific literature published in the last 25 years (Cancerlit and Medline) was reviewed. PM from 13 patients were removed. Seven were males and 6 females with a mean age 5 4/12 years (range: 11 months- 12 3/12 years). Diagnoses were Wilms' tumour (7), osteosarcoma (3), Ewing sarcoma (1), rabdomiosarcoma (1), Yolk sac tumour (1). PM were unilateral in 7 cases and bilateral in six cases. PM appeared synchronically in four patients and metacronically in nine cases (3 of these after chemotherapy). All patients received chemotherapy and four of them local radiotherapy. Surgery consisted on radical segmentectomy and only one patient needed lobectomy due to a local relapse. Nowadays five patients (38%) are in complete remission with a mean follow-up from surgery of 11 11/12 years (range: 6 3/12-20 years). Metastasectomy is an important surgical technique in global treatment of children with PM and for a selected group of patients it can offer the only opportunity for curation.

The relationship of respiratory and cardiovascular hospital admissions to the southern California wildfires of 2003

PubMed Central

Delfino, R J; Brummel, S; Wu, J; Stern, H; Ostro, B; Lipsett, M; Winer, A; Street, D H; Zhang, L; Tjoa, T; Gillen, D L

2014-01-01

Objective There is limited information on the public health impact of wildfires. The relationship of cardiorespiratory hospital admissions (n = 40 856) to wildfire-related particulate matter (PM2.5) during catastrophic wildfires in southern California in October 2003 was evaluated. Methods Zip code level PM2.5 concentrations were estimated using spatial interpolations from measured PM2.5, light extinction, meteorological conditions, and smoke information from MODIS satellite images at 250 m resolution. Generalised estimating equations for Poisson data were used to assess the relationship between daily admissions and PM2.5, adjusted for weather, fungal spores (associated with asthma), weekend, zip code-level population and sociodemographics. Results Associations of 2-day average PM2.5 with respiratory admissions were stronger during than before or after the fires. Average increases of 70 μg/m3 PM2.5 during heavy smoke conditions compared with PM2.5 in the pre-wildfire period were associated with 34% increases in asthma admissions. The strongest wildfire-related PM2.5 associations were for people ages 65– 99 years (10.1% increase per 10 μg/m3 PM2.5, 95% CI 3.0% to 17.8%) and ages 0–4 years (8.3%, 95% CI 2.2% to 14.9%) followed by ages 20–64 years (4.1%, 95% CI 20.5% to 9.0%). There were no PM2.5–asthma associations in children ages 5–18 years, although their admission rates significantly increased after the fires. Per 10 μg/m3 wildfire-related PM2.5, acute bronchitis admissions across all ages increased by 9.6% (95% CI 1.8% to 17.9%), chronic obstructive pulmonary disease admissions for ages 20–64 years by 6.9% (95% CI 0.9% to 13.1%), and pneumonia admissions for ages 5–18 years by 6.4% (95% CI 21.0% to 14.2%). Acute bronchitis and pneumonia admissions also increased after the fires. There was limited evidence of a small impact of wildfire-related PM2.5 on cardiovascular admissions. Conclusions Wildfire-related PM2.5 led to increased respiratory hospital admissions, especially asthma, suggesting that better preventive measures are required to reduce morbidity among vulnerable populations. PMID:19017694

78 FR 59261 - Approval and Promulgation of Implementation Plans; Designation of Areas for Air Quality Planning...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-26

... continue to attain the 24-hour PM 10 NAAQS for at least 10 years beyond redesignation (i.e., through 2023... maintenance demonstration showing how the area will continue to attain the 24-hour PM 10 NAAQS for 10 years... serves as the Sacramento PM 10 Maintenance Plan's attainment year emissions inventory, as satisfying the...

The reduction of summer sulfate and switch from summertime to wintertime PM2.5 concentration maxima in the United States

NASA Astrophysics Data System (ADS)

Chan, Elizabeth A. W.; Gantt, Brett; McDow, Stephen

2018-02-01

Exposure to particulate matter air pollution with a nominal mean aerodynamic diameter less than or equal to 2.5 μm (PM2.5) has been associated with health effects including cardiovascular disease and death. Here, we add to the understanding of urban and rural PM2.5 concentrations over large spatial and temporal scales in recent years. We used high-quality, publicly-available air quality monitoring data to evaluate PM2.5 concentration patterns and changes during the years 2000-2015. Compiling and averaging measurements collected across the U.S. revealed that PM2.5 concentrations from urban sites experienced seasonal maxima in both winter and summer. Within each year from 2000 to 2008, the maxima of urban summer peaks were greater than winter peaks. However, from 2012 to 2015, the maxima of urban summertime PM2.5 peaks were smaller than the urban wintertime PM2.5 maxima, due to a decrease in the magnitude of summertime maxima with no corresponding decrease in the magnitude of winter maxima. PM2.5 measurements at rural sites displayed summer peaks with magnitudes relatively similar to those of urban sites, and negligible to no winter peaks through the time period analyzed. Seasonal variations of urban and rural PM2.5 sulfate, PM2.5 nitrate, and PM2.5 organic carbon (OC) were also assessed. Summer peaks in PM2.5 sulfate decreased dramatically between 2000 and 2015, whereas seasonal PM2.5 OC and winter PM2.5 nitrate concentration maxima remained fairly consistent. These findings demonstrate that PM2.5 concentrations, especially those occurring in the summertime, have declined in the U.S. from 2000 to 2015. In addition, reduction strategies targeting sulfate have been successful and the decrease in PM2.5 sulfate contributed to the decline in total PM2.5.

Analysis of PM10, PM2.5, and PM2 5-10 concentrations in Santiago, Chile, from 1989 to 2001.

PubMed

Koutrakis, Petros; Sax, Sonja N; Sarnat, Jeremy A; Coull, Brent; Demokritou, Phil; Oyola, Pedro; Garcia, Javier; Gramsch, Ernesto

2005-03-01

Daily particle samples were collected in Santiago, Chile, at four urban locations from January 1, 1989, through December 31, 2001. Both fine PM with da < 2.5 microm (PM2.5) and coarse PM with 2.5 < da < 10 microm (PM2.5-10) were collected using dichotomous samplers. The inhalable particle fraction, PM10, was determined as the sum of fine and coarse concentrations. Wind speed, temperature and relative humidity (RH) were also measured continuously. Average concentrations of PM2.5 for the 1989-2001 period ranged from 38.5 microg/m3 to 53 microg/m3. For PM2.5-10 levels ranged from 35.8-48.2 microg/m3 and for PM10 results were 74.4-101.2 microg/m3 across the four sites. Both annual and daily PM2.5 and PM10 concentration levels exceeded the U.S. National Ambient Air Quality Standards and the European Union concentration limits. Mean PM2.5 levels during the cold season (April through September) were more than twice as high as those observed in the warm season (October through March); whereas coarse particle levels were similar in both seasons. PM concentration trends were investigated using regression models, controlling for site, weekday, month, wind speed, temperature, and RH. Results showed that PM2.5 concentrations decreased substantially, 52% over the 12-year period (1989-2000), whereas PM2.5-10 concentrations increased by approximately 50% in the first 5 years and then decreased by a similar percentage over the following 7 years. These decreases were evident even after controlling for significant climatic effects. These results suggest that the pollution reduction programs developed and implemented by the Comisión Nacional del Medio Ambiente (CONAMA) have been effective in reducing particle levels in the Santiago Metropolitan region. However, particle levels remain high and it is thus imperative that efforts to improve air quality continue.

Estimating premature mortality attributable to PM2.5 exposure and benefit of air pollution control policies in China for 2020.

PubMed

Maji, Kamal Jyoti; Dikshit, Anil Kumar; Arora, Mohit; Deshpande, Ashok

2018-01-15

In past decade of rapid industrial development and urbanization, China has witnessed increasingly persistent severe haze and smog episodes, posing serious health hazards to the Chinese population, especially in densely populated cities. Quantification of health impacts attributable to PM 2.5 (particulates with aerodynamic diameter≤2.5μm) has important policy implications to tackle air pollution. The Chinese national monitoring network has recently included direct measurements of ground level PM 2.5 , providing a potentially more reliable source for exposure assessment. This study reports PM 2.5 -related long-term mortality of year 2015 in 161 cities of nine regions across China using integrated exposure risk (IER) model for PM 2.5 exposure-response functions (ERF). It further provides an estimate of the potential health benefits by year 2020 with a realization of the goals of Air Pollution Prevention and Control Action Plan (APPCAP) and the three interim targets (ITs) and Air Quality Guidelines (AQG) for PM 2.5 by the World Health Organization (WHO). PM 2.5 -related premature mortality in 161 cities was 652 thousand, about 6.92% of total deaths in China during year 2015. Among all premature deaths, contributions of cerebrovascular disease (stroke), ischemic heart disease (IHD), chronic obstructive pulmonary disease (COPD), lung cancer (LC) and acute lower respiratory infections (ALRIs) were 51.70, 26.26, 11.77, 9.45 and 0.82%, respectively. The premature mortality in densely populated cities is very high, such as Tianjin (12,533/year), Beijing (18,817/year), Baoding (10,932/year), Shanghai (18,679/year), Chongqing (23,561/year), Chengdu (11,809/year), Harbin (9037/year) and Linyi (9141/year). The potential health benefits will be 4.4, 16.2, 34.5, 63.6 and 81.5% of the total present premature mortality when PM 2.5 concentrations in China meet the APPCAP, WHO IT-1, IT-2, IT-3 and AQG respectively, by the year 2020. In the current situation, by the end of year 2030, even if Chines government fulfills its own target to meet national ambient air quality standard of PM 2.5 (35μg/m 3 ), total premature mortality attributable to PM 2.5 will be 574 thousand across 161 cities. The present methodology will greatly help policy makers and pollution control authorities to further analyze cost and benefits of air pollution management programs in China. Copyright © 2017 Elsevier B.V. All rights reserved.

The impact of cognitive control on children's goal monitoring in a time-based prospective memory task.

PubMed

Mahy, Caitlin E V; Voigt, Babett; Ballhausen, Nicola; Schnitzspahn, Katharina; Ellis, Judi; Kliegel, Matthias

2015-01-01

The present study investigated whether developmental changes in cognitive control may underlie improvements of time-based prospective memory. Five-, 7-, 9-, and 11-year-olds (N = 166) completed a driving simulation task (ongoing task) in which they had to refuel their vehicle at specific points in time (PM task). The availability of cognitive control resources was experimentally manipulated by imposing a secondary task that required divided attention. Children completed the driving simulation task both in a full-attention condition and a divided-attention condition where they had to carry out a secondary task. Results revealed that older children performed better than younger children on the ongoing task and PM task. Children performed worse on the ongoing and PM tasks in the divided-attention condition compared to the full-attention condition. With respect to time monitoring in the final interval prior to the PM target, divided attention interacted with age such that older children's time monitoring was more negatively affected by the secondary task compared to younger children. Results are discussed in terms of developmental shifts from reactive to proactive monitoring strategies.

Burden of mortality and years of life lost due to ambient PM10 pollution in Wuhan, China.

PubMed

Zhang, Yunquan; Peng, Minjin; Yu, Chuanhua; Zhang, Lan

2017-11-01

Ambient particulate matter (PM) has been mainly linked with mortality and morbidity when assessing PM-associated health effects. Up-to-date epidemiologic evidence is very sparse regarding the relation between PM and years of life lost (YLL). The present study aimed to estimate the burden of YLL and mortality due to ambient PM pollution. Individual records of all registered deaths and daily data on PM 10 and meteorology during 2009-2012 were obtained in Wuhan, central China. Using a time-series study design, we applied generalized additive model to assess the short-term association of 10-μg/m 3 increase in PM 10 with daily YLL and mortality, adjusting for long-term trend and seasonality, mean temperature, relative humidity, public holiday, and day of the week. A linear-no-threshold dose-response association was observed between daily ambient PM 10 and mortality outcomes. PM 10 pollution along lag 0-1 days was found to be mostly strongly associated with mortality and YLL. The effects of PM 10 on cause-specific mortality and YLL showed generally similar seasonal patterns, with stronger associations consistently occurring in winter and/or autumn. Compared with males and younger persons, females and the elderly suffered more significantly from both increased YLL and mortality due to ambient PM 10 pollution. Stratified analyses by education level (0-6 and 7 + years) demonstrated great mortality impact on both subgroups, whereas only low-educated persons were strongly affected by PM 10 -associated burden of YLL. Our study confirmed that short-term PM 10 exposure was linearly associated with significant increases in both mortality incidence and years of life lost. Given the non-threshold adverse effects on mortality burden, the on-going efforts to reduce particulate air pollution would substantially benefit public health in China. Copyright © 2017 Elsevier Ltd. All rights reserved.

Establishing post mortem criteria for the metabolic syndrome: an autopsy based cross-sectional study.

PubMed

Christensen, Martin Roest; Bugge, Anne; Malik, Mariam Elmegaard; Thomsen, Jørgen Lange; Lynnerup, Niels; Rungby, Jørgen; Banner, Jytte

2018-01-01

Individuals who suffer from mental illness are more prone to obesity and related co-morbidities, including the metabolic syndrome. Autopsies provide an outstanding platform for the macroscopic, microscopic and molecular-biological investigation of diseases. Autopsy-based findings may assist in the investigation of the metabolic syndrome. To utilise the vast information that an autopsy encompasses to elucidate the pathophysiology behind the syndrome further, we aimed to both develop and evaluate a method for the post mortem definition of the metabolic syndrome. Based on the nationwide Danish SURVIVE study of deceased mentally ill, we established a set of post mortem criteria for each of the harmonized criteria of the metabolic syndrome. We based the post mortem (PM) evaluation on information from the police reports and the data collected at autopsy, such as anthropometric measurements and biochemical and toxicological analyses (PM information). We compared our PM evaluation with the data from the Danish health registries [ante mortem (AM) information, considered the gold standard] from each individual. The study included 443 deceased individuals (272 male and 171 female) with a mean age of 50.4 (± 15.5) years and a median (interquartile range) post mortem interval of 114 (84-156) hours. We found no significant difference when defining the metabolic syndrome from the PM information in comparison to the AM information ( P  = 0.175). The PM evaluation yielded a high specificity (0.93) and a moderate sensitivity (0.63) with a moderate level of agreement compared to the AM evaluation (Cohen's κ = 0.51). Neither age nor post mortem interval affected the final results. Our model of a PM definition of the metabolic syndrome proved reliable when compared to the AM information. We believe that an appropriate estimate of the prevalence of the metabolic syndrome can be established post mortem. However, while neither the PM nor the AM information is exhaustive in terms of defining an individual's health status, a superlative estimate may be obtained by combining the PM and the AM information. With this model, we open up the possibility of utilising autopsy data for future studies of the metabolic syndrome.

Particulate matter levels in a South American megacity: the metropolitan area of Lima-Callao, Peru.

PubMed

Silva, Jose; Rojas, Jhojan; Norabuena, Magdalena; Molina, Carolina; Toro, Richard A; Leiva-Guzmán, Manuel A

2017-11-13

The temporal and spatial trends in the variability of PM 10 and PM 2.5 from 2010 to 2015 in the metropolitan area of Lima-Callao, Peru, are studied and interpreted in this work. The mean annual concentrations of PM 10 and PM 2.5 have ranges (averages) of 133-45 μg m -3 (84 μg m -3 ) and 35-16 μg m -3 (26 μg m -3 ) for the monitoring sites under study. In general, the highest annual concentrations are observed in the eastern part of the city, which is a result of the pattern of persistent local winds entering from the coast in a south-southwest direction. Seasonal fluctuations in the particulate matter (PM) concentrations are observed; these can be explained by subsidence thermal inversion. There is also a daytime pattern that corresponds to the peak traffic of a total of 9 million trips a day. The PM 2.5 value is approximately 40% of the PM 10 value. This proportion can be explained by PM 10 re-suspension due to weather conditions. The long-term trends based on the Theil-Sen estimator reveal decreasing PM 10 concentrations on the order of -4.3 and -5.3% year -1 at two stations. For the other stations, no significant trend is observed. The metropolitan area of Lima-Callao is ranked 12th and 16th in terms of PM 10 and PM 2.5 , respectively, out of 39 megacities. The annual World Health Organization thresholds and national air quality standards are exceeded. A large fraction of the Lima population is exposed to PM concentrations that exceed protection thresholds. Hence, the development of pollution control and reduction measures is paramount.

Cardiovascular Effects of Long-Term Exposure to Air Pollution: A Population-Based Study With 900 845 Person-Years of Follow-up.

PubMed

Kim, Hyeanji; Kim, Joonghee; Kim, Sunhwa; Kang, Si-Hyuck; Kim, Hee-Jun; Kim, Ho; Heo, Jongbae; Yi, Seung-Muk; Kim, Kyuseok; Youn, Tae-Jin; Chae, In-Ho

2017-11-08

Studies have shown that long-term exposure to air pollution such as fine particulate matter (≤2.5 μm in aerodynamic diameter [PM 2.5 ]) increases the risk of all-cause and cardiovascular mortality. To date, however, there are limited data on the impact of air pollution on specific cardiovascular diseases. This study aimed to evaluate cardiovascular effects of long-term exposure to air pollution among residents of Seoul, Korea. Healthy participants with no previous history of cardiovascular disease were evaluated between 2007 and 2013. Exposure to air pollutants was estimated by linking the location of outdoor monitors to the ZIP code of each participant's residence. Crude and adjusted analyses were performed using Cox regression models to evaluate the risk for composite cardiovascular events including cardiovascular mortality, acute myocardial infarction, congestive heart failure, and stroke. A total of 136 094 participants were followed for a median of 7.0 years (900 845 person-years). The risk of major cardiovascular events increased with higher mean concentrations of PM 2.5 in a linear relationship, with a hazard ratio of 1.36 (95% confidence interval, 1.29-1.43) per 1 μg/m 3 PM 2.5 . Other pollutants including PM 2.5-10 of CO, SO 2 , and NO 2 , but not O 3 , were significantly associated with increased risk of cardiovascular events. The burden from air pollution was comparable to that from hypertension and diabetes mellitus. This large-scale population-based study demonstrated that long-term exposure to air pollution including PM 2.5 increases the risk of major cardiovascular disease and mortality. Air pollution should be considered an important modifiable environmental cardiovascular risk factor. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Multi-year ground-based observations of aerosol-cloud interactions in the Mid-Atlantic of the United States

NASA Astrophysics Data System (ADS)

Li, Siwei; Joseph, Everette; Min, Qilong; Yin, Bangsheng

2017-02-01

The U.S. Mid-Atlantic region experiences a wide variability of aerosol loading and frequent episodes of elevated anthropogenic aerosol loading associated with urban pollution conditions during summer months. In this study, multi-year ground-based observations (2006 to 2010) of aerosol and cloud properties from passive, active and in situ measurements at an atmospheric measurement field station in the Baltimore-Washington corridor operated by Howard University were analyzed to examine aerosol indirect effect on single-layer warm clouds including cloud optical depth (COD), liquid water path (LWP), cloud droplet effective radius (Re) and cloud droplet number concentration (Nd) in this region. A greater occurrence of polluted episodes and cloud cases with smaller Re (<7 μm) were found during the polluted year summers (2006, 2007 and 2008) than the clean year summers (2009 and 2010). The measurements of aerosol particulate matter with aerodynamic diameter≤2.5 μm (PM2.5) were used to represent the aerosol loading under cloudy conditions. Significant negative relationships between cloud droplet Re and PM2.5 were observed. Cloud cases were separated into clean and polluted groups based on the value of PM2.5. The cloud droplet Re was found proportional to LWP under clean conditions but weakly dependent on LWP under polluted conditions. The Nd was proportional to LWP under polluted condition but weakly dependent on LWP under clean conditions. Moreover, the effects of increasing fine aerosol particles on modifying cloud microphysical properties were found more significant under large LWP than small LWP in this region.

Aircraft-based Observations and Modeling of Wintertime Submicron Aerosol Composition over the Northeastern U.S.

NASA Astrophysics Data System (ADS)

Shah, V.; Jaegle, L.; Schroder, J. C.; Campuzano-Jost, P.; Jimenez, J. L.; Guo, H.; Sullivan, A.; Weber, R. J.; Green, J. R.; Fiddler, M.; Bililign, S.; Lopez-Hilfiker, F.; Lee, B. H.; Thornton, J. A.

2017-12-01

Submicron aerosol particles (PM1) remain a major air pollution concern in the urban areas of northeastern U.S. While SO2 and NOx emission controls have been effective at reducing summertime PM1 concentrations, this has not been the case for wintertime sulfate and nitrate concentrations, suggesting a nonlinear response during winter. During winter, organic aerosol (OA) is also an important contributor to PM1 mass despite low biogenic emissions, suggesting the presence of important urban sources. We use aircraft-based observations collected during the Wintertime INvestigation of Transport, Emissions and Reactivity (WINTER) campaign (Feb-March 2015), together with the GEOS-Chem chemical transport model, to investigate the sources and chemical processes governing wintertime PM1 over the northeastern U.S. The mean observed concentration of PM1 between the surface and 1 km was 4 μg m-3, about 30% of which was composed of sulfate, 20% nitrate, 10% ammonium, and 40% OA. The model reproduces the observed sulfate, nitrate and ammonium concentrations after updates to HNO3 production and loss, SO2 oxidation, and NH3 emissions. We find that 65% of the sulfate formation occurs in the aqueous phase, and 55% of nitrate formation through N2O5 hydrolysis, highlighting the importance of multiphase and heterogeneous processes during winter. Aqueous-phase sulfate production and the gas-particle partitioning of nitrate and ammonium are affected by atmospheric acidity, which in turn depends on the concentration of these species. We examine these couplings with GEOS-Chem, and assess the response of wintertime PM1 concentrations to further emission reductions based on the U.S. EPA projections for the year 2023. For OA, we find that the standard GEOS-Chem simulation underestimates the observed concentrations, but a simple parameterization developed from previous summer field campaigns is able to reproduce the observations and the contribution of primary and secondary OA. We find that residential wood combustion accounts for about 25% of the OA, while secondary production from urban anthropogenic VOCs accounts for the rest. We examine how OA concentrations may change as a result of changing emissions for the year 2023.

75 FR 13710 - Approval and Promulgation of Implementation Plans; Designation of Areas for Air Quality Planning...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-23

...-10 standard is determined by calculating the expected number of days in a year with PM-10... PM-10. See 40 CFR part 50, appendix K. A complete year of air quality data, as referred to in 40 CFR... certified. As noted above, the 24-hour PM-10 standard is attained when the expected number of days per year...

Risk for emerging bipolar disorder, variants, and symptoms in children with attention deficit hyperactivity disorder, now grown up

PubMed Central

Elmaadawi, Ahmed Z; Jensen, Peter S; Arnold, L Eugene; Molina, Brooke SG; Hechtman, Lily; Abikoff, Howard B; Hinshaw, Stephen P; Newcorn, Jeffrey H; Greenhill, Laurence Lee; Swanson, James M; Galanter, Cathryn A

2015-01-01

AIM: To determine the prevalence of bipolar disorder (BD) and sub-threshold symptoms in children with attention deficit hyperactivity disorder (ADHD) through 14 years’ follow-up, when participants were between 21-24 years old. METHODS: First, we examined rates of BD type I and II diagnoses in youth participating in the NIMH-funded Multimodal Treatment Study of ADHD (MTA). We used the diagnostic interview schedule for children (DISC), administered to both parents (DISC-P) and youth (DISCY). We compared the MTA study subjects with ADHD (n = 579) to a local normative comparison group (LNCG, n = 289) at 4 different assessment points: 6, 8, 12, and 14 years of follow-ups. To evaluate the bipolar variants, we compared total symptom counts (TSC) of DSM manic and hypomanic symptoms that were generated by DISC in ADHD and LNCG subjects. Then we sub-divided the TSC into pathognomonic manic (PM) and non-specific manic (NSM) symptoms. We compared the PM and NSM in ADHD and LNCG at each assessment point and over time. We also evaluated the irritability as category A2 manic symptom in both groups and over time. Finally, we studied the irritability symptom in correlation with PM and NSM in ADHD and LNCG subjects. RESULTS: DISC-generated BD diagnosis did not differ significantly in rates between ADHD (1.89%) and LNCG 1.38%). Interestingly, no participant met BD diagnosis more than once in the 4 assessment points in 14 years. However, on the symptom level, ADHD subjects reported significantly higher mean TSC scores: ADHD 3.0; LNCG 1.7; P < 0.001. ADHD status was associated with higher mean NSM: ADHD 2.0 vs LNCG 1.1; P < 0.0001. Also, ADHD subjects had higher PM symptoms than LNCG, with PM means over all time points of 1.3 ADHD; 0.9 LNCG; P = 0.0001. Examining both NSM and PM, ADHD status associated with greater NSM than PM. However, Over 14 years, the NSM symptoms declined and changed to PM over time (df 3, 2523; F = 20.1; P < 0.0001). Finally, Irritability (BD DSM criterion-A2) rates were significantly higher in ADHD than LNCG (χ2 = 122.2, P < 0.0001), but irritability was associated more strongly with NSM than PM (df 3, 2538; F = 43.2; P < 0.0001). CONCLUSION: Individuals with ADHD do not appear to be at significantly greater risk for developing BD, but do show higher rates of BD symptoms, especially NSM. The greater linkage of irritability to NSM than to PM suggests caution when making BD diagnoses based on irritability alone as one of 2 (A-level) symptoms for BD diagnosis, particularly in view of its frequent presentation with other psychopathologies. PMID:26740933

Historical Prediction Modeling Approach for Estimating Long-Term Concentrations of PM2.5 in Cohort Studies before the 1999 Implementation of Widespread Monitoring.

PubMed

Kim, Sun-Young; Olives, Casey; Sheppard, Lianne; Sampson, Paul D; Larson, Timothy V; Keller, Joshua P; Kaufman, Joel D

2017-01-01

Recent cohort studies have used exposure prediction models to estimate the association between long-term residential concentrations of fine particulate matter (PM2.5) and health. Because these prediction models rely on PM2.5 monitoring data, predictions for times before extensive spatial monitoring present a challenge to understanding long-term exposure effects. The U.S. Environmental Protection Agency (EPA) Federal Reference Method (FRM) network for PM2.5 was established in 1999. We evaluated a novel statistical approach to produce high-quality exposure predictions from 1980 through 2010 in the continental United States for epidemiological applications. We developed spatio-temporal prediction models using geographic predictors and annual average PM2.5 data from 1999 through 2010 from the FRM and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks. Temporal trends before 1999 were estimated by using a) extrapolation based on PM2.5 data in FRM/IMPROVE, b) PM2.5 sulfate data in the Clean Air Status and Trends Network, and c) visibility data across the Weather Bureau Army Navy network. We validated the models using PM2.5 data collected before 1999 from IMPROVE, California Air Resources Board dichotomous sampler monitoring (CARB dichot), the Children's Health Study (CHS), and the Inhalable Particulate Network (IPN). In our validation using pre-1999 data, the prediction model performed well across three trend estimation approaches when validated using IMPROVE and CHS data (R2 = 0.84-0.91) with lower R2 values in early years. Model performance using CARB dichot and IPN data was worse (R2 = 0.00-0.85) most likely because of fewer monitoring sites and inconsistent sampling methods. Our prediction modeling approach will allow health effects estimation associated with long-term exposures to PM2.5 over extended time periods ≤ 30 years. Citation: Kim SY, Olives C, Sheppard L, Sampson PD, Larson TV, Keller JP, Kaufman JD. 2017. Historical prediction modeling approach for estimating long-term concentrations of PM2.5 in cohort studies before the 1999 implementation of widespread monitoring. Environ Health Perspect 125:38-46; http://dx.doi.org/10.1289/EHP131.

Prenatal Particulate Air Pollution and Neurodevelopment in Urban Children: Examining Sensitive Windows and Sex-specific Associations

PubMed Central

Chiu, Yueh-Hsiu Mathilda; Hsu, Hsiao-Hsien Leon; Coull, Brent A.; Bellinger, David C.; Kloog, Itai; Schwartz, Joel; Wright, Robert O.; Wright, Rosalind J.

2015-01-01

Background Brain growth and structural organization occurs in stages beginning prenatally. Toxicants may impact neurodevelopment differently dependent upon exposure timing and fetal sex. Objectives We implemented innovative methodology to identify sensitive windows for the associations between prenatal particulate matter with diameter≤2.5μm (PM2.5) and children’s neurodevelopment. Methods We assessed 267 full-term urban children’s prenatal daily PM2.5 exposure using a validated satellite-based spatio-temporally resolved prediction model. Outcomes included IQ (WISC-IV), attention (omission errors [OEs], commission errors [CEs], hit reaction time [HRT], and HRT standard error [HRT-SE] on the Conners’ CPT-II), and memory (general memory [GM] index and its components - verbal [VEM] and visual [VIM] memory, and attention-concentration [AC] indices on the WRAML-2) assessed at age 6.5±0.98 years. To identify the role of exposure timing, we used distributed lag models to examine associations between weekly prenatal PM2.5 exposure and neurodevelopment. Sex-specific associations were also examined. Results Mothers were primarily minorities (60% Hispanic, 25% black); 69% had ≤12 years of education. Adjusting for maternal age, education, race, and smoking, we found associations between higher PM2.5 levels at 31–38 weeks with lower IQ, at 20–26 weeks gestation with increased OEs, at 32–36 weeks with slower HRT, and at 22–40 weeks with increased HRT-SE among boys, while significant associations were found in memory domains in girls (higher PM2.5 exposure at 18–26 weeks with reduced VIM, at 12–20 weeks with reduced GM). Conclusions Increased PM2.5 exposure in specific prenatal windows was associated with poorer function across memory and attention domains with variable associations based on sex. Refined determination of time window- and sex-specific associations may enhance insight into underlying mechanisms and identification of vulnerable subgroups. PMID:26641520

Prenatal particulate air pollution and neurodevelopment in urban children: Examining sensitive windows and sex-specific associations.

PubMed

Chiu, Yueh-Hsiu Mathilda; Hsu, Hsiao-Hsien Leon; Coull, Brent A; Bellinger, David C; Kloog, Itai; Schwartz, Joel; Wright, Robert O; Wright, Rosalind J

2016-02-01

Brain growth and structural organization occurs in stages beginning prenatally. Toxicants may impact neurodevelopment differently dependent upon exposure timing and fetal sex. We implemented innovative methodology to identify sensitive windows for the associations between prenatal particulate matter with diameter ≤ 2.5 μm (PM2.5) and children's neurodevelopment. We assessed 267 full-term urban children's prenatal daily PM2.5 exposure using a validated satellite-based spatio-temporally resolved prediction model. Outcomes included IQ (WISC-IV), attention (omission errors [OEs], commission errors [CEs], hit reaction time [HRT], and HRT standard error [HRT-SE] on the Conners' CPT-II), and memory (general memory [GM] index and its components - verbal [VEM] and visual [VIM] memory, and attention-concentration [AC] indices on the WRAML-2) assessed at age 6.5±0.98 years. To identify the role of exposure timing, we used distributed lag models to examine associations between weekly prenatal PM2.5 exposure and neurodevelopment. Sex-specific associations were also examined. Mothers were primarily minorities (60% Hispanic, 25% black); 69% had ≤12 years of education. Adjusting for maternal age, education, race, and smoking, we found associations between higher PM2.5 levels at 31-38 weeks with lower IQ, at 20-26 weeks gestation with increased OEs, at 32-36 weeks with slower HRT, and at 22-40 weeks with increased HRT-SE among boys, while significant associations were found in memory domains in girls (higher PM2.5 exposure at 18-26 weeks with reduced VIM, at 12-20 weeks with reduced GM). Increased PM2.5 exposure in specific prenatal windows may be associated with poorer function across memory and attention domains with variable associations based on sex. Refined determination of time window- and sex-specific associations may enhance insight into underlying mechanisms and identification of vulnerable subgroups. Copyright © 2015 Elsevier Ltd. All rights reserved.

Health Benefits of Decreases in PM2.5 and Ozone in the United States from 1998 to 2016

NASA Astrophysics Data System (ADS)

Nawaz, O.; Zhang, Y.; Tong, D.; van Donkelaar, A.; Martin, R.; West, J. J.

2017-12-01

Between 1990 and 2015 the US average concentration of PM2.5 decreased by 37% and ozone decreased by 22%, driven by environmental regulations and technological advances. These decreases in pollutants are expected to have brought substantial benefits for public health in the US. Here we assess the effects of this decrease by estimating the total burden of PM2.5 and ozone on premature mortality, each year between 1998-2016. Two data sets of ambient concentration were implemented in the health impact analysis that included different subsets of the time period. First, we use data from the North American Chemical Reanalysis project, which uses OMI NO2 and MODIS AOD observations for data assimilation to constrain ozone and PM2.5 between 2009-2016. Second, we use satellite-derived estimates of ground-level PM2.5 using AOD retrievals from NASA satellites combined with the GEOS-Chem chemical transport model between 1998-2015; these estimates are calibrated to ground-based observations using a geographically weighted regression. Using yearly data on population and baseline mortality provided by the Centers for Disease Control (CDC), we assess how air pollution-related mortality has changed annually within the continental United States, and analyze trends to determine how effectively the health burden has been reduced by environmental regulations and other factors.

Association between Atmospheric Fine Particulate Matter and Hospital Admissions for Chronic Obstructive Pulmonary Disease in Southwestern Taiwan: A Population-Based Study

PubMed Central

Hwang, Su-Lun; Guo, Su-Er; Chi, Miao-Ching; Chou, Chiang-Ting; Lin, Yu-Ching; Lin, Chieh-Mo; Chou, Yen-Li

2016-01-01

Objectives: This paper reports on the findings of a population-based study to evaluate the relationship between atmospheric fine particulate matter (PM2.5) levels and hospital admissions for chronic obstructive pulmonary disease (COPD) in southwestern Taiwan over a three-year period, 2008–2010. Methods: Data on hospital admissions for COPD and PM2.5 levels were obtained from the National Health Insurance Research database (NHIRD) and the Environmental Protection Administration from 2008 to 2010, respectively. The lag structure of relative risks (RRs) of hospital admissions for COPD was estimated using a Poisson regression model. Results: During the study period, the overall average hospitalization rate of COPD and mean 24-h average level of PM2.5 was 0.18% and 39.37 μg/m3, respectively. There were seasonal variations in PM2.5 concentrations in southwestern Taiwan, with higher PM2.5 concentrations in both spring (average: 48.54 μg/m3) and winter (49.96 μg/m3) than in summer (25.89 μg/m3) and autumn (33.37 μg/m3). Increased COPD admissions were significantly associated with PM2.5 in both spring (February–April) and winter (October–January), with the relative risks (RRs) for every 10 μg/m3 increase in PM2.5 being 1.25 (95% CI = 1.22–1.27) and 1.24 (95% CI = 1.23–1.26), respectively, at a lag zero days (i.e., no lag days). Lag effects on COPD admissions were observed for PM2.5, with the elevated RRs beginning at lag zero days and larger RRs estimates tending to occur at longer lags (up to six days, i.e., lag 0–5 days). Conclusions: In general, findings reveal an association between atmospheric fine particulate matter (PM2.5) and hospital admissions for COPD in southwestern Taiwan, especially during both spring and winter seasons. PMID:27023589

Contribution of dust storms to PM10 levels in an urban arid environment.

PubMed

Krasnov, Helena; Katra, Itzhak; Koutrakis, Petros; Friger, Michael D

2014-01-01

Quantitative information on the contribution of dust storms to atmospheric PM10 (particulate matter with an aerodynamic diameter < or = 10 microm) levels is still lacking, especially in urban environments with close proximity to dust sources. The main objective of this study was to quantify the contribution of dust storms to PM10 concentrations in a desert urban center, the city of Beer-Sheva, Negev, Israel, during the period of 2001-2012. Toward this end, a background value based on the "dust-free" season was used as a threshold value to identify potentially "dust days." Subsequently, the net contribution of dust storms to PM10 was assessed. During the study period, daily PM10 concentrations ranged from 6 to over 2000 microg/m3. In each year, over 10% of the daily concentrations exceeded the calculated threshold (BVt) of 71 microg/m3. An average daily net contribution of dust to PM10 of 122 microg/m3 was calculated for the entire study period based on this background value. Furthermore, a dust storm intensity parameter (Ai) was used to analyze several storms with very high PM10 contributions (hourly averages of 1000-5197 microg/m3). This analysis revealed that the strongest storms occurred mainly in the last 3 yr of the study. Finally, these findings indicate that this arid urban environment experiences high PM10 levels whose origin lies in both local and regional dust events. The findings indicate that over time, the urban arid environment experiences high PM10 levels whose origin lies in local and regional dust events. It was noticed that the strongest storms have occurred mainly in the last 3 yr. It is believed that environmental changes such as global warming and desertification may lead to an increased air pollution and risk exposure to human health.

Satellite-based estimates of long-term exposure to fine particulate matter are associated with C-reactive protein in 30 034 Taiwanese adults.

PubMed

Zhang, Zilong; Chang, Ly-Yun; Lau, Alexis K H; Chan, Ta-Chien; Chieh Chuang, Yuan; Chan, Jimmy; Lin, Changqing; Kai Jiang, Wun; Dear, Keith; Zee, Benny C Y; Yeoh, Eng-Kiong; Hoek, Gerard; Tam, Tony; Qian Lao, Xiang

2017-08-01

Particulate matter (PM) air pollution is associated with the risk of cardiovascular morbidity and mortality. However, the biological mechanism underlying the associations remains unclear. Atherosclerosis, the underlying pathology of cardiovascular disease, is a chronic inflammatory process. We therefore investigated the association of long-term exposure to fine PM (PM2.5) with C-reactive protein (CRP), a sensitive marker of systemic inflammation, in a large Taiwanese population. Participants were from a large cohort who participated in a standard medical examination programme with measurements of high-sensitivity CRP between 2007 and 2014. We used a spatiotemporal model to estimate 2-year average PM2.5 exposure at each participant's address, based on satellite-derived aerosol optical depth data. General regression models were used for baseline data analysis and mixed-effects linear regression models were used for repeated data analysis to investigate the associations between PM2.5 exposure and CRP, adjusting for a wide range of potential confounders. In this population of 30 034 participants with 39 096 measurements, every 5 μg/m3 PM2.5 increment was associated with a 1.31% increase in CRP [95% confidence interval (CI): 1.00%, 1.63%) after adjusting for confounders. For those participants with repeated CRP measurements, no significant changes were observed between the first and last measurements (0.88 mg/l vs 0.89 mg/l, P = 0.337). The PM2.5 concentrations remained stable over time between 2007 and 2014. Long-term exposure to PM2.5 is associated with increased level of systemic inflammation, supporting the biological link between PM2.5 air pollution and deteriorating cardiovascular health. Air pollution reduction should be an important strategy to prevent cardiovascular disease. © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association

Spatial patterning in PM2.5 constituents under an inversion-focused sampling design across an urban area of complex terrain

PubMed Central

Tunno, Brett J; Dalton, Rebecca; Michanowicz, Drew R; Shmool, Jessie L C; Kinnee, Ellen; Tripathy, Sheila; Cambal, Leah; Clougherty, Jane E

2016-01-01

Health effects of fine particulate matter (PM2.5) vary by chemical composition, and composition can help to identify key PM2.5 sources across urban areas. Further, this intra-urban spatial variation in concentrations and composition may vary with meteorological conditions (e.g., mixing height). Accordingly, we hypothesized that spatial sampling during atmospheric inversions would help to better identify localized source effects, and reveal more distinct spatial patterns in key constituents. We designed a 2-year monitoring campaign to capture fine-scale intra-urban variability in PM2.5 composition across Pittsburgh, PA, and compared both spatial patterns and source effects during “frequent inversion” hours vs 24-h weeklong averages. Using spatially distributed programmable monitors, and a geographic information systems (GIS)-based design, we collected PM2.5 samples across 37 sampling locations per year to capture variation in local pollution sources (e.g., proximity to industry, traffic density) and terrain (e.g., elevation). We used inductively coupled plasma mass spectrometry (ICP-MS) to determine elemental composition, and unconstrained factor analysis to identify source suites by sampling scheme and season. We examined spatial patterning in source factors using land use regression (LUR), wherein GIS-based source indicators served to corroborate factor interpretations. Under both summer sampling regimes, and for winter inversion-focused sampling, we identified six source factors, characterized by tracers associated with brake and tire wear, steel-making, soil and road dust, coal, diesel exhaust, and vehicular emissions. For winter 24-h samples, four factors suggested traffic/fuel oil, traffic emissions, coal/industry, and steel-making sources. In LURs, as hypothesized, GIS-based source terms better explained spatial variability in inversion-focused samples, including a greater contribution from roadway, steel, and coal-related sources. Factor analysis produced source-related constituent suites under both sampling designs, though factors were more distinct under inversion-focused sampling. PMID:26507005

Improving Air Pollution Modeling Over The Po Valley Using Saharan Dust Transport Forecasts

NASA Astrophysics Data System (ADS)

Kishcha, P.; Carnevale, C.; Finzi, G.; Pisoni, E.; Volta, M.; Nickovic, S.; Alpert, P.

2012-04-01

Our study shows that Saharan dust can contribute significantly to PM10 concentrations in the Po Valley. This dust contribution should be taken into account when estimating the exceedance of pollution limits. The DREAM dust model has been used for several years for producing operational dust forecasts at Tel-Aviv University, Israel. DREAM has been producing daily forecasts of 3-D distribution of dust concentrations over the Mediterranean region, Middle East, Europe, and over the Atlantic Ocean (http://wind.tau.ac.il/dust8/dust.html). In the current study, DREAM dust forecasts were used to give better model estimates of the contribution of Saharan dust to PM10 concentration over the Po Valley, in Northern Italy. This was carried out by the integration of daily Saharan dust forecasts into a mesoscale Transport Chemical Aerosol Model (TCAM). The Po Valley in Northern Italy is frequently affected by high PM10 concentrations, where both natural and anthropogenic sources play a significant role. Our study of TCAM and DREAM integration was carried out for the period May 15 - June 30, 2007, when four significant dust events were observed. The integrated TCAM-DREAM model performance was evaluated by comparing PM10 measurements with modeled PM10 concentrations. First, Saharan dust impact on TCAM performance was analyzed at eleven remote PM10 sites which had the lowest level of air pollution (PM10 ≤ 14 μg/m3) over the period under consideration. For those remote sites, the observed high PM10 concentrations during dust events stood prominently on the background of low PM10 concentrations. At the remote sites, such a strong deviation from the background level can not be attributed to anthropogenic aerosol emissions because of their distance from anthropogenic sources. The observed maxima in PM10 concentration during dust events is evidence of dust aerosol near the surface in Northern Italy. During all dust events under consideration, the integrated TCAM-DREAM model produced more accurate PM10 concentrations than the base TCAM model. Then, a comparison between modeled concentrations and PM10 measurements was carried out at 230 PM10 monitoring sites, distributed within the model domain. This model-vs.-measurement comparison showed that the integrated TCAM -DREAM model more accurately reproduced PM10 concentrations than the base TCAM model, both in term of correlation and mean error. Our results are of importance to countries which have to pay a penalty for exceeding the pollution limit. By extracting dust contribution from PM10 measurements, these countries could show lower rates of man-made pollution.

Daily trends and source apportionment of ultrafine particulate mass (PM0.1) over an annual cycle in a typical California city.

PubMed

Kuwayama, Toshihiro; Ruehl, Chris R; Kleeman, Michael J

2013-12-17

Toxicology studies indicate that inhalation of ultrafine particles (Dp < 0.1 μm) causes adverse health effects, presumably due to their large surface area-to-volume ratio that can drive heterogeneous reactions. Epidemiological associations between ultrafine particles and health effects, however, have been difficult to identify due to the lack of appropriate long-term monitoring and exposure data. The majority of the existing ultrafine particle epidemiology studies are based on exposure to particle number, although an independent analysis suggests that ultrafine particle mass (PM0.1) correlates better with particle surface area. More information is needed to characterize PM0.1 exposure to fully evaluate the health effects of ultrafine particles using epidemiology. The present study summarizes 1 year of daily PM0.1 chemistry and source apportionment at Sacramento, CA, USA. Positive matrix factorization (PMF) was used to resolve PM0.1 source contributions from old-technology diesel engines, residential wood burning, rail, regional traffic, and brake wear/road dust. Diesel PM0.1 and total PM0.1 concentrations were reduced by 97 and 26%, respectively, as a result of the adoption of cleaner diesel technology. The strong linear correlation between PM0.1 and particle surface area in central California suggests that the adoption of clean diesel engines reduced particle surface area by similar amounts. PM0.1 sulfate reduction occurred as a result of reduced primary particle surface area available for sulfate condensation. The current study demonstrates the capability of measuring PM0.1 source contributions over a 12 month period and identifies the extended benefits of emissions reduction efforts for diesel engines on ambient concentrations of primary and secondary PM0.1.

Spatial analysis of MODIS aerosol optical depth, PM2.5, and chronic coronary heart disease.

PubMed

Hu, Zhiyong

2009-05-12

Numerous studies have found adverse health effects of acute and chronic exposure to fine particulate matter (PM2.5). Air pollution epidemiological studies relying on ground measurements provided by monitoring networks are often limited by sparse and unbalanced spatial distribution of the monitors. Studies have found correlations between satellite aerosol optical depth (AOD) and PM2.5 in some land regions. Satellite aerosol data may be used to extend the spatial coverage of PM2.5 exposure assessment. This study was to investigate correlation between PM2.5 and AOD in the conterminous USA, to derive a spatially complete PM2.5 surface by merging satellite AOD data and ground measurements based on the potential correlation, and to examine if there is an association of coronary heart disease with PM2.5. Years 2003 and 2004 daily MODIS (Moderate Resolution Imaging Spectrometer) Level 2 AOD images were collated with US EPA PM2.5 data covering the conterminous USA. Pearson's correlation analysis and geographically weighted regression (GWR) found that the relationship between PM2.5 and AOD is not spatially consistent across the conterminous states. The average correlation is 0.67 in the east and 0.22 in the west. GWR predicts well in the east and poorly in the west. The GWR model was used to derive a PM2.5 grid surface using the mean AOD raster calculated using the daily AOD data (RMSE = 1.67 microg/m3). Fitting of a Bayesian hierarchical model linking PM2.5 with age-race standardized mortality rates (SMRs) of chronic coronary heart disease found that areas with higher values of PM2.5 also show high rates of CCHD mortality: = 0.802, posterior 95% Bayesian credible interval (CI) = (0.386, 1.225). There is a spatial variation of the relationship between PM2.5 and AOD in the conterminous USA. In the eastern USA where AOD correlates well with PM2.5, AOD can be merged with ground PM2.5 data to derive a PM2.5 surface for epidemiological study. The study found that chronic coronary heart disease mortality rate increases with exposure to PM2.5.

Saharan dust contribution to PM levels: The EC LIFE+ DIAPASON project

NASA Astrophysics Data System (ADS)

Gobbi, G. P.; Wille, H.; Sozzi, R.; Angelini, F.; Barnaba, F.; Costabile, F.; Frey, S.; Bolignano, A.; Di Giosa, A.

2012-04-01

The contribution of Saharan-dust advections to both daily and annual PM average values can be significant all over Southern Europe. The most important effects of dust on the number of PM exceedances are mostly observed in polluted areas and large cities. While a wide literature exists documenting episodes of Saharan dust transport towards the Euro-Mediterranean region and Europe in general, a limited number of studies are still available providing statistically significant results on the impact of Saharan dust on the particulate matter loads over the continent. A four-year (2001-2004) study performed in Rome (Italy) found these events to contribute to the average ground PM10 with about 15±10 µg/m3 on about 17% of the days in a year. Since the PM10 yearly average of many traffic stations in Rome is close to 40 μg/m3, these events can cause the PM10 concentration to exceed air quality limit values (50 μg/m3 as daily average) set by the EU Air Quality Directive 2008/50/EC. Although the European legislation allows Member States to subtract the contribution of natural sources before counting PM10 exceedances, definition of an optimal methodology to quantitatively assess such contribution is still in progress. On the basis of the current European Guidelines on the assessment of natural contributions to PM, the DIAPASON project ("Desert-dust Impact on Air quality through model-Predictions and Advanced Sensors ObservatioNs", recently funded under the EC LIFE+ program) has been formulated to provide a robust, user-oriented methodology to assess the presence of desert dust and its contribution to PM levels. To this end, in addition to satellite-based data and model forecasts, the DIAPASON methodology will employ innovative and affordable technologies, partly prototyped within the project itself, as an operational Polarization Lidar-Ceilometer (laser radar) capable of detecting and profiling dust clouds from the ground up to 10 km altitude. The DIAPASON Project (2011-2014) will be first implemented as a network of three stations in the Rome metropolitan area. However, the DIAPASON methodology to detect/quantify the Saharan dust contribution to PM will be designed to be easily applicable by air-quality and meteorological agencies. In fact, the possibility of manufacturing cheap, operational polarization lidar-ceilometers and scatter them on the territory will also represent a breakthrough in the detection and quantification of other atmospheric aerosol layers, as volcanic or wild-fire plumes, with further benefits in terms of meteo forecasts, flight security and air quality assessments.

Source Contributions of Urban PM2.5 in the Beijing-Tianjin-Hebei Region: Changes between 2006 and 2013 and Relative Impacts of Emissions and Meteorology

NASA Astrophysics Data System (ADS)

Li, X.; Zhang, Q.; Zhang, Y.; Zheng, B.; Li, M.; Wang, K.; Chen, Y.; Wallington, T. J.; Han, W.; Shen, W.; Zhang, X.; He, K.

2015-12-01

Anthropogenic emissions in China have been controlled for years to improve ambient air quality. However, severe haze events caused by atmospheric aerosols with aerodynamic diameter less than or equal to 2.5 μm (PM2.5) have continued to occur, especially in the Beijing-Tianjin-Hebei (BTH) region. The Chinese government has set an ambitious goal to reduce urban PM2.5 concentrations by 25% in BTH by 2017 relative to the 2012 levels. Source apportionment (SA) is necessary to the development of the effective emission control strategies. In this work, the Comprehensive Air Quality Model with extensions (CAMx) with the Particulate Source Apportionment Technology (PSAT) is applied to the China domain for the years 2006 and 2013. Ambient surface concentrations of PM2.5 and its components are generally well reproduced. To quantify the contributions of each emission category or region to PM2.5 in BTH, the total emissions are divided into 7 emission categories and 11 source regions. The source contributions determined in this work are generally consistent with results from previous work. In 2013, the industrial (44%) and residential (27%) sectors are the dominant contributors to urban PM2.5 in BTH. The residential sector is the largest contributor in winter; the industry sector dominates in other seasons. A slight increasing trend (+3% for industry and +6% for residential) is found in 2013 relative to 2006, necessitating more attention to these two sectors. Local emissions make the largest contribution (40%-60%) for all receptors. Change of source contribution of PM2.5 in Beijing and northern Hebei are dominate by change of local emission. However, for Tianjin, and central and southern Hebei, change of meteorology condition are as important as change of emission, because regional inflow in these areas is more important than in Beijing and northern Hebei and can increase under unfavorable weather conditions, indicating a strong need for regional joint emission control efforts. The results in this study enhance the quantitative understanding of the source-receptor relationships and provide an important basis for policymaking to advance the control of PM2.5 pollution in China. Both sector-based and fuel-based source apportionment will be available to further improve the comparability with receptor model results.

Estimating daily PM2.5 and PM10 across the complex geo-climate region of Israel using MAIAC satellite-based AOD data.

PubMed

Kloog, Itai; Sorek-Hamer, Meytar; Lyapustin, Alexei; Coull, Brent; Wang, Yujie; Just, Allan C; Schwartz, Joel; Broday, David M

2015-12-01

Estimates of exposure to PM 2.5 are often derived from geographic characteristics based on land-use regression or from a limited number of fixed ground monitors. Remote sensing advances have integrated these approaches with satellite-based measures of aerosol optical depth (AOD), which is spatially and temporally resolved, allowing greater coverage for PM 2.5 estimations. Israel is situated in a complex geo-climatic region with contrasting geographic and weather patterns, including both dark and bright surfaces within a relatively small area. Our goal was to examine the use of MODIS-based MAIAC data in Israel, and to explore the reliability of predicted PM 2.5 and PM 10 at a high spatiotemporal resolution. We applied a three stage process, including a daily calibration method based on a mixed effects model, to predict ground PM 2.5 and PM 10 over Israel. We later constructed daily predictions across Israel for 2003-2013 using spatial and temporal smoothing, to estimate AOD when satellite data were missing. Good model performance was achieved, with out-of-sample cross validation R 2 values of 0.79 and 0.72 for PM 10 and PM 2.5 , respectively. Model predictions had little bias, with cross-validated slopes (predicted vs. observed) of 0.99 for both the PM 2.5 and PM 10 models. To our knowledge, this is the first study that utilizes high resolution 1km MAIAC AOD retrievals for PM prediction while accounting for geo-climate complexities, such as experienced in Israel. This novel model allowed the reconstruction of long- and short-term spatially resolved exposure to PM 2.5 and PM 10 in Israel, which could be used in the future for epidemiological studies.

Estimating daily PM2.5 and PM10 across the complex geo-climate region of Israel using MAIAC satellite-based AOD data

PubMed Central

Kloog, Itai; Sorek-Hamer, Meytar; Lyapustin, Alexei; Coull, Brent; Wang, Yujie; Just, Allan C.; Schwartz, Joel; Broday, David M.

2017-01-01

Estimates of exposure to PM2.5 are often derived from geographic characteristics based on land-use regression or from a limited number of fixed ground monitors. Remote sensing advances have integrated these approaches with satellite-based measures of aerosol optical depth (AOD), which is spatially and temporally resolved, allowing greater coverage for PM2.5 estimations. Israel is situated in a complex geo-climatic region with contrasting geographic and weather patterns, including both dark and bright surfaces within a relatively small area. Our goal was to examine the use of MODIS-based MAIAC data in Israel, and to explore the reliability of predicted PM2.5 and PM10 at a high spatiotemporal resolution. We applied a three stage process, including a daily calibration method based on a mixed effects model, to predict ground PM2.5 and PM10 over Israel. We later constructed daily predictions across Israel for 2003–2013 using spatial and temporal smoothing, to estimate AOD when satellite data were missing. Good model performance was achieved, with out-of-sample cross validation R2 values of 0.79 and 0.72 for PM10 and PM2.5, respectively. Model predictions had little bias, with cross-validated slopes (predicted vs. observed) of 0.99 for both the PM2.5 and PM10 models. To our knowledge, this is the first study that utilizes high resolution 1km MAIAC AOD retrievals for PM prediction while accounting for geo-climate complexities, such as experienced in Israel. This novel model allowed the reconstruction of long- and short-term spatially resolved exposure to PM2.5 and PM10 in Israel, which could be used in the future for epidemiological studies. PMID:28966551

The harmonic development of the Earth tide generating potential due to the direct effect of the planets

NASA Astrophysics Data System (ADS)

Hartmann, Torsten; Wenzel, Hans-Georg

1994-09-01

The time-harmonic development of the Earth tide generating potential due to the direct effect of the planets Venus, Jupiter, Mars, Mercury and Saturn has been computed. The catalog of the fully normalized potential coefficients contains 1483 waves. It is based on the DE102 numerical ephemeris of the planets between years 1900 and 2200. Gravity tides due to the planets computed from the catalog at the surface of the Earth have an accuracy of about 0.027 pm/sq s (1 pm/sq s = 10(exp -12) m/sq s = 0.1 ngal) rms and 0.160 / 0.008 pm/sq s at maximum in time / frequency domain using the new benchmark tidal gravity series (Wenzel 1994).

The National Shipbuilding Research Program. Short Course on Implementing Advanced Technology. Course Notes

DTIC Science & Technology

1996-01-01

12.30PM LUNCH 12.30-1.00 PM EXERCISE - U.S. VERSUS FOREIGN COST BREAKDOWN 1.00-1.30 PM THE CANDY STORE - TOTAL QUALITY MANAGEMENT 1.30-2000 PM SEAMLESS...AVONDALE’S RUSSIAN TANKER, AND BENDER’S REEFER SHIP PROJECTS ALL APPEAR DEAD OTHER U.S. SHIPBUILDERS ARE STILL IN NEGOTIATION WITH POTENTIAL FOREIGN AND...derived: Direct ManhourdCGT Total Employee Manhours/CGT CGT/ Direct worker Year CGT/Total Employee Year 2 3 NATIONAL RESEARCH COUNCIL DESIGN AND

Statistical Analysis of SSMIS Sea Ice Concentration Threshold at the Arctic Sea Ice Edge during Summer Based on MODIS and Ship-Based Observational Data.

PubMed

Ji, Qing; Li, Fei; Pang, Xiaoping; Luo, Cong

2018-04-05

The threshold of sea ice concentration (SIC) is the basis for accurately calculating sea ice extent based on passive microwave (PM) remote sensing data. However, the PM SIC threshold at the sea ice edge used in previous studies and released sea ice products has not always been consistent. To explore the representable value of the PM SIC threshold corresponding on average to the position of the Arctic sea ice edge during summer in recent years, we extracted sea ice edge boundaries from the Moderate-resolution Imaging Spectroradiometer (MODIS) sea ice product (MOD29 with a spatial resolution of 1 km), MODIS images (250 m), and sea ice ship-based observation points (1 km) during the fifth (CHINARE-2012) and sixth (CHINARE-2014) Chinese National Arctic Research Expeditions, and made an overlay and comparison analysis with PM SIC derived from Special Sensor Microwave Imager Sounder (SSMIS, with a spatial resolution of 25 km) in the summer of 2012 and 2014. Results showed that the average SSMIS SIC threshold at the Arctic sea ice edge based on ice-water boundary lines extracted from MOD29 was 33%, which was higher than that of the commonly used 15% discriminant threshold. The average SIC threshold at sea ice edge based on ice-water boundary lines extracted by visual interpretation from four scenes of the MODIS image was 35% when compared to the average value of 36% from the MOD29 extracted ice edge pixels for the same days. The average SIC of 31% at the sea ice edge points extracted from ship-based observations also confirmed that choosing around 30% as the SIC threshold during summer is recommended for sea ice extent calculations based on SSMIS PM data. These results can provide a reference for further studying the variation of sea ice under the rapidly changing Arctic.

Development and validation of a novel algorithm based on the ECG magnet response for rapid identification of any unknown pacemaker.

PubMed

Squara, Fabien; Chik, William W; Benhayon, Daniel; Maeda, Shingo; Latcu, Decebal Gabriel; Lacaze-Gadonneix, Jonathan; Tibi, Thierry; Thomas, Olivier; Cooper, Joshua M; Duthoit, Guillaume

2014-08-01

Pacemaker (PM) interrogation requires correct manufacturer identification. However, an unidentified PM is a frequent occurrence, requiring time-consuming steps to identify the device. The purpose of this study was to develop and validate a novel algorithm for PM manufacturer identification, using the ECG response to magnet application. Data on the magnet responses of all recent PM models (≤15 years) from the 5 major manufacturers were collected. An algorithm based on the ECG response to magnet application to identify the PM manufacturer was subsequently developed. Patients undergoing ECG during magnet application in various clinical situations were prospectively recruited in 7 centers. The algorithm was applied in the analysis of every ECG by a cardiologist blinded to PM information. A second blinded cardiologist analyzed a sample of randomly selected ECGs in order to assess the reproducibility of the results. A total of 250 ECGs were analyzed during magnet application. The algorithm led to the correct single manufacturer choice in 242 ECGs (96.8%), whereas 7 (2.8%) could only be narrowed to either 1 of 2 manufacturer possibilities. Only 2 (0.4%) incorrect manufacturer identifications occurred. The algorithm identified Medtronic and Sorin Group PMs with 100% sensitivity and specificity, Biotronik PMs with 100% sensitivity and 99.5% specificity, and St. Jude and Boston Scientific PMs with 92% sensitivity and 100% specificity. The results were reproducible between the 2 blinded cardiologists with 92% concordant findings. Unknown PM manufacturers can be accurately identified by analyzing the ECG magnet response using this newly developed algorithm. Copyright © 2014 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Artificial intelligence based approach to forecast PM2.5 during haze episodes: A case study of Delhi, India

NASA Astrophysics Data System (ADS)

Mishra, Dhirendra; Goyal, P.; Upadhyay, Abhishek

2015-02-01

Delhi has been listed as the worst performer across the world with respect to the presence of alarmingly high level of haze episodes, exposing the residents here to a host of diseases including respiratory disease, chronic obstructive pulmonary disorder and lung cancer. This study aimed to analyze the haze episodes in a year and to develop the forecasting methodologies for it. The air pollutants, e.g., CO, O3, NO2, SO2, PM2.5 as well as meteorological parameters (pressure, temperature, wind speed, wind direction index, relative humidity, visibility, dew point temperature, etc.) have been used in the present study to analyze the haze episodes in Delhi urban area. The nature of these episodes, their possible causes, and their major features are discussed in terms of fine particulate matter (PM2.5) and relative humidity. The correlation matrix shows that temperature, pressure, wind speed, O3, and dew point temperature are the dominating variables for PM2.5 concentrations in Delhi. The hour-by-hour analysis of past data pattern at different monitoring stations suggest that the haze hours were occurred approximately 48% of the total observed hours in the year, 2012 over Delhi urban area. The haze hour forecasting models in terms of PM2.5 concentrations (more than 50 μg/m3) and relative humidity (less than 90%) have been developed through artificial intelligence based Neuro-Fuzzy (NF) techniques and compared with the other modeling techniques e.g., multiple linear regression (MLR), and artificial neural network (ANN). The haze hour's data for nine months, i.e. from January to September have been chosen for training and remaining three months, i.e., October to December in the year 2012 are chosen for validation of the developed models. The forecasted results are compared with the observed values with different statistical measures, e.g., correlation coefficients (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA). The performed analysis has indicated that R has values 0.25 for MLR, 0.53 for ANN, and NF: 0.72, between the observed and predicted PM2.5 concentrations during haze hours invalidation period. The results show that the artificial intelligence implementations have a more reasonable agreement with the observed values. Finally, it can be concluded that the most convincing advantage of artificial intelligence based NF model is capable for better forecasting of haze episodes in Delhi urban area than ANN and MLR models.

Impact of a Revised Curriculum Focusing on Clinical Neurology and Musculoskeletal Care on a Required Fourth-Year Medical Student Physical Medicine and Rehabilitation Clerkship

PubMed Central

Faulk, Clinton E.; Harrell, Kelly M.; Lawson, Luan E.; Moore, Daniel P.

2016-01-01

Background. A Required Fourth-Year Medical Student Physical Medicine and Rehabilitation (PM&R) Clerkship was found to increase students' knowledge of PM&R; however the students' overall rotation evaluations were consistently lower than the other 8 required clerkships at the medical school. Objective. To describe the impact of a revised curriculum based upon Entrustable Professional Activities and focusing on basic pain management, musculoskeletal care, and neurology. Setting. Academic Medical Center. Participants. 73 fourth-year medical students. Methods. The curriculum changes included a shift in the required readings from rehabilitation specific topics toward more general content in the areas of clinical neurology and musculoskeletal care. Hands-on workshops on neurological and musculoskeletal physical examination techniques, small group case-based learning, an anatomy clinical correlation lecture, and a lecture on pain management were integrated into the curriculum. Main Outcome Measurements. Student evaluations of the clerkship. Results. Statistically significant improvements were found in the students' evaluations of usefulness of lecturers, development of patient interviewing skills, and diagnostic and patient management skills (p ≤ 0.05). Conclusions. This study suggests that students have a greater satisfaction with a required PM&R clerkship when lecturers utilize a variety of pedagogic methods to teach basic pain, neurology and musculoskeletal care skills in the rehabilitation setting rather than rehabilitation specific content. PMID:28025624

Impact of a Revised Curriculum Focusing on Clinical Neurology and Musculoskeletal Care on a Required Fourth-Year Medical Student Physical Medicine and Rehabilitation Clerkship.

PubMed

Norbury, John W; Faulk, Clinton E; Harrell, Kelly M; Lawson, Luan E; Moore, Daniel P

2016-01-01

Background . A Required Fourth-Year Medical Student Physical Medicine and Rehabilitation (PM&R) Clerkship was found to increase students' knowledge of PM&R; however the students' overall rotation evaluations were consistently lower than the other 8 required clerkships at the medical school. Objective . To describe the impact of a revised curriculum based upon Entrustable Professional Activities and focusing on basic pain management, musculoskeletal care, and neurology. Setting . Academic Medical Center. Participants . 73 fourth-year medical students. Methods . The curriculum changes included a shift in the required readings from rehabilitation specific topics toward more general content in the areas of clinical neurology and musculoskeletal care. Hands-on workshops on neurological and musculoskeletal physical examination techniques, small group case-based learning, an anatomy clinical correlation lecture, and a lecture on pain management were integrated into the curriculum. Main Outcome Measurements . Student evaluations of the clerkship. Results . Statistically significant improvements were found in the students' evaluations of usefulness of lecturers, development of patient interviewing skills, and diagnostic and patient management skills ( p ≤ 0.05). Conclusions . This study suggests that students have a greater satisfaction with a required PM&R clerkship when lecturers utilize a variety of pedagogic methods to teach basic pain, neurology and musculoskeletal care skills in the rehabilitation setting rather than rehabilitation specific content.

Functional specification of the Performance Measurement (PM) module

NASA Technical Reports Server (NTRS)

Berliner, J. E.

1980-01-01

The design of the Performance Measurement Module is described with emphasis on what the PM Module would do, and what it would look like to the user. The PM Module as described could take several man-years to develop. An evolutionary approach to the implementation of the PM Module is presented which would provide an operational baseline PM Module within a few months.

Executive Functioning and Prospective Memory in Young Children

ERIC Educational Resources Information Center

Mahy, Caitlin E. V.; Moses, Louis J.

2011-01-01

The current study examined the role of executive functioning (EF) in children's prospective memory (PM) by assessing the effect of delay and number of intentions to-be-remembered on PM, as well as relations between PM and EF. Ninety-six 4-, 5-, and 6-year-olds completed a PM task and two executive function tasks. The PM task required children to…

Refined Assessment of Human PM2.5 Exposure in Chinese city by Incorporating Time-activity Data

NASA Astrophysics Data System (ADS)

Zhu, W.; Wang, H.

2015-12-01

Since urban residents tend to spend a majority of time indoors throughout a day, it has been widely discussed in recent years, whether fixed-site monitoring PM2.5 ambient concentration is feasible as a surrogate of human PM2.5 exposure. Comprehensive understanding of residents' daily time-activity patterns (TAP) and possible indoor behavior are urgently needed to perform a more accurate estimate of human PM2.5exposure, especially in China, where is experiencing rapid urbanization.Field surveys of TAP were carried out in a Chinese city of Suzhou from 2014 to 2015 to evaluate PM2.5 exposure in various micro-environments (ME, e.g., residence, outdoors and in-transit). We gathered and analyzed urban residents' seasonal time-activity data using 24h retrospective time-location diaries, as well as diversified exposure-related indoor information (e.g. ventilation, environment tobacco smoke and cooking). PM2.5exposure is calculated through the incorporation of ambient concentration data, modified indoor/outdoor empirical functions and TAP. The spatial distributions of TAP-based exposure and static-population based exposure are also compared.Residents in Suzhou urban area spend over 65% of time at home and 90% indoors. There are significant temporal (season, day type) and socioeconomic differences (gender, age, education, living alone, having children at home, employment status, etc.) of time-activity distributions, which makes the sum of PM2.5 ME exposure differs notably from static-population based ambient exposure. People prefer to spend more time at home both in winter (P<0.05) and on weekends (P<0.001), less time outdoors in winter but more on weekends (P<0.001). Gender, education and living alone are negative associated with time spent home, while age, children at home and employment status are positively related. On the other hand, due to lack of monitoring stations in unban Suzhou, the inverse distance squared weighting method is not ideally performed and may be less representative of the ambient PM2.5characteristics than satellite data.

Long term PM2.5 estimation and its impact on human health in Beijing, China

NASA Astrophysics Data System (ADS)

Zheng, Sheng; Pozzer, Andrea; Cao, Chunxiang

2014-05-01

Due to the economic growth and urbanization, the emissions of pollutants have increased significantly in the North China Plain (NCP). Beijing, the capital of China, is located at the northern tip of NCP, and it is considered one of the most densely populated cities with the poorest air quality. This is of major concerns, because of the impact of high pollutants concentration on human health. The present study analyses the characteristics of AOD and the particulate matter with diameter < 2.5 μm (PM2.5) and its impact on human health in the central Beijing areas. We acquire AOD from Aerosol Robotic Network (AERONET) in Beijing from 2001 to 2012. The AOD data are fitted with a lognormal distribution, and the 95% of the cumulative probability is used as the threshold for episodes of high AOD. Most episodes occur in summer, mostly in June, though this is combined with high precipitation. Episodes of high AOD caused by coarse pollutants occur only in March and April, and they are mostly caused by dust from the north. According to wind direction, wind speed, boundary layer height (BLH) and pollutant emission distribution, episodes of high AOD are due to the anthropogenic pollutants from the south (Hebei province). Based on ground PM2.5 observation from the US embassy in Beijing from 2010 to 2011, we establish a relationship between PM2.5and AERONET AOD, including BLH and relative humidity (RH) correction. Thanks to this method, 12 years of PM2.5 are estimated for the Beijing central area, allowing the estimation of long term concentrations of this pollutant. Since there is no obvious difference among the daily PM2.5 of six stations lying in Chaoyang, Dongcheng, and Xicheng district, we use the daily PM2.5 from US embassy station to represent the PM2.5 concentration in these three districts, and calculate yearly premature mortality due to long term exposure to PM2.5among the population with an age of ≥ 30 yr in these three districts.

Population-based incidence, treatment and survival of patients with peritoneal metastases of unknown origin.

PubMed

Thomassen, Irene; Verhoeven, Rob H A; van Gestel, Yvette R B M; van de Wouw, Agnes J; Lemmens, Valery E P P; de Hingh, Ignace H J T

2014-01-01

Until recently, peritoneal metastases (PM) were regarded as an untreatable condition, regardless of the organ of origin. Currently, promising treatment options are available for selected patients with PM from colorectal, appendiceal, ovarian or gastric carcinoma. The aim of this study was to investigate the incidence, treatment and survival of patients presenting with PM in whom the origin of PM remains unknown. Data from patients diagnosed with PM of unknown origin during 1984-2010 were extracted from the Eindhoven Cancer Registry. European age-standardised incidence rates were calculated and data on treatment and survival were analysed. In total 1051 patients were diagnosed with PM of unknown origin. In 606 patients (58%) the peritoneum was the only site of metastasis, and 445 patients also had other metastases. Chemotherapy usage has increased from 8% in the earliest period to 16% in most recent years (p=.016). Median survival was extremely poor with only 42days (95% confidence interval (CI) 39-47days) and did not change over time. Median survival of patients not receiving chemotherapy was significantly worse than of those receiving chemotherapy (36 versus 218days, p<.0001). The prognosis of PM of unknown origin is extremely poor and did not improve over time. Given the recent progress that has been achieved in selected patients presenting with PM, maximum efforts should be undertaken in order to diagnose the origin of PM as accurately as possible. Potentially effective treatment strategies should be further explored for patients in whom the organ of origin remains unknown. Copyright © 2013 Elsevier Ltd. All rights reserved.

Primary mediastinal and retroperitoneal malignant germ cell tumors in children and adolescents: Results of the TGM95 trial, a study of the French Society of Pediatric Oncology (Société Française des Cancers de l'Enfant).

PubMed

Sudour-Bonnange, Hélène; Faure-Conter, Cécile; Martelli, Hélène; Hameury, Frederic; Fresneau, Brice; Orbach, Daniel; Vérité, Cécile

2017-09-01

To examine the clinical presentation, treatment and results in children and adolescents with primary mediastinal (PM) and retroperitoneal (RP) germ cell tumors (GCTs). The TGM95 trial for malignant GCTs was conducted in France between 1995 and 2005 to evaluate a strategy adapted to prognostic factors with cisplatin-based chemotherapy and surgical management. We reviewed patients with TGCTs at PM and RP sites. Among 239 patients, there were 16 patients with PM and 5 with RP tumors, which represent 9% of all patients, highlighting the rarity of these extragonadal locations. A bimodal demographic distribution was observed (11/21 patients <5 years old and 7/21 patients >12 years old). A majority of patients presented with bulky tumors that required urgent care with neoadjuvant chemotherapy. In all patients, elevation of alpha-fetoprotein indicated a yolk sac tumor component. Human chorionic gonadotrophin was elevated in five patients (four adolescents), suggesting a choriocarcinoma or seminoma component. The diagnosis was based on elevation of these tumor markers in addition to imaging. Chemosensitivity was observed for a majority of patients. An aggressive surgical approach allowed a microscopic complete resection in 12/15 patients with PM tumors and 4/5 with RP tumors. Overall, 14/16 and 4/5 patients survived, respectively. Three adolescents died of tumor progression. In children with mediastinal or RP GCTs, the prognosis is favorable when a strategy of delayed aggressive surgery is performed after cisplatin-based chemotherapy. Younger patients have a better prognosis. Relapses were observed only in adolescents and could not be cured. © 2017 Wiley Periodicals, Inc.

Estimating particle speciation concentrations using MISR retrieved aerosol properties in southern California

NASA Astrophysics Data System (ADS)

Meng, X.; Liu, Y.; Diner, D. J.; Garay, M. J.

2016-12-01

Ambient fine particle (PM2.5) has been positively associated with increased mortality and morbidity worldwide. Recent studies highlight the characteristics and differential toxicity of PM2.5 chemical components, which are important for identifying sources, developing targeted particulate matter (PM) control strategies, and protecting public health. Modelling with satellite retrieved data has been proved as the most cost-effective way to estimate ground PM2.5 levels; however, limited studies have predict PM2.5 chemical components with this method. In this study, the experimental MISR 4.4 km aerosol retrievals were used to predict ground-level particle sulfate, nitrite, organic carbon and element carbon concentrations in 16 counties of southern California. The PM2.5 chemical components concentrations were obtained from the National Chemical Speciation Network (CSN) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) network. A generalized additive model (GAM) was developed based on 16-years data (2000-2015) by combining the MISR aerosol retrievals, meteorological variables and geographical indicators together. Model performance was assessed by model fitted R2 and root-mean-square error (RMSE) and 10-fold cross validation. Spatial patterns of sulfate, nitrate, OC and EC concentrations were also examined with 2-D prediction surfaces. This is the first attempt to develop high-resolution spatial models to predict PM2.5 chemical component concentrations with MISR retrieved aerosol properties, which will provide valuable population exposure estimates for future studies on the characteristics and differential toxicity of PM2.5 speciation.

Internalizing versus Externalizing Control: Different Ways to Perform a Time-Based Prospective Memory Task

ERIC Educational Resources Information Center

Huang, Tracy; Loft, Shayne; Humphreys, Michael S.

2014-01-01

"Time-based prospective memory" (PM) refers to performing intended actions at a future time. Participants with time-based PM tasks can be slower to perform ongoing tasks (costs) than participants without PM tasks because internal control is required to maintain the PM intention or to make prospective-timing estimates. However, external…

Influence of Climate on PM2.5 Concentrations over Europe : a Meteorological Analysis using a 9-year Model Simulation

NASA Astrophysics Data System (ADS)

Lecoeur, À.; Seigneur, C.; Terray, L.; Pagé, C.

2012-04-01

In the early 1970s, it has been demonstrated that a large number of deaths and health problems are associated with particulate pollution. As a consequence, several governments have set health-based air quality standards to protect public health. Particulate matter with an aerodynamical diameter of 2.5 μg.m-3 or less (PM2.5) is particularly concerned by these measures. As PM2.5 concentrations are strongly dependent on meteorological conditions, it is important to investigate the relationships between PM2.5 and meteorological parameters. This will help to understand the processes at play and anticipate the effects of climate change on PM2.5 air quality. Most of the previous work agree that temperature, wind speed, humidity, rain rate and mixing height are the meteorological variables that impact PM2.5 concentrations the most. A large number of those studies used Global Circulation Models (GCM) and Chemical Transport Models (CTM) and focus on the USA. They typically predict a diminution of PM2.5 concentrations in the future, with some geographical and/or temporal discrepancies, when only the climate evolution is considered. When considering changes in emissions along with climate, no consensus has yet been found. Furthermore, the correlations between PM2.5 concentrations and meteorological variables are often low, which prevents a straightforward analysis of their relationships. In this work, we consider that PM2.5 concentrations depend on both large-scale atmospheric circulation and local meteorological variables. We thus investigate the influence of present climate on PM2.5 concentrations over Europe by representing it using a weather regimes/types approach. We start by exploring the relationships between classical weather regimes, meteorological variables and PM2.5 concentrations over five stations in Europe, using the EMEP air quality database. The pressure at sea level is used in the classification as it effectively describes the atmospheric circulation. We experimentally verify some intuitive results: weather regimes associated with weak (resp. high) precipitation, wind and low (resp. high) temperatures correspond to higher (resp. lower) PM2.5 concentrations. We also observe that rain rate is the variable that impacts PM2.5 concentrations the most. Next, we search for better relationships by adding this second variable to the classification: we therefore build new weather regimes, called weather types. Because of the low number of the EMEP observations, we compute PM2.5 concentrations with the Polyphemus/Polair3D CTM for years between 2000 and 2008 in order to obtain a spatially and temporally complete dataset of PM2.5 concentrations and chemical components, which can be used to relate PM2.5 concentrations to meteorological regimes and specific variables. By classifying both a large-scale variable and a local variable that influence the PM2.5 concentrations and using gridded data of the modeled concentrations of PM2.5, we obtain a more robust analysis. The results of this work will provide the basis to predict the effects of climate change (via the evolution of weather regimes/types frequencies) on PM2.5 chemical composition and concentrations.

Regional background aerosols over the Balearic Islands over the last 3 years: ground-based concentrations, atmospheric deposition and sources

NASA Astrophysics Data System (ADS)

Cerro, Jose Carlos; Pey, Jorge; Bujosa, Carles; Caballero, Sandra; Alastuey, Andres; Sicard, Michael; Artiñano, Begoña; Querol, Xavier

2013-04-01

In the context of the ChArMEx (The Chemistry-Aerosol Mediterranean Experiment, https://charmex.lsce.ipsl.fr) initiative, a 3-year study over a regional background environment (Can Llompart, CLP) in Mallorca has been conducted. Ground-based PM mass concentrations, gaseous pollutants and meteorological parameters were continuously registered from 2010 to 2012. Since the beginning of the campaign, PM10 daily samples for chemical determinations were obtained every 4 days, and dry and wet deposition samples were collected every week. Moreover, additional instruments (condensation particle counter, multi-angle absorption photometer, airpointer, sequential high and low volume samplers) were deployed during intensive filed campaigns in 2011 and 2012, as well as the sampling frequency was intensified. In the laboratory, PM samples were analyzed for inorganic compounds, and organic and elemental carbon following different approaches. In addition, n-alkanes, iso-alkanes, antiso-alkanes, levoglucosan, alkanoic acids and cholesterol were determined by GC-MS chromatography in a selection of 30 samples. Mean PM10, PM2.5 and PM1 concentrations in the period 2010-2012 reached 17, 11, and 8 µg/m3 respectively. Mass concentrations displayed marked seasonal trends, with much higher background levels in summer due to stagnant conditions over the western Mediterranean and increased frequency of Saharan dust events. Likewise, diverse-intensity peaks of coarse PM due to African dust inputs were observed along the year. On average, African dust in PM10 accounted for 1.0-1.5 µg/m3. Sporadic pollution events, characterized by most of the particles in the fine mode, were related to the transport of anthropogenic polluted air masses from central and eastern Europe. Wet and dry atmospheric deposition samples are being analyzed to quantify the deposition fluxes for different soluble and insoluble compounds. On average, PM10 composition is made up of organic matter (23%), mineral components (17%), sulphate (14%), sea spray (10%), nitrate (7%), NH4 (7%) and elemental carbon (1%), with 21% of the mass unexplained (though as being principally water). Intensive sampling campaigns were positive to assess the concentrations of black carbon and number of ultrafine particles and their time-variability. Accordingly, black carbon followed a similar pattern to that of PM1 but also displayed fresh anthropogenic inputs from road traffic. Number concentration peaked frequently at midday because of new-formation of particles from photochemical reactions, occasionally at hourly values above 100.000 particles per cm3. A preliminary source exploration by means of Principal Component Analysis has been done with the 30-samples group characterized more in detail in terms of chemical determinations. This first examination encountered 6 sources: mineral, sea spray, biomass burning, regional pollution, industry and biogenic emissions. Acknowledgements This work was supported by the Spanish Ministry of Science and Innovation and FEDER funds (CGL2011-13580-E/CLI). ENDESA, through AMBILINE, has been taking care of the instruments most of the time, has provided all the necessary support for the campaign, and has provided data on gaseous pollutants and meteorological parameters.

Prospective memory impairments in heavy social drinkers are partially overcome by future event simulation.

PubMed

Platt, Bradley; Kamboj, Sunjeev K; Italiano, Tommaso; Rendell, Peter G; Curran, H Valerie

2016-02-01

Recent research suggests that alcohol acutely impairs prospective memory (PM), and this impairment can be overcome using a strategy called 'future event simulation' (FES). Impairment in event-based PM found in detoxifying alcohol-dependent participants is reversed through FES. However, the impact of the most common problematic drinking patterns that do not involve alcohol dependence on PM remains unclear. Here, we examine the impact of frequent heavy drinking on PM and the degree to which any impairments can be reversed through FES. PM was assessed in 19 heavy drinkers (AUDIT scores ≥ 15) and 18 matched control participants (AUDIT scores ≤ 7) using the 'Virtual Week' task both at baseline and again following FES. Heavy drinkers performed significantly worse than controls on regular and irregular time-based PM tasks. FES improved the performance of controls but not of heavy drinkers on time-based tasks. In contrast, FES improved heavy drinkers' performance on event-based PM tasks. These findings suggest that heavy drinkers experience deficits in strategic monitoring processing associated with time-based PM tasks which do not abate after FES. That the same strategy improves their event-based PM suggests that FES may be helpful for individuals with problematic drinking patterns in improving their prospective memory.

Analyzing 20 years of Black Carbon measurements in Germany

NASA Astrophysics Data System (ADS)

Kutzner, R. D.; Quedenau, J.; Kuik, F.; von Schneidemesser, E.; Schmale, J.

2016-12-01

Black Carbon (BC) is an important short-lived climate-forcing pollutant contributing to global warming through absorption of sunlight. In addition, BC, as a component of particulate matter (PM) exerts adverse health effects. Anthropogenic emission sources of BC include residential heating, transport, and agricultural fires, and the dominant natural emission source is wildfires. Despite the adverse effects of BC, legislation that requires mandatory monitoring of BC concentrations does not currently exist in the European Union (EU). Instead, BC is only indirectly monitored as component of PM10 and PM2.5 (PM with a diameter smaller 10 µm and 2.5 µm, respectively). Before the introduction of mandatory PM10 and PM2.5 monitoring in the EU in 2005 and 2015, respectively, `black smoke' (BS), a surrogate for BC, was a required measurement in Germany from the early 1990s. The annual mean limit value was 14 µg/m3 from 1995 and 8 µg/m³ from 1998. In 2004, many measurements were stopped, with the repeal of the regulations. In most German federal states a limited number BC monitoring stations continued to operate. We present a synthesis of BC data from 213 stations across Germany covering the period between 1994 and 2014. Due to the lack of a standardized method and respective legislation, the data set is very heterogeneous relying on twelve different measurement methods including chemical, optical, and thermal-optical methods. Stations include, among others, urban background, traffic and rural. We highlight results from the year 2009, as it is the year with the largest measurement coverage based on the same measurement method, with 28 stations. Further, we calculated trends in BC concentrations for 13 stations with at least 10 years of data, for median concentrations, as well as 5th percentile (background) and 95th percentile (peak episodes). Preliminary results suggest that concentrations have generally declined, with a larger trend at traffic stations compared to urban background stations between 2005 and 2014. However, preliminary results also show that concentrations are highest during the colder months, likely linked to residential heating.

Episode-Based Evolution Pattern Analysis of Haze Pollution: Method Development and Results from Beijing, China.

PubMed

Zheng, Guangjie; Duan, Fengkui; Ma, Yongliang; Zhang, Qiang; Huang, Tao; Kimoto, Takashi; Cheng, Yafang; Su, Hang; He, Kebin

2016-05-03

Haze episodes occurred in Beijing repeatedly in 2013, resulting in 189 polluted days. These episodes differed in terms of sources, formation processes, and chemical composition and thus required different control policies. Therefore, an overview of the similarities and differences among these episodes is needed. For this purpose, we conducted one-year online observations and developed a program that can simultaneously divide haze episodes and identify their shapes. A total of 73 episodes were identified, and their shapes were linked with synoptic conditions. Pure-haze events dominated in wintertime, whereas mixed haze-dust (PM2.5/PM10 < 60%) and mixed haze-fog (Aerosol Water/PM2.5 ∼ 0.3) events dominated in spring and summer-autumn, respectively. For all types, increase of ratio of PM2.5 in PM10 was typically achieved before PM2.5 reached ∼150 μg/m(3). In all PM2.5 species observed, organic matter (OM) was always the most abundant component (18-60%), but it was rarely the driving factor: its relative contribution usually decreased as the pollution level increased. The only OM-driven episode observed was associated with intensive biomass-burning activities. In comparison, haze evolution generally coincided with increasing sulfur and nitrogen oxidation ratios (SOR and NOR), indicating the enhanced production of secondary inorganic species. Applicability of these conclusions required further tests with simultaneously multisite observations.

Warmer is healthier: effects on mortality rates of changes in average fine particulate matter (PM2.5) concentrations and temperatures in 100 U.S. cities.

PubMed

Cox, Louis A; Popken, Douglas A; Ricci, Paolo F

2013-08-01

Recent studies have indicated that reducing particulate pollution would substantially reduce average daily mortality rates, prolonging lives, especially among the elderly (age ≥ 75). These benefits are projected by statistical models of significant positive associations between levels of fine particulate matter (PM2.5) levels and daily mortality rates. We examine the empirical correspondence between changes in average PM2.5 levels and temperatures from 1999 to 2000, and corresponding changes in average daily mortality rates, in each of 100 U.S. cities in the National Mortality and Morbidity Air Pollution Study (NMMAPS) data base, which has extensive PM2.5, temperature, and mortality data for those 2 years. Increases in average daily temperatures appear to significantly reduce average daily mortality rates, as expected from previous research. Unexpectedly, reductions in PM2.5 do not appear to cause any reductions in mortality rates. PM2.5 and mortality rates are both elevated on cold winter days, creating a significant positive statistical relation between their levels, but we find no evidence that reductions in PM2.5 concentrations cause reductions in mortality rates. For all concerned, it is crucial to use causal relations, rather than statistical associations, to project the changes in human health risks due to interventions such as reductions in particulate air pollution. Copyright © 2013 Elsevier Inc. All rights reserved.

Impact of a required fourth-year medical student rotation in physical medicine and rehabilitation.

PubMed

Faulk, Clinton E; Mali, Jimmy; Mendoza, Paola Maria; Musick, David; Sembrano, Roderick

2012-05-01

This study evaluated the impact of a 2-wk required rotation in Physical Medicine and Rehabilitation (PM&R) on fourth-year medical students' knowledge of PM&R and attitude toward teamwork in patient care. Survey results on attitudes toward a team approach to patient care and knowledge in PM&R were compared prerotation and postrotation. One hundred thirty-eight fourth-year medical students participated in this 2-yr study. The combined response rates for the attitude and knowledge surveys were 62% and 56%, respectively. As measured by a pretest and posttest self-reported knowledge assessment, the rotation increased knowledge of PM&R (P ≤ 0.05). Four aspects of the rotation that were rated higher by students from the second year of the rotation were role and responsibility definition, incorporation of current literature, enhancement of clinical skills, and general rotation satisfaction. The rotation provides an experience for medical students to increase their knowledge of PM&R.

Prospective memory deficits in illicit polydrug users are associated with the average long-term typical dose of ecstasy typically consumed in a single session.

PubMed

Gallagher, Denis T; Hadjiefthyvoulou, Florentia; Fisk, John E; Montgomery, Catharine; Robinson, Sarita J; Judge, Jeannie

2014-01-01

Neuroimaging evidence suggests that ecstasy-related reductions in SERT densities relate more closely to the number of tablets typically consumed per session rather than estimated total lifetime use. To better understand the basis of drug related deficits in prospective memory (p.m.) we explored the association between p.m. and average long-term typical dose and long-term frequency of use. Study 1: Sixty-five ecstasy/polydrug users and 85 nonecstasy users completed an event-based, a short-term and a long-term time-based p.m. task. Study 2: Study 1 data were merged with outcomes on the same p.m. measures from a previous study creating a combined sample of 103 ecstasy/polydrug users, 38 cannabis-only users, and 65 nonusers of illicit drugs. Study 1: Ecstasy/polydrug users had significant impairments on all p.m. outcomes compared with nonecstasy users. Study 2: Ecstasy/polydrug users were impaired in event-based p.m. compared with both other groups and in long-term time-based p.m. compared with nonillicit drug users. Both drug using groups did worse on the short-term time-based p.m. task compared with nonusers. Higher long-term average typical dose of ecstasy was associated with poorer performance on the event and short-term time-based p.m. tasks and accounted for unique variance in the two p.m. measures over and above the variance associated with cannabis and cocaine use. The typical ecstasy dose consumed in a single session is an important predictor of p.m. impairments with higher doses reflecting increasing tolerance giving rise to greater p.m. impairment.

Quantifying public health benefits of environmental strategy of PM2.5 air quality management in Beijing-Tianjin-Hebei region, China.

PubMed

Chen, Li; Shi, Mengshuang; Li, Suhuan; Gao, Shuang; Zhang, Hui; Sun, Yanling; Mao, Jian; Bai, Zhipeng; Wang, Zhongliang; Zhou, Jiang

2017-07-01

In 2013, China issued "Air Pollution Prevention and Control Action Plan (Action Plan)" to improve air quality. To assess the benefits of this program in Beijing-Tianjin-Hebei (BTH) region, where the density of population and emissions vary greatly, we simulated the air quality benefit based on BenMAP to satisfy the Action Plan. In this study, we estimate PM 2.5 concentration using Voronoi spatial interpolation method on a grid with a spatial resolution of 1×1km 2 . Combined with the exposure-response function between PM 2.5 concentration and health endpoints, health effects of PM 2.5 exposure are analyzed. The economic loss is assessed by using the willingness to pay (WTP) method and human capital (HC) method. When the PM 2.5 concentration falls by 25% in BTH and reached 60μg/m 3 in Beijing, the avoiding deaths will be in the range of 3175 to 14051 based on different functions each year. Of the estimated mortality attributable to all causes, 3117 annual deaths were due to lung cancer, 1924 - 6318 annual deaths were due to cardiovascular, and 343 - 1697 annual deaths were due to respiratory. Based on WTP, the estimated monetary values for the avoided cases of all cause mortality, cardiovascular mortality, respiratory mortality and lung cancer ranged from 1110 to 29632, 673 to 13325, 120 to 3579, 1091 to 6574 million yuan, respectively. Based on HC, the corresponding values for the avoided cases of these four mortalities were 267 to 1178, 161 to 529, 29 to 143 and 261 million yuan, respectively. Copyright © 2016. Published by Elsevier B.V.

40 CFR 52.2527 - Determination of attainment.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., EPA determined that the Steubenville-Weirton fine particle (PM2.5) nonattainment area attained the... 3-year period 2007-2009, EPA determined that the Charleston fine particle (PM2.5) nonattainment area... fine particle (PM2.5) nonattainment areas attained the 1997 annual PM2.5 National Ambient Air Quality...

40 CFR 52.2527 - Determination of attainment.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., EPA determined that the Steubenville-Weirton fine particle (PM2.5) nonattainment area attained the... 3-year period 2007-2009, EPA determined that the Charleston fine particle (PM2.5) nonattainment area... fine particle (PM2.5) nonattainment areas attained the 1997 annual PM2.5 National Ambient Air Quality...

40 CFR 52.2527 - Determination of attainment.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., EPA determined that the Steubenville-Weirton fine particle (PM2.5) nonattainment area attained the... 3-year period 2007-2009, EPA determined that the Charleston fine particle (PM2.5) nonattainment area... fine particle (PM2.5) nonattainment areas attained the 1997 annual PM2.5 National Ambient Air Quality...

Carotid Intima-Media Thickness and Long-Term Exposure to Traffic-Related Air Pollution in Middle-Aged Residents of Taiwan: A Cross-Sectional Study.

PubMed

Su, Ta-Chen; Hwang, Juey-Jen; Shen, Yu-Cheng; Chan, Chang-Chuan

2015-08-01

Associations between long-term exposure to air pollution and carotid intima-media thickness (CIMT) have inconsistent findings. In this study we aimed to evaluate association between 1-year average exposure to traffic-related air pollution and CIMT in middle-aged adults in Asia. CIMT was measured in Taipei, Taiwan, between 2009 and 2011 in 689 volunteers 35-65 years of age who were recruited as the control subjects of an acute coronary heart disease cohort study. We applied land-use regression models developed by the European Study of Cohorts for Air Pollution Effects (ESCAPE) to estimate each subject's 1-year average exposure to traffic-related air pollutants with particulate matter diameters ≤ 10 μm (PM10) and ≤ 2.5 μm (PM2.5) and the absorbance levels of PM2.5 (PM2.5abs), nitrogen dioxide (NO2), and nitrogen oxides (NOx) in the urban environment. One-year average air pollution exposures were 44.21 ± 4.19 μg/m3 for PM10, 27.34 ± 5.12 μg/m3 for PM2.5, and (1.97 ± 0.36) × 10-5/m for PM2.5abs. Multivariate regression analyses showed average percentage increases in maximum left CIMT of 4.23% (95% CI: 0.32, 8.13) per 1.0 × 10-5/m increase in PM2.5abs; 3.72% (95% CI: 0.32, 7.11) per 10-μg/m3 increase in PM10; 2.81% (95% CI: 0.32, 5.31) per 20-μg/m3 increase in NO2; and 0.74% (95% CI: 0.08, 1.41) per 10-μg/m3 increase in NOx. The associations were not evident for right CIMT, and PM2.5 mass concentration was not associated with the outcomes. Long-term exposures to traffic-related air pollution of PM2.5abs, PM10, NO2, and NOx were positively associated with subclinical atherosclerosis in middle-aged adults.

Trends in simulated chemical composition of global and regional population-weighted fine particulate matter over the recent 25 years

NASA Astrophysics Data System (ADS)

Li, C.; Martin, R.; van Donkelaar, A.; Boys, B.; Hammer, M. S.; Xu, J.; Marais, E. A.; Reff, A.; Strum, M.; Ridley, D. A.; Crippa, M.; Zhang, Q.

2017-12-01

We interpret in situ and satellite observations with a chemical transport model (GEOS-Chem) to understand global trends in population-weighted mean chemical composition of fine particulate matter (PM2.5) over 1989-2013. Simulated PM2.5 composition concentrations at 2˚ × 2.5˚ resolution are downscaled to 0.1˚ × 0.1˚ with satellite-based estimates of PM2.5 to better represent population exposure. Trends in simulated and observed population-weighted mean PM2.5 composition over 1989-2013 exhibit a high degree of consistency for (in situ vs. downscaled simulation) PM2.5 (-2.4 vs. -2.4 % yr-1), secondary inorganic aerosols (-4.3 vs. -4.1% yr-1), organic aerosols (OA, -3.6 vs. -3.0 % yr-1) and black carbon (-4.3 vs. -3.9 % yr-1) over North America, as well as sulfate (-4.7 vs. -5.8 % yr-1) over Europe. The downscaled simulation also has overlapping 95% confidence intervals with satellite-derived trends in population-weighted mean PM2.5 for 20 of the 21 Global Burden of Disease Study (GBD) regions over 1998-2013. Over 1989-2013, most (79%) of the simulated increase in global population-weighted mean PM2.5 of 0.28 μg m-3yr-1 is explained by significantly (p < 0.05) increasing OA (0.10 μg m-3yr-1), nitrate (0.05 μg m-3yr-1), sulfate (0.04 μg m-3yr-1) and ammonium (0.03 μg m-3yr-1). These species predominantly drive trends in population-weighted mean PM2.5 over populous regions of South Asia (0.94 μg m-3yr-1), East Asia (0.66 μg m-3yr-1), Western Europe (-0.47 μg m-3yr-1) and North America (-0.32 μg m-3yr-1), primarily due to changes in anthropogenic emissions. Mineral dust from deserts and OA over open burning regions usually cause weak, insignificant trends in population-weighted mean PM2.5, despite strong inter-annual variation. Global trends in area-weighted mean PM2.5 differ significantly from population-weighted trends in both the magnitude and sign, indicating the importance of population weighting for relevance to human exposure studies. This study provides new insights into global changes in PM2.5 exposure through the recent 25 years, with particular attention given to the evolution of PM2.5 composition.

Trends of particulate matter (PM2.5) and chemical composition at a regional background site in the Western Mediterranean over the last nine years (2002-2010)

NASA Astrophysics Data System (ADS)

Cusack, M.; Alastuey, A.; Pérez, N.; Pey, J.; Querol, X.

2012-04-01

The time variability and long term trends of PM2.5 (particulate matter of diameter <2.5 μm) at various regional background (RB) sites across Europe are studied and interpreted in this work. Long-term trends of PM2.5 concentrations are relatively scarce across Europe, with few studies outlining the changes measured in PM2.5 concentrations over a significant period of time. To this end, data on mean annual levels of PM2.5 measured at Montseny (MSY, North East Spain) and various RB sites in Spain and Europe are evaluated and compared, and subsequently analysed for statistically significant trends. The MSY site registered higher average PM2.5 levels than those measured at a selection of other RB sites across Spain, Portugal, Germany and Scandinavia, but lower than those measured in Switzerland, Italy and Austria. Reductions in PM2.5 were observed across all stations in Spain and Europe to varying degrees. MSY underwent a statistically significant reduction since measurements began, indicating a year-on-year gradual decrease (-3.7 μg m-3, calculated from the final year of data compared to the mean). Similar trends were observed in other RB sites across Spain (-1.9 μg m-3). Reductions recorded in PM2.5 across Europe were varied, with many experiencing gradual, year-on-year decreases (-1.8 μg m-3). These reductions have been attributed to various causes: the introduction and implementation of pollution abatement strategies in EU member states, the effect of the current economic crisis on emissions of PM2.5 and the influence of anomalous meteorology observed during the winters of 2009 and 2010. The North Atlantic Oscillation (NAO), a large scale meteorological phenomenon most prevalent during winter, was observed to influence the frequency of Saharan dust intrusions across the Iberian Peninsula. Chemical composition of PM2.5 at MSY is characterised by high levels of organic matter (OM) and sulphate, followed by crustal material, nitrate and ammonia. Sea Spray and finally elemental carbon (EC) comprised a minor part of the total PM2.5 mass. Statistical trend analysis was performed on the various chemical components of PM2.5 recorded at MSY to determine which components were accountable for the decrease in PM2.5 concentration. It is shown that OM underwent the largest decrease over the time period with a statistically significant trend (-1.3 μg m-3 of the mean), followed by sulphate (-0.8 μg m-3), ammonium (-0.5 μg m-3) and nitrate (-0.4 μg m-3). Conversely, sea spray, EC and crustal material reductions were found to be negligible.

Assessment of population exposure to PM2.5 for mortality in China and its public health benefit based on BenMAP.

PubMed

Chen, Li; Shi, Mengshuang; Gao, Shuang; Li, Suhuan; Mao, Jian; Zhang, Hui; Sun, Yanling; Bai, Zhipeng; Wang, Zhongliang

2017-02-01

Along with the rapid socioeconomic development, air pollution in China has become a severe problem. One component of air pollution, in particular, PM 2.5 has aroused wide public concern because of its high concentration. In this study, data were collected from over 900 monitoring sites of the newly constructed PM 2.5 monitoring network in China. The interpolation methods were used to simulate the PM 2.5 exposure level of China especially in rural areas, thus reflecting the spatial variation of PM 2.5 pollution. We calculated the health benefit caused by PM 2.5 in China in 2014 based on Environmental Benefits Mapping and Analysis Program (BenMAP), assuming achievement of China National Ambient Air Quality Standard (No. GB3095-2012). By reducing the annual average concentration of PM 2.5 to the annual Grade II standard (35 μg/m 3 ), the avoided deaths for cardiovascular disease, respiratory disease and lung cancer could reach 89,000 (95% CI, 8000-170,000), 47,000 (95% CI, 3000-91,000) and 32,000 (95% CI, 6000-58,000) per year using long term health function, respectively. The attributable fractions of cardiovascular disease, respiratory disease and lung cancer to all cause were 42%, 22% and 15%, respectively. The total economic benefits for rolling back the concentration of PM 2.5 to the level of 35 μg/m 3 were estimated to be 260 (95%CI: (73, 440) billion RMB and 72 (95%CI: (45, 99) billion RMB using willingness to pay (WTP) and human capital (HC) methods, respectively, which account for 0.40% (95%CI: (0.11%, 0.69%) and 0.11% (95%CI: (0.07%, 0.15%) of the total annual Gross Domestic Product (GDP) of China in 2014. Copyright © 2016 Elsevier Ltd. All rights reserved.

Weather Condition dominates the Regional PM2.5 Pollutions in the Eastern Coastal Provinces of China during winter

NASA Astrophysics Data System (ADS)

Cai, Zhe; Jiang, Fei; Chen, Jingming; Jiang, Ziqiang

2017-04-01

China has been suffering from severe particulate matter (PM) pollution in recent years. Both pollution area and pollution levels are increasing gradually. The PM pollution episodes not only occur in the traditional developed areas like Yangtze River Delta (YRD) and Beijing-Tianjin-Hebei (BTH) region, but also frequently happen in the whole eastern coastal provinces (ECPs) of China. Based on hourly PM2.5 concentrations during December 2013 February 2014 of 55 cities located in the ECPs, we investigated the spatial and temporal variabilities of PM2.5 concentrations and the corresponding meteorological conditions during winter. The results shown that basically the seasonal mean concentrations over the whole ECPs exceeded the China's national standard of 75 μg/m3, and the most polluted area with mean concentrations greater than 150 μg/m3 were located in the southwest of Hebei and the west of Shandong provinces. From December to February, there was a decrease trend for the PM2.5 pollution in most areas, especially in the YRD region, while the PM2.5 concentrations over north of Hebei province increased. The spatial distributions and monthly variations are strongly related to the weather conditions. Overall, severe PM pollution was corresponding to a stable weather condition, i.e., small Sea Level Pressure (SLP) gradient, lower Planetary Boundary Layer (PBL) height and weaker wind fields. Statistics shown that the changes of mean PM2.5 concentrations over the ECPs region usually lagged behind the variations of PBL height and wind speeds about 12 18 hours. The variations of weather conditions could explain about 71% (R2) of the overall changes of PM2.5 concentrations in the ECPs region. This study gives a full insight into the PM2.5 pollution in the area of eastern coastal provinces of China during winter, which would be helpful to predict and control the PM2.5 pollution for this area in the future.

Satellite-Based Spatiotemporal Trends in PM2.5 Concentrations: China 2004-2013

NASA Technical Reports Server (NTRS)

Ma, Zongwei; Hu, Xuefei; Sayer, Andrew M.; Levy, Robert; Zhang, Qiang; Xue, Yingang; Tong, Shilu; Bi, Jun; Huang, Lei; Liu, Yang

2016-01-01

Three decades of rapid economic development is causing severe and widespread PM2.5(particulate matter (is) less than 2.5 ) pollution in China. However, research on the health impacts of PM2.5 exposure has been hindered by limited historical PM2.5 concentration data. We estimated ambient PM2.5 concentrations from 2004 to 2013 in China at 0.1 deg resolution using the most recent satellite data and evaluated model performance with available ground observations. We developed a two-stage spatial statistical model using the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) and assimilated meteorology, land use data, and PM2.5 concentrations from China's recently established ground monitoring network. An inverse variance weighting (IVW) approach was developed to combine MODIS Dark Target and Deep Blue AOD to optimize data coverage. We evaluated model predicted PM2.5 concentrations from 2004 to early 2014 using ground observations. The overall model cross-validation R(sup 2) and relative prediction error were 0.79 and 35.6%, respectively. Validation beyond the model year (2013) indicated that it accurately predicted PM(sub 2.5) concentrations with little bias at the monthly (R(sup 2) = 0.73), regression slope = 0.91) and seasonal (R(sup 2) = 0.79), regression slope = 0.92) levels. Seasonal variations revealed that winter was the most polluted season and that summer was the cleanest season. Analysis of predicted PM2.5 levels showed a mean annual increase of 1.97 micro-g/cu cm between 2004 and 2007 and a decrease of 0.46 micro-g/cu cm between 2008 and 2013. Our satellite-driven model can provide reliable historical PM2.5 estimates in China at a resolution comparable to those used in epidemiologic studies on the health effects of long-term PM2.5 exposure in North America. This data source can potentially advance research on PM2.5 health effects in China.

33 CFR 207.170c - Kissimmee River, navigation locks between Lake Tohopekaliga and Lake Okeechobee, Fla.; use...

Code of Federal Regulations, 2010 CFR

2010-07-01

....m. Saturday and Sunday Mar. 1 through Oct. 31 5:30 a.m. to 7:30 p.m. Do Nov. 1 through Feb. 28 5:30 a.m. to 6:30 p.m. Lock S-65A Seven days a week All year 8:00 a.m. to 5:00 p.m. Locks S-65B, S-65C, and S-65D Monday through Friday All year 8:00 a.m. to 5:00 p.m. Saturday and Sunday Mar. 1 through Oct...

33 CFR 207.170c - Kissimmee River, navigation locks between Lake Tohopekaliga and Lake Okeechobee, Fla.; use...

Code of Federal Regulations, 2013 CFR

2013-07-01

....m. Saturday and Sunday Mar. 1 through Oct. 31 5:30 a.m. to 7:30 p.m. Do Nov. 1 through Feb. 28 5:30 a.m. to 6:30 p.m. Lock S-65A Seven days a week All year 8:00 a.m. to 5:00 p.m. Locks S-65B, S-65C, and S-65D Monday through Friday All year 8:00 a.m. to 5:00 p.m. Saturday and Sunday Mar. 1 through Oct...

33 CFR 207.170c - Kissimmee River, navigation locks between Lake Tohopekaliga and Lake Okeechobee, Fla.; use...

Code of Federal Regulations, 2014 CFR

2014-07-01

....m. Saturday and Sunday Mar. 1 through Oct. 31 5:30 a.m. to 7:30 p.m. Do Nov. 1 through Feb. 28 5:30 a.m. to 6:30 p.m. Lock S-65A Seven days a week All year 8:00 a.m. to 5:00 p.m. Locks S-65B, S-65C, and S-65D Monday through Friday All year 8:00 a.m. to 5:00 p.m. Saturday and Sunday Mar. 1 through Oct...

33 CFR 207.170c - Kissimmee River, navigation locks between Lake Tohopekaliga and Lake Okeechobee, Fla.; use...

Code of Federal Regulations, 2012 CFR

2012-07-01

....m. Saturday and Sunday Mar. 1 through Oct. 31 5:30 a.m. to 7:30 p.m. Do Nov. 1 through Feb. 28 5:30 a.m. to 6:30 p.m. Lock S-65A Seven days a week All year 8:00 a.m. to 5:00 p.m. Locks S-65B, S-65C, and S-65D Monday through Friday All year 8:00 a.m. to 5:00 p.m. Saturday and Sunday Mar. 1 through Oct...

33 CFR 207.170c - Kissimmee River, navigation locks between Lake Tohopekaliga and Lake Okeechobee, Fla.; use...

Code of Federal Regulations, 2011 CFR

2011-07-01

....m. Saturday and Sunday Mar. 1 through Oct. 31 5:30 a.m. to 7:30 p.m. Do Nov. 1 through Feb. 28 5:30 a.m. to 6:30 p.m. Lock S-65A Seven days a week All year 8:00 a.m. to 5:00 p.m. Locks S-65B, S-65C, and S-65D Monday through Friday All year 8:00 a.m. to 5:00 p.m. Saturday and Sunday Mar. 1 through Oct...

The relationship of glutathione-S-transferases copy number variation and indoor air pollution to symptoms and markers of respiratory disease.

PubMed

Hersoug, Lars-Georg; Brasch-Andersen, Charlotte; Husemoen, Lise Lotte Nystrup; Sigsgaard, Torben; Linneberg, Allan

2012-07-01

Exposure to particulate matter (PM) may induce inflammation and oxidative stress in the airways. Carriers of null polymorphisms of glutathione S-transferases (GSTs), which detoxify reactive oxygen species, may be particularly susceptible to the effects of PM. To investigate whether deletions of GSTM1 and GSTT1 modify the potential effects of exposure to indoor sources of PM on symptoms and objective markers of respiratory disease. We conducted a population-based, cross-sectional study of 3471 persons aged 18-69 years. Information about exposure to indoor sources of PM and respiratory symptoms was obtained by a self-administered questionnaire. In addition, measurements of lung function (spirometry) and fractional exhaled nitric oxide were performed. Copy number variation of GSTM1 and GSTT1 was determined by polymerase chain reaction-based assays. We found that none of the symptoms and objective markers of respiratory disease were significantly associated with the GST null polymorphisms. An increasing number of positive alleles of the GSTM1 polymorphism tended to be associated lower prevalence of wheeze, cough, and high forced expiratory volume in 1 s (FEV(1) ), but these trends were not statistically significant. Furthermore, we did not observe any statistically significant interactions between GST copy number variation and exposure to indoor sources of PM in relation to respiratory symptoms and markers. In this adult population, GST copy number variations were not significantly associated with respiratory outcomes and did not modify the effects of self-reported exposure to indoor sources of PM on respiratory outcomes. © 2011 Blackwell Publishing Ltd.

Where is PM gone? Trends and variability of atmospheric PM10, PM2.5 and PM10-2.5 in the Po valley over the last decade (and more).

NASA Astrophysics Data System (ADS)

Bigi, Alessandro; Ghermandi, Grazia

2017-04-01

The Po Valley is one of the largest European regions with a remarkably high concentration level of atmospheric pollutants, both for particulate and gaseous compounds. In the last decade stringent regulations on air quality standards and on anthropogenic emissions have been set by the European Commission, leading to an overall improvement in air quality across Europe. In order to assess the decadal pattern and variability in PM across the Po valley we thoroughly investigated the time series of PM10, PM2.5 and PM10-2.5 from 41, 44 and 15 sites respectively (Bigi & Ghermandi 2014, 2016). PM2.5 and PM10-2.5 (PM10) series with a 7 (10) year or longer record have been analysed for long term trend in deseasonalized monthly means, annual quantiles and in monthly frequency distribution by robust statistical methods. A widespread and significant decreasing trend was observed at several sites for all size fractions, with the drop, up to a few percent per year, occurring mainly in winter for PM2.5 and throughout the year for PM10. All series were tested for a significant weekly periodicity (a proxy to estimate the impact of primary anthropogenic emissions) by 3 different statistical methods, yielding positive results for summer PM2.5 and PM10, and for both summer and winter PM10-2.5. Hierarchical cluster analysis showed larger variability for PM10 than for PM2.5. The former was split in five clusters: two encompassing the metropolitan areas of Turin and Milan and their respective nearby sites and the other three clusters gathering northeast, northwest and central Po Valley sites respectively. PM2.5 clusters divide the valley in western, eastern and southern/Apennines foothill sectors. The trend in atmospheric concentration was compared with the time series of local primary and precursor emissions, vehicular fleet details and fuel sales. A significant basin-wide drop in emissions occurred for gaseous pollutants, contrarily to primary emissions of PM10 and PM2.5, whose drop was low and spatially restricted. Overall the decrease in atmospheric PM2.5 and PM10 seems to originate from a drop in both primary emissions and in precursors of secondary inorganic aerosol emissions, largely ascribed to vehicular traffic. Potentially, the recent increase in biomass burning emissions in winter and the modest decrease in NH3 weaken an otherwise even larger drop in atmospheric concentrations. References Bigi, A. & Ghermandi, G. Long-term trend and variability of atmospheric PM10 concentration in the Po Valley Atmospheric Chemistry and Physics, 2014, 14, 4895-4907 Bigi, A. & Ghermandi, G. Trends and variability of atmospheric PM2.5 and PM10-2.5 concentration in the Po Valley, Italy Atmospheric Chemistry and Physics, 2016, 16, 15777-15788

Associations between air pollution and mortality in Phoenix, 1995-1997.

PubMed Central

Mar, T F; Norris, G A; Koenig, J Q; Larson, T V

2000-01-01

We evaluated the association between mortality outcomes in elderly individuals and particulate matter (PM) of varying aerodynamic diameters (in micrometers) [PM(10), PM(2.5), and PM(CF )(PM(10) minus PM(2.5))], and selected particulate and gaseous phase pollutants in Phoenix, Arizona, using 3 years of daily data (1995-1997). Although source apportionment and epidemiologic methods have been previously combined to investigate the effects of air pollution on mortality, this is the first study to use detailed PM composition data in a time-series analysis of mortality. Phoenix is in the arid Southwest and has approximately 1 million residents (9. 7% of the residents are > 65 years of age). PM data were obtained from the U.S. Environmental Protection Agency (EPA) National Exposure Research Laboratory Platform in central Phoenix. We obtained gaseous pollutant data, specifically carbon monoxide, nitrogen dioxide, ozone, and sulfur dioxide data, from the EPA Aerometric Information Retrieval System Database. We used Poisson regression analysis to evaluate the associations between air pollution and nonaccidental mortality and cardiovascular mortality. Total mortality was significantly associated with CO and NO(2) (p < 0.05) and weakly associated with SO(2), PM(10), and PM(CF) (p < 0. 10). Cardiovascular mortality was significantly associated with CO, NO(2), SO(2), PM(2.5), PM(10), PM(CF) (p < 0.05), and elemental carbon. Factor analysis revealed that both combustion-related pollutants and secondary aerosols (sulfates) were associated with cardiovascular mortality. PMID:10753094

Association of Changes in Air Quality With Bronchitic Symptoms in Children in California, 1993-2012.

PubMed

Berhane, Kiros; Chang, Chih-Chieh; McConnell, Rob; Gauderman, W James; Avol, Edward; Rapapport, Ed; Urman, Robert; Lurmann, Fred; Gilliland, Frank

2016-04-12

Childhood bronchitic symptoms are significant public and clinical health problems that produce a substantial burden of disease. Ambient air pollutants are important determinants of bronchitis occurrence. To determine whether improvements in ambient air quality in Southern California were associated with reductions in bronchitic symptoms in children. A longitudinal study involving 4602 children (age range, 5-18 years) from 3 cohorts was conducted during the 1993-2001, 1996-2004, and 2003-2012 years in 8 Southern California communities. A multilevel logistic model was used to estimate the association of changes in pollution levels with bronchitic symptoms. Average concentrations of nitrogen dioxide, ozone, particulate matter with an aerodynamic diameter of less than 10 µm (PM10) and less than 2.5 µm (PM2.5). Annual age-specific prevalence of bronchitic symptoms during the previous 12 months based on the parent's or child's report of a daily cough for 3 months in a row, congestion or phlegm other than when accompanied by a cold, or bronchitis. The 3 cohorts included a total of 4602 children (mean age at baseline, 8.0 years; 2268 girls [49.3%]; 2081 Hispanic white [45.2%]) who had data from 2 or more annual questionnaires. Among these children, 892 (19.4%) had asthma at age 10 years. For nitrogen dioxide, the odds ratio (OR) for bronchitic symptoms among children with asthma at age 10 years was 0.79 (95% CI, 0.67-0.94) for a median reduction of 4.9 ppb, with absolute decrease in prevalence of 10.1%. For ozone, the OR was 0.66 (95% CI, 0.50-0.86) for a median reduction of 3.6 ppb, with an absolute decrease in prevalence of 16.3%. For PM10, the OR was 0.61 (95% CI, 0.48-0.78) for a median reduction of 5.8 µg/m3, with an absolute decrease in prevalence of 18.7%. For PM2.5, the OR was 0.68 (95% CI, 0.53-0.86) for a median reduction of 6.8 µg/m3, with absolute decrease in prevalence of 15.4%. Among children without asthma (n = 3710), the ORs were 0.84 (95% CI, 0.76-0.92) for nitrogen dioxide; 0.85 (95% CI, 0.74-0.97) for ozone, 0.80 (95% CI, 0.70-0.92) for PM10, and 0.79 (95% CI, 0.69-0.91) for PM2.5; with absolute decrease in prevalence of 1.8% for nitrogen dioxide, 1.7% for ozone, 2.2% for PM10, and 2.3% for PM2.5. The associations were similar or slightly stronger at age 15 years. Decreases in ambient pollution levels were associated with statistically significant decreases in bronchitic symptoms in children. Although the study design does not establish causality, the findings support potential benefit of air pollution reduction on asthma control.

Particulate matter air quality assessment over southeast United States using satellite and ground measurements

NASA Astrophysics Data System (ADS)

Gupta, Pawan

Fine particles (PM2.5, particles with aerodynamic diameter less than 2.5 mum) can penetrate deep inside the human lungs and recent scientific studies have shown thousands of deaths occur each year around the world, prematurely, due to a high concentration of particulate matter. Therefore, monitoring and forecasting of surface level fine particulate matter air quality is very important. Typically air quality measurements are made from ground stations. In recent years, linear regression relationships between satellite derived aerosol optical thickness (AOT) and surface measured PM2.5 mass concentration are formed and used to estimate PM2.5 in the areas where surface measurements are not available. This type of simple linear relationships varies with regions and seasons, and does not provide accurate enough estimation of surface level pollution and many studies have shown that AOT alone is not sufficient for PM2.5 mass concentration estimations. Furthermore, AOT represents aerosol loading in the entire column of the atmosphere whereas PM2.5 is measured at the surface; hence, the knowledge of vertical distribution of aerosols coupled with meteorology becomes critical in PM2.5 estimations. In this dissertation I used three years (2004-2006) of coincident hourly PM2.5, MODerate resolution Imaging Spectroradiometer (MODIS) derived AOT, and Rapid Update Cycle (RUC) analyzed meteorological fields to assess PM2.5 air quality in the Southeast United States. I explored the use of two-variate (TVM), multi-variate (MVM) and artificial neural network (ANN) methods for estimating PM2.5 over 85 stations in the region. First, satellite data were analyzed for sampling biases, quality, and impact of clouds. Results show that MODIS-Terra AOT data was available only about 50% of the days in any given month due to cloud over and unfavorable surface conditions, but this produced a sampling bias of less than 2 mugm-3. Results indicate that there is up to three fold improvements in the correlation coefficients (R) while using MVM (that includes meteorology) over different regions and seasons when compared to the TVM and further improvements were noticed when ANN method is applied. The improvement in absolute percentage error of estimation ranges from 5% to 50% over different seasons and regions when compared with TVM models. Overall ANN models performed better than TVM and MVM models. Based on these results, we recommend using meteorological variables along with satellite observations for improving particulate matter air quality assessment from satellite observations in the region.

10-year spatial and temporal trends of PM2.5 concentrations in the southeastern US estimated using high-resolution satellite data

PubMed Central

Hu, X.; Waller, L. A.; Lyapustin, A.; Wang, Y.; Liu, Y.

2017-01-01

Long-term PM2.5 exposure has been associated with various adverse health outcomes. However, most ground monitors are located in urban areas, leading to a potentially biased representation of true regional PM2.5 levels. To facilitate epidemiological studies, accurate estimates of the spatiotemporally continuous distribution of PM2.5 concentrations are important. Satellite-retrieved aerosol optical depth (AOD) has been increasingly used for PM2.5 concentration estimation due to its comprehensive spatial coverage. Nevertheless, previous studies indicated that an inherent disadvantage of many AOD products is their coarse spatial resolution. For instance, the available spatial resolutions of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging SpectroRadiometer (MISR) AOD products are 10 and 17.6 km, respectively. In this paper, a new AOD product with 1 km spatial resolution retrieved by the multi-angle implementation of atmospheric correction (MAIAC) algorithm based on MODIS measurements was used. A two-stage model was developed to account for both spatial and temporal variability in the PM2.5–AOD relationship by incorporating the MAIAC AOD, meteorological fields, and land use variables as predictors. Our study area is in the southeastern US centered at the Atlanta metro area, and data from 2001 to 2010 were collected from various sources. The model was fitted annually, and we obtained model fitting R2 ranging from 0.71 to 0.85, mean prediction error (MPE) from 1.73 to 2.50 μg m−3, and root mean squared prediction error (RMSPE) from 2.75 to 4.10 μg m−3. In addition, we found cross-validation R2 ranging from 0.62 to 0.78, MPE from 2.00 to 3.01 μgm−3, and RMSPE from 3.12 to 5.00 μgm−3, indicating a good agreement between the estimated and observed values. Spatial trends showed that high PM2.5 levels occurred in urban areas and along major highways, while low concentrations appeared in rural or mountainous areas. Our time-series analysis showed that, for the 10-year study period, the PM2.5 levels in the southeastern US have decreased by ∼20 %. The annual decrease has been relatively steady from 2001 to 2007 and from 2008 to 2010 while a significant drop occurred between 2007 and 2008. An observed increase in PM2.5 levels in year 2005 is attributed to elevated sulfate concentrations in the study area in warm months of 2005. PMID:28966656

Prospective Memory Impairments in Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia: Clinical and Neural Correlates.

PubMed

Dermody, Nadene; Hornberger, Michael; Piguet, Olivier; Hodges, John R; Irish, Muireann

2016-01-01

Prospective memory (PM) refers to a future-oriented form of memory in which the individual must remember to execute an intended action either at a future point in time (Time-based) or in response to a specific event (Event-based). Lapses in PM are commonly exhibited in neurodegenerative disorders including Alzheimer's disease (AD) and frontotemporal dementia (FTD), however, the neurocognitive mechanisms driving these deficits remain unknown. To investigate the clinical and neural correlates of Time- and Event-based PM disruption in AD and the behavioral-variant FTD (bvFTD). Twelve AD, 12 bvFTD, and 12 healthy older Control participants completed a modified version of the Cambridge Prospective Memory test, which examines Time- and Event-based aspects of PM. All participants completed a standard neuropsychological assessment and underwent whole-brain structural MRI. AD and bvFTD patients displayed striking impairments across Time- and Event-based PM relative to Controls, however, Time-based PM was disproportionately affected in the AD group. Episodic memory dysfunction and hippocampal atrophy were found to correlate strongly with PM integrity in both patient groups, however, dissociable neural substrates were also evident for PM performance across dementia syndromes. Our study reveals the multifaceted nature of PM dysfunction in neurodegenerative disorders, and suggests common and dissociable neurocognitive mechanisms, which subtend these deficits in each patient group. Future studies of PM disturbance in dementia syndromes will be crucial for the development of successful interventions to improve functional independence in the patient's daily life.

Ambient fine particulate matter air pollution and leisure-time physical inactivity among US adults.

PubMed

An, R; Xiang, X

2015-12-01

There is mounting evidence documenting the adverse health effects of short- and long-term exposure to ambient fine particulate matter (PM2.5) air pollution, but population-based evidence linking PM2.5 and health behaviour remains lacking. This study examined the relationship between ambient PM2.5 air pollution and leisure-time physical inactivity among US adults 18 years of age and above. Retrospective data analysis. Participant-level data (n = 2,381,292) from the Behavioral Risk Factor Surveillance System 2003-2011 surveys were linked with Wide-ranging Online Data for Epidemiologic Research air quality data by participants' residential county and interview month/year. Multilevel logistic regressions were performed to examine the effect of ambient PM2.5 air pollution on participants' leisure-time physical inactivity, accounting for various individual and county-level characteristics. Regressions were estimated on the overall sample and subsamples stratified by sex, age cohort, race/ethnicity and body weight status. One unit (μg/m(3)) increase in county monthly average PM2.5 concentration was found to be associated with an increase in the odds of physical inactivity by 0.46% (95% confidence interval = 0.34%-0.59%). The effect was similar between the sexes but to some extent (although not always statistically significant) larger for younger adults, Hispanics, and overweight/obese individuals compared with older adults, non-Hispanic whites or African Americans, and normal weight individuals, respectively. Ambient PM2.5 air pollution is found to be associated with a modest but measurable increase in individuals' leisure-time physical inactivity, and the relationship tends to differ across population subgroups. Copyright © 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Historical Prediction Modeling Approach for Estimating Long-Term Concentrations of PM2.5 in Cohort Studies before the 1999 Implementation of Widespread Monitoring

PubMed Central

Kim, Sun-Young; Olives, Casey; Sheppard, Lianne; Sampson, Paul D.; Larson, Timothy V.; Keller, Joshua P.; Kaufman, Joel D.

2016-01-01

Introduction: Recent cohort studies have used exposure prediction models to estimate the association between long-term residential concentrations of fine particulate matter (PM2.5) and health. Because these prediction models rely on PM2.5 monitoring data, predictions for times before extensive spatial monitoring present a challenge to understanding long-term exposure effects. The U.S. Environmental Protection Agency (EPA) Federal Reference Method (FRM) network for PM2.5 was established in 1999. Objectives: We evaluated a novel statistical approach to produce high-quality exposure predictions from 1980 through 2010 in the continental United States for epidemiological applications. Methods: We developed spatio-temporal prediction models using geographic predictors and annual average PM2.5 data from 1999 through 2010 from the FRM and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks. Temporal trends before 1999 were estimated by using a) extrapolation based on PM2.5 data in FRM/IMPROVE, b) PM2.5 sulfate data in the Clean Air Status and Trends Network, and c) visibility data across the Weather Bureau Army Navy network. We validated the models using PM2.5 data collected before 1999 from IMPROVE, California Air Resources Board dichotomous sampler monitoring (CARB dichot), the Children’s Health Study (CHS), and the Inhalable Particulate Network (IPN). Results: In our validation using pre-1999 data, the prediction model performed well across three trend estimation approaches when validated using IMPROVE and CHS data (R2 = 0.84–0.91) with lower R2 values in early years. Model performance using CARB dichot and IPN data was worse (R2 = 0.00–0.85) most likely because of fewer monitoring sites and inconsistent sampling methods. Conclusions: Our prediction modeling approach will allow health effects estimation associated with long-term exposures to PM2.5 over extended time periods ≤ 30 years. Citation: Kim SY, Olives C, Sheppard L, Sampson PD, Larson TV, Keller JP, Kaufman JD. 2017. Historical prediction modeling approach for estimating long-term concentrations of PM2.5 in cohort studies before the 1999 implementation of widespread monitoring. Environ Health Perspect 125:38–46; http://dx.doi.org/10.1289/EHP131 PMID:27340825

Asian aerosols: current and year 2030 distributions and implications to human health and regional climate change.

PubMed

Carmichael, Gregory R; Adhikary, Bhupesh; Kulkarni, Sarika; D'Allura, Alessio; Tang, Youhua; Streets, David; Zhang, Qiang; Bond, Tami C; Ramanathan, Veerabhadran; Jamroensan, Aditsuda; Marrapu, Pallavi

2009-08-01

Aerosol distributions in Asia calculated over a 4-year period and constrained by satellite observations of aerosol optical depth (AOD) are presented. Vast regions in Asia that include > 80% of the population have PM2.5 concentrations that exceed on an annual basis the WHO guideline of 10 microg/m3, often by factors of 2 to 4. These high aerosol loadings also have important radiative effects, causing a significant dimming at the surface, and mask approximately 45% of the warming by greenhouse gases. Black carbon (BC) concentrations are high throughout Asia, representing 5-10% of the total AOD, and contributing significantly to atmospheric warming (its warming potential is approximately 55% of that due to CO2). PM levels and AODs in year 2030, estimated based on simulations that consider future changes in emissions, are used to explore opportunities for win-win strategies built upon addressing air quality and climate change together. It is found that in 2030 the PM2.5 levels in significant parts of Asia will increase and exacerbate health impacts; but the aerosols will have a larger masking effect on radiative forcing, due to a decrease in BC and an increase in SO2 emissions.

77 FR 74115 - Approval and Promulgation of Air Quality Implementation Plans; Pennsylvania; The 2002 Base Year...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-13

... ), volatile organic compounds (VOCs), ammonia (NH 3 ), and sulfur dioxide (SO 2 ). EPA has reviewed the... , coarse particles (PM 10 ), nitrogen oxides (NO X ), volatile organic compounds (VOCs), ammonia (NH 3...

Local- and regional-scale air pollution modelling (PM10) and exposure assessment for pregnancy trimesters, infancy, and childhood to age 15 years: Avon Longitudinal Study of Parents And Children (ALSPAC).

PubMed

Gulliver, John; Elliott, Paul; Henderson, John; Hansell, Anna L; Vienneau, Danielle; Cai, Yutong; McCrea, Adrienne; Garwood, Kevin; Boyd, Andy; Neal, Lucy; Agnew, Paul; Fecht, Daniela; Briggs, David; de Hoogh, Kees

2018-04-01

We established air pollution modelling to study particle (PM 10 ) exposures during pregnancy and infancy (1990-1993) through childhood and adolescence up to age ~15 years (1991-2008) for the Avon Longitudinal Study of Parents And Children (ALSPAC) birth cohort. For pregnancy trimesters and infancy (birth to 6 months; 7 to 12 months) we used local (ADMS-Urban) and regional/long-range (NAME-III) air pollution models, with a model constant for local, non-anthropogenic sources. For longer exposure periods (annually and the average of birth to age ~8 and to age ~15 years to coincide with relevant follow-up clinics) we assessed spatial contrasts in local sources of PM 10 with a yearly-varying concentration for all background sources. We modelled PM 10 (μg/m 3 ) for 36,986 address locations over 19 years and then accounted for changes in address in calculating exposures for different periods: trimesters/infancy (n = 11,929); each year of life to age ~15 (n = 10,383). Intra-subject exposure contrasts were largest between pregnancy trimesters (5 th to 95 th centile: 24.4-37.3 μg/m 3 ) and mostly related to temporal variability in regional/long-range PM 10 . PM 10 exposures fell on average by 11.6 μg/m 3 from first year of life (mean concentration = 31.2 μg/m 3 ) to age ~15 (mean = 19.6 μg/m 3 ), and 5.4 μg/m 3 between follow-up clinics (age ~8 to age ~15). Spatial contrasts in 8-year average PM 10 exposures (5 th to 95 th centile) were relatively low: 25.4-30.0 μg/m 3 to age ~8 years and 20.7-23.9 μg/m 3 from age ~8 to age ~15 years. The contribution of local sources to total PM 10 was 18.5%-19.5% during pregnancy and infancy, and 14.4%-17.0% for periods leading up to follow-up clinics. Main roads within the study area contributed on average ~3.0% to total PM 10 exposures in all periods; 9.5% of address locations were within 50 m of a main road. Exposure estimates will be used in a number of planned epidemiological studies. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Modified multiblock partial least squares path modeling algorithm with backpropagation neural networks approach

NASA Astrophysics Data System (ADS)

Yuniarto, Budi; Kurniawan, Robert

2017-03-01

PLS Path Modeling (PLS-PM) is different from covariance based SEM, where PLS-PM use an approach based on variance or component, therefore, PLS-PM is also known as a component based SEM. Multiblock Partial Least Squares (MBPLS) is a method in PLS regression which can be used in PLS Path Modeling which known as Multiblock PLS Path Modeling (MBPLS-PM). This method uses an iterative procedure in its algorithm. This research aims to modify MBPLS-PM with Back Propagation Neural Network approach. The result is MBPLS-PM algorithm can be modified using the Back Propagation Neural Network approach to replace the iterative process in backward and forward step to get the matrix t and the matrix u in the algorithm. By modifying the MBPLS-PM algorithm using Back Propagation Neural Network approach, the model parameters obtained are relatively not significantly different compared to model parameters obtained by original MBPLS-PM algorithm.

Fast inverse distance weighting-based spatiotemporal interpolation: a web-based application of interpolating daily fine particulate matter PM2:5 in the contiguous U.S. using parallel programming and k-d tree.

PubMed

Li, Lixin; Losser, Travis; Yorke, Charles; Piltner, Reinhard

2014-09-03

Epidemiological studies have identified associations between mortality and changes in concentration of particulate matter. These studies have highlighted the public concerns about health effects of particulate air pollution. Modeling fine particulate matter PM2.5 exposure risk and monitoring day-to-day changes in PM2.5 concentration is a critical step for understanding the pollution problem and embarking on the necessary remedy. This research designs, implements and compares two inverse distance weighting (IDW)-based spatiotemporal interpolation methods, in order to assess the trend of daily PM2.5 concentration for the contiguous United States over the year of 2009, at both the census block group level and county level. Traditionally, when handling spatiotemporal interpolation, researchers tend to treat space and time separately and reduce the spatiotemporal interpolation problems to a sequence of snapshots of spatial interpolations. In this paper, PM2.5 data interpolation is conducted in the continuous space-time domain by integrating space and time simultaneously, using the so-called extension approach. Time values are calculated with the help of a factor under the assumption that spatial and temporal dimensions are equally important when interpolating a continuous changing phenomenon in the space-time domain. Various IDW-based spatiotemporal interpolation methods with different parameter configurations are evaluated by cross-validation. In addition, this study explores computational issues (computer processing speed) faced during implementation of spatiotemporal interpolation for huge data sets. Parallel programming techniques and an advanced data structure, named k-d tree, are adapted in this paper to address the computational challenges. Significant computational improvement has been achieved. Finally, a web-based spatiotemporal IDW-based interpolation application is designed and implemented where users can visualize and animate spatiotemporal interpolation results.

Fast Inverse Distance Weighting-Based Spatiotemporal Interpolation: A Web-Based Application of Interpolating Daily Fine Particulate Matter PM2.5 in the Contiguous U.S. Using Parallel Programming and k-d Tree

PubMed Central

Li, Lixin; Losser, Travis; Yorke, Charles; Piltner, Reinhard

2014-01-01

Epidemiological studies have identified associations between mortality and changes in concentration of particulate matter. These studies have highlighted the public concerns about health effects of particulate air pollution. Modeling fine particulate matter PM2.5 exposure risk and monitoring day-to-day changes in PM2.5 concentration is a critical step for understanding the pollution problem and embarking on the necessary remedy. This research designs, implements and compares two inverse distance weighting (IDW)-based spatiotemporal interpolation methods, in order to assess the trend of daily PM2.5 concentration for the contiguous United States over the year of 2009, at both the census block group level and county level. Traditionally, when handling spatiotemporal interpolation, researchers tend to treat space and time separately and reduce the spatiotemporal interpolation problems to a sequence of snapshots of spatial interpolations. In this paper, PM2.5 data interpolation is conducted in the continuous space-time domain by integrating space and time simultaneously, using the so-called extension approach. Time values are calculated with the help of a factor under the assumption that spatial and temporal dimensions are equally important when interpolating a continuous changing phenomenon in the space-time domain. Various IDW-based spatiotemporal interpolation methods with different parameter configurations are evaluated by cross-validation. In addition, this study explores computational issues (computer processing speed) faced during implementation of spatiotemporal interpolation for huge data sets. Parallel programming techniques and an advanced data structure, named k-d tree, are adapted in this paper to address the computational challenges. Significant computational improvement has been achieved. Finally, a web-based spatiotemporal IDW-based interpolation application is designed and implemented where users can visualize and animate spatiotemporal interpolation results. PMID:25192146

33 CFR 165.939 - Safety Zones; Annual Fireworks Events in the Captain of the Port Buffalo Zone.

Code of Federal Regulations, 2010 CFR

2010-07-01

... effective from 9 p.m. to 10 p.m. on July 1 of each year. (3) French Festival Fireworks, Cape Vincent, NY—(i.... to 10 p.m. on the third weekend of September each year. (6) Island Festival Fireworks Display... Festival, Rochester, NY—(i) Location. All waters of Lake Ontario within a 500-foot radius of land position...

Model calculated global, regional and megacity premature mortality due to air pollution

NASA Astrophysics Data System (ADS)

Lelieveld, J.; Barlas, C.; Giannadaki, D.; Pozzer, A.

2013-07-01

Air pollution by fine particulate matter (PM2.5) and ozone (O3) has increased strongly with industrialization and urbanization. We estimate the premature mortality rates and the years of human life lost (YLL) caused by anthropogenic PM2.5 and O3 in 2005 for epidemiological regions defined by the World Health Organization (WHO). This is based upon high-resolution global model calculations that resolve urban and industrial regions in greater detail compared to previous work. Results indicate that 69% of the global population is exposed to an annual mean anthropogenic PM2.5 concentration of >10 μg m-3 (WHO guideline) and 33% to > 25 μg m-3 (EU directive). We applied an epidemiological health impact function and find that especially in large countries with extensive suburban and rural populations, air pollution-induced mortality rates have been underestimated given that previous studies largely focused on the urban environment. We calculate a global respiratory mortality of about 773 thousand/year (YLL ≈ 5.2 million/year), 186 thousand/year by lung cancer (YLL ≈ 1.7 million/year) and 2.0 million/year by cardiovascular disease (YLL ≈ 14.3 million/year). The global mean per capita mortality caused by air pollution is about 0.1% yr-1. The highest premature mortality rates are found in the Southeast Asia and Western Pacific regions (about 25% and 46% of the global rate, respectively) where more than a dozen of the most highly polluted megacities are located.

40 CFR 93.123 - Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis).

Code of Federal Regulations, 2011 CFR

2011-07-01

... (“Localized CO, PM10, and PM2.5 violations”) must be based on quantitative analysis using the applicable air... § 93.116 may be based on either: (i) Quantitative methods that represent reasonable and common... hot-spot analyses. (1) The hot-spot demonstration required by § 93.116 must be based on quantitative...

40 CFR 93.123 - Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis).

Code of Federal Regulations, 2013 CFR

2013-07-01

... (“Localized CO, PM10, and PM2.5 violations”) must be based on quantitative analysis using the applicable air... § 93.116 may be based on either: (i) Quantitative methods that represent reasonable and common... hot-spot analyses. (1) The hot-spot demonstration required by § 93.116 must be based on quantitative...

40 CFR 93.123 - Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis).

Code of Federal Regulations, 2012 CFR

2012-07-01

... (“Localized CO, PM10, and PM2.5 violations”) must be based on quantitative analysis using the applicable air... § 93.116 may be based on either: (i) Quantitative methods that represent reasonable and common... hot-spot analyses. (1) The hot-spot demonstration required by § 93.116 must be based on quantitative...

40 CFR 93.123 - Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis).

Code of Federal Regulations, 2010 CFR

2010-07-01

... (“Localized CO, PM10, and PM2.5 violations”) must be based on quantitative analysis using the applicable air... § 93.116 may be based on either: (i) Quantitative methods that represent reasonable and common... hot-spot analyses. (1) The hot-spot demonstration required by § 93.116 must be based on quantitative...

The Army Budget Amended Fiscal Year 1990-91

DTIC Science & Technology

1989-05-01

Station -PERS: Personnel -PGTS: Precision Gunnery Target System -PHIL: Phillipines -PIP: Product Improvement Program -PL: Public Law -PM TRADE : Program...COMANDS 24.174 24.884 27,092 37,280 FOREIGN CURRECY FLUCTUATION 453,848 73,260 0 0 009 BASE INFORMATION MANAGEMENT 72,028 68.967 78,953 80,323 056 BASE

Air Pollution and Lung Function in Dutch Children: A Comparison of Exposure Estimates and Associations Based on Land Use Regression and Dispersion Exposure Modeling Approaches

PubMed Central

Gehring, Ulrike; Hoek, Gerard; Keuken, Menno; Jonkers, Sander; Beelen, Rob; Eeftens, Marloes; Postma, Dirkje S.; Brunekreef, Bert

2015-01-01

Background There is limited knowledge about the extent to which estimates of air pollution effects on health are affected by the choice for a specific exposure model. Objectives We aimed to evaluate the correlation between long-term air pollution exposure estimates using two commonly used exposure modeling techniques [dispersion and land use regression (LUR) models] and, in addition, to compare the estimates of the association between long-term exposure to air pollution and lung function in children using these exposure modeling techniques. Methods We used data of 1,058 participants of a Dutch birth cohort study with measured forced expiratory volume in 1 sec (FEV1), forced vital capacity (FVC), and peak expiratory flow (PEF) measurements at 8 years of age. For each child, annual average outdoor air pollution exposure [nitrogen dioxide (NO2), mass concentration of particulate matter with diameters ≤ 2.5 and ≤ 10 μm (PM2.5, PM10), and PM2.5 soot] was estimated for the current addresses of the participants by a dispersion and a LUR model. Associations between exposures to air pollution and lung function parameters were estimated using linear regression analysis with confounder adjustment. Results Correlations between LUR- and dispersion-modeled pollution concentrations were high for NO2, PM2.5, and PM2.5 soot (R = 0.86–0.90) but low for PM10 (R = 0.57). Associations with lung function were similar for air pollutant exposures estimated using LUR and dispersion modeling, except for associations of PM2.5 with FEV1 and FVC, which were stronger but less precise for exposures based on LUR compared with dispersion model. Conclusions Predictions from LUR and dispersion models correlated very well for PM2.5, NO2, and PM2.5 soot but not for PM10. Health effect estimates did not depend on the type of model used to estimate exposure in a population of Dutch children. Citation Wang M, Gehring U, Hoek G, Keuken M, Jonkers S, Beelen R, Eeftens M, Postma DS, Brunekreef B. 2015. Air pollution and lung function in Dutch children: a comparison of exposure estimates and associations based on land use regression and dispersion exposure modeling approaches. Environ Health Perspect 123:847–851; http://dx.doi.org/10.1289/ehp.1408541 PMID:25839747

Bloodstream infections caused by multi-drug resistant Proteus mirabilis: Epidemiology, risk factors and impact of multi-drug resistance.

PubMed

Korytny, Alexander; Riesenberg, Klaris; Saidel-Odes, Lisa; Schlaeffer, Fransisc; Borer, Abraham

2016-01-01

The prevalence of antimicrobial co-resistance among ESBL-producing Enterobactereaceae is extremely high in Israel. Multidrug-resistant Proteus mirabilis strains (MDR-PM), resistant to almost all antibiotic classes have been described. The aim was to determine the risk factors for bloodstream infections caused by MDR-PM and clinical outcomes. A retrospective case-control study. Adult patients with PM bacteremia during 7 years were identified retrospectively and their files reviewed for demographics, underlying diseases, Charlson Comorbidity Index, treatment and outcome. One hundred and eighty patients with PM-bloodstream infection (BSI) were included; 90 cases with MDR-PM and 90 controls with sensitive PM (S-PM). Compared to controls, cases more frequently were from nursing homes, had recurrent hospital admissions in the past year and received antibiotic therapy in the previous 3 months, were bedridden and suffered from peripheral vascular disease and peptic ulcer disease (p < 0.001). Two-thirds of the MDR-PM isolates were ESBL-producers vs 4.4% of S-PM isolates (p < 0.001, OR = 47.6, 95% CI = 15.9-142.6). In-hospital crude mortality rate of patients with MDR-PM BSI was 37.7% vs 23.3% in those with S-PM BSI (p = 0.0359, OR = 2, 95% CI = 1.4-3.81). PM bacteremia in elderly and functionally-dependent patients is likely to be caused by nearly pan-resistant PM strains in the institution; 51.8% of the patients received inappropriate empiric antibiotic treatment. The crude mortality rate of patients with MDR-PM BSI was significantly higher than that of patients with S-PM BSI.

Temporal and Spatial Variations in Fine and Coarse Particles in Seoul, Korea

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghim, Young Sung

2015-01-01

Concentrations of fine (PM2.5) and coarse particles (PM10 -2.5), whose diameters are less 2.5 µm, and between 2.5 and 10 µm, respectively, at ambient air monitoring stations in Seoul between 2002 and 2008 were analyzed. Effects of Asian dust are mainly manifested as concentration spikes of PM10 - 2.5 but were considerable on PM2.5 levels in 2002 when Asian dust storms were the strongest. Excluding the effects of Asian dust, annual average PM2.5 showed a downward trend. Despite a similarity in year - to - year variations, PM10- 2.5, mostly affected by fugitive dust emissions, and CO and NO2, primarilymore » affected by motor vehicle emissions, did not show a decrease. PM2.5 along with CO and NO2 had the highest values during the morning rush hour. PM10 - 2.5 peak lagged about one hour behind that of PM2.5 because of fugitive dust emissions despite an increasing mixing height. On high PM2.5 days, PM2. 5 peaks occurred two hours later than usual as the effects of secondary formation became more important. A test for the spatial variabilities shows that PM10 - 2.5, which is known to be greatly influenced by local effects, is lower in its correlation coeffic ient and higher in its coefficient of divergence (COD, which serves as an indicator for spatial variability) than PM2.5, albeit that the difference between the two is small. The average COD of PM2.5 among monitoring stations was about 0.2 but was lowered t o 0.13 when considering high PM2.5 days only, which signifies that spatial uniformity increases significantly.« less

Chemical characteristic and toxicity assessment of particle associated PAHs for the short-term anthropogenic activity event: During the Chinese New Year's Festival in 2013.

PubMed

Shi, Guo-Liang; Liu, Gui-Rong; Tian, Ying-Ze; Zhou, Xiao-Yu; Peng, Xing; Feng, Yin-Chang

2014-06-01

PM10 and PM2.5 samples were simultaneously collected during a period which covered the Chinese New Year's (CNY) Festival. The concentrations of particulate matter (PM) and 16 polycyclic aromatic hydrocarbons (PAHs) were measured. The possible source contributions and toxicity risks were estimated for Festival and non-Festival periods. According to the diagnostic ratios and Multilinear Engine 2 (ME2), three sources were identified and their contributions were calculated: vehicle emission (48.97% for PM10, 53.56% for PM2.5), biomass & coal combustion (36.83% for PM10, 28.76% for PM2.5), and cook emission (22.29% for PM10, 27.23% for PM2.5). An interesting result was found: although the PAHs are not directly from the fireworks display, they were still indirectly influenced by biomass combustion which is affiliated with the fireworks display. Additionally, toxicity risks of different sources were estimated by Multilinear Engine 2-BaP equivalent (ME2-BaPE): vehicle emission (54.01% for PM10, 55.42% for PM2.5), cook emission (25.59% for PM10, 29.05% for PM2.5), and biomass & coal combustion source (20.90% for PM10, 14.28% for PM2.5). It is worth to be noticed that the toxicity contribution of cook emission was considerable in Festival period. The findings can provide useful information to protect the urban human health, as well as develop the effective air control strategies in special short-term anthropogenic activity event. Copyright © 2014 Elsevier B.V. All rights reserved.

Seasonal contribution of assessed sources to submicron and fine particulate matter in a Central European urban area.

PubMed

Samek, Lucyna; Stegowski, Zdzislaw; Styszko, Katarzyna; Furman, Leszek; Fiedor, Joanna

2018-05-30

This study presents the air pollution findings of the submicron (PM1) and fine (PM2.5) particulate matter. The submicron particles are entirely absorbed by the human body and they cause the greatest health risk. For the PM2.5 concentration, there are yearly and/or daily limit values regulations by the European Union (EU) and World Health Organization (WHO). There are no such regulations for PM1 but for health risk reason the knowledge of its concentration is important. This paper presents the seasonal concentration contribution of PM1 and PM2.5, their chemical composition and assessed three basic sources. Daily samples of both fractions were collected from 2nd July 2016 to 27th February 2017 in Krakow, Poland. Apart from PM1 and PM2.5 the concentration of 16 elements, 8 ions and BC for each samples were measured. Based on these chemical species the positive matrix factorization (PMF) receptor modeling was used for the determination of three main sources contribution to the PM1 and PM2.5 concentrations. Daily average concentrations of PM2.5 were 12 μg/m 3 in summer and 60 μg/m 3 in winter. For PM1 it was 6.9 μg/m 3 in summer and 17.3 μg/m 3 in winter. These data show a significant difference in percentage contribution of PM1 in PM2.5 in summer (58%) and in winter (29%). For the combustion source, the concentrations calculated from PMF modeling in winter were 4.8 μg/m 3 for PM1 and 31 μg/m 3 for PM2.5. In summer, the concentrations were smaller than 1 μg/m 3 for both fractions. Secondary aerosols' concentration for PM1 was 3.4 μg/m 3 in summer and 11 μg/m 3 in winter - for PM2.5 these were 7.1 μg/m 3 and 17 μg/m 3 respectively. The third source - soil, industry and traffic together, had small seasonal variation: for PM1 it was from 1.4 to 1.8 μg/m 3 and for PM2.5 from 4.7 to 7.9 μg/m 3 . Copyright © 2018 Elsevier Ltd. All rights reserved.

78 FR 27071 - Approval and Promulgation of Air Quality Implementation Plans; Alaska: Mendenhall Valley...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-09

... lungs and cause serious adverse health effects. People with heart or lung diseases, children and older...) submitted with the Mendenhall Valley NAA PM 10 LMP, for base year 2004 and projected year 2018, identifies... projected to remain close to that level through 2018. Fugitive dust emissions from travel on unpaved roads...

Outdoor air pollution and uncontrolled asthma in the San Joaquin Valley, California.

PubMed

Meng, Ying-Ying; Rull, Rudolph P; Wilhelm, Michelle; Lombardi, Christina; Balmes, John; Ritz, Beate

2010-02-01

The San Joaquin Valley (SJV) in California ranks among the worst in the USA in terms of air quality, and its residents report some of the highest rates of asthma symptoms and asthma-related emergency department (ED) visits and hospitalisations in California. Using California Health Interview Survey data, the authors examined associations between air pollution and asthma morbidity in this region. Eligible subjects were SJV residents (2001 California Health Interview Survey) who reported physician-diagnosed asthma (n=1502, 14.6%). The authors considered two outcomes indicative of uncontrolled asthma: (1) daily or weekly asthma symptoms and (2) asthma-related ED visits or hospitalisation in the past year. Based on residential zip code, subjects were assigned annual average concentrations of ozone, PM(10) and PM(2.5) for the 1-year period prior to the interview date from their closest government air monitoring station within an 8 km (5 miles) radius. Adjusting for age, gender, race/ethnicity, poverty level and insurance status, the authors observed increased odds of experiencing daily or weekly asthma symptoms for ozone, PM(10) and PM(2.5) (OR(ozone) 1.23, 95% CI 0.94 to 1.60 per 10 ppb; OR(PM10) 1.29, 95% CI 1.05 to 1.57 per 10 microg/m(3); and OR(PM2.5) 1.82; 95% CI 1.11 to 2.98 per 10 microg/m(3)). The authors also observed increased odds of asthma-related ED visits or hospitalisations for ozone (OR 1.49, 95% CI 1.05 to 2.11 per 10 ppb) and a 29% increase in odds for PM(10) (OR 1.29, 95% CI 0.99 to 1.69 per 10 microg/m(3)). Overall, these findings suggest that individuals with asthma living in areas of the SJV with high ozone and particulate pollution levels are more likely to have frequent asthma symptoms and asthma-related ED visits and hospitalisations.

A health-based assessment of particulate air pollution in urban areas of Beijing in 2000-2004.

PubMed

Zhang, Minsi; Song, Yu; Cai, Xuhui

2007-04-15

Particulate air pollution is a serious problem in Beijing. The annual concentration of particulate matter with aerodynamic diameter less than 10 microm (PM(10)), ranging from 141 to 166 microg m(-3) in 2000-2004, could be very harmful to human health. In this paper, we presented the mortality and morbidity effects of PM(10) pollution based on statistical data and the epidemiological exposure-response function. The economic costs to health during the 5 years were estimated to lie between US$1670 and $3655 million annually, accounting for about 6.55% of Beijing's gross domestic product each year. The total costs were apportioned into two parts caused by: the local emissions and long-range transported pollution. The contribution from local emissions dominated the total costs, accounting on average for 3.60% of GDP. However, the contributions from transported pollution cannot be neglected, and the relative percentage to the total costs from the other regions could account for about 45%. An energy policy and effective measures should be proposed to reduce particulate matter, especially PM(2.5) pollution in Beijing to protect public health. The Beijing government also needs to cooperate with the other local governments to reduce high background level of particulate air pollution.

Insights into organic-aerosol sources via a novel laser-desorption/ionization mass spectrometry technique applied to one year of PM10 samples from nine sites in central Europe

NASA Astrophysics Data System (ADS)

Daellenbach, Kaspar R.; El-Haddad, Imad; Karvonen, Lassi; Vlachou, Athanasia; Corbin, Joel C.; Slowik, Jay G.; Heringa, Maarten F.; Bruns, Emily A.; Luedin, Samuel M.; Jaffrezo, Jean-Luc; Szidat, Sönke; Piazzalunga, Andrea; Gonzalez, Raquel; Fermo, Paola; Pflueger, Valentin; Vogel, Guido; Baltensperger, Urs; Prévôt, André S. H.

2018-02-01

We assess the benefits of offline laser-desorption/ionization mass spectrometry in understanding ambient particulate matter (PM) sources. The technique was optimized for measuring PM collected on quartz-fiber filters using silver nitrate as an internal standard for m/z calibration. This is the first application of this technique to samples collected at nine sites in central Europe throughout the entire year of 2013 (819 samples). Different PM sources were identified by positive matrix factorization (PMF) including also concomitant measurements (such as NOx, levoglucosan, and temperature). By comparison to reference mass spectral signatures from laboratory wood burning experiments as well as samples from a traffic tunnel, three biomass burning factors and two traffic factors were identified. The wood burning factors could be linked to the burning conditions; the factors related to inefficient burns had a larger impact on air quality in southern Alpine valleys than in northern Switzerland. The traffic factors were identified as primary tailpipe exhaust and most possibly aged/secondary traffic emissions. The latter attribution was supported by radiocarbon analyses of both the organic and elemental carbon. Besides these sources, factors related to secondary organic aerosol were also separated. The contribution of the wood burning emissions based on LDI-PMF (laser-desorption/ionization PMF) correlates well with that based on AMS-PMF (aerosol mass spectrometer PMF) analyses, while the comparison between the two techniques for other components is more complex.

Estimation of vehicular emissions using dynamic emission factors: A case study of Delhi, India

NASA Astrophysics Data System (ADS)

Mishra, Dhirendra; Goyal, P.

2014-12-01

The estimation of vehicular emissions depends mainly on the values of emission factors, which are used for the development of a comprehensive emission inventory of vehicles. In this study the variations of emission factors as well as the emission rates have been studied in Delhi. The implementation of compressed natural gas (CNG), in the diesel and petrol, public vehicles in the year 2001 has changed the complete air quality scenario of Delhi. The dynamic emission factors of criteria pollutants viz. carbon monoxide (CO), nitrogen oxide (NOx) and particulate matter (PM10) for all types of vehicles have been developed after, which are based on the several factors such as regulated emission limits, number of vehicle deterioration, vehicle increment, vehicle age etc. These emission factors are found to be decreased continuously throughout the study years 2003-2012. The International Vehicle Emissions (IVE) model is used to estimate the emissions of criteria pollutants by utilizing a dataset available from field observations at different traffic intersections in Delhi. Thus the vehicular emissions, based on dynamic emission factors have been estimated for the years 2003-2012, which are found to be comparable with the monitored concentrations at different locations in Delhi. It is noticed that the total emissions of CO, NOx, and PM10 are increased by 45.63%, 68.88% and 17.92%, respectively up to the year 2012 and the emissions of NOx and PM10 are grown continuously with an annual average growth rate of 5.4% and 1.7% respectively.

Trends in arsenic levels in PM10 and PM 2.5 aerosol fractions in an industrialized area.

PubMed

García-Aleix, J R; Delgado-Saborit, J M; Verdú-Martín, G; Amigó-Descarrega, J M; Esteve-Cano, V

2014-01-01

Arsenic is a toxic element that affects human health and is widely distributed in the environment. In the area of study, the main Spanish and second largest European industrial ceramic cluster, the main source of arsenic aerosol is related to the impurities in some boracic minerals used in the ceramic process. Epidemiological studies on cancer occurrence in Spain points out the study region as one with the greater risk of cancer. Concentrations of particulate matter and arsenic content in PM10 and PM2.5 were measured and characterized by ICP-MS in the area of study during the years 2005-2010. Concentrations of PM10 and its arsenic content range from 27 to 46 μg/m(3) and from 0.7 to 6 ng/m(3) in the industrial area, respectively, and from 25 to 40 μg/m(3) and from 0.7 to 2.8 ng/m(3) in the urban area, respectively. Concentrations of PM2.5 and its arsenic content range from 12 to 14 μg/m(3) and from 0.5 to 1.4 ng/m(3) in the urban background area, respectively. Most of the arsenic content is present in the fine fraction, with ratios of PM2.5/PM10 in the range of 0.65-0.87. PM10, PM2.5, and its arsenic content show a sharp decrease in recent years associated with the economic downturn, which severely hit the production of ceramic materials in the area under study. The sharp production decrease due to the economic crisis combined with several technological improvements in recent years such as substitution of boron, which contains As impurities as raw material, have reduced the concentrations of PM10, PM2.5, and As in air to an extent that currently meets the existing European regulations.

Long-Term Fine Particulate Matter Exposure and Major Depressive Disorder in a Community-Based Urban Cohort

PubMed Central

Kim, Kyoung-Nam; Lim, Youn-Hee; Bae, Hyun Joo; Kim, Myounghee; Jung, Kweon; Hong, Yun-Chul

2016-01-01

Background: Previous studies have associated short-term air pollution exposure with depression. Although an animal study showed an association between long-term exposure to particulate matter ≤ 2.5 μm (PM2.5) and depression, epidemiological studies assessing the long-term association are scarce. Objective: We aimed to determine the association between long-term PM2.5 exposure and major depressive disorder (MDD). Methods: A total of 27,270 participants 15–79 years of age who maintained an address within the same districts in Seoul, Republic of Korea, throughout the entire study period (between 2002 and 2010) and without a previous MDD diagnosis were analyzed. We used three district-specific exposure indices as measures of long-term PM2.5 exposure. Cox proportional hazards models adjusted for potential confounding factors and measured at district and individual levels were constructed. We further conducted stratified analyses according to underlying chronic diseases such as diabetes mellitus, cardiovascular disease, and chronic obstructive pulmonary disease. Results: The risk of MDD during the follow-up period (2008–2010) increased with an increase of 10 μg/m3 in PM2.5 in 2007 [hazard ratio (HR) = 1.44; 95% CI: 1.17, 1.78], PM2.5 between 2007 and 2010 (HR = 1.59; 95% CI: 1.02, 2.49), and 12-month moving average of PM2.5 until an event or censor (HR = 1.47; 95% CI: 1.14, 1.90). The association between long-term PM2.5 exposure and MDD was greater in participants with underlying chronic diseases than in participants without these diseases. Conclusion: Long-term PM2.5 exposure increased the risk of MDD among the general population. Individuals with underlying chronic diseases are more vulnerable to long-term PM2.5 exposure. Citation: Kim KN, Lim YH, Bae HJ, Kim M, Jung K, Hong YC. 2016. Long-term fine particulate matter exposure and major depressive disorder in a community-based urban cohort. Environ Health Perspect 124:1547–1553; http://dx.doi.org/10.1289/EHP192 PMID:27129131

Association of IL-6 with PM2.5 Components: Importance of Characterizing Filter-Based PM2.5 Following Extraction.

PubMed

Roper, Courtney; Chubb, Lauren G; Cambal, Leah; Tunno, Brett; Clougherty, Jane E; Fattman, Cheryl; Mischler, Steven E

2017-01-01

Filter-based toxicology studies are conducted to establish the biological plausibility of the well-established health impacts associated with fine particulate matter (PM 2.5 ) exposure. Ambient PM 2.5 collected on filters is extracted into solution for toxicology applications, but frequently, characterization is nonexistent or only performed on filter-based PM 2.5 , without consideration of compositional differences that occur during the extraction processes. To date, the impact of making associations to measured components in ambient instead of extracted PM 2.5 has not been investigated. Filter-based PM 2.5 was collected at locations ( n = 5) and detailed characterization of both ambient and extracted PM 2.5 was performed. Alveolar macrophages (AMJ2-C11) were exposed (3, 24, and 48 h) to PM 2.5 and the pro-inflammatory cytokine interleukin (IL)-6 was measured. IL-6 release differed significantly between PM 2.5 collected from different locations; surprisingly, IL-6 release was highest following treatment with PM 2.5 from the lowest ambient concentration location. IL-6 was negatively correlated with the sum of ambient metals analyzed, as well as with concentrations of specific constituents which have been previously associated with respiratory health effects. However, positive correlations of IL-6 with extracted concentrations indicated that the negative associations between IL-6 and ambient concentrations do not accurately represent the relationship between inflammation and PM 2.5 exposure. Additionally, seven organic compounds had significant associations with IL-6 release when considering ambient concentrations, but they were not detected in the extracted solution. Basing inflammatory associations on ambient concentrations that are not necessarily representative of in vitro exposures creates misleading results; this study highlights the importance of characterizing extraction solutions to conduct accurate health impact research.

Satellite-Based Estimates of Long-Term Exposure to Fine Particles and Association with Mortality in Elderly Hong Kong Residents

PubMed Central

Wong, Chit Ming; Tsang, Hilda; Thach, Thuan Quoc; Thomas, G. Neil; Lam, Kin Bong Hubert; Chan, King Pan; Yang, Lin; Lau, Alexis K.H.; Ayres, Jon G.; Lee, Siu Yin; Man Chan, Wai; Hedley, Anthony J.; Lam, Tai Hing

2015-01-01

Background A limited number of studies on long-term effects of particulate matter with aerodynamic diameter < 2.5 μm (PM2.5) on health suggest it can be an important cause of morbidity and mortality. In Asia where air quality is poor and deteriorating, local data on long-term effects of PM2.5 to support policy on air quality management are scarce. Objectives We assessed long-term effects of PM2.5 on the mortality in a single Asian city. Methods For 10–13 years, we followed up a cohort of 66,820 participants ≥ 65 years of age who were enrolled and interviewed in all 18 Elderly Health Centres of the Department of Health, Hong Kong, in 1998–2001. Their residential addresses were geocoded into x- and y-coordinates, and their proxy exposures to PM2.5 at their addresses in 1 × 1 km grids were estimated from the U.S. National Aeronautics and Space Administration (NASA) satellite data. We used Cox regression models to calculate hazard ratios (HRs) of mortality associated with PM2.5. Results Mortality HRs per 10-μg/m3 increase in PM2.5 were 1.14 (95% CI: 1.07, 1.22) for all natural causes, 1.22 (95% CI: 1.08, 1.39) for cardiovascular causes, 1.42 (95% CI: 1.16, 1.73) for ischemic heart disease, 1.24 (95% CI: 1.00, 1.53) for cerebrovascular disease, and 1.05 (95% CI: 0.90, 1.22) for respiratory causes. Conclusions Our methods in using NASA satellite data provide a readily accessible and affordable approach to estimation of a sufficient range of individual PM2.5 exposures in a single city. This approach can expand the capacity to conduct environmental accountability studies in areas with few measurements of fine particles. Citation Wong CM, Lai HK, Tsang H, Thach TQ, Thomas GN, Lam KB, Chan KP, Yang L, Lau AK, Ayres JG, Lee SY, Chan WM, Hedley AJ, Lam TH. 2015. Satellite-based estimates of long-term exposure to fine particles and association with mortality in elderly Hong Kong residents. Environ Health Perspect 123:1167–1172; http://dx.doi.org/10.1289/ehp.1408264 PMID:25910279

Satellite-Based Estimates of Long-Term Exposure to Fine Particles and Association with Mortality in Elderly Hong Kong Residents.

PubMed

Wong, Chit Ming; Lai, Hak Kan; Tsang, Hilda; Thach, Thuan Quoc; Thomas, G Neil; Lam, Kin Bong Hubert; Chan, King Pan; Yang, Lin; Lau, Alexis K H; Ayres, Jon G; Lee, Siu Yin; Chan, Wai Man; Hedley, Anthony J; Lam, Tai Hing

2015-11-01

A limited number of studies on long-term effects of particulate matter with aerodynamic diameter < 2.5 μm (PM2.5) on health suggest it can be an important cause of morbidity and mortality. In Asia where air quality is poor and deteriorating, local data on long-term effects of PM2.5 to support policy on air quality management are scarce. We assessed long-term effects of PM2.5 on the mortality in a single Asian city. For 10-13 years, we followed up a cohort of 66,820 participants ≥ 65 years of age who were enrolled and interviewed in all 18 Elderly Health Centres of the Department of Health, Hong Kong, in 1998-2001. Their residential addresses were geocoded into x- and y-coordinates, and their proxy exposures to PM2.5 at their addresses in 1 × 1 km grids were estimated from the U.S. National Aeronautics and Space Administration (NASA) satellite data. We used Cox regression models to calculate hazard ratios (HRs) of mortality associated with PM2.5. Mortality HRs per 10-μg/m3 increase in PM2.5 were 1.14 (95% CI: 1.07, 1.22) for all natural causes, 1.22 (95% CI: 1.08, 1.39) for cardiovascular causes, 1.42 (95% CI: 1.16, 1.73) for ischemic heart disease, 1.24 (95% CI: 1.00, 1.53) for cerebrovascular disease, and 1.05 (95% CI: 0.90, 1.22) for respiratory causes. Our methods in using NASA satellite data provide a readily accessible and affordable approach to estimation of a sufficient range of individual PM2.5 exposures in a single city. This approach can expand the capacity to conduct environmental accountability studies in areas with few measurements of fine particles. Wong CM, Lai HK, Tsang H, Thach TQ, Thomas GN, Lam KB, Chan KP, Yang L, Lau AK, Ayres JG, Lee SY, Chan WM, Hedley AJ, Lam TH. 2015. Satellite-based estimates of long-term exposure to fine particles and association with mortality in elderly Hong Kong residents. Environ Health Perspect 123:1167-1172; http://dx.doi.org/10.1289/ehp.1408264.

The Burden of COPD Morbidity Attributable to the Interaction between Ambient Air Pollution and Temperature in Chengdu, China.

PubMed

Qiu, Hang; Tan, Kun; Long, Feiyu; Wang, Liya; Yu, Haiyan; Deng, Ren; Long, Hu; Zhang, Yanlong; Pan, Jingping

2018-03-11

Evidence on the burden of chronic obstructive pulmonary disease (COPD) morbidity attributable to the interaction between ambient air pollution and temperature has been limited. This study aimed to examine the modification effect of temperature on the association of ambient air pollutants (including particulate matter (PM) with aerodynamic diameter <10 μm (PM 10 ) and <2.5 μm (PM 2.5 ), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO) and ozone (O₃)) with risk of hospital admissions (HAs) for COPD, as well as the associated morbidity burden in urban areas of Chengdu, China, from 2015 to 2016. Based on the generalized additive model (GAM) with quasi-Poisson link, bivariate response surface model and stratification parametric model were developed to investigate the potential interactions between ambient air pollution and temperature on COPD HAs. We found consistent interactions between ambient air pollutants (PM 2.5 , PM 10 and SO₂) and low temperature on COPD HAs, demonstrated by the stronger associations between ambient air pollutants and COPD HAs at low temperatures than at moderate temperatures. Subgroup analyses showed that the elderly (≥80 years) and males were more vulnerable to this interaction. The joint effect of PM and low temperature had the greatest impact on COPD morbidity burden. Using WHO air quality guidelines as reference concentration, about 17.30% (95% CI: 12.39%, 22.19%) and 14.72% (95% CI: 10.38%, 19.06%) of COPD HAs were attributable to PM 2.5 and PM 10 exposures on low temperature days, respectively. Our findings suggested that low temperature significantly enhanced the effects of PM and SO₂ on COPD HAs in urban Chengdu, resulting in increased morbidity burden. This evidence has important implications for developing interventions to reduce the risk effect of COPD morbidity.

A method to derive the relationship between the annual and short-term air quality limits--analysis using the WHO Air Quality Guidelines for health protection.

PubMed

Lai, Hak-Kan; Hedley, Anthony J; Thach, Thuan-Quoc; Wong, Chit-Ming

2013-09-01

The World Health Organization (WHO) Air Quality Guidelines (AQG) were launched in 2006, but gaps remain in evidence on health impacts and relationships between short-term and annual AQG needed for health protection. We tested whether relationships between WHO short-term and annual AQG for particulates (PM10 and PM2.5) and nitrogen dioxide (NO2) are concordant worldwide and derived the annual limits for sulfur dioxide (SO2) and ozone (O3) based on the short-term AQG. We obtained air pollutant data over seven years (2004-2010) in seven cities from Asia-Pacific, North America and Europe. Based on probability distribution concept using maximum as the short-term limit and arithmetic mean as the annual limit, we developed a new method to derive limit value one from another in each paired limits for each pollutant with capability to account for allowable exceedances. We averaged the limit derived each year for each city, then used meta-analysis to pool the limit values in all cities. Pooled mean short-term limit for NO2 (140.5μg/m(3) [130.6-150.4]) was significantly lower than the WHO AQG of 200μg/m(3) while for PM10 (46.4μg/m(3) [95CI:42.1-50.7]) and PM2.5 (28.6μg/m(3) [24.5-32.6]) were not significantly different from the WHO AQG of 50 and 25μg/m(3) respectively. Pooled mean annual limits for SO2 and O3 were 4.6μg/m(3) [3.7-5.5] and 27.0μg/m(3) [21.7-32.2] respectively. Results were robust in various sensitivity analyses. The distribution relationships between the current WHO short-term and annual AQG are supported by empirical data from seven cities for PM10 and PM2.5, but not for NO2. The short-term AQG for NO2 should be lowered for concordance with the selected annual AQG for health protection. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Effects of particulate matter on respiratory disease and the impact of meteorological factors in Busan, Korea.

PubMed

Jo, Eun-Jung; Lee, Woo-Seop; Jo, Hyun-Young; Kim, Chang-Hoon; Eom, Jung-Seop; Mok, Jeong-Ha; Kim, Mi-Hyun; Lee, Kwangha; Kim, Ki-Uk; Lee, Min-Ki; Park, Hye-Kyung

2017-03-01

Both air pollution and weather impact hospitalization for respiratory diseases. However, few studies have investigated the contribution of weather to hospitalization related to the adverse effects of air pollution. This study analyzed the effects of particulate matter (PM) on daily respiratory-related hospital admissions, taking into account meteorological factors. Daily hospital admissions for respiratory diseases (acute bronchitis, allergic rhinitis, and asthma) between 2007 and 2010 were extracted from the National Health Insurance Corporation, Korea. Patients were divided into three age-based groups (0-15, 16-64, and ≥65 years). PM levels were obtained from 19 monitoring stations in Busan. The mean number of patients admitted for acute bronchitis, allergic rhinitis, and asthma was 5.8 ± 11.9, 4.4 ± 6.1, and 3.3 ± 3.3, respectively. During that time, the daily mean PM 10 and PM 2.5 concentrations were 49.6 ± 20.5 and 24.2 ± 10.9 μg/m 3 , respectively. The mean temperature anomaly was 7.0 ± 2.3 °C; the relative humidity was 62.0 ± 18.0%. Hospital admission rates for respiratory diseases increased with increasing PM and temperature, and with decreasing relative humidity. A multivariate analysis including PM, temperature anomaly, relative humidity, and age showed a significant increase in respiratory-related admissions with increasing PM levels and a decreasing relative humidity. Higher PM 2.5 levels had a greater effect on respiratory-related hospital admission than did PM 10 levels. Children and the elderly were the most susceptible to hospital admission for respiratory disease. PM levels and meteorological factors impacted hospitalization for respiratory diseases, especially in children and the elderly. The effect of PM on respiratory diseases increased as the relative humidity decreased. Copyright © 2017 Elsevier Ltd. All rights reserved.

An enhanced PM 2.5 air quality forecast model based on nonlinear regression and back-trajectory concentrations

NASA Astrophysics Data System (ADS)

Cobourn, W. Geoffrey

2010-08-01

An enhanced PM 2.5 air quality forecast model based on nonlinear regression (NLR) and back-trajectory concentrations has been developed for use in the Louisville, Kentucky metropolitan area. The PM 2.5 air quality forecast model is designed for use in the warm season, from May through September, when PM 2.5 air quality is more likely to be critical for human health. The enhanced PM 2.5 model consists of a basic NLR model, developed for use with an automated air quality forecast system, and an additional parameter based on upwind PM 2.5 concentration, called PM24. The PM24 parameter is designed to be determined manually, by synthesizing backward air trajectory and regional air quality information to compute 24-h back-trajectory concentrations. The PM24 parameter may be used by air quality forecasters to adjust the forecast provided by the automated forecast system. In this study of the 2007 and 2008 forecast seasons, the enhanced model performed well using forecasted meteorological data and PM24 as input. The enhanced PM 2.5 model was compared with three alternative models, including the basic NLR model, the basic NLR model with a persistence parameter added, and the NLR model with persistence and PM24. The two models that included PM24 were of comparable accuracy. The two models incorporating back-trajectory concentrations had lower mean absolute errors and higher rates of detecting unhealthy PM2.5 concentrations compared to the other models.

Characterization of Fine Particulate Matter and Associated Health Burden in Nanjing.

PubMed

Nie, Dongyang; Chen, Mindong; Wu, Yun; Ge, Xinlei; Hu, Jianlin; Zhang, Kai; Ge, Pengxiang

2018-03-27

Particulate matter (PM) air pollution has become a serious environmental problem in Nanjing and poses great health risks to local residents. In this study, characteristics of particulate matter with an aerodynamic diameter less than 2.5 μm (PM 2.5 ) over Nanjing were analyzed using hourly and daily averaged PM 2.5 concentrations and meteorological parameters collected from nine national monitoring sites during the period of March 2014 to February 2017. Then, the integrated exposure-response (IER) model was applied to assess premature mortality, years of life lost (YLL) attributable to PM 2.5 , and mortality benefits due to PM 2.5 reductions. The concentrations of PM 2.5 varied among hours, seasons and years, which can be explained by differences in emission sources, secondary formations and meteorological conditions. The decreased ratio of PM 2.5 to CO suggested that secondary contributions decreased while the relative contributions of vehicle exhaust increased from increased CO data. According to the values of attributable fractions (AF), stroke was the major cause of death, followed by ischemic heart disease (IHD), lung cancer (LC) and chronic obstructive pulmonary disease (COPD). The estimated total deaths in Nanjing due to PM 2.5 were 12,055 and 10,771, leading to 98,802 and 87,647 years of life lost in 2014 and 2015, respectively. The elderly and males had higher health risks than youngsters and females. When the PM 2.5 concentrations meet the World Health Organization (WHO) Air Quality Guidelines (AQG) of 10 μg/m³, 84% of the premature deaths would be avoided, indicating that the Nanjing government needs to adopt more stringent measure to reduce PM pollution and enhance the health benefits.

Characterization of Fine Particulate Matter and Associated Health Burden in Nanjing

PubMed Central

Nie, Dongyang; Chen, Mindong; Ge, Xinlei; Zhang, Kai; Ge, Pengxiang

2018-01-01

Particulate matter (PM) air pollution has become a serious environmental problem in Nanjing and poses great health risks to local residents. In this study, characteristics of particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) over Nanjing were analyzed using hourly and daily averaged PM2.5 concentrations and meteorological parameters collected from nine national monitoring sites during the period of March 2014 to February 2017. Then, the integrated exposure-response (IER) model was applied to assess premature mortality, years of life lost (YLL) attributable to PM2.5, and mortality benefits due to PM2.5 reductions. The concentrations of PM2.5 varied among hours, seasons and years, which can be explained by differences in emission sources, secondary formations and meteorological conditions. The decreased ratio of PM2.5 to CO suggested that secondary contributions decreased while the relative contributions of vehicle exhaust increased from increased CO data. According to the values of attributable fractions (AF), stroke was the major cause of death, followed by ischemic heart disease (IHD), lung cancer (LC) and chronic obstructive pulmonary disease (COPD). The estimated total deaths in Nanjing due to PM2.5 were 12,055 and 10,771, leading to 98,802 and 87,647 years of life lost in 2014 and 2015, respectively. The elderly and males had higher health risks than youngsters and females. When the PM2.5 concentrations meet the World Health Organization (WHO) Air Quality Guidelines (AQG) of 10 μg/m3, 84% of the premature deaths would be avoided, indicating that the Nanjing government needs to adopt more stringent measure to reduce PM pollution and enhance the health benefits. PMID:29584626

2007 Version 5.0 Technical Support Document

EPA Pesticide Factsheets

Preparation of Emissions Inventories for the Version 5.0, 2007 Emissions Modeling Platform describes how emissions based on the 2008 NEI, version 2 and were processed to represent the year 2007 in support of air quality modeling of the PM NAAQS.

Estimated Short-Term Effects of Coarse Particles on Daily Mortality in Stockholm, Sweden

PubMed Central

Johansson, Christer; Forsberg, Bertil

2011-01-01

Background: Although serious health effects associated with particulate matter (PM) with aerodynamic diameter ≤ 10 μm (PM10) and ≤ 2.5 μm (PM2.5; fine fraction) are documented in many studies, the effects of coarse PM (PM2.5–10) are still under debate. Objective: In this study, we estimated the effects of short-term exposure of PM2.5–10 on daily mortality in Stockholm, Sweden. Method: We collected data on daily mortality for the years 2000 through 2008. Concentrations of PM10, PM2.5, ozone, and carbon monoxide were measured simultaneously in central Stockholm. We used additive Poisson regression models to examine the association between daily mortality and PM2.5–10 on the day of death and the day before. Effect estimates were adjusted for other pollutants (two-pollutant models) during different seasons. Results: We estimated a 1.68% increase [95% confidence interval (CI): 0.20%, 3.15%] in daily mortality per 10-μg/m3 increase in PM2.5–10 (single-pollutant model). The association with PM2.5–10 was stronger for November through May, when road dust is most important (1.69% increase; 95% CI: 0.21%, 3.17%), compared with the rest of the year (1.31% increase; 95% CI: –2.08%, 4.70%), although the difference was not statistically significant. When adjusted for other pollutants, particularly PM2.5, the effect estimates per 10 μg/m3 for PM2.5–10 decreased slightly but were still higher than corresponding effect estimates for PM2.5. Conclusions: Our analysis shows an increase in daily mortality associated with elevated urban background levels of PM2.5–10. Regulation of PM2.5–10 should be considered, along with actions to specifically reduce PM2.5–10 emissions, especially road dust suspension, in cities. PMID:22182596

The effects of PM2.5 on asthmatic and allergic diseases or symptoms in preschool children of six Chinese cities, based on China, Children, Homes and Health (CCHH) project.

PubMed

Chen, Fei'er; Lin, Zhijing; Chen, Renjie; Norback, Dan; Liu, Cong; Kan, Haidong; Deng, Qihong; Huang, Chen; Hu, Yu; Zou, Zhijun; Liu, Wei; Wang, Juan; Lu, Chan; Qian, Hua; Yang, Xu; Zhang, Xin; Qu, Fang; Sundell, Jan; Zhang, Yinping; Li, Baizhan; Sun, Yuexia; Zhao, Zhuohui

2018-01-01

The urbanization and industrialization in China is accompanied by bad air quality, and the prevalence of asthma in Chinese children has been increasing in recent years. To investigate the associations between ambient PM 2.5 levels and asthmatic and allergic diseases or symptoms in preschool children in China, we assigned PM 2.5 exposure data from the Global Burden of Disease (GBD) project to 205 kindergartens at a spatial resolution of 0.1° × 0.1° in six cities in China (Shanghai, Nanjing, Chongqing, Changsha, Urumqi, and Taiyuan). A hierarchical multiple logistical regression model was applied to analyze the associations between kindergarten-level PM 2.5 exposure and individual-level outcomes of asthmatic and allergic symptoms. The individual-level variables, including gender, age, family history of asthma and allergic diseases, breastfeeding, parental smoking, indoor dampness, interior decoration pollution, household annual income, and city-level variable-annual temperature were adjusted. A total of 30,759 children (average age 4.6 years, 51.7% boys) were enrolled in this study. Apart from family history, indoor dampness, and decoration as predominant risk factors, we found that an increase of 10 μg/m 3 of the annual PM 2.5 was positively associated with the prevalence of allergic rhinitis by an odds ratio (OR) of 1.20 (95% confidence interval [CI] 1.11, 1.29) and diagnosed asthma by OR of 1.10 (95% CI 1.03, 1.18). Those who lived in non-urban (vs. urban) areas were exposed to more severe indoor air pollution arising from biomass combustion and had significantly higher ORs between PM 2.5 and allergic rhinitis and current rhinitis. Our study suggested that long-term exposure to PM 2.5 might increase the risks of asthmatic and allergic diseases or symptoms in preschool children in China. Compared to those living in urban areas, children living in suburban or rural areas had a higher risk of PM 2.5 exposure. Copyright © 2017 Elsevier Ltd. All rights reserved.

SAUR Inhibition of PP2C-D Phosphatases Activates Plasma Membrane H+-ATPases to Promote Cell Expansion in Arabidopsis[C][W

PubMed Central

Spartz, Angela K.; Ren, Hong; Park, Mee Yeon; Grandt, Kristin N.; Lee, Sang Ho; Murphy, Angus S.; Sussman, Michael R.; Overvoorde, Paul J.; Gray, William M.

2014-01-01

The plant hormone auxin promotes cell expansion. Forty years ago, the acid growth theory was proposed, whereby auxin promotes proton efflux to acidify the apoplast and facilitate the uptake of solutes and water to drive plant cell expansion. However, the underlying molecular and genetic bases of this process remain unclear. We have previously shown that the SAUR19-24 subfamily of auxin-induced SMALL AUXIN UP-RNA (SAUR) genes promotes cell expansion. Here, we demonstrate that SAUR proteins provide a mechanistic link between auxin and plasma membrane H+-ATPases (PM H+-ATPases) in Arabidopsis thaliana. Plants overexpressing stabilized SAUR19 fusion proteins exhibit increased PM H+-ATPase activity, and the increased growth phenotypes conferred by SAUR19 overexpression are dependent upon normal PM H+-ATPase function. We find that SAUR19 stimulates PM H+-ATPase activity by promoting phosphorylation of the C-terminal autoinhibitory domain. Additionally, we identify a regulatory mechanism by which SAUR19 modulates PM H+-ATPase phosphorylation status. SAUR19 as well as additional SAUR proteins interact with the PP2C-D subfamily of type 2C protein phosphatases. We demonstrate that these phosphatases are inhibited upon SAUR binding, act antagonistically to SAURs in vivo, can physically interact with PM H+-ATPases, and negatively regulate PM H+-ATPase activity. Our findings provide a molecular framework for elucidating auxin-mediated control of plant cell expansion. PMID:24858935

How to evaluate population management? Transforming the Care Continuum Alliance population health guide toward a broadly applicable analytical framework.

PubMed

Struijs, Jeroen N; Drewes, Hanneke W; Heijink, Richard; Baan, Caroline A

2015-04-01

Many countries face the persistent twin challenge of providing high-quality care while keeping health systems affordable and accessible. As a result, the interest for more efficient strategies to stimulate population health is increasing. A possible successful strategy is population management (PM). PM strives to address health needs for the population at-risk and the chronically ill at all points along the health continuum by integrating services across health care, prevention, social care and welfare. The Care Continuum Alliance (CCA) population health guide, which recently changed their name in Population Health Alliance (PHA) provides a useful instrument for implementing and evaluating such innovative approaches. This framework is developed for PM specifically and describes the core elements of the PM-concept on the basis of six subsequent interrelated steps. The aim of this article is to transform the CCA framework into an analytical framework. Quantitative methods are refined and we operationalized a set of indicators to measure the impact of PM in terms of the Triple Aim (population health, quality of care and cost per capita). Additionally, we added a qualitative part to gain insight into the implementation process of PM. This resulted in a broadly applicable analytical framework based on a mixed-methods approach. In the coming years, the analytical framework will be applied within the Dutch Monitor Population Management to derive transferable 'lessons learned' and to methodologically underpin the concept of PM. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Spatiotemporal patterns of particulate matter (PM) and associations between PM and mortality in Shenzhen, China.

PubMed

Zhang, Fengying; Liu, Xiaojian; Zhou, Lei; Yu, Yong; Wang, Li; Lu, Jinmei; Wang, Wuyi; Krafft, Thomas

2016-03-02

Most studies on air pollution exposure and its associations with human health in China have focused on the heavily polluted industrial areas and/or mega-cities, and studies on cities with comparatively low air pollutant concentrations are still rare. Only a few studies have attempted to analyse particulate matter (PM) for the vibrant economic centre Shenzhen in the Pearl River Delta. So far no systematic investigation of PM spatiotemporal patterns in Shenzhen has been undertaken and the understanding of pollution exposure in urban agglomerations with comparatively low pollution is still limited. We analyze daily and hourly particulate matter concentrations and all-cause mortality during 2013 in Shenzhen, China. Temporal patterns of PM (PM2.5 and PM10) with aerodynamic diameters of 2.5 (10) μm or less (or less (including particles with a diameter that equals to 2.5 (10) μm) are studied, along with the ratio of PM2.5 to PM10. Spatial distributions of PM10 and PM2.5 are addressed and associations of PM10 or PM2.5 and all-cause mortality are analyzed. Annual average PM10 and PM2.5 concentrations were 61.3 and 39.6 μg/m(3) in 2013. PM2.5 failed to meet the Class 2 annual limit of the National Ambient Air Quality Standard. PM2.5 was the primary air pollutant, with 8.8 % of days having heavy PM2.5 pollution. The daily PM2.5/PM10 ratios were high. Hourly PM2.5 concentrations in the tourist area were lower than downtown throughout the day. PM10 and PM2.5 concentrations were higher in western parts of Shenzhen than in eastern parts. Excess risks in the number of all-cause mortality with a 10 μg/m(3) increase of PM were 0.61 % (95 % confidence interval [CI]: 0.50-0.72) for PM10, and 0.69 % (95 % CI: 0.55-0.83) for PM2.5, respectively. The greatest ERs of PM10 and PM2.5 were in 2-day cumulative measures for the all-cause mortality, 2-day lag for females and the young (0-65 years), and L02 for males and the elder (>65 years). PM2.5 had higher risks on all-cause mortality than PM10. Effects of high PM pollution on mortality were stronger in the elder and male. Our findings provide additional relevant information on air quality monitoring and associations of PM and human health, valuable data for further scientific research in Shenzhen and for the on-going discourse on improving environmental policies.

The Characteristics of Air Pollutants during Two Distinct Episodes of Fireworks Burning in a Valley City of North China.

PubMed

Song, Yang; Wan, Xiaoming; Bai, Shuoxin; Guo, Dong; Ren, Ci; Zeng, Yu; Li, Yirui; Li, Xuewen

2017-01-01

The elevation and dissipation of pollutants after the ignition of fireworks in different functional areas of a valley city were investigated. The Air Quality Index (AQI) as well as inter-day and intra-day concentrations of various air pollutants (PM10, PM2.5, SO2, NO2, CO, O3) were measured during two episodes that took place during Chinese New Year festivities. For the special terrain of Jinan, the mean concentrations of pollutants increased sharply within 2-4 h of the firework displays, and concentrations were 4-6 times higher than the usual levels. It took 2-3 d for the pollutants to dissipate to background levels. Compared to Preliminary Eve (more fireworks are ignited on New Year's Eve, but the amounts of other human activities are also lesser), the primary pollutants PM2.5, PM10, and CO reached higher concentrations on New Year's Eve, and the highest concentrations of these pollutants were detected in living quarters. All areas suffered from serious pollution problems on New Year's Eve (rural = urban for PM10, but rural > urban for PM2.5). However, SO2 and NO2 levels were 20%-60% lower in living quarters and industrial areas compared to the levels in these same areas on Preliminary Eve. In contrast to the other pollutants, O3 concentrations fell instead of rising with the firework displays. Interactions between firework displays and other human activities caused different change trends of pollutants. PM2.5 and PM10 were the main pollutants, and the rural living quarter had some of the highest pollution levels.

Assessment of the health impacts of particulate matter characteristics.

PubMed

Bell, Michelle L

2012-01-01

While numerous studies have demonstrated that shortterm exposure to particulate matter (PM*) is associated with adverse health effects, the characteristics of PM that cause harm are not well understood, and PM toxicity may vary by its chemical composition. This study investigates whether spatial and temporal patterns in PM health effect estimates based on total mass can be explained by spatial and temporal heterogeneity in the chemical composition of the particles. A database of 52 chemical components of PM with an aerodynamic diameter < or = 2.5 pm (PM2.5) was constructed for 187 U.S. counties, for 2000 through 2005, based on data from U.S. Environmental Protection Agency (U.S. EPA) monitoring networks. Components that covary with PM2.5 total mass and/or are large contributors to PM2.5, total mass were identified using actual and seasonally detrended data. Using Bayesian hierarchical modeling, seasonal and temporal variation in PM2.5 and the risk of total, cardiovascular, and respiratory hospital admissions were investigated for persons > or = 65 years in 202 U.S. counties for 1999 through 2005. Seasonal variation was investigated using three model structures with different underlying assumptions about the relationship between PM2.5 and hospitalizations. The findings of this study indicate higher effects in winter for both causes of hospitalization, and higher effects in the Northeast for cardiovascular admissions, although 53% of the counties were in this region. Higher PM2.5 effect estimates for cardiovascular or respiratory hospitalizations were observed in seasons and counties with a higher PM2.5 content of nickel (Ni), vanadium (V), or EC. Mortality effect estimates for PM with an aerodynamic diameter < or = 10 pm (PM10) were higher in seasons and counties with higher PM2.5 Ni content. The association between the Ni content of PM2.5 and effect estimates for cardiovascular hospitalization was robust to adjustment by EC, V, or both EC and V. An interquartile range (IQR) increase in the fraction of PM2.5 that is Ni was associated with a 14.9% (PI, 3.4-26.4) increase in the relative rates of cardiovascular hospital admissions associated with PM2.5 total mass adjusted for EC and V. No associations were observed between PM total mass health effect estimates and community-level variables for socioeconomic status, racial composition, or urbanicity. Communities with a higher prevalence of central AC had lower PM2.5 effect estimates for cardiovascular hospital admissions. The findings of this study indicate strong spatial and temporal variation in the chemical composition of the particle mixture and in the regional and seasonal variation in health effect estimates for PM2.5 total mass. The chemical composition of particles partially explained the heterogeneity of effect estimates. Observed associations could be related to the components themselves, to other components, or to a combination of components that share similar sources. The findings do not exclude the possibility that other components or characteristics of PM are harmful. The limitations of this study include the use of community-level aggregated data for exposure and for the variables used to investigate alternate hypotheses. Also, particle components and chemical forms (e.g., ammonium sulfate) not measured in the U.S. EPA database were not included. PM10 results in particular should be viewed with caution as the time frame of measurement and PM size fraction are different for the chemical composition and health effects data. A better understanding of the particular chemical components or sources that are most harmful to health can help decision-makers develop more targeted air pollution regulations and can aid in understanding the biological mechanisms by which air pollution-related health effects occur, thereby informing future research.

A GIS based emissions inventory at 1 km × 1 km spatial resolution for air pollution analysis in Delhi, India

NASA Astrophysics Data System (ADS)

Guttikunda, Sarath K.; Calori, Giuseppe

2013-03-01

In Delhi, between 2008 and 2011, at seven monitoring stations, the daily average of particulates with diameter <2.5 μm (PM2.5) was 123 ± 87 μg m-3 and particulates with diameter <10 μm (PM10) was 208 ± 137 μg m-3. The bulk of the pollution is due to motorization, power generation, and construction activities. In this paper, we present a multi-pollutant emissions inventory for the National Capital Territory of Delhi, covering the main district and its satellite cities - Gurgaon, Noida, Faridabad, and Ghaziabad. For the base year 2010, we estimate emissions (to the nearest 000's) of 63,000 tons of PM2.5, 114,000 tons of PM10, 37,000 tons of sulfur dioxide, 376,000 tons of nitrogen oxides, 1.42 million tons of carbon monoxide, and 261,000 tons of volatile organic compounds. The inventory is further spatially disaggregated into 80 × 80 grids at 0.01° resolution for each of the contributing sectors, which include vehicle exhaust, road dust re-suspension, domestic cooking and heating, power plants, industries (including brick kilns), diesel generator sets and waste burning. The GIS based spatial inventory coupled with temporal resolution of 1 h, was utilized for chemical transport modeling using the ATMoS dispersion model. The modeled annual average PM2.5 concentrations were 122 ± 10 μg m-3 for South Delhi; 90 ± 20 μg m-3 for Gurgaon and Dwarka; 93 ± 26 μg m-3 for North-West Delhi; 93 ± 23 μg m-3 for North-East Delhi; 42 ± 10 μg m-3 for Greater Noida; 77 ± 11 μg m-3 for Faridabad industrial area. The results have been compared to measured ambient PM pollution to validate the emissions inventory.

Accumulating Evidence about What Prospective Memory Costs Actually Reveal

ERIC Educational Resources Information Center

Strickland, Luke; Heathcote, Andrew; Remington, Roger W.; Loft, Shayne

2017-01-01

Event-based prospective memory (PM) tasks require participants to substitute an atypical PM response for an ongoing task response when presented with PM targets. Responses to ongoing tasks are often slower with the addition of PM demands ("PM costs"). Prominent PM theories attribute costs to capacity-sharing between the ongoing and PM…

[Epidemiological profile of traffic accidents in Marília, São Paulo State, Brazil, 2012].

PubMed

Biffe, Carina Rejane Fernandes; Harada, Airi; Bacco, Alexander Bocchi; Coelho, Carine Silveira; Baccarelli, João Lucas Ferrareto; Silva, Karoline Lopes; Braccialli, Luzmarina Aparecida Doretto; Beloni, Margarete; Bernardes, Maria Luiza Guidinho; Lacerda, Stephanie Ribeiro; Silva, Thainá Inoue

2017-01-01

to describe the profile of victims of traffic accidents and traffic-related deaths in Marília-SP, Brazil. this is a descriptive study, based on data from police reports (PR) and Death Certificates (DC), in 2012. 1,537 PR were gathered; among the 3,257 individuals involved in traffic accidents, 67.3% were men, and 53.3% were between 20-39 years of age; most accidents occurred on road intersections (35.2%), at 8 a.m. (6.8%), 1 p.m. (7.2%) and 7 p.m. (8.1%); motorcycle was the most involved vehicle in the accidents (47.6%); among the 78 deaths reported, 61 were men, 31 were over 50 years old, and 23 were motorcyclists; 32 fatal accidents occurred on highways. the main victims and fatal victims of traffic accidents were male motorcyclists; fatal accidents occurred mainly on highways, and the main victims were over 50 years old.

Public-health impact of outdoor air pollution for 2(nd) air pollution management policy in Seoul metropolitan area, Korea.

PubMed

Leem, Jong Han; Kim, Soon Tae; Kim, Hwan Cheol

2015-01-01

Air pollution contributes to mortality and morbidity. We estimated the impact of outdoor air pollution on public health in Seoul metropolitan area, Korea. Attributable cases of morbidity and mortality were estimated. Epidemiology-based exposure-response functions for a 10 μg/m3 increase in particulate matter (PM2.5 and PM10) were used to quantify the effects of air pollution. Cases attributable to air pollution were estimated for mortality (adults ≥ 30 years), respiratory and cardiovascular hospital admissions (all ages), chronic bronchitis (all ages), and acute bronchitis episodes (≤18 years). Environmental exposure (PM2.5 and PM10) was modeled for each 3 km × 3 km. In 2010, air pollution caused 15.9% of total mortality or approximately 15,346 attributable cases per year. Particulate air pollution also accounted for: 12,511 hospitalized cases of respiratory disease; 20,490 new cases of chronic bronchitis (adults); 278,346 episodes of acute bronchitis (children). After performing the 2(nd) Seoul metropolitan air pollution management plan, the reducible death number associated with air pollution is 14,915 cases per year in 2024. We can reduce 57.9% of death associated with air pollution. This assessment estimates the public-health impacts of current patterns of air pollution. Although individual health risks of air pollution are relatively small, the public-health consequences are remarkable. Particulate air pollution remains a key target for public-health action in the Seoul metropolitan area. Our results, which have also been used for economic valuation, should guide decisions on the assessment of environmental health-policy options.

Characteristics of PM10 and CO2 concentrations on 100 underground subway station platforms in 2014 and 2015

NASA Astrophysics Data System (ADS)

Hwang, Sung Ho; Park, Wha Me; Park, Jae Bum; Nam, Taegyun

2017-10-01

In this study, the concentrations of particulate matter 10 μm or less in diameter (PM10) and carbon dioxide (CO2) were measured in 100 underground subway stations, and the potential health risks of PM10, and environmental factors affecting these concentrations were analyzed. The concentrations were measured from May 2014 to September 2015 in stations along Seoul Metro lines 1-4. There were significantly different PM10 concentrations among the underground subway stations along lines 1, 2, 3, and 4. The PM10 concentrations were associated with the CO2 concentrations, construction years, station depths, and numbers of passengers. The underground PM10 concentrations were significantly higher than the outdoor PM10 concentrations. In addition, the PM10 concentrations were higher in the stations that were constructed in the 1970s than in those constructed after the 1970s. The PM10 and CO2 concentrations varied significantly, depending on the construction year and number of passengers. The hazard quotient is higher than the acceptable level of 1.0 μg kg-1 day for children, indicating that they are at risk of exposure to unsafe PM10 levels when travelling by the metro. Therefore, stricter management may be necessary for the stations constructed in the 1970s as well as those with higher numbers of passengers.

Is long-term particulate matter and nitrogen dioxide air pollution associated with incident monoclonal gammopathy of undetermined significance (MGUS)? An analysis of the Heinz Nixdorf Recall study.

PubMed

Orban, Ester; Arendt, Marina; Hennig, Frauke; Lucht, Sarah; Eisele, Lewin; Jakobs, Hermann; Dürig, Jan; Hoffmann, Barbara; Jöckel, Karl-Heinz; Moebus, Susanne

2017-11-01

Exposure to air pollution activates the innate immune system and influences the adaptive immune system in experimental settings. We investigated the association of residential long-term exposure to particulate matter (PM) and NO 2 air pollution with monoclonal gammopathy of undetermined significance (MGUS) as a marker of adaptive immune system activation. We used data from the baseline (2000-2003), 5-year (2006-2008) and 10-year (2011-2015) follow-up examinations of the German Heinz Nixdorf Recall cohort study of 4814 participants (45-75years). Residential exposure to PM size fractions and NO 2 was estimated by land-use regression (ESCAPE-LUR, annual mean 2008/2009) and dispersion chemistry transport models (EURAD-CTM, 3-year mean at baseline). We used logistic regression to estimate the effects of air pollutants on incident MGUS, adjusting for age, sex, education, smoking status, physical activity, and BMI. As a non-linear approach, we looked at quartiles (2-4) of the air pollutants in comparison to quartile 1. Of the 3949 participants with complete data, 100 developed MGUS during the 10-year follow-up. In the main model, only PM coarse was associated with incident MGUS (OR per IQR (1.9μg/m 3 ): 1.32, 95% CI 1.04-1.67). We further found positive associations between PM size fractions estimated by ESCAPE-LUR and incident MGUS by quartiles of exposure (OR Q4 vs Q1: PM 2.5 2.03 (1.08-3.80); PM 10 1.97 (1.05-3.67); PM coarse 1.98 (1.09-3.60)). Our results indicate that an association between long-term exposure to PM and MGUS may exist. Further epidemiologic studies are needed to corroborate this possible link. Copyright © 2017 Elsevier Ltd. All rights reserved.

Satellite remote sensing of particulate matter air quality: the cloud-cover problem.

PubMed

Christopher, Sundar A; Gupta, Pawan

2010-05-01

Satellite assessments of particulate matter (PM) air quality that use solar reflectance methods are dependent on availability of clear sky; in other words, mass concentrations of PM less than 2.5 microm in aerodynamic diameter (PM2.5) cannot be estimated from satellite observations under cloudy conditions or bright surfaces such as snow/ice. Whereas most ground monitors measure PM2.5 concentrations on an hourly basis regardless of cloud conditions, space-borne sensors can only estimate daytime PM2.5 in cloud-free conditions, therefore introducing a bias. In this study, an estimate of this clear-sky bias is provided from monthly to yearly time scales over the continental United States. One year of the Moderate Resolution Imaging Spectroradiometer (MODIS) 550-nm aerosol optical depth (AOD) retrievals from Terra and Aqua satellites, collocated with 371 U.S. Environmental Protection Agency (EPA) ground monitors, have been analyzed. The results indicate that the mean differences between PM2.5 reported by ground monitors and PM2.5 calculated from ground monitors during the satellite overpass times during cloud-free conditions are less than +/- 2.5 microg m(-3), although this value varies by season and location. The mean differences are not significant as calculated by t tests (alpha = 0.05). On the basis of this analysis, it is concluded that for the continental United States, cloud cover is not a major problem for inferring monthly to yearly PM2.5 from space-borne sensors.

Prospective Memory Deficits Are Associated With Poorer Everyday Functioning in Parkinson’s Disease

PubMed Central

Pirogovsky, Eva; Woods, Steven Paul; Filoteo, J. Vincent; Gilbert, Paul E.

2013-01-01

Although individuals with Parkinson’s disease (PD) evidence moderate deficits in prospective memory (PM), it is not known whether PM deficits confer an increased risk of poorer everyday functioning. In the current study, 33 individuals with PD and 26 demographically similar normal controls (NC) were administered performance-based and self-report measures of PM and everyday functioning, including medication and financial management. As compared to NC, PD participants demonstrated significantly lower scores on performance-based measures of PM and financial capacity, worse performance at a trend level on performance-based medication management and endorsed significantly greater self-reported declines in PM and instrumental activities of daily living (iADLs). In the PD sample, the laboratory measure of PM significantly correlated with performance-based measures of financial capacity and medication management and a self-report measure of medication management. Self-reported PM failures significantly correlated with perceived declines in iADLs, worse medication management, and poorer health-related quality of life. Although future studies are needed to examine the incremental ecological validity of PM in PD, findings from this study extend prior research by providing preliminary evidence that PM impairment may play a significant role in a range of critical everyday functions in PD. PMID:22846463

Four-Week Strategy-Based Training to Enhance Prospective Memory in Older Adults: Targeting Intention Retention Is More Beneficial than Targeting Intention Formation.

PubMed

Ihle, Andreas; Albiński, Rafal; Gurynowicz, Kamila; Kliegel, Matthias

2018-01-01

So far, training of prospective memory (PM) focused on very short instances (single sessions) and targeted the intention-formation phase only. We aimed to compare the effectiveness of 2 different 4-week strategy-based PM training types, namely imagery training (targeting the encoding of the PM intention in the intention-formation phase) versus rehearsal training (targeting the maintenance of the PM intention in the intention-retention phase) in older adults. We used a 4-week training protocol (8 sessions in total, 2 sessions per week). From the 44 participants, 21 were randomly assigned to the imagery training (vividly imagining a mental picture to memorize the connection between the PM cue words and related actions during intention formation) and 23 to the rehearsal training (rehearsing the PM cue words during intention retention). The criterion PM task was assessed before and after the training. Comparing the effectiveness of both training types, we found a significant time by training type interaction on PM accuracy in terms of PM cue detection, F(1, 42) = 6.07, p = 0.018, η2p = 0.13. Subsequent analyses revealed that the rehearsal training was more effective in enhancing PM accuracy in terms of PM cue detection than the imagery training. Strategy-based PM training in older adults targeting the maintenance of the PM intention in the intention-retention phase may be more effective in enhancing PM accuracy in terms of PM cue detection than the strategy targeting the encoding of the PM intention in the intention-formation phase. This suggests that for successful prospective remembering, older adults may need more support to keep the PM cues active in memory while working on the ongoing task than to initially encode the PM intention. © 2018 S. Karger AG, Basel.

Indoor air pollution from burning yak dung as a household fuel in Tibet

NASA Astrophysics Data System (ADS)

Xiao, Qingyang; Saikawa, Eri; Yokelson, Robert J.; Chen, Pengfei; Li, Chaoliu; Kang, Shichang

2015-02-01

Yak dung is widely used for cooking and heating in Tibet. We measured real-time concentrations of black carbon (BC) and fine particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) emitted by yak dung burning in six households with different living conditions and stove types in the Nam Co region, Tibet. We observed a much lower average BC/PM2.5 mass ratio (0.013, range 0.006-0.028) from dung combustion in this area than previously reported estimates, ranging between 0.05 and 0.11. Based on our measurements, estimated fuel use, and published emission factors of BC and PM2.5, about 0.4-1.7 Gg/year of BC is emitted by yak dung combustion in Tibet in addition to the previously estimated 0.70 Gg/year of BC for Tibetan residential sources. Our survey shows that most residents were aware of adverse health impacts of indoor yak dung combustion and approximately 2/3 of residents had already installed chimney stoves to mitigate indoor air pollution. However, our measurements reveal that, without adequate ventilation, installing a chimney may not ensure good indoor air quality. For instance, the 6-h average BC and PM2.5 concentrations in a stone house using a chimney stove were 24.5 and 873 μg/m3, respectively. We also observed a change in the BC/PM2.5 ratios before and after a snow event. The impact of dung moisture content on combustion efficiency and pollutant emissions needs further investigation.

Survival analysis of cancer risk reduction strategies for BRCA1/2 mutation carriers.

PubMed

Kurian, Allison W; Sigal, Bronislava M; Plevritis, Sylvia K

2010-01-10

Women with BRCA1/2 mutations inherit high risks of breast and ovarian cancer; options to reduce cancer mortality include prophylactic surgery or breast screening, but their efficacy has never been empirically compared. We used decision analysis to simulate risk-reducing strategies in BRCA1/2 mutation carriers and to compare resulting survival probability and causes of death. We developed a Monte Carlo model of breast screening with annual mammography plus magnetic resonance imaging (MRI) from ages 25 to 69 years, prophylactic mastectomy (PM) at various ages, and/or prophylactic oophorectomy (PO) at ages 40 or 50 years in 25-year-old BRCA1/2 mutation carriers. With no intervention, survival probability by age 70 is 53% for BRCA1 and 71% for BRCA2 mutation carriers. The most effective single intervention for BRCA1 mutation carriers is PO at age 40, yielding a 15% absolute survival gain; for BRCA2 mutation carriers, the most effective single intervention is PM, yielding a 7% survival gain if performed at age 40 years. The combination of PM and PO at age 40 improves survival more than any single intervention, yielding 24% survival gain for BRCA1 and 11% for BRCA2 mutation carriers. PM at age 25 instead of age 40 offers minimal incremental benefit (1% to 2%); substituting screening for PM yields a similarly minimal decrement in survival (2% to 3%). Although PM at age 25 plus PO at age 40 years maximizes survival probability, substituting mammography plus MRI screening for PM seems to offer comparable survival. These results may guide women with BRCA1/2 mutations in their choices between prophylactic surgery and breast screening.

Probing Emissions of Military Cargo Aircraft: Description of a Joint Field Measurement Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheng, Mengdawn; Corporan, E.; DeWitt, M.

2008-01-01

Direct emissions of NOx, volatile organic compounds, and particulate matter (PM) by aircraft contribute to the pollutant levels found in the atmosphere. Aircraft emissions can be injected at the ground level or directly at the high altitude in flight. Conversion of the precursor gases into secondary PM is one of the pathways for the increased atmospheric PM. Atmospheric PM interacts with solar radiation altering atmospheric radiation balance and potentially contributing to global and regional climate changes. Also, direct emissions of air toxics, ozone precursors and PM from aircraft in and around civilian airports and military air bases can worsen localmore » air quality in non-attainment and/or maintenance areas. These emissions need to be quantified. However, the current EPA methods for particle emission measurements from such sources, modified Method 5 and Conditional Test Method 039, are gravimetric-based, and it is anticipated that these methods will not be suitable for current and future generations of aircraft turbine engines, whose particle mass emissions are low. To evaluate measurement approaches for military aircraft emissions, two complementary projects were initiated in 2005. A joint field campaign between these two programs was executed during the first week of October 2005 at the Kentucky Air National Guard (KYANG) base in Louisville, KY. This campaign represented the first in a series of field studies for each program funded by the DoD Strategic Environmental Research and Development Program (SERDP) and provided the basis for cross-comparison of the sampling approaches and measurement techniques employed by the respective program teams. This paper describes the overall programmatic of the multi-year SERDP aircraft emissions research and presents a summary of the results from the joint field campaign.« less

77 FR 74421 - Approval and Promulgation of Air Quality Implementation Plans for PM2.5

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-14

... calculation of future year PM 2.5 design values using the SMAT assumptions contained in the modeled guidance\\4... components. Future PM 2.5 design values at specified monitoring sites were estimated by adding the future... nonattainment area, all future site-specific PM 2.5 design values were below the concentration specified in the...

Evaluation of ground-based particulate matter in association with measurements from space

NASA Astrophysics Data System (ADS)

Nakata, Makiko; Yoshida, Akihito; Sano, Itaru; Mukai, Sonoyo

2017-10-01

Air pollution is problem of deep concern to human health. In Japan, the air pollution levels experienced during the recent period of rapid economic growth have been reduced. However, fine particulate matter (PM2.5) has not yet reached the environmental standards at many monitoring stations. The Japanese environmental quality standard for PM2.5 that was ratified in 2009 lags about four decades behind other air pollutants, including sulfur dioxide, nitrogen dioxide, carbon monoxide, photochemical oxidants, and suspended particulate matter. Recently, trans-national air pollutants have been observed to cause high concentrations of PM2.5 in Japan. To obtain wide distribution of PM2.5, the satellite based PM2.5 products are extremely useful. We investigate PM2.5 concentrations measured using ground samplers in Japan and the satellite based PM2.5 products, taking into consideration various geographical and weather conditions.

Fine Particulate Matter Pollution and Risk of Community-Acquired Sepsis

PubMed Central

McClure, Leslie A.; Griffin, Russell; Al-Hamdan, Mohammad Z.; Wang, Henry E.

2018-01-01

While air pollution has been associated with health complications, its effect on sepsis risk is unknown. We examined the association between fine particulate matter (PM2.5) air pollution and risk of sepsis hospitalization. We analyzed data from the 30,239 community-dwelling adults in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort linked with satellite-derived measures of PM2.5 data. We defined sepsis as a hospital admission for a serious infection with ≥2 systemic inflammatory response (SIRS) criteria. We performed incidence density sampling to match sepsis cases with 4 controls by age (±5 years), sex, and race. For each matched group we calculated mean daily PM2.5 exposures for short-term (30-day) and long-term (one-year) periods preceding the sepsis event. We used conditional logistic regression to evaluate the association between PM2.5 exposure and sepsis, adjusting for education, income, region, temperature, urbanicity, tobacco and alcohol use, and medical conditions. We matched 1386 sepsis cases with 5544 non-sepsis controls. Mean 30-day PM2.5 exposure levels (Cases 12.44 vs. Controls 12.34 µg/m3; p = 0.28) and mean one-year PM2.5 exposure levels (Cases 12.53 vs. Controls 12.50 µg/m3; p = 0.66) were similar between cases and controls. In adjusted models, there were no associations between 30-day PM2.5 exposure levels and sepsis (4th vs. 1st quartiles OR: 1.06, 95% CI: 0.85–1.32). Similarly, there were no associations between one-year PM2.5 exposure levels and sepsis risk (4th vs. 1st quartiles OR: 0.96, 95% CI: 0.78–1.18). In the REGARDS cohort, PM2.5 air pollution exposure was not associated with risk of sepsis. PMID:29690517

Fine Particulate Matter Pollution and Risk of Community-Acquired Sepsis.

PubMed

Sarmiento, Elisa J; Moore, Justin Xavier; McClure, Leslie A; Griffin, Russell; Al-Hamdan, Mohammad Z; Wang, Henry E

2018-04-21

While air pollution has been associated with health complications, its effect on sepsis risk is unknown. We examined the association between fine particulate matter (PM 2.5 ) air pollution and risk of sepsis hospitalization. We analyzed data from the 30,239 community-dwelling adults in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort linked with satellite-derived measures of PM 2.5 data. We defined sepsis as a hospital admission for a serious infection with ≥2 systemic inflammatory response (SIRS) criteria. We performed incidence density sampling to match sepsis cases with 4 controls by age (±5 years), sex, and race. For each matched group we calculated mean daily PM 2.5 exposures for short-term (30-day) and long-term (one-year) periods preceding the sepsis event. We used conditional logistic regression to evaluate the association between PM 2.5 exposure and sepsis, adjusting for education, income, region, temperature, urbanicity, tobacco and alcohol use, and medical conditions. We matched 1386 sepsis cases with 5544 non-sepsis controls. Mean 30-day PM 2.5 exposure levels (Cases 12.44 vs. Controls 12.34 µg/m³; p = 0.28) and mean one-year PM 2.5 exposure levels (Cases 12.53 vs. Controls 12.50 µg/m³; p = 0.66) were similar between cases and controls. In adjusted models, there were no associations between 30-day PM 2.5 exposure levels and sepsis (4th vs. 1st quartiles OR: 1.06, 95% CI: 0.85⁻1.32). Similarly, there were no associations between one-year PM 2.5 exposure levels and sepsis risk (4th vs. 1st quartiles OR: 0.96, 95% CI: 0.78⁻1.18). In the REGARDS cohort, PM 2.5 air pollution exposure was not associated with risk of sepsis.

Spatial variation of PM2.5, PM10, PM2.5 absorbance and PMcoarse concentrations between and within 20 European study areas and the relationship with NO2 - Results of the ESCAPE project

NASA Astrophysics Data System (ADS)

Eeftens, Marloes; Tsai, Ming-Yi; Ampe, Christophe; Anwander, Bernhard; Beelen, Rob; Bellander, Tom; Cesaroni, Giulia; Cirach, Marta; Cyrys, Josef; de Hoogh, Kees; De Nazelle, Audrey; de Vocht, Frank; Declercq, Christophe; Dėdelė, Audrius; Eriksen, Kirsten; Galassi, Claudia; Gražulevičienė, Regina; Grivas, Georgios; Heinrich, Joachim; Hoffmann, Barbara; Iakovides, Minas; Ineichen, Alex; Katsouyanni, Klea; Korek, Michal; Krämer, Ursula; Kuhlbusch, Thomas; Lanki, Timo; Madsen, Christian; Meliefste, Kees; Mölter, Anna; Mosler, Gioia; Nieuwenhuijsen, Mark; Oldenwening, Marieke; Pennanen, Arto; Probst-Hensch, Nicole; Quass, Ulrich; Raaschou-Nielsen, Ole; Ranzi, Andrea; Stephanou, Euripides; Sugiri, Dorothee; Udvardy, Orsolya; Vaskövi, Éva; Weinmayr, Gudrun; Brunekreef, Bert; Hoek, Gerard

2012-12-01

The ESCAPE study (European Study of Cohorts for Air Pollution Effects) investigates relationships between long-term exposure to outdoor air pollution and health using cohort studies across Europe. This paper analyses the spatial variation of PM2.5, PM2.5 absorbance, PM10 and PMcoarse concentrations between and within 20 study areas across Europe.We measured NO2, NOx, PM2.5, PM2.5 absorbance and PM10 between October 2008 and April 2011 using standardized methods. PMcoarse was determined as the difference between PM10 and PM2.5. In each of the twenty study areas, we selected twenty PM monitoring sites to represent the variability in important air quality predictors, including population density, traffic intensity and altitude. Each site was monitored over three 14-day periods spread over a year, using Harvard impactors. Results for each site were averaged after correcting for temporal variation using data obtained from a reference site, which was operated year-round.Substantial concentration differences were observed between and within study areas. Concentrations for all components were higher in Southern Europe than in Western and Northern Europe, but the pattern differed per component with the highest average PM2.5 concentrations found in Turin and the highest PMcoarse in Heraklion. Street/urban background concentration ratios for PMcoarse (mean ratio 1.42) were as large as for PM2.5 absorbance (mean ratio 1.38) and higher than those for PM2.5 (1.14) and PM10 (1.23), documenting the importance of non-tailpipe emissions. Correlations between components varied between areas, but were generally high between NO2 and PM2.5 absorbance (average R2 = 0.80). Correlations between PM2.5 and PMcoarse were lower (average R2 = 0.39). Despite high correlations, concentration ratios between components varied, e.g. the NO2/PM2.5 ratio varied between 0.67 and 3.06.In conclusion, substantial variability was found in spatial patterns of PM2.5, PM2.5 absorbance, PM10 and PMcoarse. The highly standardized measurement of particle concentrations across Europe will contribute to a consistent assessment of health effects across Europe.

Multi-year objective analyses of warm season ground-level ozone and PM2.5 over North America using real-time observations and Canadian operational air quality models

NASA Astrophysics Data System (ADS)

Robichaud, A.; Ménard, R.

2013-05-01

We present multi-year objective analyses (OA) on a high spatio-temporal resolution (15 or 21 km, every hour) for the warm season period (1 May-31 October) for ground-level ozone (2002-2012) and for fine particulate matter (diameter less than 2.5 microns (PM2.5)) (2004-2012). The OA used here combines the Canadian Air Quality forecast suite with US and Canadian surface air quality monitoring sites. The analysis is based on an optimal interpolation with capabilities for adaptive error statistics for ozone and PM2.5 and an explicit bias correction scheme for the PM2.5 analyses. The estimation of error statistics has been computed using a modified version of the Hollingsworth-Lönnberg's (H-L) method. Various quality controls (gross error check, sudden jump test and background check) have been applied to the observations to remove outliers. An additional quality control is applied to check the consistency of the error statistics estimation model at each observing station and for each hour. The error statistics are further tuned "on the fly" using a χ2 (chi-square) diagnostic, a procedure which verifies significantly better than without tuning. Successful cross-validation experiments were performed with an OA set-up using 90% of observations to build the objective analysis and with the remainder left out as an independent set of data for verification purposes. Furthermore, comparisons with other external sources of information (global models and PM2.5 satellite surface derived measurements) show reasonable agreement. The multi-year analyses obtained provide relatively high precision with an absolute yearly averaged systematic error of less than 0.6 ppbv (parts per billion by volume) and 0.7 μg m-3 (micrograms per cubic meter) for ozone and PM2.5 respectively and a random error generally less than 9 ppbv for ozone and under 12 μg m-3 for PM2.5. In this paper, we focus on two applications: (1) presenting long term averages of objective analysis and analysis increments as a form of summer climatology and (2) analyzing long term (decadal) trends and inter-annual fluctuations using OA outputs. Our results show that high percentiles of ozone and PM2.5 are both following a decreasing trend overall in North America with the eastern part of United States (US) presenting the highest decrease likely due to more effective pollution controls. Some locations, however, exhibited an increasing trend in the mean ozone and PM2.5 such as the northwestern part of North America (northwest US and Alberta). The low percentiles are generally rising for ozone which may be linked to increasing emissions from emerging countries and the resulting pollution brought by the intercontinental transport. After removing the decadal trend, we demonstrate that the inter-annual fluctuations of the high percentiles are significantly correlated with temperature fluctuations for ozone and precipitation fluctuations for PM2.5. We also show that there was a moderately significant correlation between the inter-annual fluctuations of the high percentiles of ozone and PM2.5 with economic indices such as the Industrial Dow Jones and/or the US gross domestic product growth rate.

Interannual variability of ammonia concentrations over the United States: sources and implications

NASA Astrophysics Data System (ADS)

Schiferl, Luke D.; Heald, Colette L.; Van Damme, Martin; Clarisse, Lieven; Clerbaux, Cathy; Coheur, Pierre-François; Nowak, John B.; Neuman, J. Andrew; Herndon, Scott C.; Roscioli, Joseph R.; Eilerman, Scott J.

2016-09-01

The variability of atmospheric ammonia (NH3), emitted largely from agricultural sources, is an important factor when considering how inorganic fine particulate matter (PM2.5) concentrations and nitrogen cycling are changing over the United States. This study combines new observations of ammonia concentration from the surface, aboard aircraft, and retrieved by satellite to both evaluate the simulation of ammonia in a chemical transport model (GEOS-Chem) and identify which processes control the variability of these concentrations over a 5-year period (2008-2012). We find that the model generally underrepresents the ammonia concentration near large source regions (by 26 % at surface sites) and fails to reproduce the extent of interannual variability observed at the surface during the summer (JJA). Variability in the base simulation surface ammonia concentration is dominated by meteorology (64 %) as compared to reductions in SO2 and NOx emissions imposed by regulation (32 %) over this period. Introduction of year-to-year varying ammonia emissions based on animal population, fertilizer application, and meteorologically driven volatilization does not substantially improve the model comparison with observed ammonia concentrations, and these ammonia emissions changes have little effect on the simulated ammonia concentration variability compared to those caused by the variability of meteorology and acid-precursor emissions. There is also little effect on the PM2.5 concentration due to ammonia emissions variability in the summer when gas-phase changes are favored, but variability in wintertime emissions, as well as in early spring and late fall, will have a larger impact on PM2.5 formation. This work highlights the need for continued improvement in both satellite-based and in situ ammonia measurements to better constrain the magnitude and impacts of spatial and temporal variability in ammonia concentrations.

PMF and PSCF based source apportionment of PM2.5 at a regional background site in North China

NASA Astrophysics Data System (ADS)

Zong, Zheng; Wang, Xiaoping; Tian, Chongguo; Chen, Yingjun; Fu, Shanfei; Qu, Lin; Ji, Ling; Li, Jun; Zhang, Gan

2018-05-01

To apportion regional PM2.5 (atmospheric particles with aerodynamic diameter < 2.5 μm) source types and their geographic pattern in North China, 120 daily PM2.5 samples on Beihuangcheng Island (BH, a regional background site in North China) were collected from August 20th, 2014 to September 15th, 2015 showing one-year period. After the chemical analyses on carbonaceous species, water-soluble ions and inorganic elements, various approaches, such as Mann-Kendall test, chemical mass closure, ISORROPIA II model, Positive Matrix Factorization (PMF) linked with Potential Source Contribution Function (PSCF), were used to explore the PM2.5 speciation, sources, and source regions. Consequently, distinct seasonal variations of PM2.5 and its main species were found and could be explained by varying emission source characteristics. Based on PMF model, seven source factors for PM2.5 were identified, which were coal combustion + biomass burning, vehicle emission, mineral dust, ship emission, sea salt, industry source, refined chrome industry with the contribution of 48.21%, 30.33%, 7.24%, 6.63%, 3.51%, 3.2%, and 0.88%, respectively. In addition, PSCF analysis using the daily contribution of each factor from PMF result suggested that Shandong peninsula and Hebei province were identified as the high potential region for coal combustion + biomass burning; Beijing-Tianjin-Hebei (BTH) region was the main source region for industry source; Bohai Sea and East China Sea were found to be of high source potential for ship emission; Geographical region located northwest of BH Island was possessed of high probability for sea salt; Mineral dust presumably came from the region of Mongolia; Refined chrome industry mostly came from Liaoning, Jilin province; The vehicle emission was primarily of BTH region origin, centring on metropolises, such as Beijing and Tianjin. These results provided precious implications for PM2.5 control strategies in North China.

Fine particulate air pollution and all-cause mortality within the Harvard Six-Cities Study: variations in risk by period of exposure.

PubMed

Villeneuve, Paul J; Goldberg, Mark S; Krewski, Daniel; Burnett, Richard T; Chen, Yue

2002-11-01

We used Poisson regression methods to examine the relation between temporal changes in the levels of fine particulate air pollution (PM(2.5)) and the risk of mortality among participants of the Harvard Six Cities longitudinal study. Our analyses were based on 1430 deaths that occurred between 1974 and 1991 in a cohort that accumulated 105,714 person-years of follow-up. For each city, indices of PM(2.5) were derived using daily samples. Individual level data were collected on several risk factors including: smoking, education, body mass index (BMI), and occupational exposure to dusts. Time-dependent indices of PM(2.5) were created across 13 calendar periods (< 1979, 1979, 1980, em leader, 1989, >/= 1990) to explore whether recent or chronic exposures were more important predictors of mortality. The relative risk (RR) of mortality calculated using Poisson regression based on average city-specific exposures that remained constant during follow-up was 1.31 [95% confidence interval (CI) = 1.12-1.52] per 18.6 microg/m(3) of PM(2.5). This result was similar to the risk calculated using the Cox model (RR = 1.26, 95% CI = 1.08-1.46). The RR of mortality was attenuated when the Poisson regression model included a time-dependent estimate of exposure (RR = 1.19, 95% CI = 1.04-1.36). There was little variation in RR across time-dependent indices of PM(2.5). The attenuated risk of mortality that was observed with a time-dependent index of PM(2.5) is due to the combined influence of city-specific variations in mortality rates and decreasing levels of air pollution that occurred during follow-up. The RR of mortality associated with PM(2.5) did not depend on when exposure occurred in relation to death, possibly because of little variation between the time-dependent city-specific exposure indices.

On the characterization of subpixel effects for passive microwave remote sensing of snow in montane environments

NASA Astrophysics Data System (ADS)

Vander Jagt, Benjamin John

Snow and its water equivalent plays a vital role in global water and energy balances, with particular relevance in mountainous areas with arid and semi-arid climate regimes. Spaceborne passive microwave (PM) remote sensing measurements are attractive for snowpack characterization due to their continuous global coverage and historical record; over 30 years of research has been invested in the development of methods to characterize large-scale snow water resources from PM-based measurements. Historically, use of PM data for snowpack characterization in montane enviroments has been obstructed by the complex subpixel variability of snow properties within the PM measurement footprint. The main subpixel effects can be grouped as: the effect of snow microstructure (e.g. snow grain size) and stratigraphy on snow microwave emission, vegetation attenuation of PM measurements, and the sensitivity PM brightness temperature (Tb) observation to the variability of different subpixel properties at spaceborne measurement scales. This dissertation is focused on a systematic examination of these issues, which thus far have prevented the widespread integration of snow water equivalent (SWE) retrieval methods. It is meant to further our comprehension of the underlying processes at work in these rugged, remote, a hydrologically important areas. The role that snow microstructure plays in the PM retrievals of SWE is examined first. Traditional estimates of grain size are subjective and prone to error. Objective techniques to characterize grain size are described and implemented, including near infrared (NIR), stereology, and autocorrelation based approaches. Results from an intensive Colorado field study in which independent estimates of grain size and their modeled brightness temperature (Tb) emission are evaluated against PM Tb observations are included. The coarse resolution of the passive microwave measurements provides additional challenges when trying to resolve snow states via remote sensing observations. The natural heterogeneity of snowpack (e.g. depth, stratigraphy, etc) and vegetative states within the PM footprint occurs at spatial scales smaller than PM observation scales. The sensitivity to changes in snow depth given sub-pixel variability in snow and vegetation is explored and quantified using the comprehensive dataset acquired during the Cold Land Processes experiment (CLPX). Lastly, vegetation has long been an obstacle in efforts to derive snow depth and mass estimates from passive microwave (PM) measurements of brightness temperature (Tb). We introduce a vegetation transmissivity model that is derived entirely from multi-scale and multi-temporal PM Tb observations and a globally available vegetation dataset, specifically the Leaf Area Index (LAI). This newly constructed model characterizes the attenuation of PM Tb observations at frequencies typically employed for snow retrieval algorithms, as a function of LAI. Additionally, the model is used to predict how much SWE is observable within the major river basins of Colorado and the central Rockies.

Long-term trends of ambient particulate matter emission source contributions and the accountability of control strategies in Hong Kong over 1998-2008

NASA Astrophysics Data System (ADS)

Yuan, Zibing; Yadav, Varun; Turner, Jay R.; Louie, Peter K. K.; Lau, Alexis Kai Hon

2013-09-01

Despite extensive emission control measures targeting motor vehicles and to a lesser extent other sources, annual-average PM10 mass concentrations in Hong Kong have remained relatively constant for the past several years and for some air quality metrics, such as the frequency of poor visibility days, conditions have degraded. The underlying drivers for these long-term trends were examined by performing source apportionment on eleven years (1998-2008) of data for seven monitoring sites in the Hong Kong PM10 chemical speciation network. Nine factors were resolved using Positive Matrix Factorization. These factors were assigned to emission source categories that were classified as local (operationally defined as within the Hong Kong Special Administrative Region) or non-local based on temporal and spatial patterns in the source contribution estimates. This data-driven analysis provides strong evidence that local controls on motor vehicle emissions have been effective in reducing motor vehicle-related ambient PM10 burdens with annual-average contributions at neighborhood- and larger-scale monitoring stations decreasing by ˜6 μg m-3 over the eleven year period. However, this improvement has been offset by an increase in annual-average contributions from non-local contributions, especially secondary sulfate and nitrate, of ˜8 μg m-3 over the same time period. As a result, non-local source contributions to urban-scale PM10 have increased from 58% in 1998 to 70% in 2008. Most of the motor vehicle-related decrease and non-local source driven increase occurred over the period 1998-2004 with more modest changes thereafter. Non-local contributions increased most dramatically for secondary sulfate and secondary nitrate factors and thus combustion-related control strategies, including but not limited to power plants, are needed for sources located in the Pearl River Delta and more distant regions to improve air quality conditions in Hong Kong. PMF-resolved source contribution estimates were also used to examine differential contributions of emission source categories during high PM episodes compared to study-average behavior. While contributions from all source categories increased to some extent on high PM days, the increases were disproportionately high for the non-local sources. Thus, controls on emission sources located outside the Hong Kong Special Administrative Region will be needed to effectively decrease the frequency and severity of high PM episodes.

A case-crossover analysis of forest fire haze events and mortality in Malaysia

NASA Astrophysics Data System (ADS)

Sahani, Mazrura; Zainon, Nurul Ashikin; Wan Mahiyuddin, Wan Rozita; Latif, Mohd Talib; Hod, Rozita; Khan, Md Firoz; Tahir, Norhayati Mohd; Chan, Chang-Chuan

2014-10-01

The Southeast Asian (SEA) haze events due to forest fires are recurrent and affect Malaysia, particularly the Klang Valley region. The aim of this study is to examine the risk of haze days due to biomass burning in Southeast Asia on daily mortality in the Klang Valley region between 2000 and 2007. We used a case-crossover study design to model the effect of haze based on PM10 concentration to the daily mortality. The time-stratified control sampling approach was used, adjusted for particulate matter (PM10) concentrations, time trends and meteorological influences. Based on time series analysis of PM10 and backward trajectory analysis, haze days were defined when daily PM10 concentration exceeded 100 μg/m3. The results showed a total of 88 haze days were identified in the Klang Valley region during the study period. A total of 126,822 cases of death were recorded for natural mortality where respiratory mortality represented 8.56% (N = 10,854). Haze events were found to be significantly associated with natural and respiratory mortality at various lags. For natural mortality, haze events at lagged 2 showed significant association with children less than 14 years old (Odd Ratio (OR) = 1.41; 95% Confidence Interval (CI) = 1.01-1.99). Respiratory mortality was significantly associated with haze events for all ages at lagged 0 (OR = 1.19; 95% CI = 1.02-1.40). Age-and-gender-specific analysis showed an incremental risk of respiratory mortality among all males and elderly males above 60 years old at lagged 0 (OR = 1.34; 95% CI = 1.09-1.64 and OR = 1.41; 95% CI = 1.09-1.84 respectively). Adult females aged 15-59 years old were found to be at highest risk of respiratory mortality at lagged 5 (OR = 1.66; 95% CI = 1.03-1.99). This study clearly indicates that exposure to haze events showed immediate and delayed effects on mortality.

Effect of air pollution on the total bacteria and pathogenic bacteria in different sizes of particulate matter.

PubMed

Liu, Huan; Zhang, Xu; Zhang, Hao; Yao, Xiangwu; Zhou, Meng; Wang, Jiaqi; He, Zhanfei; Zhang, Huihui; Lou, Liping; Mao, Weihua; Zheng, Ping; Hu, Baolan

2018-02-01

In recent years, air pollution events have occurred frequently in China during the winter. Most studies have focused on the physical and chemical composition of polluted air. Some studies have examined the bacterial bioaerosols both indoors and outdoors. But few studies have focused on the relationship between air pollution and bacteria, especially pathogenic bacteria. Airborne PM samples with different diameters and different air quality index values were collected in Hangzhou, China from December 2014 to January 2015. High-throughput sequencing of 16S rRNA was used to categorize the airborne bacteria. Based on the NCBI database, the "Human Pathogen Database" was established, which is related to human health. Among all the PM samples, the diversity and concentration of total bacteria were lowest in the moderately or heavily polluted air. However, in the PM2.5 and PM10 samples, the relative abundances of pathogenic bacteria were highest in the heavily and moderately polluted air respectively. Considering the PM samples with different particle sizes, the diversities of total bacteria and the proportion of pathogenic bacteria in the PM10 samples were different from those in the PM2.5 and TSP samples. The composition of PM samples with different sizes range may be responsible for the variances. The relative humidity, carbon monoxide and ozone concentrations were the main factors, which affected the diversity of total bacteria and the proportion of pathogenic bacteria. Among the different environmental samples, the compositions of the total bacteria were very similar in all the airborne PM samples, but different from those in the water, surface soil, and ground dust samples. Which may be attributed to that the long-distance transport of the airflow may influence the composition of the airborne bacteria. This study of the pathogenic bacteria in airborne PM samples can provide a reference for environmental and public health researchers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Re-focusing the ethical discourse on personalized medicine: a qualitative interview study with stakeholders in the German healthcare system.

PubMed

Schleidgen, Sebastian; Marckmann, Georg

2013-05-24

In recent years, personalized medicine (PM) has become a highly regarded line of development in medicine. Yet, it is still a relatively new field. As a consequence, the discussion of its future developments, in particular of its ethical implications, in most cases can only be anticipative. Such anticipative discussions, however, pose several challenges. Nevertheless, they play a crucial role for shaping PM's further developments. Therefore, it is vital to understand how the ethical discourse on PM is conducted, i.e. on what - empirical and normative - assumptions ethical arguments are based regarding PM's current and future developments. To gather this information, we conducted a qualitative interview study with stakeholders in the German health care system. Our purposive sample included 17 representatives of basic research, clinical research, health economics, regulatory authorities, reimbursement institutions, pharmaceutical industry, patient organizations, as well as clinicians and legal experts involved in PM developments or policy making. We used an interview guide with open-ended questions and analyzed transcriptions of the interviews by means of qualitative content analysis. The respondents addressed a multitude of concerns in the context of research on as well as application of personalized preventive and therapeutic measures both on the individual and on the societal level. Interestingly, regarding future developments of PM the ethical evaluation seemed to follow the rule: the less likely its application, the more problematic a PM measure is assessed. The more likely its application, on the other hand, the less problematic it is evaluated. The results of our study suggest re-focusing the ethical discourse on PM in Germany towards a constructive ethical monitoring which ensures to include only, nevertheless all of the actual and/or potential concerns that are ethically relevant in order to allow balancing them against the actual and potential ethically relevant benefits of PM measures. To render this possible, we propose a strategy for evaluating ethical concerns in the context of PM.

Remote sensing of ambient particles in Delhi and its environs: estimation and validation

PubMed Central

KUMAR, N.; CHU, A.; FOSTER, A.

2011-01-01

Recent advances in atmospheric remote sensing offer a unique opportunity to compute indirect estimates of air quality, particularly for developing countries that lack adequate spatial–temporal coverage of air pollution monitoring. The present research establishes an empirical relationship between satellite-based aerosol optical depth (AOD) and ambient particulate matter (PM) in Delhi and its environs. The PM data come from two different sources. Firstly, a field campaign was conducted to monitor airborne particles ≤ 2.5 μm and ≤10 μm in aerodynamic diameter (PM2.5 and PM10 respectively) at 113 spatially dispersed sites from July to December 2003 using photometric samplers. Secondly, data on eight hourly PM10 and total suspended particulate (TSP) matter, collected using gravimetric samplers, from 2000 to 2005 were acquired from the Central Pollution Control Board (CPCB). The aerosol optical depths were estimated from MODIS data, acquired from NASA’s Goddard Space Flight Center Earth Sciences Distributed Active Archive Center from 2000 to 2005. Both the PM and AOD data were collocated by time and space: PM mass ± 150 min of AOD time, and ± 2.5 and 5 km radius (separately) of the centroid of the AOD pixel for the 5 and 10 km AOD, respectively. The analysis here shows that PM correlates positively with the 5 km AOD; a 1% change in the AOD explains 0.52% ± 0.20% and 0.39% ± 0.15% changes in PM2.5 within 45 and 150 min intervals (of AOD data) respectively. At a coarser spatial resolution, however, the relationship between AOD and PM is relatively weak. But, the relationship turns significantly stronger when monthly estimates are analysed over a span of six years (2000 to 2005), especially for the winter months, which have relatively stable meteorological conditions. PMID:22162895

Gravimetric analysis for PM2.5 mass concentration based on year-round monitoring at an urban site in Beijing.

PubMed

Wang, Yanli; Yang, Wen; Han, Bin; Zhang, Wenjie; Chen, Mindong; Bai, Zhipeng

2016-02-01

Daily PM2.5 (particulate matter with an aerodynamic diameter of below 2.5 μm) mass concentrations were measured by gravimetric analysis in Chinese Research Academy of Environmental Sciences (CRAES), in the northern part of the Beijing urban area, from December 2013 to April 2015. Two pairs of Teflon (T1/T2) and Quartz (Q1/Q2) samples were obtained, for a total number of 1352 valid filters. Results showed elevated pollution in Beijing, with an annual mean PM2.5 mass concentration of 102 μg/m(3). According to the calculated PM2.5 mass concentration, 50% of our sampling days were acceptable (PM2.5<75 μg/m(3)), 30% had slight/medium pollution (75-150 μg/m(3)), and 7% had severe pollution (> 250 μg/m(3)). Sampling interruption occurred frequently for the Teflon filter group (75%) in severe pollution periods, resulting in important data being missing. Further analysis showed that high PM2.5 combined with high relative humidity (RH) gave rise to the interruptions. The seasonal variation of PM2.5 was presented, with higher monthly average mass concentrations in winter (peak value in February, 422 μg/m(3)), and lower in summer (7 μg/m(3) in June). From May to August, the typical summer period, least severe pollution events were observed, with high precipitation levels accelerating the process of wet deposition to remove PM2.5. The case of February presented the most serious pollution, with monthly averaged PM2.5 of 181 μg/m(3) and 32% of days with severe pollution. The abundance of PM2.5 in winter could be related to increased coal consumption for heating needs. Copyright © 2015. Published by Elsevier B.V.

Particulate emissions calculations from fall tillage operations using point and remote sensors.

PubMed

Moore, Kori D; Wojcik, Michael D; Martin, Randal S; Marchant, Christian C; Bingham, Gail E; Pfeiffer, Richard L; Prueger, John H; Hatfield, Jerry L

2013-07-01

Soil preparation for agricultural crops produces aerosols that may significantly contribute to seasonal atmospheric particulate matter (PM). Efforts to reduce PM emissions from tillage through a variety of conservation management practices (CMPs) have been made, but the reductions from many of these practices have not been measured in the field. A study was conducted in California's San Joaquin Valley to quantify emissions reductions from fall tillage CMP. Emissions were measured from conventional tillage methods and from a "combined operations" CMP, which combines several implements to reduce tractor passes. Measurements were made of soil moisture, bulk density, meteorological profiles, filter-based total suspended PM (TSP), concentrations of PM with an equivalent aerodynamic diameter ≤10 μm (PM) and PM with an equivalent aerodynamic diameter ≤2.5 μm (PM), and aerosol size distribution. A mass-calibrated, scanning, three-wavelength light detection and ranging (LIDAR) procedure estimated PM through a series of algorithms. Emissions were calculated via inverse modeling with mass concentration measurements and applying a mass balance to LIDAR data. Inverse modeling emission estimates were higher, often with statistically significant differences. Derived PM emissions for conventional operations generally agree with literature values. Sampling irregularities with a few filter-based samples prevented calculation of a complete set of emissions through inverse modeling; however, the LIDAR-based emissions dataset was complete. The CMP control effectiveness was calculated based on LIDAR-derived emissions to be 29 ± 2%, 60 ± 1%, and 25 ± 1% for PM, PM, and TSP size fractions, respectively. Implementation of this CMP provides an effective method for the reduction of PM emissions. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Association of long-term exposure to local industry- and traffic-specific particulate matter with arterial blood pressure and incident hypertension.

PubMed

Fuks, Kateryna B; Weinmayr, Gudrun; Hennig, Frauke; Tzivian, Lilian; Moebus, Susanne; Jakobs, Hermann; Memmesheimer, Michael; Kälsch, Hagen; Andrich, Silke; Nonnemacher, Michael; Erbel, Raimund; Jöckel, Karl-Heinz; Hoffmann, Barbara

2016-08-01

Long-term exposure to fine particulate matter (PM2.5) may lead to increased blood pressure (BP). The role of industry- and traffic-specific PM2.5 remains unclear. We investigated the associations of residential long-term source-specific PM2.5 exposure with arterial BP and incident hypertension in the population-based Heinz Nixdorf Recall cohort study. We defined hypertension as systolic BP≥140mmHg, or diastolic BP≥90mmHg, or current use of BP lowering medication. Long-term concentrations of PM2.5 from all local sources (PM2.5ALL), local industry (PM2.5IND) and traffic (PM2.5TRA) were modeled with a dispersion and chemistry transport model (EURAD-CTM) with a 1km(2) resolution. We performed a cross-sectional analysis with BP and prevalent hypertension at baseline, using linear and logistic regression, respectively, and a longitudinal analysis with incident hypertension at 5-year follow-up, using Poisson regression with robust variance estimation. We adjusted for age, sex, body mass index, lifestyle, education, and major road proximity. Change in BP (mmHg), odds ratio (OR) and relative risk (RR) for hypertension were calculated per 1μg/m(3) of exposure concentration. PM2.5ALL was highly correlated with PM2.5IND (Spearman's ρ=0.92) and moderately with PM2.5TRA (ρ=0.42). In adjusted cross-sectional analysis with 4539 participants, we found positive associations of PM2.5ALL with systolic (0.42 [95%-CI: 0.03, 0.80]) and diastolic (0.25 [0.04, 0.46]) BP. Higher, but less precise estimates were found for PM2.5IND (systolic: 0.55 [-0.05, 1.14]; diastolic: 0.35 [0.03, 0.67]) and PM2.5TRA (systolic: 0.88 [-1.55, 3.31]; diastolic: 0.41 [-0.91, 1.73]). We found crude positive association of PM2.5TRA with prevalence (OR 1.41 [1.10, 1.80]) and incidence of hypertension (RR 1.38 [1.03, 1.85]), attenuating after adjustment (OR 1.19 [0.90, 1.58] and RR 1.28 [0.94, 1.72]). We found no association of PM2.5ALL and PM2.5IND with hypertension. Long-term exposures to all-source and industry-specific PM2.5 were positively related to BP. We could not separate the effects of industry-specific PM2.5 from all-source PM2.5. Estimates with traffic-specific PM2.5 were generally higher but inconclusive. Copyright © 2016. Published by Elsevier GmbH.

MASS CONCENTRATION RELATIONSHIPS FROM THE NERL RTP PARTICULATE MATTER PANEL STUDY

EPA Science Inventory

The National Exposure Research Laboratory's (NERL) Research Triangle Park (RTP) Particulate Matter (PM) Panel Study has completed a one-year investigation of personal, residential and ambient PM-related mass concentrations in two potentially susceptible subpopulations. PM2.5, P...

Trends of particulate matter (PM2.5) and chemical composition at a regional background site in the Western Mediterranean over the last nine years (2002-2010)

NASA Astrophysics Data System (ADS)

Cusack, M.; Alastuey, A.; Pérez, N.; Pey, J.; Querol, X.

2012-09-01

The time variability and long term trends of PM2.5 (particulate matter of diameter < 2.5 μm) at various regional background (RB) sites across Europe are studied and interpreted in this work. Data on mean annual levels of PM2.5 measured at Montseny (MSY, North East Spain) and various RB sites in Spain and Europe are evaluated and compared, and subsequently analysed for statistically significant trends. The MSY site registered higher average PM2.5 levels than those measured at a selection of other RB sites across Spain, Portugal, Germany and Scandinavia by percentage compared to the mean of all the stations in these countries, but lower than those measured in Switzerland, Italy and Austria. Reductions in PM2.5 were observed across all stations in Spain and Europe to varying degrees (7-49%). MSY underwent a statistically significant reduction since measurements began, indicating a year-on-year gradual decrease (-3.7 μg m-3, calculated from the final year of data compared to the mean). Similar trends were observed in other RB sites across Spain (-1.9 μg m-3). Reductions recorded in PM2.5 across Europe were varied, with many experiencing gradual, year-on-year decreases (-1.8 μg m-3). These reductions have been attributed to various causes: the introduction and implementation of pollution abatement strategies in EU member states, the effect of the current economic crisis on emissions of PM2.5 and the influence of meteorology observed during the winters of 2009 and 2010. In addition, the North Atlantic Oscillation (NAO), a large scale meteorological phenomenon most prevalent during winter, was observed to influence the frequency of Saharan dust intrusions across the Iberian Peninsula. Chemical composition of PM2.5 at MSY is characterised by high levels of organic matter (OM) and sulphate, followed by crustal material, nitrate and ammonia. Sea Spray and elemental carbon (EC) comprised a minor part of the total PM2.5 mass. Statistical trend analysis was performed on the various chemical components of PM2.5 recorded at MSY to determine which components were accountable for the decrease in PM2.5 concentration. It is shown that OM underwent the largest decrease over the time period with a statistically significant trend (-1.3 μg m-3 compared to the mean), followed by sulphate (-0.8 μg m-3), ammonium (-0.5 μg m-3) and nitrate (-0.4 μg m-3). Conversely, sea spray, EC and crustal material reductions were found to be negligible.

Assessment of the Possible Association of Air Pollutants PM10, O3, NO2 With an Increase in Cardiovascular, Respiratory, and Diabetes Mortality in Panama City

PubMed Central

Zúñiga, Julio; Tarajia, Musharaf; Herrera, Víctor; Urriola, Wilfredo; Gómez, Beatriz; Motta, Jorge

2016-01-01

Abstract In recent years, Panama has experienced a marked economic growth, and this, in turn, has been associated with rapid urban development and degradation of air quality. This study is the first evaluation done in Panama on the association between air pollution and mortality. Our objective was to assess the possible association between monthly levels of PM10, O3, and NO2, and cardiovascular, respiratory, and diabetes mortality, as well as the seasonal variation of mortality in Panama City, Panama. The study was conducted in Panama City, using air pollution data from January 2003 to December 2013. We utilized a Poisson regression model based on generalized linear models, to evaluate the association between PM10, NO2, and O3 exposure and mortality from diabetes, cardiovascular, and respiratory diseases. The sample size for PM10, NO2, and O2 was 132, 132, and 108 monthly averages, respectively. We found that levels of PM10, O3, and NO2 were associated with increases in cardiovascular, respiratory, and diabetes mortality. For PM10 levels ≥ 40 μg/m3, we found an increase in cardiovascular mortality of 9.7% (CI 5.8–13.6%), and an increase of 12.6% (CI 0.2–24.2%) in respiratory mortality. For O3 levels ≥ 20 μg/m3 we found an increase of 32.4% (IC 14.6–52.9) in respiratory mortality, after a 2-month lag period following exposure in the 65 to <74 year-old age group. For NO2 levels ≥20 μg/m3 we found an increase in respiratory mortality of 11.2% (IC 1.9–21.3), after a 2-month lag period following exposure among those aged between 65 and <74 years. There could be an association between the air pollution in Panama City and an increase in cardiovascular, respiratory, and diabetes mortality. This study confirms the urgent need to improve the measurement frequency of air pollutants in Panama. PMID:26765444

Assessment of the Possible Association of Air Pollutants PM10, O3, NO2 With an Increase in Cardiovascular, Respiratory, and Diabetes Mortality in Panama City: A 2003 to 2013 Data Analysis.

PubMed

Zúñiga, Julio; Tarajia, Musharaf; Herrera, Víctor; Urriola, Wilfredo; Gómez, Beatriz; Motta, Jorge

2016-01-01

In recent years, Panama has experienced a marked economic growth, and this, in turn, has been associated with rapid urban development and degradation of air quality. This study is the first evaluation done in Panama on the association between air pollution and mortality. Our objective was to assess the possible association between monthly levels of PM10, O3, and NO2, and cardiovascular, respiratory, and diabetes mortality, as well as the seasonal variation of mortality in Panama City, Panama.The study was conducted in Panama City, using air pollution data from January 2003 to December 2013. We utilized a Poisson regression model based on generalized linear models, to evaluate the association between PM10, NO2, and O3 exposure and mortality from diabetes, cardiovascular, and respiratory diseases. The sample size for PM10, NO2, and O2 was 132, 132, and 108 monthly averages, respectively.We found that levels of PM10, O3, and NO2 were associated with increases in cardiovascular, respiratory, and diabetes mortality. For PM10 levels ≥ 40 μg/m3, we found an increase in cardiovascular mortality of 9.7% (CI 5.8-13.6%), and an increase of 12.6% (CI 0.2-24.2%) in respiratory mortality. For O3 levels ≥ 20 μg/m3 we found an increase of 32.4% (IC 14.6-52.9) in respiratory mortality, after a 2-month lag period following exposure in the 65 to <74 year-old age group. For NO2 levels ≥20 μg/m3 we found an increase in respiratory mortality of 11.2% (IC 1.9-21.3), after a 2-month lag period following exposure among those aged between 65 and <74 years.There could be an association between the air pollution in Panama City and an increase in cardiovascular, respiratory, and diabetes mortality. This study confirms the urgent need to improve the measurement frequency of air pollutants in Panama.

Prospective memory and its correlates and predictors in schizophrenia: an extension of previous findings.

PubMed

Ungvari, Gabor S; Xiang, Yu-Tao; Tang, Wai-Kwong; Shum, David

2008-09-01

Prospective memory (PM) is the ability to remember to do something in the future without explicit prompts. Extending the number of subjects and the scope of our previously published study, this investigation examined the relationship between PM and socio-demographic and clinical factors, activities of daily living (ADL) and frontal lobe functions in patients with chronic schizophrenia. One hundred and ten Chinese schizophrenia patients, 60 from the previous study and 50 additional patients recruited for this study, and 110 matched healthy comparison subjects (HC) formed the study sample. Patients' clinical condition and activity of daily living were evaluated with the Brief Psychiatric Rating Scale (BPRS) and the Functional Needs Assessment (FNA). Time- and event-based PM tasks and three tests of prefrontal lobe functions (Design Fluency Test [DFT], Tower of London [TOL], Wisconsin Card Sorting Test [WCST]) were also administered. Patients' level of ADL and psychopathology were not associated with PM functions and only anticholinergic medications (ACM) showed a significant negative correlational relationship with PM tasks. Confirming the findings of the previous study, patients performed significantly more poorly on all two PM tasks than HC. Performance on time-based PM task significantly correlated with age, education level and DFT in HC and with age, DFT, TOL and WCST in patients. Patients' performance on the event-based PM correlated with DFT and one measure of WCST. In patients, TOL and age predicted the performance on time-based PM task; DFT and WCST predicted the event-based task. Involving a large sample of patients with matched controls, this study confirmed that PM is impaired in chronic schizophrenia. Deficient PM functions were related to prefrontal lobe dysfunction in both HC and patients but not to the patients' clinical condition, nor did they significantly affect ADL. ACMs determined certain aspects of PM.

An integrated general purpose SiPM based optical module with a high dynamic range

NASA Astrophysics Data System (ADS)

Bretz, T.; Engel, R.; Hebbeker, T.; Kemp, J.; Middendorf, L.; Peters, C.; Schumacher, J.; Šmída, R.; Veberič, D.

2018-06-01

Silicon photomultipliers (SiPMs) are semiconductor-based light-sensors offering a high gain, a mechanically and optically robust design and high photon detection efficiency. Due to these characteristics, they started to replace conventional photomultiplier tubes in many applications in recent years. This paper presents an optical module based on SiPMs designed for the application in scintillators as well as lab measurements. The module hosts the SiPM bias voltage supply and three pre-amplifiers with different gain levels to exploit the full dynamic range of the SiPMs. Two SiPMs, read-out in parallel, are equipped with light guides to increase the sensitive area. The light guides are optimized for the read-out of wavelength shifting fibers as used in many plastic scintillator detectors. The optical and electrical performance of the module is characterized in detail in laboratory measurements. Prototypes have been installed and tested in a modified version of the Scintillator Surface Detector developed for AugerPrime, the upgrade of the Pierre Auger Observatory. The SiPM module is operated in the Argentinian Pampas and first data proves its usability in such harsh environments.

The attributable risk of chronic obstructive pulmonary disease due to ambient fine particulate pollution among older adults.

PubMed

Lin, Hualiang; Qian, Zhengmin Min; Guo, Yanfei; Zheng, Yang; Ai, Siqi; Hang, Jian; Wang, Xiaojie; Zhang, Lingli; Liu, Tao; Guan, Weijie; Li, Xing; Xiao, Jianpeng; Zeng, Weilin; Xian, Hong; Howard, Steven W; Ma, Wenjun; Wu, Fan

2018-04-01

The linkage between ambient fine particle pollution (PM 2.5 ) and chronic obstructive pulmonary disease (COPD) and the attributable risk remained largely unknown. This study determined the cross-sectional association between ambient PM 2.5 and prevalence of COPD among adults ≥50 years of age. We surveyed 29,290 participants aged 50 years and above in this study. The annual average concentrations of PM 2.5 derived from satellite data were used as the exposure indicator. A mixed effect model was applied to determine the associations and the burden of COPD attributable to PM 2.5. RESULTS: Among the participants, 1872 (6.39%) were classified as COPD cases. Our analysis observed a threshold concentration of 30 μg/m 3 in the PM 2.5 -COPD association, above which we found a linear positive exposure-response association between ambient PM 2.5 and COPD. The odds ratio (OR) for each 10 μg/m 3 increase in ambient PM 2.5 was 1.21(95% CI: 1.13, 1.30). Stratified analyses suggested that males, older subjects (65 years and older) and those with lower education attainment might be the vulnerable subpopulations. We further estimated that about 13.79% (95% CI: 7.82%, 21.62%) of the COPD cases could be attributable to PM 2.5 levels higher than 30 μg/m 3 in the study population. Our analysis indicates that ambient PM 2.5 exposure could increase the risk of COPD and accounts for a substantial fraction of COPD among the study population. Copyright © 2018. Published by Elsevier Ltd.

Health Risk Assessment of Inhalable Particulate Matter in Beijing Based on the Thermal Environment

PubMed Central

Xu, Lin-Yu; Yin, Hao; Xie, Xiao-Dong

2014-01-01

Inhalable particulate matter (PM10) is a primary air pollutant closely related to public health, and an especially serious problem in urban areas. The urban heat island (UHI) effect has made the urban PM10 pollution situation more complex and severe. In this study, we established a health risk assessment system utilizing an epidemiological method taking the thermal environment effects into consideration. We utilized a remote sensing method to retrieve the PM10 concentration, UHI, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI). With the correlation between difference vegetation index (DVI) and PM10 concentration, we utilized the established model between PM10 and thermal environmental indicators to evaluate the PM10 health risks based on the epidemiological study. Additionally, with the regulation of UHI, NDVI and NDWI, we aimed at regulating the PM10 health risks and thermal environment simultaneously. This study attempted to accomplish concurrent thermal environment regulation and elimination of PM10 health risks through control of UHI intensity. The results indicate that urban Beijing has a higher PM10 health risk than rural areas; PM10 health risk based on the thermal environment is 1.145, which is similar to the health risk calculated (1.144) from the PM10 concentration inversion; according to the regulation results, regulation of UHI and NDVI is effective and helpful for mitigation of PM10 health risk in functional zones. PMID:25464132

Estimation of Fine Particulate Matter in Taipei Using Landuse Regression and Bayesian Maximum Entropy Methods

PubMed Central

Yu, Hwa-Lung; Wang, Chih-Hsih; Liu, Ming-Che; Kuo, Yi-Ming

2011-01-01

Fine airborne particulate matter (PM2.5) has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS), the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME) method. The resulting epistemic framework can assimilate knowledge bases including: (a) empirical-based spatial trends of PM concentration based on landuse regression, (b) the spatio-temporal dependence among PM observation information, and (c) site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan) from 2005–2007. PMID:21776223

Estimation of fine particulate matter in Taipei using landuse regression and bayesian maximum entropy methods.

PubMed

Yu, Hwa-Lung; Wang, Chih-Hsih; Liu, Ming-Che; Kuo, Yi-Ming

2011-06-01

Fine airborne particulate matter (PM2.5) has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS), the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME) method. The resulting epistemic framework can assimilate knowledge bases including: (a) empirical-based spatial trends of PM concentration based on landuse regression, (b) the spatio-temporal dependence among PM observation information, and (c) site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan) from 2005-2007.

33 CFR 117.757 - Townsend Inlet.

Code of Federal Regulations, 2010 CFR

2010-07-01

... March of every year. (b) From 11 p.m. on December 24 until 11 p.m. on December 25, the draw need open... the fourth Sunday in March of every year, the draw need not open for vessels. If the fourth Sunday...

Burden of Outdoor Air Pollution in Kerala, India—A First Health Risk Assessment at State Level.

PubMed

Tobollik, Myriam; Razum, Oliver; Wintermeyer, Dirk; Plass, Dietrich

2015-08-28

Ambient air pollution causes a considerable disease burden, particularly in South Asia. The objective of the study is to test the feasibility of applying the environmental burden of disease method at state level in India and to quantify a first set of disease burden estimates due to ambient air pollution in Kerala. Particulate Matter (PM) was used as an indicator for ambient air pollution. The disease burden was quantified in Years of Life Lost (YLL) for the population (30 + years) living in urban areas of Kerala. Scenario analyses were performed to account for uncertainties in the input parameters. 6108 (confidence interval (95% CI): 4150-7791) of 81,636 total natural deaths can be attributed to PM, resulting in 96,359 (95% CI: 65,479-122,917) YLLs due to premature mortality (base case scenario, average for 2008-2011). Depending on the underlying assumptions the results vary between 69,582 and 377,195 YLLs. Around half of the total burden is related to cardiovascular deaths. Scenario analyses show that a decrease of 10% in PM concentrations would save 15,904 (95% CI: 11,090-19,806) life years. The results can be used to raise awareness about air quality standards at a local level and to support decision-making processes aiming at cleaner and healthier environments.

High Contributions of Secondary Inorganic Aerosols to PM2.5 under Polluted Levels at a Regional Station in Northern China.

PubMed

Li, Yang; Tao, Jun; Zhang, Leiming; Jia, Xiaofang; Wu, Yunfei

2016-12-15

Daily PM 2.5 samples were collected at Shangdianzi (SDZ) regional site in Beijing-Tianjin-Hebei (BTH) region in 2015. Samples were subject to chemical analysis for organic carbon (OC), elemental carbon (EC), and major water-soluble inorganic ions. The annual average PM 2.5 mass concentration was 53 ± 36 μg·m -3 with the highest seasonal average concentration in spring and the lowest in summer. Water-soluble inorganic ions and carbonaceous aerosols accounted for 34% ± 15% and 33% ± 9%, respectively, of PM 2.5 mass on annual average. The excellent, good, lightly polluted, moderately polluted, and heavily polluted days based on the Air Quality Index (AQI) of PM 2.5 accounted for 40%, 42%, 11%, 4%, and 3%, respectively, of the year. The sum of the average concentration of sulfate, nitrate, and ammonium (SNA) increased from 4.2 ± 2.9 μg·m -3 during excellent days to 85.9 ± 22.4 μg·m -3 during heavily polluted days, and their contributions to PM 2.5 increased from 15% ± 8% to 49% ± 10% accordingly. In contrast, the average concentration of carbonaceous aerosols increased from 9.2 ± 2.8 μg·m -3 to 51.2 ± 14.1 μg·m -3 , and their contributions to PM 2.5 decreased from 34% ± 6% to 29% ± 7%. Potential source contribution function (PSCF) analysis revealed that the major sources for high PM 2.5 and its dominant chemical components were within the area mainly covering Shandong, Henan, and Hebei provinces. Regional pollutant transport from Shanxi province and Inner Mongolia autonomous region located in the west direction of SDZ was also important during the heating season.

The state of the service: a survey of psychiatry resident education in psychosomatic medicine.

PubMed

Heinrich, Thomas W; Schwartz, Ann C; Zimbrean, Paula C; Wright, Mark T

2013-01-01

Although required by the Accreditation Council for Graduate Medical Education, training of general psychiatry residents in Psychosomatic Medicine (PM) varies significantly between programs. In 1996, the Academy of Psychosomatic Medicine (APM) developed guidelines for residency training in PM. Since then, there has been no assessment of the status of PM training during psychiatry residency. Assessment of the current state of PM training in U.S. psychiatry residency programs. A 46-item questionnaire was sent via e-mail to 206 residency directors. Four major areas were assessed: the timing and duration of the PM rotation, level of faculty supervision, didactic curriculum, and role (or potential role) of the APM in residency education. Ninety-two surveys were returned (response rate 45%). Forty-four (54%) of the general psychiatry residencies reported the total duration of the C-L rotation as being between 3 and 6 months (including both full- and part-time rotation). Only 38 (46%) programs' residents complete their PM experience in 1 year of residency. The average Full-Time Equivalent of teaching faculty per service was 1.74 (standard deviation 0.92). Sixty-four (77%) programs have a formal didactic curriculum in C-L. Eighty-one (98%) respondents were aware of the APM. Fifty-eight (70%) had APM members among faculty. The most popular responses on how the APM could best serve training programs were the creation of a subspecialty curriculum (73%) as well as the development of a competency-based evaluation tool (66%). There is significant variation in how residents are taught PM during their training. The APM is a well-recognized organization that may define what constitutes adequate residency training in PM and may help programs fulfill the educational needs of residents. © 2013 The Academy of Psychosomatic Medicine. Published by Elsevier Inc. All rights reserved.

Stochastic univariate and multivariate time series analysis of PM2.5 and PM10 air pollution: A comparative case study for Plovdiv and Asenovgrad, Bulgaria

NASA Astrophysics Data System (ADS)

Gocheva-Ilieva, S.; Stoimenova, M.; Ivanov, A.; Voynikova, D.; Iliev, I.

2016-10-01

Fine particulate matter PM2.5 and PM10 air pollutants are a serious problem in many urban areas affecting both the health of the population and the environment as a whole. The availability of large data arrays for the levels of these pollutants makes it possible to perform statistical analysis, to obtain relevant information, and to find patterns within the data. Research in this field is particularly topical for a number of Bulgarian cities, European country, where in recent years regulatory air pollution health limits are constantly being exceeded. This paper examines average daily data for air pollution with PM2.5 and PM10, collected by 3 monitoring stations in the cities of Plovdiv and Asenovgrad between 2011 and 2016. The goal is to find and analyze actual relationships in data time series, to build adequate mathematical models, and to develop short-term forecasts. Modeling is carried out by stochastic univariate and multivariate time series analysis, based on Box-Jenkins methodology. The best models are selected following initial transformation of the data and using a set of standard and robust statistical criteria. The Mathematica and SPSS software were used to perform calculations. This examination showed measured concentrations of PM2.5 and PM10 in the region of Plovdiv and Asenovgrad regularly exceed permissible European and national health and safety thresholds. We obtained adequate stochastic models with high statistical fit with the data and good quality forecasting when compared against actual measurements. The mathematical approach applied provides an independent alternative to standard official monitoring and control means for air pollution in urban areas.

Urban versus rural health impacts attributable to PM2.5 and O3 in northern India

NASA Astrophysics Data System (ADS)

Karambelas, Alexandra; Holloway, Tracey; Kinney, Patrick L.; Fiore, Arlene M.; DeFries, Ruth; Kiesewetter, Gregor; Heyes, Chris

2018-06-01

Ambient air pollution in India contributes to negative health impacts and early death. Ground-based monitors often used to quantify health impacts are located in urban regions, yet approximately 70% of India’s population lives in rural communities. We simulate high-resolution concentrations of fine particulate matter (PM) and ozone from the regional Community Multi-scale Air Quality model over northern India, including updated estimates of anthropogenic emissions for transportation, residential combustion and location-based industrial and electrical generating emissions in a new anthropogenic emissions inventory. These simulations inform seasonal air quality and health impacts due to anthropogenic emissions, contrasting urban versus rural regions. For our northern India domain, we estimate 463 200 (95% confidence interval: 444 600–482 600) adults die prematurely each year from PM2.5 and that 37 800 (28 500–48 100) adults die prematurely each year from O3. This translates to 5.8 deaths per 10 000 attributable to air pollution out of an annual rate of 72 deaths per 10 000 (8.1% of deaths) using 2010 estimates. We estimate that the majority of premature deaths resulting from PM2.5 and O3 are in rural (383 600) as opposed to urban (117 200) regions, where we define urban as cities and towns with populations of at least 100 000 people. These findings indicate the need for rural monitoring and appropriate health studies to understand and mitigate the effects of ambient air pollution on this population in addition to supporting model evaluation.

Air pollution over the North China Plain and its implication of regional transport: A new sight from the observed evidences.

PubMed

Ge, Baozhu; Wang, Zifa; Lin, Weili; Xu, Xiaobin; Li, Jie; Ji, Dongshen; Ma, Zhiqiang

2018-03-01

High concentrations of the fine particles (PM 2.5 ) are frequently observed during all seasons over the North China Plain (NCP) region in recent years. In NCP, the contributions of regional transports to certain area, e.g. Beijing city, are often discussed and estimated by models when considering an effective air pollution controlling strategy. In this study, we selected three sites from southwest to northeast in NCP, in which the concentrations of air pollutants displayed a multi-step decreasing trend in space. An approach based on the measurement results at these sites has been developed to calculate the relative contributions of the minimal local emission (MinLEC) and the maximum regional transport (MaxRTC) to the air pollutants (e.g., SO 2 , NO 2 , CO, PM 2.5 ) in Beijing. The minimal influence of local emission is estimated by the difference of the air pollutants' concentrations between urban and rural areas under the assumption of a similar influence of regional transport. Therefore, it's convenient to estimate the contributions of local emission from regional transport based on the selective measurement results instead of the complex numerical model simulation. For the whole year of 2013, the averaged contributions of MinLEC (MaxRTC) for NO 2 , SO 2 , PM 2.5 and CO are 61.7% (30.7%), 46.6% (48%), 52.1% (40.2%) and 35.8% (45.5%), respectively. The diurnal variation of MaxRTC for SO 2 , PM 2.5 and CO shows an increased pattern during the afternoon and reached a peak (more than 50%) around 18:00, which indicates that the regional transport is the important role for the daytime air pollution in Beijing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Air pollution characteristics and health risks in Henan Province, China.

PubMed

Shen, Fuzhen; Ge, Xinlei; Hu, Jianlin; Nie, Dongyang; Tian, Li; Chen, Mindong

2017-07-01

Events of severe air pollution occurred frequently in China recently, thus understanding of the air pollution characteristics and its health risks is very important. In this work, we analyzed a two-year dataset (March 2014 - February 2016) including daily concentrations of six criteria pollutants (PM 2.5 , PM 10 , CO, SO 2 , NO 2 , and O 3 ) from 18 cities in Henan province. Results reveal the serious air pollution status in Henan province, especially the northern part, and Zhengzhou is the city with the worst air quality. Annual average PM 2.5 concentrations exceed the second grade of Chinese Ambient Air Quality Standard (75μg/m 3 ) at both 2014 and 2015. PM 2.5 is typically the major pollutant, but ozone pollution can be significant during summer. Furthermore, as the commonly used air quality index (AQI) neglects the mutual health effects from multiple pollutants, we introduced the aggregate air quality index (AAQI) and health-risk based air quality index (HAQI) to evaluate the health risks. Results show that based on HAQI, the current AQI system likely significantly underestimate the health risks of air pollution, highlighting that the general public may need stricter health protection measures. The population-weighted two-year average HAQI data further demonstrates that all population in the studied cities in Henan province live with polluted air - 72% of the population is exposed to air that is unhealthy for sensitive people, while 28% of people is exposed to air that can be harmful to healthy people; and the health risks are much greater during winter than during other seasons. Future works should further improve the HAQI algorithm, and validate the links between the clinical/epidemiologic data and the HAQI values. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of mobile source emission trends in the United States

NASA Astrophysics Data System (ADS)

Dallmann, Timothy R.; Harley, Robert A.

2010-07-01

A fuel-based approach is used to estimate exhaust emissions of nitrogen oxides (NOx) and fine particulate matter (PM2.5) from mobile sources in the United States for the years 1996-2006. Source categories considered include on-road and off-road gasoline and diesel engines. Pollutant emissions for each mobile source category were estimated by combining fuel consumption with emission factors expressed per unit of fuel burned. Over the 10-year time period that is the focus of this study, sales of gasoline and diesel fuel intended for on-road use increased by 15 and 43%, respectively. Diesel fuel use by off-road equipment increased by ˜20% over the same time period. Growth in fuel consumption offset some of the reductions in pollutant emission factors that occurred during this period. For NOx, there have been dramatic (factor of 2) decreases in emission factors for on-road gasoline engines between 1996 and 2006. In contrast, diesel NOx emission factors decreased more gradually. Exhaust PM2.5 emission factors appear to have decreased for most engine categories, but emission uncertainties are large for this pollutant. Diesel engines appear to be the dominant mobile source of both NOx and PM2.5; the diesel share of total NOx has increased over time as gasoline engine emissions have declined. Comparing fuel-based emission estimates with U.S. Environmental Protection Agency's national emission inventory led to the following conclusions: (1) total emissions of NOx and PM2.5 estimated by two different methods were similar, (2) source contributions to these totals differ significantly, with higher relative contributions coming from on-road diesel engines in this study.

Impact of latency time on survival for adolescents and young adults with a second primary malignancy.

PubMed

Goldfarb, Melanie; Rosenberg, Aaron S; Li, Qian; Keegan, Theresa H M

2018-03-15

The adverse impact of second primary malignancies (SPMs) on survival is substantial for adolescents and young adults (AYAs; ie, those 15-39 years old). No studies have evaluated whether the latency time between the first malignancy (the primary malignancy [PM]) and the SPM affects cancer-specific survival (CSS). A multivariate Cox proportional hazards regression with Surveillance, Epidemiology, and End Results data for 13 regions from 1992 to 2008 was used to ascertain whether the latency time (1-5 vs ≥ 6 years) to the development of an SPM affected the CSS and overall survival with respect to either the PM or SPM for AYAs with common SPMs. The majority of 1515 AYAs with an SPM had their PM diagnosed between the ages of 26 and 39 years (74.2%) and an SPM diagnosed within 1 to 5 years (72.9%) of the PM's diagnosis. Overall, AYAs that developed an SPM 1 to 5 years after the diagnosis (vs ≥ 6 years) had an increased risk of death from cancer (hazard ratio [HR], 2.52; 95% confidence interval [CI], 1.92-3.29) as well as any cause (HR, 2.60; 95% CI, 2.04-3.32). Specifically, for AYAs with an SPM that was leukemia or a colorectal, breast, or central nervous system malignancy, a shorter latency time (1-5 years) from their PM diagnosis was associated with an overall significantly increased risk of death (2.6-fold) from either their PM or that particular SPM. However, latency did not appear to affect the CSS with respect to either the PM or SPM for AYA patients with a lymphoma or sarcoma SPM. Most AYAs who develop an SPM do so within 1 to 5 years of their primary cancer diagnosis, and they have an increased risk of death from cancer in comparison with AYAs with an SPM developing after longer survivorship intervals. Cancer 2018;124:1260-8. © 2017 American Cancer Society. © 2017 American Cancer Society.

Influence of advections of particulate matter from biomass combustion on specific-cause mortality in Madrid in the period 2004-2009.

PubMed

Linares, C; Carmona, R; Tobías, A; Mirón, I J; Díaz, J

2015-05-01

Approximately, 20 % of particulate and aerosol emissions into the urban atmosphere are of natural origin (including wildfires and Saharan dust). During these natural episodes, PM10 and PM2.5 levels usually exceed World Health Organisation (WHO) health protection thresholds. This study sought to evaluate the possible effect of advections of particulate matter from biomass fuel combustion on daily specific-cause mortality among the general population and the segment aged ≥ 75 years in Madrid. Ecological time-series study in the city of Madrid from January 01, 2004 to December 31, 2009. The dependent variable analysed was daily mortality due to natural (ICD-10:A00-R99), circulatory (ICD-10:I00-I99), and respiratory (ICD-10:J00-J99) causes in the population, both general and aged ≥ 75 years. The following independent and control variables were considered: a) daily mean PM2.5 and PM10 concentrations; b) maximum daily temperature; c) daily mean O3 and NO2 concentrations; d) advection of particulate matter from biomass combustion ( http://www.calima.ws/ ), using a dichotomous variable and e) linear trend and seasonalities. We conducted a descriptive analysis, performed a test of means and, to ascertain relative risk, fitted a model using autoregressive Poisson regression and stratifying by days with and without biomass advection, in both populations. Of the 2192 days analysed, biomass advection occurred on 56, with mean PM2.5 and PM10 values registering a significant increase during these days. PM10 had a greater impact on organic mortality with advection (RRall ages = 1.035 [1.011-1.060]; RR  ≥  75 years = 1.066 [1.031-1.103]) than did PM2.5 without advection (RRall ages = 1.017 [1.009-1.025]; RR  ≥  75 years = 1.012 [1.003-1.022]). Among specific causes, respiratory-though not circulatory-causes were associated with PM10 on days with advection in ≥ 75 year age group. PM10, rather than PM2.5, were associated with an increase in natural cause mortality on days with advection of particulate matter from biomass combustion, particularly in the ≥ 75 year age group.

Use of Visual Range Measurements to Predict PM2.5 Exposures in Southwest Asia and Afghanistan

PubMed Central

Masri, Shahir; Garshick, Eric; Hart, Jaime; Bouhamra, Walid; Koutrakis, Petros

2016-01-01

Military personnel deployed to Southwest Asia and Afghanistan were exposed to high levels of ambient particulate matter (PM) indicating the potential for exposure-related health effects. However, historical quantitative ambient PM exposure data for conducting epidemiological health studies are unavailable due to a lack of monitoring stations. Since visual range is proportional to particle light extinction (scattering and absorption), visibility can serve as a surrogate for PM2.5 concentrations where ground measurements are not available. We used data on visibility, relative humidity (RH), and PM2.5 ground measurements collected in Kuwait from years 2004 to 2005 to establish the relationship between PM2.5 and visibility. Model validation obtained by regressing trimester average PM2.5 predictions against PM2.5 measurements in Kuwait produced an r2 value of 0.84. Cross validation of urban and rural sites in Kuwait also revealed good model fit. We applied this relationship to location-specific visibility data at 104 regional sites between years 2000 and 2012 to estimate monthly average PM2.5 concentrations. Monthly averages at sites in Iraq, Afghanistan, United Arab Emirates, Kuwait, Djibouti, and Qatar ranged from 10 to 365 µg/m3 during this period, while site averages ranged from 22 to 80 µg/m3, indicating considerable spatial and temporal heterogeneity in ambient PM2.5 across these regions. These data support the use of historical visibility data to estimate location-specific PM2.5 concentrations for use in future epidemiological studies in the region. PMID:27700621

Characterization of PM2.5 and the major chemical components during a 1-year campaign in rural Guangzhou, Southern China

NASA Astrophysics Data System (ADS)

Lai, Senchao; Zhao, Yan; Ding, Aijun; Zhang, Yingyi; Song, Tianli; Zheng, Junyu; Ho, Kin Fai; Lee, Shun-cheng; Zhong, Liuju

2016-01-01

A 1-year campaign was conducted in the rural area of Guangzhou, a megacity in southern China, to collect fine particulate matter (PM2.5) from March 2012 to February 2013. The mass concentrations of PM2.5 and the major chemical components including 6 water-soluble ions, organic carbon (OC), elemental carbon (EC), and 13 additional elements were measured. The annual average concentration of PM2.5 was 44.2 ± 25.8 μg/m3. Sulfate was the most dominant component, accounting for 28.6% of PM2.5, followed by organic matter (21.9%). Both sea salt and crustal material accounted for only a small fraction of PM2.5 (< 5%). Seasonal enhancement of PM2.5 was observed in autumn 2012, especially with high-PM2.5 events (more than 100 μg/m3) in October. The backward Lagrangian particle dispersion modeling (LPDM) and the cluster analysis of the back-trajectories indicate that the northern area is an important source region of long-range transport. An enhancement of PM2.5 as well as sulfate, OC, and EC was observed in the samples with the influence of northern air masses. However, the footprint retroplume of the samples shows that the sources in the Pearl River Delta Region should also be considered, especially secondary aerosol formation and biomass/biofuel burning. Two high-PM2.5 case studies show that both local and long-range transport can play important roles in the PM2.5 elevation episode.

Variations in Particulate Matter (PM 2.5) Concentration Levels at a Major Bay Area Rapid Transit (BART) Railway Station

NASA Astrophysics Data System (ADS)

Luong, K.; Sethy, D.; Yu, I.; Hernandez, N.; Fang, K.; Zhang, W.; Li, J.; Hoang, R.; Munui, K. N.; Sot, R.; Rodriguez, V. A.; Chiu, D.; Sankar, R.; Bonzo, R.

2016-12-01

Previous research has identified high levels of PM 2.5 in Embarcadero Station within the Bay Area Rapid Transit (BART) system. The current study examined PM 2.5 levels within Embarcadero Station to confirm previous results, as well as to determine exposure with respect to a location on the platform. Data collected confirmed the effectiveness of using DustTrak devices to collect elevated PM data. Our research established a model for PM 2.5 levels in a stationary location on the Embarcadero platform over a span of 10 minutes.This allowed us to compare the east and west ends of Embarcadero station platform for levels of PM2.5. A significantly higher level of PM2.5 was found on the east end of the platform, supporting last year's study. This methodology builds on last year's research to show a sustained high level of PM 2.5 on either end of the platform, with a significant elevated levels on the east end. Collecting data from a stationary location provided insight on exposure for an individual waiting in one spot rather than walking along the platform prior to train arrival. While the level of PM 2.5 varied over time, the average PM 2.5 over the 10 minute period were still at unhealthy levels. Our research suggests that location of an individual on the platform does affect their exposure level and therefore recommendations can be made for individuals with higher risk.

Inventory of African desert dust events in the north-central Iberian Peninsula in 2003-2014 based on sun-photometer-AERONET and particulate-mass-EMEP data

NASA Astrophysics Data System (ADS)

Cachorro, Victoria E.; Burgos, Maria A.; Mateos, David; Toledano, Carlos; Bennouna, Yasmine; Torres, Benjamín; de Frutos, Ángel M.; Herguedas, Álvaro

2016-07-01

A reliable identification of desert dust (DD) episodes over north-central Spain is carried out based on the AErosol RObotic NETwork (AERONET) columnar aerosol sun photometer (aerosol optical depth, AOD, and Ångström exponent, α) and European Monitoring and Evaluation Programme (EMEP) surface particulate-mass concentration (PMx, x = 10, 2.5, and 2.5-10 µm) as the main core data. The impact of DD on background aerosol conditions is detectable by means of aerosol load thresholds and complementary information provided by HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory Model) air mass back trajectories, MODIS (Moderate Resolution Imaging Spectroradiometer) images, forecast aerosol models, and synoptic maps, which have been carefully reviewed by a human observer for each day included in the DD inventory. This identification method allows the detection of low and moderate DD intrusions and also of mixtures of mineral dust with other aerosol types by means of the analysis of α. During the period studied (2003-2014), a total of 152 DD episodes composed of 418 days are identified. Overall, this means ˜ 13 episodes and ˜ 35 days per year with DD intrusion, representing 9.5 % days year-1. During the identified DD intrusions, 19 daily exceedances over 50 µg m-3 are reported at the surface. The occurrence of DD event days during the year peaks in March and June, with a marked minimum in April and lowest occurrence in winter. A large interannual variability is observed showing a statistically significant temporal decreasing trend of ˜ 3 days year-1. The DD impact on the aerosol climatology is addressed by evaluating the DD contribution in magnitude and percent (in brackets) for AOD, PM10, PM2.5, and PM2.5 - 10, obtaining mean values of 0.015 (11.5 %), 1.3 µg m-3 (11.8 %), 0.55 µg m-3 (8.5 %) and 0.79 µg m-3 (16.1 %), respectively. Annual cycles of the DD contribution for AOD and PM10 present two maxima - one in summer (0.03 and 2.4 µg m-3 for AOD in June and PM10 in August) and another in March (0.02 for AOD and 2.2 µg m-3 for PM10) - both displaying a similar evolution with exceptions in July and September. The seasonal cycle of the DD contribution to AOD does not follow the pattern of the total AOD (close to a bell shape), whereas both PM10 cycles (total and DD contribution) are more similar to each other in shape, with an exception in September. The interannual evolution of the DD contribution to AOD and PM10 has evidenced a progressive decrease. This decline in the levels of mineral dust aerosols can explain up to 30 % of the total aerosol load decrease observed in the study area during the period 2003-2014. The relationship between columnar and surface DD contribution shows a correlation coefficient of 0.81 for the interannual averages. Finally, synoptic conditions during DD events are also analysed, observing that the north African thermal low causes most of the events ( ˜ 53 %). The results presented in this study highlight the relevance of the area studied since it can be considered representative of the clean background in the western Mediterranean Basin where DD events have a high impact on aerosol load levels.

Short-term exposures to ambient air pollution and risk of recurrent ischemic stroke.

PubMed

Wing, Jeffrey J; Adar, Sara D; Sánchez, Brisa N; Morgenstern, Lewis B; Smith, Melinda A; Lisabeth, Lynda D

2017-01-01

To investigate the association between short-term changes in ambient pollution (particulate matter <2.5µm in aerodynamic diameter (PM 2.5 ) and ozone (O 3 )) and the risk of recurrent ischemic stroke among individuals living in a bi-ethnic community. We identified recurrent ischemic stroke cases from the population-based Brain Attack Surveillance in Corpus Christi (BASIC) project between 2000 and 2012. Associations between PM 2.5 (mean 24-h) and O 3 (maximal 8-h) levels, measured on the previous day, and odds of ischemic stroke were assessed using a time-stratified case-crossover design and modeled using conditional logistic regression. There were 317 recurrent ischemic strokes after excluding 41 strokes that occurred on days with missing air pollution data. Mean age was 72 years (SD=12) and median time to stroke recurrence was 1.1 years (IQR: 0.2-2.8 years). Median levels of PM 2.5 and O 3 over the study period were 7.7μg/m 3 (IQR: 5.6-10.7μg/m 3 ) and 35.2 ppb (IQR: 25.0-46.1 ppb), respectively. We observed no associations between previous-day PM 2.5 and O 3 and odds of recurrent stroke (OR=0.95 per 10µg/m 3 of PM 2.5 , 95% CI: 0.71-1.28 and OR=0.97 per 10ppb of O 3 , 95% CI: 0.87-1.07) after adjusting for ambient temperature and relative humidity. Co-adjustment of both pollutants did not change the results. We found no evidence of associations between previous-day air pollution levels and recurrent ischemic stroke. Research on the influence of air pollutants on risk of stroke recurrence is still in its infancy, and more research is necessary in studies that are adequately powered to understand the relation. Copyright © 2016 Elsevier Inc. All rights reserved.

Orbital Solutions and Absolute Elements of the W UMa Binary MW Pavonis

NASA Astrophysics Data System (ADS)

Alvarez, Gabriella E.; Sowell, James R.; Williamon, Richard M.; Lapasset, Emilio

2015-08-01

We present differential $UBV$ photoelectric photometry obtained by Williamon of the short-period A-type W~UMa binary MW~Pav. With the Wilson-Devinney analysis program we obtained a simultaneous solution of these observations with the $UBV$ photometry of Lapasset (1977,1980), the $V$ measurements by the $ASAS$ program, and the double-lined radial velocity measurements of Rucinski & Duerbeck (2006). Our solution indicates that MW~Pav is in an overcontact state, where both components exceed their critical Roche lobes. We derive masses of $M_1 = 1.514 \\pm 0.063 \\, M_\\sun$ and $M_2 = 0.327 \\pm 0.014 \\, M_\\sun$, and equal-volume radii of $R_1 = 2.412 \\pm 0.034 \\, R_\\sun$ and $R_2 = 1.277 \\pm 0.019 \\, R_\\sun$ for the primary and secondary, respectively. The system is assumed to have a circular orbit and is seen at an inclination of $86.39\\arcdeg \\pm 0.63\\arcdeg$. The effective temperature of the primary was held fixed at $6900$~K, whereas the secondary's temperature was found to be $6969 \\pm 10$~K. The asymmetry of the light curves requires a large, single star spot on the smaller, less massive secondary component. A consistent base solution, with different spot characteristics for the Williamon, Lapasset, and $ASAS$ data, was found. The modeled spot varied little during the 40-year range of photometric observations. The combined solution utilized a third light component and found that the period is changing at a rate of dP/dt~=~$(6.50 \\pm 0.19) \\times 10^{-10}$.

Drug concentrations in post-mortem femoral blood compared with therapeutic concentrations in plasma

PubMed Central

Launiainen, Terhi; Ojanperä, Ilkka

2014-01-01

Therapeutic drug concentrations measured in plasma are of limited value as reference intervals for interpretation in post-mortem (PM) toxicology. In this study, drug concentration distributions were studied in PM femoral venous blood from 57 903 Finnish autopsy cases representing all causes of death during an 11-year period. Cause-of-death information was obtained from death certificates issued by forensic pathologists. Median, mean, and upper percentile (90th, 95th, 97.5th) concentrations were calculated for 129 drugs. To illustrate how PM median concentrations relate to established therapeutic ranges in plasma, a PM blood/plasma relationship was calculated for each drug. Males represented 75% of the subjects and showed a lower median age (55 yrs) than females (59 yrs). In 43% of these cases, blood alcohol concentration was higher than 0.2‰, and the median was 1.8‰. Sixty-one (47%) of the 129 drugs showed a PM blood/plasma relationship of 1. For 22 drugs (17%), the relationship was <1, and for 46 drugs (35%), the relationship was >1. No marked correlation was found between the PM blood/plasma relationship and the volume of distribution (Vd). For 36 drugs, more than 10% of cases were fatal poisonings attributed to this drug as the main finding. These drug concentration distributions based on a large database provide a helpful reference not only to forensic toxicologists and pathologists but also to clinical pharmacologists in charge of interpreting drug concentrations in PM cases. © 2013 The Authors. Drug Testing and Analysis published by John Wiley & Sons, Ltd. PMID:23881890

Revealing driving factors of China's PM2.5 pollution

NASA Astrophysics Data System (ADS)

Zheng, Y.; Zhao, H.; Zhang, Q.; Geng, G.; Tong, D.; Peng, L.; He, K.

2017-12-01

China's rapid economic development and intensive energy consumption are deteriorating the air quality significantly. Understanding the key driving factors behind China's growing emissions of air pollutants and the accompanying PM2.5 pollution is critical for the development of China's clean air policies and also provides insight into how other emerging economies may develop a clear sky future. Here we reveal the socioeconomic drivers of the variations of China's PM2.5 concentrations during 2002-2012 by using an interdisciplinary framework that integrates an emission inventory model, an index decomposition analysis model, and a regional air quality model. The decomposition results demostrate that the improvements in emission efficiency and energy efficiency failed to offset the increased emissions of both primary PM2.5 and gaseous PM2.5 precursors (including SO2 NOx, and volatile organic compounds) triggered by the surging economic growth during 2002-2012. During the same time, the effects of energy structure, production structure and population growth were relatively less significant to all pollutants, which indicates the potential of large emission abatements through energy structure and production structure adjustment. Sensitivity simulations by the air quality model based on the provincial decomposition results also show that the economic growth have outpaced efficiency improvements in the increments of PM2.5 concentrations during the study years. As China continues to develop rapidly, future policies should promote further improvements in efficiency and accelerate the adjustments toward clean energy and production structures, which are critical for reducing China's emissions and alleviating the severe PM2.5 pollution.

Multivariate methods for indoor PM10 and PM2.5 modelling in naturally ventilated schools buildings

NASA Astrophysics Data System (ADS)

Elbayoumi, Maher; Ramli, Nor Azam; Md Yusof, Noor Faizah Fitri; Yahaya, Ahmad Shukri Bin; Al Madhoun, Wesam; Ul-Saufie, Ahmed Zia

2014-09-01

In this study the concentrations of PM10, PM2.5, CO and CO2 concentrations and meteorological variables (wind speed, air temperature, and relative humidity) were employed to predict the annual and seasonal indoor concentration of PM10 and PM2.5 using multivariate statistical methods. The data have been collected in twelve naturally ventilated schools in Gaza Strip (Palestine) from October 2011 to May 2012 (academic year). The bivariate correlation analysis showed that the indoor PM10 and PM2.5 were highly positive correlated with outdoor concentration of PM10 and PM2.5. Further, Multiple linear regression (MLR) was used for modelling and R2 values for indoor PM10 were determined as 0.62 and 0.84 for PM10 and PM2.5 respectively. The Performance indicators of MLR models indicated that the prediction for PM10 and PM2.5 annual models were better than seasonal models. In order to reduce the number of input variables, principal component analysis (PCA) and principal component regression (PCR) were applied by using annual data. The predicted R2 were 0.40 and 0.73 for PM10 and PM2.5, respectively. PM10 models (MLR and PCR) show the tendency to underestimate indoor PM10 concentrations as it does not take into account the occupant's activities which highly affect the indoor concentrations during the class hours.

Factors governing water condensation in the Martian atmosphere

NASA Technical Reports Server (NTRS)

Colburn, David S.; Pollack, J. B.; Haberle, Robert M.

1988-01-01

Modeling results are presented suggesting a diurnal condensation cycle at high altitudes at some seasons and latitudes. In a previous paper, the use of atmospheric optical depth measurements at the Viking lander site to show diurnal variability of water condensation at different seasons of the Mars year was described. Factors influencing the amount of condensation include latitude, season, atmospheric dust content and water vapor content at the observation site. A one-dimensional radiative-convective model is used herein based on the diabatic heating routines under development for the Mars General Circulation Model. The model predicts atmospheric temperature profiles at any latitude, season, time of day and dust load. From these profiles and an estimate of the water vapor, one can estimate the maximum occurring at an early morning hour (AM) and the minimum in the late afternoon (PM). Measured variations in the atmospheric optical density between AM and PM measurements were interpreted as differences in AM and PM condensation.

COMPARATIVE TOXICITY OF AIR POLLUTION PARTICLES COLLECTED FROM DIFFERENT GEOGRAPHICAL LOCATIONS

EPA Science Inventory

Air pollution particulate matter (PM) is responsible for more than 500,000 deaths worldwide each year. PM pollution is a complex mixture containing dozens of different compounds; the composition of PM can vary dramatically among different locations depending on the sources of pa...

Posterior microphthalmos pigmentary retinopathy syndrome.

PubMed

Pehere, Niranjan; Jalali, Subhadra; Deshmukh, Himanshu; Kannabiran, Chitra

2011-04-01

Posterior Microphthalmos Pigmentary Retinopathy Syndrome (PMPRS). Posterior microphthalmos (PM) is a relatively infrequent type of microphthalmos where posterior segment is predominantly affected with normal anterior segment measurements. Herein, we report two siblings with posterior microphthalmos retinopathy syndrome with postulated autosomal recessive mode of inheritance. A 13-year-old child had PM and retinitis pigmentosa (RP) and his 7-year-old sister had PM, RP, and foveoschisis. The genetics of this syndrome and variable phenotype is discussed. Importance of being aware of posterior microphthalmos and its posterior segment associations is highlighted.

Comparison of remote sensing and fixed-site monitoring approaches for examining air pollution and health in a national study population

NASA Astrophysics Data System (ADS)

Prud'homme, Genevieve; Dobbin, Nina A.; Sun, Liu; Burnett, Richard T.; Martin, Randall V.; Davidson, Andrew; Cakmak, Sabit; Villeneuve, Paul J.; Lamsal, Lok N.; van Donkelaar, Aaron; Peters, Paul A.; Johnson, Markey

2013-12-01

Satellite remote sensing (RS) has emerged as a cutting edge approach for estimating ground level ambient air pollution. Previous studies have reported a high correlation between ground level PM2.5 and NO2 estimated by RS and measurements collected at regulatory monitoring sites. The current study examined associations between air pollution and adverse respiratory and allergic health outcomes using multi-year averages of NO2 and PM2.5 from RS and from regulatory monitoring. RS estimates were derived using satellite measurements from OMI, MODIS, and MISR instruments. Regulatory monitoring data were obtained from Canada's National Air Pollution Surveillance Network. Self-reported prevalence of doctor-diagnosed asthma, current asthma, allergies, and chronic bronchitis were obtained from the Canadian Community Health Survey (a national sample of individuals 12 years of age and older). Multi-year ambient pollutant averages were assigned to each study participant based on their six digit postal code at the time of health survey, and were used as a marker for long-term exposure to air pollution. RS derived estimates of NO2 and PM2.5 were associated with 6-10% increases in respiratory and allergic health outcomes per interquartile range (3.97 μg m-3 for PM2.5 and 1.03 ppb for NO2) among adults (aged 20-64) in the national study population. Risk estimates for air pollution and respiratory/allergic health outcomes based on RS were similar to risk estimates based on regulatory monitoring for areas where regulatory monitoring data were available (within 40 km of a regulatory monitoring station). RS derived estimates of air pollution were also associated with adverse health outcomes among participants residing outside the catchment area of the regulatory monitoring network (p < 0.05). The consistency between risk estimates based on RS and regulatory monitoring as well as the associations between air pollution and health among participants living outside the catchment area for regulatory monitoring suggest that RS can provide useful estimates of long-term ambient air pollution in epidemiologic studies. This is particularly important in rural communities and other areas where monitoring and modeled air pollution data are limited or unavailable.

Assessment of annual air pollution levels with PM1, PM2.5, PM10 and associated heavy metals in Algiers, Algeria.

PubMed

Talbi, Abdelhamid; Kerchich, Yacine; Kerbachi, Rabah; Boughedaoui, Ménouèr

2018-01-01

Concentrations of particulate matter less than 1  μm, 2.5  μm, 10 μm and their contents of heavy metals were investigated in two different stations, urban and roadside at Algiers (Algeria). Sampling was conducted during two years by a high volume samplers (HVS) equipped with a cascade impactor at four levels stage, for one year sampling. The characterization of the heavy metals associated to the particulate matter (PM) was carried out by X-Ray Fluorescence analysis (XRF). The annual average concentration of PM 1 , PM 2.5 and PM 10 in both stations were 18.24, 32.23 and 60.01 μg m -3 respectively. The PM 1 , PM 2.5 and PM 10 concentrations in roadside varied from 13.46 to 25.59 μg m -3 , 20.82-49.85 μg m -3 and 45.90-77.23 μg m -3 respectively. However in the urban station, the PM 1 , PM 2.5 and PM 10 concentrations varied from 10.45 to 26.24 μg m -3 , 18.53-47.58 μg m -3 and 43.8-91.62 μg m -3 . The heavy metals associated to the PM were confirmed by Scanning Electron Microscopy-Energy Dispersive X-Ray analyses (SEM-EDX). The different spots of PM 2.5 analysis by SEM-EDX shows the presence of nineteen elements with anthropogenic and natural origins, within the heavy metal detected, the lead was found with maximum of 5% (weight percent). In order to determine the source contributions of PM levels at the two sampling sites sampling, principal compound analysis (PCA) was applied to the collected data. Statistical analysis confirmed anthropogenic source with traffic being a significant source and high contribution of natural emissions. At both sites, the PM 2.5 /PM 10 ratio is lower than that usually recorded in developed countries. The study of the back-trajectories of the air masses starting from Sahara shows that desert dust influences the concentration and the composition of the PM measured in Algiers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Air pollution in China: Status and spatiotemporal variations.

PubMed

Song, Congbo; Wu, Lin; Xie, Yaochen; He, Jianjun; Chen, Xi; Wang, Ting; Lin, Yingchao; Jin, Taosheng; Wang, Anxu; Liu, Yan; Dai, Qili; Liu, Baoshuang; Wang, Ya-Nan; Mao, Hongjun

2017-08-01

In recent years, China has experienced severe and persistent air pollution associated with rapid urbanization and climate change. Three years' time series (January 2014 to December 2016) concentrations data of air pollutants including particulate matter (PM 2.5 and PM 10 ) and gaseous pollutants (SO 2 , NO 2 , CO, and O 3 ) from over 1300 national air quality monitoring sites were studied to understand the severity of China's air pollution. In 2014 (2015, 2016), annual population-weighted-average (PWA) values in China were 65.8 (55.0, 50.7) μg m -3 for PM 2.5 , 107.8 (91.1, 85.7) μg m -3 for PM 10 , 54.8 (56.2, 57.2) μg m -3 for O 3 _8 h, 39.6 (33.3, 33.4) μg m -3 for NO 2 , 34.1 (26, 21.9) μg m -3 for SO 2 , 1.2 (1.1, 1.1) mg m -3 for CO, and 0.60 (0.59, 0.58) for PM 2.5 /PM 10 , respectively. In 2014 (2015, 2016), 7% (14%, 19%), 17% (27%, 34%), 51% (67%, 70%) and 88% (97%, 98%) of the population in China lived in areas that meet the level of annual PM 2.5 , PM 10 , NO 2 , and SO 2 standard metrics from Chinese Ambient Air Quality Standards-Grade II. The annual PWA concentrations of PM 2.5 , PM 10 , O 3 _8 h, NO 2 , SO 2 , CO in the Northern China are about 40.4%, 58.9%, 5.9%, 24.6%, 96.7%, and 38.1% higher than those in Southern China, respectively. Though the air quality has been improving recent years, PM 2.5 pollution in wintertime is worsening, especially in the Northern China. The complex air pollution caused by PM and O 3 (the third frequent major pollutant) is an emerging problem that threatens the public health, especially in Chinese mega-city clusters. NOx controls were more beneficial than SO 2 controls for improvement of annual PM air quality in the northern China, central, and southwest regions. Future epidemiologic studies are urgently required to estimate the health impacts associated with multi-pollutants exposure, and revise more scientific air quality index standards. Copyright © 2017 Elsevier Ltd. All rights reserved.

Source apportionment of speciated PM2.5 and non-parametric regressions of PM2.5 and PM(coarse) mass concentrations from Denver and Greeley, Colorado, and construction and evaluation of dichotomous filter samplers

NASA Astrophysics Data System (ADS)

Piedrahita, Ricardo A.

The Denver Aerosol Sources and Health study (DASH) was a long-term study of the relationship between the variability in fine particulate mass and chemical constituents (PM2.5, particulate matter less than 2.5mum) and adverse health effects such as cardio-respiratory illnesses and mortality. Daily filter samples were chemically analyzed for multiple species. We present findings based on 2.8 years of DASH data, from 2003 to 2005. Multilinear Engine 2 (ME-2), a receptor-based source apportionment model was applied to the data to estimate source contributions to PM2.5 mass concentrations. This study relied on two different ME-2 models: (1) a 2-way model that closely reflects PMF-2; and (2) an enhanced model with meteorological data that used additional temporal and meteorological factors. The Coarse Rural Urban Sources and Health study (CRUSH) is a long-term study of the relationship between the variability in coarse particulate mass (PMcoarse, particulate matter between 2.5 and 10mum) and adverse health effects such as cardio-respiratory illnesses, pre-term births, and mortality. Hourly mass concentrations of PMcoarse and fine particulate matter (PM2.5) are measured using tapered element oscillating microbalances (TEOMs) with Filter Dynamics Measurement Systems (FDMS), at two rural and two urban sites. We present findings based on nine months of mass concentration data, including temporal trends, and non-parametric regressions (NPR) results, which were used to characterize the wind speed and wind direction relationships that might point to sources. As part of CRUSH, 1-year coarse and fine mode particulate matter filter sampling network, will allow us to characterize the chemical composition of the particulate matter collected and perform spatial comparisons. This work describes the construction and validation testing of four dichotomous filter samplers for this purpose. The use of dichotomous splitters with an approximate 2.5mum cut point, coupled with a 10mum cut diameter inlet head allows us to collect the separated size fractions that the collocated TEOMs collect continuously. Chemical analysis of the filters will include inorganic ions, organic compounds, EC, OC, and biological analyses. Side by side testing showed the cut diameters were in agreement with each other, and with a well characterized virtual impactor lent to the group by the University of Southern California. Error propagation was performed and uncertainty results were similar to the observed standard deviations.

Progress in oral personalized medicine: contribution of 'omics'.

PubMed

Glurich, Ingrid; Acharya, Amit; Brilliant, Murray H; Shukla, Sanjay K

2015-01-01

Precision medicine (PM), representing clinically applicable personalized medicine, proactively integrates and interprets multidimensional personal health data, including clinical, 'omics', and environmental profiles, into clinical practice. Realization of PM remains in progress. The focus of this review is to provide a descriptive narrative overview of: 1) the current status of oral personalized medicine; and 2) recent advances in genomics and related 'omic' and emerging research domains contributing to advancing oral-systemic PM, with special emphasis on current understanding of oral microbiomes. A scan of peer-reviewed literature describing oral PM or 'omic'-based research conducted on humans/data published in English within the last 5 years in journals indexed in the PubMed database was conducted using mesh search terms. An evidence-based approach was used to report on recent advances with potential to advance PM in the context of historical critical and systematic reviews to delineate current state-of-the-art technologies. Special focus was placed on oral microbiome research associated with health and disease states, emerging research domains, and technological advances, which are positioning realization of PM. This review summarizes: 1) evolving conceptualization of personalized medicine; 2) emerging insight into roles of oral infectious and inflammatory processes as contributors to both oral and systemic diseases; 3) community shifts in microbiota that may contribute to disease; 4) evidence pointing to new uncharacterized potential oral pathogens; 5) advances in technological approaches to 'omics' research that will accelerate PM; 6) emerging research domains that expand insights into host-microbe interaction including inter-kingdom communication, systems and network analysis, and salivaomics; and 7) advances in informatics and big data analysis capabilities to facilitate interpretation of host and microbiome-associated datasets. Furthermore, progress in clinically applicable screening assays and biomarker definition to inform clinical care are briefly explored. Advancement of oral PM currently remains in research and discovery phases. Although substantive progress has been made in advancing the understanding of the role of microbiome dynamics in health and disease and is being leveraged to advance early efforts at clinical translation, further research is required to discern interpretable constituency patterns in the complex interactions of these microbial communities in health and disease. Advances in biotechnology and bioinformatics facilitating novel approaches to rapid analysis and interpretation of large datasets are providing new insights into oral health and disease, potentiating clinical application and advancing realization of PM within the next decade.

Personal Exposure to Particulate Matter and Endotoxin in California Dairy Workers

NASA Astrophysics Data System (ADS)

Garcia, Johnny

The average number of cows per dairy has increased over the last thirty years, with little known about how this increase may impact occupational exposure. Thirteen California dairies and 226 workers participated in this study throughout the 2008 summer months. Particulate Matter (PM) and endotoxin concentrations were quantified using ambient area based and personal air samplers. Two size fractions were collected, Total Suspended Particulate matter (TSP) and PM 2.5. Differences across dairies were evaluated by placing area based integrated air samplers in established locations on the dairies, e.g. milking parlor, drylot corral, and freestall barns. The workers occupational exposure was quantified using personal air samplers. We analyzed concentrations along with the time workers spent conducting specific job tasks during their shift to identify high exposure job tasks. Biological and chemical analytical methods were employed to ascertain endotoxin concentrations in personal and area based air samples. Recombinant factor C assays (rFC) were used to analyze biologically active endotoxin and gas chromatography coupled with mass spectrometry in tandem (GC-MS/MS) was used to quantify total endotoxin. The PM2.5 concentrations ranged from 2-116 mug/m3 for ambient area concentration and 7-495 mug/m3 for personal concentrations while TSP concentrations ranged from 74-1690 mug/m3 for area ambient concentrations and 191-4950 mug/m3 for personal concentrations. Biologically active endotoxin concentrations in the TSP size fraction from ambient area based samples ranged from 11-2095 EU/m3 and 45-2061 EU/m3 for personal samples. Total endotoxin in the TSP size fraction ranged from 75-10,166 pmol/m3 for area based samples and 34-11,689 pmol/m3 for personal samples. Drylot corrals were found to have higher sample mean concentrations when compared to other locations on the dairies for PM and endotoxin. Re-bedding, of the freestalls, was found to consistently lead to higher personal sample mean concentrations when compared to other tasks performed on dairies for both endotoxin and PM. In mixed effect regression models, regional ambient concentrations of PM 2.5 helped account for variation in PM2.5 concentration outcomes. We found that while upwind and downwind mean concentrations were not significantly different, central mean concentrations were higher than upwind concentration. Variation in TSP levels was largely explained by dairy-level characteristics such as the age of the dairy and number of animals in the drylot corrals and freestall barns. The different locations within the dairy were found to differ in mean concentrations for TSP. Biologically active and total endotoxin concentration variation was explained by meteorological data, wind speed, relative humidity, and dairy waste management practices. Personal exposure levels where found to be higher than area based concentrations for PM and endotoxin. Endotoxin characteristics differed by particle size and location within the dairy. The chain length proportion for endotoxin in the PM 2.5 size fraction was dominated by C12 and C16 in the TSP size fraction.

Air Pollution Exposure during Pregnancy and Childhood Autistic Traits in Four European Population-Based Cohort Studies: The ESCAPE Project

PubMed Central

Guxens, Mònica; Ghassabian, Akhgar; Gong, Tong; Garcia-Esteban, Raquel; Porta, Daniela; Giorgis-Allemand, Lise; Almqvist, Catarina; Aranbarri, Aritz; Beelen, Rob; Badaloni, Chiara; Cesaroni, Giulia; de Nazelle, Audrey; Estarlich, Marisa; Forastiere, Francesco; Forns, Joan; Gehring, Ulrike; Ibarluzea, Jesús; Jaddoe, Vincent W.V.; Korek, Michal; Lichtenstein, Paul; Nieuwenhuijsen, Mark J.; Rebagliato, Marisa; Slama, Rémy; Tiemeier, Henning; Verhulst, Frank C.; Volk, Heather E.; Pershagen, Göran; Brunekreef, Bert; Sunyer, Jordi

2015-01-01

Background Prenatal exposure to air pollutants has been suggested as a possible etiologic factor for the occurrence of autism spectrum disorder. Objectives We aimed to assess whether prenatal air pollution exposure is associated with childhood autistic traits in the general population. Methods Ours was a collaborative study of four European population-based birth/child cohorts—CATSS (Sweden), Generation R (the Netherlands), GASPII (Italy), and INMA (Spain). Nitrogen oxides (NO2, NOx) and particulate matter (PM) with diameters of ≤ 2.5 μm (PM2.5), ≤ 10 μm (PM10), and between 2.5 and 10 μm (PMcoarse), and PM2.5 absorbance were estimated for birth addresses by land-use regression models based on monitoring campaigns performed between 2008 and 2011. Levels were extrapolated back in time to exact pregnancy periods. We quantitatively assessed autistic traits when the child was between 4 and 10 years of age. Children were classified with autistic traits within the borderline/clinical range and within the clinical range using validated cut-offs. Adjusted cohort-specific effect estimates were combined using random-effects meta-analysis. Results A total of 8,079 children were included. Prenatal air pollution exposure was not associated with autistic traits within the borderline/clinical range (odds ratio = 0.94; 95% CI: 0.81, 1.10 per each 10-μg/m3 increase in NO2 pregnancy levels). Similar results were observed in the different cohorts, for the other pollutants, and in assessments of children with autistic traits within the clinical range or children with autistic traits as a quantitative score. Conclusions Prenatal exposure to NO2 and PM was not associated with autistic traits in children from 4 to 10 years of age in four European population-based birth/child cohort studies. Citation Guxens M, Ghassabian A, Gong T, Garcia-Esteban R, Porta D, Giorgis-Allemand L, Almqvist C, Aranbarri A, Beelen R, Badaloni C, Cesaroni G, de Nazelle A, Estarlich M, Forastiere F, Forns J, Gehring U, Ibarluzea J, Jaddoe VW, Korek M, Lichtenstein P, Nieuwenhuijsen MJ, Rebagliato M, Slama R, Tiemeier H, Verhulst FC, Volk HE, Pershagen G, Brunekreef B, Sunyer J. 2016. Air pollution exposure during pregnancy and childhood autistic traits in four European population-based cohort studies: the ESCAPE Project. Environ Health Perspect 124:133–140; http://dx.doi.org/10.1289/ehp.1408483 PMID:26068947

Validity of midday total testosterone levels in older men with erectile dysfunction.

PubMed

Welliver, R Charles; Wiser, Herbert J; Brannigan, Robert E; Feia, Kendall; Monga, Manoj; Köhler, Tobias S

2014-07-01

Based on studies showing the circadian rhythmicity of testosterone the optimal time of day to draw total testosterone in men has classically been reported as between 8 and 11 a.m. However, further studies demonstrated that the testosterone circadian rhythmicity becomes blunted with age. We retrospectively reviewed the charts of 2,569 men who presented with erectile dysfunction for total testosterone and draw times. We compared the men by age group, including less than 40 years and 5-year groupings after age 40 years. Total testosterone was analyzed for variability during the most common draw time hours (7 a.m. to 2 p.m.). Mean total testosterone at 7 to 9 a.m. and 9 a.m. to 2 p.m. clinically and statistically differed only in men younger than 40 vs 40 to 44 years old (mean difference 207 ng/dl, 95% CI 98-315, p = 0.0004 vs 149 ng/dl, 95% CI 36-262, p = 0.01). No other group showed a clinically and statistically significant difference between those periods. Total testosterone in men with erectile dysfunction who are younger than 45 years should be drawn as close to 7 a.m. as possible because a statistically and clinically relevant decrease in testosterone will occur during the course of the day. Men older than 45 years with erectile dysfunction can have total testosterone drawn at any time before 2 p.m. without misleading results. Copyright © 2014 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Spatial Correlation Analysis between Particulate Matter 10 (PM10) Hazard and Respiratory Diseases in Chiang Mai Province, Thailand

NASA Astrophysics Data System (ADS)

Trang, N. Ha; Tripathi, N. K.

2014-11-01

Every year, during dry season, Chiang Mai and other northern provinces of Thailand face the problem of haze which is mainly generated by the burning of agricultural waste and forest fire, contained high percentage of particulate matter. Particulate matter 10 (PM10), being very small in size, can be inhaled easily to the deepest parts of the human lung and throat respiratory functions. Due to this, it increases the risk of respiratory diseases mainly in the case of continuous exposure to this seasonal smog. MODIS aerosol images (MOD04) have been used for four weeks in March 2007 for generating the hazard map by linking to in-situ values of PM10. Simple linear regression model between PM10 and AOD got fair correlation with R2 = 0.7 and was applied to transform PM10 pattern. The hazard maps showed the dominance of PM10 in northern part of Chiang Mai, especially in second week of March when PM10 level was three to four times higher than standard. The respiratory disease records and public health station of each village were collected from Provincial Public Health Department in Chiang Mai province. There are about 300 public health stations out of 2070 villages; hence thiessen polygon was created to determine the representative area of each public health station. Within each thiessen polygon, respiratory disease incident rate (RDIR) was calculated based on the number of patients and population. Global Moran's I was computed for RDIR to explore spatial pattern of diseases through four weeks of March. Moran's I index depicted a cluster pattern of respiratory diseases in 2nd week than other weeks. That made sense for a relationship between PM10 and respiratory diseases infections. In order to examine how PM10 affect the human respiratory system, geographically weighted regression model was used to observe local correlation coefficient between RDIR and PM10 across study area. The result captured a high correlation between respiratory diseases and high level of PM10 in northeast districts of Chiang Mai in second week of March.

Estimation of PM2.5 and PM10 using ground-based AOD measurements during KORUS-AQ campaign

NASA Astrophysics Data System (ADS)

Koo, J. H.; Kim, J.; Kim, S.; Go, S.; Lee, S.; Lee, H.; Mok, J.; Hong, J.; Lee, J.; Eck, T. F.; Holben, B. N.

2017-12-01

During the KORUS-AQ campaign (2 May - 12 June, 2016), aerosol optical depth (AOD) was obtained at multiple channels using various ground-based instruments at Yonsei University, Seoul: AERONET sunphotometer, SKYNET skyradiometer, Brewer spectrophotometer, and multi-filter rotating shadowband radiometer (MFRSR). At the same location, planetary boundary layer (PBL) height and vertical profile of backscattering coefficients also can be obtained based on the celiometer measurements. Using celiometer products and various AODs, we try to estimate the amount of particular matter (PM2.5 and PM10) and validate with in-situ surface PM2.5 and PM10 measurements from AIRKOREA network. Direct comparison between PM2.5 and AOD reveals that the ultraviolet(UV) channel AOD has better correlations, due to the higher sensitivity of short wavelength to the fine-mode particle. In contrast, PM10 shows the highest correlation with the near-infrared(NIR) AOD. Next, we extract the boundary-layer portion of AOD using either PBL height or vertical profile of backscattering coefficients to compare with PM2.5 and PM10. Both results enhance the correlation, but consideration of weighting factor calculated from backscattering coefficients shows larger contribution to the correlation increase. Finally, we performed the multiple linear regression to estimate PM2.5 and PM10 using AODs. Consideration of meteorology (temperature, wind speed, and relative humidity) can enhance the correlation and also O3 and NO2 consideration highly contributes to the high correlation. This finding implies the importance to consider the ambient condition of secondary aerosol formation related to the PM2.5 variation. Multiple regression model finally finds the correlation 0.7-0.8, and diminishes the wavelength-dependent correlation patterns.

Paediatric pedestrian trauma: the danger after school.

PubMed

Newbury, Clinton; Hsiao, Kai; Dansey, Rangi; Hamill, James

2008-09-01

To examine the demographics of road pedestrian trauma in children in the Auckland region and to provide data that can help target prevention strategies. A retrospective analysis was conducted of all children (0-14 years) in the Auckland region admitted to the hospital or killed following a pedestrian versus vehicle injury for the 6-year period 2000-2005. Excluded were pedestrians injured in a driveway. Over the 6-year period, 364 children were involved in pedestrian crashes resulting in 25 deaths. The median age was 7 years. Males comprised 63%. Pacific Islanders and Maori were over-represented. Three hundred seventeen patients had injury times recorded. Of these, 49% occurred between 3 and 7 pm. Injury peaks for school days showed a tri-modal pattern with injury peaks at 8-9 am, 3-4 pm and 5-6 pm with the 3-4 pm after-school peak predominating. Prevention strategies should concentrate on the hours after school finishes and should be tailored for Maori and Pacific Island communities.

Exposure to fine particle matter, nitrogen dioxide and benzene during pregnancy and cognitive and psychomotor developments in children at 15 months of age.

PubMed

Lertxundi, Aitana; Baccini, Michela; Lertxundi, Nerea; Fano, Eduardo; Aranbarri, Aritz; Martínez, Maria Dolores; Ayerdi, Mikel; Álvarez, Jon; Santa-Marina, Loreto; Dorronsoro, Miren; Ibarluzea, Jesus

2015-07-01

Prenatal exposure to air pollutants has recently been identified as a potential risk factor for neuropsychological impairment. To assess whether prenatal exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2) and benzene were associated with impaired development in infants during their second year of life. Regression analyses, based on 438 mother-child pairs, were performed to estimate the association between mother exposure to air pollutants during pregnancy and neurodevelopment of the child. The average exposure to PM2.5, NO2 and benzene over the whole pregnancy was calculated for each woman. During the second year of life, infant neuropsychological development was assessed using the Bayley Scales of Infant Development. Regression analyses were performed to estimate the association between exposure and outcomes, accounting for potential confounders. We estimated that a 1 μg/m(3) increase during pregnancy in the average levels of PM2.5 was associated with a -1.14 point decrease in motor score (90% CI: -1.75; -0.53) and that a 1 μg/m(3) increase of NO2 exposure was associated with a -0.29 point decrease in mental score (90% CI: -0.47; -0.11). Benzene did not show any significant association with development. Considering women living closer (≤ 100 m) to metal processing activities, we found that motor scores decreased by -3.20 (90% CI: -5.18; -1.21) for PM2.5 and -0.51 (-0.89; -0.13) for NO2, while mental score decreased by -2.71 (90% CI: -4.69; -0.74) for PM2.5, and -0.41 (9% CI: -0.76; -0.06) for NO2. Our findings suggest that prenatal residential exposure to PM2.5 and NO2 adversely affects infant motor and cognitive developments. This negative effect could be higher in the proximity of metal processing plants. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cognitive and neural plasticity in older adults’ prospective memory following training with the Virtual Week computer game

PubMed Central

Rose, Nathan S.; Rendell, Peter G.; Hering, Alexandra; Kliegel, Matthias; Bidelman, Gavin M.; Craik, Fergus I. M.

2015-01-01

Prospective memory (PM) – the ability to remember and successfully execute our intentions and planned activities – is critical for functional independence and declines with age, yet few studies have attempted to train PM in older adults. We developed a PM training program using the Virtual Week computer game. Trained participants played the game in 12, 1-h sessions over 1 month. Measures of neuropsychological functions, lab-based PM, event-related potentials (ERPs) during performance on a lab-based PM task, instrumental activities of daily living, and real-world PM were assessed before and after training. Performance was compared to both no-contact and active (music training) control groups. PM on the Virtual Week game dramatically improved following training relative to controls, suggesting PM plasticity is preserved in older adults. Relative to control participants, training did not produce reliable transfer to laboratory-based tasks, but was associated with a reduction of an ERP component (sustained negativity over occipito-parietal cortex) associated with processing PM cues, indicative of more automatic PM retrieval. Most importantly, training produced far transfer to real-world outcomes including improvements in performance on real-world PM and activities of daily living. Real-world gains were not observed in either control group. Our findings demonstrate that short-term training with the Virtual Week game produces cognitive and neural plasticity that may result in real-world benefits to supporting functional independence in older adulthood. PMID:26578936

78 FR 34095 - Adequacy Status of the Idaho, Northern Ada County PM10

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-06

... 10 State Implementation Plan, Maintenance Plan: Ten-Year Update (Maintenance Plan Update) are..., Northern Ada County PM 10 State Implementation Plan for Transportation Conformity Purposes AGENCY... particulate matter with an aerodynamic diameter of a nominal 10 microns or less (PM 10 ), nitrogen oxides (NOx...

40 CFR 52.2056 - Determinations of attainment.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 2009, EPA determined that the Harrisburg-Lebanon-Carlisle (Harrisburg) fine particle (PM2.5... air quality data for the 3-year period 2007 to 2009, EPA determined that the Johnstown fine particle... particle (PM2.5) nonattainment area attained the 1997 annual PM2.5 National Ambient Air Quality Standard...

40 CFR 52.2056 - Determinations of attainment.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 2009, EPA determined that the Harrisburg-Lebanon-Carlisle (Harrisburg) fine particle (PM2.5... air quality data for the 3-year period 2007 to 2009, EPA determined that the Johnstown fine particle... particle (PM2.5) nonattainment area attained the 1997 annual PM2.5 National Ambient Air Quality Standard...

Indoor PM2.5 and its Polycyclic Aromatic Hydrocarbons in Relation with Incense Burning

NASA Astrophysics Data System (ADS)

Bootdee, Susira; Chantara, Somporn; Prapamontol, Tippawan

2018-03-01

This study aims to determine fine particulate matter (PM2.5) and polycyclic aromatic hydrocarbons (PAHs) emitted from incense burning to assess human health risk. PM2.5 samples were collected for 8 hrs and 24 hrs during special occasions and normal period from two shrines in the city of Chiang Mai, Thailand. PM2.5-bound PAHs were extracted and analyzed by GC-MS. The highest average PM2.5 concentrations were found during Chinese New Year (625±147 µg/m3 (8 hrs) and 406±159 µg/m3 (24 hrs)). The highest total PAHs concentrations were also found during the same period (168±60 ng/m3 for 8 hrs and 102±26 and for 24 hrs). Concentrations of PM2.5 and carcinogenic-PAHs were highly correlated (r = 0.451-0.802) and were high during special occasions particularly during Chinese New Year due to high number of visitors and amount of incense being burned. The toxicity equivalent (TEQ) values were also relatively high during Chinese New Year (31-32 ng/m3 (8 hrs) and 10-20 ng/m3 (24 hrs)). It can be revealed that incense burning emits air pollutants and can increase degree of indoor air pollution and human health risk.

Satellite remote sensing of fine particulate air pollutants over Indian mega cities

NASA Astrophysics Data System (ADS)

Sreekanth, V.; Mahesh, B.; Niranjan, K.

2017-11-01

In the backdrop of the need for high spatio-temporal resolution data on PM2.5 mass concentrations for health and epidemiological studies over India, empirical relations between Aerosol Optical Depth (AOD) and PM2.5 mass concentrations are established over five Indian mega cities. These relations are sought to predict the surface PM2.5 mass concentrations from high resolution columnar AOD datasets. Current study utilizes multi-city public domain PM2.5 data (from US Consulate and Embassy's air monitoring program) and MODIS AOD, spanning for almost four years. PM2.5 is found to be positively correlated with AOD. Station-wise linear regression analysis has shown spatially varying regression coefficients. Similar analysis has been repeated by eliminating data from the elevated aerosol prone seasons, which has improved the correlation coefficient. The impact of the day to day variability in the local meteorological conditions on the AOD-PM2.5 relationship has been explored by performing a multiple regression analysis. A cross-validation approach for the multiple regression analysis considering three years of data as training dataset and one-year data as validation dataset yielded an R value of ∼0.63. The study was concluded by discussing the factors which can improve the relationship.

Spatio-temporal PM and AOD estimations over Northeast Asia during DRAGON NE-Asia campaign

NASA Astrophysics Data System (ADS)

Park, M.; Song, C.; Kim, J.

2013-12-01

Particulate matter (PM) is closely related to human health, air quality, and climate changes. It has been directly measured on the surface level. However, ground-based measurements have a limitation in spatial coverage of PM concentrations. In order to overcome this spatial limitation of ground measurements, AOD, which is considered as a proxy to PM concentration, was used in this study. AOD was first utilized to figure out the characteristics of PM and was then used to estimate the PM concentrations in Northeast Asia during the DRAGON Northeast-Asia campaign (March-May 2012), using CMAQ-estimated AOD, COMS/GOCI-retrieved AOD, and the AOD data from the DRAGON NE-Asia campaign. First of all, current emission inventories (MEIC and INTEX-B based emission inventories) were evaluated to improve CMAQ modeling results. Next, several algorithms to convert aerosol composition to AOD were evaluated using intensive measurement data from the DRAGON NE-Asia campaign. The accuracy of the CMAQ-estimated AOD was further evaluated with hourly observing GOCI-retrieved AOD. After the evaluation, CMAQ-calculated AOD was mathematically combined with GOCI-retrieved AOD via data assimilation. After this, AERONET AOD measured by the DRAGON NE-Asia campaign was again combined with the assimilated AOD from CMAQ and GOCI AODs to produce more accurate spatio-temporal AOD fields over Northeast Asia. Using several relationships between PM (PM10 and PM2.5) and AOD, the best surface-PM concentrations over the entire domain were calculated. It was then evaluated with ground-based PM2.5 measurements from the DRAGON NE-Asia campaign. A good agreement between estimated PM2.5 and measured PM2.5 over the domain was found. Finally, the PM and AOD information was used to investigate the effects of transboundary PM pollution from China to the Korean peninsula.

Air Pollution and Ischemic Stroke Among Young Adults.

PubMed

Yitshak Sade, Maayan; Novack, Victor; Ifergane, Gal; Horev, Anat; Kloog, Itai

2015-12-01

Studies have demonstrated consistent associations between cardiovascular illness and particulate matter (PM) <10 and <2.5 μm in diameter, but stroke received less attention. We hypothesized that air pollution, an inflammation progenitor, can be associated with stroke incidence in young patients in whom the usual risk factors for stroke are less prevalent. We aimed to evaluate the association between stroke incidence and exposure to PM <10 and <2.5 μm, in a desert area characterized by a wide range of PM. We included all members of the largest health maintenance organization in Israel, who were admitted to a local hospital with stroke between 2005 and 2012. Exposure assessment was based on a hybrid model incorporating daily satellite remote sensing data at 1-km spatial resolution. We performed case-crossover analysis, stratified by personal characteristics and distance from main roads. We identified 4837 stroke cases (89.4% ischemic stroke). Interquartile range of PM <10 and <2.5 μm was 36.3 to 54.7 and 16.7 to 23.3 μg/m(3), respectively. The subjects' average age was 70 years; 53.4% were males. Associations between ischemic stroke and increases of interquartile range average concentrations of particulate matter <10 or <2.5 μm at the day of the event were observed among subjects <55 years (odds ratio [95% confidence interval], 1.11 [1.02-1.20] and 1.10 [1.00-1.21]). Stronger associations were observed in subjects living within 75 m from a main road (1.22 [1.03-1.43] and 1.26 [1.04-1.51]). We observed higher risk for ischemic stroke associated with PM among young adults. This finding can be explained by the inflammatory mechanism, linking air pollution and stroke. © 2015 American Heart Association, Inc.

Risk-based prioritization among air pollution control strategies in the Yangtze River Delta, China.

PubMed

Zhou, Ying; Fu, Joshua S; Zhuang, Guoshun; Levy, Jonathan I

2010-09-01

The Yangtze River Delta (YRD) in China is a densely populated region with recent dramatic increases in energy consumption and atmospheric emissions. We studied how different emission sectors influence population exposures and the corresponding health risks, to inform air pollution control strategy design. We applied the Community Multiscale Air Quality (CMAQ) Modeling System to model the marginal contribution to baseline concentrations from different sectors. We focused on nitrogen oxide (NOx) control while considering other pollutants that affect fine particulate matter [aerodynamic diameter < or = 2.5 mum (PM2.5)] and ozone concentrations. We developed concentration-response (C-R) functions for PM2.5 and ozone mortality for China to evaluate the anticipated health benefits. In the YRD, health benefits per ton of emission reductions varied significantly across pollutants, with reductions of primary PM2.5 from the industry sector and mobile sources showing the greatest benefits of 0.1 fewer deaths per year per ton of emission reduction. Combining estimates of health benefits per ton with potential emission reductions, the greatest mortality reduction of 12,000 fewer deaths per year [95% confidence interval (CI), 1,200-24,000] was associated with controlling primary PM2.5 emissions from the industry sector and reducing sulfur dioxide (SO2) from the power sector, respectively. Benefits were lower for reducing NOx emissions given lower consequent reductions in the formation of secondary PM2.5 (compared with SO2) and increases in ozone concentrations that would result in the YRD. Although uncertainties related to C-R functions are significant, the estimated health benefits of emission reductions in the YRD are substantial, especially for sectors and pollutants with both higher health benefits per unit emission reductions and large potential for emission reductions.

Multi-Center, Community-Based Cardiac Implantable Electronic Devices Registry: Population, Device Utilization, and Outcomes.

PubMed

Gupta, Nigel; Kiley, Mary Lou; Anthony, Faith; Young, Charlie; Brar, Somjot; Kwaku, Kevin

2016-03-09

The purpose of this study is to describe key elements, clinical outcomes, and potential uses of the Kaiser Permanente-Cardiac Device Registry. This is a cohort study of implantable cardioverter defibrillators (ICD), pacemakers (PM), and cardiac resynchronization therapy (CRT) devices implanted between January 1, 2007 and December 31, 2013 by ≈400 physicians in 6 US geographical regions. Registry data variables, including patient characteristics, comorbidities, indication for procedures, complications, and revisions, were captured using the healthcare system's electronic medical record. Outcomes were identified using electronic screening algorithms and adjudicated via chart review. There were 11 924 ICDs, 33 519 PMs, 4472 CRTs, and 66 067 leads registered. A higher proportion of devices were implanted in males: 75.1% (ICD), 55.0% (PM), and 66.7% (CRT), with mean patient age 63.2 years (ICD), 75.2 (PM), and 67.2 (CRT). The 30-day postoperative incidence of tamponade, hematoma, and pneumothorax were ≤0.3% (ICD), ≤0.6% (PM), and ≤0.4% (CRT). Device failures requiring revision occurred at a rate of 2.17% for ICDs, 0.85% for PMs, and 4.93% for CRTs, per 100 patient observation years. Superficial infection rates were <0.03% for all devices; deep infection rates were 0.6% (ICD), 0.5% (PM), and 1.0% (CRT). Results were used to monitor vendor-specific variations and were systematically shared with individual regions to address potential variations in outcomes, utilization, and to assist with the management of device recalls. The Kaiser Permanente-Cardiac Device Registry is a robust tool to monitor postprocedural patient outcomes and postmarket surveillance of implants and potentially change practice patterns. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Effect of gellan gum on the thermogelation property and drug release profile of Poloxamer 407 based ophthalmic formulation.

PubMed

Dewan, Mitali; Sarkar, Gunjan; Bhowmik, Manas; Das, Beauty; Chattoapadhyay, Atis Kumar; Rana, Dipak; Chattopadhyay, Dipankar

2017-09-01

The effect of gellan gum on the gelation behavior and in-vitro release of a specific drug named pilocarpine hydrochloride from different ophthalmic formulations based on poloxamer 407 is examined. The mixture of 0.3wt% gellan gum and 18wt% poloxamer (PM) solutions show a considerable increase in gel strength in physiological condition. Gel dissolution rate from PM based formulation is significantly decreased due to the addition of gellan gum. FTIR spectra analysis witnesses an interaction in between OH groups of two polymers which accounts for lowering in gelation temperature of PM-gellan gum based formulations. It is also observed from the cryo-SEM study that the pore size of PM gel decreases with an addition of gellan gum and in-vitro release studies indicate that PM-gellan gum based formulation retain drug better than the PM solution alone. Therefore, the developed formulation has the potential to be utilized as an in-situ ophthalmic drug carrier. Copyright © 2017 Elsevier B.V. All rights reserved.

Simulations of Sulfate-Nitrate-Ammonium (SNA) aerosols during the extreme haze events over Northern China in October 2014

NASA Astrophysics Data System (ADS)

Chen, D.; Liu, Z.; Fast, J. D.; Ban, J.

2017-12-01

Extreme haze events have occurred frequently over China in recent years. Although many studies have investigated the formation mechanisms associated with PM2.5 for heavily polluted regions in China based on observational data, adequately predicting peak PM2.5 concentrations is still challenging for regional air quality models. In this study, we evaluate the performance of one configuration of the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) and use the model to investigate the sensitivity of heterogeneous reactions on simulated peak sulfate, nitrate, and ammonium concentrations in the vicinity of Beijing during four extreme haze episodes in October 2014 over the North China Plain. The highest observed PM2.5 concentration of 469 μg m-3 occurred in Beijing. Comparisons with observations show that the model reproduced the temporal variability in PM2.5 with the highest PM2.5 values on polluted days (defined as days in which observed PM2.5 is greater than 75 μg m-3), but predictions of sulfate, nitrate, and ammonium were too low on days with the highest observed concentrations. Observational data indicate that the sulfur/nitric oxidation rates are strongly correlated with relative humidity during periods of peak PM2.5; however, the model failed to reproduce the highest PM2.5 concentrations due to missing heterogeneous/aqueous reactions. As the parameterizations of those heterogeneous reactions are not well established yet, estimates of SO2-to-H2SO4 and NO2/NO3-to-HNO3 reaction rates that depend on relative humidity were applied which improved the simulation of sulfate, nitrate, and ammonium enhancement on polluted days in terms of both concentrations and partitioning among those species. Sensitivity simulations showed that the extremely high heterogeneous reaction rates and also higher emission rates than those reported in the emission inventory were likely important factors contributing to those peak PM2.5 concentrations.

An ecological analysis of PM2.5 concentrations and lung cancer mortality rates in China.

PubMed

Fu, Jingying; Jiang, Dong; Lin, Gang; Liu, Kun; Wang, Qiao

2015-11-24

To explore the association between Particulate Matter (PM)2.5 (particles with an aerodynamic diameter less than 2.5 µm) and lung cancer mortality rates and to estimate the potential risk of lung cancer mortality related to exposure to high PM2.5 concentrations. Geographically weighted regression was performed to evaluate the relation between PM2.5 concentrations and lung cancer mortality for males, females and for both sexes combined, in 2008, based on newly available long-term data. Lung cancer fatalities from long-term exposure to PM2.5 were calculated according to studies by Pope III et al and the WHO air quality guidelines (AQGs). 31 provinces in China. PM2.5 was associated with the lung cancer mortality of males, females and both sexes combined, in China, although there were exceptions in several regions, for males and females. The number of lung cancer fatalities calculated by the WHO AQGs ranged from 531,036 to 532,004, whereas the number calculated by the American Cancer Society (ACS) reached 614,860 after long-term (approximately 3-4 years) exposure to PM2.5 concentrations since 2008. There is a positive correlation between PM2.5 and lung cancer mortality rate, and the relationship between them varies across the entire country of China. The number of lung cancer fatalities estimated by ACS was closer to the actual data than those of the WHO AQGs. Therefore, the ACS estimate of increased risk of lung cancer mortality from long-term exposure to PM2.5 might be more applicable for evaluating lung cancer fatalities in China than the WHO estimate. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Evaluating the dynamical characteristics of particle matter emissions in an open ore yard with industrial operation activities.

PubMed

Cong, X C; Yang, G S; Qu, J H; Dai, M X

2016-11-01

A study to investigate the dynamical characteristics of particle matter emissions in a working open yard is conducted in Caofeidian Port of Hebei Province, China. The average diurnal concentrations of the total suspended particulate (TSP) matter and respirable particulate matter (PM 10 and PM 5 ) are monitored during the field measurement campaign. Sampling is performed at a regular interval at 8 monitoring stations in the yard with normal industrial activities. The average TSP, PM 10 and PM 5 concentrations range from 285 to 568, 198 to 423 and 189 to 330 μg.m-3 in the yard, respectively. The linear regression correlation coefficient of TSP/PM 10 and TSP/PM 5 is 0.95±0.01 and 0.88±0.02, respectively.By using the Spearman correlation method, the wind speed and relative humidity are both weakly correlated with the PM 10 and PM 5 concentrations according to the measurements. In addition, industrial operation activities, such as vehicular traffic in the yard and the loading time of stackers, are significantly positively correlated with the PM concentration. Using the multivariate regression method, the main parameters influencing the TSP concentration variations are integratedly analysed. The traffic volume is found to be a significant predictor of TSP concentration variation, with the smallest P value (P<0.05).To understand the dynamical characteristics of particle emissions in the yard, the emissions from the truck transports, that is, from unpaved haul roads and from the loading process, are established. Then, the dynamical emission factor (EF D ) based on the industrial activities in the yard is proposed. The dynamical emissions average 5.25x10 5 kg.year -1 and EF D is evaluated to be 0.29 kg.(ton.day) -1 during the measurement period. These outcomes have meaningful implications not only for understanding the dynamical characteristics of particle emissions in the working stockyard but also for implementing effective control measures at appropriate sites in the harbour area.

To Investigate the Effects of Air Pollution (PM10 and SO2) on the Respiratory Diseases Asthma and Chronic Obstructive Pulmonary Disease.

PubMed

Saygın, Mustafa; Gonca, Taner; Öztürk, Önder; Has, Mehmet; Çalışkan, Sadettin; Has, Zehra Güliz; Akkaya, Ahmet

2017-04-01

Effects of air pollution parameters of sulfur dioxide (SO2) and particulate matter (PM10) values on the respiratory system were investigated. Data of SO 2 and PM10 were obtained daily for air pollution and classified into two groups: Group I (2006-2007), coal burning years and Group II (2008-2009), natural gas+ coal burning. Groups I and II were divided into two subgroups according to the months of combustion as combustible (November-April) and noncombustible (May-October). The number of patients with asthma and chronic obstructive pulmonary disorder (COPD) was recorded between 2006 and 2009. There was no statistically significant difference between Groups I and II for PM10 and SO 2 (p>0.05). Within the years, the values of SO 2 and PM10 were statistically different between the groups defined by month (p<0.01). The number of patients in the combustible and noncombustible subgroups were found to be different for every 4 years, and the numbers of patients with COPD or asthma were not changed through the years. There was a strong correlation between PM10 and COPD (r=0.59, p<0.01) and a weak correlation between PM10 and asthma (r=0.25, p>0.05). A correlation was found between SO 2 and COPD (p<0.01) but not between SO 2 and asthma (p>0.05). The number of visits for COPD and asthma was statistically different between combustible and noncombustible subgroups (X2:58.61, p=0.000; X2:34.55, p=0.000, respectively). The r2 values for SO 2 and PM10 for COPD patients were 17% and 24%, respectively, in contrast to 8% and 5%, respectivley for asthma patients. Air pollution is known to increase respiratory disease occurrences. With decrease in the usage of solid fuel, air pollution could be reduced and may be effective in preventing respiratory diseases.

Temporal Trend in Lung Cancer Burden Attributed to Ambient Fine Particulate Matter in Guangzhou, China.

PubMed

Liao, Yu; Xu, Lin; Lin, Xiao; Hao, Yuan Tao

2017-10-01

To estimate the lung cancer burden that may be attributable to ambient fine particulate matter (PM2.5) pollution in Guangzhou city in China from 2005 to 2013. The data regarding PM2.5 exposure were obtained from the 'Ambient air pollution exposure estimation for the Global Burden of Disease 2013' dataset at 0.1° ×0.1° spatial resolution. Disability-adjusted life years (DALYs) were estimated based on the information of mortality and incidence of lung cancer. Comparative risk analysis and integrated exposure-response function were used to estimate attributed disease burden. The population-weighted average concentration of PM2.5 was increased by 34.6% between 1990 and 2013, from 38.37 μg/m3 to 51.31 μg/m3. The lung cancer DALYs in both men and women were increased by 36.2% from 2005 to 2013. The PM2.5 attributed lung cancer DALYs increased from 12105.0 (8181.0 for males and 3924.0 for females) in 2005 to 16489.3 (11291.7 for males and 5197.6 for females) in 2013. An average of 23.1% lung cancer burden was attributable to PM2.5 pollution in 2013. PM2.5 has caused serious but under-appreciated public health burden in Guangzhou and the trend deteriorates. Effective strategies are needed to tackle this major public health problem. Copyright © 2017 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.

Particulate matter concentration mapping from MODIS satellite data: a Vietnamese case study

NASA Astrophysics Data System (ADS)

Nguyen, Thanh T. N.; Bui, Hung Q.; Pham, Ha V.; Luu, Hung V.; Man, Chuc D.; Pham, Hai N.; Le, Ha T.; Nguyen, Thuy T.

2015-09-01

Particulate Matter (PM) pollution is one of the most important air quality concerns in Vietnam. In this study, we integrate ground-based measurements, meteorological and satellite data to map temporal PM concentrations at a 10 × 10 km grid for the entire of Vietnam. We specifically used MODIS Aqua and Terra data and developed statistically-significant regression models to map and extend the ground-based PM concentrations. We validated our models over diverse geographic provinces i.e., North East, Red River Delta, North Central Coast and South Central Coast in Vietnam. Validation suggested good results for satellite-derived PM2.5 data compared to ground-based PM2.5 (n = 285, r2 = 0.411, RMSE = 20.299 μg m-3 and RE = 39.789%). Further, validation of satellite-derived PM2.5 on two independent datasets for North East and South Central Coast suggested similar results (n = 40, r2 = 0.455, RMSE = 21.512 μg m-3, RE = 45.236% and n = 45, r2 = 0.444, RMSE = 8.551 μg m-3, RE = 46.446% respectively). Also, our satellite-derived PM2.5 maps were able to replicate seasonal and spatial trends of ground-based measurements in four different regions. Our results highlight the potential use of MODIS datasets for PM estimation at a regional scale in Vietnam. However, model limitation in capturing maximal or minimal PM2.5 peaks needs further investigations on ground data, atmospheric conditions and physical aspects.

Prenatal particulate air pollution exposure and body composition in urban preschool children: Examining sensitive windows and sex-specific associations.

PubMed

Chiu, Yueh-Hsiu Mathilda; Hsu, Hsiao-Hsien Leon; Wilson, Ander; Coull, Brent A; Pendo, Mathew P; Baccarelli, Andrea; Kloog, Itai; Schwartz, Joel; Wright, Robert O; Taveras, Elsie M; Wright, Rosalind J

2017-10-01

Evolving animal studies and limited epidemiological data show that prenatal air pollution exposure is associated with childhood obesity. Timing of exposure and child sex may play an important role in these associations. We applied an innovative method to examine sex-specific sensitive prenatal windows of exposure to PM 2.5 on anthropometric measures in preschool-aged children. Analyses included 239 children born ≥ 37 weeks gestation in an ethnically-mixed lower-income urban birth cohort. Prenatal daily PM 2.5 exposure was estimated using a validated satellite-based spatio-temporal model. Body mass index z-score (BMI-z), fat mass, % body fat, subscapular and triceps skinfold thickness, waist and hip circumferences and waist-to-hip ratio (WHR) were assessed at age 4.0 ± 0.7 years. Using Bayesian distributed lag interaction models (BDLIMs), we examined sex differences in sensitive windows of weekly averaged PM 2.5 levels on these measures, adjusting for child age, maternal age, education, race/ethnicity, and pre-pregnancy BMI. Mothers were primarily Hispanic (55%) or Black (26%), had ≤ 12 years of education (66%) and never smoked (80%). Increased PM 2.5 exposure 8-17 and 15-22 weeks gestation was significantly associated with increased BMI z-scores and fat mass in boys, but not in girls. Higher PM 2.5 exposure 10-29 weeks gestation was significantly associated with increased WHR in girls, but not in boys. Prenatal PM 2.5 was not significantly associated with other measures of body composition. Estimated cumulative effects across pregnancy, accounting for sensitive windows and within-window effects, were 0.21 (95%CI = 0.01-0.37) for BMI-z and 0.36 (95%CI = 0.12-0.68) for fat mass (kg) in boys, and 0.02 (95%CI = 0.01-0.03) for WHR in girls, all per µg/m 3 increase in PM 2.5 . Increased prenatal PM 2.5 exposure was more strongly associated with indices of increased whole body size in boys and with an indicator of body shape in girls. Methods to better characterize vulnerable windows may provide insight into underlying mechanisms contributing to sex-specific associations. Copyright © 2017 Elsevier Inc. All rights reserved.

Exposure to PM2.5 and Blood Lead Level in Two Populations in Ulaanbaatar, Mongolia.

PubMed

Enkhbat, Undarmaa; Rule, Ana M; Resnick, Carol; Ochir, Chimedsuren; Olkhanud, Purevdorj; Williams, D'Ann L

2016-02-15

Approximately 60% of the households in Ulaanbaatar live in gers (a traditional Mongolian dwelling) in districts outside the legal limits of the city, without access to basic infrastructure, such as water, sewage systems, central heating, and paved roads, in contrast to apartment residents. This stark difference in living conditions creates different public health challenges for Ulaanbaatar residents. Through this research study we aim to test our hypothesis that women living in gers burning coal in traditional stoves for cooking and heating during the winter are exposed to higher concentrations of airborne PM2.5 than women living in apartments in Ulaanbaatar, Mongolia, and this exposure may include exposures to lead in coal with effects on blood lead levels. This cross-sectional study recruited a total of 50 women, 40-60 years of age, from these two settings. Air sampling was carried out during peak cooking and heating times, 5:00 p.m.-11:00 p.m., using a direct-reading instrument (TSI SidePak™) and integrated polytetrafluoroethylene (PTFE) filters using the SKC Personal Environmental Monitor. Blood lead level (BLL) was measured using a LeadCare II rapid field test method. In our study population, measured PM2.5 geometric mean (GM) concentrations using the SidePak™ in the apartment group was 31.5 (95% CI:17-99) μg/m³, and 100 (95% CI: 67-187) μg/m³ in ger households (p < 0.001). The GM integrated gravimetric PM2.5 concentrations in the apartment group were 52.8 (95% CI: 39-297) μg/m³ and 127.8 (95% CI: 86-190) μg/m³ in ger households (p = 0.004). The correlation coefficient for the SidePak™ PM2.5 concentrations and filter based PM2.5 concentrations was r = 0.72 (p < 0.001). Blood Lead Levels were not statistically significant different between apartment residents and ger residents (p = 0.15). The BLL is statistically significant different (p = 0.01) when stratified by length of exposures outside of the home. This statistically significant difference in increased BLL could be due to occupational or frequent exposure to other sources of indoor or outdoor air pollution that were not measured. Blood lead levels from our study population are the first study measurements published on women aged 40-60 years of age in Mongolia.

Contingent valuation of health and mood impacts of PM2.5 in Beijing, China.

PubMed

Yin, Hao; Pizzol, Massimo; Jacobsen, Jette Bredahl; Xu, Linyu

2018-07-15

Air pollution from PM 2 . 5 affects many cities worldwide, causing both health impacts and mood depression. One of the obstacles to implementing environmental regulations for PM 2 . 5 reduction is that there are limited studies of PM 2 . 5 welfare loss and few investigations of mood depression caused by PM 2 . 5 . This article describes a survey study conducted in Beijing, China to estimate the welfare loss due to PM 2 . 5 . In total, 1709 participants completed either a face-to-face or online survey. A contingent valuation method was applied to elicit people's willingness to pay to avoid PM 2 . 5 pollution and willingness to accept a compensation for such pollution. The payment/compensation was evaluated for two outcome variables: perceived health impacts and mood depression caused by PM 2 . 5 pollution. This is one of few papers that explicitly studies the effects of PM 2 . 5 on subjective well-being, and to the authors' knowledge, the first to estimate welfare loss from PM 2 . 5 using a random forest model. Compared to the standard Turnbull, probit, and two-part models, the random forest model gave the best fit to the data, suggesting that this may be a useful tool for future studies too. The welfare loss due to health impacts and mood depression is CNY 1388.4/person/year and CNY 897.7/person/year respectively, indicating that the public attaches great importance to mood, feelings and happiness. The study provides scientific support to the development of economic policy instruments for PM 2 . 5 control in China. Copyright © 2018. Published by Elsevier B.V.

Source-receptor reconciliation of fine-particulate emissions from residential wood combustion in the southeastern United States

EPA Science Inventory

An extensive collection of speciated PM2.5 measurements including organic tracers permitted a detailed examination of the emissions from residential wood combustion (RWC) in the southeastern United States over an entire year (2007). The Community Multiscale Air Quality model-base...

AN INTEGRATED SYNTHESIS OF KEY AND POLICY RELEVANT FINDINGS FROM EPA'S SUPERSITES PROGRAM AND RELATED STUDIES

EPA Science Inventory

This presentation provides an overview and initial insights into the findings based on results from EPA's PM Supersites Program and related studies. Many key atmospheric sciences findings have been identified through the research conducted during the last five years as part of t...

Global Estimates of Fine Particulate Matter Using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors

NASA Technical Reports Server (NTRS)

Van Donkelaar, Aaron; Martin, Randall V.; Brauer, Michael; Hsu, N. Christina; Kahn, Ralph A.; Levy, Robert C.; Lyapustin, Alexei; Sayer, Andrew M.; Winker, David M.

2016-01-01

We estimated global fine particulate matter (PM(sub 2.5)) concentrations using information from satellite-, simulation- and monitor-based sources by applying a Geographically Weighted Regression (GWR) to global geophysically-based satellite-derived PM(sub 2.5) estimates. Aerosol optical depth from multiple satellite products (MISR, MODIS Dark Target, MODIS and SeaWiFS Deep Blue, and MODIS MAIAC) was combined with simulation (GEOS-Chem) based upon their relative uncertainties as determined using ground-based sun photometer (AERONET) observations for 1998-2014. The GWR predictors included simulated aerosol composition and land use information. The resultant PM(sub 2.5) estimates were highly consistent (R(sup 2) equals 0.81) with out-of-sample cross-validated PM(sub 2.5) concentrations from monitors. The global population-weighted annual average PM(sub 2.5) concentrations were 3-fold higher than the 10 micrograms per cubic meter WHO guideline, driven by exposures in Asian and African regions. Estimates in regions with high contributions from mineral dust were associated with higher uncertainty, resulting from both sparse ground-based monitoring, and challenging conditions for retrieval and simulation. This approach demonstrates that the addition of even sparse ground-based measurements to more globally continuous PM(sub 2.5) data sources can yield valuable improvements to PM(sub 2.5) characterization on a global scale.

Investigation of physico-chemical characteristics of size-segregated particulate matter in a metropolitan environment and their impact on air quality in southern California

NASA Astrophysics Data System (ADS)

Pakbin, Payam

Numerous epidemiological studies have associated the adverse respiratory and cardiovascular effects to atmospheric particulate matter (PM) exposure. There is ample literature providing evidence of adverse effects for all inhalable particle size ranges, however the biological mechanisms responsible for the toxicity of PM are still uncertain. Due to the lack of data about how different PM components act in a complex mixture, it is not possible to precisely quantify the contributions from the main sources and components to the effects on human health. Thus, PM in health impact assessments is usually regarded as a uniform pollutant, regardless of the contribution from different sources, and assuming the same effect on morality. This is probably not a correct assumption, but is a pragmatic compromise while waiting for sufficient knowledge that will allow the use of indicators other than particle mass. As a result linking the toxicity of PM with several of its chemical components has been the focus of considerable research over the past decade. The associations between health endpoints with the hundreds of potentially toxic chemical species and PM characteristics may be daunting and not cost efficient. Therefore it is desirable to focus on the casualty of the few critical chemical components that current science supports as potentially the most harmful to human health. Such information will allow for more effective regulatory control strategies, more targeted air quality standards, and as a result, reductions in population exposure to the most harmful types of airborne PM. The current particulate matter emission standards are based on PM mass only. However, the prevailing scientific opinion contends that PM mass is a surrogate measure of other physical and chemical properties of PM that are the actual causes of the observed health effects. In this study we focus on the PM components that are not currently regulated, while there is ample evidence that they can cause hazardous health outcomes. The effect of the new after-treatment technologies on the composition of the remaining organic compounds, including the semi-volatile organic carbon (SVOC) fraction, is studied. While the association of adverse health effects with SVOC compounds has been reasonably well documented, the exact mechanisms by which SVOC compounds inflict health effects remain largely unknown. Therefore a new technology is developed that makes it possible to conduct toxicity and inhalation exposure studies separately to PM and vapor phase SVOC to investigate the degree to which health effects attributable to these pollutants are affected by their phases. In addition, in regards of PM10 standards, coarse PM emissions are usually from hard to control sources like windblown soil and dust, brake lining abrasion, tire wear and bioaerosols, therefore control of fine PM emissions is easier to achieve in order to meet PM10 standards. Coarse and fine PM have substantially different sources and sinks, and as a result different chemical composition, which would lead to potentially different health outcomes. Moreover, the available CPM mass concentration data is much more limited compared to ambient PM2.5 mass concentration data and hence significantly less is quantitatively known about the characteristics of CPM. In order to study the physical, chemical and toxicological characteristics of CPM in Los Angeles Basin, 10 distinct measurement sites were employed to sample the CPM for an entire year, in order to provide a much needed database of coarse PM characteristics in the Los Angeles basin, providing the seasonal and spatial variations over a variety of urban and semi-rural areas during one year of sampling period.

Mortality assessment attributed to long-term exposure to fine particles in ambient air of the megacity of Tehran, Iran.

PubMed

Yarahmadi, Maryam; Hadei, Mostafa; Nazari, Seyed Saeed Hashemi; Conti, Gea Oliveri; Alipour, Mohammd Reza; Ferrante, Margherita; Shahsavani, Abbas

2018-05-01

Few studies regarding the health effects of long-term exposure to particulate matter with an aerodynamic diameter of 2.5 μm or less (PM 2.5 ) have been carried out in Asia or the Middle East. The objective of our study was to assess total, lung cancer and chronic obstructive pulmonary disease (COPD) mortality attributed to long-term exposure to PM 2.5 among adults aged over 30 years in Tehran from March 2013 to March 2016 using AirQ + software. AirQ + modeling software was used to estimate the number of deaths attributed to PM 2.5 concentrations higher than 10 μg m -3 . Air quality data were obtained from the Department of Environment (DOE) and Tehran Air Quality Control Company (TAQCC). Only valid stations with data completeness of 75% in all 3 years were selected for entry into the model. The 3-year average of the 24-h concentrations was 39.17 μg m -3 . The results showed that the annual average concentration of PM 2.5 in 2015-2016 was reduced by 13% compared to that in 2013-2014. The annual average number of all natural, COPD, and lung cancer deaths attributable to long-term exposure to PM 2.5 in adults aged more than 30 years was 5073, 158, and 142 cases, respectively. The results of all three health endpoints indicate that the mortality attributable to PM 2.5 decreased yearly from 2013 to 2016 and that the reduced mortality was related to a corresponding reduction in the PM 2.5 concentration. Considering these first positive results, the steps that have been currently taken for reducing air pollution in Tehran should be continued to further improve the already positive effects of these measures on reducing health outcomes.

Navy Explosive Ordnance Disposal School Master Development Plan for Test Area D-51 Final Environmental Assessment

DTIC Science & Technology

2008-01-01

Year 2005 through 2009: VOCE = .016 * Trips NOxE = .015 * Trips PM10E = .0022 * Trips COE = .262 * Trips Year 2010 and beyond: VOCE = .012 * Trips...NOxE = .013 * Trips PM10E = .0022 * Trips COE = .262 * Trips To convert from pounds per day to tons per year: VOC (tons/yr) = VOCE * DPYII

Comparison between five acellular oxidative potential measurement assays performed with detailed chemistry on PM10 samples from the city of Chamonix (France)

NASA Astrophysics Data System (ADS)

Calas, Aude; Uzu, Gaëlle; Kelly, Frank J.; Houdier, Stephan; Martins, Jean M. F.; Thomas, Fabrice; Molton, Florian; Charron, Aurélie; Dunster, Christina; Oliete, Ana; Jacob, Véronique; Besombes, Jean-Luc; Chevrier, Florie; Jaffrezo, Jean-Luc

2018-06-01

Many studies have demonstrated associations between exposure to ambient particulate matter (PM) and adverse health outcomes in humans that can be explained by PM capacity to induce oxidative stress in vivo. Thus, assays have been developed to quantify the oxidative potential (OP) of PM as a more refined exposure metric than PM mass alone. Only a small number of studies have compared different acellular OP measurements for a given set of ambient PM samples. Yet, fewer studies have compared different assays over a year-long period and with detailed chemical characterization of ambient PM. In this study, we report on seasonal variations of the dithiothreitol (DTT), ascorbic acid (AA), electron spin resonance (ESR) and the respiratory tract lining fluid (RTLF, composed of the reduced glutathione (GSH) and ascorbic acid (ASC)) assays over a 1-year period in which 100 samples were analyzed. A detailed PM10 characterization allowed univariate and multivariate regression analyses in order to obtain further insight into groups of chemical species that drive OP measurements. Our results show that most of the OP assays were strongly intercorrelated over the sampling year but also these correlations differed when considering specific sampling periods (cold vs. warm). All acellular assays are correlated with a significant number of chemical species when considering univariate correlations, especially for the DTT assay. Evidence is also presented of a seasonal contrast over the sampling period with significantly higher OP values during winter for the DTT, AA, GSH and ASC assays, which were assigned to biomass burning species by the multiple linear regression models. The ESR assay clearly differs from the other tests as it did not show seasonal dynamics and presented weaker correlations with other assays and chemical species.

Fine particulate air pollution and premature atrial contractions: The REasons for Geographic And Racial Differences in Stroke study.

PubMed

O'Neal, Wesley T; Soliman, Elsayed Z; Efird, Jimmy T; Judd, Suzanne E; Howard, Virginia J; Howard, George; McClure, Leslie A

2017-05-01

Several reports have suggested that particulate matter (PM) exposure increases the risk for atrial arrhythmias. However, data from large-scale epidemiologic studies supporting this hypothesis are lacking. We examined the association of PM <2.5 μm in diameter (PM 2.5 ) concentration with premature atrial contractions (PACs) in 26,609 (mean age=65±9.4 years; 55% female; 41% black) participants from the REGARDS (REasons for Geographic And Racial Differences in Stroke) study. Estimates of short- (2 weeks) and long-term (1 year) PM 2.5 exposure were computed before each participant's baseline visit using geographic information system data on the individual level at the coordinates of study participants' residences. PACs were identified from baseline electrocardiograms. A total of 2140 (8.2%) participants had evidence of PACs on the baseline electrocardiogram. Short-term PM 2.5 (per 10 μg/m 3 ) exposure was not associated with PACs (OR=1.09, 95% CI=0.98, 1.23). Increases in long-term PM 2.5 (per 10 μg/m 3 ) were associated with PACs (OR=1.40, 95% CI=1.10, 1.78). Interactions were not detected for short- and long-term PM 2.5 exposure by age, sex, or race. Long- but not short-term PM 2.5 exposure is associated with PACs. This suggests a role for long-term PM 2.5 exposure in initiating supraventricular arrhythmias that are triggered by PACs.

Long-term exposure to ambient air pollution and respiratory disease mortality in Shenyang, China: a 12-year population-based retrospective cohort study.

PubMed

Dong, Guang-Hui; Zhang, Pengfei; Sun, Baijun; Zhang, Liwen; Chen, Xi; Ma, Nannan; Yu, Fei; Guo, Huimin; Huang, Hui; Lee, Yungling Leo; Tang, Naijun; Chen, Jie

2012-01-01

In China, both the levels and patterns of outdoor air pollution have altered dramatically with the rapid economic development and urbanization over the past two decades. However, few studies have investigated the association of outdoor air pollution with respiratory mortality, especially in the high pollution range. We conducted a retrospective cohort study of 9,941 residents aged ≥35 years old in Shenyang, China, to examine the association between outdoor air pollutants [particulate matter <10 µm in aerodynamic diameter (PM(10)), sulfur dioxide (SO(2)) and nitrogen dioxide (NO(2))] and mortality using 12 years of data. We applied extended Cox proportional hazards modeling with time-dependent covariates to respiratory mortality. Analyses were also stratified by age, sex, educational level, smoking status, personal income, occupational exposure and body mass index (BMI) to examine the association of air pollution with mortality. We found significant associations between PM(10) and NO(2) levels and respiratory disease mortality. Our analysis found a relative risk of 1.67 [95% confidence interval (CI) 1.60-1.74] and 2.97 (95% CI 2.69-3.27) for respiratory mortality per 10 µg/m(3) increase in PM(10) and NO(2), respectively. The effects of air pollution were more apparent in women than in men. Age, sex, educational level, smoking status, personal income, occupational exposure, BMI and exercise frequency influenced the relationship between outdoor PM(10) and NO(2) and mortality. For SO(2), only smoking, little regular exercise and BMI above 18.5 influenced the relationship with mortality. These data contribute to the scientific literature on the long-term effects of air pollution for the high-exposure settings typical in developing countries. Copyright © 2011 S. Karger AG, Basel.

Short-Term Effects of the Particulate Pollutants Contained in Saharan Dust on the Visits of Children to the Emergency Department due to Asthmatic Conditions in Guadeloupe (French Archipelago of the Caribbean)

PubMed Central

Cadelis, Gilbert; Tourres, Rachel; Molinie, Jack

2014-01-01

Background The prevalence of asthma in children is a significant phenomenon in the Caribbean. Among the etiologic factors aggravating asthma in children, environmental pollution is one of the main causes. In Guadeloupe, pollution is primarily transported by Saharan dust including inhalable particles. Methods This study assesses, over one year (2011), the short-term effects of pollutants referred to as PM10 (PM10: particulate matter <10 µm) and PM2.5–10 (PM2.5–10: particulate matter >2.5 µm and <10 µm) contained in Saharan dust, on the visits of children aged between 5 and 15 years for asthma in the health emergency department of the main medical facility of the archipelago of Guadeloupe. A time-stratified case-crossover model was applied and the data were analysed by a conditional logistic regression for all of the children but also for sub-groups corresponding to different age classes and genders. Results The visits for asthma concerned 836 children including 514 boys and 322 girls. The Saharan dust has affected 15% of the days of the study (337 days) and involved an increase in the average daily concentrations of PM10 (49.7 µg/m3 vs. 19.2 µg/m3) and PM 2.5–10 (36.2 µg/m3 vs. 10.3 µg/m3) compared to days without dust. The excess risk percentages (IR%) for visits related to asthma in children aged between 5 and 15 years on days with dust compared to days without dust were, for PM10, ((IR %: 9.1% (CI95%, 7.1%–11.1%) versus 1.1%(CI95%, −5.9%–4.6%)) and for PM2.5–10 (IR%: 4.5%(CI95%, 2.5%–6.5%) versus 1.6% (CI95%, −1.1%–3.4%). There was no statistical difference in the IR% for periods with Saharan dust among different age group of children and between boys and girls for PM10 and PM2.5–10. Conclusion The PM10 and PM2.5–10 pollutants contained in the Saharan dust increased the risk of visiting the health emergency department for children with asthma in Guadeloupe during the study period. PMID:24603899

Quantifying the relationship between extreme air pollution events and extreme weather events

NASA Astrophysics Data System (ADS)

Zhang, Henian; Wang, Yuhang; Park, Tae-Won; Deng, Yi

2017-05-01

Extreme weather events can strongly affect surface air quality, which has become a major environmental factor to affect human health. Here, we examined the relationship between extreme ozone and PM2.5 (particular matter with an aerodynamic diameter less than 2.5 μm) events and the representative meteorological parameters such as daily maximum temperature (Tmax), minimum relative humidity (RHmin), and minimum wind speed (Vmin), using the location-specific 95th or 5th percentile threshold derived from historical reanalysis data (30 years for ozone and 10 years for PM2.5). We found that ozone and PM2.5 extremes were decreasing over the years, reflecting EPA's tightened standards and effort on reducing the corresponding precursor's emissions. Annual ozone and PM2.5 extreme days were highly correlated with Tmax and RHmin, especially in the eastern U.S. They were positively (negatively) correlated with Vmin in urban (rural and suburban) stations. The overlapping ratios of ozone extreme days with Tmax were fairly constant, about 32%, and tended to be high in fall and low in winter. Ozone extreme days were most sensitive to Tmax, then RHmin, and least sensitive to Vmin. The majority of ozone extremes occurred when Tmax was between 300 K and 320 K, RHmin was less than 40%, and Vmin was less than 3 m/s. The number of annual extreme PM2.5 days was highly positively correlated with the extreme RHmin/Tmax days, with correlation coefficient between PM2.5/RHmin highest in urban and suburban regions and the correlation coefficient between PM2.5/Tmax highest in rural area. Tmax has more impact on PM2.5 extreme over the eastern U.S. Extreme PM2.5 days were more likely to occur at low RH conditions in the central and southeastern U.S., especially during spring time, and at high RH conditions in the northern U.S. and the Great Plains. Most extreme PM2.5 events occurred when Tmax was between 300 K and 320 K and RHmin was between 10% and 50%. Extreme PM2.5 days usually occurred when Vmin was under 2 m/s. However, during spring season in the Southeast and fall season in Northwest, high winds were found to accompany extreme PM2.5 days, likely reflecting the impact of fire emissions.

Two Model-Based Methods for Policy Analyses of Fine Particulate Matter Control in China: Source Apportionment and Source Sensitivity

NASA Astrophysics Data System (ADS)

Li, X.; Zhang, Y.; Zheng, B.; Zhang, Q.; He, K.

2013-12-01

Anthropogenic emissions have been controlled in recent years in China to mitigate fine particulate matter (PM2.5) pollution. Recent studies show that sulfate dioxide (SO2)-only control cannot reduce total PM2.5 levels efficiently. Other species such as nitrogen oxide, ammonia, black carbon, and organic carbon may be equally important during particular seasons. Furthermore, each species is emitted from several anthropogenic sectors (e.g., industry, power plant, transportation, residential and agriculture). On the other hand, contribution of one emission sector to PM2.5 represents contributions of all species in this sector. In this work, two model-based methods are used to identify the most influential emission sectors and areas to PM2.5. The first method is the source apportionment (SA) based on the Particulate Source Apportionment Technology (PSAT) available in the Comprehensive Air Quality Model with extensions (CAMx) driven by meteorological predictions of the Weather Research and Forecast (WRF) model. The second method is the source sensitivity (SS) based on an adjoint integration technique (AIT) available in the GEOS-Chem model. The SA method attributes simulated PM2.5 concentrations to each emission group, while the SS method calculates their sensitivity to each emission group, accounting for the non-linear relationship between PM2.5 and its precursors. Despite their differences, the complementary nature of the two methods enables a complete analysis of source-receptor relationships to support emission control policies. Our objectives are to quantify the contributions of each emission group/area to PM2.5 in the receptor areas and to intercompare results from the two methods to gain a comprehensive understanding of the role of emission sources in PM2.5 formation. The results will be compared in terms of the magnitudes and rankings of SS or SA of emitted species and emission groups/areas. GEOS-Chem with AIT is applied over East Asia at a horizontal grid resolution of 0.5° (Lat) × 0.67° (Lon). WRF/CAMx with PSAT is applied to nested grids: 36-km × 36-km over China and 12-km × 12-km over northern China. These simulations are performed for 2006 and 2011. Beijing and northern Hebei are selected as representative receptor areas. Simulated surface concentrations by both models are evaluated with available observations in China. Focusing on inorganic aerosols (sulfate, nitrate and ammonium), preliminary SS results from GEOS-Chem/AIT at Beijing identify the top three major emission sectors to be agriculture, residential, and transportation in winter and agriculture, industry and power plant in summer. The top four source areas are northern Hebei, local, Neimenggu, and Liaoning in winter and northern Hebei, local, Shandong, and southern Hebei in summer. The synthesis of SS and SA for influential emission groups or areas from this work will provide a quantitative basis for emission control strategy development and policy making for PM2.5 control in China.

Adults with developmental dyslexia show selective impairments in time-based and self-initiated prospective memory: Self-report and clinical evidence.

PubMed

Smith-Spark, James H; Zięcik, Adam P; Sterling, Christopher

2017-03-01

Prospective memory (PM; memory for delayed intentions) would seem to be impaired in dyslexia but evidence is currently limited in scope. There is a need, therefore, firstly, to explore PM under controlled conditions using a broader range of PM tasks than used previously and, secondly, to determine whether objectively measured and self-reported PM problems can be found in the same individuals with dyslexia. The responses of 30 adults with dyslexia were compared with those of 30 IQ-matched adults without dyslexia on a self-report and a clinical measure of PM. Dyslexia-related deficits were shown on the clinical measure overall and, more particularly, when PM responses had to be made to cues based on time rather than environmental events. Adults with dyslexia were also more likely to forget to carry out an intention under naturalistic conditions 24h later. On the self-report questionnaire, the group with dyslexia reported significantly more frequent problems with PM overall, despite using more techniques to aid their memory. In particular, problems were identified with longer-term PM tasks and PM which had to be self-initiated. Dyslexia-related PM deficits were found under both laboratory and everyday conditions in the same participants; the first time that this has been demonstrated. These findings support previous experimental research which has highlighted dyslexia-related deficits in PM when the enacting of intentions is based on time cues and/or has to be self-initiated rather than being in prompted by environmental events. Copyright © 2017 Elsevier Ltd. All rights reserved.

Decline of ambient air pollution levels due to measures to control automobile emissions and effects on the prevalence of respiratory and allergic disorders among children in Japan.

PubMed

Hasunuma, Hideki; Ishimaru, Yasushi; Yoda, Yoshiko; Shima, Masayuki

2014-05-01

In Japan, air pollution due to nitrogen oxides (NOx) and particulate matter (PM) has been gradually reduced since control measures based on the Automobile NOx/PM law were enforced beginning in 2001. The effects of decrease in air pollutants due to the control measures during the past decade on the prevalence of respiratory and allergic disorders such as asthma in children were evaluated. Using data of 618,973 children collected in 28 regions of Japan from 1997 to 2009, we evaluated whether reductions in the concentrations of nitrogen dioxide (NO2) and suspended particulate matter (SPM) contribute to the decrease in the prevalence of asthma, wheezing, bronchitis, allergic rhinitis, and atopic dermatitis by multiple linear regression analysis, including adjustments for related factors. The annual rates of decrease in air pollution in the PM-law-enforced areas were 2.0 and 2.5 times higher for NO2 and SPM, respectively, compared with those in the non-enforced areas. The prevalence of asthma decreased significantly at -0.073% per year in the areas in which measures based on the Automobile NOx/PM law were taken but not in area where such measures were not applied. Multiple linear regression analysis showed a reduction in the ambient air pollution was significantly associated with a reduction in the prevalence of asthma, with a rate of 0.118% [95% confidence interval (CI): 0.012-0.225] per 1 ppb for NO2, and 0.050% [95% CI: 0.020-0.080] per 1 μg/m(3) for SPM. An increase in the ambient air pollution was associated with an increase in the prevalence of atopic dermatitis of 0.390% [95% CI: 0.107-0.673] per 1 ppb for NO2, 0.141% [95% CI: 0.058-0.224] per 1 μg/m(3) for SPM. The changes in the prevalence of wheezing and allergic rhinitis were not significantly correlated with changes in air pollutant concentrations. The enforcement of measures to control automobile emissions based on the Automobile NOx/PM law was shown to have reduced air pollution and contributed to decreases in the prevalence of respiratory and allergic disorders in 3-year-old children. Copyright © 2014 Elsevier Inc. All rights reserved.

33 CFR 165.918 - Safety Zones; Annual events requiring safety zones in the Captain of the Port Sault Sainte Marie...

Code of Federal Regulations, 2014 CFR

2014-07-01

... due to inclement weather, then this section will be enforced July 5 from 9 p.m. until 11 p.m. (2... zone will be enforced each year on July 4 from 9 p.m. until 12:30 a.m. on July 5. If the July 4 fireworks are cancelled due to inclement weather, then this section will be enforced on July 5 from 9 p.m...

33 CFR 165.918 - Safety Zones; Annual events requiring safety zones in the Captain of the Port Sault Sainte Marie...

Code of Federal Regulations, 2011 CFR

2011-07-01

... due to inclement weather, then this section will be enforced July 5 from 9 p.m. until 11 p.m. (2... zone will be enforced each year on July 4 from 9 p.m. until 12:30 a.m. on July 5. If the July 4 fireworks are cancelled due to inclement weather, then this section will be enforced on July 5 from 9 p.m...

33 CFR 165.918 - Safety Zones; Annual events requiring safety zones in the Captain of the Port Sault Sainte Marie...

Code of Federal Regulations, 2012 CFR

2012-07-01

... due to inclement weather, then this section will be enforced July 5 from 9 p.m. until 11 p.m. (2... zone will be enforced each year on July 4 from 9 p.m. until 12:30 a.m. on July 5. If the July 4 fireworks are cancelled due to inclement weather, then this section will be enforced on July 5 from 9 p.m...

Everyday and prospective memory deficits in ecstasy/polydrug users.

PubMed

Hadjiefthyvoulou, Florentia; Fisk, John E; Montgomery, Catharine; Bridges, Nikola

2011-04-01

The impact of ecstasy/polydrug use on real-world memory (i.e. everyday memory, cognitive failures and prospective memory [PM]) was investigated in a sample of 42 ecstasy/polydrug users and 31 non-ecstasy users. Laboratory-based PM tasks were administered along with self-reported measures of PM to test whether any ecstasy/polydrug-related impairment on the different aspects of PM was present. Self-reported measures of everyday memory and cognitive failures were also administered. Ecstasy/polydrug associated deficits were observed on both laboratory and self-reported measures of PM and everyday memory. The present study extends previous research by demonstrating that deficits in PM are real and cannot be simply attributed to self-misperceptions. The deficits observed reflect some general capacity underpinning both time- and event-based PM contexts and are not task specific. Among this group of ecstasy/polydrug users recreational use of cocaine was also prominently associated with PM deficits. Further research might explore the differential effects of individual illicit drugs on real-world memory.

Exposure to ambient air pollution and the incidence of dementia: A population-based cohort study.

PubMed

Chen, Hong; Kwong, Jeffrey C; Copes, Ray; Hystad, Perry; van Donkelaar, Aaron; Tu, Karen; Brook, Jeffrey R; Goldberg, Mark S; Martin, Randall V; Murray, Brian J; Wilton, Andrew S; Kopp, Alexander; Burnett, Richard T

2017-11-01

Emerging studies have implicated air pollution in the neurodegenerative processes. Less is known about the influence of air pollution, especially at the relatively low levels, on developing dementia. We conducted a population-based cohort study in Ontario, Canada, where the concentrations of pollutants are among the lowest in the world, to assess whether air pollution exposure is associated with incident dementia. The study population comprised all Ontario residents who, on 1 April 2001, were 55-85years old, Canadian-born, and free of physician-diagnosed dementia (~2.1 million individuals). Follow-up extended until 2013. We used population-based health administrative databases with a validated algorithm to ascertain incident diagnosis of dementia as well as prevalent cases. Using satellite observations, land-use regression model, and an optimal interpolation method, we derived long-term average exposure to fine particulate matter (≤2.5μm in diameter) (PM 2.5 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ), respectively at the subjects' historical residences based on a population-based registry. We used multilevel spatial random-effects Cox proportional hazards models, adjusting for individual and contextual factors, such as diabetes, brain injury, and neighborhood income. We conducted various sensitivity analyses, such as lagging exposure up to 10years and considering a negative control outcome for which no (or weaker) association with air pollution is expected. We identified 257,816 incident cases of dementia in 2001-2013. We found a positive association between PM 2.5 and dementia incidence, with a hazard ratio (HR) of 1.04 (95% confidence interval (CI): 1.03-1.05) for every interquartile-range increase in exposure to PM 2.5 . Similarly, NO 2 was associated with increased incidence of dementia (HR=1.10; 95% CI: 1.08-1.12). No association was found for O 3 . These associations were robust to all sensitivity analyses examined. These estimates translate to 6.1% of dementia cases (or 15,813 cases) attributable to PM 2.5 and NO 2 , based on the observed distribution of exposure relative to the lowest quartile in concentrations in this cohort. In this large cohort, exposure to air pollution, even at the relative low levels, was associated with higher dementia incidence. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Impact of Saharan dust particles on hospital admissions in Madrid (Spain).

PubMed

Reyes, María; Díaz, Julio; Tobias, Aurelio; Montero, Juan Carlos; Linares, Cristina

2014-01-01

Saharan dust intrusions make a major contribution to levels of particulate matter (PM) present in the atmosphere of large cities. We analysed the impact of different PM fractions during periods with and without Saharan dust intrusions, using time-series analysis with Poisson regression models, based on: concentrations of coarse PM (PM10 and PM10-2.5) and fine PM (PM2.5); and daily all-, circulatory- and respiratory-cause hospital admissions. While periods without Saharan dust intrusions were marked by a statistically significant association between daily mean PM2.5 concentrations and all- and circulatory-cause hospital admissions, periods with such intrusions saw a significant increase in respiratory-cause admissions associated with fractions corresponding to PM10 and PM10-2.5.

Radiation Hardness of dSiPM Sensors in a Proton Therapy Radiation Environment

NASA Astrophysics Data System (ADS)

Diblen, Faruk; Buitenhuis, Tom; Solf, Torsten; Rodrigues, Pedro; van der Graaf, Emiel; van Goethem, Marc-Jan; Brandenburg, Sytze; Dendooven, Peter

2017-07-01

In vivo verification of dose delivery in proton therapy by means of positron emission tomography (PET) or prompt gamma imaging is mostly based on fast scintillation detectors. The digital silicon photomultiplier (dSiPM) allows excellent scintillation detector timing properties and is thus being considered for such verification methods. We present here the results of the first investigation of radiation damage to dSiPM sensors in a proton therapy radiation environment. Radiation hardness experiments were performed at the AGOR cyclotron facility at the KVI-Center for Advanced Radiation Technology, University of Groningen. A 150-MeV proton beam was fully stopped in a water target. In the first experiment, bare dSiPM sensors were placed at 25 cm from the Bragg peak, perpendicular to the beam direction, a geometry typical for an in situ implementation of a PET or prompt gamma imaging device. In the second experiment, dSiPM-based PET detectors containing lutetium yttrium orthosilicate scintillator crystal arrays were placed at 2 and 4 m from the Bragg peak, perpendicular to the beam direction; resembling an in-room PET implementation. Furthermore, the experimental setup was simulated with a Geant4-based Monte Carlo code in order to determine the angular and energy distributions of the neutrons and to determine the 1-MeV equivalent neutron fluences delivered to the dSiPM sensors. A noticeable increase in dark count rate (DCR) after an irradiation with about 108 1-MeV equivalent neutrons/cm2 agrees with observations by others for analog SiPMs, indicating that the radiation damage occurs in the single photon avalanche diodes and not in the electronics integrated on the sensor chip. It was found that in the in situ location, the DCR becomes too large for successful operation after the equivalent of a few weeks of use in a proton therapy treatment room (about 5 × 1013 protons). For PET detectors in an in-room setup, detector performance was unchanged even after an irradiation equivalent to three years of use in a treatment room (3 × 1015 protons).

A new method for assessing the contribution of Primary Biological Atmospheric Particles to the mass concentration of the atmospheric aerosol.

PubMed

Perrino, Cinzia; Marcovecchio, Francesca

2016-02-01

Primary Biologic Atmospheric Particles (PBAPs) constitute an interesting and poorly investigated component of the atmospheric aerosol. We have developed and validated a method for evaluating the contribution of overall PBAPs to the mass concentration of atmospheric particulate matter (PM). The method is based on PM sampling on polycarbonate filters, staining of the collected particles with propidium iodide, observation at epifluorescence microscope and calculation of the bioaerosol mass using a digital image analysis software. The method has been also adapted to the observation and quantification of size-segregated aerosol samples collected by multi-stage impactors. Each step of the procedure has been individually validated. The relative repeatability of the method, calculated on 10 pairs of atmospheric PM samples collected side-by-side, was 16%. The method has been applied to real atmospheric samples collected in the vicinity of Rome, Italy. Size distribution measurements revealed that PBAPs was mainly in the coarse fraction of PM, with maxima in the range 5.6-10 μm. 24-h samples collected during different period of the year have shown that the concentration of bioaerosol was in the range 0.18-5.3 μg m(-3) (N=20), with a contribution to the organic matter in PM10 in the range 0.5-31% and to the total mass concentration of PM10 in the range 0.3-18%. The possibility to determine the concentration of total PBAPs in PM opens up interesting perspectives in terms of studying the health effects of these components and of increasing our knowledge about the composition of the organic fraction of the atmospheric aerosol. Copyright © 2015 Elsevier Ltd. All rights reserved.

Indoor human exposure to size-fractionated aerosols during the 2015 Southeast Asian smoke haze and assessment of exposure mitigation strategies

NASA Astrophysics Data System (ADS)

Sharma, Ruchi; Balasubramanian, Rajasekhar

2017-11-01

The 2015 smoke haze episode was one of the most severe and prolonged transboundary air pollution events ever seen in Southeast Asia (SEA), affecting the air quality of several countries within the region including Indonesia, Malaysia and Singapore. The 24 h mean outdoor PM2.5 (particulate matter (PM) with aerodynamic diameter ≤ 2.5 μm) concentrations ranged from 72-157 μg m-3 in Singapore during this episode, exceeding the WHO 24 h mean PM2.5 guidelines (25 μg m-3) several times over. The smoke haze episode not only affected ambient air quality, but also indoor air quality due to the migration of PM of different sizes from the outdoor to the indoor environment. Despite the frequent occurrence of smoke haze episodes over the years, their potential health impacts on indoor building occupants remain largely unknown in SEA due to the lack of systematic investigations and observational data. The current work was carried out in Singapore to assess human exposure to size-resolved PM during the 2015 smoke haze episode, and to evaluate the effectiveness of exposure mitigation measures in smoke-haze-impacted naturally ventilated indoor environments. The potential health risks associated with exposure to PM2.5 were assessed based on the concentrations of redox active particulate-bound trace elements, which are known to be harmful to human health, with and without exposure mitigation. Overall, it was observed that human health exposure to PM2.5 and its carcinogenic chemical components was reduced substantially by 62% (p < 0.05) while using an air cleaner. However, extremely small hazardous particles were only partially removed by the air cleaner and remain a matter of concern for public health.

Household air pollution from various types of rural kitchens and its exposure assessment.

PubMed

Sidhu, Maninder Kaur; Ravindra, Khaiwal; Mor, Suman; John, Siby

2017-05-15

Exposure to household air pollutants has become a leading environmental health risk in developing countries. Considering this, real-time temporal variation in fine particulate matter (PM 2.5 ) and carbon monoxide (CO) concentrations were measured in various types of rural household kitchens. Observed average concentrations of PM 2.5 , CO, percent relative humidity (%RH) and temperature (T) in five different kitchen types were 549.6μg/m 3 , 4.2ppm, 70.2% and 20°C respectively. Highest CO and PM 2.5 concentration were found in household performing cooking in indoor kitchens (CO: 9.3ppm; PM 2.5 : 696.5μg/m 3 ) followed by outdoor kitchens (CO: 5.8ppm; PM 2.5 : 539.5μg/m 3 ). The concentration of PM 2.5 and CO varied according to the fuel type and highest concentration was observed in kitchens using cowdung cakes followed by agricultural residue>firewood>biogas>Liquefied Petroleum Gas (LPG). Results revealed that the pollutants concentration varied with kitchen type, fuel type and the location of kitchen. An exposure index was developed to calculate the exposure of cook, non-cook and children below 5years. Analysis of exposure index values shows that cooks, who use solid biomass fuel (SBF) in indoor kitchen, are four times more exposed to the harmful pollutants than the cooks using clean fuel. Further, using indoor PM 2.5 concentrations, hazard quotient was calculated based on evaluation of intake concentration and toxicological risk, which also shows that SBF users have higher health risks (hazard quotient>1) than the clean fuel (LPG) users. Copyright © 2017 Elsevier B.V. All rights reserved.

Are air pollution and traffic noise independently associated with atherosclerosis: the Heinz Nixdorf Recall Study.

PubMed

Kälsch, Hagen; Hennig, Frauke; Moebus, Susanne; Möhlenkamp, Stefan; Dragano, Nico; Jakobs, Hermann; Memmesheimer, Michael; Erbel, Raimund; Jöckel, Karl-Heinz; Hoffmann, Barbara

2014-04-01

Living close to high traffic has been linked to subclinical atherosclerosis, however it is not clear, whether fine particulate matter (PM) air pollution or noise, two important traffic-related exposures, are responsible for the association. We investigate the independent associations of long-term exposure to fine PM and road traffic noise with thoracic aortic calcification (TAC), a reliable measure of subclinical atherosclerosis. We used baseline data (2000-2003) from the German Heinz Nixdorf Recall Study, a population-based cohort of 4814 randomly selected participants. We assessed residential long-term exposure to PM with a chemistry transport model, and to road traffic noise using façade levels from noise models as weighted 24 h mean noise (Lden) and night-time noise (Lnight). Thoracic aortic calcification was quantified from non-contrast enhanced electron beam computed tomography. We used multiple linear regression to estimate associations of environmental exposures with ln(TAC+1), adjusting for each other, individual, and neighbourhood characteristics. In 4238 participants (mean age 60 years, 49.9% male), PM2.5 (aerodynamic diameter ≤2.5 µm) and Lnight are both associated with an increasing TAC-burden of 18.1% (95% CI: 6.6; 30.9%) per 2.4 µg/m(3) PM2.5 and 3.9% (95% CI 0.0; 8.0%) per 5dB(A) Lnight, respectively, in the full model and after mutual adjustment. We did not observe effect measure modification of the PM2.5 association by Lnight or vice versa. Long-term exposure to fine PM and night-time traffic noise are both independently associated with subclinical atherosclerosis and may both contribute to the association of traffic proximity with atherosclerosis.

Comparison of receptor models for source apportionment of the PM10 in Zaragoza (Spain).

PubMed

Callén, M S; de la Cruz, M T; López, J M; Navarro, M V; Mastral, A M

2009-08-01

Receptor models are useful to understand the chemical and physical characteristics of air pollutants by identifying their sources and by estimating contributions of each source to receptor concentrations. In this work, three receptor models based on principal component analysis with absolute principal component scores (PCA-APCS), Unmix and positive matrix factorization (PMF) were applied to study for the first time the apportionment of the airborne particulate matter less or equal than 10microm (PM10) in Zaragoza, Spain, during 1year sampling campaign (2003-2004). The PM10 samples were characterized regarding their concentrations in inorganic components: trace elements and ions and also organic components: polycyclic aromatic hydrocarbons (PAH) not only in the solid phase but also in the gas phase. A comparison of the three receptor models was carried out in order to do a more robust characterization of the PM10. The three models predicted that the major sources of PM10 in Zaragoza were related to natural sources (60%, 75% and 47%, respectively, for PCA-APCS, Unmix and PMF) although anthropogenic sources also contributed to PM10 (28%, 25% and 39%). With regard to the anthropogenic sources, while PCA and PMF allowed high discrimination in the sources identification associated with different combustion sources such as traffic and industry, fossil fuel, biomass and fuel-oil combustion, heavy traffic and evaporative emissions, the Unmix model only allowed the identification of industry and traffic emissions, evaporative emissions and heavy-duty vehicles. The three models provided good correlations between the experimental and modelled PM10 concentrations with major precision and the closest agreement between the PMF and PCA models.

Prenatal fine particulate exposure and early childhood asthma: Effect of maternal stress and fetal sex.

PubMed

Lee, Alison; Leon Hsu, Hsiao-Hsien; Mathilda Chiu, Yueh-Hsiu; Bose, Sonali; Rosa, Maria José; Kloog, Itai; Wilson, Ander; Schwartz, Joel; Cohen, Sheldon; Coull, Brent A; Wright, Robert O; Wright, Rosalind J

2018-05-01

The impact of prenatal ambient air pollution on child asthma may be modified by maternal stress, child sex, and exposure dose and timing. We prospectively examined associations between coexposure to prenatal particulate matter with an aerodynamic diameter of less than 2.5 microns (PM 2.5 ) and maternal stress and childhood asthma (n = 736). Daily PM 2.5 exposure during pregnancy was estimated using a validated satellite-based spatiotemporally resolved prediction model. Prenatal maternal negative life events (NLEs) were dichotomized around the median (high: NLE ≥ 3; low: NLE < 3). We used Bayesian distributed lag interaction models to identify sensitive windows for prenatal PM 2.5 exposure on children's asthma by age 6 years, and determine effect modification by maternal stress and child sex. Bayesian distributed lag interaction models identified a critical window of exposure (19-23 weeks' gestation, cumulative odds ratio, 1.15; 95% CI, 1.03-1.26; per interquartile range [1.7 μg/m 3 ] increase in prenatal PM 2.5 level) during which children concomitantly exposed to prenatal PM 2.5 and maternal stress had increased risk of asthma. No significant association was seen in children born to women reporting low prenatal stress. When examining modifying effects of prenatal stress and fetal sex, we found that boys born to mothers with higher prenatal stress were most vulnerable (19-21 weeks' gestation; cumulative odds ratio, 1.28; 95% CI, 1.15-1.41; per interquartile range increase in PM 2.5 ). Prenatal PM 2.5 exposure during sensitive windows is associated with increased risk of child asthma, especially in boys concurrently exposed to elevated maternal stress. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Identifying sensitive windows for prenatal particulate air pollution exposure and mitochondrial DNA content in cord blood.

PubMed

Rosa, Maria José; Just, Allan C; Guerra, Marco Sánchez; Kloog, Itai; Hsu, Hsiao-Hsien Leon; Brennan, Kasey J; García, Adriana Mercado; Coull, Brent; Wright, Rosalind J; Téllez Rojo, Martha María; Baccarelli, Andrea A; Wright, Robert O

2017-01-01

Changes in mitochondrial DNA (mtDNA) can serve as a marker of cumulative oxidative stress (OS) due to the mitochondria's unique genome and relative lack of repair systems. In utero particulate matter ≤2.5μm (PM 2.5 ) exposure can enhance oxidative stress. Our objective was to identify sensitive windows to predict mtDNA damage experienced in the prenatal period due to PM 2.5 exposure using mtDNA content measured in cord blood. Women affiliated with the Mexican social security system were recruited during pregnancy in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) study. Mothers with cord blood collected at delivery and complete covariate data were included (n=456). Mothers' prenatal daily exposure to PM 2.5 was estimated using a satellite-based spatio-temporally resolved prediction model and place of residence during pregnancy. DNA was extracted from umbilical cord leukocytes. Quantitative real-time polymerase chain reaction (qPCR) was used to determine mtDNA content. A distributive lag regression model (DLM) incorporating weekly averages of daily PM 2.5 predictions was constructed to plot the association between exposure and OS over the length of pregnancy. In models that included child's sex, mother's age at delivery, prenatal environmental tobacco smoke exposure, birth year, maternal education, and assay batch, we found significant associations between higher PM 2.5 exposure during late pregnancy (35-40weeks) and lower mtDNA content in cord blood. Increased PM 2.5 during a specific prenatal window in the third trimester was associated with decreased mtDNA content suggesting heightened sensitivity to PM-induced OS during this life stage. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Decadal Spatial and Temporal Analysis of PM10 in Istanbul: 1998-2008

NASA Astrophysics Data System (ADS)

Kilic, D.; Baltacibasi, S.; Unal, A.; Kindap, T.

2012-04-01

This study provides valuable new insights into the key contributors to ambient air quality in Istanbul, one of the largest mega-cities in Europe. The study builds on work in Europe that links air quality with national dynamics such as economical, vehicle activity and, meteorology in the long-term. Spatial and temporal analysis was performed on PM10 levels measured at 10 air quality monitoring sta- tions (AQMSs) in Istanbul from 1998 to 2008. The analysis found that ambient air quality levels are linked with winter temperatures as well as economic activity. The mean annual PM10 levels in 2001 are among the three lowest years in the period. This decrease corresponds with daily temperature data and annual number of heating degree days which shows that 2001 was one of the warmest winters in Istanbul. Warmer temperatures led to a decrease in energy demand for heating purposes, as demonstrated by the coal sales data. Low ambient air quality levels in 2001 also correspond to a decrease in gross domestic product and electricity demand due to the national economic crisis in March 2001 which affected industrial activity and as a result industrial and energy production related emissions. The study also found that air quality levels in Istanbul are a threat to human health and the environment. Based on the annual and seasonal PM10 profiles of the stations, 5 of the 6 AQMSs in the European Side of the city had mean PM10 values above the EU limit for PM10 for over 50% of the time. According to the linear regression analysis, there is no significant increase or decrease in the annual PM10 trend in Istanbul, this may be due warm winter and economic crisis in 2001.

Lake Holloman Recreational Area Development Environmental Assessment

DTIC Science & Technology

2009-08-01

facilities Total daily trips are applied to the following factors depending on the corresponding years. Year 2005 through 2009: VOCE = .016...Trips NOxE = .015 * Trips PM10E = .0022 * Trips COE = .262 * Trips Year 2010 and beyond: VOCE = .012 * Trips NOxE = .013 * Trips PM10E = .0022...Trips COE = .262 * Trips To convert from pounds per day to tons per year: VOC (tons/yr) = VOCE * DPYII/2000 NOx (tons/yr) = NOxE * DPYII/2000

Acute stress affects prospective memory functions via associative memory processes.

PubMed

Szőllősi, Ágnes; Pajkossy, Péter; Demeter, Gyula; Kéri, Szabolcs; Racsmány, Mihály

2018-01-01

Recent findings suggest that acute stress can improve the execution of delayed intentions (prospective memory, PM). However, it is unclear whether this improvement can be explained by altered executive control processes or by altered associative memory functioning. To investigate this issue, we used physical-psychosocial stressors to induce acute stress in laboratory settings. Then participants completed event- and time-based PM tasks requiring the different contribution of control processes and a control task (letter fluency) frequently used to measure executive functions. According to our results, acute stress had no impact on ongoing task performance, time-based PM, and verbal fluency, whereas it enhanced event-based PM as measured by response speed for the prospective cues. Our findings indicate that, here, acute stress did not affect executive control processes. We suggest that stress affected event-based PM via associative memory processes. Copyright © 2017 Elsevier B.V. All rights reserved.

Oxidative potential of ambient PM2.5 in the coastal cities of the Bohai Sea, northern China: Seasonal variation and source apportionment.

PubMed

Liu, WeiJian; Xu, YunSong; Liu, WenXin; Liu, QingYang; Yu, ShuangYu; Liu, Yang; Wang, Xin; Tao, Shu

2018-05-01

Emissions of air pollutants from primary and secondary sources in China are considerably higher than those in developed countries, and exposure to air pollution is main risk of public health. Identifying specific particulate matter (PM) compositions and sources are essential for policy makers to propose effective control measures for pollutant emissions. Ambient PM 2.5 samples covered a whole year were collected from three coastal cities of the Bohai Sea. Oxidative potential (OP) was selected as the indicator to characterize associated PM compositions and sources most responsible for adverse impacts on human health. Positive matrix factorization (PMF) and multiple linear regression (MLR) were employed to estimate correlations of PM 2.5 sources with OP. The volume- and mass-based dithiothreitol (DTT v and DTT m ) activities of PM 2.5 were significantly higher in local winter or autumn (p < 0.01). Spatial and seasonal variations in DTT v and DTT m were much larger than mass concentrations of PM 2.5 , indicated specific chemical components are responsible for PM 2.5 derived OP. Strong correlations (r > 0.700, p < 0.01) were found between DTT activity and water-soluble organic carbon (WSOC) and some transition metals. Using PMF, source fractions of PM 2.5 were resolved as secondary source, traffic source, biomass burning, sea spray and urban dust, industry, coal combustion, and mineral dust. Further quantified by MLR, coal combustion, biomass burning, secondary sources, industry, and traffic source were dominant contributors to the water-soluble DTT v activity. Our results also suggested large differences in seasonal contributions of different sources to DTT v variability. A higher contribution of DTT v was derived from coal combustion during the local heating period. Secondary sources exhibited a greater fraction of DTT v in summer, when there was stronger solar radiation. Traffic sources exhibited a prevailing contribution in summer, and industry contributed larger proportions in spring and winter. Future abatement priority of air pollution should reduce the sources contributing to OP of PM 2.5 . Copyright © 2018 Elsevier Ltd. All rights reserved.

Burden of Outdoor Air Pollution in Kerala, India—A First Health Risk Assessment at State Level

PubMed Central

Tobollik, Myriam; Razum, Oliver; Wintermeyer, Dirk; Plass, Dietrich

2015-01-01

Ambient air pollution causes a considerable disease burden, particularly in South Asia. The objective of the study is to test the feasibility of applying the environmental burden of disease method at state level in India and to quantify a first set of disease burden estimates due to ambient air pollution in Kerala. Particulate Matter (PM) was used as an indicator for ambient air pollution. The disease burden was quantified in Years of Life Lost (YLL) for the population (30 + years) living in urban areas of Kerala. Scenario analyses were performed to account for uncertainties in the input parameters. 6108 (confidence interval (95% CI): 4150–7791) of 81,636 total natural deaths can be attributed to PM, resulting in 96,359 (95% CI: 65,479–122,917) YLLs due to premature mortality (base case scenario, average for 2008–2011). Depending on the underlying assumptions the results vary between 69,582 and 377,195 YLLs. Around half of the total burden is related to cardiovascular deaths. Scenario analyses show that a decrease of 10% in PM concentrations would save 15,904 (95% CI: 11,090–19,806) life years. The results can be used to raise awareness about air quality standards at a local level and to support decision-making processes aiming at cleaner and healthier environments. PMID:26343701

Curriculum-Based Measurement of Reading Growth: Weekly versus Intermittent Progress Monitoring

ERIC Educational Resources Information Center

Jenkins, Joseph; Schulze, Margaret; Marti, Allison; Harbaugh, Allen G.

2017-01-01

We examined the idea that leaner schedules of progress monitoring (PM) can lighten assessment demands without undermining decision-making accuracy. Using curriculum-based measurement of reading, we compared effects on decision accuracy of 5 intermittent PM schedules relative to that of every-week PM. For participating students with high-incidence…

Distribution and sources of polycyclic aromatic hydrocarbons in size-differentiated re-suspended dust on building surfaces in an oilfield city, China

NASA Astrophysics Data System (ADS)

Kong, Shaofei; Lu, Bing; Ji, Yaqin; Bai, Zhipeng; Xu, Yonghai; Liu, Yong; Jiang, Hua

2012-08-01

Thirty re-suspended dust samples were collected from building surfaces in an oilfield city, re-suspended and sampled through PM2.5, PM10 and PM100 inlets and analyzed for 18 PAHs by GC-MS technique. PAHs concentrations, toxicity and profiles characteristic for different districts and size were studied. PAHs sources were identified by diagnostic ratios and primary component analysis. Results showed that the total amounts of analyzed PAHs in re-suspended dust in Dongying were 45.29, 23.79 and 11.41 μg g-1 for PM2.5, PM10 and PM100, respectively. PAHs tended to concentrate in finer particles with mass ratios of PM2.5/PM10 and PM10/PM100 as 1.96 ± 0.86 and 2.53 ± 1.57. The old district with more human activities and long oil exploitation history exhibited higher concentrations of PAHs from both combustion and non-combustion sources. BaP-based toxic equivalent factor and BaP-based equivalent carcinogenic power exhibited decreasing sequence as PM2.5 > PM10 > PM100 suggesting that the finer the particles, the more toxic of the dust. NaP, Phe, Flu, Pyr, BbF and BghiP were the abundant species. Coefficient of divergence analysis implied that PAHs in different districts and size fractions had common sources. Coal combustion, industrial sources, vehicle emission and petroleum were probably the main contributions according to the principal component analysis result.

Simulating Silicon Photomultiplier Response to Scintillation Light

PubMed Central

Jha, Abhinav K.; van Dam, Herman T.; Kupinski, Matthew A.; Clarkson, Eric

2015-01-01

The response of a Silicon Photomultiplier (SiPM) to optical signals is affected by many factors including photon-detection efficiency, recovery time, gain, optical crosstalk, afterpulsing, dark count, and detector dead time. Many of these parameters vary with overvoltage and temperature. When used to detect scintillation light, there is a complicated non-linear relationship between the incident light and the response of the SiPM. In this paper, we propose a combined discrete-time discrete-event Monte Carlo (MC) model to simulate SiPM response to scintillation light pulses. Our MC model accounts for all relevant aspects of the SiPM response, some of which were not accounted for in the previous models. We also derive and validate analytic expressions for the single-photoelectron response of the SiPM and the voltage drop across the quenching resistance in the SiPM microcell. These analytic expressions consider the effect of all the circuit elements in the SiPM and accurately simulate the time-variation in overvoltage across the microcells of the SiPM. Consequently, our MC model is able to incorporate the variation of the different SiPM parameters with varying overvoltage. The MC model is compared with measurements on SiPM-based scintillation detectors and with some cases for which the response is known a priori. The model is also used to study the variation in SiPM behavior with SiPM-circuit parameter variations and to predict the response of a SiPM-based detector to various scintillators. PMID:26236040

Potential air quality benefits from increased solar photovoltaic electricity generation in the Eastern United States

NASA Astrophysics Data System (ADS)

Abel, David; Holloway, Tracey; Harkey, Monica; Rrushaj, Arber; Brinkman, Greg; Duran, Phillip; Janssen, Mark; Denholm, Paul

2018-02-01

We evaluate how fine particulate matter (PM2.5) and precursor emissions could be reduced if 17% of electricity generation was replaced with solar photovoltaics (PV) in the Eastern United States. Electricity generation is simulated using GridView, then used to scale electricity-sector emissions of sulfur dioxide (SO2) and nitrogen oxides (NOX) from an existing gridded inventory of air emissions. This approach offers a novel method to leverage advanced electricity simulations with state-of-the-art emissions inventories, without necessitating recalculation of emissions for each facility. The baseline and perturbed emissions are input to the Community Multiscale Air Quality Model (CMAQ version 4.7.1) for a full accounting of time- and space-varying air quality changes associated with the 17% PV scenario. These results offer a high-value opportunity to evaluate the reduced-form AVoided Emissions and geneRation Tool (AVERT), while using AVERT to test the sensitivity of results to changing base-years and levels of solar integration. We find that average NOX and SO2 emissions across the region decrease 20% and 15%, respectively. PM2.5 concentrations decreased on average 4.7% across the Eastern U.S., with nitrate (NO3-) PM2.5 decreasing 3.7% and sulfate (SO42-) PM2.5 decreasing 9.1%. In the five largest cities in the region, we find that the most polluted days show the most significant PM2.5 decrease under the 17% PV generation scenario, and that the greatest benefits are accrued to cities in or near the Ohio River Valley. We find summer health benefits from reduced PM2.5 exposure estimated as 1424 avoided premature deaths (95% Confidence Interval (CI): 284 deaths, 2 732 deaths) or a health savings of 13.1 billion (95% CI: 0.6 billion, 43.9 billion) These results highlight the potential for renewable energy as a tool for air quality managers to support current and future health-based air quality regulations.

Application Study of Comprehensive Forecasting Model Based on Entropy Weighting Method on Trend of PM2.5 Concentration in Guangzhou, China

PubMed Central

Liu, Dong-jun; Li, Li

2015-01-01

For the issue of haze-fog, PM2.5 is the main influence factor of haze-fog pollution in China. The trend of PM2.5 concentration was analyzed from a qualitative point of view based on mathematical models and simulation in this study. The comprehensive forecasting model (CFM) was developed based on the combination forecasting ideas. Autoregressive Integrated Moving Average Model (ARIMA), Artificial Neural Networks (ANNs) model and Exponential Smoothing Method (ESM) were used to predict the time series data of PM2.5 concentration. The results of the comprehensive forecasting model were obtained by combining the results of three methods based on the weights from the Entropy Weighting Method. The trend of PM2.5 concentration in Guangzhou China was quantitatively forecasted based on the comprehensive forecasting model. The results were compared with those of three single models, and PM2.5 concentration values in the next ten days were predicted. The comprehensive forecasting model balanced the deviation of each single prediction method, and had better applicability. It broadens a new prediction method for the air quality forecasting field. PMID:26110332

Application Study of Comprehensive Forecasting Model Based on Entropy Weighting Method on Trend of PM2.5 Concentration in Guangzhou, China.

PubMed

Liu, Dong-jun; Li, Li

2015-06-23

For the issue of haze-fog, PM2.5 is the main influence factor of haze-fog pollution in China. The trend of PM2.5 concentration was analyzed from a qualitative point of view based on mathematical models and simulation in this study. The comprehensive forecasting model (CFM) was developed based on the combination forecasting ideas. Autoregressive Integrated Moving Average Model (ARIMA), Artificial Neural Networks (ANNs) model and Exponential Smoothing Method (ESM) were used to predict the time series data of PM2.5 concentration. The results of the comprehensive forecasting model were obtained by combining the results of three methods based on the weights from the Entropy Weighting Method. The trend of PM2.5 concentration in Guangzhou China was quantitatively forecasted based on the comprehensive forecasting model. The results were compared with those of three single models, and PM2.5 concentration values in the next ten days were predicted. The comprehensive forecasting model balanced the deviation of each single prediction method, and had better applicability. It broadens a new prediction method for the air quality forecasting field.

The effect of future ambient air pollution on human premature mortality to 2100 using output from the ACCMIP model ensemble

NASA Astrophysics Data System (ADS)

Silva, Raquel A.; West, J. Jason; Lamarque, Jean-François; Shindell, Drew T.; Collins, William J.; Dalsoren, Stig; Faluvegi, Greg; Folberth, Gerd; Horowitz, Larry W.; Nagashima, Tatsuya; Naik, Vaishali; Rumbold, Steven T.; Sudo, Kengo; Takemura, Toshihiko; Bergmann, Daniel; Cameron-Smith, Philip; Cionni, Irene; Doherty, Ruth M.; Eyring, Veronika; Josse, Beatrice; MacKenzie, Ian A.; Plummer, David; Righi, Mattia; Stevenson, David S.; Strode, Sarah; Szopa, Sophie; Zengast, Guang

2016-08-01

Ambient air pollution from ground-level ozone and fine particulate matter (PM2.5) is associated with premature mortality. Future concentrations of these air pollutants will be driven by natural and anthropogenic emissions and by climate change. Using anthropogenic and biomass burning emissions projected in the four Representative Concentration Pathway scenarios (RCPs), the ACCMIP ensemble of chemistry-climate models simulated future concentrations of ozone and PM2.5 at selected decades between 2000 and 2100. We use output from the ACCMIP ensemble, together with projections of future population and baseline mortality rates, to quantify the human premature mortality impacts of future ambient air pollution. Future air-pollution-related premature mortality in 2030, 2050 and 2100 is estimated for each scenario and for each model using a health impact function based on changes in concentrations of ozone and PM2.5 relative to 2000 and projected future population and baseline mortality rates. Additionally, the global mortality burden of ozone and PM2.5 in 2000 and each future period is estimated relative to 1850 concentrations, using present-day and future population and baseline mortality rates. The change in future ozone concentrations relative to 2000 is associated with excess global premature mortality in some scenarios/periods, particularly in RCP8.5 in 2100 (316 thousand deaths year-1), likely driven by the large increase in methane emissions and by the net effect of climate change projected in this scenario, but it leads to considerable avoided premature mortality for the three other RCPs. However, the global mortality burden of ozone markedly increases from 382 000 (121 000 to 728 000) deaths year-1 in 2000 to between 1.09 and 2.36 million deaths year-1 in 2100, across RCPs, mostly due to the effect of increases in population and baseline mortality rates. PM2.5 concentrations decrease relative to 2000 in all scenarios, due to projected reductions in emissions, and are associated with avoided premature mortality, particularly in 2100: between -2.39 and -1.31 million deaths year-1 for the four RCPs. The global mortality burden of PM2.5 is estimated to decrease from 1.70 (1.30 to 2.10) million deaths year-1 in 2000 to between 0.95 and 1.55 million deaths year-1 in 2100 for the four RCPs due to the combined effect of decreases in PM2.5 concentrations and changes in population and baseline mortality rates. Trends in future air-pollution-related mortality vary regionally across scenarios, reflecting assumptions for economic growth and air pollution control specific to each RCP and region. Mortality estimates differ among chemistry-climate models due to differences in simulated pollutant concentrations, which is the greatest contributor to overall mortality uncertainty for most cases assessed here, supporting the use of model ensembles to characterize uncertainty. Increases in exposed population and baseline mortality rates of respiratory diseases magnify the impact on premature mortality of changes in future air pollutant concentrations and explain why the future global mortality burden of air pollution can exceed the current burden, even where air pollutant concentrations decrease.

The effect of future ambient air pollution on human premature mortality to 2100 using output from the ACCMIP model ensemble.

PubMed

Silva, Raquel A; West, J Jason; Lamarque, Jean-François; Shindell, Drew T; Collins, William J; Dalsoren, Stig; Faluvegi, Greg; Folberth, Gerd; Horowitz, Larry W; Nagashima, Tatsuya; Naik, Vaishali; Rumbold, Steven T; Sudo, Kengo; Takemura, Toshihiko; Bergmann, Daniel; Cameron-Smith, Philip; Cionni, Irene; Doherty, Ruth M; Eyring, Veronika; Josse, Beatrice; MacKenzie, I A; Plummer, David; Righi, Mattia; Stevenson, David S; Strode, Sarah; Szopa, Sophie; Zeng, Guang

2016-01-01

Ambient air pollution from ground-level ozone and fine particulate matter (PM 2.5 ) is associated with premature mortality. Future concentrations of these air pollutants will be driven by natural and anthropogenic emissions and by climate change. Using anthropogenic and biomass burning emissions projected in the four Representative Concentration Pathway scenarios (RCPs), the ACCMIP ensemble of chemistry-climate models simulated future concentrations of ozone and PM 2.5 at selected decades between 2000 and 2100. We use output from the ACCMIP ensemble, together with projections of future population and baseline mortality rates, to quantify the human premature mortality impacts of future ambient air pollution. Future air pollution-related premature mortality in 2030, 2050 and 2100 is estimated for each scenario and for each model using a health impact function based on changes in concentrations of ozone and PM 2.5 relative to 2000 and projected future population and baseline mortality rates. Additionally, the global mortality burden of ozone and PM 2.5 in 2000 and each future period is estimated relative to 1850 concentrations, using present-day and future population and baseline mortality rates. The change in future ozone concentrations relative to 2000 is associated with excess global premature mortality in some scenarios/periods, particularly in RCP8.5 in 2100 (316 thousand deaths/year), likely driven by the large increase in methane emissions and by the net effect of climate change projected in this scenario, but it leads to considerable avoided premature mortality for the three other RCPs. However, the global mortality burden of ozone markedly increases from 382,000 (121,000 to 728,000) deaths/year in 2000 to between 1.09 and 2.36 million deaths/year in 2100, across RCPs, mostly due to the effect of increases in population and baseline mortality rates. PM 2.5 concentrations decrease relative to 2000 in all scenarios, due to projected reductions in emissions, and are associated with avoided premature mortality, particularly in 2100: between -2.39 and -1.31 million deaths/year for the four RCPs. The global mortality burden of PM 2.5 is estimated to decrease from 1.70 (1.30 to 2.10) million deaths/year in 2000 to between 0.95 and 1.55 million deaths/year in 2100 for the four RCPs, due to the combined effect of decreases in PM 2.5 concentrations and changes in population and baseline mortality rates. Trends in future air pollution-related mortality vary regionally across scenarios, reflecting assumptions for economic growth and air pollution control specific to each RCP and region. Mortality estimates differ among chemistry-climate models due to differences in simulated pollutant concentrations, which is the greatest contributor to overall mortality uncertainty for most cases assessed here, supporting the use of model ensembles to characterize uncertainty. Increases in exposed population and baseline mortality rates of respiratory diseases magnify the impact on premature mortality of changes in future air pollutant concentrations and explain why the future global mortality burden of air pollution can exceed the current burden, even where air pollutant concentrations decrease.

Modelling of the urban concentrations of PM2.5 on a high resolution for a period of 35 years, for the assessment of lifetime exposure and health effects

NASA Astrophysics Data System (ADS)

Kukkonen, Jaakko; Kangas, Leena; Kauhaniemi, Mari; Sofiev, Mikhail; Aarnio, Mia; Jaakkola, Jouni J. K.; Kousa, Anu; Karppinen, Ari

2018-06-01

Reliable and self-consistent data on air quality are needed for an extensive period of time for conducting long-term, or even lifetime health impact assessments. We have modelled the urban-scale concentrations of fine particulate matter (PM2.5) in the Helsinki Metropolitan Area for a period of 35 years, from 1980 to 2014. The regional background concentrations were evaluated based on reanalyses of the atmospheric composition on global and European scales, using the SILAM model. The high-resolution urban computations included both the emissions originated from vehicular traffic (separately exhaust and suspension emissions) and those from small-scale combustion, and were conducted using the road network dispersion model CAR-FMI and the multiple-source Gaussian dispersion model UDM-FMI. The modelled concentrations of PM2.5 agreed fairly well with the measured data at a regional background station and at four urban measurement stations, during 1999-2014. The modelled concentration trends were also evaluated for earlier years, until 1988, using proxy analyses. There was no systematic deterioration of the agreement of predictions and data for earlier years (the 1980s and 1990s), compared with the results for more recent years (2000s and early 2010s). The local vehicular emissions were about 5 times higher in the 1980s, compared with the emissions during the latest considered years. The local small-scale combustion emissions increased slightly over time. The highest urban concentrations of PM2.5 occurred in the 1980s; these have since decreased to about to a half of the highest values. In general, regional background was the largest contribution in this area. Vehicular exhaust has been the most important local source, but the relative shares of both small-scale combustion and vehicular non-exhaust emissions have increased in time. The study has provided long-term, high-resolution concentration databases on regional and urban scales that can be used for the assessment of health effects associated with air pollution.

A high-resolution air pollutants emission inventory in 2013 for the Beijing-Tianjin-Hebei region, China

NASA Astrophysics Data System (ADS)

Qi, Ji; Zheng, Bo; Li, Meng; Yu, Fang; Chen, Chuchu; Liu, Fei; Zhou, Xiafei; Yuan, Jing; Zhang, Qiang; He, Kebin

2017-12-01

We developed a high-resolution Beijing-Tianjin-Hebei (BTH) regional air pollutants emission inventory for the year 2013. The inventory was established using a bottom-up approach based on facility-level activity data obtained from multiple data sources. The estimates from the BTH 2013 emission inventory show that the total emissions of SO2, NOX, PM2.5, PM10, CO, NMVOC, NH3, BC, and OC were 2,305, 2,686, 1,090, 1,494, 20,567, 2,207, 623, 160, and 254 Gg, respectively. The industry sector is the largest emissions source for SO2, NOX, PM2.5, PM10, CO, and NMVOC in the BTH region, contributing 72.6%, 43.7%, 59.6%, 64.7%, 60.3%, and 70.4% of the total emissions, respectively. Power plants contributed 11.8% and 23.3% of the total SO2 and NOX emissions, respectively. The transportation sector contributed 28.9% of the total NOX emissions. Emissions from the residential sector accounted for 31.3%, 21.5%, 46.6% and 71.7% of the total PM2.5, NMVOC, BC and OC emissions, respectively. In addition, more than 90% of the total NH3 emissions originate from the agriculture sector, with 44.2% from fertilizer use and 47.7% from livestock. The spatial distribution results illustrate that air pollutant emissions are mainly distributed over the eastern and southern BTH regions. Beijing, Tianjin, Shijiazhuang, Tangshan and Handan are the major contributors of air pollutants. The major NMVOC species in the BTH region are ethylene, acetylene, ethane and toluene. Ethylene is the biggest contributor in Tianjin and Hebei. The largest contributor in Beijing is toluene. There is relatively low uncertainty in SO2 and NOX emission estimates, medium uncertainty in PM2.5, PM10 and CO emission estimates, and high uncertainties in VOC, NH3, BC and OC emission estimates. The proposed policy recommendations, based on the BTH 2013 emission inventory, would be helpful to develop strategies for air pollution control.

Spatial and temporal source apportionment of PM2.5 in Georgia, 2002 to 2013

NASA Astrophysics Data System (ADS)

Zhai, Xinxin; Mulholland, James A.; Russell, Armistead G.; Holmes, Heather A.

2017-07-01

The Chemical Mass Balance (CMB) receptor model was applied to estimate PM2.5 source impacts over Georgia from 2002 to 2013 using ambient PM2.5 species concentration data from 13 sites. Measurements of 19 PM2.5 species were used as inputs along with measurement-based source profiles to estimate the impacts of nine sources, including both primary components (from heavy duty diesel vehicle, light duty gasoline vehicle, biomass burning, coal combustion, and suspended dust sources) and secondary pollutants (ammonium sulfate, ammonium bisulfate, ammonium nitrate, and secondary organic carbon). From 2002 to 2013, PM2.5 total mass decreased from 13.8 μg/m3 to 9.2 μg/m3 averaged across all sites, a 33% decrease. Largest decreases were observed for secondary sulfate and nitrate species (58% and 44%, respectively). The amount of neutralization by ammonium did not change substantially over the time period in spite of substantial decreases in sulfate and nitrate concentrations. Total mobile source impacts decreased more at urban sites (39%) than rural sites (23%), whereas biomass burning decreased more at rural sites (34%) than urban sites (27%). The estimated central-site source impacts are found to spatially represent large areas for secondary pollutants, smaller areas for biomass burning and dust, and very local areas for mobile sources and coal combustion. Trends from the National Emissions Inventory were compared with the annual trends of mobile source impacts, coal combustion impacts, and sulfate concentrations, resulting in statistically significant positive trends with Pearson R2 of 0.80, 0.64, and 0.79, respectively. Results presented here suggest that PM2.5 reductions in Georgia and the Southeast have been achieved by control of both stationary and mobile sources, and that PM2.5 is comprised of increasing fractions of biomass burning emissions and suspended dust. The temporal trends of source impacts at each site adds information about source changes beyond the every-three-year emission inventories for evaluation of emission-based model results.

Long-term exposure to traffic-related particulate matter impairs cognitive function in the elderly.

PubMed

Ranft, Ulrich; Schikowski, Tamara; Sugiri, Dorothee; Krutmann, Jean; Krämer, Ursula

2009-11-01

Animal studies have suggested that fine particulate matter (PM) can translocate from the upper respiratory tract to the brain and cause brain inflammation. Brain inflammation is involved in the pathogenesis of neurodegenerative diseases. Hypothesizing therefore that long-term exposure to fine PM might contribute to the development of Alzheimer's disease (AD), the objective of this study was to investigate the association between exposure to fine PM and mild cognitive impairment (MCI) which is associated with a high risk of progression to AD. A study group of 399 women aged 68-79 years who lived for more than 20 years at the same residential address has been assessed for long-term exposure to PM and tested for MCI. The exposure assessment comprised background concentration of PM(10) and traffic-related PM indicated by the distance of the residential address to the next busy road. The women were assessed for MCI by a battery of several neuropsychological tests and their odor identification ability. Consistent effects of traffic-related air pollution exposure on test performances including a dose-response relation were found. The associations were adjusted for potential confounders using regression analysis. These results indicate that chronic exposure to traffic-related PM may be involved in the pathogenesis of AD.

Allowing Brief Delays in Responding Improves Event-Based Prospective Memory for Young Adults Living with HIV Disease

PubMed Central

Loft, Shayne; Doyle, Katie L.; Naar-King, Sylvie; Outlaw, Angulique Y.; Nichols, Sharon L.; Weber, Erica; Blackstone, Kaitlin; Woods, Steven Paul

2014-01-01

Event-based prospective memory (PM) tasks require individuals to remember to perform an action when they encounter a specific cue in the environment, and have clear relevance for daily functioning for individuals with HIV. In many everyday tasks, the individual must not only maintain the intent to perform the PM task, but the PM task response also competes with the alternative and more habitual task response. The current study examined whether event-based PM can be improved by slowing down the pace of the task environment. Fifty-seven young adults living with HIV performed an ongoing lexical decision task while simultaneously performing a PM task of monitoring for a specific word (which was focal to the ongoing task of making lexical decisions) or syllable contained in a word (which was nonfocal). Participants were instructed to refrain from making task responses until after a tone was presented, which occurred at varying onsets (0–1600ms) after each stimulus appeared. Improvements in focal and non-focal PM accuracy were observed with response delays of 600ms. Furthermore, the difference in PM accuracy between the low demand focal PM task and the resource demanding non-focal PM task was reduced by half across increasingly longer delays, falling from 31% at 0ms delay to only 14% at 1600ms delay. The degree of ongoing task response slowing for the PM conditions, relative to a control condition that did not have a PM task and made lexical decisions only, also decreased with increased delay. Overall, the evidence indicates that delaying the task responses of younger HIV-infected adults increased the probability that the PM relevant features of task stimuli were adequately assessed prior to the ongoing task response, and by implication that younger HIV infected adults can more adequately achieve PM goals when the pace of the task environment is slowed down. PMID:25116075

Evaluation of PM2.5 surface concentration simulated by Version 1 of the NASA’s MERRA Aerosol Reanalysis over Israel and Taiwan

PubMed Central

Provençal, Simon; Buchard, Virginie; da Silva, Arlindo M.; Leduc, Richard; Barrette, Nathalie; Elhacham, Emily; Wang, Sheng-Hsiang

2018-01-01

Version 1 of the NASA MERRA Aerosol Reanalysis (MERRAero) assimilates bias-corrected aerosol optical depth (AOD) data from MODIS-Terra and MODIS-Aqua, and simulates particulate matter (PM) concentration data to reproduce a consistent database of AOD and PM concentration around the world from 2002 to the end of 2015. The purpose of this paper is to evaluate MERRAero’s simulation of fine PM concentration against surface measurements in two regions of the world with relatively high levels of PM concentration but with profoundly different PM composition, those of Israel and Taiwan. Being surrounded by major deserts, Israel’s PM load is characterized by a significant contribution of mineral dust, and secondary contributions of sea salt particles, given its proximity to the Mediterranean Sea, and sulfate particles originating from Israel’s own urban activities and transported from Europe. Taiwan’s PM load is composed primarily of anthropogenic particles (sulfate, nitrate and carbonaceous particles) locally produced or transported from China, with an additional contribution of springtime transport of mineral dust originating from Chinese and Mongolian deserts. The evaluation in Israel produced favorable results with MERRAero slightly overestimating measurements by 6% on average and reproducing an excellent year-to-year and seasonal fluctuation. The evaluation in Taiwan was less favorable with MERRAero underestimating measurements by 42% on average. Two likely reasons explain this discrepancy: emissions of anthropogenic PM and their precursors are largely uncertain in China, and MERRAero doesn’t include nitrate particles in its simulation, a pollutant of predominately anthropogenic sources. MERRAero nevertheless simulates well the concentration of fine PM during the summer, when Taiwan is least affected by the advection of pollution from China. PMID:29670645

Evaluation of PM2.5 Surface Concentration Simulated by Version 1 of the Nasa's MERRA Aerosol Reanalysis Over Israel and Taiwan

NASA Technical Reports Server (NTRS)

Provencal, Simon; Buchard, Virginie; da Silva, Arlindo M.; Leduc, Richard; Barrette, Nathalie; Elhacham, Emily; Wang, Sheng-Hsiang

2017-01-01

Version 1 of the NASA MERRA Aerosol Reanalysis (MERRAero) assimilates bias-corrected 18 aerosol optical depth (AOD) data from MODIS-Terra and MODIS-Aqua, and simulates particulate 19 matter (PM) concentration data to reproduce a consistent database of AOD and PM concentration around 20 the world from 2002 to the end of 2015. The purpose of this paper is to evaluate MERRAeros simulation 21 of fine PM concentration against surface measurements in two regions of the world with relatively high 22 levels of PM concentration but with profoundly different PM composition, those of Israel and Taiwan. 23 Being surrounded by major deserts, Israels PM load is characterized by a significant contribution of 24 mineral dust, and secondary contributions of sea salt particles, given its proximity to the Mediterranean 25 Sea, and sulfate particles originating from Israels own urban activities and transported from Europe. 26 Taiwans PM load is composed primarily of anthropogenic particles (sulfate, nitrate and carbonaceous 27 particles) locally produced or transported from China, with an additional contribution of springtime 28 transport of mineral dust originating from Chinese and Mongolian deserts. The evaluation in Israel 29 produced favorable results with MERRAero slightly overestimating measurements by 6 on average 30 and reproducing an excellent year-to-year and seasonal fluctuation. The evaluation in Taiwan was less 31 favorable with MERRAero underestimating measurements by 42 on average. Two likely reasons 32 explain this discrepancy: emissions of anthropogenic PM and their precursors are largely uncertain in 33 China, and MERRAero doesnt include nitrate particles in its simulation, a pollutant of predominately 34 anthropogenic sources. MERRAero nevertheless simulates well the concentration of fine PM during the 35 summer, when Taiwan is least affected by the advection of pollution from China.

THE RESEARCH TRIANGLE PARK PARTICULATE MATTER PANEL STUDY: MODELING AMBIENT SOURCE CONTRIBUTION TO PERSONAL AND RESIDENTIAL PM MASS CONCENTRATIONS

EPA Science Inventory

The Research Triangle Park (RTP) Particulate Matter (PM) Panel Study represented a one-year investigation of personal, residential and ambient PM mass concentrations across distances as large as 70 km in central North Carolina. One of the primary goals of this effort was to est...

Boiler Briquette Coal versus Raw Coal: Part I-Stack Gas Emissions.

PubMed

Ge, Su; Bai, Zhipeng; Liu, Weili; Zhu, Tan; Wang, Tongjian; Qing, Sheng; Zhang, Junfeng

2001-04-01

Stack gas emissions were characterized for a steam-generating boiler commonly used in China. The boiler was tested when fired with a newly formulated boiler briquette coal (BB-coal) and when fired with conventional raw coal (R-coal). The stack gas emissions were analyzed to determine emission rates and emission factors and to develop chemical source profiles. A dilution source sampling system was used to collect PM on both Teflon membrane filters and quartz fiber filters. The Teflon filters were analyzed gravimetrically for PM 10 and PM 2.5 mass concentrations and by X-ray fluorescence (XRF) for trace elements. The quartz fiber filters were analyzed for organic carbon (OC) and elemental carbon (EC) using a thermal/optical reflectance technique. Sulfur dioxide was measured using the standard wet chemistry method. Carbon monoxide was measured using an Orsat combustion analyzer. The emission rates of the R-coal combustion (in kg/hr), determined using the measured stack gas concentrations and the stack gas emission rates, were 0.74 for PM 10 , 0.38 for PM 25 , 20.7 for SO 2 , and 6.8 for CO, while those of the BB-coal combustion were 0.95 for PM 10 , 0.30 for PM 2 5 , 7.5 for SO 2 , and 5.3 for CO. The fuel-mass-based emission factors (in g/kg) of the R-coal, determined using the emission rates and the fuel burn rates, were 1.68 for PM 10 , 0.87 for PM 25 , 46.7 for SO 2 , and 15 for CO, while those of the BB-coal were 2.51 for PM 10 , 0.79 for PM 2.5 , 19.9 for SO 2 , and 14 for CO. The task-based emission factors (in g/ton steam generated) of the R-coal, determined using the fuel-mass-based emission factors and the coal/ steam conversion factors, were 0.23 for PM 10 , 0.12 for PM 2.5 , 6.4 for SO 2 , and 2.0 for CO, while those of the BB-coal were 0.30 for PM 10 , 0.094 for PM 2.5 , 2.4 for SO 2 , and 1.7 for CO. PM 10 and PM 2.5 elemental compositions are also presented for both types of coal tested in the study.

Boiler briquette coal versus raw coal: Part I--Stack gas emissions.

PubMed

Ge, S; Bai, Z; Liu, W; Zhu, T; Wang, T; Qing, S; Zhang, J

2001-04-01

Stack gas emissions were characterized for a steam-generating boiler commonly used in China. The boiler was tested when fired with a newly formulated boiler briquette coal (BB-coal) and when fired with conventional raw coal (R-coal). The stack gas emissions were analyzed to determine emission rates and emission factors and to develop chemical source profiles. A dilution source sampling system was used to collect PM on both Teflon membrane filters and quartz fiber filters. The Teflon filters were analyzed gravimetrically for PM10 and PM2.5 mass concentrations and by X-ray fluorescence (XRF) for trace elements. The quartz fiber filters were analyzed for organic carbon (OC) and elemental carbon (EC) using a thermal/optical reflectance technique. Sulfur dioxide was measured using the standard wet chemistry method. Carbon monoxide was measured using an Orsat combustion analyzer. The emission rates of the R-coal combustion (in kg/hr), determined using the measured stack gas concentrations and the stack gas emission rates, were 0.74 for PM10, 0.38 for PM2.5, 20.7 for SO2, and 6.8 for CO, while those of the BB-coal combustion were 0.95 for PM10, 0.30 for PM2.5, 7.5 for SO2, and 5.3 for CO. The fuel-mass-based emission factors (in g/kg) of the R-coal, determined using the emission rates and the fuel burn rates, were 1.68 for PM10, 0.87 for PM2.5, 46.7 for SO2, and 15 for CO, while those of the BB-coal were 2.51 for PM10, 0.79 for PM2.5, 19.9 for SO2, and 14 for CO. The task-based emission factors (in g/ton steam generated) of the R-coal, determined using the fuel-mass-based emission factors and the coal/steam conversion factors, were 0.23 for PM10, 0.12 for PM2.5, 6.4 for SO2, and 2.0 for CO, while those of the BB-coal were 0.30 for PM10, 0.094 for PM2.5, 2.4 for SO2, and 1.7 for CO. PM10 and PM2.5 elemental compositions are also presented for both types of coal tested in the study.

Reducing mortality risk by targeting specific air pollution sources: Suva, Fiji.

PubMed

Isley, C F; Nelson, P F; Taylor, M P; Stelcer, E; Atanacio, A J; Cohen, D D; Mani, F S; Maata, M

2018-01-15

Health implications of air pollution vary dependent upon pollutant sources. This work determines the value, in terms of reduced mortality, of reducing ambient particulate matter (PM 2.5 : effective aerodynamic diameter 2.5μm or less) concentration due to different emission sources. Suva, a Pacific Island city with substantial input from combustion sources, is used as a case-study. Elemental concentration was determined, by ion beam analysis, for PM 2.5 samples from Suva, spanning one year. Sources of PM 2.5 have been quantified by positive matrix factorisation. A review of recent literature has been carried out to delineate the mortality risk associated with these sources. Risk factors have then been applied for Suva, to calculate the possible mortality reduction that may be achieved through reduction in pollutant levels. Higher risk ratios for black carbon and sulphur resulted in mortality predictions for PM 2.5 from fossil fuel combustion, road vehicle emissions and waste burning that surpass predictions for these sources based on health risk of PM 2.5 mass alone. Predicted mortality for Suva from fossil fuel smoke exceeds the national toll from road accidents in Fiji. The greatest benefit for Suva, in terms of reduced mortality, is likely to be accomplished by reducing emissions from fossil fuel combustion (diesel), vehicles and waste burning. Copyright © 2017. Published by Elsevier B.V.

Retrieval of Atmospheric Particulate Matter Using Satellite Data Over Central and Eastern China

NASA Astrophysics Data System (ADS)

Chen, G. L.; Guang, J.; Li, Y.; Che, Y. H.; Gong, S. Q.

2018-04-01

Fine particulate matter (PM2.5) is a particle cluster with diameters less than or equal to 2.5 μm. Over the past few decades, regional air pollution composed of PM2.5 has frequently occurred over Central and Eastern China. In order to estimate the concentration, distribution and other properties of PM2.5, the general retrieval models built by establishing the relationship between aerosol optical depth (AOD) and PM2.5 has been widely used in many studies, including experimental models via statistics analysis and physical models with certain physical mechanism. The statistical experimental models can't be extended to other areas or historical period due to its dependence on the ground-based observations and necessary auxiliary data, which limits its further application. In this paper, a physically based model is applied to estimate the concentration of PM2.5 over Central and Eastern China from 2007 to 2016. The ground-based PM2.5 measurements were used to be as reference data to validate our retrieval results. Then annual variation and distribution of PM2.5 concentration in the Central and Eastern China was analysed. Results shows that the annual average PM2.5 show a trend of gradually increasing and then decreasing during 2007-2016, with the highest value in 2011.

Evaluating effectiveness and cost-effectiveness of a group psychological intervention using cognitive behavioural strategies for women with common mental disorders in conflict-affected rural Pakistan: study protocol for a randomised controlled trial.

PubMed

Chiumento, Anna; Hamdani, Syed Usman; Khan, Muhammad Naseem; Dawson, Katie; Bryant, Richard A; Sijbrandij, Marit; Nazir, Huma; Akhtar, Parveen; Masood, Aqsa; Wang, Duolao; van Ommeren, Mark; Rahman, Atif

2017-04-26

The impact of humanitarian disasters upon mental health is well recognised. The evidence for psychological interventions for mental health is mounting, but few interventions have been rigorously tested in humanitarian settings. To be sustainable in humanitarian settings interventions need to be short, simple, deliverable by nonspecialists under supervision, and adopt a transdiagnostic approach where an array of mental health outcomes are addressed simultaneously. These elements have been incorporated into the newly developed WHO Problem Management Plus (PM+) Group intervention. The aim of this trial is to evaluate the locally adapted PM+ Group intervention for women in Swat, Pakistan. This PM+ Group trial is a two-arm, single-blind, cluster randomised controlled trial conducted in a community-based setting with women in rural Pakistan. PM+ is delivered in partnership with the Lady Health Worker (LHW) Programme which provides community-based health care to women in Pakistan. Thirty-four LHW clusters will be randomised in a 1:1 allocation ratio using a permuted-block randomisation method. Participants screened and found to meet the inclusion criteria will be allocated to either the PM+ intervention group (n = 306), or the control arm (n = 306). The manualised PM+ intervention involves five sessions, each lasting 3 h, and introduces four strategies applied by participants to problems that they are facing. It is delivered by local female facilitators with a minimum of 16 years of education who are provided with targeted training and supervision. The primary outcome is individual psychological distress, measured by levels of anxiety and depression on the Hospital Anxiety and Depression Scale at 20 weeks after baseline. Secondary outcomes include major depression, post-traumatic stress disorder, levels of social support, levels of functioning, and economic effectiveness. Intervention acceptability will be explored through an embedded qualitative study. The PM+ Group trial will provide important evidence on the effectiveness of an empirically supported psychological treatment delivered by nonspecialists in a humanitarian setting. If proven effective, the qualitative component will inform strategies for PM+ Group scale-up in health systems in other humanitarian settings. Australian New Zealand Clinical Trials Registry, identifier: ACTRN12616000037404. Registered on 19 January 2016; WHO Protocol ID RPC705, v.4, 2 November 2015.

The classification of PM10 concentrations in Johor Based on Seasonal Monsoons

NASA Astrophysics Data System (ADS)

Hamid, Hazrul Abdul; Hanafi Rahmat, Muhamad; Aisyah Sapani, Siti

2018-04-01

Air is the most important living resource in life. Contaminated air could adversely affect human health and the environment, especially during the monsoon season. Contamination occurs as a result of human action and haze. There are several pollutants present in the air where one of them is PM10. Secondary data was obtained from the Department of Environment from 2010 until 2014 and was analyzed using the hourly average of PM10 concentrations. This paper examined the relation between PM10 concentrations and the monsoon seasons (Northeast Monsoon and Southwest Monsoon) in Larkin and Pasir Gudang. It was expected that the concentration of PM10 would be higher during the Southwest Monsoon as it is a dry season. The data revealed that the highest PM10 concentrations were recorded between 2010 to 2014 during this particular monsoon season. The characteristics of PM10 concentration were compared using descriptive statistics based on the monsoon seasons and classified using the hierarchical cluster analysis (Ward Methods). The annual average of PM10 concentration during the Southwest Monsoon had exceeded the standard set by the Malaysia Ambient Air Quality Guidelines (50 μg/m3) while the PM10 concentration during the Northeast Monsoon was below the acceptable level for both stations. The dendrogram displayed showed two clusters for each monsoon season for both stations excepted for the PM10 concentration during the Northeast Monsoon in Larkin which was classified into three clusters due to the haze in 2010. Overall, the concentration of PM10 in 2013 was higher based on the clustering shown for every monsoon season at both stations according to the characteristics in the descriptive statistics.

77 FR 1894 - Approval and Promulgation of Implementation Plans; Georgia; Rome; Fine Particulate Matter 2002...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-12

... ENVIRONMENTAL PROTECTION AGENCY 40 CFR Part 52 [EPA-R04-OAR-2011-0849-201153(b); FRL-9617-3] Approval and Promulgation of Implementation Plans; Georgia; Rome; Fine Particulate Matter 2002 Emissions... approve the fine particulate matter (PM 2.5 ) 2002 base year emissions inventory portion of the State...

A New Polar Magnetic Index of Geomagnetic Activity and its Application to Monitoring Ionospheric Parameters

NASA Technical Reports Server (NTRS)

Lyatsky, Wladislaw; Khazanov, George V.

2008-01-01

For improving the reliability of Space Weather prediction, we developed a new, Polar Magnetic (PM) index of geomagnetic activity, which shows high correlation with both upstream solar wind data and related events in the magnetosphere and ionosphere. Similarly to the existing polar cap PC index, the new, PM index was computed from data from two near-pole geomagnetic observatories; however, the method for computing the PM index is different. The high correlation of the PM index with both solar wind data and events in Geospace environment makes possible to improve significantly forecasting geomagnetic disturbances and such important parameters as the cross-polar-cap voltage and global Joule heating in high latitude ionosphere, which play an important role in the development of geomagnetic, ionospheric and thermospheric disturbances. We tested the PM index for 10-year period (1995-2004). The correlation between PM index and upstream solar wind data for these years is very high (the average correlation coefficient R approximately equal to 0.86). The PM index also shows the high correlation with the cross-polar-cap voltage and hemispheric Joule heating (the correlation coefficient between the actual and predicted values of these parameters is approximately 0.9), which results in significant increasing the prediction reliability of these parameters. Using the PM index of geomagnetic activity provides a significant increase in the forecasting reliability of geomagnetic disturbances and related events in Geospace environment. The PM index may be also used as an important input parameter in modeling ionospheric, magnetospheric, and thermospheric processes.

PM2.5 aerosols collected in the Antarctic Peninsula with a solar powered sampler during austral summer periods

NASA Astrophysics Data System (ADS)

Préndez, M.; Wachter, J.; Vega, C.; Flocchini, R. G.; Wakayabashi, P.; Morales, J. R.

Collection of PM2.5 particles was carried out in Antarctica in the summer periods of years 2006 and 2007 using solar panels to operate the sampling unit. The unit was installed 2.5 km from the B. O'Higgins Chilean base to avoid possible air contamination from oil or gas burning electric power stations. The aerosols were analyzed by XRF identifying twenty elements between Na and Sr. Results showed the presence of elements of typical Earth crust and seawater origins. In addition, considerable amounts of non-sea sulfur together with traces of Pb and Se from probable long distant anthropogenic activities were observed.

Satellite-based Estimates of Ambient Air Pollution and Global Variations in Childhood Asthma Prevalence

NASA Technical Reports Server (NTRS)

Anderson, H. Ross; Butland, Barbara K.; Donkelaar, Aaron Matthew Van; Brauer, Michael; Strachan, David P.; Clayton, Tadd; van Dingenen, Rita; Amann, Marcus; Brunekreef, Bert; Cohen, Aaron;

Satellite-based Estimates of Ambient Air Pollution and Global Variations in Childhood Asthma Prevalence

PubMed Central

Butland, Barbara K.; van Donkelaar, Aaron; Brauer, Michael; Strachan, David P.; Clayton, Tadd; van Dingenen, Rita; Amann, Marcus; Brunekreef, Bert; Cohen, Aaron; Dentener, Frank; Lai, Christopher; Lamsal, Lok N.; Martin, Randall V.; One, ISAAC Phase

2012-01-01

Background: The effect of ambient air pollution on global variations and trends in asthma prevalence is unclear. Objectives: Our goal was to investigate community-level associations between asthma prevalence data from the International Study of Asthma and Allergies in Childhood (ISAAC) and satellite-based estimates of particulate matter with aerodynamic diameter < 2.5 µm (PM2.5) and nitrogen dioxide (NO2), and modelled estimates of ozone. Methods: We assigned satellite-based estimates of PM2.5 and NO2 at a spatial resolution of 0.1° × 0.1° and modeled estimates of ozone at a resolution of 1° × 1° to 183 ISAAC centers. We used center-level prevalence of severe asthma as the outcome and multilevel models to adjust for gross national income (GNI) and center- and country-level sex, climate, and population density. We examined associations (adjusting for GNI) between air pollution and asthma prevalence over time in centers with data from ISAAC Phase One (mid-1900s) and Phase Three (2001–2003). Results: For the 13- to 14-year age group (128 centers in 28 countries), the estimated average within-country change in center-level asthma prevalence per 100 children per 10% increase in center-level PM2.5 and NO2 was –0.043 [95% confidence interval (CI): –0.139, 0.053] and 0.017 (95% CI: –0.030, 0.064) respectively. For ozone the estimated change in prevalence per parts per billion by volume was –0.116 (95% CI: –0.234, 0.001). Equivalent results for the 6- to 7-year age group (83 centers in 20 countries), though slightly different, were not significantly positive. For the 13- to 14-year age group, change in center-level asthma prevalence over time per 100 children per 10% increase in PM2.5 from Phase One to Phase Three was –0.139 (95% CI: –0.347, 0.068). The corresponding association with ozone (per ppbV) was –0.171 (95% CI: –0.275, –0.067). Conclusion: In contrast to reports from within-community studies of individuals exposed to traffic pollution, we did not find evidence of a positive association between ambient air pollution and asthma prevalence as measured at the community level. PMID:22548921

Public health benefits of reducing air pollution in Shanghai: a proof-of-concept methodology with application to BenMAP.

PubMed

Voorhees, A Scott; Wang, Jiandong; Wang, Cuicui; Zhao, Bin; Wang, Shuxiao; Kan, Haidong

2014-07-01

In recent years, levels of particulate matter (PM) air pollution in China have been relatively high, exceeding China's Class II standards in many cities and impacting public health. This analysis takes Chinese health impact functions and underlying health incidence, applies 2010-2012 modeled and monitored PM air quality data, and estimates avoided cases of mortality and morbidity in Shanghai, assuming achievement of China's Class II air quality standards. In Shanghai, the estimated avoided all cause mortality due to PM10 ranged from 13 to 55 cases per day and from 300 to 800 cases per year. The estimated avoided impact on hospital admissions due to PM10 ranged from 230 cases to 580 cases per day and from 5400 to 7900 per year. The estimated avoided impact on all cause mortality due to PM2.5 ranged from 6 to 26 cases per day and from 39 to 1400 per year. The estimated impact on all cause mortality of a year exposure to an annual or monthly mean PM2.5 concentration ranged from 180 to 3500 per year. In Shanghai, the avoided cases of all cause mortality had an estimated monetary value ranging from 170 million yuan (1 US dollar=4.2 yuan Purchasing Power Parity) to 1200 million yuan. Avoided hospital admissions had an estimated value from 20 to 43 million yuan. Avoided emergency department visits had an estimated value from 5.6 million to 15 million yuan. Avoided outpatient visits had an estimated value from 21 million to 31 million yuan. In this analysis, available data were adequate to estimate avoided health impacts and assign monetary value. Sufficient supporting documentation was available to construct and format data sets for use in the United States Environmental Protection Agency's health and environmental assessment model, known as the Environmental Benefits Mapping and Analysis Program - Community Edition ("BenMAP-CE"). Published by Elsevier B.V.

Monitoring of airborne particulate matter at mountainous urban sites.

PubMed

Dai, Jun; Kim, Ki-Hyun; Dutta, Tanushree; Park, Wha Me; Hong, Jong-Ki; Jung, Kweon; Brown, Richard J C

2016-08-01

Concentrations of various size fractions (TSP, PM10, PM2.5, and PM1.0) of particulate matter (PM) were measured at two mountainous sites, Buk Han (BH) and Gwan AK (GA), along with one ground reference site at Gwang Jin (GJ), located in Seoul, South Korea for the 4 years from 2010 to 2013. The daily average concentrations of TSP, PM10, PM2.5, and PM1.0 at BH were 47.9 ± 32.5, 37.0 ± 24.6, 20.6 ± 12.9, and 15.3 ± 9.53 μg m(-3), respectively. These values were slightly larger than those measured at GA while much lower than those measured at the reference site (GJ). Seasonal variations in PM concentrations were consistent across all locations with a relative increase in concentrations observed in spring and winter. Correlation analysis showed clear differences in PM concentrations between the mountainous sites and the reference site. Analysis of these PM concentrations indicated that the distribution of PM in the mountainous locations was affected by a number of manmade sources from nearby locations, including both traffic and industrial emissions.

PM levels in the Basque Country (Northern Spain): analysis of a 5-year data record and interpretation of seasonal variations

NASA Astrophysics Data System (ADS)

Viana, M.; Querol, X.; Alastuey, A.; Gangoiti, G.; Menéndez, M.

Levels of PM observed at the air quality network from the Basque Country in 1996-2000 ranged from 16 μg PM 10/m 3 at regional background sites, to 35-40 μg TSP/m 3 (equivalent to 25-30 μg PM 10/m 3) at urban background sites, to 40-48 μg TSP/m 3 (30-40 μg PM 10/m 3) at roadside sites; to 50-64 μg TSP/m 3 (35-50 μg PM 10/m 3) at industrial and heavy traffic sites. The EU daily and annual PM 10 limit values for 2005 are not equivalent for the Basque Country, and consequently only the mean 1996-2000 PM levels from one station would exceed the 2005 annual limit value but most of them surpass n=35 exceedances of the daily limit value. The equivalent n to the 2005 annual limit value is around 80. Four major processes exert an influence on PM levels throughout the Basque territory: local and regional anthropogenic contributions, precipitation, African dust and European transport. PM at Llodio (an urban background site under industrial influence and mean PM 10, PM 2.5 and PM 1 levels for 2001 of 34, 25 and 21 μg/m 3) is mainly distributed in the fine mode: 74% of PM 10 is constituted by PM 2.5, and 64% of PM 2.5 presents a diameter <1 μm. The particle size distribution of PM varies seasonally with the fine fractions prevailing in summer (PM 2.5/PM 10=80-90%) and the coarser increasing in winter (PM 2.5/PM 10=60-70%). Meso- and synoptic scale processes affecting global PM levels in the Basque Country have been identified (mainly pollution episodes, African, Atlantic and EU transport). The results obtained allowed us to evaluate the impact of the different types of PM episodes on ambient PM levels and particle size fractions.

Socioeconomic and urban-rural differentials in exposure to air pollution and mortality burden in England.

PubMed

Milojevic, Ai; Niedzwiedz, Claire L; Pearce, Jamie; Milner, James; MacKenzie, Ian A; Doherty, Ruth M; Wilkinson, Paul

2017-10-06

Socioeconomically disadvantaged populations often have higher exposures to particulate air pollution, which can be expected to contribute to differentials in life expectancy. We examined socioeconomic differentials in exposure and air pollution-related mortality relating to larger scale (5 km resolution) variations in background concentrations of selected pollutants across England. Ozone and particulate matter (sub-divided into PM 10 , PM 2.5 , PM 2.5-10 , primary, nitrate and sulphate PM 2.5 ) were simulated at 5 km horizontal resolution using an atmospheric chemistry transport model (EMEP4UK). Annual mean concentrations of these pollutants were assigned to all 1,202,578 residential postcodes in England, which were classified by urban-rural status and socioeconomic deprivation based on the income and employment domains of the 2010 English Index of Multiple Deprivation for the Lower-level Super Output Area of residence. We used life table methods to estimate PM 2.5 -attributable life years (LYs) lost in both relative and absolute terms. Concentrations of the most particulate fractions, but not of nitrate PM 2.5 or ozone, were modestly higher in areas of greater socioeconomic deprivation. Relationships between pollution level and socioeconomic deprivation were non-linear and varied by urban-rural status. The pattern of PM 2.5 concentrations made only a small contribution to the steep socioeconomic gradient in LYs lost due to PM 2.5 per 10 3 population, which primarily was driven by the steep socioeconomic gradient in underlying mortality rates. In rural areas, the absolute burden of air pollution-related LYs lost was lowest in the most deprived deciles. Air pollution shows modest socioeconomic patterning at 5 km resolution in England, but absolute attributable mortality burdens are strongly related to area-level deprivation because of underlying mortality rates. Measures that cause a general reduction in background concentrations of air pollution may modestly help narrow socioeconomic differences in health.

A Study of Particulate Matter (PM2.5) Concentration Variance by Distance from Train Platform at a Major Bay Area Rapid Transit (BART) Railway Station

NASA Astrophysics Data System (ADS)

Solis, M.; Nguyen, H.; Adeyan, A.; Adeyan, E.; Taylor, S.; Hardaway, K.; Peterson, E.; Ortega, J.; Marshall, R.

2017-12-01

Over the past five years, the East Bay Academy for Young Scientists (EBAYS) has been investigating air quality at Bay Area Rapid Transit (BART) train stations. In particular, prior EBAYS research has revealed extremely high levels of particulate matter (PM 2.5) at the multi-leveled Embarcadero Station, which is underground and is one of the most frequently visited stations in the entire BART system. During the summer of 2017 data was collected to determine whether or not air quality differed on the three levels of this station. In conducting this study the research team was separated into pairs, each pair in possession of a Dustrak II or AirBeam PM analyzer and each pair assigned to a particular level. Within each measurement trial data was collected for 15 minutes. Measurements were also made on the eastern and western ends of the platforms to detect possible variations in PM concentration. Preliminary results obtained thus far indicate that dangerously high levels of PM 2.5 concentration occur on all three levels of the station. This is especially problematic because it suggests that individuals who spend extensive amounts of time at this station (e.g., station agents and other workers) are exposed to extremely high PM 2.5 concentration levels and as a result are working under conditions that are quite hazardous to their health. Based on observations made during testing, increased levels of PM 2.5 tend to correlate with the departure or arrival of BART trains that results in particulate matter being scattered about the train platform and other levels. Further studies should be conducted to verify this observation and to contribute to better understanding the sources and behavior of PM 2.5 at each level of the station.

High Contributions of Secondary Inorganic Aerosols to PM2.5 under Polluted Levels at a Regional Station in Northern China

PubMed Central

Li, Yang; Tao, Jun; Zhang, Leiming; Jia, Xiaofang; Wu, Yunfei

2016-01-01

Daily PM2.5 samples were collected at Shangdianzi (SDZ) regional site in Beijing–Tianjin–Hebei (BTH) region in 2015. Samples were subject to chemical analysis for organic carbon (OC), elemental carbon (EC), and major water-soluble inorganic ions. The annual average PM2.5 mass concentration was 53 ± 36 μg·m−3 with the highest seasonal average concentration in spring and the lowest in summer. Water-soluble inorganic ions and carbonaceous aerosols accounted for 34% ± 15% and 33% ± 9%, respectively, of PM2.5 mass on annual average. The excellent, good, lightly polluted, moderately polluted, and heavily polluted days based on the Air Quality Index (AQI) of PM2.5 accounted for 40%, 42%, 11%, 4%, and 3%, respectively, of the year. The sum of the average concentration of sulfate, nitrate, and ammonium (SNA) increased from 4.2 ± 2.9 μg·m−3 during excellent days to 85.9 ± 22.4 μg·m−3 during heavily polluted days, and their contributions to PM2.5 increased from 15% ± 8% to 49% ± 10% accordingly. In contrast, the average concentration of carbonaceous aerosols increased from 9.2 ± 2.8 μg·m−3 to 51.2 ± 14.1 μg·m−3, and their contributions to PM2.5 decreased from 34% ± 6% to 29% ± 7%. Potential source contribution function (PSCF) analysis revealed that the major sources for high PM2.5 and its dominant chemical components were within the area mainly covering Shandong, Henan, and Hebei provinces. Regional pollutant transport from Shanxi province and Inner Mongolia autonomous region located in the west direction of SDZ was also important during the heating season. PMID:27983711

Simulations of Sulfate-Nitrate-Ammonium (SNA) aerosols during the extreme haze events over Northern China in 2014

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Dan; Liu, Zhiquan; Fast, Jerome D.

Extreme haze events have occurred frequently over China in recent years. Although many studies have investigated the formation mechanisms associated with PM2.5 for heavily polluted regions in China based on observational data, adequately predicting peak PM2.5 concentrations is still challenging for regional air quality models. In this study, we evaluate the performance of one configuration of the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) and use the model to investigate the sensitivity of heterogeneous reactions on simulated peak sulfate, nitrate, and ammonium concentrations in the vicinity of Beijing during four extreme haze episodes in October 2014 over themore » North China Plain. The highest observed PM2.5 concentration of 469 μg m-3 occurred in Beijing. Comparisons with observations show that the model reproduced the temporal variability in PM2.5 with the highest PM2.5 values on polluted days (defined as days in which observed PM2.5 is greater than 75 μg m-3), but predictions of sulfate, nitrate, and ammonium were too low on days with the highest observed concentrations. Observational data indicate that the sulfur/nitric oxidation rates are strongly correlated with relative humidity during periods of peak PM2.5; however, the model failed to reproduce the highest PM2.5 concentrations due to missing heterogeneous reactions. As the parameterizations of those reactions is not well established yet, estimates of SO2-to-H2SO4 and NO2/NO3-to-HNO3 reaction rates that depend on relative humidity were applied which improved the simulation of sulfate, nitrate, and ammonium enhancement on polluted days in terms of both concentrations and partitioning among those species. Sensitivity simulations showed that the extremely high heterogeneous reaction rates and also higher emission rates than those reported in the emission inventory« less

40 CFR 93.123 - Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis).

Code of Federal Regulations, 2014 CFR

2014-07-01

... PM2.5 violations”) must be based on quantitative analysis using the applicable air quality models... either: (i) Quantitative methods that represent reasonable and common professional practice; or (ii) A...) The hot-spot demonstration required by § 93.116 must be based on quantitative analysis methods for the...

Using operational active remote sensing devices to detect Saharan dust advections and evaluate their contribution to the PM10 levels: The EU LIFE+ "DIAPASON" project

NASA Astrophysics Data System (ADS)

Gobbi, Gian Paolo; Wille, Holger; Sozzi, Roberto; Barnaba, Francesca; Costabile, Francesca; Angelini, Federico; Frey, Steffen; Bolignano, Andrea; Morelli, Matteo

2013-04-01

The contribution of Saharan-dust advections to both daily and annual PM average mass concentrations can be significant all over Southern Europe. The Directive 2008/50/EC allows subtraction of PM10 exceedances caused by natural contributions from the statistic used to determine air-quality levels in Europe. To this purpose, the Commission Staff Working Paper 6771/11 (EC, 2011) provides specific Guidelines on methods to quantify and subtract the contribution of these sources in the framework of the Air Quality Directive. For Saharan dust, the EC methodology is largely based on a thorough analysis performed over the Iberian Peninsula (Escudero et al, 2007), although revision of the current methodology is in progress. In line with the EC Guidelines, the DIAPASON project ("Desert-dust Impact on Air quality through model-Predictions and Advanced Sensors ObservatioNs"), funded under the EC LIFE+ program, has been formulated to provide a robust, user-oriented, and demonstrated method to assess the presence of desert dust and evaluate its contribution to PM10 levels at the monitoring sites. To this end, in addition to satellite-based data and model forecasts already included in the EC Guidelines, DIAPASON will take advantage, in both the Project implementation and demonstration phase, of innovative and affordable technologies (partly prototyped within the project itself), namely operational Polarization Lidar-Ceilometers (PLC) capable of detecting and profiling dust clouds from the ground up to 10 km altitude. The PLC prototypes have been already finalized during the initial phase of the Project. Three of them will be networked in relevant air quality monitoring stations located in the Rome metropolitan area (Italy) during the DIAPASON observational phase (one-year long field campaign) starting in March 2013. The Rome region was chosen as the DIAPASON pilot scale area since highly impacted by urban pollution and frequently affected by Saharan dust transport events. In fact, a preliminary assessment of the role of Saharan dust in this area, based on a four-year dataset (2001-2004) has shown average increases of PM10 levels of the order of 11.9 µg/m3 when Saharan dust presence is either predicted by models or observed by a depolarization lidar. Conversely, PM10 increases computed relying only on the Lidar detections (i.e., presence of dust layers actually observed) were of the order of 15.6 µg/m3. Both analyses indicate the annual average contribution of dust advections to the city PM10 mass concentrations to be of the order of 2.3 µg/m3 (Gobbi et al., 2013). These results confirm Saharan advections in the central Mediterranean as important modulators of PM10 loads and exceedances. After the demonstrative pilot scale study, the DIAPASON results will be spatially generalised to a wider area. The final DIAPASON methodology to detect/quantify the Saharan dust contribution to PM10 will be tailored for a national scale application, and easily transferable to other air-quality and meteorological agencies in Europe. In this work, preliminary results from the combined analysis of Saharan dust model predictions, PM10 data and lidar records performed within DIAPASON will be shown, with particular focus on the added-value provided by continuous polarization lidar data in integrating the present EC Methodology. - EC, Commission Staff Working Paper 6771/11 establishing guidelines for demonstration and subtraction of exceedances attributable to natural sources under the Directive 2008/50/EC on ambient air quality and cleaner air for Europe, European Commission, 2011. - Escudero, M., Querol, X., Pey, J., Alastuey, A., Pérez, N., Ferreira, F., Alonso, S., Rodríguez, S. and Cuevas, E., A methodology for the quantification of the net African dust load in air quality monitoring networks, Atmos. Envir., 41, 5516-5524, 2007. - Gobbi,G. P., F. Angelini, F. Barnaba, F. Costabile, J. M. Baldasano, S. Basart, R. Sozzi and A. Bolignano, Changes in Particulate Matter Physical Properties During Saharan Advections over Rome (Italy): A Four-Year Study, 2001-2004, Atmos. Chem. Phys., Discus., 2013.

[Parameters modification and evaluation of two evapotranspiration models based on Penman-Monteith model for summer maize].

PubMed

Wang, Juan; Wang, Jian Lin; Liu, Jia Bin; Jiang, Wen; Zhao, Chang Xing

2017-06-18

The dynamic variations of evapotranspiration (ET) and weather data during summer maize growing season in 2013-2015 were monitored with eddy covariance system, and the applicability of two operational models (FAO-PM model and KP-PM model) based on the Penman-Monteith model were analyzed. Firstly, the key parameters in the two models were calibrated with the measured data in 2013 and 2014; secondly, the daily ET in 2015 calculated by the FAO-PM model and KP-PM model was compared to the observed ET, respectively. Finally, the coefficients in the KP-PM model were further revised with the coefficients calculated according to the different growth stages, and the performance of the revised KP-PM model was also evaluated. These statistical parameters indicated that the calculated daily ET for 2015 by the FAO-PM model was closer to the observed ET than that by the KP-PM model. The daily ET calculated from the revised KP-PM model for daily ET was more accurate than that from the FAO-PM model. It was also found that the key parameters in the two models were correlated with weather conditions, so the calibration was necessary before using the models to predict the ET. The above results could provide some guidelines on predicting ET with the two models.

Improvement of PM concentration predictability using WRF-CMAQ-DLM coupled system and its applications

NASA Astrophysics Data System (ADS)

Lee, Soon Hwan; Kim, Ji Sun; Lee, Kang Yeol; Shon, Keon Tae

2017-04-01

Air quality due to increasing Particulate Matter(PM) in Korea in Asia is getting worse. At present, the PM forecast is announced based on the PM concentration predicted from the air quality prediction numerical model. However, forecast accuracy is not as high as expected due to various uncertainties for PM physical and chemical characteristics. The purpose of this study was to develop a numerical-statistically ensemble models to improve the accuracy of prediction of PM10 concentration. Numerical models used in this study are the three dimensional atmospheric model Weather Research and Forecasting(WRF) and the community multiscale air quality model (CMAQ). The target areas for the PM forecast are Seoul, Busan, Daegu, and Daejeon metropolitan areas in Korea. The data used in the model development are PM concentration and CMAQ predictions and the data period is 3 months (March 1 - May 31, 2014). The dynamic-statistical technics for reducing the systematic error of the CMAQ predictions was applied to the dynamic linear model(DLM) based on the Baysian Kalman filter technic. As a result of applying the metrics generated from the dynamic linear model to the forecasting of PM concentrations accuracy was improved. Especially, at the high PM concentration where the damage is relatively large, excellent improvement results are shown.

77 FR 76415 - Approval and Promulgation of Air Quality Implementation Plans; West Virginia; Redesignation of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-28

...EPA is approving a redesignation request and State Implementation Plan (SIP) revision submitted by the State of West Virginia. The West Virginia Department of Environmental Protection (WVDEP) requested that the West Virginia portion of the Huntington- Ashland, WV-KY-OH fine particulate matter (PM2.5) nonattainment area (``Huntington-Ashland Area'' or ``Area'') be redesignated as attainment for the 1997 annual PM2.5 national ambient air quality standard (NAAQS). In this rulemaking action, EPA is approving the 1997 annual PM2.5 redesignation request for the West Virginia portion of the Area. EPA is also approving the maintenance plan SIP revision that the State submitted in conjunction with its redesignation request. The maintenance plan provides for continued attainment of the 1997 annual PM2.5 NAAQS for 10 years after redesignation of the West Virginia portion of the Area. The maintenance plan includes an insignificance determination for the onroad motor vehicle contribution of PM2.5, nitrogen oxides (NOX), and sulfur dioxide (SO2) for the West Virginia portion of the Area for purposes of transportation conformity. EPA is approving West Virginia's insignificance determination for transportation conformity. EPA is also finding that the Area continues to attain the standard. This rulemaking action approving the 1997 annual PM2.5 NAAQS redesignation request, maintenance plan, and insignificance determination for transportation conformity for the West Virginia portion of the Area is based on EPA's determination that the Area has met the criteria for redesignation to attainment specified in the Clean Air Act (CAA).

Subjective memory complaints, depressive symptoms and instrumental activities of daily living in mild cognitive impairment.

PubMed

Ryu, Seon Young; Lee, Sang Bong; Kim, Tae Woo; Lee, Taek Jun

2016-03-01

The diagnostic relevance of subjective memory complaints (SMCs) in mild cognitive impairment (MCI) remains to be unresolved. The aim of this study is to determine clinical correlates of SMCs in MCI. Furthermore, we examined whether there are the differences due to different aspects of complaints (i.e. prospective memory (PM) versus retrospective memory (RM) complaints). We examined the cross-sectional associations between SMCs and depressive symptoms, instrumental activities of daily living (IADL), and cognitive measures in sixty-six individuals with MCI (mean age: 65.7 ± 8.01 years). The criteria for MCI included SMCs, objective cognitive impairment, normal general cognitive function, largely intact functional activities, and absence of dementia. SMCs were assessed using the Prospective and Retrospective Memory Questionnaire (PRMQ), which contains 16 items describing everyday memory failure of both PM and RM. SMC severity (i.e. PRMQ total score) was associated with stronger depressive symptoms and worse IADL performance. SMCs were not related to cognitive measures. For PM and RM subscores, both depressive symptoms and IADL were related to the PRMQ-PM and -RM scores. The main contributors to these PM and RM scores were depressive symptoms and IADL impairment, respectively. This study suggests that SMCs are more associated with depressive symptoms and IADL problems than with cognitive performance in individuals with MCI. Furthermore, while PM and RM complaints are related to both depressive symptoms and IADL, the differences between these main contributors suggest that RM complaints based on IADL could be more associated with the organically driven pathological features of MCI.

Real-Time and Seamless Monitoring of Ground-Level PM2.5 Using Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Li, Tongwen; Zhang, Chengyue; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Liangpei

2018-04-01

Satellite remote sensing has been reported to be a promising approach for the monitoring of atmospheric PM2.5. However, the satellite-based monitoring of ground-level PM2.5 is still challenging. First, the previously used polar-orbiting satellite observations, which can be usually acquired only once per day, are hard to monitor PM2.5 in real time. Second, many data gaps exist in satellitederived PM2.5 due to the cloud contamination. In this paper, the hourly geostationary satellite (i.e., Harawari-8) observations were adopted for the real-time monitoring of PM2.5 in a deep learning architecture. On this basis, the satellite-derived PM2.5 in conjunction with ground PM2.5 measurements are incorporated into a spatio-temporal fusion model to fill the data gaps. Using Wuhan Urban Agglomeration as an example, we have successfully derived the real-time and seamless PM2.5 distributions. The results demonstrate that Harawari-8 satellite-based deep learning model achieves a satisfactory performance (out-of-sample cross-validation R2 = 0.80, RMSE = 17.49 μg/m3) for the estimation of PM2.5. The missing data in satellite-derive PM2.5 are accurately recovered, with R2 between recoveries and ground measurements of 0.75. Overall, this study has inherently provided an effective strategy for the realtime and seamless monitoring of ground-level PM2.5.

Progress in oral personalized medicine: contribution of ‘omics’

PubMed Central

Glurich, Ingrid; Acharya, Amit; Brilliant, Murray H.; Shukla, Sanjay K.

2015-01-01

Background Precision medicine (PM), representing clinically applicable personalized medicine, proactively integrates and interprets multidimensional personal health data, including clinical, ‘omics’, and environmental profiles, into clinical practice. Realization of PM remains in progress. Objective The focus of this review is to provide a descriptive narrative overview of: 1) the current status of oral personalized medicine; and 2) recent advances in genomics and related ‘omic’ and emerging research domains contributing to advancing oral-systemic PM, with special emphasis on current understanding of oral microbiomes. Design A scan of peer-reviewed literature describing oral PM or ‘omic’-based research conducted on humans/data published in English within the last 5 years in journals indexed in the PubMed database was conducted using mesh search terms. An evidence-based approach was used to report on recent advances with potential to advance PM in the context of historical critical and systematic reviews to delineate current state-of-the-art technologies. Special focus was placed on oral microbiome research associated with health and disease states, emerging research domains, and technological advances, which are positioning realization of PM. Results This review summarizes: 1) evolving conceptualization of personalized medicine; 2) emerging insight into roles of oral infectious and inflammatory processes as contributors to both oral and systemic diseases; 3) community shifts in microbiota that may contribute to disease; 4) evidence pointing to new uncharacterized potential oral pathogens; 5) advances in technological approaches to ‘omics’ research that will accelerate PM; 6) emerging research domains that expand insights into host–microbe interaction including inter-kingdom communication, systems and network analysis, and salivaomics; and 7) advances in informatics and big data analysis capabilities to facilitate interpretation of host and microbiome-associated datasets. Furthermore, progress in clinically applicable screening assays and biomarker definition to inform clinical care are briefly explored. Conclusion Advancement of oral PM currently remains in research and discovery phases. Although substantive progress has been made in advancing the understanding of the role of microbiome dynamics in health and disease and is being leveraged to advance early efforts at clinical translation, further research is required to discern interpretable constituency patterns in the complex interactions of these microbial communities in health and disease. Advances in biotechnology and bioinformatics facilitating novel approaches to rapid analysis and interpretation of large datasets are providing new insights into oral health and disease, potentiating clinical application and advancing realization of PM within the next decade. PMID:26344171

Meta-analysis of the effect of pregrazing pasture mass on pasture intake, milk production, and grazing behavior of dairy cows strip-grazing temperate grasslands.

PubMed

Pérez-Prieto, L A; Delagarde, R

2012-09-01

Grazing management is a key factor in pasture-based dairy systems, which can be improved given advanced knowledge of the effects of pregrazing pasture mass (PM) on the performance of dairy cows. The aim of this study was to quantify the effects of PM on the pasture intake, milk production, milk composition, and grazing behavior of strip- or rotational-grazing dairy cows, based on a meta-analysis of published research papers. A database was created that included experiments in which the effects of PM on pasture intake and milk production of dairy cows were studied. Papers were selected only if at least 2 PM were compared under similar experimental conditions, particularly the same pasture allowance (SPA). The final database included 15 papers with 27 PM comparisons. For analytical purposes, the database was subdivided into 3 subsets that varied according to the estimation height at which pasture allowance was determined; that is, where PM were compared at the SPA above ground level (SPA(0) subset), above 2 to 3 cm (SPA(3) subset), and above 4 to 5 cm (SPA(5) subset). Statistical analyses were conducted on the entire database (global analysis) and within each subset using linear model procedures. An interaction between PM and estimation height was found for pasture intake and milk production in the global analysis. On the basis of the predictive equations, pasture intake increased by 1.58 kg of dry matter/d per tonne increase in PM when PM were compared at SPA(0), was not affected by PM when PM were compared at SPA(3), and decreased by 0.65 kg of dry matter/d per tonne increase in PM when PM were compared at SPA(5). This is consistent with the effect of PM on milk production, which was positive and negative (1.04 and -0.79 kg/t of PM, respectively) when PM were compared at SPA(0) and SPA(5), respectively. Grazing time was only slightly affected by PM, irrespective of estimation height, because the effect of PM on pasture intake was mainly dependent on the variation in pasture intake rate. Pasture intake rate increased with increasing PM at SPA(0) but decreased with increasing PM at SPA(5). This meta-analysis clearly demonstrates that the effects of PM on pasture intake, milk production, and behavior of strip-grazing dairy cows depend largely on the height at which the PM and pasture allowance are measured. These results have methodological implications for future grazing research because it can be recommended that PM be compared at similar levels of pasture availability (i.e., at the same pasture allowance above 2 to 3 cm) to avoid possible misinterpretations of results. They also reveal the benefits of improving grazing management and intake prediction through modeling in pasture-based dairy systems. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Aerosols in the CALIOPE air quality modelling system: evaluation and analysis of PM levels, optical depths and chemical composition over Europe

NASA Astrophysics Data System (ADS)

Basart, S.; Pay, M. T.; Jorba, O.; Pérez, C.; Jiménez-Guerrero, P.; Schulz, M.; Baldasano, J. M.

2012-04-01

The CALIOPE air quality modelling system is developed and applied to Europe with high spatial resolution (12 km × 12 km). The modelled daily-to-seasonal aerosol variability over Europe in 2004 is evaluated and analysed. Aerosols are estimated from two models, CMAQv4.5 (AERO4) and BSC-DREAM8b. CMAQv4.5 calculates biogenic, anthropogenic and sea salt aerosol and BSC-DREAM8b provides the natural mineral dust contribution from North African deserts. For the evaluation, we use daily PM10, PM2.5 and aerosol components data from 55 stations of the EMEP/CREATE network and total, coarse and fine aerosol optical depth (AOD) data from 35 stations of the AERONET sun photometer network. Annual correlations between modelled and observed values for PM10 and PM2.5 are 0.55 and 0.47, respectively. Correlations for total, coarse and fine AOD are 0.51, 0.63, and 0.53, respectively. The higher correlations of the PM10 and the coarse mode AOD are largely due to the accurate representation of the African dust influence in the forecasting system. Overall PM and AOD levels are underestimated. The evaluation of the aerosol components highlights underestimations in the fine fraction of carbonaceous matter (EC and OC) and secondary inorganic aerosols (SIA; i.e. nitrate, sulphate and ammonium). The scores of the bulk parameters are significantly improved after applying a simple model bias correction based on the observed aerosol composition. The simulated PM10 and AOD present maximum values over the industrialized and populated Po Valley and Benelux regions. SIA are dominant in the fine fraction representing up to 80% of the aerosol budget in latitudes north of 40° N. In southern Europe, high PM10 and AOD are linked to the desert dust transport from the Sahara which contributes up to 40% of the aerosol budget. Maximum seasonal ground-level concentrations (PM10 > 30 μg m-3) are found between spring and early autumn. We estimate that desert dust causes daily exceedances of the PM10 European air quality limit value (50 μg m-3) in large areas south of 45° N with more than 75 exceedances per year in the southernmost regions.

Tunable and switchable dual-wavelength single polarization narrow linewidth SLM erbium-doped fiber laser based on a PM-CMFBG filter.

PubMed

Yin, Bin; Feng, Suchun; Liu, Zhibo; Bai, Yunlong; Jian, Shuisheng

2014-09-22

A tunable and switchable dual-wavelength single polarization narrow linewidth single-longitudinal-mode (SLM) erbium-doped fiber (EDF) ring laser based on polarization-maintaining chirped moiré fiber Bragg grating (PM-CMFBG) filter is proposed and demonstrated. For the first time as we know, the CMFBG inscribed on the PM fiber is applied for the wavelength-tunable and-switchable dual-wavelength laser. The PM-CMFBG filter with ultra-narrow transmission band (0.1 pm) and a uniform polarization-maintaining fiber Bragg grating (PM-FBG) are used to select the laser longitudinal mode. The stable single polarization SLM operation is guaranteed by the PM-CMFBG filter and polarization controller. A tuning range of about 0.25 nm with about 0.075 nm step is achieved by stretching the uniform PM-FBG. Meanwhile, the linewidth of the fiber laser for each wavelength is approximate 6.5 and 7.1 kHz with a 20 dB linewidth, which indicates the laser linewidth is approximate 325 Hz and 355 Hz FWHM.

Respiratory hospitalizations in association with fine PM and its ...

EPA Pesticide Factsheets

Despite observed geographic and temporal variation in particulate matter (PM)-related health morbidities, only a small number of epidemiologic studies have evaluated the relation between PM2.5 chemical constituents and respiratory disease. Most assessments are limited by inadequate spatial and temporal resolution of ambient PM measurements and/or by their approaches to examine the role of specific PM components on health outcomes. In a case-crossover analysis using daily average ambient PM2.5 total mass and species estimates derived from the Community Multiscale Air Quality (CMAQ) model and available observations, we examined the association between the chemical components of PM (including elemental and organic carbon, sulfate, nitrate, ammonium, and other remaining) and respiratory hospitalizations in New York State. We evaluated relationships between levels (low, medium, high) of PM constituent mass fractions, and assessed modification of the PM2.5–hospitalization association via models stratified by mass fractions of both primary and secondary PM components. In our results, average daily PM2.5 concentrations in New York State were generally lower than the 24-hr average National Ambient Air Quality Standard (NAAQS). Year-round analyses showed statistically significant positive associations between respiratory hospitalizations and PM2.5 total mass, sulfate, nitrate, and ammonium concentrations at multiple exposure lags (0.5–2.0% per interquartile range [IQR

Short-term population-based and spatiotemporal nonlinear concentration-response associations between fine particulate matter and children's respiratory clinic visits

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Chien, Lung-Chang

2014-05-01

Advert health impacts associated with the PM2.5 exposure have been confirmed in mortality and cardiovascular diseases; however, findings of the influence of PM2.5 on respiratory diseases investigated among previous studies are still inconsistent. We investigated the short-term population-based associations between the respiratory clinic visits of children population and the PM2.5 exposure levels with considering both the spatiotemporal distributions of the ambient pollution and clinic visit data. We applied a spatiotemporal structured additive regression model to examine the concentration-response (C-R) association between daily children's respiratory clinic visits and PM2.5 concentrations. The analysis was performed separately on the four selected respiratory disease categories of the population-based dataset, obtained from Taiwan National Health Insurance database, covering the 41 districts in Taipei area during the period of 2005 to 2007. This study reveals a strong nonlinear C-R pattern that the PM2.5 increment can significantly affect respiratory health at PM2.5 concentration ≤ 18.17µg/m3 for both preschool children and schoolchildren. The elevated risks are especially present in the category of acute respiratory infections. PM2.5 increase is mostly non-significant to the more severe respiratory diseases, e.g., COPD and pneumonia, over the ranges of 8.85-92.45µg/m3. The significantly higher relative rate of respiratory clinic visit most likely concentrated at populated areas. We highlight the nonlinearity of the respiratory health impacts of PM2.5 on children's populations from the first study, to our knowledge, to investigate this population-based association. The strong nonlinearity can possibly cause the inconsistency of PM2.5 health impact assessments with linear assumptions.

The short-term association of selected components of fine particulate matter and mortality in the Denver Aerosol Sources and Health (DASH) study

EPA Science Inventory

Associations of short-term exposure to fine particulate matter (PM2.5) with daily mortality may be due to specific PM2.5 chemical components. Objectives: Daily concentrations of PM2.5 chemical species were measured over five consecutive years in Denver, CO to investigate whethe...

78 FR 38223 - Approval and Promulgation of Implementation Plans; Designation of Areas for Air Quality Planning...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-26

... demonstration showing how the area will continue to attain the 24-hour PM 10 NAAQS for at least 10 years beyond...; California; South Coast Air Basin; Approval of PM 10 Maintenance Plan and Redesignation to Attainment for the PM 10 Standard AGENCY: Environmental Protection Agency (EPA). ACTION: Final rule. SUMMARY: EPA is...

Personal exposure measurements of school-children to fine particulate matter (PM2.5) in winter of 2013, Shanghai, China.

PubMed

Zhang, Lijun; Guo, Changyi; Jia, Xiaodong; Xu, Huihui; Pan, Meizhu; Xu, Dong; Shen, Xianbiao; Zhang, Jianghua; Tan, Jianguo; Qian, Hailei; Dong, Chunyang; Shi, Yewen; Zhou, Xiaodan; Wu, Chen

2018-01-01

The aim of this study was to perform an exposure assessment of PM2.5 (particulate matter less than 2.5μm in aerodynamic diameter) among children and to explore the potential sources of exposure from both indoor and outdoor environments. In terms of real-time exposure measurements of PM2.5, we collected data from 57 children aged 8-12 years (9.64 ± 0.93 years) in two schools in Shanghai, China. Simultaneously, questionnaire surveys and time-activity diaries were used to estimate the environment at home and daily time-activity patterns in order to estimate the exposure dose of PM2.5 in these children. Principle component regression analysis was used to explore the influence of potential sources of PM2.5 exposure. All the median personal exposure and microenvironment PM2.5 concentrations greatly exceeded the daily 24-h PM2.5 Ambient Air Quality Standards of China, the USA, and the World Health Organization (WHO). The median Etotal (the sum of the PM2.5 exposure levels in different microenvironment and fractional time) of all students was 3014.13 (μg.h)/m3. The concentration of time-weighted average (TWA) exposure of all students was 137.01 μg/m3. The median TWA exposure level during the on-campus period (135.81 μg/m3) was significantly higher than the off-campus period (115.50 μg/m3, P = 0.013 < 0.05). Besides ambient air pollution and meteorological conditions, storey height of the classroom and mode of transportation to school were significantly correlated with children's daily PM2.5 exposure. Children in the two selected schools were exposed to high concentrations of PM2.5 in winter of 2013 in Shanghai. Their personal PM2.5 exposure was mainly associated with ambient air conditions, storey height of the classroom, and children's transportation mode to school.

40 CFR 94.306 - Certification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... declarations are required for each pollutant (THC+NOX and PM). (2) Declare FELs for each engine family... model year. Manufacturers that have certified engine families with credit balances for THC+NOX and/or PM...

40 CFR 94.306 - Certification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... declarations are required for each pollutant (THC+NOX and PM). (2) Declare FELs for each engine family... model year. Manufacturers that have certified engine families with credit balances for THC+NOX and/or PM...

40 CFR 94.306 - Certification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... declarations are required for each pollutant (THC+NOX and PM). (2) Declare FELs for each engine family... model year. Manufacturers that have certified engine families with credit balances for THC+NOX and/or PM...

40 CFR 94.306 - Certification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... declarations are required for each pollutant (THC+NOX and PM). (2) Declare FELs for each engine family... model year. Manufacturers that have certified engine families with credit balances for THC+NOX and/or PM...

40 CFR 94.306 - Certification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... declarations are required for each pollutant (THC+NOX and PM). (2) Declare FELs for each engine family... model year. Manufacturers that have certified engine families with credit balances for THC+NOX and/or PM...

The first signs of prospective memory.

PubMed

Ślusarczyk, Elżbieta; Niedźwieńska, Agnieszka; Białecka-Pikul, Marta

2018-06-05

We conducted a study to examine the impact of motivation and length of delay on performance on prospective memory (PM) tasks in 2-year of children. A total of 158 children aged exactly 24 months were asked to perform a naturalistic PM task. Length of delay (10 min; 35 min) and motivation (high; very high) were between-subjects factors. Two thirds of children had to be excluded from the analysis because of poor retrospective memory for the PM task instructions which were no longer remembered at the end of the session. For the children who did remember the instructions, both motivation and delay had significant effects on PM. Also, their PM performance was reliably above zero, even after the long delay. The findings indicate that when children as young as 24 months are able to remember the PM task instructions they can reliably succeed in PM tasks that are intrinsically motivating for them.

Historical evaluation of vehicle emission control in Guangzhou based on a multi-year emission inventory

NASA Astrophysics Data System (ADS)

Zhang, Shaojun; Wu, Ye; Liu, Huan; Wu, Xiaomeng; Zhou, Yu; Yao, Zhiliang; Fu, Lixin; He, Kebin; Hao, Jiming

2013-09-01

The Guangzhou government adopted many vehicle emission control policies and strategies during the five-year preparation (2005-2009) to host the 2010 Asian Games. This study established a multi-year emission inventory for vehicles in Guangzhou during 2005-2009 and estimated the uncertainty in total vehicle emissions by taking the assumed uncertainties in fleet-average emission factors and annual mileage into account. In 2009, the estimated total vehicle emissions in Guangzhou were 313 000 (242 000-387 000) tons of CO, 60 900 (54 000-70 200) tons of THC, 65 600 (56 800-74 100) tons of NOx and 2740 (2100-3400) tons of PM10. Vehicle emissions within the urban area of Guangzhou were estimated to be responsible for ˜40% of total gaseous pollutants and ˜25% of total PM10 in the entire city. Although vehicle use intensity increased rapidly in Guangzhou during 2005-2009, vehicle emissions were estimated to have been reduced by 12% for CO, 21% for THC and 20% for PM10 relative to those in 2005. NOx emissions were estimated to have remained almost constant during this period. Compared to the "without control" scenario, 19% (15%-23%) of CO, 20% (18%-23%) of THC, 9% (8%-10%) of NOx and 16% (12%-20%) of PM10 were estimated to have been mitigated from a combination of the implementation of Euro III standards for light-duty vehicles (LDVs) and heavy-duty diesel vehicles and improvement of fuel quality. This study also evaluated several enhanced vehicle emission control actions taken recently. For example, the enhanced I/M program for LDVs was estimated to reduce 11% (9%-14%) of CO, 9% (8%-10%) of THC and 2% (2%-3%) of NOx relative to total vehicle emissions in 2009. Total emission reductions by temporary traffic controls for the Asian Games were estimated equivalent to 9% (7%-11%) of CO, 9% (8%-10%) of THC, 5% (5%-6%) of NOx and 10% (8%-13%) of PM10 estimated total vehicle emissions in 2009. Those controls are essential to further vehicle emission mitigation in Guangzhou required by the new National Ambient Air Quality Standards.

SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications

NASA Astrophysics Data System (ADS)

Snider, G.; Weagle, C. L.; Martin, R. V.; van Donkelaar, A.; Conrad, K.; Cunningham, D.; Gordon, C.; Zwicker, M.; Akoshile, C.; Artaxo, P.; Anh, N. X.; Brook, J.; Dong, J.; Garland, R. M.; Greenwald, R.; Griffith, D.; He, K.; Holben, B. N.; Kahn, R.; Koren, I.; Lagrosas, N.; Lestari, P.; Ma, Z.; Vanderlei Martins, J.; Quel, E. J.; Rudich, Y.; Salam, A.; Tripathi, S. N.; Yu, C.; Zhang, Q.; Zhang, Y.; Brauer, M.; Cohen, A.; Gibson, M. D.; Liu, Y.

2015-01-01

Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2.5) at the global scale. Satellite remote sensing offers a promising approach to provide information on both short- and long-term exposure to PM2.5 at local-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD). We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health-effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) includes a global federation of ground-level monitors of hourly PM2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of regions around the world, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. Mean PM2.5 concentrations across sites vary by more than 1 order of magnitude. Our initial measurements indicate that the ratio of AOD to ground-level PM2.5 is driven temporally and spatially by the vertical profile in aerosol scattering. Spatially this ratio is also strongly influenced by the mass scattering efficiency.

Modeling Of In-Vehicle Human Exposure to Ambient Fine Particulate Matter

PubMed Central

Liu, Xiaozhen; Frey, H. Christopher

2012-01-01

A method for estimating in-vehicle PM2.5 exposure as part of a scenario-based population simulation model is developed and assessed. In existing models, such as the Stochastic Exposure and Dose Simulation model for Particulate Matter (SHEDS-PM), in-vehicle exposure is estimated using linear regression based on area-wide ambient PM2.5 concentration. An alternative modeling approach is explored based on estimation of near-road PM2.5 concentration and an in-vehicle mass balance. Near-road PM2.5 concentration is estimated using a dispersion model and fixed site monitor (FSM) data. In-vehicle concentration is estimated based on air exchange rate and filter efficiency. In-vehicle concentration varies with road type, traffic flow, windspeed, stability class, and ventilation. Average in-vehicle exposure is estimated to contribute 10 to 20 percent of average daily exposure. The contribution of in-vehicle exposure to total daily exposure can be higher for some individuals. Recommendations are made for updating exposure models and implementation of the alternative approach. PMID:23101000

Long-term trends and health impact of PM2.5 and O3 in Tehran, Iran, 2006-2015.

PubMed

Faridi, Sasan; Shamsipour, Mansour; Krzyzanowski, Michal; Künzli, Nino; Amini, Heresh; Azimi, Faramarz; Malkawi, Mazen; Momeniha, Fatemeh; Gholampour, Akbar; Hassanvand, Mohammad Sadegh; Naddafi, Kazem

2018-05-01

The main objectives of this study were (1) investigation of the temporal variations of ambient fine particulate matter (PM 2.5 ) and ground level ozone (O 3 ) concentrations in Tehran megacity, the capital and most populous city in Iran, over a 10-year period from 2006 to 2015, and (2) estimation of their long-term health effects including all-cause and cause-specific mortality. For the first goal, the data of PM 2.5 and O 3 concentrations, measured at 21 regulatory monitoring network stations in Tehran, were obtained and the temporal trends were investigated. The health impact assessment of PM 2.5 and O 3 was performed using the World Health Organization (WHO) AirQ+ software updated in 2016 by WHO European Centre for Environment and Health. Local baseline incidences in Tehran level were used to better reveal the health effects associated with PM 2.5 and O 3 . Our study showed that over 2006-2015, annual mean concentrations of PM 2.5 and O 3 varied from 24.7 to 38.8 μg m -3 and 35.4 to 76.0 μg m -3 , respectively, and were significantly declining in the recent 6 years (2010-2015) for PM 2.5 and 8 years (2008-2015) for O 3 . However, Tehran citizens were exposed to concentrations of annual PM 2.5 exceeding the WHO air quality guideline (WHO AQG) (10 μg m -3 ), U.S. EPA and Iranian standard levels (12 μg m -3 ) during entire study period. We estimated that long-term exposure to ambient PM 2.5 contributed to between 24.5% and 36.2% of mortality from cerebrovascular disease (stroke), 19.8% and 24.1% from ischemic heart disease (IHD), 13.6% and 19.2% from lung cancer (LC), 10.7% and 15.3% from chronic obstructive pulmonary disease (COPD), 15.0% and 25.2% from acute lower respiratory infection (ALRI), and 7.6% and 11.3% from all-cause annual mortality in the time period. We further estimated that deaths from IHD accounted for most of mortality attributable to long-term exposure to PM 2.5 . The years of life lost (YLL) attributable to PM 2.5 was estimated to vary from 67,970 to 106,706 during the study period. In addition, long-term exposure to O 3 was estimated to be responsible for 0.9% to 2.3% of mortality from respiratory diseases. Overall, long-term exposure to ambient PM 2.5 and O 3 contributed substantially to mortality in Tehran megacity. Air pollution is a modifiable risk factor. Appropriate sustainable control policies are recommended to protect public health. Copyright © 2018 Elsevier Ltd. All rights reserved.

Particulate Matter deposition on Quercus ilex leaves in an industrial city of central Italy.

PubMed

Sgrigna, G; Sæbø, A; Gawronski, S; Popek, R; Calfapietra, C

2015-02-01

A number of studies have focused on urban trees to understand their mitigation capacity of air pollution. In this study particulate matter (PM) deposition on Quercus ilex leaves was quantitatively analyzed in four districts of the City of Terni (Italy) for three periods of the year. Fine (between 0.2 and 2.5 μm) and Large (between 2.5 and 10 μm) PM fractions were analyzed. Mean PM deposition value on Quercus ilex leaves was 20.6 μg cm(-2). Variations in PM deposition correlated with distance to main roads and downwind position relatively to industrial area. Epicuticular waxes were measured and related to accumulated PM. For Fine PM deposited in waxes we observed a higher value (40% of total Fine PM) than Large PM (4% of total Large PM). Results from this study allow to increase our understanding about air pollution interactions with urban vegetation and could be hopefully taken into account when guidelines for local urban green management are realized. Copyright © 2014 Elsevier Ltd. All rights reserved.

Sustaining prospective memory functioning in amnestic mild cognitive impairment: A lifespan approach to the critical role of encoding.

PubMed

Pereira, Antonina; Altgassen, Mareike; Atchison, Lesley; de Mendonça, Alexandre; Ellis, Judi

2018-04-16

Prospective memory (PM), the ability to remember to perform future activities, is a fundamental requirement for independent living. PM tasks pervade our daily lives, and PM failures represent one of the most prominent memory concerns across the entire life span. This study aimed to address this issue by exploring the potential benefits of specific encoding strategies on memory for intentions across healthy adulthood and in the early stages of cognitive impairment. PM performance was explored through an experimental paradigm in 96 participants: 32 amnestic mild cognitively impaired patients aged 64-87 years (M = 6.75, SD = 5.88), 32 healthy older adults aged 62-84 years (M = 76.06, SD = 6.03), and 32 younger adults 18-22 years (M = 19.75, SD = 1.16). The potential benefit of the use of enactment (i.e., physically simulating the intended action) at encoding to support an autonomous performance despite neuronal degeneration was assessed. PM was consistently identified as a sensitive and specific indicator of cognitive impairment. Importantly, enacted encoding was consistently beneficial for PM performance of all the participants, but especially so in the case of healthy and cognitively impaired older adults. These positive results have unveiled the potential of this encoding technique to optimize attentional demands through an adaptive allocation of strategic resources across both healthy and cognitively impaired samples. Theoretical implications of this work are discussed as well as the considerable translational potential to improve social well-being. A better understanding of the strategies that can enhance PM offers the potential for cost-effective and widely applicable tools which may support independent living across the adult life span. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Chronic Exposure to Fine Particles and Mortality: An Extended Follow-up of the Harvard Six Cities Study from 1974 to 2009

PubMed Central

Laden, Francine; Dockery, Douglas; Schwartz, Joel

2012-01-01

Background: Epidemiologic studies have reported associations between fine particles (aerodynamic diameter ≤ 2.5 µm; PM2.5) and mortality. However, concerns have been raised regarding the sensitivity of the results to model specifications, lower exposures, and averaging time. Objective: We addressed these issues using 11 additional years of follow-up of the Harvard Six Cities study, incorporating recent lower exposures. Methods: We replicated the previously applied Cox regression, and examined different time lags, the shape of the concentration–response relationship using penalized splines, and changes in the slope of the relation over time. We then conducted Poisson survival analysis with time-varying effects for smoking, sex, and education. Results: Since 2001, average PM2.5 levels, for all six cities, were < 18 µg/m3. Each increase in PM2.5 (10 µg/m3) was associated with an adjusted increased risk of all-cause mortality (PM2.5 average on previous year) of 14% [95% confidence interval (CI): 7, 22], and with 26% (95% CI: 14, 40) and 37% (95% CI: 7, 75) increases in cardiovascular and lung-cancer mortality (PM2.5 average of three previous years), respectively. The concentration–response relationship was linear down to PM2.5 concentrations of 8 µg/m3. Mortality rate ratios for PM2.5 fluctuated over time, but without clear trends despite a substantial drop in the sulfate fraction. Poisson models produced similar results. Conclusions: These results suggest that further public policy efforts that reduce fine particulate matter air pollution are likely to have continuing public health benefits. PMID:22456598

Air pollution modeling over very complex terrain: An evaluation of WRF-Chem over Switzerland for two 1-year periods

NASA Astrophysics Data System (ADS)

Ritter, Mathias; Müller, Mathias D.; Tsai, Ming-Yi; Parlow, Eberhard

2013-10-01

The fully coupled chemistry module (WRF-Chem) within the Weather Research and Forecasting (WRF) model has been implemented over a Swiss domain for the years 2002 and 1991. The very complex terrain requires a high horizontal resolution (2 × 2 km2), which is achieved by nesting the Swiss domain into a coarser European one. The temporal and spatial distribution of O3, NO2 and PM10 as well as temperature and solar radiation are evaluated against ground-based measurements. The model performs well for the meteorological parameters with Pearson correlation coefficients of 0.92 for temperature and 0.88-0.89 for solar radiation. Temperature has root mean square errors (RMSE) of 3.30 K and 3.51 K for 2002 and 1991 and solar radiation has RMSEs of 122.92 and 116.35 for 2002 and 1991, respectively. For the modeled air pollutants, a multi-linear regression post-processing was used to eliminate systematic bias. Seasonal variations of post-processed air pollutants are represented correctly. However, short-term peaks of several days are not captured by the model. Averaged daily maximum and daily values of O3 achieved Pearson correlation coefficients of 0.69-0.77 whereas averaged NO2 and PM10 had the highest correlations for yearly average values (0.68-0.78). The spatial distribution reveals the importance of PM10 advection from the Po valley to southern Switzerland (Ticino). The absolute errors are ranging from - 10 to 15 μg/m3 for ozone, - 9 to 3 μg/m3 for NO2 and - 4 to 3 μg/m3 for PM10. However, larger errors occur along heavily trafficked roads, in street canyons or on mountains. We also compare yearly modeled results against a dedicated Swiss dispersion model for NO2 and PM10. The dedicated dispersion model has a slightly better statistical performance, but WRF-Chem is capable of computing the temporal evolution of three-dimensional data for a variety of air pollutants and meteorological parameters. Overall, WRF-Chem with the application of post-processing algorithms can produce encouraging statistical values over very complex terrain which are competitive with similar studies.

Characteristics and classification of PM2.5 pollution episodes in Beijing from 2013 to 2015.

PubMed

Wang, Xiaoqi; Wei, Wei; Cheng, Shuiyuan; Li, Jianbing; Zhang, Hanyu; Lv, Zhe

2018-01-15

During the period of 2013-2015, a total of 34 PM 2.5 pollution episodes occurred in Beijing, each of which remained for at least 2days. Among that, 28 times occurred in winter half year with the average concentration of 243.1μg/m 3 and summer half year with the average concentration of 194.1μg/m 3 . These episodes were mainly associated with lower wind speed and lower visibility as well as higher relative humidity, indicating that they belonged to heavy pollution under static stability. The PM 2.5 pollution was classified into two categories according to the back trajectory analysis and meteorological background field. Category I, accounting for 22 times among all the pollution episodes, was due to air mass transport from Beijing's southern regions with north-south direction pressure gradient and sparse isopiestic. And category II was mainly led by northwestern air masses accompanied with a large area of uniform pressure field. Then, a typical case study was conducted for each category to recognize the sub-region contribution to Beijing's PM 2.5 pollution based on WRF-CAMx modeling system, and the simulation results indicated that local emission source contribution decreased significantly during the accumulation phase for category I, but increased during that of category II, with an average contribution of 47.3% and 77.1% during the entire pollution period of each category, respectively. Two red alerts of air pollution occurred in December 2015 were also analyzed based on the episode classification. It was found that the second red alert pollution episode belonged to category II. The emission control measures in Beijing worked more obviously with the reduction effect ratio of 15.4% compared to the first red alert period (9.7%). Copyright © 2017 Elsevier B.V. All rights reserved.

Two years of near real-time chemical composition of submicron aerosols in the region of Paris using an Aerosol Chemical Speciation Monitor (ACSM) and a multi-wavelength Aethalometer

NASA Astrophysics Data System (ADS)

Petit, J.-E.; Favez, O.; Sciare, J.; Crenn, V.; Sarda-Estève, R.; Bonnaire, N.; Močnik, G.; Dupont, J.-C.; Haeffelin, M.; Leoz-Garziandia, E.

2015-03-01

Aerosol mass spectrometer (AMS) measurements have been successfully used towards a better understanding of non-refractory submicron (PM1) aerosol chemical properties based on short-term campaigns. The recently developed Aerosol Chemical Speciation Monitor (ACSM) has been designed to deliver quite similar artifact-free chemical information but for low cost, and to perform robust monitoring over long-term periods. When deployed in parallel with real-time black carbon (BC) measurements, the combined data set allows for a quasi-comprehensive description of the whole PM1 fraction in near real time. Here we present 2-year long ACSM and BC data sets, between mid-2011 and mid-2013, obtained at the French atmospheric SIRTA supersite that is representative of background PM levels of the region of Paris. This large data set shows intense and time-limited (a few hours) pollution events observed during wintertime in the region of Paris, pointing to local carbonaceous emissions (mainly combustion sources). A non-parametric wind regression analysis was performed on this 2-year data set for the major PM1 constituents (organic matter, nitrate, sulfate and source apportioned BC) and ammonia in order to better refine their geographical origins and assess local/regional/advected contributions whose information is mandatory for efficient mitigation strategies. While ammonium sulfate typically shows a clear advected pattern, ammonium nitrate partially displays a similar feature, but, less expectedly, it also exhibits a significant contribution of regional and local emissions. The contribution of regional background organic aerosols (OA) is significant in spring and summer, while a more pronounced local origin is evidenced during wintertime, whose pattern is also observed for BC originating from domestic wood burning. Using time-resolved ACSM and BC information, seasonally differentiated weekly diurnal profiles of these constituents were investigated and helped to identify the main parameters controlling their temporal variations (sources, meteorological parameters). Finally, a careful investigation of all the major pollution episodes observed over the region of Paris between 2011 and 2013 was performed and classified in terms of chemical composition and the BC-to-sulfate ratio used here as a proxy of the local/regional/advected contribution of PM. In conclusion, these first 2-year quality-controlled measurements of ACSM clearly demonstrate their great potential to monitor on a long-term basis aerosol sources and their geographical origin and provide strategic information in near real time during pollution episodes. They also support the capacity of the ACSM to be proposed as a robust and credible alternative to filter-based sampling techniques for long-term monitoring strategies.

A New Combined Stepwise-Based High-Order Decoupled Direct and Reduced-Form Method To Improve Uncertainty Analysis in PM2.5 Simulations.

PubMed

Huang, Zhijiong; Hu, Yongtao; Zheng, Junyu; Yuan, Zibing; Russell, Armistead G; Ou, Jiamin; Zhong, Zhuangmin

2017-04-04

The traditional reduced-form model (RFM) based on the high-order decoupled direct method (HDDM), is an efficient uncertainty analysis approach for air quality models, but it has large biases in uncertainty propagation due to the limitation of the HDDM in predicting nonlinear responses to large perturbations of model inputs. To overcome the limitation, a new stepwise-based RFM method that combines several sets of local sensitive coefficients under different conditions is proposed. Evaluations reveal that the new RFM improves the prediction of nonlinear responses. The new method is applied to quantify uncertainties in simulated PM 2.5 concentrations in the Pearl River Delta (PRD) region of China as a case study. Results show that the average uncertainty range of hourly PM 2.5 concentrations is -28% to 57%, which can cover approximately 70% of the observed PM 2.5 concentrations, while the traditional RFM underestimates the upper bound of the uncertainty range by 1-6%. Using a variance-based method, the PM 2.5 boundary conditions and primary PM 2.5 emissions are found to be the two major uncertainty sources in PM 2.5 simulations. The new RFM better quantifies the uncertainty range in model simulations and can be applied to improve applications that rely on uncertainty information.

Investigating the Effect of Social Changes on Age-Specific Gun-Related Homicide Rates in New York City During the 1990s

PubMed Central

Messner, Steven F.; Tracy, Melissa; Vlahov, David; Goldmann, Emily; Tardiff, Kenneth J.; Galea, Sandro

2010-01-01

Objectives. We assessed whether New York City's gun-related homicide rates in the 1990s were associated with a range of social determinants of homicide rates. Methods. We used cross-sectional time-series data for 74 New York City police precincts from 1990 through 1999, and we estimated Bayesian hierarchical models with a spatial error term. Homicide rates were estimated separately for victims aged 15–24 years (youths), 25–34 years (young adults), and 35 years or older (adults). Results. Decreased cocaine consumption was associated with declining homicide rates in youths (posterior median [PM] = 0.25; 95% Bayesian confidence interval [BCI] = 0.07, 0.45) and adults (PM = 0.07; 95% BCI = 0.02, 0.12), and declining alcohol consumption was associated with fewer homicides in young adults (PM = 0.14; 95% BCI = 0.02, 0.25). Receipt of public assistance was associated with fewer homicides for young adults (PM = –104.20; 95% BCI = –182.0, –26.14) and adults (PM = –28.76; 95% BCI = –52.65, –5.01). Misdemeanor policing was associated with fewer homicides in adults (PM = –0.01; 95% BCI = –0.02, –0.001). Conclusions. Substance use prevention policies and expansion of the social safety net may be able to cause major reductions in homicide among age groups that drive city homicide trends. PMID:20395590

Using new satellite based exposure methods to study the association between pregnancy pm2.5 exposure, premature birth and birth weight in Massachusetts

PubMed Central

2012-01-01

Background Adverse birth outcomes such as low birth weight and premature birth have been previously linked with exposure to ambient air pollution. Most studies relied on a limited number of monitors in the region of interest, which can introduce exposure error or restrict the analysis to persons living near a monitor, which reduces sample size and generalizability and may create selection bias. Methods We evaluated the relationship between premature birth and birth weight with exposure to ambient particulate matter (PM2.5) levels during pregnancy in Massachusetts for a 9-year period (2000–2008). Building on a novel method we developed for predicting daily PM2.5 at the spatial resolution of a 10x10km grid across New-England, we estimated the average exposure during 30 and 90 days prior to birth as well as the full pregnancy period for each mother. We used linear and logistic mixed models to estimate the association between PM2.5 exposure and birth weight (among full term births) and PM2.5 exposure and preterm birth adjusting for infant sex, maternal age, maternal race, mean income, maternal education level, prenatal care, gestational age, maternal smoking, percent of open space near mothers residence, average traffic density and mothers health. Results Birth weight was negatively associated with PM2.5 across all tested periods. For example, a 10 μg/m3 increase of PM2.5 exposure during the entire pregnancy was significantly associated with a decrease of 13.80 g [95% confidence interval (CI) = −21.10, -6.05] in birth weight after controlling for other factors, including traffic exposure. The odds ratio for a premature birth was 1.06 (95% confidence interval (CI) = 1.01–1.13) for each 10 μg/m3 increase of PM2.5 exposure during the entire pregnancy period. Conclusions The presented study suggests that exposure to PM2.5 during the last month of pregnancy contributes to risks for lower birth weight and preterm birth in infants. PMID:22709681

Ground-Water, Surface-Water, and Water-Chemistry Data, Black Mesa Area, Northeastern Arizona--2004-05

DTIC Science & Technology

2006-02-27

samples from 7 wells having more than 10 years of data and from 2 springs. Rough Rock PM5, Keams Canyon PM2, Second Mesa PM2, and Kayenta PM2 show...source of water for industrial and municipal uses in the Black Mesa area. It consists of three formations—the Navajo Sandstone, the Kayenta ...A R I Z O N A 98 NAVAJO IND. RES. 77 264 191 160 163 Kayenta 160 Tuba City Chinle 89 Mishongnovi Shipaulovi 264 87 30’ 36° 35°30

Expanding the Estimation of Surface PM2.5 from Aqua and Terra MODIS Aerosol Optical Depth in the EPA's AirNow Satellite Data Processor to Suomi NPP VIIRS

NASA Astrophysics Data System (ADS)

Szykman, J.; Kondragunta, S.; Zhang, H.; Dickerson, P.; van Donkelaar, A.; Martin, R. V.; Pasch, A. N.; White, J. E.; DeWinter, J. L.; Zahn, P. H.; Dye, T. S.; Haderman, M. D.

2012-12-01

The U.S. Environmental Protection Agency's (EPA) Air Quality Index (AQI) relies on hourly measurements of ground-based surface PM2.5 (particles smaller than 2.5 μm in median diameter) to develop daily AQI index maps. The EPA is improving the accuracy of AQI information and extending its coverage for reporting to the public by incorporating National Aeronautics and Space Administration (NASA) satellite-derived surface PM2.5 concentrations into daily AQI maps. The additional coverage will provide air quality information in regions without dense monitoring networks. The AirNow Satellite Data Processor (ASDP) uses daily PM2.5 estimates and uncertainties derived from average Aqua and Terra MODerate resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) in near real-time over the United States. The algorithm to derive surface PM2.5 from MODIS AOD relies on linear relationships between AOD and PM2.5 generated from multi-year GEOS-Chem model simulations (van Donkelaar et al., 2012). Parameters from the regression equation (slopes and intercepts) are saved in a lookup table (LUT) with 4 km spatial resolution for each day of a given year. To improve data accuracy and continuity, a filter is applied to remove MODIS AOD with low accuracy (e.g., over bright surfaces) and an inverse distance weighted average is applied to fill in gaps created by cloud coverage. Daily surface PM2.5 estimates and their uncertainties are generated at the National Oceanic and Atmospheric Administration (NOAA) using the van Donkelaar et al. algorithm and near real-time MODIS AOD products from Terra and Aqua and are provided to the EPA through its Infusing satellite Data into Environmental Applications (IDEA) website. The Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on October 28, 2011, and similar to MODIS, provides AOD products for real-time applications. NOAA plans to explore the value of VIIRS AOD products to improve AQI. This presentation will focus on a description of ASDP, including an overview of the algorithm used to estimate surface PM2.5 using satellite data and examples of high resolution VIIRS AOD products and their value to the ASDP. Disclaimer: Although this work was reviewed by the U.S. Environmental Protection Agency and approved for publication, it may not necessarily reflect official Agency policy.

Predictability Analysis of PM10 Concentrations in Budapest

NASA Astrophysics Data System (ADS)

Ferenczi, Zita

2013-04-01

Climate, weather and air quality may have harmful effects on human health and environment. Over the past few hundred years we had to face the changes in climate in parallel with the changes in air quality. These observed changes in climate, weather and air quality continuously interact with each other: pollutants are changing the climate, thus changing the weather, but climate also has impacts on air quality. The increasing number of extreme weather situations may be a result of climate change, which could create favourable conditions for rising of pollutant concentrations. Air quality in Budapest is determined by domestic and traffic emissions combined with the meteorological conditions. In some cases, the effect of long-range transport could also be essential. While the time variability of the industrial and traffic emissions is not significant, the domestic emissions increase in winter season. In recent years, PM10 episodes have caused the most critical air quality problems in Budapest, especially in winter. In Budapest, an air quality network of 11 stations detects the concentration values of different pollutants hourly. The Hungarian Meteorological Service has developed an air quality prediction model system for the area of Budapest. The system forecasts the concentration of air pollutants (PM10, NO2, SO2 and O3) for two days in advance. In this work we used meteorological parameters and PM10 data detected by the stations of the air quality network, as well as the forecasted PM10 values of the air quality prediction model system. In this work we present the evaluation of PM10 predictions in the last two years and the most important meteorological parameters affecting PM10 concentration. The results of this analysis determine the effect of the meteorological parameters and the emission of aerosol particles on the PM10 concentration values as well as the limits of this prediction system.

Traffic-related air pollution and hyperactivity/inattention, dyslexia and dyscalculia in adolescents of the German GINIplus and LISAplus birth cohorts.

PubMed

Fuertes, Elaine; Standl, Marie; Forns, Joan; Berdel, Dietrich; Garcia-Aymerich, Judith; Markevych, Iana; Schulte-Koerne, Gerd; Sugiri, Dorothea; Schikowski, Tamara; Tiesler, Carla M T; Heinrich, Joachim

2016-12-01

Few studies have examined the link between air pollution exposure and behavioural problems and learning disorders during late childhood and adolescence. To determine whether traffic-related air pollution exposure is associated with hyperactivity/inattention, dyslexia and dyscalculia up to age 15years using the German GINIplus and LISAplus birth cohorts (recruitment 1995-1999). Hyperactivity/inattention was assessed using the German parent-completed (10years) and self-completed (15years) Strengths and Difficulties Questionnaire. Responses were categorized into normal versus borderline/abnormal. Parent-reported dyslexia and dyscalculia (yes/no) at age 10 and 15years were defined using parent-completed questionnaires. Individual-level annual average estimates of nitrogen dioxide (NO 2 ), particulate matter (PM) 10 mass, PM 2.5 mass and PM 2.5 absorbance concentrations were assigned to each participant's birth, 10year and 15year home address. Longitudinal associations between the air pollutants and the neurodevelopmental outcomes were assessed using generalized estimation equations, separately for both study areas, and combined in a random-effects meta-analysis. Odds ratios and 95% confidence intervals are given per interquartile range increase in pollutant concentration. The prevalence of abnormal/borderline hyperactivity/inattention scores and parental-reported dyslexia and dyscalculia at 15years of age was 12.9%, 10.5% and 3.4%, respectively, in the combined population (N=4745). In the meta- analysis, hyperactivity/inattention was associated with PM 2.5 mass estimated to the 10 and 15year addresses (1.12 [1.01, 1.23] and 1.11 [1.01, 1.22]) and PM 2.5 absorbance estimated to the 10 and 15year addresses (1.14 [1.05, 1.25] and 1.13 [1.04, 1.23], respectively). We report associations suggesting a potential link between air pollution exposure and hyperactivity/inattention scores, although these findings require replication. Copyright © 2016 Elsevier Ltd. All rights reserved.

PM10 and Pb evolution in an industrial area of the Mediterranean basin

NASA Astrophysics Data System (ADS)

Vicente, A. B.; Jordán, M. M.; Pallarés, S.; Sanfeliu, T.

2007-02-01

The study area is highly industrialized, with businesses involved in the non-metal mineral products sector and ceramic industries (colors, frits and enamel manufacturing) standing out. Air quality evaluation was performed regarding atmospheric particles (PM10 fraction) and Pb in a Spanish coastal area during 2001 and 2002 in order to compare these values with other areas in the Mediterranean basin. Once the samples were collected, their PM10 fraction concentration levels were determined gravimetrically. A Pb analysis in air pollution filters was carried out by ICP-MS. The seasonal and weekly variabilities of these contaminants were also studied, with the objective of being able to explain their origin and thus minimize their possible damaging effects. A similar evolution of PM10 and Pb was observed in both years of the study. Higher PM10 concentrations have been detected during the months of June and July, lower values between March-May, August and October-December, and intermediate values in January and February. A similar tendency has been observed by other authors in European industrialized cities. Regarding Pb, the monthly mean remains constant during the entire year. In the study area, Pb represents 0.6% as a mean of the total PM10 mass, with a variation range between 0.1 and 5.1%. The major crystalline phases in PM10 were quartz, calcite, dolomite, illite, kaolinite and feldspars.

Military Energy Alternatives Conference

DTIC Science & Technology

2012-03-08

Power Generation and Alternative Energy Branch US Army RDECOM CERDEC CP&ID Power Division Aberdeen Proving Ground, MD...Co-generation Applications •Tactical Mobile Power •Vehicle-mounted Auxiliary Power and Environmental Control •Energy Security for Base...Mobile Power (PM MEP / PM CP) Vehicle Power (PM Tactical Vehicle / PM HTV) Portable Solar Photovoltaic (PV) Modules and Mobile Hybrid PV Power Sources

Particulate matter dynamics in naturally ventilated freestall dairy barns

NASA Astrophysics Data System (ADS)

Joo, H. S.; Ndegwa, P. M.; Heber, A. J.; Ni, J.-Q.; Bogan, B. W.; Ramirez-Dorronsoro, J. C.; Cortus, E. L.

2013-04-01

Particulate matter (PM) concentrations and ventilation rates, in two naturally ventilated freestall dairy barns, were continuously monitored for two years. The first barn (B1) housed 400 fresh lactating cows, while the second barn (B2) housed 835 non-fresh lactating cows and 15 bulls. The relationships between PM concentrations and accepted governing parameters (environmental conditions and cattle activity) were examined. In comparison with other seasons, PM concentrations were lowest in winter. Total suspended particulate (TSP) concentrations in spring and autumn were relatively higher than those in summer. Overall: the concentrations in the barns and ambient air, for all the PM categories (PM2.5, PM10, and TSP), exhibited non-normal positively skewed distributions, which tended to overestimate mean or average concentrations. Only concentrations of PM2.5 and PM10 increased with ambient air temperature (R2 = 0.60-0.82), whereas only concentrations of TSP increased with cattle activity. The mean respective emission rates of PM2.5, PM10, and TSP for the two barns ranged between 1.6-4.0, 11.9-15.0, and 48.7-52.5 g d-1 cow-1, indicating similar emissions from the two barns.

Estimating health service utilization for treatment of pneumococcal disease: the case of Brazil.

PubMed

Sartori, A M C; Novaes, C G; de Soárez, P C; Toscano, C M; Novaes, H M D

2013-07-02

Health service utilization (HSU) is an essential component of economic evaluations of health initiatives. Defining HSU for cases of pneumococcal disease (PD) is particularly complex considering the varying clinical manifestations and diverse severity. We describe the process of developing estimates of HSU for PD as part of an economic evaluation of the introduction of pneumococcal conjugate vaccine in Brazil. Nationwide inpatient and outpatient HSU by children under-5 years with meningitis (PM), sepsis (PS), non-meningitis non-sepsis invasive PD (NMNS), pneumonia, and acute otitis media (AOM) was estimated. We assumed that all cases of invasive PD (PM, PS, and NMNS) required hospitalization. The study perspective was the health system, including both the public and private sectors. Data sources were obtained from national health information systems, including the Hospital Information System (SIH/SUS) and the Notifiable Diseases Information System (SINAN); surveys; and community-based and health care facility-based studies. We estimated hospitalization rates of 7.69 per 100,000 children under-5 years for PM (21.4 for children <1 years of age and 4.3 for children aged 1-4 years), 5.89 for PS (20.94 and 2.17), and 4.01 for NMNS (5.5 and 3.64) in 2004, with an overall hospitalization rate of 17.59 for all invasive PD (47.27 and 10.11). The estimated incidence rate of all-cause pneumonia was 93.4 per 1000 children under-5 (142.8 for children <1 years of age and 81.2 for children aged 1-4 years), considering both hospital and outpatient care. Secondary data derived from health information systems and the available literature enabled the development of national HSU estimates for PD in Brazil. Estimating HSU for noninvasive disease was challenging, particularly in the case of outpatient care, for which secondary data are scarce. Information for the private sector is lacking in Brazil, but estimates were possible with data from the public sector and national population surveys. Copyright © 2013 Elsevier Ltd. All rights reserved.

ENSO-related PM10 variability on the Korean Peninsula

NASA Astrophysics Data System (ADS)

Wie, Jieun; Moon, Byung-Kwon

2017-10-01

Particulate matter, defined as particles of less than 10 μm in diameter (PM10), was analyzed over the Korean Peninsula from 2001 to 2015 to examine the influence of the El Niño-Southern Oscillation (ENSO) on subseasonal PM10 variability. The PM10 data were obtained from 151 air quality monitoring stations provided by the Korea Environment Corporation (KECO). Lead-lag correlation analysis, which was performed to investigate the connection between NDJF (November-February) NINO3 index and seasonal mean PM10 data, did not yield any statistically significant correlations. However, using five-pentad moving-averaged PM10 data, statistically significant correlations between NDJF NINO3 index and PM10 variability were found in four subseasonal periods, with alternating positive and negative correlations. In the periods during which PM10 levels on the Korean Peninsula were positively (negatively) correlated with the ENSO index, the positive PM10 anomalies are associated with El Niño (La Niña) years, which implies that the occurrence of high-PM10 events could be modulated by the ENSO phase. In addition, this ENSO-related PM10 variation is negatively correlated with ENSO-related precipitation in the Korean Peninsula, indicating that more (less) wet deposition leads to lower (higher) PM10 level. Therefore, we conclude that the ENSO-induced precipitation anomalies over the Korean Peninsula are mainly responsible for ENSO-related PM10 variations. This study will be helpful for further identifying detailed chemistry-climate processes that control PM10 concentrations.

Virtual reality-based prospective memory training program for people with acquired brain injury.

PubMed

Yip, Ben C B; Man, David W K

2013-01-01

Acquired brain injuries (ABI) may display cognitive impairments and lead to long-term disabilities including prospective memory (PM) failure. Prospective memory serves to remember to execute an intended action in the future. PM problems would be a challenge to an ABI patient's successful community reintegration. While retrospective memory (RM) has been extensively studied, treatment programs for prospective memory are rarely reported. The development of a treatment program for PM, which is considered timely, can be cost-effective and appropriate to the patient's environment. A 12-session virtual reality (VR)-based cognitive rehabilitation program was developed using everyday PM activities as training content. 37 subjects were recruited to participate in a pretest-posttest control experimental study to evaluate its treatment effectiveness. Results suggest that significantly better changes were seen in both VR-based and real-life PM outcome measures, related cognitive attributes such as frontal lobe functions and semantic fluency. VR-based training may be well accepted by ABI patients as encouraging improvement has been shown. Large-scale studies of a virtual reality-based prospective memory (VRPM) training program are indicated.

Acute effects of ambient particulate matter pollution on hospital admissions for mental and behavioral disorders: A time-series study in Shijiazhuang, China.

PubMed

Song, Jie; Zheng, Liheng; Lu, Mengxue; Gui, Lihui; Xu, Dongqun; Wu, Weidong; Liu, Yue

2018-04-25

Until now, few epidemiological studies have focused on the association between ambient particulate matter pollution and mental and behavioral disorders, especially in developing countries. Thus, a time-series study on the short-term association between both fine and inhalable particles (PM 2.5 and PM 10 ) and daily hospital admissions for mental and behavioral disorders in Shijiazhuang, China was conducted, from 2014 to 2016. An over-dispersed, generalized additive model was used to analyze the associations after controlling for time trend, weather conditions, day of the week, and holidays. In addition, the modification effects of age, sex, and season were estimated. A total of 9156 cases of hospital admissions for mental and behavioral disorders were identified. A 10 μg/m 3 increase in a 3-day average concentration (lag02) of PM 2.5 and PM 10 correspond to an increase of 0.48% (95% confidence interval (CI): 0.18-0.79%) and 0.32% (95% CI: 0.03-0.62%) in daily hospital admission for mental and behavioral disorders, respectively. We found stronger associations of PM 2.5 and PM 10 with mental and behavioral disorders in male and elder individuals (≥45 years) than in female and younger individuals (<45 years). Further, results indicated a generally stronger association of PM 2.5 with mental and behavioral disorders in the cool season than in the warm season. This research found a significant association between ambient PM 2.5 and PM 10 and hospital admission for mental and behavioral disorders in Shijiazhuang, China. Copyright © 2018 Elsevier B.V. All rights reserved.

One year study of PM2.5 in Xinxiang city, North China: Seasonal characteristics, climate impact and source.

PubMed

Feng, Jinglan; Yu, Hao; Mi, Kai; Su, Xianfa; Li, Yi; Li, Qilu; Sun, Jianhui

2018-06-15

This study was conducted in order to explore the seasonal characteristics, climate impact and source of PM 2.5 in Xinxiang, China. Daily PM 2.5 samples were collected at urban site from January to December in 2015. Average PM 2.5 concentration was 100.6 ± 65.8 μg m -3 in Xinxiang, which was several times higher than China Ambient Air Quality Standards (GB3095-2012). Secondary inorganic aerosols (SIA) constituted 70% of the total ionic concentrations. The average concentration of SO 4 2- was 6.4 ± 12.0 μg m -3 , which ranked the highest among the water-soluble ions analyzed. Seasonal variations of PM 2.5 and its major chemical components were significant, most of them with high values in winter and the lowest values in summer, especially with heavier PM 2.5 events (more than 200 μg/m 3 ) in December. SIA and OC on polluted days were 2.1-2.3 times higher than those of on clean days. It was estimated that Fe, Li, Na, Mg, Al, K, Ca and Sr were emitted from crustal sources and Pb, Cr, Ni, Cu, Zn, As, Cd and V were emitted from anthropogenic emissions using the EF values. Analysis using the tracer and PCA/MLR revealed that vehicle exhausts were the most important source of PM 2.5 , which contributed 26.9% of PM 2.5 over the whole study period. This study provides detailed composition data and first comprehensive analysis of PM 2.5 in Xinxiang during a whole year. Copyright © 2018. Published by Elsevier Inc.

Ambient Air Pollution and Atherosclerosis in Los Angeles

PubMed Central

Künzli, Nino; Jerrett, Michael; Mack, Wendy J.; Beckerman, Bernardo; LaBree, Laurie; Gilliland, Frank; Thomas, Duncan; Peters, John; Hodis, Howard N.

2005-01-01

Associations have been found between long-term exposure to ambient air pollution and cardiovascular morbidity and mortality. The contribution of air pollution to atherosclerosis that underlies many cardiovascular diseases has not been investigated. Animal data suggest that ambient particulate matter (PM) may contribute to atherogenesis. We used data on 798 participants from two clinical trials to investigate the association between atherosclerosis and long-term exposure to ambient PM up to 2.5 μm in aerodynamic diameter (PM2.5). Baseline data included assessment of the carotid intima-media thickness (CIMT), a measure of subclinical atherosclerosis. We geocoded subjects’ residential areas to assign annual mean concentrations of ambient PM2.5. Exposure values were assigned from a PM2.5 surface derived from a geostatistical model. Individually assigned annual mean PM2.5 concentrations ranged from 5.2 to 26.9 μg/m3 (mean, 20.3). For a cross-sectional exposure contrast of 10 μg/m3 PM2.5, CIMT increased by 5.9% (95% confidence interval, 1–11%). Adjustment for age reduced the coefficients, but further adjustment for covariates indicated robust estimates in the range of 3.9–4.3% (p-values, 0.05–0.1). Among older subjects (≥60 years of age), women, never smokers, and those reporting lipid-lowering treatment at baseline, the associations of PM2.5 and CIMT were larger with the strongest associations in women ≥60 years of age (15.7%, 5.7–26.6%). These results represent the first epidemiologic evidence of an association between atherosclerosis and ambient air pollution. Given the leading role of cardiovascular disease as a cause of death and the large populations exposed to ambient PM2.5, these findings may be important and need further confirmation. PMID:15687058

One year online chemical speciation of submicron particulate matter (PM1) sampled at a French industrial and coastal site

NASA Astrophysics Data System (ADS)

Zhang, Shouwen; Riffault, Véronique; Dusanter, Sébastien; Augustin, Patrick; Fourmentin, Marc; Delbarre, Hervé

2015-04-01

The harbor of Dunkirk (Northern France) is surrounded by different industrial plants (metallurgy, petrochemistry, food processing, power plant, etc.), which emit gaseous and particulate pollutants such as Volatile Organic Compounds (VOCs), oxides of nitrogen (NOx) and sulfur (SO2), and submicron particles (PM1). These emissions are poorly characterized and their impact on neighboring urban areas has yet to be assessed. Studies are particularly needed in this type of complex environments to get a better understanding of PM1sources, especially from the industrial sector, their temporal variability, and their transformation. Several instruments, capable of real-time measurements (temporal resolution ≤ 30 min), were deployed at a site located downwind from the industrial area of Dunkirk for a one-year duration (July 2013-September 2014). An Aerosol Chemical Speciation Monitor (ACSM) and an Aethalometer monitored the main chemical species in the non-refractory submicron particles and black carbon, respectively. Concomitant measurements of trace gases and wind speed and direction were also performed. This dataset was analyzed considering four wind sectors, characteristics of marine, industrial, industrial-urban, and urban influences, and the different seasons. We will present a descriptive analysis of PM1, showing strong variations of ambient concentrations, as well as evidences of SO2 to SO4 gas-particle conversion when industrial plumes reached the monitoring site. The organic fraction measured by ACSM (37% of the total mass on average) was analyzed using a source-receptor model based on Positive Matrix Factorization (PMF) to identify chemical signatures of main emission sources and to quantify the contribution of each source to the PM1 budget given the wind sector. Four main factors were identified: hydrocarbon organic aerosol (HOA), oxygenated organic aerosol (OOA), biomass burning organic aerosol (BBOA) and cooking-like organic aerosol (COA). Overall, the total PM1 mass loading was dominated by secondary inorganic species and OOA. The seasonal variations of different identified factors will be discussed as well as the influence of ship emissions.

Exposure to long-term air pollution and road traffic noise in relation to cholesterol: A cross-sectional study.

PubMed

Sørensen, Mette; Hjortebjerg, Dorrit; Eriksen, Kirsten T; Ketzel, Matthias; Tjønneland, Anne; Overvad, Kim; Raaschou-Nielsen, Ole

2015-12-01

Exposure to traffic noise and air pollution have both been associated with cardiovascular disease, though the mechanisms behind are not yet clear. We aimed to investigate whether the two exposures were associated with levels of cholesterol in a cross-sectional design. In 1993–1997, 39,863 participants aged 50–64 year and living in the Greater Copenhagen area were enrolled in a population-based cohort study. For each participant, non-fasting total cholesterol was determined in whole blood samples on the day of enrolment. Residential addresses 5-years preceding enrolment were identified in a national register and road traffic noise (Lden) were modeled for all addresses. For air pollution, nitrogen dioxide (NO2) was modeled at all addresses using a dispersion model and PM2.5 was modeled at all enrolment addresses using a land-use regression model. Analyses were done using linear regression with adjustment for potential confounders as well as mutual adjustment for the three exposures. Baseline residential exposure to the interquartile range of road traffic noise,NO2 and PM2.5 was associated with a 0.58 mg/dl (95% confidence interval: −0.09; 1.25), a 0.68 mg/dl (0.22; 1.16) and a 0.78 mg/dl (0.22; 1.34) higher level of total cholesterol in single pollutant models, respectively. In two pollutant models with adjustment for noise in air pollution models and vice versa, the association between air pollution and cholesterol remained for both air pollution variables (NO2: 0.72 (0.11; 1.34); PM2.5: 0.70 (0.12; 1.28) mg/dl), whereas there was no association for noise (−0.08mg/dl). In three-pollutant models (NO2, PM2.5 and road traffic noise), estimates for NO2 and PM2.5 were slightly diminished (NO2: 0.58 (−0.05; 1.22); PM2.5: 0.57 (−0.02; 1.17) mg/dl). Air pollution and possibly also road traffic noise may be associated with slightly higher levels of cholesterol, though associations for the two exposures were difficult to separate.

Comparing Aerosol Retrievals from Ground-Based Instruments at the Impact-Pm Field Campaign

NASA Astrophysics Data System (ADS)

Kupinski, M.; Bradley, C. L.; Kalashnikova, O. V.; Xu, F.; Diner, D. J.; Clements, C. B.; Camacho, C.

2016-12-01

Detection of aerosol types, components having different size and chemical composition, over urban areas is important for understanding their impact on health and climate. In particular, sustained contact with size-differentiated airborne particulate matter: PM10 and PM2.5 can lead to adverse health effects such as asthma attacks, heart and lung diseases, and premature mortality. Multi-angular polarimetric measurements have been advocated in recent years as an additional tool to better understand and retrieve the aerosol properties needed for improved predictions of aerosol impart on air quality and climate. We deployed the ground-based Multiangle SpectroPolarimetric Imager (GroundMSPI) for accurate spectropolarimetric and radiance measurements co-located with the AERONET CIMEL sun photometer and a Halo Doppler 18 m resolution lidar from San José State University at the Garland-Fresno Air Quality supersite in Fresno, CA on July 7 during the Imaging Polarimetric Assessment and Characterization of Tropospheric Particulate Matter (ImPACT-PM) field experiment. GroundMSPI sampled the atmospheric scattering phase function in and 90 degrees out of the principal plane every 15 minutes in an automated manner, utilizing the 2-axis gimbal mount in elevation and azimuth. The goal of this work is verify atmospheric measurement of GroundMSPI with the coincident CIMEL sun photometer and ground-based lidar. Diffuse-sky radiance measurements of GroundMSPI are compared with the CIMEL sun photometer throughout the day. AERONET aerosol parameters such as size, shape, and index of refraction as well as lidar aerosol extinction profiles will be used in a forward radiative transfer model to compare with GroundMSPI observations and optimize these parameters to best match GroundMSPI data.

PM source identification at Sunland Park, New Mexico, using a simple heuristic meteorological and chemical analysis.

PubMed

Li, Wen-Whai; Cardenas, Nidia; Walton, John; Trujillo, David; Morales, Hugo; Arimoto, Richard

2005-03-01

The causes for evening low-wind PM10 and PM2.5 peaks at Sunland Park, NM, were investigated by using wind sector analysis and by assessing relationships between PM loadings and meteorological parameters through canonical ordination analysis. Both PM10 and PM2.5 concentrations during the evening hours accounted for approximately 50% of their respective 24-hr averages, and the PM10 was mainly composed of coarse material (PM10-2.5 amounted to 77% of PM10). A wind sector analysis based on data from three surface meteorological monitoring stations in the region narrowed the potential source region for PM10 and PM2.5 to an area within a few kilometers south of Sunland Park. Canonical ordination analysis confirmed that the peak frequently occurred under stable conditions with weak southerly winds. Chemical analyses of PM showed that elemental and organic carbon (EC and OC, respectively) dominate PM2.5 and inorganic elements dominate PM10-2.5. The combined data for EC/OC, geologic elements, and various trace elements indicate that under low wind and stable conditions, traffic-related PM emissions (motor vehicle exhausts and re-suspended road dust) from the south of the site are the most likely sources for the evening PM10 and PM2.5 peaks.

Low-carbon energy generates public health savings in California

NASA Astrophysics Data System (ADS)

Zapata, Christina B.; Yang, Chris; Yeh, Sonia; Ogden, Joan; Kleeman, Michael J.

2018-04-01

California's goal to reduce greenhouse gas (GHG) emissions to a level that is 80 % below 1990 levels by the year 2050 will require adoption of low-carbon energy sources across all economic sectors. In addition to reducing GHG emissions, shifting to fuels with lower carbon intensity will change concentrations of short-lived conventional air pollutants, including airborne particles with a diameter of less than 2.5 µm (PM2.5) and ozone (O3). Here we evaluate how business-as-usual (BAU) air pollution and public health in California will be transformed in the year 2050 through the adoption of low-carbon technologies, expanded electrification, and modified activity patterns within a low-carbon energy scenario (GHG-Step). Both the BAU and GHG-Step statewide emission scenarios were constructed using the energy-economic optimization model, CA-TIMES, that calculates the multi-sector energy portfolio that meets projected energy supply and demand at the lowest cost, while also satisfying scenario-specific GHG emissions constraints. Corresponding criteria pollutant emissions for each scenario were then spatially allocated at 4 km resolution to support air quality analysis in different regions of the state. Meteorological inputs for the year 2054 were generated under a Representative Concentration Pathway (RCP) 8.5 future climate. Annual-average PM2.5 and O3 concentrations were predicted using the modified emissions and meteorology inputs with a regional chemical transport model. In the final phase of the analysis, mortality (total deaths) and mortality rate (deaths per 100 000) were calculated using established exposure-response relationships from air pollution epidemiology combined with simulated annual-average PM2.5 and O3 exposure. Net emissions reductions across all sectors are -36 % for PM0.1 mass, -3.6 % for PM2.5 mass, -10.6 % for PM2.5 elemental carbon, -13.3 % for PM2.5 organic carbon, -13.7 % for NOx, and -27.5 % for NH3. Predicted deaths associated with air pollution in 2050 dropped by 24-26 % in California (1537-2758 avoided deaths yr-1) in the climate-friendly 2050 GHG-Step scenario, which is equivalent to a 54-56 % reduction in the air pollution mortality rate (deaths per 100 000) relative to 2010 levels. These avoided deaths have an estimated value of USD 11.4-20.4 billion yr-1 based on the present-day value of a statistical life (VSL) equal to USD 7.6 million. The costs for reducing California GHG emissions 80 % below 1990 levels by the year 2050 depend strongly on numerous external factors such as the global price of oil. Best estimates suggest that meeting an intermediate target (40 % reduction in GHG emissions by the year 2030) using a non-optimized scenario would reduce personal income by USD 4.95 billion yr-1 (-0.15 %) and lower overall state gross domestic product by USD 16.1 billion yr-1 (-0.45 %). The public health benefits described here are comparable to these cost estimates, making a compelling argument for the adoption of low-carbon energy in California, with implications for other regions in the United States and across the world.

The moving-window Bayesian maximum entropy framework: estimation of PM(2.5) yearly average concentration across the contiguous United States.

PubMed

Akita, Yasuyuki; Chen, Jiu-Chiuan; Serre, Marc L

2012-09-01

Geostatistical methods are widely used in estimating long-term exposures for epidemiological studies on air pollution, despite their limited capabilities to handle spatial non-stationarity over large geographic domains and the uncertainty associated with missing monitoring data. We developed a moving-window (MW) Bayesian maximum entropy (BME) method and applied this framework to estimate fine particulate matter (PM(2.5)) yearly average concentrations over the contiguous US. The MW approach accounts for the spatial non-stationarity, while the BME method rigorously processes the uncertainty associated with data missingness in the air-monitoring system. In the cross-validation analyses conducted on a set of randomly selected complete PM(2.5) data in 2003 and on simulated data with different degrees of missing data, we demonstrate that the MW approach alone leads to at least 17.8% reduction in mean square error (MSE) in estimating the yearly PM(2.5). Moreover, the MWBME method further reduces the MSE by 8.4-43.7%, with the proportion of incomplete data increased from 18.3% to 82.0%. The MWBME approach leads to significant reductions in estimation error and thus is recommended for epidemiological studies investigating the effect of long-term exposure to PM(2.5) across large geographical domains with expected spatial non-stationarity.

Spring maize yield, soil water use and water use efficiency under plastic film and straw mulches in the Loess Plateau

PubMed Central

Lin, Wen; Liu, Wenzhao; Xue, Qingwu

2016-01-01

To compare the soil water balance, yield and water use efficiency (WUE) of spring maize under different mulching types in the Loess Plateau, a 7-year field experiment was conducted in the Changwu region of the Loess Plateau. Three treatments were used in this experiment: straw mulch (SM), plastic film mulch (PM) and conventional covering without mulch (CK). Results show that the soil water change of dryland spring maize was as deep as 300 cm depth and hence 300 cm is recommended as the minimum depth when measure the soil water in this region. Water use (ET) did not differ significantly among the treatments. However, grain yield was significantly higher in PM compared with CK. WUE was significantly higher in PM than in CK for most years of the experiment. Although ET tended to be higher in PM than in the other treatments (without significance), the evaporation of water in the fallow period also decreased. Thus, PM is sustainable with respect to soil water balance. The 7-year experiment and the supplemental experiment thus confirmed that straw mulching at the seedling stage may lead to yield reduction and this effect can be mitigated by delaying the straw application to three-leaf stage. PMID:27976710

Evaluation of the temporal variations of air quality in Taipei City, Taiwan, from 1994 to 2003.

PubMed

Chang, Shuenn-Chin; Lee, Chung-Te

2008-03-01

Data collected from the five air-quality monitoring stations established by the Taiwan Environmental Protection Administration in Taipei City from 1994 to 2003 are analyzed to assess the temporal variations of air quality. Principal component analysis (PCA) is adopted to convert the original measuring pollutants into fewer independent components through linear combinations while still retaining the majority of the variance of the original data set. Two principal components (PCs) are retained together explaining 82.73% of the total variance. PC1, which represents primary pollutants such as CO, NO(x), and SO(2), shows an obvious decrease over the last 10 years. PC2, which represents secondary pollutants such as ozone, displays a yearly increase over the time period when a reduction of primary pollutants is obvious. In order to track down the control measures put forth by the authorities, 47 days of high PM(10) concentrations caused by transboundary transport have been eliminated in analyzing the long-term trend of PM(10) in Taipei City. The temporal variations over the past 10 years show that the moderate peak in O(3) demonstrates a significant upward trend even when the local primary pollutants have been well under control. Monthly variations of PC scores demonstrate that primary pollution is significant from January to April, while ozone increases from April to August. The results of the yearly variations of PC scores show that PM(10) has gradually shifted from a strong correlation with PC1 during the early years to become more related to PC2 in recent years. This implies that after a reduction of primary pollutants, the proportion of secondary aerosols in PM(10) may increase. Thus, reducing the precursor concentrations of secondary aerosols will be an effective way to lower PM(10) concentrations.

Yield Potential of Soil Water and Its Sustainability for Dryland Spring Maize with Plastic Film Mulch on the Loess Plateau

NASA Astrophysics Data System (ADS)

Lin, Wen; Liu, Wenzhao

2016-04-01

Plastic film mulch(PM) is an agronomic measure widely used in the dryland spring maize production system on the Loess Plateau of China. The measure can greatly increase yield of dryland maize due to its significant effects on soil water conservation. Few researches have been done to investigate how the yield potential is impacted by PM. The yield-water use (ET) boundary equation raised by French and Schultz provides a simple approach to calculate crop water limited yield potential and gives a benchmark for farmers in managing their crops. However, method used in building the equation is somewhat arbitrary and has no strict principle, which leads to the uncertainty of equation when it is applied. Though using PM can increase crop yield, it increases soil temperature, promotes crop growth and increases the water transpired by crop, which further leads to high water consumption as compared with crops without PM. This means that PM may lead to the overuse of soil water and hence is unsustainable in a long run. This research is mainly focused on the yield potential and sustainability of PMing for spring maize on the Loess Plateau. A principle that may be utilized by any other researchers was proposed based on French & Schultz's boundary equation and on part of quantile regression theory. We used a data set built by collecting the experimental data from published papers and analyzed the water-limited yield potential of spring maize on the Loess Plateau. Moreover, maize yield and soil water dynamics under PM were investigated by a long-term site field experiment. Results show that on the Loess Plateau, the water limited yield potential can be calculated using the boundary equation y = 60.5×(x - 50), with a platform yield of 15954 kghm-2 after the water use exceeds 314 mm. Without PMing, the water limited yield potential can be estimated by the boundary equation y = 47.5×(x - 62.3) , with a platform yield of 12840 kghm-2 when the water use exceeds 325 mm, which means PM can increase the yield potential of spring maize in water limited condition. From the result the field experiment, the grain yield under PM ranged from 6556 to 12615 kg/ha, being 803 to 3616 kg/hm-2 higher than no mulching (CK); and the WUE under plastic mulch ranged from 18.3 to 33.5 kghm-2mm-1, significantly higher than the CK in most of the experiment years (17.5-23.6 kghm-2mm-1). The ET for PM was higher than that of the CK (significance in 2009 and 2011), while it also increased the root biomass in soil, over consumed soil water and improved soil structure increased rainfall infiltration in fallow period. The result shows that the stored water by PM was 12 to 56 mm higher than the CK in the seven experiment years. So after seven years of cultivation, no significant difference was observed between treatments for the soil water storage in 0-6 m soil profile, which means that plastic film mulch can not only increase maize yield, but also is sustainable in the respect of soil water.

Factors relating to windblown dust in associations between ...

EPA Pesticide Factsheets

Introduction: In effect estimates of city-specific PM2.5-mortality associations across United States (US), there exists a substantial amount of spatial heterogeneity. Some of this heterogeneity may be due to mass distribution of PM; areas where PM2.5 is likely to be dominated by large size fractions (above 1 micron; e.g., the contribution of windblown dust), may have a weaker association with mortality. Methods: Log rate ratios (betas) for the PM2.5-mortality association—derived from a model adjusting for time, an interaction with age-group, day of week, and natural splines of current temperature, current dew point, and unconstrained temperature at lags 1, 2, and 3, for 313 core-based statistical areas (CBSA) and their metropolitan divisions (MD) over 1999-2005—were used as the outcome. Using inverse variance weighted linear regression, we examined change in log rate ratios in association with PM10-PM2.5 correlation as a marker of windblown dust/higher PM size fraction; linearity of associations was assessed in models using splines with knots at quintile values. Results: Weighted mean PM2.5 association (0.96 percent increase in total non-accidental mortality for a 10 ug/m3 increment in PM2.5) increased by 0.34 (95% confidence interval: 0.20, 0.48) per interquartile change (0.25) in the PM10-PM2.5 correlation, and explained approximately 8% of the observed heterogeneity; the association was linear based on spline analysis. Conclusions: Preliminary results pro

The Asymmetry Parameter and Branching Ratio of Sigma Plus Radiative Decay

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foucher, Maurice Emile

1992-05-01

We have measured the asymmetry parameter and branching ratio of themore » $$\\Sigma^+$$ radiative decay. This high statistics experiment (FNAL 761) was performed in the Proton Center charged hyperon beam at Fermi National Accelerator Laboratory in Batavia, Illinois. We find for the asymmetry parameter -0.720 $$\\pm$$ 0.086 $$\\pm$$ 0.045 where the first error is statistical and the second is systematic. This result is based on a sample of 34754 $$\\pm$$ 212 events. We find a preliminary value for the branching ratio $$Br ( \\Sigma^+ \\to p\\gamma )$$ $$/ Br ( \\Sigma^+ \\to p \\pi^0 )$$ = (2.14 $$\\pm$$ 0.07 $$\\pm$$ 0.11) x $$10^{-3}$$ where the first error is statistical and the second is systematic. This result is based on a sample of 31040 $$\\pm$$ 650 events. Both results are in agreement with previous low statistics measurements.« less

Stokes space modulation format classification based on non-iterative clustering algorithm for coherent optical receivers.

PubMed

Mai, Xiaofeng; Liu, Jie; Wu, Xiong; Zhang, Qun; Guo, Changjian; Yang, Yanfu; Li, Zhaohui

2017-02-06

A Stokes-space modulation format classification (MFC) technique is proposed for coherent optical receivers by using a non-iterative clustering algorithm. In the clustering algorithm, two simple parameters are calculated to help find the density peaks of the data points in Stokes space and no iteration is required. Correct MFC can be realized in numerical simulations among PM-QPSK, PM-8QAM, PM-16QAM, PM-32QAM and PM-64QAM signals within practical optical signal-to-noise ratio (OSNR) ranges. The performance of the proposed MFC algorithm is also compared with those of other schemes based on clustering algorithms. The simulation results show that good classification performance can be achieved using the proposed MFC scheme with moderate time complexity. Proof-of-concept experiments are finally implemented to demonstrate MFC among PM-QPSK/16QAM/64QAM signals, which confirm the feasibility of our proposed MFC scheme.

Particulate matter speciation profiles for light-duty gasoline vehicles in the United States.

PubMed

Sonntag, Darrell B; Baldauf, Richard W; Yanca, Catherine A; Fulper, Carl R

2014-05-01

Representative profiles for particulate matter particles less than or equal to 2.5 microm (PM2.5) are developed from the Kansas City Light-Duty Vehicle Emissions Study for use in the US. Environmental Protection Agency (EPA) vehicle emission model, the Motor Vehicle Emission Simulator (MOVES), and for inclusion in the EPA SPECIATE database for speciation profiles. The profiles are compatible with the inputs of current photochemical air quality models, including the Community Multiscale Air Quality Aerosol Module Version 6 (AE6). The composition of light-duty gasoline PM2.5 emissions differs significantly between cold start and hot stabilized running emissions, and between older and newer vehicles, reflecting both impacts of aging/deterioration and changes in vehicle technology. Fleet-average PM2.5 profiles are estimated for cold start and hot stabilized running emission processes. Fleet-average profiles are calculated to include emissions from deteriorated high-emitting vehicles that are expected to continue to contribute disproportionately to the fleet-wide PM2.5 emissions into the future. The profiles are calculated using a weighted average of the PM2.5 composition according to the contribution of PM2.5 emissions from each class of vehicles in the on-road gasoline fleet in the Kansas City Metropolitan Statistical Area. The paper introduces methods to exclude insignificant measurements, correct for organic carbon positive artifact, and control for contamination from the testing infrastructure in developing speciation profiles. The uncertainty of the PM2.5 species fraction in each profile is quantified using sampling survey analysis methods. The primary use of the profiles is to develop PM2.5 emissions inventories for the United States, but the profiles may also be used in source apportionment, atmospheric modeling, and exposure assessment, and as a basis for light-duty gasoline emission profiles for countries with limited data. PM2.5 speciation profiles were developed from a large sample of light-duty gasoline vehicles tested in the Kansas City area. Separate PM2.5 profiles represent cold start and hot stabilized running emission processes to distinguish important differences in chemical composition. Statistical analysis was used to construct profiles that represent PM2.5 emissions from the U.S. vehicle fleet based on vehicles tested from the 2005 calendar year Kansas City metropolitan area. The profiles have been incorporated into the EPA MOVES emissions model, as well as the EPA SPECIATE database, to improve emission inventories and provide the PM2.5 chemical characterization needed by CMAQv5.0 for atmospheric chemistry modeling.

Crosstalk of PmCBFs and PmDAMs Based on the Changes of Phytohormones under Seasonal Cold Stress in the Stem of Prunus mume

PubMed Central

Zhou, Yuzhen; Li, Yushu; Zhuo, Xiaokang; Ahmad, Sagheer; Han, Yu; Yong, Xue; Zhang, Qixiang

2018-01-01

Plants facing the seasonal variations always need a growth restraining mechanism when temperatures turn down. C-repeat binding factor (CBF) genes work essentially in the cold perception. Despite lots of researches on CBFs, the multiple crosstalk is still interesting on their interaction with hormones and dormancy-associated MADS (DAM) genes in the growth and dormancy control. Therefore, this study highlights roles of PmCBFs in cold-induced dormancy from different orgens. And a sense-response relationship between PmCBFs and PmDAMs is exhibited in this process, jointly regulated by six PmCBFs and PmDAM4–6. Meantime, GA3 and ABA showed negative and positive correlation with PmCBFs expression levels, respectively. We also find a high correlation between IAA and PmDAM1–3. Finally, we display the interaction mode of PmCBFs and PmDAMs, especially PmCBF1-PmDAM1. These results can disclose another view of molecular mechanism in plant growth between cold-response pathway and dormancy regulation together with genes and hormones. PMID:29360732

Which Triple Aim related measures are being used to evaluate population management initiatives? An international comparative analysis.

PubMed

Hendrikx, Roy J P; Drewes, Hanneke W; Spreeuwenberg, Marieke; Ruwaard, Dirk; Struijs, Jeroen N; Baan, Caroline A

2016-05-01

Population management (PM) initiatives are introduced in order to create sustainable health care systems. These initiatives should focus on the continuum of health and well-being of a population by introducing interventions that integrate various services. To be successful they should pursue the Triple Aim, i.e. simultaneously improve population health and quality of care while reducing costs per capita. This study explores how PM initiatives measure the Triple Aim in practice. An exploratory search was combined with expert consultations to identify relevant PM initiatives. These were analyzed based on general characteristics, utilized measures and related selection criteria. In total 865 measures were used by 20 PM initiatives. All quality of care domains were included by at least 11 PM initiatives, while most domains of population health and costs were included by less than 7 PM initiatives. Although their goals showed substantial overlap, the measures applied showed few similarities between PM initiatives and were predominantly selected based on local priority areas and data availability. Most PM initiatives do not measure the full scope of the Triple Aim. Additionally, variety between measures limits comparability between PM initiatives. Consensus on the coverage of Triple Aim domains and a set of standardized measures could further both the inclusion of the various domains as well as the comparability between PM initiatives. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

INTEGRATION OF SATELLITE, MODELED, AND GROUND BASED AEROSOL DATA FOR USE IN AIR QUALITY AND PUBLIC HEALTH APPLICATIONS ( AGU-BALTIMORE )

EPA Science Inventory

Within the next several years NOAA and EPA will begin to issue PM_2.5 air quality forecasts over the entire domain of the eastern United States, eventually extending to national coverage. These forecasts will provide continuous estimated values of particulate matter on ...

Assessing temporally and spatially resolved PM 2.5 exposures for epidemiological studies using satellite aerosol optical depth measurements

NASA Astrophysics Data System (ADS)

Kloog, Itai; Koutrakis, Petros; Coull, Brent A.; Lee, Hyung Joo; Schwartz, Joel

2011-11-01

Land use regression (LUR) models provide good estimates of spatially resolved long-term exposures, but are poor at capturing short term exposures. Satellite-derived Aerosol Optical Depth (AOD) measurements have the potential to provide spatio-temporally resolved predictions of both long and short term exposures, but previous studies have generally showed relatively low predictive power. Our objective was to extend our previous work on day-specific calibrations of AOD data using ground PM 2.5 measurements by incorporating commonly used LUR variables and meteorological variables, thus benefiting from both the spatial resolution from the LUR models and the spatio-temporal resolution from the satellite models. Later we use spatial smoothing to predict PM 2.5 concentrations for day/locations with missing AOD measures. We used mixed models with random slopes for day to calibrate AOD data for 2000-2008 across New-England with monitored PM 2.5 measurements. We then used a generalized additive mixed model with spatial smoothing to estimate PM 2.5 in location-day pairs with missing AOD, using regional measured PM 2.5, AOD values in neighboring cells, and land use. Finally, local (100 m) land use terms were used to model the difference between grid cell prediction and monitored value to capture very local traffic particles. Out-of-sample ten-fold cross-validation was used to quantify the accuracy of our predictions. For days with available AOD data we found high out-of-sample R2 (mean out-of-sample R2 = 0.830, year to year variation 0.725-0.904). For days without AOD values, our model performance was also excellent (mean out-of-sample R2 = 0.810, year to year variation 0.692-0.887). Importantly, these R2 are for daily, rather than monthly or yearly, values. Our model allows one to assess short term and long-term human exposures in order to investigate both the acute and chronic effects of ambient particles, respectively.