COMPARISON OF PM 2.5 AND PM 10 MONITORS

EPA Science Inventory

An extensive PM monitoring study was conducted during the 1998 Baltimore PM Epidemiology-Exposure Study of the Elderly. One goal was to investigate the mass concentration comparability between various monitoring instrumentation located across residential indoor, residential out...

Ischemic Heart Disease Incidence in Relation to Fine versus Total Particulate Matter Exposure in a U.S. Aluminum Industry Cohort

PubMed Central

Neophytou, Andreas M.; Noth, Elizabeth M.; Liu, Sa; Costello, Sadie; Hammond, S. Katharine; Cullen, Mark R.; Eisen, Ellen A.

2016-01-01

Ischemic heart disease (IHD) has been linked to exposures to airborne particles with an aerodynamic diameter <2.5 μm (PM2.5) in the ambient environment and in occupational settings. Routine industrial exposure monitoring, however, has traditionally focused on total particulate matter (TPM). To assess potential benefits of PM2.5 monitoring, we compared the exposure-response relationships between both PM2.5 and TPM and incidence of IHD in a cohort of active aluminum industry workers. To account for the presence of time varying confounding by health status we applied marginal structural Cox models in a cohort followed with medical claims data for IHD incidence from 1998 to 2012. Analyses were stratified by work process into smelters (n = 6,579) and fabrication (n = 7,432). Binary exposure was defined by the 10th-percentile cut-off from the respective TPM and PM2.5 exposure distributions for each work process. Hazard Ratios (HR) comparing always exposed above the exposure cut-off to always exposed below the cut-off were higher for PM2.5, with HRs of 1.70 (95% confidence interval (CI): 1.11–2.60) and 1.48 (95% CI: 1.02–2.13) in smelters and fabrication, respectively. For TPM, the HRs were 1.25 (95% CI: 0.89–1.77) and 1.25 (95% CI: 0.88–1.77) for smelters and fabrication respectively. Although TPM and PM2.5 were highly correlated in this work environment, results indicate that, consistent with biologic plausibility, PM2.5 is a stronger predictor of IHD risk than TPM. Cardiovascular risk management in the aluminum industry, and other similar work environments, could be better guided by exposure surveillance programs monitoring PM2.5. PMID:27249060

Evaluation of multisectional and two-section particulate matter photochemical grid models in the Western United States.

PubMed

Morris, Ralph; Koo, Bonyoung; Yarwood, Greg

2005-11-01

Version 4.10s of the comprehensive air-quality model with extensions (CAMx) photochemical grid model has been developed, which includes two options for representing particulate matter (PM) size distribution: (1) a two-section representation that consists of fine (PM2.5) and coarse (PM2.5-10) modes that has no interactions between the sections and assumes all of the secondary PM is fine; and (2) a multisectional representation that divides the PM size distribution into N sections (e.g., N = 10) and simulates the mass transfer between sections because of coagulation, accumulation, evaporation, and other processes. The model was applied to Southern California using the two-section and multisection representation of PM size distribution, and we found that allowing secondary PM to grow into the coarse mode had a substantial effect on PM concentration estimates. CAMx was then applied to the Western United States for the 1996 annual period with a 36-km grid resolution using both the two-section and multisection PM representation. The Community Multiscale Air Quality (CMAQ) and Regional Modeling for Aerosol and Deposition (REMSAD) models were also applied to the 1996 annual period. Similar model performance was exhibited by the four models across the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network monitoring networks. All four of the models exhibited fairly low annual bias for secondary PM sulfate and nitrate but with a winter overestimation and summer underestimation bias. The CAMx multisectional model estimated that coarse mode secondary sulfate and nitrate typically contribute <10% of the total sulfate and nitrate when averaged across the more rural IMPROVE monitoring network.

Field characterization of the PM2.5 Aerosol Chemical Speciation Monitor: insights into the composition, sources, and processes of fine particles in eastern China

NASA Astrophysics Data System (ADS)

Zhang, Yunjiang; Tang, Lili; Croteau, Philip L.; Favez, Olivier; Sun, Yele; Canagaratna, Manjula R.; Wang, Zhuang; Couvidat, Florian; Albinet, Alexandre; Zhang, Hongliang; Sciare, Jean; Prévôt, André S. H.; Jayne, John T.; Worsnop, Douglas R.

2017-12-01

A PM2.5-capable aerosol chemical speciation monitor (Q-ACSM) was deployed in urban Nanjing, China, for the first time to measure in situ non-refractory fine particle (NR-PM2.5) composition from 20 October to 19 November 2015, along with parallel measurements of submicron aerosol (PM1) species by a standard Q-ACSM. Our results show that the NR-PM2.5 species (organics, sulfate, nitrate, and ammonium) measured by the PM2.5-Q-ACSM are highly correlated (r2 > 0.9) with those measured by a Sunset Lab OC  /  EC analyzer and a Monitor for AeRosols and GAses (MARGA). The comparisons between the two Q-ACSMs illustrated similar temporal variations in all NR species between PM1 and PM2.5, yet substantial mass fractions of aerosol species were observed in the size range of 1-2.5 µm. On average, NR-PM1-2.5 contributed 53 % of the total NR-PM2.5, with sulfate and secondary organic aerosols (SOAs) being the two largest contributors (26 and 27 %, respectively). Positive matrix factorization of organic aerosol showed similar temporal variations in both primary and secondary OAs between PM1 and PM2.5, although the mass spectra were slightly different due to more thermal decomposition on the capture vaporizer of the PM2.5-Q-ACSM. We observed an enhancement of SOA under high relative humidity conditions, which is associated with simultaneous increases in aerosol pH, gas-phase species (NO2, SO2, and NH3) concentrations and aerosol water content driven by secondary inorganic aerosols. These results likely indicate an enhanced reactive uptake of SOA precursors upon aqueous particles. Therefore, reducing anthropogenic NOx, SO2, and NH3 emissions might not only reduce secondary inorganic aerosols but also the SOA burden during haze episodes in China.

The impact of emotion on prospective memory and monitoring: no pain, big gain.

PubMed

May, Cynthia; Owens, Max; Einstein, Gilles O

2012-12-01

The emotionally enhanced memory effect is robust across studies of retrospective memory, with heightened recall for items with emotional content (e.g., words like "murder") relative to neutral items (e.g., words like "envelope"). Only a handful of studies have examined the influence of emotion on prospective memory (PM), with mixed results. In some cases emotion enhances PM, and in others it impairs PM. Interpretation of these findings is clouded by methodological differences across studies and by the fact that, to date, no study has examined the impact of emotion on PM monitoring. In our study, we assessed PM performance when PM targets were neutral, negative, and positive, and also investigated monitoring across these different PM target types. Participants showed heightened PM performance for positive and negative relative to neutral targets, yet there was no evidence of additional monitoring for emotional targets. In fact, measures of monitoring were significantly reduced when the PM targets were emotional rather than neutral. Our findings suggest that it is possible to boost PM performance in a focal task using emotional cues, and that the use of emotional cues reduces the need for monitoring.

Comparative assessment of a real-time particle monitor against the reference gravimetric method for PM10 and PM2.5 in indoor air

NASA Astrophysics Data System (ADS)

Tasić, Viša; Jovašević-Stojanović, Milena; Vardoulakis, Sotiris; Milošević, Novica; Kovačević, Renata; Petrović, Jelena

2012-07-01

Accurate monitoring of indoor mass concentrations of particulate matter is very important for health risk assessment as people in developed countries spend approximately 90% of their time indoors. The direct reading, aerosol monitoring device, Turnkey, OSIRIS Particle Monitor (Model 2315) and the European reference low volume sampler, LVS3 (Sven/Leckel LVS3) with size-selective inlets for PM10 and PM2.5 fractions were used to assess the comparability of available optical and gravimetric methods for particulate matter characterization in indoor air. Simultaneous 24-hour samples were collected in an indoor environment for 60 sampling periods in the town of Bor, Serbia. The 24-hour mean PM10 levels from the OSIRIS monitor were well correlated with the LVS3 levels (R2 = 0.87) and did not show statistically significant bias. The 24-hour mean PM2.5 levels from the OSIRIS monitor were moderately correlated with the LVS3 levels (R2 = 0.71), but show statistically significant bias. The results suggest that the OSIRIS monitor provides sufficiently accurate measurements for PM10. The OSIRIS monitor underestimated the indoor PM10 concentrations by approximately 12%, relative to the reference LVS3 sampler. The accuracy of PM10 measurements could be further improved through empirical adjustment. For the fine fraction of particulate matter, PM2.5, it was found that the OSIRIS monitor underestimated indoor concentrations by approximately 63%, relative to the reference LVS3 sampler. This could lead to exposure misclassification in health effects studies relying on PM2.5 measurements collected with this instrument in indoor environments.

The strategic control of prospective memory monitoring in response to complex and probabilistic contextual cues.

PubMed

Bugg, Julie M; Ball, B Hunter

2017-07-01

Participants use simple contextual cues to reduce deployment of costly monitoring processes in contexts in which prospective memory (PM) targets are not expected. This study investigated whether this strategic monitoring pattern is observed in response to complex and probabilistic contextual cues. Participants performed a lexical decision task in which words or nonwords were presented in upper or lower locations on screen. The specific condition was informed that PM targets ("tor" syllable) would occur only in words in the upper location, whereas the nonspecific condition was informed that targets could occur in any location or word type. Context was blocked such that word type and location changed every 8 trials. In Experiment 1, the specific condition used the complex contextual cue to reduce monitoring in unexpected contexts relative to the nonspecific condition. This pattern largely was not evidenced when the complex contextual cue was probabilistic (Experiment 2). Experiment 3 confirmed that strategic monitoring is observed for a complex cue that is deterministic, but not one that is probabilistic. Additionally, Experiments 1 and 3 demonstrated a disadvantage associated with strategic monitoring-namely, that the specific condition was less likely to respond to a PM target in an unexpected context. Experiment 3 provided evidence that this disadvantage is attributable to impaired noticing of the target. The novel findings suggest use of a complex contextual cue per se is not a boundary condition for the strategic, context-specific allocation of monitoring processes to support prospective remembering; however, strategic monitoring is constrained by the predictive utility of the complex contextual cue.

40 CFR 63.11465 - What are the standards for new and existing sources?

Code of Federal Regulations, 2010 CFR

2010-07-01

... Metals Processing Area Sources Standards, Compliance, and Monitoring Requirements § 63.11465 What are the... through a fabric filter or baghouse that achieves a particulate matter (PM) control efficiency of at least... affected source through a fabric filter or baghouse that achieves a PM control efficiency of at least 99.5...

Apportionment of particulate matter sources in the Rio de Janeiro Metropolitan area

NASA Astrophysics Data System (ADS)

Gioda, A.; Mateus, V.; Ventura, L.; Amaral, B.

2013-05-01

Continuous monitoring of particulate matter (PM) is extremely important in order to observe possible trends and take measures to reduce emissions. In Brazil, few cities have network stations, which make these measurements even more crucial. Furthermore, there is a need to update and create new standards of air quality, which can only be done based on a suitable inventory. Levels of total suspended particles (TSP), PM10 and PM2.5 were monitored in the Metropolitan area of Rio de Janeiro. Mean concentrations of TSP, PM10 and PM2.5 were 70, 60 and 14 μg/m3, respectively. Some of the monitored sampling points exceeded the Brazilian guidelines for PM10 (50 μg/m3) and TSP (80 μg/m3). However, the PM2.5 levels measured in the present study are of extreme concern, since they exceeded the guideline suggested by the World Health Organization (WHO - 10 μg/m3) in almost all the study sites. The average PM2.5/PM10 ratios ranged from 0.1 to 0.3, being more dependent on traffic emissions, while PM10/PTS ratios ranged from 0.6 to 0.7. The particles were composed mainly of soil elements (~50%) and ammonium sulfate and ammonium nitrate (20-40%), which are recognized as secondary inorganic aerosols. Rural areas and sites near the ocean presented the lowest levels for all particle sizes. This is probably due to an enhanced dispersion of the particles by the sea breeze. On the other hand, higher PM concentrations were observed for the sites near industrial areas and heavy traffic, as expected. The monthly distribution profile observed for PM showed clear increases in PM levels from May to September at all stations. This increase is due to the stagnation of the air during winter, which is related to meteorological processes such as low relative humidity and low rainfall. Consequently, due to this stagnation pollutant concentrations show increases. According to the dataset from the Unified Health System there is a clear trend of increased hospitalizations for respiratory diseases in winter, when increased concentrations of PM are observed, which was verified in this study.

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.

The CCRUSH study: Characterization of coarse and fine particulate matter in northeastern Colorado

NASA Astrophysics Data System (ADS)

Clements, Nicholas Steven

Particulate matter in the troposphere adversely impacts human health when inhaled and alters climate through cloud formation processes and by absorbing/scattering light. Particles smaller than 2.5 mum in diameter (fine particulate matter; PM2.5), are typically emitted from combustion-related sources and can form and grow through secondary processing in the atmosphere. Coarse particles (PM10-2.5), ranging 2.5 to 10 mum, are typically generated through abrasive processes, such as erosion of road surfaces, entrained via resuspension, and settle quickly out of the atmosphere due to their large size. After deciding against regulating PM10-2.5 in 2006 citing, among other reasons, mixed results from epidemiological studies of the pollutant and lack of knowledge on health impacts in rural areas, the United States Environmental Protection Agency (US EPA) funded a series of studies that investigated the ambient composition, toxicology, and epidemiology of PM10-2.5. One such study, The Colorado Coarse Rural-Urban Sources and Health (CCRUSH) study, aimed to characterize the composition, sources, and health effects of PM10-2.5 in semi-arid northeastern Colorado and consisted of two field campaigns and an epidemiological study. Summarized here are the results from the two field campaigns, the first of which included over three years of continuous PM10-2.5 and PM2.5 mass concentration monitoring at multiple sites in urban-Denver and rural-Greeley, Colorado. This data set was used to characterize the spatiotemporal variability of PM10-2.5 and PM2.5. During the second year of continuous monitoring, PM 10-2.5 and PM2.5 filter samples were collected for compositional analyses that included: elemental composition, bulk elemental and organic carbon concentrations, water-soluble organic carbon concentrations, UV-vis absorbance, fluorescence spectroscopy, and endotoxin content. Elemental composition was used to understand enrichment of trace elements in atmospheric particles and to identify sources via positive matrix factorization (PMF). The organic fraction of both particulate size ranges was explored with a variety of bulk characterization techniques commonly utilized in analysis of soil and aquatic natural organic matter. To date, the CCRUSH study is one of the largest research efforts devoted to understanding PM10-2.5 and provides the US EPA with vital information that will be used in future policy making decisions regarding the regulation of this pollutant.

Distinct Neural Circuits Support Transient and Sustained Processes in Prospective Memory and Working Memory

PubMed Central

West, Robert; Braver, Todd

2009-01-01

Current theories are divided as to whether prospective memory (PM) involves primarily sustained processes such as strategic monitoring, or transient processes such as the retrieval of intentions from memory when a relevant cue is encountered. The current study examined the neural correlates of PM using a functional magnetic resonance imaging design that allows for the decomposition of brain activity into sustained and transient components. Performance of the PM task was primarily associated with sustained responses in a network including anterior prefrontal cortex (lateral Brodmann area 10), and these responses were dissociable from sustained responses associated with active maintenance in working memory. Additionally, the sustained responses in anterior prefrontal cortex correlated with faster response times for prospective responses. Prospective cues also elicited selective transient activity in a region of interest along the right middle temporal gyrus. The results support the conclusion that both sustained and transient processes contribute to efficient PM and provide novel constraints on the functional role of anterior PFC in higher-order cognition. PMID:18854581

Requirements for developing a regional monitoring capacity for aerosols in Europe within EMEP.

PubMed

Kahnert, Michael; Lazaridis, Mihalis; Tsyro, Svetlana; Torseth, Kjetil

2004-07-01

The European Monitoring and Evaluation Programme (EMEP) has been established to provide information to Parties to the Convention on Long Range Transboundary Air Pollution on deposition and concentration of air pollutants, as well as on the quantity and significance of long-range transmission of pollutants and transboundary fluxes. To achieve its objectives with the required scientific credibility and technical underpinning, a close integration of the programme's main elements is performed. These elements are emission inventories, chemical transport modelling, and the monitoring of atmospheric chemistry and deposition fluxes, which further are integrated towards abatement policy development. A critical element is the air pollution monitoring that is performed across Europe with a focus not only on health effect aspects and compliance monitoring, but also on process studies and source receptor relationships. Without a strong observational basis a predictive modelling capacity cannot be developed and validated. Thus the modelling success strongly depends on the quality and quantity of available observations. Particulate matter (PM) is a relatively recent addition to the EMEP monitoring programme, and the network for PM mass observations is still evolving. This article presents the current status of EMEP aerosol observations, followed by a critical evaluation in view of EMEP's main objectives and its model development requirements. Specific recommendations are given for improving the PM monitoring programme within EMEP.

Indoor PM1, PM2.5, PM10 and outdoor PM2.5 concentrations in primary schools in Sari, Iran.

PubMed

Mohammadyan, Mahmoud; Shabankhani, Bijan

2013-09-01

This study was carried out to determine the distribution of particles in classrooms in primary schools located in the centre of the city of Sari, Iran and identify the relationship between indoor classroom particle levels and outdoor PM2.5 concentrations. Outdoor PM2.5 and indoor PM1, PM2.5, and PM10 were monitored using a real-time Micro Dust Pro monitor and a GRIMM monitor, respectively. Both monitors were calibrated by gravimetric method using filters. The Kolmogorov-Smirnov test showed that all indoor and outdoor data fitted normal distribution. Mean indoor PM1, PM2.5, PM10 and outdoor PM2.5 concentrations for all of the classrooms were 17.6 μg m(-3), 46.6 μg m(-3), 400.9 μg m(-3), and 36.9 μg m(-3), respectively. The highest levels of indoor and outdoor PM2.5 concentrations were measured at the Shahed Boys School (69.1 μg m(-3) and 115.8 μg m(-3), respectively). The Kazemi school had the lowest levels of indoor and outdoor PM2.5 (29.1 μg m(-3) and 15.5 μg m(-3), respectively). In schools located near both main and small roads, the association between indoor fine particle (PM2.5 and PM1) and outdoor PM2.5 levels was stronger than that between indoor PM10 and outdoor PM2.5 levels. Mean indoor PM2.5 and PM10 and outdoor PM2.5 were higher than the standards for PM2.5 and PM10, and there was a good correlation between indoor and outdoor fine particle concentrations.

Field and laboratory comparison of PM10 instruments in high winds

NASA Astrophysics Data System (ADS)

Sharratt, Brenton; Pi, Huawei

2018-06-01

Instruments capable of measuring PM10 (particulate matter ≤10 μm in aerodynamic diameter) concentrations may vary in performance as a result of different technologies utilized in measuring PM10. Therefore, the performance of five instruments capable of measuring PM10 concentrations above eroding soil surfaces was tested during high wind events at field sites in the Columbia Plateau and inside a wind tunnel. Comparisons among the Big Spring Number Eight (BSNE) sampler, DustTrak monitor, E-sampler, High-Volume sampler, and Tapered Element Oscillating Microbalance (TEOM) monitor were made at field sites during nine wind erosion events and inside a wind tunnel at two wind speeds (7 and 12 m s-1) and two ambient PM10 concentrations (2 and 50 mg m-3). PM10 concentrations were similar for the High-Volume sampler and TEOM monitor as well as for the BSNE samplers and DustTrak monitors but higher for the High-Volume sampler and TEOM monitor than the E-sampler during field erosion events. Based upon wind tunnel experiments, the TEOM monitor measured the highest PM10 concentration while the DustTrak monitor typically measured the lowest PM10 concentration as compared with other instruments. In addition, PM10 concentration appeared to lower for all instruments at a wind speed of 12 as compared with 7 m s-1 inside the wind tunnel. Differences in the performance of instruments in measuring PM10 concentration poses risks in comparing PM10 concentration among different instrument types or using multiple instrument types to jointly measure concentrations in the field or laboratory or even the same instrument type subject to different wind speeds.

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.

Monitoring cure properties of out-of-autoclave BMI composites using IFPI sensor

NASA Astrophysics Data System (ADS)

Kaur, Amardeep; Anandan, Sudharshan; Yuan, Lei; Watkins, Steve E.; Chandrashekhara, K.; Xiao, Hai; Phan, Nam

2016-04-01

A non-destructive technique for inspection of a Bismaleimide (BMI) composite is presented using an optical fiber sensor. High performance BMI composites are used for Aerospace application for their mechanical strength. They are also used as an alternative to toughened epoxy resins. A femtosecond-laser-inscribed Intrinsic Fabry-Perot Interferometer (IFPI) sensor is used to perform real time cure monitoring of a BMI composite. The composite is cured using the out-of-autoclave (OOA) process. The IFPI sensor was used for in-situ monitoring; different curing stages are analyzed throughout the curing process. Temperature-induced-strain was measured to analyze the cure properties. The IFPI structure comprises of two reflecting mirrors inscribed on the core of the fiber using a femtosecond-laser manufacturing process. The manufacturing process makes the sensor thermally stable and robust for embedded applications. The sensor can withstand very high temperatures of up to 850 °C. The temperature and strain sensitivities of embedded IFPI sensor were measured to be 1.4 pm/μepsilon and 0.6 pm/μepsilon respectively.

Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

PubMed

Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

2017-08-01

Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM 2.5 is a promising way to fill the areas that are not covered by ground PM 2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM 2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM 2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R 2  = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM 2.5 estimates.

Integrated Process Monitoring based on Systems of Sensors for Enhanced Nuclear Safeguards Sensitivity and Robustness

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

Humberto E. Garcia

This paper illustrates safeguards benefits that process monitoring (PM) can have as a diversion deterrent and as a complementary safeguards measure to nuclear material accountancy (NMA). In order to infer the possible existence of proliferation-driven activities, the objective of NMA-based methods is often to statistically evaluate materials unaccounted for (MUF) computed by solving a given mass balance equation related to a material balance area (MBA) at every material balance period (MBP), a particular objective for a PM-based approach may be to statistically infer and evaluate anomalies unaccounted for (AUF) that may have occurred within a MBP. Although possibly being indicativemore » of proliferation-driven activities, the detection and tracking of anomaly patterns is not trivial because some executed events may be unobservable or unreliably observed as others. The proposed similarity between NMA- and PM-based approaches is important as performance metrics utilized for evaluating NMA-based methods, such as detection probability (DP) and false alarm probability (FAP), can also be applied for assessing PM-based safeguards solutions. To this end, AUF count estimates can be translated into significant quantity (SQ) equivalents that may have been diverted within a given MBP. A diversion alarm is reported if this mass estimate is greater than or equal to the selected value for alarm level (AL), appropriately chosen to optimize DP and FAP based on the particular characteristics of the monitored MBA, the sensors utilized, and the data processing method employed for integrating and analyzing collected measurements. To illustrate the application of the proposed PM approach, a protracted diversion of Pu in a waste stream was selected based on incomplete fuel dissolution in a dissolver unit operation, as this diversion scenario is considered to be problematic for detection using NMA-based methods alone. Results demonstrate benefits of conducting PM under a system-centric strategy that utilizes data collected from a system of sensors and that effectively exploits known characterizations of sensors and facility operations in order to significantly improve anomaly detection, reduce false alarm, and enhance assessment robustness under unreliable partial sensor information.« less

Community airborne particulate matter from mining for sand used as hydraulic fracturing proppant.

PubMed

Peters, Thomas M; O'Shaughnessy, Patrick T; Grant, Ryan; Altmaier, Ralph; Swanton, Elizabeth; Falk, Jeffrey; Osterberg, David; Parker, Edith; Wyland, Nancy G; Sousan, Sinan; Stark, Aimee Liz; Thorne, Peter S

2017-12-31

Field and laboratory studies were conducted to evaluate the impact of proppant sand mining and processing activities on community particulate matter (PM) concentrations. In field studies outside 17 homes within 800m of sand mining activities (mining, processing, and transport), respirable (PM 4 ) crystalline silica concentrations were low (<0.4μg/m 3 ) with crystalline silica detected on 7 samples (2% to 4% of mass). In long-term monitoring at 6 homes within 800m of sand mining activities, the highest daily mean PM concentrations observed were 14.5μg/m 3 for PM 2.5 and 37.3μg/m 3 for PM 10 , although infrequent (<3% of time), short-term elevated PM concentrations occurred when wind blew over the facility. In laboratory studies, aerosolized sand was shown to produce respirable-sized particles, containing 6% to 19% crystalline silica. Dispersion modeling of a mine and processing facility indicated that PM 10 can exceed standards short distances (<40m) beyond property lines. Lastly, fence-line PM and crystalline silica concentrations reported to state agencies were substantially below regulatory or guideline values, although several excursions were observed for PM 10 when winds blew over the facility. Taken together, community exposures to airborne particulate matter from proppant sand mining activities at sites similar to these appear to be unlikely to cause chronic adverse health conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Goal impact influences the evaluative component of performance monitoring: Evidence from ERPs.

PubMed

Severo, Mario Carlo; Walentowska, Wioleta; Moors, Agnes; Pourtois, Gilles

2017-10-01

Successful performance monitoring (PM) requires continuous assessment of context and action outcomes. Electrophysiological studies have reliably identified event-related potential (ERP) markers for evaluative feedback processing during PM: the Feedback-Related Negativity (FRN) and P3 components. The functional significance of FRN remains debated in the literature, with recent research suggesting that feedback's goal relevance can account for FRN (amplitude) modulation, apart from its valence or expectedness alone. Extending this account, the present study assessed whether graded differentiations in feedback's relevance or importance to one's goal (referred to as goal impact) would influence PM at the FRN (and P3) level. To this end, we ran a within-subject crossover design experiment in which 40 participants completed two standard cognitive control tasks (Go/No Go and Simon), while 64-channel electroencephalography was recorded. Critically, both tasks entailed similar reward processing but systematically varied in goal impact assignment (high vs. low), manipulated through their supposed diagnosticity for daily life functioning and activation of social comparison. ERP results showed that goal impact reliably modulated FRN in a general manner. Irrespective of feedback valence, it was overall less negative in the high compared to the low impact condition, suggesting a general decrease in feedback monitoring in the former compared to the latter condition. These findings lend support to the idea that PM is best conceived operating not solely based on motor cues, but is shaped by motivational demands. Copyright © 2017 Elsevier B.V. All rights reserved.

40 CFR 60.674 - Monitoring of operations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... compliance with the applicable PM concentration limit in Table 2 of this subpart. The revised visible... Mineral Processing Plants § 60.674 Monitoring of operations. (a) The owner or operator of any affected... repeat testing requirement specified in Table 3 of this subpart provided that the affected facility meets...

Focal/Nonfocal Cue Effects in Prospective Memory: Monitoring Difficulty or Different Retrieval Processes?

ERIC Educational Resources Information Center

Scullin, Michael K.; McDaniel, Mark A.; Shelton, Jill T.; Lee, Ji Hae

2010-01-01

We investigated whether focal/nonfocal effects (e.g., Einstein et al., 2005) in prospective memory (PM) are explained by cue differences in monitoring difficulty. In Experiment 1, we show that syllable cues (used in Einstein et al., 2005) are more difficult to monitor for than are word cues; however, initial-letter cues (in words) are similar in…

Overview of the Brooklyn traffic real-time ambient pollutant penetration and environmental dispersion (B-TRAPPED) study: theoretical background and model for design of field experiments.

PubMed

Hahn, Intaek; Wiener, Russell W; Richmond-Bryant, Jennifer; Brixey, Laurie A; Henkle, Stacy W

2009-12-01

The Brooklyn traffic real-time ambient pollutant penetration and environmental dispersion (B-TRAPPED) study was a multidisciplinary field research project that investigated the transport, dispersion, and infiltration processes of traffic emission particulate matter (PM) pollutants in a near-highway urban residential area. The urban PM transport, dispersion, and infiltration processes were described mathematically in a theoretical model that was constructed to develop the experimental objectives of the B-TRAPPED study. In the study, simultaneous and continuous time-series PM concentration and meteorological data collected at multiple outdoor and indoor monitoring locations were used to characterize both temporal and spatial patterns of the PM concentration movements within microscale distances (<500 m) from the highway. Objectives of the study included (1) characterizing the temporal and spatial PM concentration fluctuation and distribution patterns in the urban street canyon; (2) investigating the effects of urban structures such as a tall building or an intersection on the transport and dispersion of PM; (3) studying the influence of meteorological variables on the transport, dispersion, and infiltration processes; (4) characterizing the relationships between the building parameters and the infiltration mechanisms; (5) establishing a cause-and-effect relationship between outdoor-released PM and indoor PM concentrations and identifying the dominant mechanisms involved in the infiltration process; (6) evaluating the effectiveness of a shelter-in-place area for protection against outdoor-released PM pollutants; and (7) understanding the predominant airflow and pollutant dispersion patterns within the neighborhood using wind tunnel and CFD simulations. The 10 papers in this first set of papers presenting the results from the B-TRAPPED study address these objectives. This paper describes the theoretical background and models representing the interrelated processes of transport, dispersion, and infiltration. The theoretical solution for the relationship between the time-dependent indoor PM concentration and the initial PM concentration at the outdoor source was obtained. The theoretical models and solutions helped us to identify important parameters in the processes of transport, dispersion, and infiltration. The B-TRAPPED study field experiments were then designed to investigate these parameters in the hope of better understanding urban PM pollutant behaviors.

Retrieve Aerosol Concentration Based On Surface Model and Distribution of Concentration of PM2.5 ——A Case Study of Beijing

NASA Astrophysics Data System (ADS)

Cui, H.

2017-12-01

As China's economy continues to grow, urbanization continues to advance, along with growth in all areas to pollutant emissions in the air industry, air quality also continued to deteriorate. Aerosol concentrations as a measure of air quality of the most important part of are more and more people's attention. Traditional monitoring stations measuring aerosol concentration method is accurate, but time-consuming and can't be done simultaneously measure a large area, can only rely on data from several monitoring sites to predict the concentration of the panorama. Remote Sensing Technology retrieves aerosol concentrations being by virtue of their efficient, fast advantages gradually into sight. In this paper, by the method of surface model to start with the physical processes of atmospheric transport, innovative aerosol concentration coefficient proposed to replace the traditional aerosol concentrations, pushed to a set of retrieval of aerosol concentration coefficient method, enabling fast and efficient Get accurate air pollution target area. At the same paper also monitoring data for PM2.5 in Beijing were analyzed from different angles, from the perspective of the data summarized in Beijing PM2.5 concentration of time, space, geographical distribution and concentration of PM2.5 and explored the relationship between aerosol concentration coefficient and concentration of PM2.5.

Large Controlled Observational Study on Remote Monitoring of Pacemakers and Implantable Cardiac Defibrillators: A Clinical, Economic, and Organizational Evaluation.

PubMed

Dario, Claudio; Delise, Pietro; Gubian, Lorenzo; Saccavini, Claudio; Brandolino, Glauco; Mancin, Silvia

2016-01-13

Patients with implantable devices such as pacemakers (PMs) and implantable cardiac defibrillators (ICDs) should be followed up every 3-12 months, which traditionally required in-clinic visits. Innovative devices allow data transmission and technical or medical alerts to be sent from the patient's home to the physician (remote monitoring). A number of studies have shown its effectiveness in timely detection and management of both clinical and technical events, and endorsed its adoption. Unfortunately, in daily practice, remote monitoring has been implemented in uncoordinated and rather fragmented ways, calling for a more strategic approach. The objective of the study was to analyze the impact of remote monitoring for PM and ICD in a "real world" context compared with in-clinic follow-up. The evaluation focuses on how this service is carried out by Local Health Authorities, the impact on the cardiology unit and the health system, and organizational features promoting or hindering its effectiveness and efficiency. A multi-center, multi-vendor, controlled, observational, prospective study was conducted to analyze the impact of remote monitoring implementation. A total of 2101 patients were enrolled in the study: 1871 patients were followed through remote monitoring of PM/ICD (I-group) and 230 through in-clinic visits (U-group). The follow-up period was 12 months. In-clinic device follow-ups and cardiac visits were significantly lower in the I-group compared with the U-group, respectively: PM, I-group = 0.43, U-group = 1.07, P<.001; ICD, I-group = 0.98, U-group = 2.14, P<.001. PM, I-group = 0.37, U-group = 0.85, P<.001; ICD, I-group = 1.58, U-group = 1.69, P=.01. Hospitalizations for any cause were significantly lower in the I-group for PM patients only (I-group = 0.37, U-group = 0.50, P=.005). There were no significant differences regarding use of the emergency department for both PM and ICD patients. In the I-group, 0.30 (PM) and 0.37 (ICD) real clinical events per patient per year were detected within a mean (SD) time of 1.18 (2.08) days. Mean time spent by physicians to treat a patient was lower in the I-group compared to the U-group (-4.1 minutes PM; -13.7 minutes ICD). Organizational analysis showed that remote monitoring implementation was rather haphazard and fragmented. From a health care system perspective, the economic analysis showed statistically significant gains (P<.001) for the I-group using PM. This study contributes to build solid evidence regarding the usefulness of RM in detecting and managing clinical and technical events with limited use of manpower and other health care resources. To fully gain the benefits of RM of PM/ICD, it is vital that organizational processes be streamlined and standardized within an overarching strategy.

Large Controlled Observational Study on Remote Monitoring of Pacemakers and Implantable Cardiac Defibrillators: A Clinical, Economic, and Organizational Evaluation

PubMed Central

2016-01-01

Background Patients with implantable devices such as pacemakers (PMs) and implantable cardiac defibrillators (ICDs) should be followed up every 3–12 months, which traditionally required in-clinic visits. Innovative devices allow data transmission and technical or medical alerts to be sent from the patient's home to the physician (remote monitoring). A number of studies have shown its effectiveness in timely detection and management of both clinical and technical events, and endorsed its adoption. Unfortunately, in daily practice, remote monitoring has been implemented in uncoordinated and rather fragmented ways, calling for a more strategic approach. Objective The objective of the study was to analyze the impact of remote monitoring for PM and ICD in a “real world” context compared with in-clinic follow-up. The evaluation focuses on how this service is carried out by Local Health Authorities, the impact on the cardiology unit and the health system, and organizational features promoting or hindering its effectiveness and efficiency. Methods A multi-center, multi-vendor, controlled, observational, prospective study was conducted to analyze the impact of remote monitoring implementation. A total of 2101 patients were enrolled in the study: 1871 patients were followed through remote monitoring of PM/ICD (I-group) and 230 through in-clinic visits (U-group). The follow-up period was 12 months. Results In-clinic device follow-ups and cardiac visits were significantly lower in the I-group compared with the U-group, respectively: PM, I-group = 0.43, U-group = 1.07, P<.001; ICD, I-group = 0.98, U-group = 2.14, P<.001. PM, I-group = 0.37, U-group = 0.85, P<.001; ICD, I-group = 1.58, U-group = 1.69, P=.01. Hospitalizations for any cause were significantly lower in the I-group for PM patients only (I-group = 0.37, U-group = 0.50, P=.005). There were no significant differences regarding use of the emergency department for both PM and ICD patients. In the I-group, 0.30 (PM) and 0.37 (ICD) real clinical events per patient per year were detected within a mean (SD) time of 1.18 (2.08) days. Mean time spent by physicians to treat a patient was lower in the I-group compared to the U-group (-4.1 minutes PM; -13.7 minutes ICD). Organizational analysis showed that remote monitoring implementation was rather haphazard and fragmented. From a health care system perspective, the economic analysis showed statistically significant gains (P<.001) for the I-group using PM. Conclusions This study contributes to build solid evidence regarding the usefulness of RM in detecting and managing clinical and technical events with limited use of manpower and other health care resources. To fully gain the benefits of RM of PM/ICD, it is vital that organizational processes be streamlined and standardized within an overarching strategy. PMID:26764170

Prospective Memory in HIV-associated Neurocognitive Disorders (HAND): The Neuropsychological Dynamics of Time Monitoring

PubMed Central

Doyle, Katie L.; Loft, Shayne; Morgan, Erin E.; Weber, Erica; Cushman, Clint; Johnston, Elaine; Grant, Igor; Woods, Steven Paul

2013-01-01

Strategic monitoring during a delay interval is theorized to be an essential feature of time-based prospective memory (TB PM), the cognitive architecture of which is thought to rely heavily on frontostriatal systems and executive functions. This hypothesis was examined in 55 individuals with HIV-associated neurocognitive disorders (HAND) and 108 seronegative comparison participants who were administered the Memory for Intentions Screening Test (MIST), during which time monitoring (clock checking) behavior was measured. Results revealed a significant interaction between HAND group and the frequency of clock checking, in which individuals with HAND monitored checked the clock significantly less often than the comparison group across the TB PM retention intervals of the MIST. Subsequent analyses in the HAND sample revealed that the frequency of clocking checking was positively related to overall TB performance, as well as to standard clinical measures of retrospective memory and verbal fluency. These findings add support to a growing body of research elucidating TB PM’s reliance on strategic monitoring processes dependent upon intact frontostriatal systems. HIV-associated TB strategic time monitoring deficits may manifest in poorer functioning outcomes, including medication non-adherence and dependence in activities of daily living. Future research is needed to further delineate the cognitive mechanisms underlying strategic time monitoring in order to advise rehabilitation strategies for reducing HAND related TB PM deficits. PMID:23465043

Differential effects of emotional cues on components of prospective memory: an ERP study

PubMed Central

Cona, Giorgia; Kliegel, Matthias; Bisiacchi, Patrizia S.

2015-01-01

So far, little is known about the neurocognitive mechanisms associated with emotion effects on prospective memory (PM) performance. Thus, this study aimed at disentangling possible mechanisms for the effects of emotional valence of PM cues on the distinct phases composing PM by investigating event-related potentials (ERPs). Participants were engaged in an ongoing N-back task while being required to perform a PM task. The emotional valence of both the ongoing pictures and the PM cues was manipulated (pleasant, neutral, unpleasant). ERPs were recorded during the PM phases, such as encoding, maintenance, and retrieval of the intention. A recognition task including PM cues and ongoing stimuli was also performed at the end of the sessions. ERP results suggest that emotional PM cues not only trigger an automatic, bottom-up, capture of attention, but also boost a greater allocation of top-down processes. These processes seem to be recruited to hold attention toward the emotional stimuli and to retrieve the intention from memory, likely because of the motivational significance of the emotional stimuli. Moreover, pleasant PM cues seemed to modulate especially the prospective component, as revealed by changes in the amplitude of the ERP correlates of strategic monitoring as a function of the relevance of the valence for the PM task. Unpleasant pictures seemed to modulate especially the retrospective component, as revealed by the largest old/new effect being elicited by unpleasant PM pictures in the recognition task. PMID:25674061

A distributed network of low-cost continuous reading sensors to measure spatiotemporal variations of PM2.5 in Xi'an, China.

PubMed

Gao, Meiling; Cao, Junji; Seto, Edmund

2015-04-01

Fine particulate matter (PM2.5) is a growing public health concern especially in industrializing countries but existing monitoring networks are unable to properly characterize human exposures due to low resolution spatiotemporal data. Low-cost portable monitors can supplement existing networks in both developed and industrializing regions to increase density of sites and data. This study tests the performance of a low-cost sensor in high concentration urban environments. Seven Portable University of Washington Particle (PUWP) monitors were calibrated with optical and gravimetric PM2.5 reference monitors in Xi'an, China in December 2013. Pairwise correlations between the raw PUWP and the reference monitors were high (R(2) = 0.86-0.89). PUWP monitors were also simultaneously deployed at eight sites across Xi'an alongside gravimetric PM2.5 monitors (R(2) = 0.53). The PUWP monitors were able to identify the High-technology Zone site as a potential PM2.5 hotspot with sustained high concentrations compared to the city average throughout the day. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Assessment of the long-term impacts of PM10 and PM2.5 particles from construction works on surrounding areas.

PubMed

Azarmi, Farhad; Kumar, Prashant; Marsh, Daniel; Fuller, Gary

2016-02-01

Construction activities are common across cities; however, the studies assessing their contribution to airborne PM10 (≤10 μm) and PM2.5 (≤2.5 μm) particles on the surrounding air quality are limited. Herein, we assessed the impact of PM10 and PM2.5 arising from construction works in and around London. Measurements were carried out at 17 different monitoring stations around three construction sites between January 2002 and December 2013. Tapered element oscillating microbalance (TEOM 1400) and OSIRIS (2315) particle monitors were used to measure the PM10 and PM2.5 fractions in the 0.1-10 μm size range along with the ambient meteorological data. The data was analysed using bivariate concentration polar plots and k-means clustering techniques. Daily mean concentrations of PM10 were found to exceed the European Union target limit value of 50 μg m(-3) at 11 monitoring stations but remained within the allowable 35 exceedences per year, except at two monitoring stations. In general, construction works were found to influence the downwind concentrations of PM10 relatively more than PM2.5. Splitting of the data between working (0800-1800 h; local time) and non-working (1800-0800 h) periods showed about 2.2-fold higher concentrations of PM10 during working hours when compared with non-working hours. However, these observations did not allow to conclude that this increase was from the construction site emissions. Together, the polar concentration plots and the k-means cluster analysis applied to a pair of monitoring stations across the construction sites (i.e. one in upwind and the other in downwind) confirmed the contribution of construction sources on the measured concentrations. Furthermore, pairing the monitoring stations downwind of the construction sites showed a logarithmic decrease (with R(2) about 0.9) in the PM10 and PM2.5 concentration with distance. Our findings clearly indicate an impact of construction activities on the nearby downwind areas and a need for developing mitigation measures to limit their escape from the construction sites.

[Methodical problems of monitoring of fine particulate matters in atmospheric air of residential areas].

PubMed

Karelin, A O; Lomtev, A Yu; Mozzhukhina, N A; Yeremin, G B; Nikonov, V A

Inhalation of fine particulate matters (PM and PM ) poses a threat for the health of population. Purpose of the study the analysis of the monitoring of fine particulate matters in the atmospheric air of Saint-Petersburg and identification of the main problems of the monitoring. Research methods methods of scientific hypothetical deductive cognition, sanitary-statistical methods, general logical methods and approaches of researches: analysis, synthesis, abstracting, generalization, induction. Results. The article represents the analysis of the monitoring of fine particulate matters in the atmospheric air of Saint- Petersburg. Only 11 in automatic monitoring stations out of 22 there is carried out the control of fine particulate matters: in 7 - PM and PM, and in 4 - PM The average year concentrations were below MAC in all the stations. The maximum concentrations achieved 3 MAC, but the repeatance of cases of exceedence of concentrations more than MAC was very rare. On the average of the city concentrations of PM were decreased from 0,8 MAC in 2006 and 1,1 MAC in 2007 to 0,5 MAC in 2013-14. The executed analysis revealed main problems of the monitoring of fine particulate matters in the Russian Federation. They include the absence of the usage 1of the officially approved methods of controlling of PM and PM in the atmospheric air until March 1, 2016, lack of the modern equipment for measurement of fine particulate matters. Conclusions. Therefore, the state of the monitoring of fine particulate matters in the atmospheric air in the Russian Federation fails to be satisfactory. It is necessary to improve system of the monitoring, create modern Russian appliances, methods and means for measurement of fine particulate matters concentrations in the atmospheric air.

Development and Validation of a Collocated Exposure Monitoring Methodology using Portable Air Monitors

NASA Astrophysics Data System (ADS)

Li, Z.; Che, W.; Frey, H. C.; Lau, A. K. H.

2016-12-01

Portable air monitors are currently being developed and used to enable a move towards exposure monitoring as opposed to fixed site monitoring. Reliable methods are needed regarding capturing spatial and temporal variability in exposure concentration to obtain credible data from which to develop efficient exposure mitigation measures. However, there are few studies that quantify the validity and repeatability of the collected data. The objective of this study is to present and evaluate a collocated exposure monitoring (CEM) methodology including the calibration of portable air monitors against stationary reference equipment, side-by-side comparison of portable air monitors, personal or microenvironmental exposure monitoring and the processing and interpretation of the collected data. The CEM methodology was evaluated based on application to portable monitors TSI DustTrak II Aerosol Monitor 8530 for fine particulate matter (PM2.5) and TSI Q-Trak model 7575 with probe model 982 for CO, CO2, temperature and relative humidity. Taking a school sampling campaign in Hong Kong in January and June, 2015 as an example, the calibrated side-by-side measured 1 Hz PM2.5 concentrations showed good consistency between two sets of portable air monitors. Confidence in side-by-side comparison, PM2.5 concentrations of which most of the time were within 2 percent, enabled robust inference regarding differences when the monitors measured in classroom and pedestrian during school hour. The proposed CEM methodology can be widely applied in sampling campaigns with the objective of simultaneously characterizing pollutant concentrations in two or more locations or microenvironments. The further application of the CEM methodology to transportation exposure will be presented and discussed.

Development of a continuous monitoring system for PM10 and components of PM2.5.

PubMed

Lippmann, M; Xiong, J Q; Li, W

2000-01-01

While particulate matter with aerodynamic diameters below 10 and 2.5 microns (PM10 and PM2.5) correlate with excess mortality and morbidity, there is evidence for still closer epidemiological associations with sulfate ion, and experimental exposure-response studies suggest that the hydrogen ion and ultrafine (PM0.15) concentrations may be important risk factors. Also, there are measurement artifacts in current methods used to measure ambient PM10 and PM2.5, including negative artifacts because of losses of sampled semivolatile components (ammonium nitrate and some organics) and positive artifacts due to particle-bound water. To study such issues, we are developing a semi-continuous monitoring system for PM10, PM2.5, semivolatiles (organic compounds and NH4NO3), particle-bound water, and other PM2.5 constituents that may be causal factors. PM10 is aerodynamically sorted into three size-fractions: (1) coarse (PM10-PM2.5); (2) accumulation mode (PM2.5-PM0.15); and (3) ultrafine (PM0.15). The mass concentration of each fraction is measured in terms of the linear relation between accumulated mass and pressure drop on polycarbonate pore filters. The PM0.15 mass, being highly correlated with the ultrafine number concentration, provides a good index of the total number concentration in ambient air. For the accumulation mode (PM2.5-PM0.15), which contains nearly all of the semivolatiles and particle-bound water by mass, aliquots of the aerosol stream flow into system components that continuously monitor sulfur (by flame photometry), ammonium and nitrate (by chemiluminescence following catalytic transformations to NO), organics (by thermal-optical analysis) and particle-bound water (by electrolytic hygrometer after vacuum evaporation of sampled particles). The concentration of H+ can be calculated (by ion balance using the monitoring data on NO3-, NH4+, and SO4=).

Indoor, outdoor, and personal exposure monitoring of particulate air pollution: the Baltimore elderly epidemiology-exposure pilot study

NASA Astrophysics Data System (ADS)

Williams, Ron; Creason, John; Zweidinger, Roy; Watts, Randall; Sheldon, Linda; Shy, Carl

A 17-day pilot study investigating potential PM exposures of an elderly population was conducted near Baltimore, Maryland. Collection of residential indoor, residential outdoor, and ambient monitoring data associated with the subjects living at a common retirement facility was integrated with results from a paired epidemiological pilot study. This integration was used to investigate the potential pathophysiological health effects resulting from daily changes in estimated PM exposures with results reported elsewhere. Objectives of the exposure study were to determine the feasibility of performing PM exposure assessment upon an elderly population and establishing relationships between the various exposure measures including personal monitoring. PM 2.5 was determined to be the dominant outdoor size fraction (0.83 PM 2.5/PM 10 mass ratio by dichot monitoring). Individual 24-h PM 1.5 personal exposures ranged from 12 to 58 μg m -3. Comparison of data from matched sampling dates resulted in mean daily PM 1.5 personal, PM 2.5 outdoor, and PM 1.5 indoor concentrations of 34, 17, and 17 μg m -3, respectively. Activity patterns of the study population indicated a generally sedentary population spending a mean of 96% of each day indoors. Future studies would benefit from the use of a consistent sampling methodology across a larger number of PM measurement sites relevant to the elderly subjects, as well as a larger personal PM exposure study population to more successfully collect data needed in matched epidemiological-exposure studies.

Assessment of background particulate matter concentrations in small cities and rural locations--Prince George, Canada.

PubMed

Veira, Andreas; Jackson, Peter L; Ainslie, Bruce; Fudge, Dennis

2013-07-01

This study investigates the development and application of a simple method to calculate annual and seasonal PM2.5 and PM10 background concentrations in small cities and rural areas. The Low Pollution Sectors and Conditions (LPSC) method is based on existing measured long-term data sets and is designed for locations where particulate matter (PM) monitors are only influenced by local anthropogenic emission sources from particular wind sectors. The LPSC method combines the analysis of measured hourly meteorological data, PM concentrations, and geographical emission source distributions. PM background levels emerge from measured data for specific wind conditions, where air parcel trajectories measured at a monitoring station are assumed to have passed over geographic sectors with negligible local emissions. Seasonal and annual background levels were estimated for two monitoring stations in Prince George, Canada, and the method was also applied to four other small cities (Burns Lake, Houston, Quesnel, Smithers) in northern British Columbia. The analysis showed reasonable background concentrations for both monitoring stations in Prince George, whereas annual PM10 background concentrations at two of the other locations and PM2.5 background concentrations at one other location were implausibly high. For those locations where the LPSC method was successful, annual background levels ranged between 1.8 +/- 0.1 microg/m3 and 2.5 +/- 0.1 microg/m3 for PM2.5 and between 6.3 +/- 0.3 microg/m3 and 8.5 +/- 0.3 microg/m3 for PM10. Precipitation effects and patterns of seasonal variability in the estimated background concentrations were detectable for all locations where the method was successful. Overall the method was dependent on the configuration of local geography and sources with respect to the monitoring location, and may fail at some locations and under some conditions. Where applicable, the LPSC method can provide a fast and cost-efficient way to estimate background PM concentrations for small cities in sparsely populated regions like northern British Columbia. In rural areas like northern British Columbia, particulate matter (PM) monitoring stations are usually located close to emission sources and residential areas in order to assess the PM impact on human health. Thus there is a lack of accurate PM background concentration data that represent PM ambient concentrations in the absence of local emissions. The background calculation method developed in this study uses observed meteorological data as well as local source emission locations and provides annual, seasonal and precipitation-related PM background concentrations that are comparable to literature values for four out of six monitoring stations.

A candidate framework for PM2.5 source identification in highly industrialized urban-coastal areas

NASA Astrophysics Data System (ADS)

Mateus, Vinícius Lionel; Gioda, Adriana

2017-09-01

The variability of PM sources and composition impose tremendous challenges for police makers in order to establish guidelines. In urban PM, sources associated with industrial processes are among the most important ones. In this study, a 5-year monitoring of PM2.5 samples was carried out in an industrial district. Their chemical composition was strategically determined in two campaigns in order to check the effectiveness of mitigation policies. Gaseous pollutants (NO2, SO2, and O3) were also monitored along with meteorological variables. The new method called Conditional Bivariate Probability Function (CBPF) was successfully applied to allocate the observed concentration of criteria pollutants (gaseous pollutants and PM2.5) in cells defined by wind direction-speed which provided insights about ground-level and elevated pollution plumes. CBPF findings were confirmed by the Theil-Sen long trend estimations for criteria pollutants. By means of CBPF, elevated pollution plumes were detected in the range of 0.54-5.8 μg m-3 coming from a direction associated to stacks. With high interpretability, the use of Conditional Inference Trees (CIT) provided both classification and regression of the speciated PM2.5 in the two campaigns. The combination of CIT and Random Forests (RF) point out NO3- and Ca+2 as important predictors for PM2.5. The latter predictor mostly associated to non-sea-salt sources, given a nss-Ca2+ contribution equal to 96%.

2018 PM 2.5 Exceedances | Fine Particulate | New England ...

EPA Pesticide Factsheets

2018-06-11

Exceedances of the 35.5 ug/m3 24-hour average PM 2.5 standard and the dates they occurred for each continuous PM 2.5 monitor in New England. Data from these monitors are not used for official purposes such as determining if an areas meets the PM 2.5 standard. All data are preliminary and subject to change.

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.

An estimated method of visibility for a remote sensing system based on LabVIEW and Arduino

NASA Astrophysics Data System (ADS)

Chen, Xiaochuan; Ruan, Chi; Zheng, Hairong

2017-02-01

Visibility data have long needed to traffic meteorological monitoring and warning system, but visibility data have monitored with expensive special equipment. Visibility degradation in fog is due to the light scattering of fog droplets, which are transit from aerosols via activation. Considering strong correlation between PM2.5 (Particulate matter with diameters less than 2.5μm) mass concentration and visibility, regression models can be useful tools for retrieving visibility data from available PM2.5 data. In this study, PM2.5 is measured by low cost and commercial equipment. The results of experiment indicate that relative humidity is the key factor to impact accuracy correlation between PM2.5 and visibility, the strongest correlation locates in the RH (<60%). Results of the studies suggest that visibility decreases with increases of PM2.5 mass concentration; however, it has been found the decrease rate tapers off gradually. In order to capture the real-time visibility data, to grasp the process of low visibility events, the design of remote monitoring system is put forward. Using the GPRS network to link to cloud as a server, proposed the Arduino as the controller, design and implements a wireless serial acquisition and control system based LabVIEW and Arduino, this system can achieve the function of real-time synchronization Web publishing. The result of the test indicates that this system has typical characteristics of friendly interface, high levels of reliability and expansibility, moreover it can retrieve visibility data from available PM2.5 data that can easy to access by low-cost sensor along the highway.

Different relationships between personal exposure and ambient concentration by particle size.

PubMed

Guak, Sooyoung; Lee, Kiyoung

2018-04-06

Ambient particulate matter (PM) concentrations at monitoring stations were often used as an indicator of population exposure to PM in epidemiological studies. The correlation between personal exposure and ambient concentrations of PM varied because of diverse time-activity patterns. The aim of this study was to determine the relationship between personal exposure and ambient concentrations of PM 10 and PM 2.5 with minimal impact of time-activity pattern on personal exposure. Performance of the MicroPEM, v3.2 was evaluated by collocation with central ambient air monitors for PM 10 and PM 2.5 . A field technician repeatedly conducted measurement of 24 h personal exposures to PM 10 and PM 2.5 with a fixed time-activity pattern of office worker over 26 days in Seoul, Korea. The relationship between the MicroPEM and the ambient air monitor showed good linearity. Personal exposure and ambient concentrations of PM 2.5 were highly correlated with a fixed time-activity pattern compared with PM 10 . The finding implied a high infiltration rate of PM 2.5 and low infiltration rate of PM 10 . The relationship between personal exposure and ambient concentrations of PM 10 and PM 2.5 was different for high level episodes. In the Asian dust episode, staying indoors could reduce personal exposure to PM 10 . However, personal exposure to PM 2.5 could not be reduced by staying indoors during the fine dust advisory episode.

Assessing the impact of fine particulate matter (PM2.5) on ...

EPA Pesticide Factsheets

An enhanced research paradigm is presented to address the spatial and temporal gaps in fine particulate matter (PM2.5) measurements and generate realistic and representative concentration fields for use in epidemiological studies of human exposure to ambient air particulate concentrations. The general approach for research designed to analyze health impacts of exposure to PM2.5 is to use concentration data from the nearest ground-based air quality monitor(s), which typically have missing data on the temporal and spatial scales due to filter sampling schedules and monitor placement, respectively. To circumvent these data gaps, this research project uses a Hierarchical Bayesian Model (HBM) to generate estimates of PM2.5 in areas with and without air quality monitors by combining PM2.5 concentrations measured by monitors, PM2.5 concentration estimates derived from satellite aerosol optical depth (AOD) data, and Community-Multiscale Air Quality (CMAQ) model predictions of PM2.5 concentrations. This methodology represents a substantial step forward in the approach for developing representative PM2.5 concentration datasets to correlate with inpatient hospitalizations and emergency room visits data for asthma and inpatient hospitalizations for myocardial infarction (MI) and heart failure (HF) using case-crossover analysis. There were two key objective of this current study. First was to show that the inputs to the HBM could be expanded to include AOD data in addition t

Outdoor near-roadway, community and residential pollen, carbon dioxide and particulate matter measurements in the urban core of an agricultural region in central CA

NASA Astrophysics Data System (ADS)

Shendell, Derek G.; Therkorn, Jennifer H.; Yamamoto, Naomichi; Meng, Qingyu; Kelly, Sarah W.; Foster, Christine A.

2012-04-01

We can control asthma through proper clinical and environmental management and education. The U.S. population is growing, urbanizing and aging; seniors of low-to-middle income families are working and living longer. We conducted community-based participatory research in Visalia, Tulare County, California with a prospective, cross-sectional repeated measures design and quantitative and qualitative process; home environment and health-related outcomes data were collected. In this paper, we presented results of the air quality sampling-pollen, carbon dioxide (CO2) and particulate matter (PM) outdoors away from most major sources (agricultural fields, large pollinating trees, etc)-at a community central site close to a mobile line source and participant homes in the cooling season, July, 2009. Weather was hot and dry with light winds; diurnal variation ranged between 65-107 °F (18-42 °C) and 12-76% relative humidity at the study's central site. Co-located active (reference) and passive (PAAS) samplers were used for pollen; passive monitoring for CO2 (Telaire 7001) and active sampling for PM were conducted. Overall, we observed spatial variability in CO2, fine PM (PM2.5), and pollen counts. Weekday and study week average CO2 and PM2.5 concentrations were higher near study homes compared to central site sampling points, but peak measures and overnight/pre-dawn time period averages were elevated at the central site. Pollen counts were typically lower at homes-even if grass, trees, flowers or potted plants were present-compared to the central site closer to and generally downwind from commercial agricultural tree production. Data are new; the nine-county San Joaquin Valley has one pollen count station in the national network, and two of four government outdoor air monitoring stations in the county are in national parks. We suggest-given poor air quality in large part due to PM-adding routine pollen counts to regional/state agency air monitoring sites and more CO2 and PM monitoring.

75 FR 68329 - Meeting of the Defense Audit Advisory Committee (DAAC)

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-05

... DEPARTMENT OF DEFENSE Office of the Secretary Meeting of the Defense Audit Advisory Committee... Defense Audit Advisory Committee will be held. DATES: Monday, November 22, 2010 beginning at 3 p.m. and... of internal controls, audit processes, and processes for monitoring compliance with relevant laws and...

ASSESSMENT OF OUTDOOR, INDOOR, AND PERSONAL PM CONCENTRATION DIFFERENCES BY CONTINUOUS MONITORING

EPA Science Inventory

Many sources and factors affect the particle concentrations inside a home, often causing indoor PM concentrations to be higher than outdoors. Furthermore, daytime personal PM exposures are, on average, 50% higher than that indicated by stationary monitoring. The increased conce...

77 FR 28782 - Approval and Promulgation of Air Quality Implementation Plans; Delaware, New Jersey, and...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-16

...EPA is making two determinations regarding the Philadelphia- Wilmington, PA-NJ-DE fine particulate (PM2.5) nonattainment area (the Philadelphia Area). First, EPA is making a determination that the Philadelphia Area has attained the 1997 annual PM2.5 national ambient air quality standard (NAAQS) by its attainment date of April 5, 2010. This determination is based upon quality assured and certified ambient air monitoring data that show the area monitored attainment of the 1997 annual PM2.5 NAAQS for the 2007-2009 monitoring period. Second, EPA is making a clean data determination, finding that the Philadelphia Area has attained the 1997 PM2.5 NAAQS, based on quality assured and certified ambient air monitoring data for the 2007-2009 and 2008-2010 monitoring periods. In accordance with EPA's applicable PM2.5 implementation rule, this determination suspends the requirement for the Philadelphia Area to submit an attainment demonstration, reasonably available control measures/reasonably available control technology (RACM/RACT), a reasonable further progress (RFP) plan, and contingency measures related to attainment of the 1997 annual PM2.5 NAAQS for so long as the area continues to attain the 1997 annual PM2.5 NAAQS. These actions are being taken under the Clean Air Act (CAA).

Equating Semi-Continuous (SC) PM2.5 Mass Monitor Measurement Values with Federal Reference Method (FRM) PM2.5 Monitor Measurement Values

EPA Science Inventory

The effects of fine particulate matter (PM_2.5) on human health are well documented (Pope et al., 2002). In order to spatially and temporally assess the impact of PM_2.5 on the U.S. population, the U.S. Environmental Protection Agency (U.S. EPA) operates a ne...

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.

Wintertime vertical variations in particulate matter (PM) and precursor concentrations in the San Joaquin Valley during the California Regional Coarse PM/Fine PM Air Quality Study.

PubMed

Brown, Steven G; Roberts, Paul T; McCarthy, Michael C; Lurmann, Frederick W; Hyslop, Nicole P

2006-09-01

Air quality monitoring was conducted at a rural site with a tower in the middle of California's San Joaquin Valley (SJV) and at elevated sites in the foothills and mountains surrounding the SJV for the California Regional PM10/ PM2.5 Air Quality Study. Measurements at the surface and n a tower at 90 m were collected in Angiola, CA, from December 2000 through February 2001 and included hourly black carbon (BC), particle counts from optical particle counters, nitric oxide, ozone, temperature, relative humidity, wind speed, and direction. Boundary site measurements were made primarily using 24-hr integrated particulate matter (PM) samples. These measurements were used to understand the vertical variations of PM and PM precursors, the effect of stratification in the winter on concentrations and chemistry aloft and at the surface, and the impact of aloft-versus-surface transport on PM concentrations. Vertical variations of concentrations differed among individual species. The stratification may be important to atmospheric chemistry processes, particularly nighttime nitrate formation aloft, because NO2 appeared to be oxidized by ozone in the stratified aloft layer. Additionally, increases in accumulation-mode particle concentrations in the aloft layer during a fine PM (PM2.5) episode corresponded with increases in aloft nitrate, demonstrating the likelihood of an aloft nighttime nitrate formation mechanism. Evidence of local transport at the surface and regional transport aloft was found; transport processes also varied among the species. The distribution of BC appeared to be regional, and BC was often uniformly mixed vertically. Overall, the combination of time-resolved tower and surface measurements provided important insight into PM stratification, formation, and transport.

NodePM: A Remote Monitoring Alert System for Energy Consumption Using Probabilistic Techniques

PubMed Central

Filho, Geraldo P. R.; Ueyama, Jó; Villas, Leandro A.; Pinto, Alex R.; Gonçalves, Vinícius P.; Pessin, Gustavo; Pazzi, Richard W.; Braun, Torsten

2014-01-01

In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out. PMID:24399157

Performance management of the public healthcare services in Ireland: a review.

PubMed

Mesabbah, Mohammed; Arisha, Amr

2016-01-01

Performance Management (PM) processes have become a potent part of strategic and service quality decisions in healthcare organisations. In 2005, the management of public healthcare in Ireland was amalgamated into a single integrated management body, named the Health Service Executive (HSE). Since then, the HSE has come up with a range of strategies for healthcare developments and reforms, and has developed a PM system as part of its strategic planning. The purpose of this paper is to review the application of PM in the Irish Healthcare system, with a particular focus on Irish Hospitals and Emergency Services. An extensive review of relevant HSE's publications from 2005 to 2013 is conducted. Studies of the relevant literature related to the application of PM and of international best practices in healthcare performance systems are also presented. PM and performance measurement systems used by the HSE include many performance reports designed to monitor performance trends and strategic goals. Issues in the current PM system include inconsistency of measures and performance reporting, unclear strategy alignment, and deficiencies in reporting (e.g. feedback and corrective actions). Furthermore, PM processes have not been linked adequately into Irish public hospitals' management systems. The HSE delivers several services such as mental health, social inclusion, etc. This study focuses on the HSE's PM framework, with a particular interest in acute hospitals and emergency services. This is the first comprehensive review of Irish healthcare PM since the introduction of the HSE. A critical analysis of the HSE reports identifies the shortcomings in its current PM system.

Influence of sea-land breezes on the tempospatial distribution of atmospheric aerosols over coastal region.

PubMed

Tsai, Hsieh-Hung; Yuan, Chung-Shin; Hung, Chung-Hsuang; Lin, Chitsan; Lin, Yuan-Chung

2011-04-01

The influence of sea-land breezes (SLBs) on the spatial distribution and temporal variation of particulate matter (PM) in the atmosphere was investigated over coastal Taiwan. PM was simultaneously sampled at inland and offshore locations during three intensive sampling periods. The intensive PM sampling protocol was continuously conducted over a 48-hr period. During this time, PM2.5 and PM(2.5-10) (PM with aerodynamic diameters < 2.5 microm and between 2.5 and 10 microm, respectively) were simultaneously measured with dichotomous samplers at four sites (two inland and two offshore sites) and PM10 (PM with aerodynamic diameters < or =10 microm) was measured with beta-ray monitors at these same 4 sites and at 10 sites of the Taiwan Air Quality Monitoring Network. PM sampling on a mobile air quality monitoring boat was further conducted along the coastline to collect offshore PM using a beta-ray monitor and a dichotomous sampler. Data obtained from the inland sites (n=12) and offshore sites (n=2) were applied to plot the PM10 concentration contour using Surfer software. This study also used a three-dimensional meteorological model (Pennsylvania State University/National Center for Atmospheric Research Meteorological Model 5) and the Comprehensive Air Quality Model with Extensions to simulate surface wind fields and spatial distribution of PM10 over the coastal region during the intensive sampling periods. Spatial distribution of PM10 concentration was further used in investigating the influence of SLBs on the transport of PM10 over the coastal region. Field measurement and model simulation results showed that PM10 was transported back and forth across the coastline. In particular, a high PM10 concentration was observed at the inland sites during the day because of sea breezes, whereas a high PM10 concentration was detected offshore at night because of land breezes. This study revealed that the accumulation of PM in the near-ocean region because of SLBs influenced the tempospatial distribution of PM10 over the coastal region.

Near-Surface PM2.5 Concentrations Derived from Satellites, Simulation and Ground Monitors

NASA Astrophysics Data System (ADS)

van Donkelaar, A.; Martin, R.; Hsu, N. Y. C.; Kahn, R. A.; Levy, R. C.; Lyapustin, A.; Sayer, A. M.; Brauer, M.

2015-12-01

Exposure to fine particulate matter (PM2.5) is globally associated with 3.2 million premature deaths annually. Satellite retrievals of total column aerosol optical depth (AOD) from instruments such as MODIS, MISR and SeaWiFS are related to PM2.5 through local aerosol vertical profiles and optical properties. A globally applicable and geophysically-based AOD to PM2.5 relationship can be calculated from chemical transport model (CTM) simulations. This approach, while effective, ignores the wealth of ground monitoring data that exist in some regions of the world. We therefore use ground monitors to develop a geographically weighted regression (GWR) that predicts the residual bias in geophysically-based satellite-derived PM2.5. Predictors such as the AOD to PM2.5 relationship resolution, land cover type, and chemical composition are used to predict this bias, which can then be used to improve the initial PM2.5 estimates. This approach not only allows for direct bias correction, but also provides insight into factors biasing the initial CTM-derived AOD to PM2.5 relationship. Over North America, we find significant improvement in bias-corrected PM2.5 (r2=0.82 versus r2=0.62), with evidence that fine-scale variability in surface elevation and urban factors are major sources of error in the CTM-derived relationships. Agreement remains high (r2=0.78) even when a large fraction of ground monitors (70%) are withheld from the GWR, suggesting this technique may add value in regions with even sparse ground monitoring networks, and potentially worldwide.

Individual differences in episodic memory abilities predict successful prospective memory output monitoring.

PubMed

Hunter Ball, B; Pitães, Margarida; Brewer, Gene A

2018-02-07

Output monitoring refers to memory for one's previously completed actions. In the context of prospective memory (PM) (e.g., remembering to take medication), failures of output monitoring can result in repetitions and omissions of planned actions (e.g., over- or under-medication). To be successful in output monitoring paradigms, participants must flexibly control attention to detect PM cues as well as engage controlled retrieval of previous actions whenever a particular cue is encountered. The current study examined individual differences in output monitoring abilities in a group of younger adults differing in attention control (AC) and episodic memory (EM) abilities. The results showed that AC ability uniquely predicted successful cue detection on the first presentation, whereas EM ability uniquely predicted successful output monitoring on the second presentation. The current study highlights the importance of examining external correlates of PM abilities and contributes to the growing body of research on individual differences in PM.

Involvement of the anterior cingulate cortex in time-based prospective memory task monitoring: An EEG analysis of brain sources using Independent Component and Measure Projection Analysis

PubMed Central

Burgos, Pablo; Kilborn, Kerry; Evans, Jonathan J.

2017-01-01

Objective Time-based prospective memory (PM), remembering to do something at a particular moment in the future, is considered to depend upon self-initiated strategic monitoring, involving a retrieval mode (sustained maintenance of the intention) plus target checking (intermittent time checks). The present experiment was designed to explore what brain regions and brain activity are associated with these components of strategic monitoring in time-based PM tasks. Method 24 participants were asked to reset a clock every four minutes, while performing a foreground ongoing word categorisation task. EEG activity was recorded and data were decomposed into source-resolved activity using Independent Component Analysis. Common brain regions across participants, associated with retrieval mode and target checking, were found using Measure Projection Analysis. Results Participants decreased their performance on the ongoing task when concurrently performed with the time-based PM task, reflecting an active retrieval mode that relied on withdrawal of limited resources from the ongoing task. Brain activity, with its source in or near the anterior cingulate cortex (ACC), showed changes associated with an active retrieval mode including greater negative ERP deflections, decreased theta synchronization, and increased alpha suppression for events locked to the ongoing task while maintaining a time-based intention. Activity in the ACC was also associated with time-checks and found consistently across participants; however, we did not find an association with time perception processing per se. Conclusion The involvement of the ACC in both aspects of time-based PM monitoring may be related to different functions that have been attributed to it: strategic control of attention during the retrieval mode (distributing attentional resources between the ongoing task and the time-based task) and anticipatory/decision making processing associated with clock-checks. PMID:28863146

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.

Relationship Between PM2.5 Collected at Residential Outdoor Locations and a Central Site

EPA Science Inventory

Regression models are developed to describe the relationship between ambient PM_2.5 (particulate matter [PM] ≤ _2.5 μm in aerodynamic diameter) mass concentrations measured at a central-site monitor with those at residential outdoor monitors. Understanding the...

Using NASA Satellite Aerosol Optical Depth to Enhance PM2.5 Concentration Datasets for Use in Human Health and Epidemiology Studies

NASA Astrophysics Data System (ADS)

Huff, A. K.; Weber, S.; Braggio, J.; Talbot, T.; Hall, E.

2012-12-01

Fine particulate matter (PM2.5) is a criterion air pollutant, and its adverse impacts on human health are well established. Traditionally, studies that analyze the health effects of human exposure to PM2.5 use concentration measurements from ground-based monitors and predicted PM2.5 concentrations from air quality models, such as the U.S. EPA's Community Multi-scale Air Quality (CMAQ) model. There are shortcomings associated with these datasets, however. Monitors are not distributed uniformly across the U.S., which causes spatially inhomogeneous measurements of pollutant concentrations. There are often temporal variations as well, since not all monitors make daily measurements. Air quality model output, while spatially and temporally uniform, represents predictions of PM2.5 concentrations, not actual measurements. This study is exploring the potential of combining Aerosol Optical Depth (AOD) data from the MODIS instrument on NASA's Terra and Aqua satellites with PM2.5 monitor data and CMAQ predictions to create PM2.5 datasets that more accurately reflect the spatial and temporal variations in ambient PM2.5 concentrations on the metropolitan scale, with the overall goal of enhancing capabilities for environmental public health decision-making. AOD data provide regional information about particulate concentrations that can fill in the spatial and temporal gaps in the national PM2.5 monitor network. Furthermore, AOD is a measurement, so it reflects actual concentrations of particulates in the atmosphere, in contrast to PM2.5 predictions from air quality models. Results will be presented from the Battelle/U.S. EPA statistical Hierarchical Bayesian Model (HBM), which was used to combine three PM2.5 concentration datasets: monitor measurements, AOD data, and CMAQ model predictions. The study is focusing on the Baltimore, MD and New York City, NY metropolitan regions for the period 2004-2006. For each region, combined monitor/AOD/CMAQ PM2.5 datasets generated by the HBM are being correlated with data on inpatient hospitalizations and emergency room visits for seven respiratory and cardiovascular diseases using statistical case-crossover analyses. Preliminary results will be discussed regarding the potential for the addition of AOD data to increase the correlation between PM2.5 concentrations and health outcomes. Environmental public health tracking programs associated with the Maryland Department of Health and Mental Hygiene, the New York State Department of Health, the CDC, and the U.S. EPA have expressed interest in using the results of this study to enhance their existing environmental health surveillance activities.

Exposure measurement error in PM2.5 health effects studies: A pooled analysis of eight personal exposure validation studies

PubMed Central

2014-01-01

Background Exposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM2.5 exposures from validation studies and typically available surrogate exposures. Methods Daily personal and ambient PM2.5, and when available sulfate, measurements were compiled from nine cities, over 2 to 12 days. True exposure was defined as personal exposure to PM2.5 of ambient origin. Since PM2.5 of ambient origin could only be determined for five cities, personal exposure to total PM2.5 was also considered. Surrogate exposures were estimated as ambient PM2.5 at the nearest monitor or predicted outside subjects’ homes. We estimated calibration coefficients by regressing true on surrogate exposures in random effects models. Results When monthly-averaged personal PM2.5 of ambient origin was used as the true exposure, calibration coefficients equaled 0.31 (95% CI:0.14, 0.47) for nearest monitor and 0.54 (95% CI:0.42, 0.65) for outdoor home predictions. Between-city heterogeneity was not found for outdoor home PM2.5 for either true exposure. Heterogeneity was significant for nearest monitor PM2.5, for both true exposures, but not after adjusting for city-average motor vehicle number for total personal PM2.5. Conclusions Calibration coefficients were <1, consistent with previously reported chronic health risks using nearest monitor exposures being under-estimated when ambient concentrations are the exposure of interest. Calibration coefficients were closer to 1 for outdoor home predictions, likely reflecting less spatial error. Further research is needed to determine how our findings can be incorporated in future health studies. PMID:24410940

Space and time resolved monitoring of airborne particulate matter in proximity of a traffic roundabout in Sweden.

PubMed

Wilkinson, Kai E; Lundkvist, Johanna; Netrval, Julia; Eriksson, Mats; Seisenbaeva, Gulaim A; Kessler, Vadim G

2013-11-01

Concerns over exposure to airborne particulate matter (PM) are on the rise. Currently monitoring of PM is done on the basis of interpolating a mass of PM by volume (μg/m(3)) but has the drawback of not taking the chemical nature of PM into account. Here we propose a method of collecting PM at its emission source and employing automated analysis with scanning electron microscopy associated with EDS-analysis together with light scattering to discern the chemical composition, size distribution, and time and space resolved structure of PM emissions in a heavily trafficated roundabout in Sweden. Multivariate methods (PCA, ANOVA) indicate that the technogenic marker Fe follows roadside dust in spreading from the road, and depending on time and location of collection, a statistically significant difference can be seen, adding a useful tool to the repertoiré of detailed PM monitoring and risk assessment of local emission sources. Copyright © 2013 Elsevier Ltd. All rights reserved.

PM2.5 in household kitchens of Bhaktapur, Nepal, using four different cooking fuels

NASA Astrophysics Data System (ADS)

Pokhrel, Amod K.; Bates, Michael N.; Acharya, Jiwan; Valentiner-Branth, Palle; Chandyo, Ram K.; Shrestha, Prakash S.; Raut, Anil K.; Smith, Kirk R.

2015-07-01

In studies examining the health effects of household air pollution (HAP), lack of affordable monitoring devices often precludes collection of actual air pollution data, forcing use of exposure indicators, such as type of cooking fuel used. Among the most important pollutants is fine particulate matter (PM2.5), perhaps the best single indicator of risk from smoke exposure. In this study, we deployed an affordable and robust device to monitor PM2.5 in 824 households in Bhaktapur, Nepal. Four primary cooking fuels were used in roughly equal proportions in these households: electricity (22%), liquefied petroleum gas (LPG) (29%), kerosene (23%), and biomass (26%). PM2.5 concentrations were measured in the kitchens using a light-scattering nephelometer, the UCB-PATS (University of California, Berkeley-Particle and Temperature monitoring System). The major predictors of PM2.5 concentrations in study households were investigated. The UCB-PATS results were well correlated with the gravimetric results (R2 = 0.84; for all fuels combined). The mean household PM2.5 concentrations across all seasons of the year were 656 (standard deviation (SD):924) μg/m3 from biomass; 169 (SD: 207) μg/m3 from kerosene; 101 (SD: 130) μg/m3 from LPG; and 80 (SD: 103) μg/m3 from electric stoves. In the multivariate regression of PM2.5 measures, compared with electric stoves, use of LPG, kerosene and biomass stoves were associated with increased indoor PM2.5 concentrations of 65% (95% CI: 38-95%), 146% (103-200%), and 733% (589-907%), respectively. The UCB-PATS performed well in the field. Biomass fuel stoves without flues were the most significant sources of PM2.5, followed by kerosene and then LPG stoves. Outdoor PM2.5, and season influenced indoor PM2.5 levels. Results support careful use of inexpensive light-scattering monitors for monitoring of HAP in developing countries.

DEVELOPMENT AND EVALUATION OF A CONTINUOUS COARSE (PM10-PM2.5) PARTICLE MONITOR

EPA Science Inventory

In this paper, we describe the development and laboratory and field evaluation of a continuous coarse (2.5-10 um) particle mass (PM) monitor that can provide reliable measurements of the coarse mass (CM) concentrations in time intervals as short as 5-10 min. The operating princ...

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…

U.S. National PM2.5 Chemical Speciation Monitoring Networks – CSN and IMPROVE: Description of Networks

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) initiated the national PM2.5 Chemical Speciation Monitoring Network (CSN) in 2000 to support evaluation of long-term trends and to better quantify the impact of sources on particulate matter (PM) concentrations in the size range belo...

Network Analysis of Fine Particulate Matter (PM2.5) Emissions in China

NASA Astrophysics Data System (ADS)

Yan, Shaomin; Wu, Guang

2016-09-01

Specification of PM2.5 spatial and temporal characteristics is important for understanding PM2.5 adverse effects and policymaking. We applied network analysis to studying the dataset MIX, which contains PM2.5 emissions recorded from 2168 monitoring stations in China in 2008 and 2010. The results showed that for PM2.5 emissions from industrial sector 8 clusters were found in 2008 but they merged together into a huge cluster in 2010, suggesting that industrial sector underwent an integrating process. For PM2.5 emissions from electricity generation sector, strong locality of clusters was revealed, implying that each region had its own electricity generation system. For PM2.5 emissions from residential sector, the same pattern of 10 clusters was uncovered in both years, implicating the household energy consumption unchanged from 2008 to 2010. For PM2.5 emissions from transportation sector, the same pattern of 5 clusters with many connections in-between was unraveled, indicating the high-speed development of transportation nationalwidely. Except for the known elements, mercury (Hg) surfaced as an element for particle nucleation. To our knowledge, this is the first network study in this field.

Air Pollution Measurements by Citizen Scientists and NASA Satellites: Data Integration and Analysis

NASA Astrophysics Data System (ADS)

Gupta, P.; Maibach, J.; Levy, R. C.; Doraiswamy, P.; Pikelnaya, O.; Feenstra, B.; Polidori, A.

2017-12-01

PM2.5, or fine particulate matter, is a category of air pollutant consisting of solid particles with effective aerodynamic diameter of less than 2.5 microns. These particles are hazardous to human health, as their small size allows them to penetrate deep into the lungs. Since the late 1990's, the US Environmental Protection Agency has been monitoring PM2.5 using a network of ground-level sensors. Due to cost and space restrictions, the EPA monitoring network remains spatially sparse. That is, while the network spans the extent of the US, the distance between sensors is large enough that significant spatial variation in PM concentration can go undetected. To increase the spatial resolution of monitoring, previous studies have used satellite data to estimate ground-level PM concentrations. From imagery, one can create a measure of haziness due to aerosols, called aerosol optical depth (AOD), which then can be used to estimate PM concentrations using statistical and physical modeling. Additionally, previous research has identified a number of meteorological variables, such as relative humidity and mixing height, which aide in estimating PM concentrations from AOD. Although the high spatial resolution of satellite data is valuable alone for forecasting air quality, higher resolution ground-level data is needed to effectively study the relationship between PM2.5 concentrations and AOD. To this end, we discuss a citizen-science PM monitoring network deployed in California. Using low-cost PM sensors, this network achieves higher spatial resolution. We additionally discuss a software pipeline for integrating resulting PM measurements with satellite data, as well as initial data analysis.

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.

Characterisation of PM(10), PM(2.5) and benzene soluble organic fraction of particulate matter in an urban area of Kolkata, India.

PubMed

Gupta, A K; Nag, Subhankar; Mukhopadhyay, U K

2006-04-01

In this study, the relationship between inhalable particulate (PM(10)), fine particulate (PM(2.5)), coarse particles (PM(2.5 - 10)) and meteorological parameters such as temperature, relative humidity, solar radiation, wind speed were statistically analyzed and modelled for urban area of Kolkata during winter months of 2003-2004. Ambient air quality was monitored with a sampling frequency of twenty-four hours at three monitoring sites located near traffic intersections and in an industrial area. The monitoring sites were located 3-5 m above ground near highly trafficked and congested areas. The 24 h average PM(10) and PM(2.5) samples were collected using Thermo-Andersen high volume samplers and exposed filter papers were extracted and analysed for benzene soluble organic fraction. The ratios between PM(2.5) and PM(10) were found to be in the range of 0.6 to 0.92 and the highest ratio was found in the most polluted urban site. Statistical analysis has shown a strong positive correlation between PM(10) and PM(2.5) and inverse correlation was observed between particulate matter (PM(10) and PM(2.5)) and wind speed. Statistical analysis of air quality data shows that PM(10) and PM(2.5) are showing poor correlation with temperature, relative humidity and solar radiation. Regression equations for PM(10) and PM(2.5) and meteorological parameters were developed. The organic fraction of particulate matter soluble in benzene is an indication of poly aromatic hydrocarbon (PAH) concentration present in particulate matter. The relationship between the benzene soluble organic fraction (BSOF) of inhalable particulate (PM(10)) and fine particulate (PM(2.5)) were analysed for urban area of Kolkata. Significant positive correlation was observed between benzene soluble organic fraction of PM(10) (BSM10) and benzene soluble organic fraction of PM(2.5) (BSM2.5). Regression equations for BSM10 and BSM2.5 were developed.

Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial, California, USA.

PubMed

Carvlin, Graeme N; Lugo, Humberto; Olmedo, Luis; Bejarano, Ester; Wilkie, Alexa; Meltzer, Dan; Wong, Michelle; King, Galatea; Northcross, Amanda; Jerrett, Michael; English, Paul B; Hammond, Donald; Seto, Edmund

2017-12-01

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM 2.5 and PM 10 (particulate matter with aerodynamic diameters <2.5 and <10 μm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R 2 for converted hourly averaged Dylos mass measurements versus a PM 2.5 BAM was 0.79 and that versus a PM 10 BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM 2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R 2 = 0.35-0.81). The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.

Space-time PM2.5 mapping in the severe haze region of Jing-Jin-Ji (China) using a synthetic approach.

PubMed

He, Junyu; Christakos, George

2018-05-07

Long- and short-term exposure to PM 2.5 is of great concern in China due to its adverse population health effects. Characteristic of the severity of the situation in China is that in the Jing-Jin-Ji region considered in this work a total of 2725 excess deaths have been attributed to short-term PM 2.5 exposure during the period January 10-31, 2013. Technically, the processing of large space-time PM 2.5 datasets and the mapping of the space-time distribution of PM 2.5 concentrations often constitute high-cost projects. To address this situation, we propose a synthetic modeling framework based on the integration of (a) the Bayesian maximum entropy method that assimilates auxiliary information from land-use regression and artificial neural network (ANN) model outputs based on PM 2.5 monitoring, satellite remote sensing data, land use and geographical records, with (b) a space-time projection technique that transforms the PM 2.5 concentration values from the original spatiotemporal domain onto a spatial domain that moves along the direction of the PM 2.5 velocity spread. An interesting methodological feature of the synthetic approach is that its components (methods or models) are complementary, i.e., one component can compensate for the occasional limitations of another component. Insight is gained in terms of a PM 2.5 case study covering the severe haze Jing-Jin-Ji region during October 1-31, 2015. The proposed synthetic approach explicitly accounted for physical space-time dependencies of the PM 2.5 distribution. Moreover, the assimilation of auxiliary information and the dimensionality reduction achieved by the synthetic approach produced rather impressive results: It generated PM 2.5 concentration maps with low estimation uncertainty (even at counties and villages far away from the monitoring stations, whereas during the haze periods the uncertainty reduction was over 50% compared to standard PM 2.5 mapping techniques); and it also proved to be computationally very efficient (the reduction in computational time was over 20% compared to standard mapping techniques). Copyright © 2018 Elsevier Ltd. All rights reserved.

Mean Streets: An analysis on street level pollution in NYC

NASA Astrophysics Data System (ADS)

Parker, G.

2017-12-01

The overarching objective of this study is to quantify the spatial and temporal variability in particulatematter concentration (PM 2.5) along crowded streets in New York City. Due to their fine size and lowdensity PM 2.5 stays longer in the atmosphere and could bypass human nose and throat and penetratedeep in to the lungs and even enter the circulatory system. PM 2.5 is a by-product of automobilecombustion and is a primary cause of respiratory malfunction in NYC. The study would monitor streetlevel concentration of PM2.5 across three different routes that witness significant pedestrian traffic;observations will be conducted along these three routes at different time periods. The study will use theAirBeam community air quality monitor. The monitor tracks PM 2.5 concentration along with GPS, airtemperature and relative humidity. The surface level concentration monitored by AirBeam will becompared with atmospheric concentration of PM 2.5 that are monitored at the NOAA CREST facility onCCNY campus. The lower atmospheric values will be correlated with street level values to assess thevalidity of using of lower atmospheric values to predict street level concentrations. The street levelconcentration will be compared to the air quality forecasted by the New York Department ofEnvironment Conservation to estimate its accuracy and applicability.

COMPARISON OF FILTER-BASED AND CONTINUOUS PARTICULATE MATTER METHODOLOGIES FROM RESIDENTIAL AND AMBIENT MONITORING

EPA Science Inventory

An extensive PM monitoring study was conducted during the 1998 Baltimore PM Epidemiology-Exposure Study of the Elderly. An exposure goal of this study was. to investigate the mass concentration variability between various monitoring instrumentation located across residential in...

The moving-window Bayesian Maximum Entropy framework: Estimation of PM2.5 yearly average concentration across the contiguous United States

PubMed Central

Akita, Yasuyuki; Chen, Jiu-Chiuan; Serre, Marc L.

2013-01-01

Geostatistical methods are widely used in estimating long-term exposures for air pollution epidemiological studies, despite their limited capabilities to handle spatial non-stationarity over large geographic domains and 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 (PM2.5) yearly average concentrations over the contiguous U.S. The MW approach accounts for the spatial non-stationarity, while the BME method rigorously processes the uncertainty associated with data missingnees in the air monitoring system. In the cross-validation analyses conducted on a set of randomly selected complete PM2.5 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 PM2.5. Moreover, the MWBME method further reduces the MSE by 8.4% to 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 PM2.5 across large geographical domains with expected spatial non-stationarity. PMID:22739679

PM2.5 exposure and birth outcomes: Use of satellite- and monitor-based data

PubMed Central

Hyder, Ayaz; Lee, Hyung Joo; Ebisu, Keita; Koutrakis, Petros; Belanger, Kathleen; Bell, Michelle Lee

2014-01-01

Background Air pollution may be related to adverse birth outcomes. Exposure information from land-based monitoring stations often suffers from limited spatial coverage. Satellite data offer an alternative data source for exposure assessment. Methods We used birth certificate data for births in Connecticut and Massachusetts, U.S. (2000-2006). Gestational exposure to PM2.5 was estimated from US Environmental Protection Agency monitoring data and from satellite data. Satellite data were processed and modeled using 2 methods – denoted satellite (1) and satellite (2) – before exposure assessment. Regression models related PM2.5 exposure to birth outcomes while controlling for several confounders. Birth outcomes were mean birth weight at term birth, low birth weight at term (LBW <2500g), small for gestational age (SGA, <10th percentile for gestational age and sex), and preterm birth (<37 weeks). Results Overall, the exposure assessment method modified the magnitude of the effect estimates of PM2.5 on birth outcomes. Change in birth weight per inter-quartile range (2.41 μg/m3)-increase in PM2.5 was -6g (95% confidence interval = -8 to -5), -16g (-21 to -11) and -19g (-23 to -15), using the monitor, satellite (1) and satellite (2) methods, respectively. Adjusted odds ratios, based on the same 3 exposure methods, for term LBW were 1.01 (0.98 to 1.04), 1.06 (0.97 to 1.16), and 1.08 (1.01 to 1.16); for SGA, 1.03 (1.01 to 1.04), 1.06 (1.03 to 1.10) and 1.08 (1.04 to 1.11); and for preterm birth, 1.00 (0.99 to 1.02), 0.98 (0.94 to 1.03) and 0.99 (0.95 to 1.03). Conclusions Under exposure assessment methods, we found associations between PM2.5 exposure and adverse birth outcomes particularly for birth weight among term births and for SGA. These results add to the growing concerns that air pollution adversely affects infant health and suggest that analysis of health consequences based on satellite-based exposure assessment can provide additional useful information. PMID:24240652

PM2.5 exposure and birth outcomes: use of satellite- and monitor-based data.

PubMed

Hyder, Ayaz; Lee, Hyung Joo; Ebisu, Keita; Koutrakis, Petros; Belanger, Kathleen; Bell, Michelle Lee

2014-01-01

Air pollution may be related to adverse birth outcomes. Exposure information from land-based monitoring stations often suffers from limited spatial coverage. Satellite data offer an alternative data source for exposure assessment. We used birth certificate data for births in Connecticut and Massachusetts, United States (2000-2006). Gestational exposure to PM2.5 was estimated from US Environmental Protection Agency monitoring data and from satellite data. Satellite data were processed and modeled by using two methods-denoted satellite (1) and satellite (2)-before exposure assessment. Regression models related PM2.5 exposure to birth outcomes while controlling for several confounders. Birth outcomes were mean birth weight at term birth, low birth weight at term (<2500 g), small for gestational age (SGA, <10th percentile for gestational age and sex), and preterm birth (<37 weeks). Overall, the exposure assessment method modified the magnitude of the effect estimates of PM2.5 on birth outcomes. Change in birth weight per interquartile range (2.41 μg/m) increase in PM2.5 was -6 g (95% confidence interval = -8 to -5), -16 g (-21 to -11), and -19 g (-23 to -15), using the monitor, satellite (1), and satellite (2) methods, respectively. Adjusted odds ratios, based on the same three exposure methods, for term low birth weight were 1.01 (0.98-1.04), 1.06 (0.97-1.16), and 1.08 (1.01-1.16); for SGA, 1.03 (1.01-1.04), 1.06 (1.03-1.10), and 1.08 (1.04-1.11); and for preterm birth, 1.00 (0.99-1.02), 0.98 (0.94-1.03), and 0.99 (0.95-1.03). Under exposure assessment methods, we found associations between PM2.5 exposure and adverse birth outcomes particularly for birth weight among term births and for SGA. These results add to the growing concerns that air pollution adversely affects infant health and suggest that analysis of health consequences based on satellite-based exposure assessment can provide additional useful information.

PM2.5 Monitors in New England | Air Quality Planning Unit ...

EPA Pesticide Factsheets

2017-04-10

The New England states are currently operating a network of 58 ambient PM2.5 air quality monitors that meet EPA's Federal Reference Method (FRM) for PM2.5, which is necessary in order for the resultant data to be used for attainment/non-attainment purposes. These monitors collect particles in the ambient air smaller than 2.5 microns in size on a filter, which is weighed prior and post sampling to produce a 24-hour sample concentration.

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

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.

Monitoring of PM10 and PM2.5 around primary particulate anthropogenic emission sources

NASA Astrophysics Data System (ADS)

Querol, Xavier; Alastuey, Andrés; Rodriguez, Sergio; Plana, Felicià; Mantilla, Enrique; Ruiz, Carmen R.

Investigations on the monitoring of ambient air levels of atmospheric particulates were developed around a large source of primary anthropogenic particulate emissions: the industrial ceramic area in the province of Castelló (Eastern Spain). Although these primary particulate emissions have a coarse grain-size distribution, the atmospheric transport dominated by the breeze circulation accounts for a grain-size segregation, which results in ambient air particles occurring mainly in the 2.5-10 μm range. The chemical composition of the ceramic particulate emissions is very similar to the crustal end-member but the use of high Al, Ti and Fe as tracer elements as well as a peculiar grain-size distribution in the insoluble major phases allow us to identify the ceramic input in the bulk particulate matter. PM2.5 instead of PM10 monitoring may avoid the interference of crustal particles without a major reduction in the secondary anthropogenic load, with the exception of nitrate. However, a methodology based in PM2.5 measurement alone is not adequate for monitoring the impact of primary particulate emissions (such as ceramic emissions) on air quality, since the major ambient air particles derived from these emissions are mainly in the range of 2.5-10 μm. Consequently, in areas characterised by major secondary particulate emissions, PM2.5 monitoring should detect anthropogenic particulate pollutants without crustal particulate interference, whereas PM10 measurements should be used in areas with major primary anthropogenic particulate emissions.

METHODOLOGY FOR SITING AMBIENT AIR MONITORS AT THE NEIGHBORHOOD SCALE

EPA Science Inventory

In siting a monitor to measure compliance with U.S. National Ambient Air Quality Standards for particulate matter (PM), there is a need to characterize variations in PM concentration within a neighborhood-scale region in order to achieve monitor siting objectives.

We p...

Citizen Science Air Monitor (CSAM) Operating Procedures

EPA Science Inventory

The Citizen Science Air Monitor (CSAM) is an air monitoring system designed for measuring nitrogen dioxide (NO2) and particulate matter (PM) pollutants simultaneously. This self-contained system consists of a CairPol CairClip NO2 sensor, a Thermo Scientific personal DataRAM PM2.5...

The Brooklyn traffic real-time ambient pollutant penetration and environmental dispersion (B-TRAPPED) field study methodology.

PubMed

Richmond-Bryant, Jennifer; Hahn, Intaek; Fortune, Christopher R; Rodes, Charles E; Portzer, Jeffrey W; Lee, Sangdon; Wiener, Russell W; Smith, Luther A; Wheeler, Michael; Seagraves, Jeremy; Stein, Mark; Eisner, Alfred D; Brixey, Laurie A; Drake-Richman, Zora E; Brouwer, Lydia H; Ellenson, William D; Baldauf, Richard

2009-12-01

The Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) field study examined indoor and outdoor exposure to traffic-generated air pollution by studying the individual processes of generation of traffic emissions, transport and dispersion of air contaminants along a roadway, and infiltration of the contaminants into a residence. Real-time instrumentation was used to obtain highly resolved time-series concentration profiles for a number of air pollutants. The B-TRAPPED field study was conducted in the residential Sunset Park neighborhood of Brooklyn, NY, USA, in May 2005. The neighborhood contained the Gowanus Expressway (Interstate 278), a major arterial road (4(th) Avenue), and residential side streets running perpendicular to the Gowanus Expressway and 4(th) Avenue. Synchronized measurements were obtained inside a test house, just outside the test house façade, and along the urban residential street canyon on which the house was located. A trailer containing Federal Reference Method (FRM) and real-time monitors was located next to the Gowanus Expressway to assess the source. Ultrafine particulate matter (PM), PM(2.5), nitrogen oxides (NO(x)), sulfur dioxide (SO(2)), carbon monoxide (CO), carbon dioxide (CO(2)), temperature, relative humidity, and wind speed and direction were monitored. Different sampling schemes were devised to focus on dispersion along the street canyon or infiltration into the test house. Results were obtained for ultrafine PM, PM(2.5), criteria gases, and wind conditions from sampling schemes focused on street canyon dispersion and infiltration. For comparison, the ultrafine PM and PM(2.5) results were compared with an existing data set from the Los Angeles area, and the criteria gas data were compared with measurements from a Vancouver epidemiologic study. Measured ultrafine PM and PM(2.5) concentration levels along the residential urban street canyon and at the test house façade in Sunset Park were demonstrated to be comparable to traffic levels at an arterial road and slightly higher than those in a residential area of Los Angeles. Indoor ultrafine PM levels were roughly 3-10 times lower than outdoor levels, depending on the monitor location. CO, NO(2), and SO(2) levels were shown to be similar to values that produced increased risk of chronic obstructive pulmonary disease hospitalizations in the Vancouver studies.

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.

The Research Triangle Park particulate matter panel study: PM mass concentration relationships

NASA Astrophysics Data System (ADS)

Williams, Ron; Suggs, Jack; Rea, Anne; Leovic, Kelly; Vette, Alan; Croghan, Carry; Sheldon, Linda; Rodes, Charles; Thornburg, Jonathan; Ejire, Ademola; Herbst, Margaret; Sanders, William

The US Environmental Protection Agency has recently performed the Research Triangle Park Particulate Matter Panel Study. This was a 1-year investigation of PM and related co-pollutants involving participants living within the RTP area of North Carolina. Primary goals were to characterize the relationships between ambient and residential PM measures to those obtained from personal exposure monitoring and estimate ambient source contributions to personal and indoor mass concentrations. A total of 38 participants living in 37 homes were involved in personal, residential indoor, residential outdoor and ambient PM 2.5 exposure monitoring. Participants were 30 non-smoking hypertensive African-Americans living in a low-moderate SES neighborhood (SE Raleigh, NC) and a cohort of eight individuals having implanted cardiac defibrillators (Chapel Hill, NC). Residential and ambient monitoring of PM 10 and PM 10-2.5 (coarse by differential) was also performed. The volunteers were monitored for seven consecutive days during each of four seasons (summer 2000, fall 2000, winter 2001, spring 2001). Individual PM 2.5 personal exposure concentrations ranged from 4 to 218 μg m -3 during the study. The highest personal exposures were determined to be the result of passive environmental tobacco exposures. Subsequently, ˜7% of the total number of personal exposure trials were excluded to minimize this pollutant's effect upon the overall analysis. Results indicated that a pooled data set (seasons, cohorts, residences, participants) was appropriate for investigation of the basic mass concentration relationships. Daily personal PM 2.5 mass concentrations were typically higher than their associated residential or ambient measurements (mean personal=23.0, indoor=19.1, outdoor=19.3, ambient=19.2 μg m -3). Mean personal PM 2.5 exposures were observed to be only moderately correlated to ambient PM 2.5 concentrations ( r=0.39).

Development of intelligent monitoring purifier for indoor PM 2.5

NASA Astrophysics Data System (ADS)

Lou, Guanting; Zhu, Rong; Guo, Jiangwei; Wei, Yongqing

2018-03-01

The particulate matter 2.5 (PM2.5) refers to tiny particles or droplets in the air that are two and one half microns or less in width. PM2.5 is an air pollutant that is a concern for people’s health when levels in air are high. The intelligent monitoring purifier was developed to detect indoor PM2.5 concentration before and after purification and the monitoring data could be displayed on the LCD screen, displaying different color patterns according to the concentrations. Through the Bluetooth transport module, real-time values could also display on the mobile phone and voice broadcast PM2.5 concentration level in the air. When PM2.5 concentration is higher than the setting threshold, the convection fan rotation and the speed can be remote controlled with mobile phone through the Bluetooth transport. Therefore, the efficiency and scope of the purification could be enhanced and further better air quality could be achieved.

Comparison of the SidePak personal monitor with the Aerosol Particle Sizer (APS).

PubMed

Sánchez Jiménez, Araceli; van Tongeren, Martie; Galea, Karen S; Steinsvåg, Kjersti; MacCalman, Laura; Cherrie, John W

2011-06-01

The aim of this study was to compare the performance of the TSI Aerodynamic Particle Sizer (APS) and the TSI portable photometer SidePak to measure airborne oil mist particulate matter (PM) with aerodynamic diameters below 10 μm, 2.5 μm and 1 μm (PM(10), PM(2.5) and PM(1)). Three SidePaks each fitted with either a PM(10), PM(2.5) or a PM(1) impactor and an APS were run side by side in a controlled chamber. Oil mist from two different mineral oils and two different drilling fluid systems commonly used in offshore drilling technologies were generated using a nebulizer. Compared to the APS, the SidePaks overestimated the concentration of PM(10) and PM(2.5) by one order of magnitude and PM(1) concentrations by two orders of magnitude after exposure to oil mist for 3.3-6.5 min at concentrations ranging from 0.003 to 18.1 mg m(-3) for PM(10), 0.002 to 3.96 mg m(-3) for PM(2.5) and 0.001 to 0.418 mg m(-3) for PM(1) (as measured by the APS). In a second experiment a SidePak monitor previously exposed to oil mist overestimated PM(10) concentrations by 27% compared to measurements from another SidePak never exposed to oil mist. This could be a result of condensation of oil mist droplets in the optical system of the SidePak. The SidePak is a very useful instrument for personal monitoring in occupational hygiene due to its light weight and quiet pump. However, it may not be suitable for the measurement of particle concentrations from oil mist.

Investigation of the microbial community structure and activity as indicators of compost stability and composting process evolution.

PubMed

Chroni, Christina; Kyriacou, Adamadini; Manios, Thrassyvoulos; Lasaridi, Konstantia-Ekaterini

2009-08-01

In a bid to identify suitable microbial indicators of compost stability, the process evolution during windrow composting of poultry manure (PM), green waste (GW) and biowaste was studied. Treatments were monitored with regard to abiotic factors, respiration activity (determined using the SOUR test) and functional microflora. The composting process went through typical changes in temperature, moisture content and microbial properties, despite the inherent feedstock differences. Nitrobacter and pathogen indicators varied as a monotonous function of processing time. Some microbial groups have shown a potential to serve as fingerprints of the different process stages, but still they should be examined in context with respirometric tests and abiotic parameters. Respiration activity reflected well the process stage, verifying the value of respirometric tests to access compost stability. SOUR values below 1 mg O(2)/g VS/h were achieved for the PM and the GW compost.

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.

Spatial and temporal variations of the concentrations of PM10, PM2.5 and PM1 in China

NASA Astrophysics Data System (ADS)

Wang, Y. Q.; Zhang, X. Y.; Sun, J. Y.; Zhang, X. C.; Che, H. Z.; Li, Y.

2015-06-01

Concentrations of PM10, PM2.5 and PM1 were monitored at 24 stations of CAWNET (China Atmosphere Watch Network) from 2006 to 2014 using GRIMM 180 dust monitors. The highest particulate matter (PM) concentrations were observed at the stations of Xian, Zhengzhou and Gucheng, in Guanzhong and the Hua Bei Plain (HBP). The second highest PM concentrations were observed in northeast China, followed by southern China. According to the latest air quality standards of China, 14 stations reached the PM10 standard and only 7 stations, mainly rural and remote stations, reached the PM2.5 standard. The PM2.5 and PM10 ratios showed a clear increasing trend from northern to southern China, because of the substantial contribution of coarse mineral aerosol in northern China. The PM1 and PM2.5 ratios were higher than 80% at most stations. PM concentrations tended to be highest in winter and lowest in summer at most stations, and mineral dust impacts influenced the results in spring. A decreasing interannual trend was observed in the HBP and southern China from 2006 to 2014, but an increasing trend occurred at some stations in northeast China. Also diurnal variations of PM concentrations and meteorological factors effects were investigated.

Random forest meteorological normalisation models for Swiss PM10 trend analysis

NASA Astrophysics Data System (ADS)

Grange, Stuart K.; Carslaw, David C.; Lewis, Alastair C.; Boleti, Eirini; Hueglin, Christoph

2018-05-01

Meteorological normalisation is a technique which accounts for changes in meteorology over time in an air quality time series. Controlling for such changes helps support robust trend analysis because there is more certainty that the observed trends are due to changes in emissions or chemistry, not changes in meteorology. Predictive random forest models (RF; a decision tree machine learning technique) were grown for 31 air quality monitoring sites in Switzerland using surface meteorological, synoptic scale, boundary layer height, and time variables to explain daily PM10 concentrations. The RF models were used to calculate meteorologically normalised trends which were formally tested and evaluated using the Theil-Sen estimator. Between 1997 and 2016, significantly decreasing normalised PM10 trends ranged between -0.09 and -1.16 µg m-3 yr-1 with urban traffic sites experiencing the greatest mean decrease in PM10 concentrations at -0.77 µg m-3 yr-1. Similar magnitudes have been reported for normalised PM10 trends for earlier time periods in Switzerland which indicates PM10 concentrations are continuing to decrease at similar rates as in the past. The ability for RF models to be interpreted was leveraged using partial dependence plots to explain the observed trends and relevant physical and chemical processes influencing PM10 concentrations. Notably, two regimes were suggested by the models which cause elevated PM10 concentrations in Switzerland: one related to poor dispersion conditions and a second resulting from high rates of secondary PM generation in deep, photochemically active boundary layers. The RF meteorological normalisation process was found to be robust, user friendly and simple to implement, and readily interpretable which suggests the technique could be useful in many air quality exploratory data analysis situations.

Indoor particulate matter measurement as a tool in the process of the implementation of smoke-free hospitals.

PubMed

Nardini, S; Cagnin, R; Invernizzi, G; Ruprecht, A; Boffi, R; Formentini, S

2004-01-01

There are International and National standards that requires hospitals and health premises to be smoke-free. According to recent data from Italy and other European Countries, smoking is a widespread habit in hospitals. To get smoke-free hospitals in an Italian region, we have adopted the European Code for smoke-free hospitals, which sets standards and provides instruments for its implementation. According to the Code, whenever possible, each step towards a smoke-free hospital, should be shared by all staff. As a mean for achieving this goal, in our region the certification of single units as smoke-free units has been chosen. For getting the certification, besides implementing the Code, we planned to use ETS (Environmental Tobacco Smoke) monitoring, as ETS should not be present in hospitals. As a marker of ETS we have chosen Particulate Matter (PM), as it can easily be measured in real-time with a portable instrument and, when other even outdoor--sources of combustion can be ruled out, it is an accurate detector of cigarette smoke. Here the first experience of measuring PM in hospitals for monitoring ETS and certificating smoke-free health premises, is described. PM measurements were carried out without any previous notification in different areas of two Network hospitals of the Veneto Region, during a single working day. A real time laser-operated aerosol mass analyser was used. Several classes of PM (PM1, PM2.5, PM7, PM10, TSP Total Suspended Particles) were measured. Outdoor PM levels were found to be repeatedly lower than the annual official limits of 65 mcg/m3 and around the 24 hour official limits of 15 mcg/m3 [15 to 20 mcg/m3, with an overall mean (+/-SD) of 17.8 (1.9)] throughout the whole day. Very good indoor air quality was found in the operating theaters and isolation department, where PM2.5 concentrations were much lower than outdoor levels [1.6 (0.9) and 5.9 (0.6) mcg/m3, respectively]. No increase in PM pollution was found in the surveyed medical offices, halls and waiting rooms where smoking was positively forbidden [PM2.5 concentrations of 14.8 (2.2) and 12.9 (1.1) mcg/m3] except in a medical office and in two coffee rooms for staff only where high PM levels were recorded [PM2.5 58.7 (29.1), 27.0 (10.6) and 107.1 (47.8) mcg/m3] and an offence of smoking restrictions could be proved. The measurement of PM in hospital for monitoring ETS proved to be both feasible and sensible. PM measurements with a portable instrument can be used both for controlling the compliance with rules or chosen standards and for educating staff about smoking related hazards, thus gaining consensus for the implementation of the tobacco control policy. In our experience, PM measurement can be used as an aid inside all actions designed by the European Code for smoke-free hospitals.

Rehabilitation of executive dysfunction following brain injury: "content-free" cueing improves everyday prospective memory performance.

PubMed

Fish, Jessica; Evans, Jonathan J; Nimmo, Morag; Martin, Emma; Kersel, Denyse; Bateman, Andrew; Wilson, Barbara A; Manly, Tom

2007-03-25

Prospective memory (PM) is often claimed to rely upon executive as well as mnemonic resources. Here, we examined the contribution of executive functions towards PM by providing intermittent support for monitoring processes using "content-free" cues, which carried no direct information regarding the PM task itself. Twenty participants with non-progressive brain injury and PM difficulties received brief training in linking a cue phrase "STOP!" with pausing current activity and reviewing stored goals. The efficacy of this strategy was examined with a PM task requiring participants to make telephone calls to a voicemail service at four set times each day for 10 days. Task content was encoded using errorless learning to minimise retrospective memory-based failures. On five randomly selected days, eight text messages reading simply "STOP!" were sent to participants' mobile telephones, but crucially not within an hour of a target time. Striking improvements in performance were observed on cued days, thus demonstrating a within-subjects experimental modulation of PM performance using cues that carry no information other than by association with participants' stored memory of their intentions. In addition to the theoretical insights, the time course over which the effect was observed constitutes encouraging evidence that such strategies are useful in helping to remediate some negative consequences of executive dysfunction. It is proposed that this benefit results from enhanced efficiency of goal management via increased monitoring of current and future goals, and the steps necessary to achieve them, perhaps compensating for under-functioning fronto-parietal attention systems.

Influence of Human Activity Patterns, particle composition, and residential air exchange rates on modeled distributions of PM 2.5 exposure compared with central-site monitoring data

EPA Science Inventory

Central-site monitors do not account for factors such as outdoor-to-indoor transport and human activity patterns that influence personal exposures to ambient fine-particulate matter (PM_2.5). We describe and compare different ambient PM_2.5 exposure estimation...

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.

Assessing the impact of fine particulate matter (PM2.5) on respiratory-cardiovascular chronic diseases in the New York City Metropolitan area using Hierarchical Bayesian Model estimates.

PubMed

Weber, Stephanie A; Insaf, Tabassum Z; Hall, Eric S; Talbot, Thomas O; Huff, Amy K

2016-11-01

An enhanced research paradigm is presented to address the spatial and temporal gaps in fine particulate matter (PM 2.5 ) measurements and generate realistic and representative concentration fields for use in epidemiological studies of human exposure to ambient air particulate concentrations. The general approach for research designed to analyze health impacts of exposure to PM 2.5 is to use concentration data from the nearest ground-based air quality monitor(s), which typically have missing data on the temporal and spatial scales due to filter sampling schedules and monitor placement, respectively. To circumvent these data gaps, this research project uses a Hierarchical Bayesian Model (HBM) to generate estimates of PM 2.5 in areas with and without air quality monitors by combining PM 2.5 concentrations measured by monitors, PM 2.5 concentration estimates derived from satellite aerosol optical depth (AOD) data, and Community-Multiscale Air Quality (CMAQ) model predictions of PM 2.5 concentrations. This methodology represents a substantial step forward in the approach for developing representative PM 2.5 concentration datasets to correlate with inpatient hospitalizations and emergency room visits data for asthma and inpatient hospitalizations for myocardial infarction (MI) and heart failure (HF) using case-crossover analysis. There were two key objective of this current study. First was to show that the inputs to the HBM could be expanded to include AOD data in addition to data from PM 2.5 monitors and predictions from CMAQ. The second objective was to determine if inclusion of AOD surfaces in HBM model algorithms results in PM 2.5 air pollutant concentration surfaces which more accurately predict hospital admittance and emergency room visits for MI, asthma, and HF. This study focuses on the New York City, NY metropolitan and surrounding areas during the 2004-2006 time period, in order to compare the health outcome impacts with those from previous studies and focus on any benefits derived from the changes in the HBM model surfaces. Consistent with previous studies, the results show high PM 2.5 exposure is associated with increased risk of asthma, myocardial infarction and heart failure. The estimates derived from concentration surfaces that incorporate AOD had a similar model fit and estimate of risk as compared to those derived from combining monitor and CMAQ data alone. Thus, this study demonstrates that estimates of PM 2.5 concentrations from satellite data can be used to supplement PM 2.5 monitor data in the estimates of risk associated with three common health outcomes. Results from this study were inconclusive regarding the potential benefits derived from adding AOD data to the HBM, as the addition of the satellite data did not significantly increase model performance. However, this study was limited to one metropolitan area over a short two-year time period. The use of next-generation, high temporal and spatial resolution satellite AOD data from geostationary and polar-orbiting satellites is expected to improve predictions in epidemiological studies in areas with fewer pollutant monitors or over wider geographic areas. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

PM2.5 monitoring system based on ZigBee wireless sensor network

NASA Astrophysics Data System (ADS)

Lin, Lukai; Li, Xiangshun; Gu, Weiying

2017-06-01

In the view of the haze problem, aiming at improving the deficiency of the traditional PM2.5 monitoring methods, such as the insufficient real-time monitoring, limited transmission distance, high cost and the difficulty to maintain, the atmosphere PM2.5 monitoring system based on ZigBee technology is designed. The system combines the advantages of ZigBee’s low cost, low power consumption, high reliability and GPRS/Internet’s capability of remote transmission of data. Furthermore, it adopts TI’s Z-Stack protocol stack, and selects CC2530 chip and TI’s MSP430 microcontroller as the core, which establishes the air pollution monitoring network that is helpful for the early prediction of major air pollution disasters.

FREQUENCY DISTRIBUTIONS AND SPATIAL ANALYSIS OF FINE PARTICLE MEASUREMENTS IN ST. LOUIS DURING THE REGIONAL AIR POLLUTION STUDY/REGIONAL AIR MONITORING SYSTEM

EPA Science Inventory

Community, time-series epidemiology typically uses either 24-hour integrated particulate matter (PM) concentrations averaged across several monitors in a city or data obtained at a central monitoring site to relate PM concentrations to human health effects. If 24-hour integrated...

Accuracy and reliability of Chile's National Air Quality Information System for measuring particulate matter: Beta attenuation monitoring issue.

PubMed

Toro A, Richard; Campos, Claudia; Molina, Carolina; Morales S, Raul G E; Leiva-Guzmán, Manuel A

2015-09-01

A critical analysis of Chile's National Air Quality Information System (NAQIS) is presented, focusing on particulate matter (PM) measurement. This paper examines the complexity, availability and reliability of monitoring station information, the implementation of control systems, the quality assurance protocols of the monitoring station data and the reliability of the measurement systems in areas highly polluted by particulate matter. From information available on the NAQIS website, it is possible to confirm that the PM2.5 (PM10) data available on the site correspond to 30.8% (69.2%) of the total information available from the monitoring stations. There is a lack of information regarding the measurement systems used to quantify air pollutants, most of the available data registers contain gaps, almost all of the information is categorized as "preliminary information" and neither standard operating procedures (operational and validation) nor assurance audits or quality control of the measurements are reported. In contrast, events that cause saturation of the monitoring detectors located in northern and southern Chile have been observed using beta attenuation monitoring. In these cases, it can only be concluded that the PM content is equal to or greater than the saturation concentration registered by the monitors and that the air quality indexes obtained from these measurements are underestimated. This occurrence has been observed in 12 (20) public and private stations where PM2.5 (PM10) is measured. The shortcomings of the NAQIS data have important repercussions for the conclusions obtained from the data and for how the data are used. However, these issues represent opportunities for improving the system to widen its use, incorporate comparison protocols between equipment, install new stations and standardize the control system and quality assurance. Copyright © 2015 Elsevier Ltd. All rights reserved.

Aerosol measurement: the use of optical light scattering for the determination of particulate size distribution, and particulate mass, including the semi-volatile fraction.

PubMed

Grimm, Hans; Eatough, Delbert J

2009-01-01

The GRIMM model 1.107 monitor is designed to measure particle size distribution and particulate mass based on a light scattering measurement of individual particles in the sampled air. The design and operation of the instrument are described. Protocols used to convert the measured size number distribution to a mass concentration consistent with U.S. Environmental Protection Agency protocols for measuring particulate matter (PM) less than 10 microm (PM10) and less than 2.5 microm (PM2.5) in aerodynamic diameter are described. The performance of the resulting continuous monitor has been evaluated by comparing GRIMM monitor PM2.5 measurements with results obtained by the Rupprecht and Patashnick Co. (R&P) filter dynamic measurement system (FDMS). Data were obtained during month-long studies in Rubidoux, CA, in July 2003 and in Fresno, CA, in December 2003. The results indicate that the GRIMM monitor does respond to total PM2.5 mass, including the semi-volatile components, giving results comparable to the FDMS. The data also indicate that the monitor can be used to estimate water content of the fine particles. However, if the inlet to the monitor is heated, then the instrument measures only the nonvolatile material, more comparable to results obtained with a conventional heated filter tapered element oscillating microbalance (TEOM) monitor. A recent modification of the model 180, with a Nafion dryer at the inlet, measures total PM2.5 including the nonvolatile and semi-volatile components, but excluding fine particulate water. Model 180 was in agreement with FDMS data obtained in Lindon, UT, during January through February 2007.

Geochemistry and carbon isotopic ratio for assessment of PM10 composition, source and seasonal trends in urban environment.

PubMed

Di Palma, A; Capozzi, F; Agrelli, D; Amalfitano, C; Giordano, S; Spagnuolo, V; Adamo, P

2018-08-01

Investigating the nature of PM 10 is crucial to differentiate sources and their relative contributions. In this study we compared the levels, and the chemical and mineralogical properties of PM 10 particles sampled in different seasons at monitoring stations representative of urban background, urban traffic and suburban traffic areas of Naples city. The aims were to relate the PM 10 load and characteristics to the location of the monitoring stations, to investigate the different sources contributing to PM 10 and to highlight PM 10 seasonal variability. Bulk analyses of chemical species in the PM 10 fraction included total carbon and nitrogen, δ 13 C and other 20 elements. Both natural and anthropogenic sources were found to contribute to the exceedances of the EU PM 10 limit values. The natural contribution was mainly related to marine aerosols and soil dust, as highlighted by X-ray diffractometry and SEM-EDS microscopy. The percentage of total carbon suggested a higher contribution of biogenic components to PM 10 in spring. However, this result was not supported by the δ 13 C values which were seasonally homogeneous and not sufficient to extract single emission sources. No significant differences, in terms of PM 10 load and chemistry, were observed between monitoring stations with different locations, suggesting a homogeneous distribution of PM 10 on the studied area in all seasons. The anthropogenic contribution to PM 10 seemed to dominate in all sites and seasons with vehicular traffic acting as a main source mostly by generation of non-exhaust emissions Our findings reinforce the need to focus more on the analysis of PM 10 in terms of quality than of load, to reconsider the criteria for the classification and the spatial distribution of the monitoring stations within urban and suburban areas, with a special attention to the background location, and to emphasize all the policies promoting sustainable mobility and reduction of both exhaust and not-exhaust traffic-related emissions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial and temporal variability of fine particle composition and source types in five cities of Connecticut and Massachusetts

PubMed Central

Lee, Hyung Joo; Gent, Janneane F.; Leaderer, Brian P.; Koutrakis, Petros

2011-01-01

To protect public health from PM2.5 air pollution, it is critical to identify the source types of PM2.5 mass and chemical components associated with higher risks of adverse health outcomes. Source apportionment modeling using Positive Matrix Factorization (PMF), was used to identify PM2.5 source types and quantify the source contributions to PM2.5 in five cities of Connecticut and Massachusetts. Spatial and temporal variability of PM2.5 mass, components and source contributions were investigated. PMF analysis identified five source types: regional pollution as traced by sulfur, motor vehicle, road dust, oil combustion and sea salt. The sulfur-related regional pollution and traffic source type were major contributors to PM2.5. Due to sparse ground-level PM2.5 monitoring sites, current epidemiological studies are susceptible to exposure measurement errors. The higher correlations in concentrations and source contributions between different locations suggest less spatial variability, resulting in less exposure measurement errors. When concentrations and/or contributions were compared to regional averages, correlations were generally higher than between-site correlations. This suggests that for assigning exposures for health effects studies, using regional average concentrations or contributions from several PM2.5 monitors is more reliable than using data from the nearest central monitor. PMID:21429560

Comparison of Personal PM2.5 Exposure in Various Micro-Environments during Haze and Clean Days in Nanjing

NASA Astrophysics Data System (ADS)

Zhang, T.

2015-12-01

There is a long term trend of haze in East China. As a main component of haze, fine particle (PM2.5) in various micro-environments (MEs) is a cause for concern regarding the environment and public health. To estimate individual PM2.5 exposures in distinct, non-residential MEs and to determine exposure characteristics during haze and clean days, we conducted personal PM2.5 monitoring with portable PM2.5 personal environment monitors (MicroPEM) in 19 indoor/outdoor MEs in Nanjing, and compared personal exposure data with ambient PM2.5 levels. Personal PM2.5 exposure patterns displayed notable spatial variance, peaking in snack streets and restaurants and dipping in subways and labs. Under both haze and non-haze conditions, different characteristics of MEs and the background PM2.5 level jointly determine the spatial variance of individual exposure. Indoor MEs with better ventilation systems led to lower personal PM2.5 exposure levels. During haze days, impact from high ambient PM2.5 overwhelms influence from other factors and dominates personal exposure trends.

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 Improvement of Spatial-Temporal PM2.5 Resolution in Taiwan by Using Data Assimilation Method

NASA Astrophysics Data System (ADS)

Lin, Yong-Qing; Lin, Yuan-Chien

2017-04-01

Forecasting air pollution concentration, e.g., the concentration of PM2.5, is of great significance to protect human health and the environment. Accurate prediction of PM2.5 concentrations is limited in number and the data quality of air quality monitoring stations. The spatial and temporal variations of PM2.5 concentrations are measured by 76 National Air Quality Monitoring Stations (built by the TW-EPA) in Taiwan. The National Air Quality Monitoring Stations are costly and scarce because of the highly precise instrument and their size. Therefore, many places still out of the range of National Air Quality Monitoring Stations. Recently, there are an enormous number of portable air quality sensors called "AirBox" developed jointly by the Taiwan government and a private company. By virtue of its price and portative, the AirBox can provide higher resolution of space-time PM2.5 measurement. However, the spatiotemporal distribution and data quality are different between AirBox and National Air Quality Monitoring Stations. To integrate the heterogeneous PM2.5 data, the data assimilation method should be performed before further analysis. In this study, we propose a data assimilation method based on Ensemble Kalman Filter (EnKF), which is a variant of classic Kalman Filter, can be used to combine additional heterogeneous data from different source while modeling to improve the estimation of spatial-temporal PM2.5 concentration. The assimilation procedure uses the advantages of the two kinds of heterogeneous data and merges them to produce the final estimation. The results have shown that by combining AirBox PM2.5 data as additional information in our model based EnKF can bring the better estimation of spatial-temporal PM2.5 concentration and improve the it's space-time resolution. Under the approach proposed in this study, higher spatial-temporal resoultion could provide a very useful information for a better spatial-temporal data analysis and further environmental management, such as air pollution source localization and micro-scale air pollution analysis. Keywords: PM2.5, Data Assimilation, Ensemble Kalman Filter, Air Quality

Using big data from air quality monitors to evaluate indoor PM2.5 exposure in buildings: Case study in Beijing.

PubMed

Zuo, JinXing; Ji, Wei; Ben, YuJie; Hassan, Muhammad Azher; Fan, WenHong; Bates, Liam; Dong, ZhaoMin

2018-05-19

Due to time- and expense- consuming of conventional indoor PM 2.5 (particulate matter with aerodynamic diameter of less than 2.5 μm) sampling, the sample size in previous studies was generally small, which leaded to high heterogeneity in indoor PM 2.5 exposure assessment. Based on 4403 indoor air monitors in Beijing, this study evaluated indoor PM 2.5 exposure from 15th March 2016 to 14th March 2017. Indoor PM 2.5 concentration in Beijing was estimated to be 38.6 ± 18.4 μg/m 3 . Specifically, the concentration in non-heating season was 34.9 ± 15.8 μg/m 3 , which was 24% lower than that in heating season (46.1 ± 21.2 μg/m 3 ). A significant correlation between indoor and ambient PM 2.5 (p < 0.05) was evident with an infiltration factor of 0.21, and the ambient PM 2.5 contributed approximately 52% and 42% to indoor PM 2.5 for non-heating and heating seasons, respectively. Meanwhile, the mean indoor/outdoor (I/O) ratio was estimated to be 0.73 ± 0.54. Finally, the adjusted PM 2.5 exposure level integrating the indoor and outdoor impact was calculated to be 46.8 ± 27.4 μg/m 3 , which was approximately 42% lower than estimation only relied on ambient PM 2.5 concentration. This study is the first attempt to employ big data from commercial air monitors to evaluate indoor PM 2.5 exposure and risk in Beijing, which may be instrumental to indoor PM 2.5 pollution control. Copyright © 2018 Elsevier Ltd. All rights reserved.

The impact of photovoltaic (PV) installations on downwind particulate matter concentrations: Results from field observations at a 550-MWAC utility-scale PV plant.

PubMed

Ravikumar, Dwarakanath; Sinha, Parikhit

2017-10-01

With utility-scale photovoltaic (PV) projects increasingly developed in dry and dust-prone geographies with high solar insolation, there is a critical need to analyze the impacts of PV installations on the resulting particulate matter (PM) concentrations, which have environmental and health impacts. This study is the first to quantify the impact of a utility-scale PV plant on PM concentrations downwind of the project site. Background, construction, and post-construction PM 2.5 and PM 10 (PM with aerodynamic diameters <2.5 and <10 μm, respectively) concentration data were collected from four beta attenuation monitor (BAM) stations over 3 yr. Based on these data, the authors evaluate the hypothesis that PM emissions from land occupied by a utility-scale PV installation are reduced after project construction through a wind-shielding effect. The results show that the (1) confidence intervals of the mean PM concentrations during construction overlap with or are lower than background concentrations for three of the four BAM stations; and (2) post-construction PM 2.5 and PM 10 concentrations downwind of the PV installation are significantly lower than the background concentrations at three of the four BAM stations. At the fourth BAM station, downwind post-construction PM 2.5 and PM 10 concentrations increased marginally by 5.7% and 2.6% of the 24-hr ambient air quality standards defined by the U.S. Environmental Protection Agency, respectively, when compared with background concentrations, with the PM 2.5 increase being statistically insignificant. This increase may be due to vehicular emissions from an access road near the southwest corner of the site or a drainage berm near the south station. The findings demonstrate the overall environmental benefit of downwind PM emission abatement from a utility-scale PV installation in desert conditions due to wind shielding. With PM emission reductions observed within 10 months of completion of construction, post-construction monitoring of downwind PM levels may be reduced to a 1-yr period for other projects with similar soil and weather conditions. This study is the first to analyze impact of a utility photovoltaic (PV) project on downwind particulate matter (PM) concentration in desert conditions. The PM data were collected at four beta attenuation monitor stations over a 3-yr period. The post-construction PM concentrations are lower than background concentrations at three of four stations, therefore supporting the hypothesis of post-construction wind shielding from PV installations. With PM emission reductions observed within 10 months of completion of construction, postconstruction monitoring of downwind PM levels may be reduced to a 1-yr period for other PV projects with similar soil and weather conditions.

Comparison of geostatistical interpolation and remote sensing techniques for estimating long-term exposure to ambient PM2.5 concentrations across the continental United States.

PubMed

Lee, Seung-Jae; Serre, Marc L; van Donkelaar, Aaron; Martin, Randall V; Burnett, Richard T; Jerrett, Michael

2012-12-01

A better understanding of the adverse health effects of chronic exposure to fine particulate matter (PM2.5) requires accurate estimates of PM2.5 variation at fine spatial scales. Remote sensing has emerged as an important means of estimating PM2.5 exposures, but relatively few studies have compared remote-sensing estimates to those derived from monitor-based data. We evaluated and compared the predictive capabilities of remote sensing and geostatistical interpolation. We developed a space-time geostatistical kriging model to predict PM2.5 over the continental United States and compared resulting predictions to estimates derived from satellite retrievals. The kriging estimate was more accurate for locations that were about 100 km from a monitoring station, whereas the remote sensing estimate was more accurate for locations that were > 100 km from a monitoring station. Based on this finding, we developed a hybrid map that combines the kriging and satellite-based PM2.5 estimates. We found that for most of the populated areas of the continental United States, geostatistical interpolation produced more accurate estimates than remote sensing. The differences between the estimates resulting from the two methods, however, were relatively small. In areas with extensive monitoring networks, the interpolation may provide more accurate estimates, but in the many areas of the world without such monitoring, remote sensing can provide useful exposure estimates that perform nearly as well.

Fine PM measurements: personal and indoor air monitoring.

PubMed

Jantunen, M; Hänninen, O; Koistinen, K; Hashim, J H

2002-12-01

This review compiles personal and indoor microenvironment particulate matter (PM) monitoring needs from recently set research objectives, most importantly the NRC published "Research Priorities for Airborne Particulate Matter (1998)". Techniques and equipment used to monitor PM personal exposures and microenvironment concentrations and the constituents of the sampled PM during the last 20 years are then reviewed. Development objectives are set and discussed for personal and microenvironment PM samplers and monitors, for filter materials, and analytical laboratory techniques for equipment calibration, filter weighing and laboratory climate control. The progress is leading towards smaller sample flows, lighter, silent, independent (battery powered) monitors with data logging capacity to store microenvironment or activity relevant sensor data, advanced flow controls and continuous recording of the concentration. The best filters are non-hygroscopic, chemically pure and inert, and physically robust against mechanical wear. Semiautomatic and primary standard equivalent positive displacement flow meters are replacing the less accurate methods in flow calibration, and also personal sampling flow rates should become mass flow controlled (with or without volumetric compensation for pressure and temperature changes). In the weighing laboratory the alternatives are climatic control (set temperature and relative humidity), and mechanically simpler thermostatic heating, air conditioning and dehumidification systems combined with numerical control of temperature, humidity and pressure effects on flow calibration and filter weighing.

Grade One: Math Computation. Case Study #1

ERIC Educational Resources Information Center

Powell, Sarah R.; Seethaler, Pamela M.

2007-01-01

The purpose of this case study is to highlight the integral role that progress monitoring (PM) plays throughout any Response to Intervention (RTI) process. This example uses a three-level, responsiveness-to-intervention (RTI) method for identifying students with learning difficulties. Using a fictional first-grade classroom as the setting for…

The utility of polarization modulation infrared reflection absorption spectroscopy (PM-IRRAS) in surface and in situ studies: new data processing and presentation approach.

PubMed

Monyoncho, Evans A; Zamlynny, Vlad; Woo, Tom K; Baranova, Elena A

2018-05-29

Infrared spectroscopy is a powerful non-destructive technique for the identification and quantification of organic molecules widely used in scientific studies. For many years, efforts have been made to adopt this technique for the in situ monitoring of reactions. From these efforts, polarization modulation infrared reflection absorption spectroscopy (PM-IRRAS) was developed three decades ago. Unfortunately, because of the complexity of data processing and interpretation, PM-IRRAS had been avoided in lieu of the single potential alteration infrared spectroscopy (SPAIRS) and subtractively normalized interfacial Fourier transform infrared (SNIFTIR). In this work, we present a new approach for PM-IRRAS data processing and presentation, which provides more insight into in situ and surface studies besides dramatically improving the S/N. In this new approach, we recommend three complementary methods of data treatment (eqn (7), (9) and (10)) as the new protocols for presenting PM-IRRAS data. These equations are robust in visualising the surface processes at the solid-liquid and solid-gas interphases. Eqn (7) contrasts the surface adsorbed species with respect to the isotropic background with or without the influence of the applied potential. Eqn (9) highlights the surface potential-driven changes between the sample and the reference spectra. Eqn (10) focuses on the bulk-phase (solution/gas and surface species) potential-driven changes between the sample and the reference spectra, and hence it can be used to track the production of species, which desorb from the surface upon their formation. Examples of ethanol electro-oxidation reaction are provided as a test system for in situ studies and PVP deposited on glassy carbon for thin-film studies to illustrate the utility of the new PM-IRRAS data handling protocol, which is poised to improve the understanding of the chemistry and physics of surface processes.

Advances in Satellite Remote Sensing of Particulate Air Pollution: From MISR to MAIA

NASA Astrophysics Data System (ADS)

Diner, D. J.; Burke, K.; Xu, F.; Garay, M. J.; Kalashnikova, O. V.; Liu, Y.; Meng, X.; Wang, J.; Martin, R.; Ostro, B.

2017-12-01

Airborne particulate matter (PM) is a well-known cause of cardiovascular and respiratory disease. To estimate human exposure to PM pollution, satellite instruments such as the Terra Multi-angle Imaging SpectroRadiometer (MISR) and the Moderate resolution Imaging Spectroradiometer (MODIS) have been used in conjunction with surface monitors to map near-surface PM concentrations. The relative toxicity of different size and compositional mixtures of PM is not well understood. To address this, we are developing the Multi-Angle Imager for Aerosols (MAIA) investigation. The satellite instrument extends MISR's multiangular visible and near-infrared (VNIR) spectral coverage to 14 bands in the ultraviolet, VNIR, and shortwave IR; three of the bands are polarimetric to enhance sensitivity to aerosol size and composition. To constrain the retrievals, the observations will be combined with data from surface monitors and the WRF-Chem and GEOS-Chem chemical transport models. Existing surface PM speciation monitors will be supplemented by adding new stations to the Surface PARTiculate mAtter Network (SPARTAN). Unlike MISR, MAIA is a targeting instrument. Primary areas of interest include metropolitan areas in North and South America, Europe, the Middle East, Africa, India, and East Asia. PM retrieval algorithms are being developed using data from MISR and the high-altitude Airborne Multiangle SpectroPolarimetric Imager (AirMSPI). Epidemiologists on the MAIA science team will use the derived PM data products and birth, death, and hospital records to investigate adverse health impacts of different types of airborne particulates. MAIA's earliest possible launch date is mid-2020, making it possible for the data to be complemented by global observations from Terra as well as high temporal resolution atmospheric chemistry measurements from TEMPO (Tropospheric Emissions: Monitoring Pollution), GEMS (Geostationary Environment Monitoring Spectrometer), and Sentinel-4.

Primary particulate matter from ocean-going engines in the Southern California Air Basin.

PubMed

Agrawal, Harshit; Eden, Rudy; Zhang, Xinqiu; Fine, Philip M; Katzenstein, Aaron; Miller, J Wayne; Ospital, Jean; Teffera, Solomon; Cocker, David R

2009-07-15

The impact of primary fine particulate matter (PM2.5) from ship emissions within the Southern California Air Basin is quantified by comparing in-stack vanadium (V) and nickel (Ni) measurements from in-use ocean-going vessels (OGVs) with ambient measurements made at 10 monitoring stations throughout Southern California. V and Ni are demonstrated as robust markers for the combustion of heavy fuel oil in OGVs, and ambient measurements of fine particulate V and Ni within Southern California are shown to decrease inversely with increased distance from the ports of Los Angeles and Long Beach (ports). High levels of V and Ni were observed from in-stack emission measurements conducted on the propulsion engines of two different in-use OGVs. The in-stack V and Ni emission rates (g/h) normalized by the V and Ni contents in the fuel tested correlates with the stack total PM emission rates (g/h). The normalized emission rates are used to estimate the primary PM2.5 contributions from OGVs at 10 monitoring locations within Southern California. Primary PM2.5 contributions from OGVs were found to range from 8.8% of the total PM2.5 at the monitoring location closest to the port (West Long Beach) to 1.4% of the total PM2.5 at the monitoring location 80 km inland (Rubidoux). The calculated OGV contributions to ambient PM2.5 measurements at the 10 monitoring sites agree well with estimates developed using an emission inventory based regional model. Results of this analysis will be useful in determining the impacts of primary particulate emissions from OGVs upon worldwide communities downwind of port operations.

A Comparison of Particulate Matter from Biomass-Burning Rural and Non-Biomass-Burning Urban Households in Northeastern China

PubMed Central

Jiang, Ruoting; Bell, Michelle L.

2008-01-01

Background Biomass fuel is the primary source of domestic fuel in much of rural China. Previous studies have not characterized particle exposure through time–activity diaries or personal monitoring in mainland China. Objectives In this study we characterized indoor and personal particle exposure in six households in northeastern China (three urban, three rural) and explored differences by location, cooking status, activity, and fuel type. Rural homes used biomass. Urban homes used a combination of electricity and natural gas. Methods Stationary monitors measured hourly indoor particulate matter (PM) with an aerodynamic diameter ≤ 10 μm (PM10) for rural and urban kitchens, urban sitting rooms, and outdoors. Personal monitors for PM with an aerodynamic diameter ≤ 2.5 μm (PM2.5) were employed for 10 participants. Time–activity patterns in 30-min intervals were recorded by researchers for each participant. Results Stationary monitoring results indicate that rural kitchen PM10 levels are three times higher than those in urban kitchens during cooking. PM10 was 6.1 times higher during cooking periods than during noncooking periods for rural kitchens. Personal PM2.5 levels for rural cooks were 2.8–3.6 times higher than for all other participant categories. The highest PM2.5 exposures occurred during cooking periods for urban and rural cooks. However, rural cooks had 5.4 times higher PM2.5 levels during cooking than did urban cooks. Rural cooks spent 2.5 times more hours per day cooking than did their urban counterparts. Conclusions These findings indicate that biomass burning for cooking contributes substantially to indoor particulate levels and that this exposure is particularly elevated for cooks. Second-by-second personal PM2.5 exposures revealed differences in exposures by population group and strong temporal heterogeneity that would be obscured by aggregate metrics. PMID:18629313

A comparison of particulate matter from biomass-burning rural and non-biomass-burning urban households in northeastern China.

PubMed

Jiang, Ruoting; Bell, Michelle L

2008-07-01

Biomass fuel is the primary source of domestic fuel in much of rural China. Previous studies have not characterized particle exposure through time-activity diaries or personal monitoring in mainland China. In this study we characterized indoor and personal particle exposure in six households in northeastern China (three urban, three rural) and explored differences by location, cooking status, activity, and fuel type. Rural homes used biomass. Urban homes used a combination of electricity and natural gas. Stationary monitors measured hourly indoor particulate matter (PM) with an aerodynamic diameter < or = 10 microm (PM10) for rural and urban kitchens, urban sitting rooms, and outdoors. Personal monitors for PM with an aerodynamic diameter < or = 2.5 microm (PM2.5) were employed for 10 participants. Time-activity patterns in 30-min intervals were recorded by researchers for each participant. Stationary monitoring results indicate that rural kitchen PM10 levels are three times higher than those in urban kitchens during cooking. PM10 was 6.1 times higher during cooking periods than during noncooking periods for rural kitchens. Personal PM2.5 levels for rural cooks were 2.8-3.6 times higher than for all other participant categories. The highest PM2.5 exposures occurred during cooking periods for urban and rural cooks. However, rural cooks had 5.4 times higher PM2.5 levels during cooking than did urban cooks. Rural cooks spent 2.5 times more hours per day cooking than did their urban counterparts. These findings indicate that biomass burning for cooking contributes substantially to indoor particulate levels and that this exposure is particularly elevated for cooks. Second-by-second personal PM2.5 exposures revealed differences in exposures by population group and strong temporal heterogeneity that would be obscured by aggregate metrics.

Decreasing trends of suspended particulate matter and PM2.5 concentrations in Tokyo, 1990-2010.

PubMed

Hara, Kunio; Homma, Junichi; Tamura, Kenji; Inoue, Mariko; Karita, Kanae; Yano, Eiji

2013-06-01

In Tokyo, the annual average suspended particulate matter (SPM) and PM2.5 concentrations have decreased in the past two decades. The present study quantitatively evaluated these decreasing trends using data from air-pollution monitoring stations. Annual SPM and PM2.5 levels at 83 monitoring stations and hourly SPM and PM2.5 levels at four monitoring stations in Tokyo, operated by the Tokyo Metropolitan Government, were used for analysis, together with levels of co-pollutants and meteorological conditions. Traffic volume in Tokyo was calculated from the total traveling distance of vehicles as reported by the Ministry of Land, Infrastructure, Transport, and Tourism. High positive correlations between SPM levels and nitrogen oxide levels, sulfur dioxide levels, and traffic volume were determined. The annual average SPM concentration declined by 62.6%from 59.4 microg/m3 in 1994 to 22.2 microg/m3 in 2010, and PM2.5 concentration also declined by 49.8% from 29.3 microg/m3 in 2001 to 14.7 microg/m3 in 2010. Likewise, the frequencies of hourly average SPM and PM2.5 concentrations exceeding the daily guideline values have significantly decreased since 2001 and the hourly average SPM or PM2.5 concentrations per traffic volume for each time period have also significantly decreased since 2001. However SPM and PM2.5 concentrations increased at some monitoring stations between 2004 and 2006 and from 2009 despite strengthened environmental regulations and improvements in vehicle engine performance. The annual average SPM and PM2.5 concentrations were positively correlated with traffic volumes and in particular with the volume of diesel trucks. These results suggest that the decreasing levels of SPM and PM2.5 in Tokyo may be attributable to decreased traffic volumes, along with the effects of stricter governmental regulation and improvements to vehicle engine performance, including the fitting of devices for exhaust emission reduction.

Spatial and seasonal variation of particulate matter (PM10 and PM2.5) in Middle Eastern classrooms

NASA Astrophysics Data System (ADS)

Elbayoumi, Maher; Ramli, Nor Azam; Md Yusof, Noor Faizah Fitri; Al Madhoun, Wesam

2013-12-01

Monitoring of PM10 and PM2.5 particularly in school microenvironments is extremely important due to their impact on the global burden of disease. PM10 and PM2.5 levels were monitored inside and outside the classrooms of twelve naturally ventilated schools located in Gaza strip, Palestine. The measurements were carried out using hand held particulate matter instrument during fall, winter and spring seasons from October 2011 to May 2012. The average concentration of indoor PM10 was 349.49 (±196.57) μg m-3 and for PM2.5 was 103.96 (±84.96) μg m-3. The indoor/outdoor ratios for PM10 and PM2.5 were found to be much greater than 1.00 for all case study schools due to resuspension of deposited particles from the floors. Furthermore, strong correlations were found between indoor-outdoor PM10 and PM2.5. The variations of PM10 and PM2.5 concentrations were significant for the three seasons. During winter, the mean indoor PM10 was 1.30 and 2.50 times higher than fall and spring concentrations respectively. Meanwhile, PM2.5 concentration in winter was 3.00 times higher than fall and spring concentrations. In relation to spatial variation, the concentration of PM10 in the lower storey level was significantly higher than the classrooms located in the higher storey level.

Spatiotemporal variation of PM1 pollution in China

NASA Astrophysics Data System (ADS)

Chen, Gongbo; Morawska, Lidia; Zhang, Wenyi; Li, Shanshan; Cao, Wei; Ren, Hongyan; Wang, Boguang; Wang, Hao; Knibbs, Luke D.; Williams, Gail; Guo, Jianping; Guo, Yuming

2018-04-01

Understanding spatiotemporal variation of PM1 (mass concentrations of particles with aerodynamic diameter < 1 μm) is important due to its adverse effects on health, which is potentially more severe for its deeper penetrating capability into human bodies compared with larger particles. This study aimed to quantify the spatial and temporal distribution of PM1 across China as well as its ratio with PM2.5 (<2.5 μm) and relationships with meteorological parameters in order to deepen our knowledge of the drivers of air pollution in China. Ground-based monitoring PM1 and PM2.5 measurements, along with collocated meteorological data, were obtained from 96 stations in China for the period from November 2013 to December 2014. Generalized additive models were employed to examine the relationships between PM1 and meteorological parameters. We showed that PM1 concentrations were the lowest in summer and the highest in winter. Across China, the PM1/PM2.5 ratios ranged from 0.75-0.88, reaching higher levels in January and lower in August. For spatial distribution, higher PM1/PM2.5 ratios (>0.9) were observed in North-Eastern China, North China Plain, coastal areas of Eastern China and Sichuan Basin while lower ratios (<0.7) were present in remote areas in North-Western and Northern China (e.g., Xinjiang, Tibet and Inner Mongolia). Higher PM1/PM2.5 ratios were observed on heavily polluted days and lower ratios on clean days. The high PM1/PM2.5 ratios observed in China suggest that smaller particles, PM1 fraction, are key drivers of air pollution, and that they effectively account for the majority of PM2.5 concentrations. This emphasised the role of combustion process and secondary particle formation, the sources of PM1, and the significance of controlling them.

Performance monitoring in nicotine dependence: Considering integration of recent reinforcement history.

PubMed

Butler, Kevin; Rusted, Jennifer; Gard, Paul; Jackson, Anne

2017-05-01

Impaired monitoring of errors and conflict (performance monitoring; PM) is well documented in substance dependence (SD) including nicotine dependence and may contribute to continued drug use. Contemporary models of PM and complementary behavioural evidence suggest that PM works by integrating recent reinforcement history rather than evaluating individual behaviours. Despite this, studies of PM in SD have typically used indices derived from reaction to task error or conflict on individual trials. Consequently impaired integration of reinforcement history during action selection tasks requiring behavioural control in SD populations has been underexplored. A reinforcement learning task assessed the ability of abstinent, satiated, former and never smokers (N=60) to integrate recent reinforcement history alongside a more typical behavioural index of PM reflecting the degree of reaction time slowing following an error (post-punishment slowing; PPS). On both indices there was a consistent pattern in PM data: Former smokers had the greatest and satiated smokers the poorest PM. Specifically satiated smokers had poorer reinforcement integration than former (p=0.005) and never smokers (p=0.041) and had less post-punishment slowing than former (p<0.001), never (p=0.003) and abstinent smokers (p=0.026). These are the first data examining the effects of smoking status on PM that use an integration of reinforcement history metric. The concordance of the reinforcement integration and PPS data suggest that this could be a promising method to interrogate PM in future studies. PM is influenced by smoking status. As PM is associated with adapting behaviour, poor PM in satiated smokers may contribute towards continued smoking despite negative consequences. Former smokers show elevated PM suggesting this may be a good relapse prevention target for individuals struggling to remain abstinent however prospective and intervention studies are needed. A better understanding of PM deficits in terms of reinforcement integration failure may stimulate development of novel treatment approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

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

The value of using seasonality and meteorological variables to model intra-urban PM2.5 variation

NASA Astrophysics Data System (ADS)

Olvera Alvarez, Hector A.; Myers, Orrin B.; Weigel, Margaret; Armijos, Rodrigo X.

2018-06-01

A yearlong air monitoring campaign was conducted to assess the impact of local temperature, relative humidity, and wind speed on the temporal and spatial variability of PM2.5 in El Paso, Texas. Monitoring was conducted at four sites purposely selected to capture the local traffic variability. Effects of meteorological events on seasonal PM2.5 variability were identified. For instance, in winter low-wind and low-temperature conditions were associated with high PM2.5 events that contributed to elevated seasonal PM2.5 levels. Similarly, in spring, high PM2.5 events were associated with high-wind and low-relative humidity conditions. Correlation coefficients between meteorological variables and PM2.5 fluctuated drastically across seasons. Specifically, it was observed that for most sites correlations between PM2.5 and meteorological variables either changed from positive to negative or dissolved depending on the season. Overall, the results suggest that mixed effects analysis with season and site as fixed factors and meteorological variables as covariates could increase the explanatory value of LUR models for PM2.5.

Future thinking instructions improve prospective memory performance in adolescents.

PubMed

Altgassen, Mareike; Kretschmer, Anett; Schnitzspahn, Katharina Marlene

2017-07-01

Studies on prospective memory (PM) development in adolescents point to age-related increases through to adulthood. The goal of the present study was to examine whether instructing adolescents to engage in an episodic prospection of themselves executing future actions (i.e., future thinking) when forming an intention would improve their PM performance and reduce age-related differences. Further, we set out to explore whether future thinking instructions result in stronger memory traces and/or stronger cue-context associations by evaluating retrospective memory for the PM cues after task completion and monitoring costs during PM task processing. Adolescents and young adults were allocated to either the future thinking, repeated-encoding or standard condition. As expected, adolescents had fewer correct PM responses than young adults. Across age groups, PM performance in the standard condition was lower than in the other encoding conditions. Importantly, the results indicate a significant interaction of age by encoding condition. While adolescents benefited most from future thinking instructions, young adults performed best in the repeated-encoding condition. The results also indicate that the beneficial effects of future thinking may result from deeper intention-encoding through the simulation of future task performance.

Sources and Processes Affecting Particulate Matter Pollution over North China

NASA Astrophysics Data System (ADS)

Zhang, L.; Shao, J.; Lu, X.; Zhao, Y.; Gong, S.; Henze, D. K.

2015-12-01

Severe fine particulate matter (PM2.5) pollution over North China has received broad attention worldwide in recent years. Better understanding the sources and processes controlling pollution over this region is of great importance with urgent implications for air quality policy. We will present a four-dimensional variational (4D-Var) data assimilation system using the GEOS-Chem chemical transport model and its adjoint model at 0.25° × 0.3125° horizontal resolution, and apply it to analyze the factors affecting PM2.5 concentrations over North China. Hourly surface observations of PM2.5 and sulfur dioxide (SO2) from the China National Environmental Monitoring Center (CNEMC) can be assimilated into the model to evaluate and constrain aerosol (primary and precursors) emissions. Application of the data assimilation system to the APEC period (the Asia-Pacific Economic Cooperation summit; 5-11 November 2014) shows that 46% of the PM2.5 pollution reduction during APEC ("The APEC Blue") can be attributed to meteorology conditions and the rest 54% to emission reductions due to strict emission controls. Ammonia emissions are shown to significantly contribute to PM2.5 over North China in the fall. By converting sulfuric acid and nitric acid to longer-lived ammonium sulfate and ammonium nitrate aerosols, ammonia plays an important role in promoting their regional transport influences. We will also discuss the pathways and mechanisms of external long-range transport influences to the PM2.5 pollution over North China.

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.

Remote control improves quality of life in elderly pacemaker patients versus standard ambulatory-based follow-up.

PubMed

Comoretto, Rosanna Irene; Facchin, Domenico; Ghidina, Marco; Proclemer, Alessandro; Gregori, Dario

2017-08-01

Health-related quality of life (HRQoL) improves shortly after pacemaker (PM) implantation. No studies have investigated the HRQoL trend for elderly patients with a remote device monitoring follow-up system. Using EuroQol-5D Questionnaire and the PM-specific Assessment of Quality of Life and Related Events Questionnaire, HRQoL was measured at baseline and then repeatedly during the 6 months following PM implantation in a cohort of 42 consecutive patients. Twenty-five patients were followed-up with standard outpatient visits, while 17 used a remote monitoring system. Aquarel scores were significantly higher in patients with remote device monitoring system regarding chest discomfort and arrhythmia subscales the first month after PM implant and remained stable until 6 months. Remote monitoring affected the rate of HRQoL improvement in the first 3 months after pacemaker implantation more than ambulatory follow-up. Remote device monitoring has a significant impact on HRQoL in pacemaker patients, increasing its levels up to 6 months after implant. © 2017 John Wiley & Sons, Ltd.

78 FR 27898 - Approval and Promulgation of State Implementation Plan Revisions; Infrastructure Requirements for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-13

... arithmetic mean PM 2.5 concentration from single or multiple community- oriented monitors, and 65 [mu]g/m\\3...-oriented monitor within an area. In addition, the 24-hour PM 10 standard was revised to be based on the...): Stationary source monitoring and reporting. 110(a)(2)(G): Emergency powers. 110(a)(2)(H): Future SIP...

Journey-time exposure to particulate air pollution

NASA Astrophysics Data System (ADS)

Gulliver, John; Briggs, David J.

Journey-time exposures to particulate air pollution were investigated in Leicester, UK, between January and March 2005. Samples of TSP, PM 10, PM 2.5, and PM 1 were simultaneously collected using light scattering devices whilst journeys were made by walking an in-car. Over a period of two months, 33 pairs of walking and in-car measurements were collected along two circular routes. Average exposures while walking were seen to be higher than those found in-car for each of the particle fractions: average walking to in-car ratios were 1.2 (± 0.6), 1.5 (± 0.6), 1.3 (± 0.6), and 1.4 (± 0.6) μg m -3 for coarse (TSP-PM 10), intermediate (PM 10-PM 2.5), fine (PM 2.5-PM 1), and very fine particles (PM 1), respectively. Correlations between walking and in-car exposures were seen to be weak for coarse particles ( r=0.10, p=0.58), moderate for the intermediate particles ( r=0.49, p<0.01) but strong for fine ( r=0.89, p<0.01) and very fine ( r=0.90, P<0.01) particles. PM 10 exposures while walking were on average 70% higher than a nearby roadside fixed-site monitor whilst in-car exposures were 25% higher than the same fixed-site monitor. Particles with an aerodynamic diameter of less than 2.5 μm were seen to be highly correlated between walking and in-car particle exposures and a rural fixed-site monitor about 30 km south of Leicester.

An overview of the PM10 pollution problem, in the Metropolitan Area of Athens, Greece. Assessment of controlling factors and potential impact of long range transport.

PubMed

Grivas, G; Chaloulakou, A; Kassomenos, P

2008-01-15

The present study analyzes PM(10) concentration data collected by the Greek air quality monitoring network at 8 sites over the Greater Athens Area, for the period of 2001-2004. The primary objectives were to assess the degree of compliance with the EU-legislated air quality standard for PM(10) and also provide an overall statistical examination of the factors controlling the seasonal and spatial variation of concentrations, over the wider urban agglomeration. Daily concentrations, averaged over the whole study period, ranged between 32.3 and 60.9 microg m(-3). The four-year average concentration of PM(10) at five sites exceeded the annual limit value of 40 microg m(-3), while most of the sites surpassed the allowed percentage of exceedances of the daily limit value (50 microg m(-3)), for each of the four years. The seasonal variation of PM(10) levels was not found to be uniform across the eight sites, with average cold-period concentrations being higher at four of them and warm period concentrations being significantly higher at three sites, which also displayed recurring annual variation of monthly concentrations. Concentration levels displayed moderate spatial heterogeneity. Nevertheless significant inter-site correlations were observed (ranging between 0.55 and 085). The determination of the spatial correlation levels relied mainly on site types rather than on inter-site distances. Monitoring sites were classified accordingly using cluster analysis in two groups presenting distinct spatiotemporal variation and affected by different particle formation processes. The group including urban sites was mainly affected by primary, combustion-related processes and especially vehicular traffic, as it was also deduced through the examination of the diurnal distribution of particulate levels and through factor analysis. On the contrary, suburban background sites seemed more affected by particle transport from more polluted neighboring areas and secondary particle formation through gaseous precursors, both processes aided from favoring meteorological conditions. The association of the PM(10) levels with backwards trajectories was also examined, in an attempt to account for the possible long range transport of particles in Athens. It was found that a notable part of area-wide episodic events could be attributed to trans-boundary transport of particles, with the origins of some severe dust outbreaks traced back to the Sahara desert and the Western Mediterranean.

“Working to shape what society's expectations of us should be”: Philip Morris' societal alignment strategy

PubMed Central

Yang, J S; Malone, R E

2009-01-01

Background A key element of Philip Morris's (PM's) corporate social responsibility initiatives is “societal alignment”, defined as “strategies and programs to meet society's expectations of a responsible tobacco company”. This study explored the genesis and implementation of Philip Morris' (PM) societal alignment efforts. Methods The study retrieved and analysed approximately 375 previously undisclosed PM documents now available electronically. Using an iterative process, the study categorised themes and prepared a case analysis. Results Beginning in 1999, PM sought to become “societally aligned” by identifying expectations of a responsible tobacco company through public opinion research and developing and publicising programs to meet those expectations. Societal alignment was undertaken within the US and globally to ensure an environment favourable to PM's business objectives. Despite PM's claims to be “changing”, however, societal alignment in practice was highly selective. PM responded to public “expectations” largely by retooling existing positions and programs, while entirely ignoring other expectations that might have interfered with its business goals. It also appears that convincing employees of the value and authenticity of societal alignment was difficult. Conclusions As implementation of the Framework Convention on Tobacco Control proceeds, tobacco control advocates should closely monitor development of such “alignment” initiatives and expose the motivations and contradictions they reveal. PMID:18845623

"Working to shape what society's expectations of us should be": Philip Morris' societal alignment strategy.

PubMed

Yang, J S; Malone, R E

2008-12-01

A key element of Philip Morris's (PM's) corporate social responsibility initiatives is "societal alignment", defined as "strategies and programs to meet society's expectations of a responsible tobacco company". This study explored the genesis and implementation of Philip Morris' (PM) societal alignment efforts. The study retrieved and analysed approximately 375 previously undisclosed PM documents now available electronically. Using an iterative process, the study categorised themes and prepared a case analysis. Beginning in 1999, PM sought to become "societally aligned" by identifying expectations of a responsible tobacco company through public opinion research and developing and publicising programs to meet those expectations. Societal alignment was undertaken within the US and globally to ensure an environment favourable to PM's business objectives. Despite PM's claims to be "changing", however, societal alignment in practice was highly selective. PM responded to public "expectations" largely by retooling existing positions and programs, while entirely ignoring other expectations that might have interfered with its business goals. It also appears that convincing employees of the value and authenticity of societal alignment was difficult. As implementation of the Framework Convention on Tobacco Control proceeds, tobacco control advocates should closely monitor development of such "alignment" initiatives and expose the motivations and contradictions they reveal.

EVALUATION OF THE SMPS-APS SYSTEM AS A CONTINUOUS MONITOR FOR MEASURING PM2.5, PM10 AND COARSE (PM2.5-10) CONCENTRATIONS. (R827352C011)

EPA Science Inventory

Respirable particulate matter (PM) has been linked to mortality and morbidity by a variety of epidemiological studies. This research has led to the creation of a new PM standard for particles with diameters <2.5 μm (PM_2.5). Since the conclusion of these studie...

Spatial and temporal variability of fine particle composition and source types in five cities of Connecticut and Massachusetts.

PubMed

Lee, Hyung Joo; Gent, Janneane F; Leaderer, Brian P; Koutrakis, Petros

2011-05-01

To protect public health from PM(2.5) air pollution, it is critical to identify the source types of PM(2.5) mass and chemical components associated with higher risks of adverse health outcomes. Source apportionment modeling using Positive Matrix Factorization (PMF), was used to identify PM(2.5) source types and quantify the source contributions to PM(2.5) in five cities of Connecticut and Massachusetts. Spatial and temporal variability of PM(2.5) mass, components and source contributions were investigated. PMF analysis identified five source types: regional pollution as traced by sulfur, motor vehicle, road dust, oil combustion and sea salt. The sulfur-related regional pollution and traffic source type were major contributors to PM(2.5). Due to sparse ground-level PM(2.5) monitoring sites, current epidemiological studies are susceptible to exposure measurement errors. The higher correlations in concentrations and source contributions between different locations suggest less spatial variability, resulting in less exposure measurement errors. When concentrations and/or contributions were compared to regional averages, correlations were generally higher than between-site correlations. This suggests that for assigning exposures for health effects studies, using regional average concentrations or contributions from several PM(2.5) monitors is more reliable than using data from the nearest central monitor. Copyright © 2011 Elsevier B.V. All rights reserved.

LINKAGES ACROSS PM POLICY AND RESEARCH: EXAMINING THE POLICY RELEVANT FINDINGS FROM THE PM2.5 SUPERSITES PROGRAM

EPA Science Inventory

The PM2.5 Supersites program was designed to complement routinely operating PM2.5 networks by providing enhanced temporal and chemical/physical composition data in addressing three overarching objectives: supporting health effects and exposure research, advanced monitoring meth...

Effectiveness of temporary control measures for lowering PM2.5 pollution in Beijing and the implications

NASA Astrophysics Data System (ADS)

Wang, Yong; Xue, Yifeng; Tian, Hezhong; Gao, Jian; Chen, Ying; Zhu, Chuanyong; Liu, Huanjia; Wang, Kun; Hua, Shenbing; Liu, Shuhan; Shao, Panyang

2017-05-01

In order to investigate the effects of the temporary strengthening of air quality assurance controlling measures during the Beijing 2015 IAAF World Championships and the Military Parade Assurance Period (MPAP) in China, we collected daily PM2.5 aerosol samples at three typical sites (urban downtown, suburban and rural background area, respectively) in Beijing and investigated the variations of concentration of the water-soluble ions, elemental constituents, organic carbon (OC) and elemental carbon (EC) in PM2.5 from Aug.15 to Sept.10, 2015. Simultaneously, 1-h high-resolution continuous monitoring results of PM2.5 mass concentration as well as the chemical components which were measured at another online monitoring urban site were incorporated. The concentrations of PM2.5 and other gaseous pollutants (SO2, NO2 and CO) during the parade control period (Aug.20-Sept.3) exhibited a substantially decrease compared with the concentrations during both the non-control (August 15 to August 19 and September 4 to September 10) period and the same period in 2014. According to the CMC results, the major components were identified as secondary inorganic aerosol (SIA, the combination of sulfate, ammonium and nitrate), mineral dust and particular organic matter (POM), which together accounted for more than 80% of PM2.5 in urban and suburban sites. POM is found to account for the largest proportion, and the obviously higher proportion of POM in the urban area revealed the significance contribution from vehicles. Compared with the non-control period, the mass concentrations of SIA and secondary organic carbon (SOC) decreased obviously. However, SIA and SOC are observed to play an important role in contributing to the rapid growth process of PM2.5 under unfavorable meteorological conditions during the control period. In view of the gradual improvement of air quality in Beijing, as well as the contribution of secondary aerosol formations in total PM2.5, effective control of primary gaseous pollutants and volatile organic compounds (VOCs) will be very significant for further lowering the concentration of PM2.5 in Beijing in normal time.

Processes affecting concentrations of fine particulate matter (PM 2.5) in the UK atmosphere

NASA Astrophysics Data System (ADS)

Harrison, Roy M.; Laxen, Duncan; Moorcroft, Stephen; Laxen, Kieran

2012-01-01

PM 2.5 is now subject to a limit value and exposure-reduction targets across the European Union. This has led to a rapid expansion in PM 2.5 monitoring across Europe and this paper reviews data collected in the United Kingdom in 2009. The expected gradient between rural, urban background and roadside sites is observed, although the roadside increment is generally rather small except for heavily trafficked street canyon locations. PM 2.5:PM 10 ratios decline from around 0.8 in southeast England to below 0.6 in Scotland consistent with a higher contribution of secondary particulate matter in southeast England. Average diurnal profiles of PM 2.5 differ around the UK but have a common feature in a nocturnal minimum and a peak during the morning rush hour. Central and southern UK sites also show an evening peak following a concentration reduction during the mid afternoon which is not seen at northern UK sites and is attributed to evaporation of semi-volatile components, particularly ammonium nitrate. Concentrations of PM 2.5 are typically highest in the winter months and lowest in the mid-summer consistent with better mixing and volatilisation of semi-volatile components in the warmer months of the year. Directional analysis shows a stronger association of PM 2.5 with easterly winds associated with air masses from the European mainland than with the direction of local traffic sources.

RESULTS FROM EXPOSURE MONITORING PERFORMED DURING THE 1997 BALTIMORE PM PILOT STUDY

EPA Science Inventory

An eighteen day winter-time ambient and personal exposure monitoring study of particulate matter (PM) was conducted as part of an.integrated epidemiological-exposure pilot study of an aged population. Goals of the study were to determine the feasibility of performing active per...

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.

Second-hand smoke in four English prisons: an air quality monitoring study.

PubMed

Jayes, Leah R; Ratschen, Elena; Murray, Rachael L; Dymond-White, Suzy; Britton, John

2016-02-04

To measure levels of indoor pollution in relation to smoking in four English prisons. TSI SidePak AM510 Personal Aerosol Monitors were used to measure concentrations of particulate matter less than 2.5 μm in diameter (PM2.5) for periods of up to 9 h in selected smoking and non-smoking areas, and personal exposure monitoring of prison staff during a work shift, in four prisons. PM2.5 data were collected for average periods of 6.5 h from 48 locations on 25 wing landings where smoking was permitted in cells, on 5 non-smoking wings, 13 prisoner cells, and personal monitoring of 22 staff members. Arithmetic mean PM2.5 concentrations were significantly higher on smoking than non-smoking wing landings (43.9 μg/m(3) and 5.9 μg/m(3) respectively, p < 0.001) and in smoking than non-smoking cells (226.2 μg/m(3) and 17.0 μg/m(3) respectively, p < 0.001). Staff members wore monitors for an average of 4.18 h, during which they were exposed to arithmetic mean PM2.5 concentration of 23.5 μg/m(3). The concentration of PM2.5 pollution in smoking areas of prisons are extremely high. Smoking in prisons therefore represents a significant health hazard to prisoners and staff members.

Characterization of ambient fine particles in the northwestern area and Anchorage, Alaska.

PubMed

Kim, Eugene; Hopke, Philip K

2008-10-01

Ambient PM2.5 (particulate matter less than 2.5 microm in aerodynamic diameter) in the northwestern United States and Alaska is dominated by carbonaceous compounds associated with wood burning and transportation sources. PM2.5 source characterization studies analyzing recent PM2.5 speciation data have not been previously reported for these areas. In this study, ambient PM2.5 speciation samples collected at two monitoring sites located in the northwestern area, Olympic Peninsula, WA, and Portland, OR, and one monitoring site located in Anchorage, AK, were characterized through source apportionments. Gasoline vehicle, secondary sulfate, and wood smoke were the largest sources of PM2.5 collected at the Anchorage, Olympic, and Portland monitoring sites, respectively. Secondary sulfates showed an April peak at Anchorage and a November peak at Portland that are likely related to the increased photochemical reaction and long-range transport in Anchorage and meteorological stagnation in Portland. Secondary nitrate at the Olympic site showed a weak summer high peak that could be caused by seasonal tourism in the national park. Backward trajectories suggested that the elevated aged sea salt concentrations at the Portland monitoring site could be regional transport of sea salt that passed through other contaminated air sheds along the coast. Oil combustion emissions that might originate from ships and ferries were observed at the Olympic monitoring site.

An economic passive sampling method to detect particulate pollutants using magnetic measurements.

PubMed

Cao, Liwan; Appel, Erwin; Hu, Shouyun; Ma, Mingming

2015-10-01

Identifying particulate matter (PM) emitted from industrial processes into the atmosphere is an important issue in environmental research. This paper presents a passive sampling method using simple artificial samplers that maintains the advantage of bio-monitoring, but overcomes some of its disadvantages. The samplers were tested in a heavily polluted area (Linfen, China) and compared to results from leaf samples. Spatial variations of magnetic susceptibility from artificial passive samplers and leaf samples show very similar patterns. Scanning electron microscopy suggests that the collected PM are mostly in the range of 2-25 μm; frequent occurrence of spherical shape indicates industrial combustion dominates PM emission. Magnetic properties around power plants show different features than other plants. This sampling method provides a suitable and economic tool for semi-quantifying temporal and spatial distribution of air quality; they can be installed in a regular grid and calibrate the weight of PM. Copyright © 2015 Elsevier Ltd. All rights reserved.

Using pig manure to promote fermentation of sugarcane molasses alcohol wastewater and its effects on microbial community structure.

PubMed

Shen, Peihong; Han, Fei; Su, Shuquan; Zhang, Junya; Chen, Zhineng; Li, Junfang; Gan, Jiayi; Feng, Bin; Wu, Bo

2014-03-01

Molasses alcohol wastewater (MAW) is difficult to be bio-treated and converted into biogas. In this study, MAW mixed with pig manure (PM) in different ratios was co-digested. Biogas production, chemical oxygen demand (COD) removal and the structure of microbial communities were monitored in the process. Our results showed that under the optimal COD ratio of PM:MAW (1.0:1.5), CODremoval and biogas yield were the highest. And in fermentation tanks with different PM to MAW ratios, the structure and composition of bacterial communities varied in the early and late stage. Furthermore, the type of main bacterial operational taxonomic units (OTUs) have no differences, yet the relative abundance of OTUs varied. The current research showed that there was a good potential to the use of PM as a co-digested material to anaerobic treatment of MAW and provided references for further improving bio-treatment of MAW. Copyright © 2014 Elsevier Ltd. All rights reserved.

CHANGES IN OPERATING PROCEDURES FOR AEROSOL CONCENTRATION UNIFORMITY FOR PM2.5 AND PM10 SAMPLER TESTING

EPA Science Inventory

This technical note documents changes in the standard operating procedures used at the Environmental Protection Agency's (U.S. EPA) aerosol testing wind tunnel facility for testing of particulate matter monitoring methods of PM2.5 and PM10. These changes are relative to the op...

Emissions Inventory of PM2.5 Trace Elements across the United States

EPA Science Inventory

This paper presents the first National Emissions Inventory (NEI) of fine particulate matter (PM_2.5) that includes the full suite of PM_2.5 trace elements (atomic number >10) measured at ambient monitoring sites across the U.S. PM _2.5 emissions in ...

Recent versus chronic exposure to particulate matter air pollution in association with neurobehavioral performance in a panel study of primary schoolchildren.

PubMed

Saenen, Nelly D; Provost, Eline B; Viaene, Mineke K; Vanpoucke, Charlotte; Lefebvre, Wouter; Vrijens, Karen; Roels, Harry A; Nawrot, Tim S

2016-10-01

Children's neuropsychological abilities are in a developmental stage. Recent air pollution exposure and neurobehavioral performance are scarcely studied. In a panel study, we repeatedly administered to each child the following neurobehavioral tests: Stroop Test (selective attention) and Continuous Performance Test (sustained attention), Digit Span Forward and Backward Tests (short-term memory), and Digit-Symbol and Pattern Comparison Tests (visual information processing speed). At school, recent inside classroom particulate matter ≤2.5 or 10μm exposure (PM2.5, PM10) was monitored on each examination day. At the child's residence, recent (same day up to 2days before) and chronic (365days before examination) exposures to PM2.5, PM10 and black carbon (BC) were modeled. Repeated neurobehavioral test performances (n=894) of the children (n=310) reflected slower Stroop Test (p=0.05) and Digit-Symbol Test (p=0.01) performances with increasing recent inside classroom PM2.5 exposure. An interquartile range (IQR) increment in recent residential outdoor PM2.5 exposure was associated with an increase in average latency of 0.087s (SE: ±0.034; p=0.01) in the Pattern Comparison Test. Regarding chronic exposure at residence, an IQR increment of PM2.5 exposure was associated with slower performances in the Continuous Performance (9.45±3.47msec; p=0.007) and Stroop Tests (59.9±26.5msec; p=0.02). Similar results were obtained for PM10 exposure. In essence, we showed differential neurobehavioral changes robustly and adversely associated with recent or chronic ambient exposure to PM air pollution at residence, i.e., with recent exposure for visual information processing speed (Pattern Comparison Test) and with chronic exposure for sustained and selective attention. Copyright © 2016. Published by Elsevier Ltd.

Indoor and outdoor particulate matter in primary school classrooms with fan-assisted natural ventilation in Singapore.

PubMed

Chen, Ailu; Gall, Elliott T; Chang, Victor W C

2016-09-01

We conducted multiday continuous monitoring of indoor and outdoor particulate matter (PM) in classrooms with fan-assisted natural ventilation (NV) at five primary schools in Singapore. We monitored size-resolved number concentration of PM with diameter 0.3-10 μm at all schools and alveolar deposited surface area concentrations of PM with diameter 0.01-1.0 μm (SA0.01-1.0) at two schools. Results show that, during the monitoring period, schools closer to expressways and in the downtown area had 2-3 times higher outdoor PM0.3-1.0 number concentrations than schools located in suburban areas. Average indoor SA0.01-1.0 was 115-118 μm(2) cm(-3) during periods of occupancy and 72-87 μm(2) cm(-3) during unoccupied periods. There were close indoor and outdoor correlations for fine PM during both occupied and unoccupied periods (Pearson's r = 0.84-1.0) while the correlations for coarse PM were weak during the occupied periods (r = 0.13-0.74). Across all the schools, the size-resolved indoor/outdoor PM ratios (I/O ratios) were 0.81 to 1.58 and 0.61 to 0.95 during occupied and unoccupied periods, respectively, and average infiltration factors were 0.64 to 0.94. Average PM net emission rates, calculated during periods of occupancy in the classrooms, were lower than or in the lower range of emission rates reported in the literature. This study also reveals that indoor fine and submicron PM predominantly come from outdoor sources, while indoor sources associated with occupancy may be important for coarse PM even when the classrooms have high air exchange rates.

SPATIAL VARIABILITY OF PM2.5 IN URBAN AREAS IN THE UNITED STATES

EPA Science Inventory

Epidemiologic time-series studies typically use either daily 24-hour PM concentrations averaged across several monitors in a city or data obtained at a ?central monitoring site' to relate to human health effects. If 24-hour average concentrations differ substantially across an ur...

Using wavelet-feedforward neural networks to improve air pollution forecasting in urban environments.

PubMed

Dunea, Daniel; Pohoata, Alin; Iordache, Stefania

2015-07-01

The paper presents the screening of various feedforward neural networks (FANN) and wavelet-feedforward neural networks (WFANN) applied to time series of ground-level ozone (O3), nitrogen dioxide (NO2), and particulate matter (PM10 and PM2.5 fractions) recorded at four monitoring stations located in various urban areas of Romania, to identify common configurations with optimal generalization performance. Two distinct model runs were performed as follows: data processing using hourly-recorded time series of airborne pollutants during cold months (O3, NO2, and PM10), when residential heating increases the local emissions, and data processing using 24-h daily averaged concentrations (PM2.5) recorded between 2009 and 2012. Dataset variability was assessed using statistical analysis. Time series were passed through various FANNs. Each time series was decomposed in four time-scale components using three-level wavelets, which have been passed also through FANN, and recomposed into a single time series. The agreement between observed and modelled output was evaluated based on the statistical significance (r coefficient and correlation between errors and data). Daubechies db3 wavelet-Rprop FANN (6-4-1) utilization gave positive results for O3 time series optimizing the exclusive use of the FANN for hourly-recorded time series. NO2 was difficult to model due to time series specificity, but wavelet integration improved FANN performances. Daubechies db3 wavelet did not improve the FANN outputs for PM10 time series. Both models (FANN/WFANN) overestimated PM2.5 forecasted values in the last quarter of time series. A potential improvement of the forecasted values could be the integration of a smoothing algorithm to adjust the PM2.5 model outputs.

Evaluation of Field-deployed Low Cost PM Sensors

EPA Science Inventory

Background Particulate matter (PM) is a pollutant of high public interest regulated by national ambient air quality standards (NAAQS) using federal reference method (FRM) and federal equivalent method (FEM) instrumentation identified for environmental monitoring. PM is present i...

Performance evaluation of the active-flow personal DataRAM PM 2.5 mass monitor (Thermo Anderson pDR-1200) designed for continuous personal exposure measurements

NASA Astrophysics Data System (ADS)

Chakrabarti, Bhabesh; Fine, Philip M.; Delfino, Ralph; Sioutas, Constantinos

The need for continuous personal monitoring for exposure to particulate matter has been demonstrated by recent health studies showing effects of PM exposure on time scales of less than a few hours. Filter-based methods cannot measure this short-term variation of PM levels, which can be quite significant considering human activity patterns. The goal of this study was to evaluate the active-flow personal DataRAM for PM 2.5 (MIE pDR-1200; Thermo Electron Corp., Franklin, MA) designed as a wearable monitor to continuously measure particle exposure. The instrument precision was found to be good (2.1%) and significantly higher than the passive pDR configuration tested previously. A comparison to other proven continuous monitors resulted in good agreement at low relative humidities. Results at higher humidity followed predictable trends and provided a correction scheme that improved the accuracy of pDR readings. The pDR response to particle size also corresponded to previously observed and theoretical errors. The active flow feature of the pDR allows collection of the sampled particles on a back-up filter. The 24-h mass measured on this filter was found to compare very well with a Federal Reference Method for PM 2.5 mass.

Air-Quality Impacts and Intake Fraction of PM2.5 during the 2013 Rim Megafire.

PubMed

Navarro, Kathleen M; Cisneros, Ricardo; O'Neill, Susan M; Schweizer, Don; Larkin, Narasimhan K; Balmes, John R

2016-11-01

The 2013 Rim Fire was the third largest wildfire in California history and burned 257 314 acres in the Sierra Nevada Mountains. We evaluated air-quality impacts of PM 2.5 from smoke from the Rim Fire on receptor areas in California and Nevada. We employed two approaches to examine the air-quality impacts: (1) an evaluation of PM 2.5 concentration data collected by temporary and permanent air-monitoring sites and (2) an estimation of intake fraction (iF) of PM 2.5 from smoke. The Rim Fire impacted locations in the central Sierra nearest to the fire and extended to the northern Sierra Nevada Mountains of California and Nevada monitoring sites. Daily 24-h average PM 2.5 concentrations measured at 22 air monitors had an average concentration of 20 μg/m 3 and ranged from 0 to 450 μg/m 3 . The iF for PM 2.5 from smoke during the active fire period was 7.4 per million, which is slightly higher than representative iF values for PM 2.5 in rural areas and much lower than for urban areas. This study is a unique application of intake fraction to examine emissions-to-exposure for wildfires and emphasizes that air-quality impacts are not only localized to communities near large fires but can extend long distances and affect larger urban areas.

Development and On-Field Testing of Low-Cost Portable System for Monitoring PM2.5 Concentrations.

PubMed

N Genikomsakis, Konstantinos; Galatoulas, Nikolaos-Fivos; I Dallas, Panagiotis; Candanedo Ibarra, Luis Miguel; Margaritis, Dimitris; S Ioakimidis, Christos

2018-04-01

Recent developments in the field of low-cost sensors enable the design and implementation of compact, inexpensive and portable sensing units for air pollution monitoring with fine-detailed spatial and temporal resolution, in order to support applications of wider interest in the area of intelligent transportation systems (ITS). In this context, the present work advances the concept of developing a low-cost portable air pollution monitoring system (APMS) for measuring the concentrations of particulate matter (PM), in particular fine particles with a diameter of 2.5 μm or less (PM2.5). Specifically, this paper presents the on-field testing of the proposed low-cost APMS implementation using roadside measurements from a mobile laboratory equipped with a calibrated instrument as the basis of comparison and showcases its accuracy on characterizing the PM2.5 concentrations on 1 min resolution in an on-road trial. Moreover, it demonstrates the intended application of collecting fine-grained spatio-temporal PM2.5 profiles by mounting the developed APMS on an electric bike as a case study in the city of Mons, Belgium.

Development and On-Field Testing of Low-Cost Portable System for Monitoring PM2.5 Concentrations

PubMed Central

Galatoulas, Nikolaos-Fivos; I. Dallas, Panagiotis; Candanedo Ibarra, Luis Miguel; Margaritis, Dimitris; S. Ioakimidis, Christos

2018-01-01

Recent developments in the field of low-cost sensors enable the design and implementation of compact, inexpensive and portable sensing units for air pollution monitoring with fine-detailed spatial and temporal resolution, in order to support applications of wider interest in the area of intelligent transportation systems (ITS). In this context, the present work advances the concept of developing a low-cost portable air pollution monitoring system (APMS) for measuring the concentrations of particulate matter (PM), in particular fine particles with a diameter of 2.5 μm or less (PM2.5). Specifically, this paper presents the on-field testing of the proposed low-cost APMS implementation using roadside measurements from a mobile laboratory equipped with a calibrated instrument as the basis of comparison and showcases its accuracy on characterizing the PM2.5 concentrations on 1 min resolution in an on-road trial. Moreover, it demonstrates the intended application of collecting fine-grained spatio-temporal PM2.5 profiles by mounting the developed APMS on an electric bike as a case study in the city of Mons, Belgium. PMID:29614770

MONITORING OF PARTICULATE MATTER OUTDOORS

EPA Science Inventory

Recent studies of the size and composition of atmospheric particulate matter (PM) have demonstrated the usefulness of separating atmospheric PM into its fine and coarse components. The need to measure the mass and composition of fine and coarse PM separately has been emphasized b...

Measurements of particulate matter within the framework of the European Monitoring and Evaluation Programme (EMEP) I. First results.

PubMed

Lazaridis, Mihalis; Semb, Arne; Larssen, Steinar; Hjellbrekke, Anne-Gunn; Hov, Oystein; Hanssen, Jan Erik; Schaug, Jan; Tørseth, Kjetil

2002-02-21

Particulate matter (PM) monitoring presents a new challenge to the transboundary air pollution strategies in Europe. Evidence for the role of long-range transport of particulate matter and its significant association with a wide range of adverse health effects has urged for the inclusion of particulate matter within the European Monitoring and Evaluation Programme (EMEP) framework. Here we review available data on PM physico-chemical characteristics within the EMEP framework. In addition we identify future research needs for the characterisation of the background PM in Europe that include detailed harmonised measurements of mass, size and chemical composition (mass closure) of the ambient aerosol.

SEMI-VOLATILE SPECIES IN PM 2.5: DEVELOPMENT AND VALIDATION OF INTEGRATED AND CONTINUOUS SAMPLERS FOR PM 2.5 RESEARCH OR EXPOSURE MONITORING.

EPA Science Inventory

Fine particulate matter (PM) in urban atmospheres contains substantial amounts of semi-volatile material (e.g. ammonium nitrate and semi-volatile organic compounds), some of which is lost when PM is sampled with a filter. This study addresses the hypothesis that the concentratio...

40 CFR Table E-1 to Subpart E of... - Summary of Test Requirements for Reference and Class I Equivalent Methods for PM2.5 and PM10-2.5

Code of Federal Regulations, 2010 CFR

2010-07-01

... Reference and Class I Equivalent Methods for PM2.5 and PM10-2.5 E Table E-1 to Subpart E of Part 53... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance Characteristics of Reference Methods and Class I and Class II Equivalent Methods for PM2.5 or PM10â2.5 Pt. 53...

Modeling Criterion Shifts and Target Checking in Prospective Memory Monitoring

ERIC Educational Resources Information Center

Horn, Sebastian S.; Bayen, Ute J.

2015-01-01

Event-based prospective memory (PM) involves remembering to perform intended actions after a delay. An important theoretical issue is whether and how people monitor the environment to execute an intended action when a target event occurs. Performing a PM task often increases the latencies in ongoing tasks. However, little is known about the…

77 FR 60985 - Ambient Air Monitoring Reference and Equivalent Methods: Designation of Three New Equivalent Methods

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-05

... Methods: Designation of Three New Equivalent Methods AGENCY: Environmental Protection Agency. ACTION: Notice of the designation of three new equivalent methods for monitoring ambient air quality. SUMMARY... equivalent methods, one for measuring concentrations of PM 2.5 , one for measuring concentrations of PM 10...

Correlation Between Hierarchical Bayesian and Aerosol Optical Depth PM2.5 Data and Respiratory-Cardiovascular Chronic Diseases

EPA Science Inventory

Tools to estimate PM2.5 mass have expanded in recent years, and now include: 1) stationary monitor readings, 2) Community Multi-Scale Air Quality (CMAQ) model estimates, 3) Hierarchical Bayesian (HB) estimates from combined stationary monitor readings and CMAQ model output; and, ...

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.

Environmental Inequality in Exposures to Airborne Particulate Matter Components in the United States

PubMed Central

Ebisu, Keita

2012-01-01

Background: Growing evidence indicates that toxicity of fine particulate matter ≤ 2.5 μm in diameter (PM2.5) differs by chemical component. Exposure to components may differ by population. Objectives: We investigated whether exposures to PM2.5 components differ by race/ethnicity, age, and socioeconomic status (SES). Methods: Long-term exposures (2000 through 2006) were estimated for 215 U.S. census tracts for PM2.5 and for 14 PM2.5 components. Population-weighted exposures were combined to generate overall estimated exposures by race/ethnicity, education, poverty status, employment, age, and earnings. We compared population characteristics for tracts with and without PM2.5 component monitors. Results: Larger disparities in estimated exposures were observed for components than for PM2.5 total mass. For race/ethnicity, whites generally had the lowest exposures. Non-Hispanic blacks had higher exposures than did whites for 13 of the 14 components. Hispanics generally had the highest exposures (e.g., 152% higher than whites for chlorine, 94% higher for aluminum). Young persons (0–19 years of age) had levels as high as or higher than other ages for all exposures except sulfate. Persons with lower SES had higher estimated exposures, with some exceptions. For example, a 10% increase in the proportion unemployed was associated with a 20.0% increase in vanadium and an 18.3% increase in elemental carbon. Census tracts with monitors had more non-Hispanic blacks, lower education and earnings, and higher unemployment and poverty than did tracts without monitors. Conclusions: Exposures to PM2.5 components differed by race/ethnicity, age, and SES. If some components are more toxic than others, certain populations are likely to suffer higher health burdens. Demographics differed between populations covered and not covered by monitors. PMID:22889745

An investigation of the PM2.5 and NO2 concentrations and their human health impacts in the metro subway system of Suzhou, China.

PubMed

Cao, Shi-Jie; Kong, Xiang-Ri; Li, Linyan; Zhang, Weirong; Ye, Zi-Ping; Deng, Yelin

2017-05-24

This study measured the particle concentrations with an aerodynamic diameter smaller than 2.5 μm (PM 2.5 ), nitrogen dioxide (NO 2 ), and relative humidity (RH) at five metro subway stations in Suzhou's subway system (Lines 1 and 2). The real-time monitoring campaign was conducted from March 30 th to April 10 th and August 4 th to August 21 st , 2015. The monitoring practice was carried out during rush (7:00-9:00 AM and 17:00-19:00 PM) and regular hours (other times) at the ground and underground levels under different weather conditions with a purpose of obtaining representative data. The monitored results show that the concentrations of PM 2.5 in the train carriages were lower than the concentrations at the underground platforms during both spring and summer. The mean PM 2.5 concentrations at all the underground platforms in all the sub-stations monitored were significantly higher than those at the ground level. The human health impact was calculated to be 6300 annual DALYs (or 375 deaths) due to exposure to the subway system in Suzhou according to the UNEP-SETAC toxicity (USEtox) model. Linear regression models were applied to evaluate the relationships between the PM 2.5 , NO 2 concentrations, and RH. We found that a 10% increment in RH from the current average level of 50-60% can lead to a 9.8 μg m -3 concentration decrease in PM 2.5 . This further results in the total human health impact being reduced to 2451 DALYs (150-4753 DALYs), representing a 20% decrease (1.2-38%).

Design and application of a web-based real-time personal PM2.5 exposure monitoring system.

PubMed

Sun, Qinghua; Zhuang, Jia; Du, Yanjun; Xu, Dandan; Li, Tiantian

2018-06-15

Growing demand from public health research for conduct large-scale epidemiological studies to explore health effect of PM 2.5 was well-documented. To address this need, we design a web-based real-time personal PM 2.5 exposure monitoring system (RPPM2.5 system) which can help researcher to get big data of personal PM 2.5 exposure with low-cost, low labor requirement, and low operating technical requirements. RPPM2.5 system can provide relative accurate real-time personal exposure data for individuals, researches, and decision maker. And this system has been used in a survey of PM 2.5 personal exposure level conducted in 5 cities of China and has provided mass of valuable data for epidemiological research. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatiotemporal evaluation of EMEP4UK-WRF v4.3 atmospheric chemistry transport simulations of health-related metrics for NO2, O3, PM10, and PM2. 5 for 2001-2010

NASA Astrophysics Data System (ADS)

Lin, Chun; Heal, Mathew R.; Vieno, Massimo; MacKenzie, Ian A.; Armstrong, Ben G.; Butland, Barbara K.; Milojevic, Ai; Chalabi, Zaid; Atkinson, Richard W.; Stevenson, David S.; Doherty, Ruth M.; Wilkinson, Paul

2017-04-01

This study was motivated by the use in air pollution epidemiology and health burden assessment of data simulated at 5 km × 5 km horizontal resolution by the EMEP4UK-WRF v4.3 atmospheric chemistry transport model. Thus the focus of the model-measurement comparison statistics presented here was on the health-relevant metrics of annual and daily means of NO2, O3, PM2. 5, and PM10 (daily maximum 8 h running mean for O3). The comparison was temporally and spatially comprehensive, covering a 10-year period (2 years for PM2. 5) and all non-roadside measurement data from the UK national reference monitor network, which applies consistent operational and QA/QC procedures for each pollutant (44, 47, 24, and 30 sites for NO2, O3, PM2. 5, and PM10, respectively). Two important statistics highlighted in the literature for evaluation of air quality model output against policy (and hence health)-relevant standards - correlation and bias - together with root mean square error, were evaluated by site type, year, month, and day-of-week. Model-measurement statistics were generally better than, or comparable to, values that allow for realistic magnitudes of measurement uncertainties. Temporal correlations of daily concentrations were good for O3, NO2, and PM2. 5 at both rural and urban background sites (median values of r across sites in the range 0.70-0.76 for O3 and NO2, and 0.65-0.69 for PM2. 5), but poorer for PM10 (0.47-0.50). Bias differed between environments, with generally less bias at rural background sites (median normalized mean bias (NMB) values for daily O3 and NO2 of 8 and 11 %, respectively). At urban background sites there was a negative model bias for NO2 (median NMB = -29 %) and PM2. 5 (-26 %) and a positive model bias for O3 (26 %). The directions of these biases are consistent with expectations of the effects of averaging primary emissions across the 5 km × 5 km model grid in urban areas, compared with monitor locations that are more influenced by these emissions (e.g. closer to traffic sources) than the grid average. The biases are also indicative of potential underestimations of primary NOx and PM emissions in the model, and, for PM, with known omissions in the model of some PM components, e.g. some components of wind-blown dust. There were instances of monthly and weekday/weekend variations in the extent of model-measurement bias. Overall, the greater uniformity in temporal correlation than in bias is strongly indicative that the main driver of model-measurement differences (aside from grid versus monitor spatial representivity) was inaccuracy of model emissions - both in annual totals and in the monthly and day-of-week temporal factors applied in the model to the totals - rather than simulation of atmospheric chemistry and transport processes. Since, in general for epidemiology, capturing correlation is more important than bias, the detailed analyses presented here support the use of data from this model framework in air pollution epidemiology.

Contribution of Urban Road Traffic to PM2.5 Pollution

EPA Science Inventory

Overview of PM2.5 measurements from EPA's NAAQS monitoring sites across the US. The few measurements that exist show increased PM2.5 mass levels at near-road sites, consistent with measurements of other pollutants emitted by motor vehicles.

Human health risk characterization of petroleum coke calcining facility emissions.

PubMed

Singh, Davinderjit; Johnson, Giffe T; Harbison, Raymond D

2015-12-01

Calcining processes including handling and storage of raw petroleum coke may result in Particulate Matter (PM) and gaseous emissions. Concerns have been raised over the potential association between particulate and aerosol pollution and adverse respiratory health effects including decrements in lung function. This risk characterization evaluated the exposure concentrations of ambient air pollutants including PM10 and gaseous pollutants from a petroleum coke calciner facility. The ambient air pollutant levels were collected through monitors installed at multiple locations in the vicinity of the facility. The measured and modeled particulate levels in ambient air from the calciner facility were compared to standards protective of public health. The results indicated that exposure levels were, on occasions at sites farther from the facility, higher than the public health limit of 150 μg/m(3) 24-h average for PM10. However, the carbon fraction demonstrated that the contribution from the calciner facility was de minimis. Exposure levels of the modeled SO2, CO, NOx and PM10 concentrations were also below public health air quality standards. These results demonstrate that emissions from calcining processes involving petroleum coke, at facilities that are well controlled, are below regulatory standards and are not expected to produce a public health risk. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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

Year-long continuous personal exposure to PM 2.5 recorded by a fast responding portable nephelometer

NASA Astrophysics Data System (ADS)

Braniš, Martin; Kolomazníková, Jana

2010-08-01

Personal exposure to particulate matter of aerodynamic diameter under 2.5 μm (PM 2.5) was monitored using a DustTrak nephelometer. The battery-operated unit, worn by an adult individual for a period of approximately one year, logged integrated average PM 2.5 concentrations over 5 min intervals. A detailed time-activity diary was used to record the experimental subject's movement and the microenvironments visited. Altogether 239 days covering all the months (except April) were available for the analysis. In total, 60 463 acceptable 5-min averages were obtained. The dataset was divided into 7 indoor and 4 outdoor microenvironments. Of the total time, 84% was spent indoors, 10.9% outdoors and 5.1% in transport. The indoor 5-min PM 2.5 average was higher (55.7 μg m -3) than the outdoor value (49.8 μg m -3). The highest 5-min PM 2.5 average concentration was detected in restaurant microenvironments (1103 μg m -3), the second highest 5-min average concentration was recorded in indoor spaces heated by stoves burning solid fuels (420 μg m -3). The lowest 5-min mean aerosol concentrations were detected outdoors in rural/natural environments (25 μg m -3) and indoors at the monitored person's home (36 μg m -3). Outdoor and indoor concentrations of PM 2.5 measured by the nephelometer at home and during movement in the vicinity of the experimental subject's home were compared with those of the nearest fixed-site monitor of the national air quality monitoring network. The high correlation coefficient (0.78) between the personal and fixed-site monitor aerosol concentrations suggested that fixed-site monitor data can be used as proxies for personal exposure in residential and some other microenvironments. Collocated measurements with a reference method (β-attenuation) showed a non-linear systematic bias of the light-scattering method, limiting the use of direct concentration readings for exact exposure analysis.

Defense Coastal/Estuarine Research Program (DCERP) Baseline Monitoring Plan

DTIC Science & Technology

2007-09-19

climatological stress (e.g., temperature, drought) and shorter-term air pollutant stress (oxidants and metals ). Heavy metals of fine PM have been...speciation of the fine and coarse PM fractions will allow distinction between different PM sources such as wind blown soil dust, including dust...emitting 12% of the total PM2.5 mass (U.S. EPA, 2004b). Source apportionment modeling of PM2.5 mass concentrations from 24 Speciation Defense Coastal

Research on PM2.5 time series characteristics based on data mining technology

NASA Astrophysics Data System (ADS)

Zhao, Lifang; Jia, Jin

2018-02-01

With the development of data mining technology and the establishment of environmental air quality database, it is necessary to discover the potential correlations and rules by digging the massive environmental air quality information and analyzing the air pollution process. In this paper, we have presented a sequential pattern mining method based on the air quality data and pattern association technology to analyze the PM2.5 time series characteristics. Utilizing the real-time monitoring data of urban air quality in China, the time series rule and variation properties of PM2.5 under different pollution levels are extracted and analyzed. The analysis results show that the time sequence features of the PM2.5 concentration is directly affected by the alteration of the pollution degree. The longest time that PM2.5 remained stable is about 24 hours. As the pollution degree gets severer, the instability time and step ascending time gradually changes from 12-24 hours to 3 hours. The presented method is helpful for the controlling and forecasting of the air quality while saving the measuring costs, which is of great significance for the government regulation and public prevention of the air pollution.

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.

Modelling daily PM2.5 concentrations at high spatio-temporal resolution across Switzerland.

PubMed

de Hoogh, Kees; Héritier, Harris; Stafoggia, Massimo; Künzli, Nino; Kloog, Itai

2018-02-01

Spatiotemporal resolved models were developed predicting daily fine particulate matter (PM 2.5 ) concentrations across Switzerland from 2003 to 2013. Relatively sparse PM 2.5 monitoring data was supplemented by imputing PM 2.5 concentrations at PM 10 sites, using PM 2.5 /PM 10 ratios at co-located sites. Daily PM 2.5 concentrations were first estimated at a 1 × 1km resolution across Switzerland, using Multiangle Implementation of Atmospheric Correction (MAIAC) spectral aerosol optical depth (AOD) data in combination with spatiotemporal predictor data in a four stage approach. Mixed effect models (1) were used to predict PM 2.5 in cells with AOD but without PM 2.5 measurements (2). A generalized additive mixed model with spatial smoothing was applied to generate grid cell predictions for those grid cells where AOD was missing (3). Finally, local PM 2.5 predictions were estimated at each monitoring site by regressing the residuals from the 1 × 1km estimate against local spatial and temporal variables using machine learning techniques (4) and adding them to the stage 3 global estimates. The global (1 km) and local (100 m) models explained on average 73% of the total,71% of the spatial and 75% of the temporal variation (all cross validated) globally and on average 89% (total) 95% (spatial) and 88% (temporal) of the variation locally in measured PM 2.5 concentrations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Management of sleep apnea without high pretest probability or with comorbidities by three nights of portable sleep monitoring.

PubMed

Guerrero, Arnoldo; Embid, Cristina; Isetta, Valentina; Farre, Ramón; Duran-Cantolla, Joaquin; Parra, Olga; Barbé, Ferran; Montserrat, Josep M; Masa, Juan F

2014-08-01

Obstructive sleep apnea (OSA) diagnosis using simplified methods such as portable sleep monitoring (PM) is only recommended in patients with a high pretest probability. The aim is to determine the diagnostic efficacy, consequent therapeutic decision-making, and costs of OSA diagnosis using polysomnography (PSG) versus three consecutive studies of PM in patients with mild to moderate suspicion of sleep apnea or with comorbidity that can mask OSA symptoms. Randomized, blinded, crossover study of 3 nights of PM (3N-PM) versus PSG. The diagnostic efficacy was evaluated with receiver operating characteristic (ROC) curves. Therapeutic decisions to assess concordance between the two different approaches were performed by sleep physicians and respiratory physicians (staff and residents) using agreement level and kappa coefficient. The costs of each diagnostic strategy were considered. Fifty-six patients were selected. Epworth Sleepiness Scale was 10.1 (5.3) points. Bland-Altman plot for apnea-hypopnea index (AHI) showed good agreement. ROC curves showed the best area under the curve in patients with PSG AHI ≥ 5 [0.955 (confidence interval = 0.862-0.993)]. For a PSG AHI ≥ 5, a PM AHI of 5 would effectively exclude and confirm OSA diagnosis. For a PSG AHI ≥ 15, a PM AHI ≥ 22 would confirm and PM AHI < 7 would exclude OSA. The best agreement of therapeutic decisions was achieved by the sleep medicine specialists (81.8%). The best cost-diagnostic efficacy was obtained by the 3N-PM. Three consecutive nights of portable monitoring at home evaluated by a qualified sleep specialist is useful for the management of patients without high pretest probability of obstructive sleep apnea or with comorbidities. http://www.clinicaltrials.gov, registration number: NCT01820156. Guerrero A, Embid C, Isetta V, Farre R, Duran-Cantolla J, Parra O, Barbé F, Montserrat JM, Masa JF. Management of sleep apnea without high pretest probability or with comorbidities by three nights of portable sleep monitoring.

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...

Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach

NASA Astrophysics Data System (ADS)

Li, Tongwen; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Xuechen; Zhang, Liangpei

2017-12-01

Fusing satellite observations and station measurements to estimate ground-level PM2.5 is promising for monitoring PM2.5 pollution. A geo-intelligent approach, which incorporates geographical correlation into an intelligent deep learning architecture, is developed to estimate PM2.5. Specifically, it considers geographical distance and spatiotemporally correlated PM2.5 in a deep belief network (denoted as Geoi-DBN). Geoi-DBN can capture the essential features associated with PM2.5 from latent factors. It was trained and tested with data from China in 2015. The results show that Geoi-DBN performs significantly better than the traditional neural network. The out-of-sample cross-validation R2 increases from 0.42 to 0.88, and RMSE decreases from 29.96 to 13.03 μg/m3. On the basis of the derived PM2.5 distribution, it is predicted that over 80% of the Chinese population live in areas with an annual mean PM2.5 of greater than 35 μg/m3. This study provides a new perspective for air pollution monitoring in large geographic regions.

Spatial mapping and analysis of aerosols during a forest fire using computational mobile microscopy

NASA Astrophysics Data System (ADS)

Wu, Yichen; Shiledar, Ashutosh; Luo, Yi; Wong, Jeffrey; Chen, Cheng; Bai, Bijie; Zhang, Yibo; Tamamitsu, Miu; Ozcan, Aydogan

2018-02-01

Forest fires are a major source of particulate matter (PM) air pollution on a global scale. The composition and impact of PM are typically studied using only laboratory instruments and extrapolated to real fire events owing to a lack of analytical techniques suitable for field-settings. To address this and similar field test challenges, we developed a mobilemicroscopy- and machine-learning-based air quality monitoring platform called c-Air, which can perform air sampling and microscopic analysis of aerosols in an integrated portable device. We tested its performance for PM sizing and morphological analysis during a recent forest fire event in La Tuna Canyon Park by spatially mapping the PM. The result shows that with decreasing distance to the fire site, the PM concentration increases dramatically, especially for particles smaller than 2 µm. Image analysis from the c-Air portable device also shows that the increased PM is comparatively strongly absorbing and asymmetric, with an aspect ratio of 0.5-0.7. These PM features indicate that a major portion of the PM may be open-flame-combustion-generated element carbon soot-type particles. This initial small-scale experiment shows that c-Air has some potential for forest fire monitoring.

Seasonal variability of PM2.5 and PM10 composition and sources in an urban background site in Southern Italy.

PubMed

Cesari, D; De Benedetto, G E; Bonasoni, P; Busetto, M; Dinoi, A; Merico, E; Chirizzi, D; Cristofanelli, P; Donateo, A; Grasso, F M; Marinoni, A; Pennetta, A; Contini, D

2018-01-15

Comparison of fine and coarse fractions in terms of sources and dynamics is scarce in southeast Mediterranean countries; differences are relevant because of the importance of natural sources like sea spray and Saharan dust advection, because most of the monitoring networks are limited to PM 10 . In this work, the main seasonal variabilities of sources and processes involving fine and coarse PM (particulate matter) were studied at the Environmental-Climate Observatory of Lecce (Southern Italy). Simultaneous PM 2.5 and PM 10 samples were collected between July 2013 and July 2014 and chemically analysed to determine concentrations of several species: OC (organic carbon) and EC (elemental carbon) via thermo-optical analysis, 9 major ions via IC, and 23 metals via ICP-MS. Data was processed through mass closure analysis and Positive Matrix Factorization (PMF) receptor model characterizing seasonal variabilities of nine sources contributions. Organic and inorganic secondary aerosol accounts for 43% of PM 2.5 and 12% of PM 2.5-10 with small seasonal changes. SIA (secondary inorganic aerosol) seasonal pattern is opposite to that of SOC (secondary organic carbon). SOC is larger during the cold period, sulphate (the major contributor to SIA) is larger during summer. Two forms of nitrate were identified: NaNO 3 , correlated with chloride depletion and aging of sea-spray, mainly present in PM 2.5-10 ; NH 4 NO 3 more abundant in PM 2.5 . Biomass burning is a relevant source with larger contribution during autumn and winter because of the influence of domestic heating, however, is not negligible in spring and summer, because of the contributions of fires and agricultural practices. Mass closure analysis and PMF results identify two soil sources: crustal associated to long range transport and carbonates associated to local resuspended dust. Both sources contributes to the coarse fraction and have different dynamics with crustal source contributing mainly in high winds from SE conditions and carbonates during high winds from North direction. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China

PubMed Central

Liang, Fengchao; Gao, Meng; Xiao, Qingyang; Carmichael, Gregory R.

2017-01-01

PM2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM2.5 in grid cells with a resolution of 10 km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM2.5 concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R2 of 0.95 and 0.94, respectively and PM2.5 was overestimated by WRF-Chem (R2=0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM2.5. Current monitoring network in North China was dense enough to provide a reliable PM2.5 prediction by interpolation technique. PMID:28599195

Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China.

PubMed

Liang, Fengchao; Gao, Meng; Xiao, Qingyang; Carmichael, Gregory R; Pan, Xiaochuan; Liu, Yang

2017-10-01

PM 2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM 2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM 2.5 in grid cells with a resolution of 10km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM 2.5 concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R 2 of 0.95 and 0.94, respectively and PM 2.5 was overestimated by WRF-Chem (R 2 =0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM 2.5 . Current monitoring network in North China was dense enough to provide a reliable PM 2.5 prediction by interpolation technique. Copyright © 2017. Published by Elsevier Inc.

PM: RESEARCH METHODS FOR PM TOXIC COMPOUNDS - PARTICLE METHODS EVALUATION AND DEVELOPMENT

EPA Science Inventory

The Federal Reference Method (FRM) for Particulate Matter (PM) developed by EPA's National Exposure Research Laboratory (NERL) forms the backbone of the EPA's national monitoring strategy. It is the measurement that defines attainment of the National Ambient Air Quality Standard...

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.

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

Bayesian spatio-temporal modeling of particulate matter concentrations in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Manga, Edna; Awang, Norhashidah

2016-06-01

This article presents an application of a Bayesian spatio-temporal Gaussian process (GP) model on particulate matter concentrations from Peninsular Malaysia. We analyze daily PM10 concentration levels from 35 monitoring sites in June and July 2011. The spatiotemporal model set in a Bayesian hierarchical framework allows for inclusion of informative covariates, meteorological variables and spatiotemporal interactions. Posterior density estimates of the model parameters are obtained by Markov chain Monte Carlo methods. Preliminary data analysis indicate information on PM10 levels at sites classified as industrial locations could explain part of the space time variations. We include the site-type indicator in our modeling efforts. Results of the parameter estimates for the fitted GP model show significant spatio-temporal structure and positive effect of the location-type explanatory variable. We also compute some validation criteria for the out of sample sites that show the adequacy of the model for predicting PM10 at unmonitored sites.

Exploring relationships between outdoor air particulate-associated polycyclic aromatic hydrocarbon and PM 2.5: A case study of benzo(a)pyrene in California metropolitan regions

NASA Astrophysics Data System (ADS)

Lobscheid, Agnes B.; McKone, Thomas E.; Vallero, Daniel A.

Polycyclic aromatic hydrocarbons (PAHs) and particulate matter (PM) are co-pollutants emitted as by-products of combustion processes. Convincing evidence exists for PAHs as a primary toxic component of fine PM (PM 2.5). Because PM 2.5 is listed by the US EPA as a "Criteria Pollutant", it is monitored regularly at sites nationwide. In contrast, very limited data is available on measured ambient air concentrations of PAHs. However, between 1999 and 2001, ambient air concentrations of PM 2.5 and benzo(a)pyrene (BaP) are available for California locations. We use multivariate linear regression models (MLRMs) to predict ambient air levels of BaP in four air basins based on reported PM 2.5 concentrations and spatial, temporal and meteorological variables as variates. We obtain an R2 ranging from 0.57 to 0.72 among these basins. Significant variables ( p<0.05) include the average daily PM 2.5 concentration, wind speed, temperature and relative humidity, and the coastal distance as well as season, and holiday or weekend. Combining the data from all sites and using only these variables to estimate ambient BaP levels, we obtain an R2 of 0.55. These R2-values, combined with analysis of the residual error and cross validation using the PRESS-statistic, demonstrate the potential of our method to estimate reported outdoor air PAH exposure levels in metropolitan regions. These MLRMs provide a first step towards relating outdoor ambient PM 2.5 and PAH concentrations for epidemiological studies when PAH measurements are unavailable, or limited in spatial coverage, based on publicly available meteorological and PM 2.5 data.

The Contribution of School-Related Parental Monitoring, Self-Determination, and Self-Efficacy to Academic Achievement

ERIC Educational Resources Information Center

Affuso, Gaetana; Bacchini, Dario; Miranda, Maria Concetta

2017-01-01

The aim of this study was to examine the contribution of school-related parental monitoring (SR-PM), self-determined motivation, and academic self-efficacy to academic achievement across time. The authors hypothesized that SR-PM would affect academic achievement indirectly via its effects on self-determined motivation and academic self-efficacy…

THE MEASUREMENT OF PM2.5, INCLUDING SEMI-VOLATILE COMPONENTS, IN THE EMPACT PROGRAM: RESULTS FROM THE SALT LAKE CITY STUDY. (R827993)

EPA Science Inventory

The Salt Lake City EPA Environmental Monitoring for Public Access and Community Tracking (EMPACT) project, initiated in October 1999, is designed to evaluate the usefulness of a newly developed real-time continuous monitor (RAMS) for total (non-volatile plus semi-volatile) PM<...

40 CFR 63.1505 - Emission standards for affected sources and emission units.

Code of Federal Regulations, 2014 CFR

2014-07-01

... any PM add-on air pollution control device if a continuous opacity monitor (COM) or visible emissions... percent opacity from any PM add-on air pollution control device if a COM is chosen as the monitoring.../delacquering kiln/decoating kiln is equipped with an afterburner having a design residence time of at least 1...

Selecting optimal monitoring site locations for peak ambient particulate material concentrations using the MM5-CAMx4 numerical modelling system.

PubMed

Sturman, Andrew; Titov, Mikhail; Zawar-Reza, Peyman

2011-01-15

Installation of temporary or long term monitoring sites is expensive, so it is important to rationally identify potential locations that will achieve the requirements of regional air quality management strategies. A simple, but effective, numerical approach to selecting ambient particulate matter (PM) monitoring site locations has therefore been developed using the MM5-CAMx4 air pollution dispersion modelling system. A new method, 'site efficiency,' was developed to assess the ability of any monitoring site to provide peak ambient air pollution concentrations that are representative of the urban area. 'Site efficiency' varies from 0 to 100%, with the latter representing the most representative site location for monitoring peak PM concentrations. Four heavy pollution episodes in Christchurch (New Zealand) during winter 2005, representing 4 different aerosol dispersion patterns, were used to develop and test this site assessment technique. Evaluation of the efficiency of monitoring sites was undertaken for night and morning aerosol peaks for 4 different particulate material (PM) spatial patterns. The results demonstrate that the existing long term monitoring site at Coles Place is quite well located, with a site efficiency value of 57.8%. A temporary ambient PM monitoring site (operating during winter 2006) showed a lower ability to capture night and morning peak aerosol concentrations. Evaluation of multiple site locations used during an extensive field campaign in Christchurch (New Zealand) in 2000 indicated that the maximum efficiency achieved by any site in the city would be 60-65%, while the efficiency of a virtual background site is calculated to be about 7%. This method of assessing the appropriateness of any potential monitoring site can be used to optimize monitoring site locations for any air pollution measurement programme. Copyright © 2010 Elsevier B.V. All rights reserved.

Air Quality and Road Emission Results for Fort Stewart, Georgia

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

Kirkham, Randy R.; Driver, Crystal J.; Chamness, Mickie A.

2004-02-02

The Directorate of Public Works Environmental & Natural Resources Division (Fort Stewart /Hunter Army Airfield) contracted with the Pacific Northwest National Laboratory (PNNL) to monitor particulate matter (PM) concentrations on Fort Stewart, Georgia. The purpose of this investigation was to establish a PM sampling network using monitoring equipment typically used in U.S. Environmental Protection Agency (EPA) ''saturation sampling'', to determine air quality on the installation. In this initial study, the emphasis was on training-generated PM, not receptor PM loading. The majority of PM samples were 24-hr filter-based samples with sampling frequency ranging from every other day, to once every sixmore » days synchronized with the EPA 6th day national sampling schedule. Eight measurement sites were established and used to determine spatial variability in PM concentrations and evaluate whether fluctuations in PM appear to result from training activities and forest management practices on the installation. Data collected to date indicate the average installation PM2.5 concentration is lower than that of nearby urban Savannah, Georgia. At three sites near the installation perimeter, analyses to segregate PM concentrations by direction of air flow across the installation boundary indicate that air (below 80 ft) leaving the installation contains less PM2.5 than that entering the installation. This is reinforced by the observation that air near the ground is cleaner on average than the air at the top of the canopy.« less

Impact of wildfires on regional air pollution | Science Inventory ...

EPA Pesticide Factsheets

We examine the impact of wildfires and agricultural/prescribed burning on regional air pollution and Air Quality Index (AQI) between 2006 and 2013. We define daily regional air pollution using monitoring sites for ozone (n=1595), PM2.5 collected by Federal Reference Method (n=1058), and constituents of PM2.5 from the Interagency Monitoring of PROtected Visual Environment (IMPROVE) network (n=264) and use satellite image analysis from the NOAA Hazard Mapping System (HMS) to determine days on which visible smoke plumes are detected in the vertical column of the monitoring site. To examine the impact of smoke from these fires on regional air pollution we use a two stage approach, accounting for within site (1st stage) and between site (2nd stage) variations. At the first stage we estimate a monitor-specific plume day effect describing the relative change in pollutant concentrations on the days impacted by smoke plume while accounting for confounding effects of season and temperature_. At the second stage we combine monitor-specific plume day effects with a Bayesian hierarchical model and estimate a pooled nationally-averaged effect. HMS visible smoke plumes were detected on 6% of ozone, 8% of PM2.5 and 6% of IMPROVE network monitoring days. Our preliminary results indicate that the long range transport of air pollutants from wildfires and prescribed burns increase ozone concentration by 11% and PM2.5 mass by 34%. On all of the days where monitoring sites were AQI

Evaluation of fire weather forecasts using PM2.5 sensitivity analysis

NASA Astrophysics Data System (ADS)

Balachandran, Sivaraman; Baumann, Karsten; Pachon, Jorge E.; Mulholland, James A.; Russell, Armistead G.

2017-01-01

Fire weather forecasts are used by land and wildlife managers to determine when meteorological and fuel conditions are suitable to conduct prescribed burning. In this work, we investigate the sensitivity of ambient PM2.5 to various fire and meteorological variables in a spatial setting that is typical for the southeastern US, where prescribed fires are the single largest source of fine particulate matter. We use the method of principle components regression to estimate sensitivity of PM2.5, measured at a monitoring site in Jacksonville, NC (JVL), to fire data and observed and forecast meteorological variables. Fire data were gathered from prescribed fire activity used for ecological management at Marine Corps Base Camp Lejeune, extending 10-50 km south from the PM2.5 monitor. Principal components analysis (PCA) was run on 10 data sets that included acres of prescribed burning activity (PB) along with meteorological forecast data alone or in combination with observations. For each data set, observed PM2.5 (unitless) was regressed against PCA scores from the first seven principal components (explaining at least 80% of total variance). PM2.5 showed significant sensitivity to PB: 3.6 ± 2.2 μg m-3 per 1000 acres burned at the investigated distance scale of ∼10-50 km. Applying this sensitivity to the available activity data revealed a prescribed burning source contribution to measured PM2.5 of up to 25% on a given day. PM2.5 showed a positive sensitivity to relative humidity and temperature, and was also sensitive to wind direction, indicating the capture of more regional aerosol processing and transport effects. As expected, PM2.5 had a negative sensitivity to dispersive variables but only showed a statistically significant negative sensitivity to ventilation rate, highlighting the importance of this parameter to fire managers. A positive sensitivity to forecast precipitation was found, consistent with the practice of conducting prescribed burning on days when rain can naturally extinguish fires. Perhaps most importantly for land managers, our analysis suggests that instead of relying on the forecasts from a day before, prescribed burning decisions should be based on the forecasts released the morning of the burn when possible, since these data were more stable and yielded more statistically robust results.

A System Based on the Internet of Things for Real-Time Particle Monitoring in Buildings

PubMed Central

Roque Ferreira, Cristina; Pitarma, Rui

2018-01-01

Occupational health can be strongly influenced by the indoor environment as people spend 90% of their time indoors. Although indoor air quality (IAQ) is not typically monitored, IAQ parameters could be in many instances very different from those defined as healthy values. Particulate matter (PM), a complex mixture of solid and liquid particles of organic and inorganic substances suspended in the air, is considered the pollutant that affects more people. The most health-damaging particles are the ≤PM10 (diameter of 10 microns or less), which can penetrate and lodge deep inside the lungs, contributing to the risk of developing cardiovascular and respiratory diseases, as well as of lung cancer. This paper presents an Internet of Things (IoT) system for real-time PM monitoring named iDust. This system is based on a WEMOS D1 mini microcontroller and a PMS5003 PM sensor that incorporates scattering principle to measure the value of particles suspended in the air (PM10, PM2.5, and PM1.0). Through a Web dashboard for data visualization and remote notifications, the building manager can plan interventions for enhanced IAQ and ambient assisted living (AAL). Compared to other solutions the iDust is based on open-source technologies, providing a total Wi-Fi system, with several advantages such as its modularity, scalability, low cost, and easy installation. The results obtained are very promising, representing a meaningful tool on the contribution to IAQ and occupational health. PMID:29690534

A System Based on the Internet of Things for Real-Time Particle Monitoring in Buildings.

PubMed

Marques, Gonçalo; Roque Ferreira, Cristina; Pitarma, Rui

2018-04-21

Occupational health can be strongly influenced by the indoor environment as people spend 90% of their time indoors. Although indoor air quality (IAQ) is not typically monitored, IAQ parameters could be in many instances very different from those defined as healthy values. Particulate matter (PM), a complex mixture of solid and liquid particles of organic and inorganic substances suspended in the air, is considered the pollutant that affects more people. The most health-damaging particles are the ≤PM 10 (diameter of 10 microns or less), which can penetrate and lodge deep inside the lungs, contributing to the risk of developing cardiovascular and respiratory diseases, as well as of lung cancer. This paper presents an Internet of Things (IoT) system for real-time PM monitoring named iDust. This system is based on a WEMOS D1 mini microcontroller and a PMS5003 PM sensor that incorporates scattering principle to measure the value of particles suspended in the air (PM 10 , PM 2.5 , and PM 1.0 ). Through a Web dashboard for data visualization and remote notifications, the building manager can plan interventions for enhanced IAQ and ambient assisted living (AAL). Compared to other solutions the iDust is based on open-source technologies, providing a total Wi-Fi system, with several advantages such as its modularity, scalability, low cost, and easy installation. The results obtained are very promising, representing a meaningful tool on the contribution to IAQ and occupational health.

A comparison of transfer-appropriate processing and multi-process frameworks for prospective memory performance.

PubMed

McBride, Dawn M; Abney, Drew H

2012-01-01

We examined multi-process (MP) and transfer-appropriate processing descriptions of prospective memory (PM). Three conditions were compared that varied the overlap in processing type (perceptual/conceptual) between the ongoing and PM tasks such that two conditions involved a match of perceptual processing and one condition involved a mismatch in processing (conceptual ongoing task/perceptual PM task). One of the matched processing conditions also created a focal PM task, whereas the other two conditions were considered non-focal (Einstein & McDaniel, 2005). PM task accuracy and ongoing task completion speed in baseline and PM task conditions were measured. Accuracy results indicated a higher PM task completion rate for the focal condition than the non-focal conditions, a finding that is consistent with predictions made by the MP view. However, reaction time (RT) analyses indicated that PM task cost did not differ across conditions when practice effects are considered. Thus, the PM accuracy results are consistent with a MP description of PM, but RT results did not support the MP view predictions regarding PM cost.

Estimating PM2.5 concentrations in China from 1957 to 2014 using meteorological visibility data

NASA Astrophysics Data System (ADS)

Ma, Z.; Liu, M.; Wen, T.; Bi, J.

2017-12-01

PM2.5 is a major air pollutant that has caused severe adverse health impacts in China. It was not until late 2012 that China established its ground PM2.5 monitoring network. The lack of ground PM2.5 measurements before 2013 makes it difficult to assess the long-term trends of PM2.5 and its health impacts in China. PM2.5 has been widely recognized as an air pollutant that would cause visibility degradation. Given the facts that the visibility data has been available since 1950s in most major cities in China, it provides a potential way to figure out the long-term ground PM2.5 concentrations. In this work, we developed a national-scale spatiotemporal linear mixed effects model to estimate the long-term PM2.5 concentrations in China from 1957 to 2014 using ground visibility monitoring data as the primary predictor. We used the 2014 data to develop the model. The overall model-fitting and cross-validation R2 is 0.74 and 0.72, suggesting that the model is not over-fitted. Validation beyond the model year (2014) indicated that the model could generate accurate historical PM2.5 concentrations at the monthly (R2 = 0.72) level. Results show that air pollution is not a new environmental issue that occurs in the recent decades but a problem existing in a longer time before 1980. The PM2.5 concentrations have reached 60-80 µg/m3 in the north part of North China Plain during 1950s-1960s and increased to generally higher than 90 µg/m3 during 1970s. The results also show that the entire China experienced an overall increasing trend (0.20 µg/m3/yr, P<0.001) in PM2.5 concentrations from 1957 to 2014 with fluctuations among different periods. This study demonstrated that the visibility data allow us to preliminarily understand the spatiotemporal characteristics of PM2.5 pollution in China in a longer time scale when ground monitoring and satellite remote sensing data are unavailable.

Direct and Indirect Effects of Precipitation on Particulate Matter Concentration in the Aburrá Valley

NASA Astrophysics Data System (ADS)

Roldán Henao, N.; Hoyos Ortiz, C. D.; Herrera, L.

2017-12-01

Wet deposition, including in-cloud scavenging (ICS) and below-cloud scavenging (BCS), is one of the most important processes of particulate matter (PM) removal from the atmosphere. ICS mainly refers to the growth of particulates into cloud droplets, whereas BCS consists of collisions and coalescence between raindrops and pollutants. The overall influence of precipitation in the concentration of fine particulate matter less than 2.5 microns in size (PM2.5) in the Medellín metropolitan area located in the narrow Aburrá Valley within the Colombian Andes is assessed using weather radar derived precipitation with 5 minutes resolution and hourly data from air quality monitoring stations from the Medellín Early Warning System ( Sistema de Alerta Temprana de Medellin y el Valle de Aburra -SIATA-) monitoring network. A non-parametric probabilistic analysis is proposed in order to understand the net influence of precipitation within the diurnal cycle. Probability density functions (PDF) of PM2.5 concentration during precipitations events as well as under dry conditions are analyzed for every hour of the day. The overlapping coefficient for these distributions was used, along with the Wilcoxon Mann-Whitney test, in order to summarized the net effect of precipitation in aerosol concentration. Evidence suggests that, while there is a clear and significant role of precipitation in aerosol concentration, the net effect is contrasting and strongly depends on the diurnal cycle of atmospheric stability. During stable conditions in the lower troposphere, typically occurring during the night and before midmorning, evidence suggest that precipitation reduces the near-surface PM2.5 concentration due to an effective BCS resulting in net negative forcing. On the other hand, when a precipitation event takes place during the day, when the lower troposphere is typically unstable, the PM2.5 concentration increases, suggesting an net positive forcing given that the BCS is offset by the atmospheric stabilization effect of precipitation, which in turns results in near-surface PM accumulation.

Spatiotemporal estimation of historical PM2.5 concentrations using PM10, meteorological variables, and spatial effect

NASA Astrophysics Data System (ADS)

Li, Lianfa; Wu, Anna H.; Cheng, Iona; Chen, Jiu-Chiuan; Wu, Jun

2017-10-01

Monitoring of fine particulate matter with diameter <2.5 μm (PM2.5) started from 1999 in the US and even later in many other countries. The lack of historical PM2.5 data limits epidemiological studies of long-term exposure of PM2.5 and health outcomes such as cancer. In this study, we aimed to design a flexible approach to reliably estimate historical PM2.5 concentrations by incorporating spatial effect and the measurements of existing co-pollutants such as particulate matter with diameter <10 μm (PM10) and meteorological variables. Monitoring data of PM10, PM2.5, and meteorological variables covering the entire state of California were obtained from 1999 through 2013. We developed a spatiotemporal model that quantified non-linear associations between PM2.5 concentrations and the following predictor variables: spatiotemporal factors (PM10 and meteorological variables), spatial factors (land-use patterns, traffic, elevation, distance to shorelines, and spatial autocorrelation), and season. Our model accounted for regional-(county) scale spatial autocorrelation, using spatial weight matrix, and local-scale spatiotemporal variability, using local covariates in additive non-linear model. The spatiotemporal model was evaluated, using leaving-one-site-month-out cross validation. Our final daily model had an R2 of 0.81, with PM10, meteorological variables, and spatial autocorrelation, explaining 55%, 10%, and 10% of the variance in PM2.5 concentrations, respectively. The model had a cross-validation R2 of 0.83 for monthly PM2.5 concentrations (N = 8170) and 0.79 for daily PM2.5 concentrations (N = 51,421) with few extreme values in prediction. Further, the incorporation of spatial effects reduced bias in predictions. Our approach achieved a cross validation R2 of 0.61 for the daily model when PM10 was replaced by total suspended particulate. Our model can robustly estimate historical PM2.5 concentrations in California when PM2.5 measurements were not available.

Evaluation of coarse and fine particles in diverse Indian environments.

PubMed

George, K V; Patil, Dinakar D; Anil, Mulukutla N V; Kamal, Neel; Alappat, Babu J; Kumar, Prashant

2017-02-01

The estimates of airborne fine particle (PM 2.5 ) concentrations are possible through rigorous empirical correlations based on the monitored PM 10 data. However, such correlations change depending on the nature of sources in diverse ambient environments and, therefore, have to be environment specific. Studies presenting such correlations are limited but needed, especially for those areas, where PM 2.5 is not routinely monitored. Moreover, there are a number of studies focusing on urban environments but very limited for coal mines and coastal areas. The aim of this study is to comprehensively analyze the concentrations of both PM 10 and PM 2.5 and develop empirical correlations between them. Data from 26 different sites spread over three distinct environments, which are a relatively clean coastal area, two coal mining areas, and a highly urbanized area in Delhi were used for the study. Distributions of PM in the 0.43-10-μm size range were measured using eight-stage cascade impactors. Regression analysis was used to estimate the percentage of PM 2.5 in PM 10 across distinct environments for source identification. Relatively low percentage of PM 2.5 concentrations (21, 28, and 32%) in PM 10 were found in clean coastal and two mining areas, respectively. Percentage of PM 2.5 concentrations in PM 10 in the highly urbanized area of Delhi was 51%, indicating a presence of a much higher percentage of fine particles due to vehicular combustion in Delhi. The findings of this work are important in estimating concentrations of much harmful fine particles from coarse particles across distinct environments. The results are also useful in source identification of particulates as differences in the percentage of PM 2.5 concentrations in PM 10 can be attributed to characteristics of sources in the diverse ambient environments.

METHODS INTERCOMPARISON OF SAMPLERS FOR EPA'S NATIONAL PM 2.5 CHEMICAL SPECIATION NETWORK

EPA Science Inventory

The objective of this sampler intercomparison field study is to determine the performance characteristics for the collection of the chemical components of PM2.5 by the chemical speciation monitors developed for the national PM2.5 network relative to each other, to the Federal R...

Monitoring of treatment responses and clonal evolution of tumor cells by circulating tumor DNA of heterogeneous mutant EGFR genes in lung cancer.

PubMed

Imamura, Fumio; Uchida, Junji; Kukita, Yoji; Kumagai, Toru; Nishino, Kazumi; Inoue, Takako; Kimura, Madoka; Oba, Shigeyuki; Kato, Kikuya

2016-04-01

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have dramatic effects on EGFR-mutant non-small-cell lung cancer (NSCLC). However, most patients experience disease recurrences, approximately half of which are T790M-mediated. Monitoring EGFR status with re-biopsy has spatiotemporal limitations. EGFR circulating tumor DNA (ctDNA) in serial plasma samples was amplified and 10(5) of them were sequenced with a next-generation sequencer. Plasma mutation (PM) score was defined as the number of reads containing deletions/substitutions in 10(5)EGFR cell free DNA (cfDNA). PM scores of various EGFR mutations showed dynamic, case-specific changes during EGFR-TKI treatments in 52 patients. The effects of the treatment on EGFR ctDNA were evaluated in 38 patients with elevated pre-treatment PM scores. The ctDNA responses correlated well with radiologic responses in radiologic good responders, whereas correlation was poor in non-responders. In addition to the peaks for the most prevalent ctDNA, small peaks of ctDNA with different types of activating EGFR mutations or the T790M mutation (early T790M ctDNA) appeared transiently in 10.5% and 26.3%, respectively. Early T790M ctDNA disappeared in all patients, including 7 who eventually developed acquired resistance accompanied by elevated levels of T790M ctDNA. Monitoring ctDNA is useful in evaluating treatment responses and monitoring driver oncogene status in NSCLC. ctDNA revealed clonal heterogeneity and genetic processes of cancer evolution in individual patients. The simple presence of the T790M mutation may be insufficient to confer EGFR-TKI resistance to tumor cells. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Application of a combined measurement and modeling method to quantify windblown dust emissions from the exposed playa at Mono Lake, California.

PubMed

Ono, Duane; Kiddoo, Phill; Howard, Christopher; Davis, Guy; Richmond, Kenneth

2011-10-01

Particulate matter < or =10 microm (PM10) emissions due to wind erosion can vary dramatically with changing surface conditions. Crust formation, mechanical disturbance, soil texture, moisture, and chemical content of the soil can affect the amount of dust emitted during a wind event. A refined method of quantifying windblown dust emissions was applied at Mono Lake, CA, to account for changing surface conditions. This method used a combination of real-time sand flux monitoring, ambient PM10 monitoring, and dispersion modeling to estimate dust emissions and their downwind impact. The method identified periods with high emissions and periods when the surface was stable (no sand flux), even though winds may have been high. A network of 25 Cox sand catchers (CSCs) was used to measure the mass of saltating particles to estimate sand flux rates across a 2-km2 area. Two electronic sensors (Sensits) were used to time-resolve the CSC sand mass to estimate hourly sand flux rates, and a perimeter tapered element oscillating microbalance (TEOM) monitor measured hourly PM10 concentrations. Hourly sand flux rates were related by dispersion modeling to hourly PM10 concentrations to back-calculate the ratio of vertical PM10 flux to horizontal sand flux (K-factors). Geometric mean K-factor values (K(f)) were found to change seasonally, ranging from 1.3 x 10(-5) to 5.1 x 10(-5) for sand flux measured at 15 cm above the surface (q15). Hourly PM10 emissions, F, were calculated by applying seasonal K-factors to sand flux measurements (F = K(f) x q15). The maximum hourly PM10 emission rate from the study area was 76 g/m2 x hr (10-m wind speed = 23.5 m/sec). Maximum daily PM10 emissions were estimated at 450 g/m2 x day, and annual emissions at 1095 g/m2 x yr. Hourly PM10 emissions were used by the U.S. Environmental Protection Agency (EPA) guideline AERMOD dispersion model to estimate downwind ambient impacts. Model predictions compared well with monitor concentrations, with hourly PM10 ranging from 16 to over 60,000 microg/m3 (slope = 0.89, R2 = 0.77).

77 FR 24200 - Clean Air Act Operating Permit Program; Petitions for Objection to State Operating Permits for...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-23

... without requiring preconstruction monitoring for particulate matter less than 10 microns (PM 10 ), sulfur dioxide (SO 2 ), hydrogen sulfide (H 2 S), total reduced sulfur (TRS) and sulfuric acid mist; and (5) LDEQ... in the decision-making process. In the 2011 Petition for the modified title V pig iron permit and for...

Does Parental Monitoring Moderate the Relation between Parent-Child Communication and Pre-Coital Sexual Behaviours among Urban, Minority Early Adolescents?

ERIC Educational Resources Information Center

Santa Maria, Diane; Markham, Christine; Swank, Paul; Baumler, Elizabeth; McCurdy, Sheryl; Tortolero, Susan

2014-01-01

This study examined parental monitoring (PM) as a potential moderator of the relation between parent-child communication (PCC) and pre-coital sexual behaviours (PCSB) in an urban, minority, early adolescent population. Seventh-grade students (n = 1609) reported PCC, PM and PCSB. Multivariable logistic regression was conducted to assess for…

Influence of Exposure Error and Effect Modification by Socioeconomic Status on the Association of Acute Cardiovascular Mortality with Particulate Matter in Phoenix

EPA Science Inventory

Using ZIP code-level mortality data, the association of cardiovascular mortality with PM_2.5 and PM_10-2.5,measured at a central monitoring site, was determined for three populations at different distances from the monitoring site but with similar numbers of d...

Development of the GC-MS organic aerosol monitor (GC-MS OAM) for in-field detection of particulate organic compounds

NASA Astrophysics Data System (ADS)

Cropper, Paul M.; Overson, Devon K.; Cary, Robert A.; Eatough, Delbert J.; Chow, Judith C.; Hansen, Jaron C.

2017-11-01

Particulate matter (PM) is among the most harmful air pollutants to human health, but due to its complex chemical composition is poorly characterized. A large fraction of PM is composed of organic compounds, but these compounds are not regularly monitored due to limitations in current sampling and analysis techniques. The Organic Aerosol Monitor (GC-MS OAM) combines a collection device with thermal desorption, gas chromatography and mass spectrometry to quantitatively measure the carbonaceous components of PM on an hourly averaged basis. The GC-MS OAM is fully automated and has been successfully deployed in the field. It uses a chemically deactivated filter for collection followed by thermal desorption and GC-MS analysis. Laboratory tests show that detection limits range from 0.2 to 3 ng for 16 atmospherically relevant compounds, with the possibility for hundreds more. The GC-MS OAM was deployed in the field for semi-continuous measurement of the organic markers, levoglucosan, dehydroabietic acid, and polycyclic aromatic hydrocarbons (PAHs) from January to March 2015. Results illustrate the significance of this monitoring technique to characterize the organic components of PM and identify sources of pollution.

Reduction of atmospheric fine particle level by restricting the idling vehicles around a sensitive area.

PubMed

Lee, Yen-Yi; Lin, Sheng-Lun; Yuan, Chung-Shin; Lin, Ming-Yeng; Chen, Kang-Shin

2018-07-01

Atmospheric particles are a major problem that could lead to harmful effects on human health, especially in densely populated urban areas. Chiayi is a typical city with very high population and traffic density, as well as being located at the downwind side of several pollution sources. Multiple contributors for PM 2.5 (particulate matter with an aerodynamic diameter ≥2.5 μm) and ultrafine particles cause complicated air quality problems. This study focused on the inhibition of local emission sources by restricting the idling vehicles around a school area and evaluating the changes in surrounding atmospheric PM conditions. Two stationary sites were monitored, including a background site on the upwind side of the school and a campus site inside the school, to monitor the exposure level, before and after the idling prohibition. In the base condition, the PM 2.5  mass concentrations were found to increase 15% from the background, whereas the nitrate (NO 3 - ) content had a significant increase at the campus site. The anthropogenic metal contents in PM 2.5 were higher at the campus site than the background site. Mobile emissions were found to be the most likely contributor to the school hot spot area by chemical mass balance modeling (CMB8.2). On the other hand, the PM 2.5 in the school campus fell to only 2% after idling vehicle control, when the mobile source contribution reduced from 42.8% to 36.7%. The mobile monitoring also showed significant reductions in atmospheric PM 2.5 , PM 0.1 , polycyclic aromatic hydrocarbons (PAHs), and black carbon (BC) levels by 16.5%, 33.3%, 48.0%, and 11.5%, respectively. Consequently, the restriction of local idling emission was proven to significantly reduce PM and harmful pollutants in the hot spots around the school environment. The emission of idling vehicles strongly affects the levels of particles and relative pollutants in near-ground air around a school area. The PM 2.5 mass concentration at a campus site increased from the background site by 15%, whereas NO 3 - and anthropogenic metals also significantly increased. Meanwhile, the PM 2.5 contribution from mobile source in the campus increased 6.6% from the upwind site. An idling prohibition took place and showed impressive results. Reductions of PM 2.5 , ionic component, and non-natural metal contents were found after the idling prohibition. The mobile monitoring also pointed out a significant improvement with the spatial analysis of PM 2.5 , PM 0.1 , PAH, and black carbon concentrations. These findings are very useful to effectively improve the local air quality of a densely city during the rush hour.

A dynamic processes study of PM retention by trees under different wind conditions.

PubMed

Xie, Changkun; Kan, Liyan; Guo, Jiankang; Jin, Sijia; Li, Zhigang; Chen, Dan; Li, Xin; Che, Shengquan

2018-02-01

Particulate matter (PM) is one of the most serious environmental problems, exacerbating respiratory and vascular illnesses. Plants have the ability to reduce non-point source PM pollution through retention on leaves and branches. Studies of the dynamic processes of PM retention by plants and the mechanisms influencing this process will help to improve the efficiency of urban greening for PM reduction. We examined dynamic processes of PM retention and the major factors influencing PM retention by six trees with different branch structure characteristics in wind tunnel experiments at three different wind speeds. The results showed that the changes of PM numbers retained by plant leaves over time were complex dynamic processes for which maximum values could exceed minimum values by over 10 times. The average value of PM measured in multiple periods and situations can be considered a reliable indicator of the ability of the plant to retain PM. The dynamic processes were similar for PM 10 and PM 2.5 . They could be clustered into three groups simulated by continually-rising, inverse U-shaped, and U-shaped polynomial functions, respectively. The processes were the synthetic effect of characteristics such as species, wind speed, period of exposure and their interactions. Continually-rising functions always explained PM retention in species with extremely complex branch structure. Inverse U-shaped processes explained PM retention in species with relatively simple branch structure and gentle wind. The U-shaped processes mainly explained PM retention at high wind speeds and in species with a relatively simple crown. These results indicate that using plants with complex crowns in urban greening and decreasing wind speed in plant communities increases the chance of continually-rising or inverse U-shaped relationships, which have a positive effect in reducing PM pollution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial assessment of air quality patterns in Malaysia using multivariate analysis

NASA Astrophysics Data System (ADS)

Dominick, Doreena; Juahir, Hafizan; Latif, Mohd Talib; Zain, Sharifuddin M.; Aris, Ahmad Zaharin

2012-12-01

This study aims to investigate possible sources of air pollutants and the spatial patterns within the eight selected Malaysian air monitoring stations based on a two-year database (2008-2009). The multivariate analysis was applied on the dataset. It incorporated Hierarchical Agglomerative Cluster Analysis (HACA) to access the spatial patterns, Principal Component Analysis (PCA) to determine the major sources of the air pollution and Multiple Linear Regression (MLR) to assess the percentage contribution of each air pollutant. The HACA results grouped the eight monitoring stations into three different clusters, based on the characteristics of the air pollutants and meteorological parameters. The PCA analysis showed that the major sources of air pollution were emissions from motor vehicles, aircraft, industries and areas of high population density. The MLR analysis demonstrated that the main pollutant contributing to variability in the Air Pollutant Index (API) at all stations was particulate matter with a diameter of less than 10 μm (PM10). Further MLR analysis showed that the main air pollutant influencing the high concentration of PM10 was carbon monoxide (CO). This was due to combustion processes, particularly originating from motor vehicles. Meteorological factors such as ambient temperature, wind speed and humidity were also noted to influence the concentration of PM10.

Source apportionment of PM2.5 chemically speciated mass and particle number concentrations in New York City

NASA Astrophysics Data System (ADS)

Masiol, M.; Hopke, P. K.; Felton, H. D.; Frank, B. P.; Rattigan, O. V.; Wurth, M. J.; LaDuke, G. H.

2017-01-01

The major sources of fine particulate matter (PM2.5) in New York City (NYC) were apportioned by applying positive matrix factorization (PMF) to two different sets of particle characteristics: mass concentrations using chemical speciation data and particle number concentrations (PNC) using number size distribution, continuously monitored gases, and PM2.5 data. Post-processing was applied to the PMF results to: (i) match with meteorological data, (ii) use wind data to detect the likely locations of the local sources, and (iii) use concentration weighted trajectory models to assess the strength of potential regional/transboundary sources. Nine sources of PM2.5 mass were apportioned and identified as: secondary ammonium sulfate, secondary ammonium nitrate, road traffic exhaust, crustal dust, fresh sea-salt, aged sea-salt, biomass burning, residual oil/domestic heating and zinc. The sources of PNC were investigated using hourly average number concentrations in six size bins, gaseous air pollutants, mass concentrations of PM2.5, particulate sulfate, OC, and EC. These data were divided into 3 periods indicative of different seasonal conditions. Five sources were resolved for each period: secondary particles, road traffic, NYC background pollution (traffic and oil heating largely in Manhattan), nucleation and O3-rich aerosol. Although traffic does not account for large amounts of PM2.5 mass, it was the main source of particles advected from heavily trafficked zones. The use of residual oil had limited impacts on PM2.5 mass but dominates PNC in cold periods.

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.

VIIRS satellite and ground pm2.5 monitoring data

EPA Pesticide Factsheets

contains all satellite, pm2.5, and meteorological data used in statistical modeling effort to improve prediction of pm2.5This dataset is associated with the following publication:Schliep, E., A. Gelfand, and D. Holland. Autoregressive Spatially-Varying Coefficient Models for Predicting Daily PM2:5 Using VIIRS Satellite AOT. Advances in Statistical Climatology, Meteorology and Oceanography. Copernicus Publications, Katlenburg-Lindau, GERMANY, 1(0): 59-74, (2015).

77 FR 45954 - Approval and Promulgation of Implementation Plans and Designations of Areas for Air Quality...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-02

...EPA is making two determinations, one regarding the Knoxville, Tennessee, 1997 annual fine particulate (PM2.5) nonattainment area and one regarding the Knoxville-Sevierville-La Follette, Tennessee, 2006 24-hour PM2.5 nonattainment area (both areas have the same geographic boundary and will hereafter be collectively referred to as the ``Knoxville Area'' or ``Area''). First, EPA is determining that the Area has attained the 1997 annual PM2.5 National Ambient Air Quality Standards (NAAQS or ``standard''). Second, EPA is determining that the Area has attained the 2006 24-hour PM2.5 NAAQS. These determinations of attaining data are based upon quality-assured and certified ambient air monitoring data for the 2009-2011 period, showing that the Area has monitored attainment of the 1997 annual PM2.5 NAAQS and 2006 24-hour PM2.5 NAAQS. The requirements for the Area to submit an attainment demonstration and associated reasonably available control measures (RACM), reasonable further progress (RFP) plans, contingency measures, and other planning State Implementation Plan (SIP) revisions related to attainment of the standards shall be suspended so long as the Area continues to attain the respective PM2.5 NAAQS.

Heart rate variability and DNA methylation levels are altered after short-term metal fume exposure among occupational welders: a repeated-measures panel study.

PubMed

Fan, Tianteng; Fang, Shona C; Cavallari, Jennifer M; Barnett, Ian J; Wang, Zhaoxi; Su, Li; Byun, Hyang-Min; Lin, Xihong; Baccarelli, Andrea A; Christiani, David C

2014-12-16

In occupational settings, boilermakers are exposed to high levels of metallic fine particulate matter (PM2.5) generated during the welding process. The effect of welding PM2.5 on heart rate variability (HRV) has been described, but the relationship between PM2.5, DNA methylation, and HRV is not known. In this repeated-measures panel study, we recorded resting HRV and measured DNA methylation levels in transposable elements Alu and long interspersed nuclear element-1 (LINE-1) in peripheral blood leukocytes under ambient conditions (pre-shift) and right after a welding task (post-shift) among 66 welders. We also monitored personal PM2.5 level in the ambient environment and during the welding procedure. The concentration of welding PM2.5 was significantly higher than background levels in the union hall (0.43 mg/m3 vs. 0.11 mg/m3, p < 0.0001). The natural log of transformed power in the high frequency range (ln HF) had a significantly negative association with PM2.5 exposure (β = -0.76, p = 0.035). pNN10 and pNN20 also had a negative association with PM2.5 exposure (β = -0.16%, p = 0.006 and β = -0.13%, p = 0.030, respectively). PM2.5 was positively associated with LINE-1 methylation [β = 0.79%, 5-methylcytosince (%mC), p = 0.013]; adjusted for covariates. LINE-1 methylation did not show an independent association with HRV. Acute decline of HRV was observed following exposure to welding PM2.5 and evidence for an epigenetic response of transposable elements to short-term exposure to high-level metal-rich particulates was reported.

The direct influence of ship traffic on atmospheric PM2.5, PM10 and PAH in Venice.

PubMed

Contini, D; Gambaro, A; Belosi, F; De Pieri, S; Cairns, W R L; Donateo, A; Zanotto, E; Citron, M

2011-09-01

The direct influence of ship traffic on atmospheric levels of coarse and fine particulate matter (PM(2.5), PM(10)) and fifteen polycyclic aromatic hydrocarbons (PAHs) has been estimated in the urban area of Venice. Data analysis has been performed on results collected at three sites over the summer, when ship traffic is at a maximum. Results indicate that monitoring of the PM daily concentrations is not sufficiently detailed for the evaluation of this contribution, even though it could be useful for specific markers such as PAHs. Therefore a new methodology, based on high temporal resolution measurements coupled with wind direction information and the database of ship passages of the Harbour Authority of Venice has been developed. The sampling sites were monitored with optical detectors (DustTrack(®) and Mie pDR-1200) operating at a high temporal resolution (20s and 1s respectively) for PM(2.5) and PM(10). PAH in the particulate and gas phases were recovered from quartz fibre filters and polyurethane foam plugs using pressurised solvent extraction, the extracts were then analysed by gas chromatography- high-resolution mass spectrometry. Our results shows that the direct contribution of ships traffic to PAHs in the gas phase is 10% while the contribution to PM(2.5) and to PM(10) is from 1% up to 8%. Copyright © 2011 Elsevier Ltd. All rights reserved.

Ambient exposure to coarse and fine particle emissions from building demolition

NASA Astrophysics Data System (ADS)

Azarmi, Farhad; Kumar, Prashant

2016-07-01

Demolition of buildings produce large quantities of particulate matter (PM) that could be inhaled by on-site workers and people living in the neighbourhood, but studies assessing ambient exposure at the real-world demolition sites are limited. We measured concentrations of PM10 (≤10 μm), PM2.5 (≤2.5 μm) and PM1 (≤1 μm) along with local meteorology for 54 working hours over the demolition period. The measurements were carried out at (i) a fixed-site in the downwind of demolished building, (ii) around the site during demolition operation through mobile monitoring, (iii) different distances away from the demolition site through sequential monitoring, and (iv) inside an excavator vehicle cabin and on-site temporary office for engineers. Position of the PM instrument was continuously recorded using a Global Positioning System on a second basis during mobile measurements. Fraction of coarse particles (PM2.5-10) contributed 89 (with mean particle mass concentration, PMC ≈ 133 ± 17 μg m-3), 83 (100 ± 29 μg m-3), and 70% (59 ± 12 μg m-3) of total PMC during the fixed-site, mobile monitoring and sequential measurements, respectively, compared with only 50% (mean 12 ± 6 μg m-3) during the background measurements. The corresponding values for fine particles (PM2.5) were 11, 17 and 30% compared with 50% during background, showing a much greater release of coarse particles during demolition. The openair package in R and map source software (ArcGIS) were used to assess spatial variation of PMCs in downwind and upwind of the demolition site. A modified box model was developed to determine the emission factors, which were 210, 73 and 24 μg m-2 s-1 for PM10, PM2.5 and PM1, respectively. The average respiratory deposited doses to coarse (and fine) particles inside the excavator cabin and on-site temporary office increased by 57- (and 5-) and 13- (and 2-) times compared with the local background level, respectively. The monitoring stations in downwind direction illustrated a logarithmic decrease of PM with distance. Energy-dispersive X-ray spectroscopy and scanning electron microscopy were used to assess physicochemical features of particles. The minerals such as silica were found as a marker of demolition dust and elements such as sulphur coming from construction machinery emissions. Findings of this study highlight a need to limit occupational exposure of individuals to coarse and fine particles by enforcing effective engineering controls.

An assessment of air pollution and its attributable mortality in Ulaanbaatar, Mongolia.

PubMed

Allen, Ryan W; Gombojav, Enkhjargal; Barkhasragchaa, Baldorj; Byambaa, Tsogtbaatar; Lkhasuren, Oyuntogos; Amram, Ofer; Takaro, Tim K; Janes, Craig R

2013-03-01

Epidemiologic studies have consistently reported associations between outdoor fine particulate matter (PM 2.5 ) air pollution and adverse health effects. Although Asia bears the majority of the public health burden from air pollution, few epidemiologic studies have been conducted outside of North America and Europe due in part to challenges in population exposure assessment. We assessed the feasibility of two current exposure assessment techniques, land use regression (LUR) modeling and mobile monitoring, and estimated the mortality attributable to air pollution in Ulaanbaatar, Mongolia. We developed LUR models for predicting wintertime spatial patterns of NO 2 and SO 2 based on 2-week passive Ogawa measurements at 37 locations and freely available geographic predictors. The models explained 74% and 78% of the variance in NO 2 and SO 2 , respectively. Land cover characteristics derived from satellite images were useful predictors of both pollutants. Mobile PM 2.5 monitoring with an integrating nephelometer also showed promise, capturing substantial spatial variation in PM 2.5 concentrations. The spatial patterns in SO 2 and PM, seasonal and diurnal patterns in PM 2.5 , and high wintertime PM 2.5 /PM 10 ratios were consistent with a major impact from coal and wood combustion in the city's low-income traditional housing (ger) areas. The annual average concentration of PM 2.5 measured at a centrally located government monitoring site was 75 μg/m 3 or more than seven times the World Health Organization's PM 2.5 air quality guideline, driven by a wintertime average concentration of 148 μg/m 3 . PM 2.5 concentrations measured in a traditional housing area were higher, with a wintertime mean PM 2.5 concentration of 250 μg/m 3 . We conservatively estimated that 29% (95% CI, 12-43%) of cardiopulmonary deaths and 40% (95% CI, 17-56%) of lung cancer deaths in the city are attributable to outdoor air pollution. These deaths correspond to nearly 10% of the city's total mortality, with estimates ranging to more than 13% of mortality under less conservative model assumptions. LUR models and mobile monitoring can be successfully implemented in developing country cities, thus cost-effectively improving exposure assessment for epidemiology and risk assessment. Air pollution represents a major threat to public health in Ulaanbaatar, Mongolia, and reducing home heating emissions in traditional housing areas should be the primary focus of air pollution control efforts.

Exploring variability in pedestrian exposure to fine particulates (PM 2.5) along a busy road

NASA Astrophysics Data System (ADS)

Greaves, Stephen; Issarayangyun, Tharit; Liu, Qian

In August 2006, pedestrian exposure to PM 2.5 was monitored along a busy roadway in Sydney, Australia. The objective of the campaign was to assess the factors affecting exposure at both an inter- and intra-trip level. PM 2.5 measurements were made at second-by-second intervals using a portable aerosol monitor, while simultaneously recording location with a personal GPS device. A digital voice recorder was used to record any events or circumstances, perceived to notably increase potential PM 2.5 levels. The average PM 2.5 concentration for the 39 trips conducted was 12.8 μg m -3, which while 40% higher than concurrent ambient measurements was well within proposed daily standards for Australia. Multivariate time-series methods were then applied to study the effects of various interventions on PM 2.5 at an intra-trip level while controlling for autocorrelation. Wind speed, traffic volumes and clearway operations (independent of traffic volumes) were found to be significant predictors in addition to the previous PM 2.5 concentrations. Sensitivity analysis showed doubling traffic volumes increased PM 2.5 concentrations by 26%, while each 5 km h -1 increase in wind speed increased PM 2.5 concentrations by 10%. Several PM 2.5 hotspots were identified where concentrations exceeded 100 μg m -3. These were attributed to specific traffic (intersections, trucks, buses) and non-traffic sources (pedestrians smoking), typically only lasting a few seconds.

A Comprehensive Evaluation of a Two-Channel Portable Monitor to “Rule in” Obstructive Sleep Apnea

PubMed Central

Ward, Kim L.; McArdle, Nigel; James, Alan; Bremner, Alexandra P.; Simpson, Laila; Cooper, Matthew N.; Palmer, Lyle J.; Fedson, Annette C.; Mukherjee, Sutapa; Hillman, David R.

2015-01-01

Study Objectives: We hypothesized that a dual-channel portable monitor (PM) device could accurately identify patients who have a high pretest probability of obstructive sleep apnea (OSA), and we evaluated factors that may contribute to variability between PM and polysomnography (PSG) results. Methods: Consecutive clinic patients (N = 104) with possible OSA completed a home PM study, a PM study simultaneous with laboratory PSG, and a second home PM study. Uniform data analysis methods were applied to both PM and PSG data. Primary outcomes of interest were the positive likelihood ratio (LR+) and sensitivity of the PM device to “rule-in” OSA, defined as an apnea-hypopnea index (AHI) ≥ 5 events/h on PSG. Effects of different test environment and study nights, and order of study and analysis methods (manual compared to automated) on PM diagnostic accuracy were assessed. Results: The PM has adequate LR+ (4.8), sensitivity (80%), and specificity (83%) for detecting OSA in the unattended home setting when benchmarked against laboratory PSG, with better LR+ (> 5) and specificity (100%) and unchanged sensitivity (80%) in the simultaneous laboratory comparison. There were no significant night-night (all p > 0.10) or study order effects (home or laboratory first, p = 0.08) on AHI measures. Manual PM data review improved case finding accuracy, although this was not statistically significant (all p > 0.07). Misclassification was more frequent where OSA was mild. Conclusions: Overall performance of the PM device is consistent with current recommended criteria for an “acceptable” device to confidently “rule-in” OSA (AHI ≥ 5 events/h) in a high pretest probability clinic population. Our data support the utility of simple two-channel diagnostic devices to confirm the diagnosis of OSA in the home environment. Commentary: A commentary on this article appears in this issue on page 411. Citation: Ward KL, McArdle N, James A, Bremner AP, Simpson L, Cooper MN, Palmer LJ, Fedson AC, Mukherjee S, Hillman DR. A comprehensive evaluation of a two-channel portable monitor to “rule in” obstructive sleep apnea. J Clin Sleep Med 2015;11(4):433–444. PMID:25580606

Autoregressive spatially varying coefficients model for predicting daily PM2.5 using VIIRS satellite AOT

NASA Astrophysics Data System (ADS)

Schliep, E. M.; Gelfand, A. E.; Holland, D. M.

2015-12-01

There is considerable demand for accurate air quality information in human health analyses. The sparsity of ground monitoring stations across the United States motivates the need for advanced statistical models to predict air quality metrics, such as PM2.5, at unobserved sites. Remote sensing technologies have the potential to expand our knowledge of PM2.5 spatial patterns beyond what we can predict from current PM2.5 monitoring networks. Data from satellites have an additional advantage in not requiring extensive emission inventories necessary for most atmospheric models that have been used in earlier data fusion models for air pollution. Statistical models combining monitoring station data with satellite-obtained aerosol optical thickness (AOT), also referred to as aerosol optical depth (AOD), have been proposed in the literature with varying levels of success in predicting PM2.5. The benefit of using AOT is that satellites provide complete gridded spatial coverage. However, the challenges involved with using it in fusion models are (1) the correlation between the two data sources varies both in time and in space, (2) the data sources are temporally and spatially misaligned, and (3) there is extensive missingness in the monitoring data and also in the satellite data due to cloud cover. We propose a hierarchical autoregressive spatially varying coefficients model to jointly model the two data sources, which addresses the foregoing challenges. Additionally, we offer formal model comparison for competing models in terms of model fit and out of sample prediction of PM2.5. The models are applied to daily observations of PM2.5 and AOT in the summer months of 2013 across the conterminous United States. Most notably, during this time period, we find small in-sample improvement incorporating AOT into our autoregressive model but little out-of-sample predictive improvement.

Coarse particulate matter concentrations from residential outdoor sites associated with the North Carolina Asthma and Children's Environment Studies (NC-ACES)

NASA Astrophysics Data System (ADS)

Chen, Fu-Lin; Williams, Ronald; Svendsen, Erik; Yeatts, Karin; Creason, John; Scott, James; Terrell, Dock; Case, Martin

Coarse particulate matter (PM 10) concentration data from residential outdoor sites were collected using portable samplers as part of an exposure assessment for the North Carolina Asthma and Children's Environment Studies (NC-ACES). PM 10 values were estimated using the differential between independent PM 10 and PM 2.5 collocated MiniVol measurements. Repeated daily 24-h integrated PM 10 and PM 2.5 residential outdoor monitoring was performed at a total of 26 homes during September 2003-June 2004 in the Research Triangle Park, NC area. This effort resulted in the collection of 73 total daily measurements. This assessment was conducted to provide data needed to investigate the association of exposures to coarse particle PM mass concentrations with observed human health effects. Potential instrument bias between the differential MiniVol methodology and a dichotomous sampler were investigated. Results indicated that minimal bias of PM 10 mass concentration estimates (slope = 0.8, intercept =0.36μg m -3) existed between the dichotomous and differential MiniVol procedures. Residential outdoor PM 10 mass concentrations were observed to be highly variable across measurement days and ranged from 1.1 to 12.6μg m -3 (mean of 5.4μg m -3). An average correlation coefficient of r=0.75 existed between residential outdoor PM 10 mass concentrations and those obtained from the central ambient monitoring site. Temporal and spatial variability of PM 10 mass concentrations during the study were observed and are described in this report.

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;

Indoor-outdoor concentrations of RSPM in classroom of a naturally ventilated school building near an urban traffic roadway

NASA Astrophysics Data System (ADS)

Goyal, Radha; Khare, Mukesh

2009-12-01

A study on indoor-outdoor RSPM (PM 10, PM 2.5 and PM 1.0) mass concentration monitoring has been carried out at a classroom of a naturally ventilated school building located near an urban roadway in Delhi City. The monitoring has been planned for a year starting from August 2006 till August 2007, including weekdays (Monday, Wednesday and Friday) and weekends (Saturday and Sunday) from 8:0 a.m. to 2:0 p.m., in order to take into account hourly, daily, weekly, monthly and seasonal variations in pollutant concentrations. Meteorological parameters, including temperature, rH, pressure, wind speed and direction, and traffic parameters, including its type and volume has been monitored simultaneously to relate the concentrations of indoor-outdoor RSPM with them. Ventilation rate has also been estimated to find out its relation with indoor particulate concentrations. The results of the study indicates that RSPM concentrations in classroom exceeds the permissible limits during all monitoring hours of weekdays and weekends in all seasons that may cause potential health hazards to occupants, when exposed. I/O for all sizes of particulates are greater than 1, which implies that building envelop does not provide protection from outdoor pollutants. Further, a significant influence of meteorological parameters, ventilation rate and of traffic has been observed on I/O. Higher I/O for PM 10 is indicating the presence of its indoor sources in classroom and their indoor concentrations are strongly influenced by activities of occupants during weekdays.

Magnetic biomonitoring by moss bags for industry-derived air pollution in SW Finland

NASA Astrophysics Data System (ADS)

Salo, Hanna; Mäkinen, Joni

2014-11-01

We provide the first detailed case study using Sphagnum papillosum moss bags for active magnetic monitoring of airborne industrial pollution in order to evaluate the actual role of various emission sources and the competence of current environmental protection actions relative to the air quality. The origin and spatial spreading of particulate matter (PM) based on magnetic, chemical, and SEM-EDX analyses was studied around the Industrial Park in Harjavalta, SW Finland. The data was collected during two 6-month sampling periods along 8 km transects in 2010-2011. The results support our hypothesis that the main emission source of PM is not the Cu-Ni smelter's pipe as presumed in previous chemical monitorings. We argue that the hot spot area within the severe impact pollution zone is related to slag processing and/or other unidentified industrial activity. At short distances various dust-providing sources outweigh the fly-ash load from the Cu-Ni smelter's pipe. Active magnetic monitoring by moss bags will help in planning environmental actions as well as in improvement of health conditions for industrial staff and town residents living next to the Industrial Park.

Temporal and spatial distributions of summer-time ground-level fine particulate matters in Baltimore-DC region

NASA Astrophysics Data System (ADS)

Liu, Y.; Greenwald, R.; Sarnat, J.; Hu, X.; Kewada, P.; Morales, Y.; Goldman, G.; Redman, J.; Russell, A. G.

2011-12-01

Environmental epidemiological studies have established a robust association between chronic exposure to ambient level fine particulate matters (PM2.5) and adverse health effects such as COPD, cardiorespiratory diseases, and premature death. Population exposure to PM2.5 has historically been estimated using ground measurements which are often sparse and unevenly distributed. There has been much interest as well as suspicion in both the air quality management and research communities regarding the value of satellite retrieved AOD as particle air pollution indicators. A critical step towards the future use of satellite aerosol products in air quality monitoring and management is to better understand the AOD-PM2.5 association. The existing EPA and IMPROVE networks are insufficient to validate AOD-estimated PM2.5 surface especially when higher resolution satellite products become available in the near future. As part of DISCOVER-AQ mission, we deployed 15 portable filter-based samplers alongside of ground-based sun photometers of the Distributed Regional Aerosol Gridded Observation Network (DRAGON) in July 2011. Gravimetric analyses were conducted to estimate 24h PM2.5 mass concentrations, using Teflon filters and Personal Environmental Monitors (PEMs) operated at a flow rate of 4 LPM. Pre- and post-sampling filters were weighed at our weigh room laboratory facilities at the Georgia Institute of Technology. Our objectives are (1) to examine if AOD measured by ground-based sun-photometers with the support from ground-based lidars can provide the fine scale spatial heterogeneity observed by ground PM monitors, and (2) whether PM2.5 levels estimated by satellite AOD agree with this true PM2.5 surface. Study design, instrumentation, and preliminary results of measured PM2.5 spatial patterns in July 2011 will be presented as well as discussion of further data analysis and model development.

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.

Management of Sleep Apnea without High Pretest Probability or with Comorbidities by Three Nights of Portable Sleep Monitoring

PubMed Central

Guerrero, Arnoldo; Embid, Cristina; Isetta, Valentina; Farre, Ramón; Duran-Cantolla, Joaquin; Parra, Olga; Barbé, Ferran; Montserrat, Josep M.; Masa, Juan F.

2014-01-01

Study Objectives: Obstructive sleep apnea (OSA) diagnosis using simplified methods such as portable sleep monitoring (PM) is only recommended in patients with a high pretest probability. The aim is to determine the diagnostic efficacy, consequent therapeutic decision-making, and costs of OSA diagnosis using polysomnography (PSG) versus three consecutive studies of PM in patients with mild to moderate suspicion of sleep apnea or with comorbidity that can mask OSA symptoms. Design and Setting: Randomized, blinded, crossover study of 3 nights of PM (3N-PM) versus PSG. The diagnostic efficacy was evaluated with receiver operating characteristic (ROC) curves. Therapeutic decisions to assess concordance between the two different approaches were performed by sleep physicians and respiratory physicians (staff and residents) using agreement level and kappa coefficient. The costs of each diagnostic strategy were considered. Patients and Results: Fifty-six patients were selected. Epworth Sleepiness Scale was 10.1 (5.3) points. Bland-Altman plot for apnea-hypopnea index (AHI) showed good agreement. ROC curves showed the best area under the curve in patients with PSG AHI ≥ 5 [0.955 (confidence interval = 0.862–0.993)]. For a PSG AHI ≥ 5, a PM AHI of 5 would effectively exclude and confirm OSA diagnosis. For a PSG AHI ≥ 15, a PM AHI ≥ 22 would confirm and PM AHI < 7 would exclude OSA. The best agreement of therapeutic decisions was achieved by the sleep medicine specialists (81.8%). The best cost-diagnostic efficacy was obtained by the 3N-PM. Conclusions: Three consecutive nights of portable monitoring at home evaluated by a qualified sleep specialist is useful for the management of patients without high pretest probability of obstructive sleep apnea or with comorbidities. Clinical Trial Registration: http://www.clinicaltrials.gov, registration number: NCT01820156 Citation: Guerrero A, Embid C, Isetta V, Farre R, Duran-Cantolla J, Parra O, Barbé F, Montserrat JM, Masa JF. Management of sleep apnea without high pretest probability or with comorbidities by three nights of portable sleep monitoring. SLEEP 2014;37(8):1363-1373. PMID:25083017

Decision-Making in the Ventral Premotor Cortex Harbinger of Action

PubMed Central

Pardo-Vazquez, Jose L.; Padron, Isabel; Fernandez-Rey, Jose; Acuña, Carlos

2011-01-01

Although the premotor (PM) cortex was once viewed as the substrate of pure motor functions, soon it was realized that it was involved in higher brain functions. By this it is meant that the PM cortex functions would better be explained as motor set, preparation for limb movement, or sensory guidance of movement rather than solely by a fixed link to motor performance. These findings, together with a better knowledge of the PM cortex histology and hodology in human and non-human primates prompted quantitative studies of this area combining behavioral tasks with electrophysiological recordings. In addition, the exploration of the PM cortex neurons with qualitative methods also suggested its participation in higher functions. Behavioral choices frequently depend on temporal cues, which together with knowledge of previous outcomes and expectancies are combined to decide and choose a behavioral action. In decision-making the knowledge about the consequences of decisions, either correct or incorrect, is fundamental because they can be used to adapt future behavior. The neuronal correlates of a decision process have been described in several cortical areas of primates. Among them, there is evidence that the monkey ventral premotor (PMv) cortex, an anatomical and physiological well-differentiated area of the PM cortex, supports both perceptual decisions and performance monitoring. Here we review the evidence that the steps in a decision-making process are encoded in the firing rate of the PMv neurons. This provides compelling evidence suggesting that the PMv is involved in the use of recent and long-term sensory memory to decide, execute, and evaluate the outcomes of the subjects’ choices. PMID:21991249

Golgi and plasma membrane pools of PI(4)P contribute to plasma membrane PI(4,5)P2 and maintenance of KCNQ2/3 ion channel current

PubMed Central

Dickson, Eamonn J.; Jensen, Jill B.; Hille, Bertil

2014-01-01

Plasma membrane (PM) phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2] regulates the activity of many ion channels and other membrane-associated proteins. To determine precursor sources of the PM PI(4,5)P2 pool in tsA-201 cells, we monitored KCNQ2/3 channel currents and translocation of PHPLCδ1 domains as real-time indicators of PM PI(4,5)P2, and translocation of PHOSH2×2, and PHOSH1 domains as indicators of PM and Golgi phosphatidylinositol 4-phosphate [PI(4)P], respectively. We selectively depleted PI(4)P pools at the PM, Golgi, or both using the rapamycin-recruitable lipid 4-phosphatases. Depleting PI(4)P at the PM with a recruitable 4-phosphatase (Sac1) results in a decrease of PI(4,5)P2 measured by electrical or optical indicators. Depleting PI(4)P at the Golgi with the 4-phosphatase or disrupting membrane-transporting motors induces a decline in PM PI(4,5)P2. Depleting PI(4)P simultaneously at both the Golgi and the PM induces a larger decrease of PI(4,5)P2. The decline of PI(4,5)P2 following 4-phosphatase recruitment takes 1–2 min. Recruiting the endoplasmic reticulum (ER) toward the Golgi membranes mimics the effects of depleting PI(4)P at the Golgi, apparently due to the trans actions of endogenous ER Sac1. Thus, maintenance of the PM pool of PI(4,5)P2 appears to depend on precursor pools of PI(4)P both in the PM and in the Golgi. The decrease in PM PI(4,5)P2 when Sac1 is recruited to the Golgi suggests that the Golgi contribution is ongoing and that PI(4,5)P2 production may be coupled to important cell biological processes such as membrane trafficking or lipid transfer activity. PMID:24843134

Real-time PM10 concentration monitoring on Penang Bridge by using traffic monitoring CCTV

NASA Astrophysics Data System (ADS)

Low, K. L.; Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Wong, C. J.

2007-04-01

For this study, an algorithm was developed to determine concentration of particles less than 10μm (PM10) from still images captured by a CCTV camera on the Penang Bridge. The objective of this study is to remotely monitor the PM10 concentrations on the Penang Bridge through the internet. So, an algorithm was developed based on the relationship between the atmospheric reflectance and the corresponding air quality. By doing this, the still images were separated into three bands namely red, green and blue and their digital number values were determined. A special transformation was then performed to the data. Ground PM10 measurements were taken by using DustTrak TM meter. The algorithm was calibrated using a regression analysis. The proposed algorithm produced a high correlation coefficient (R) and low root-mean-square error (RMS) between the measured and produced PM10. Later, a program was written by using Microsoft Visual Basic 6.0 to download still images from the camera over the internet and implement the newly developed algorithm. Meanwhile, the program is running in real time and the public will know the air pollution index from time to time. This indicates that the technique using the CCTV camera images can provide a useful tool for air quality studies.

Fugitive Dust Emissions: Development of a Real-time Monitor

DTIC Science & Technology

2011-10-01

the mechanical disturbance of soils which injects particles into the air. Common sources of FD include vehicles driving on unpaved roads...agricultural tilling, and heavy construction operations. For these sources the dust-generation process is caused by two basic physical phenomena...visibility, source apportionment , etc. The PM10 standard set by the U.S. Environmental Protection Agency in 1987 is an example of size-selective

Carbon species in PM10 particle fraction at different monitoring sites.

PubMed

Godec, Ranka; Jakovljević, Ivana; Šega, Krešimir; Čačković, Mirjana; Bešlić, Ivan; Davila, Silvije; Pehnec, Gordana

2016-09-01

The aim of this study was to determine and compare the levels of elemental carbon (EC), organic carbon (OC) and polycyclic aromatic hydrocarbons (PAHs) mass concentrations in PM10 particles (particles with aerodynamic diameter less than 10 μm) between seasons (winter and summer) and at different monitoring sites (urban background and rural industrial). Daily samples of airborne particles were collected on pre-fired quartz fibre filters. PM10 mass concentrations were determined gravimetrically. Samples were analysed for OC and EC with the thermal/optical transmittance method (TOT) and for PAHs by high-performance liquid chromatography (HPLC) with a fluorescence detector. Measurements showed seasonal and spatial variations of mass concentrations for carbon species and for all of the measured PAHs (Flu, Pyr, Chry, BaA, BbF, BaP, BkF, BghiP and IP) in PM10 at the urban site and rural monitoring site described here. Diagnostic PAH ratios (Flu/(Flu + Pyr), BaA/(BaA + Cry), IP/(IP + BghiP), BaP/BghiP, IP/BghiP and BaP/(BaP + Chry)) make it possible to assess the sources of pollution, and these showed that diesel vehicles accounted for most pollution at the rural-industrial (RI) site in the summer, whereas coal and wood combustion were the causes of winter pollution. This difference between winter and summer PAH ratios were more expressed at the RI site than at the UB site because at the UB site the predominant heating fuel was gas. The OC/EC ratio yielded the same conclusion. Factor analysis showed that EC and OC originated from traffic at both sites, PAHs with 5 or more benzene rings originated from wood pellets industry or biomass burning, while Pyr and Flu originated from diesel combustion or as a consequence of different atmospheric behaviour - evaporation and participation in oxidation and photo oxidation processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

A national-scale review of air pollutant concentrations measured in the U.S. near-road monitoring network during 2014 and 2015

NASA Astrophysics Data System (ADS)

DeWinter, Jennifer L.; Brown, Steven G.; Seagram, Annie F.; Landsberg, Karin; Eisinger, Douglas S.

2018-06-01

In 2010, the U.S. Environmental Protection Agency (EPA) revised the National Ambient Air Quality Standards (NAAQS) for NO2 to include a primary health-based standard for hourly NO2, and required air quality monitoring next to major roadways in urban areas in the U.S. Requirements for near-road measurements also include carbon monoxide (CO) and particulate matter smaller than 2.5 μm in diameter (PM2.5). We performed a national-scale assessment of air pollutants measured at 81 sites in the near-road environment during the first two years (2014 and 2015) of the new measurement program. We evaluated how concentrations at these locations compared to the NAAQS, to concentrations measured at other sites within the same urban areas, and when considering their site characteristics (distance of monitor to road, traffic volume, and meteorology). We also estimated the contribution of emissions from adjacent roadways at each near-road site to the PM2.5 concentrations above the local urban background concentrations, i.e., the near-road "increment." Hourly values of CO reached a maximum of 4.8 ppm across 31 sites in 2014 and 9.6 ppm across 47 sites in 2015, and were well below the NAAQS levels for both the 1-hr (35 ppm) and 8-hr (9 ppm) standards. Hourly concentrations of near-road NO2 reached 258 ppb across 40 sites in 2014; however, there were only two occurrences of a daily 1-hr maximum NO2 concentration above 100 ppb (the level of the hourly NO2 standard). In 2015, hourly concentrations of near-road NO2, monitored at 61 sites in 55 urban areas, reached 154 ppb. Only 0.0015% (n = 5) of hourly NO2 observations in 2015 exceeded 100 ppb. The highest annual NO2 average recorded in 2015 (29.9 ppb) occurred at the Ontario site located along I-10 in the Los Angeles, California, area and was below the level of the NO2 annual standard (53 ppb); in 2014, the highest annual mean NO2 was also observed in Los Angeles at the Anaheim site (27.1 ppb). In 2014, sites in Cincinnati, Indianapolis, and Louisville recorded annual average PM2.5 concentrations at or above 12 μg/m3 (the level of the annual standard). There were 15 occurrences in 2014 of 24-hr PM2.5 concentrations above the NAAQS level of 35 μg/m3. Annual average PM2.5 exceeded 12 μg/m3 at near-road sites in five urban areas in 2015, and there were 33 days across 12 near-road locations with 24-hr PM2.5 concentrations above 35 μg/m3. Across the near-road monitoring network, annual average PM2.5 concentrations did not have a significant relationship with traffic volume or distance between the monitor and the adjacent roadway; rather, variations in PM2.5 were mostly driven by urban-scale PM2.5, with a typically small "increment" above urban-scale concentrations due to a site's proximity to the roadway. We estimated this increment, i.e., the difference between near-road PM2.5 concentrations and the concentrations at sites in the urban area of each near-road monitor, to be on average 1.2 μg/m3 (σ = 0.3 μg/m3), with a range of -1.2 μg/m3 to 3.1 μg/m3 across the 26 sites (four of which had a negative increment). The near-road increment is on average 13% of the near-road PM2.5, and 15% of the near-road PM2.5 for sites within 20 m of the roadway.

FIELD EVALUATION OF SAMPLERS FOR EPA'S NATIONAL PM 2.5 CHEMICAL SPECIATION NETWORK-PRELIMINARY RESULTS FROM ATLANTA

EPA Science Inventory

The US EPA bas established a national network at nearly 1100 sites to monitor PM2.5 mass for testing compliance with the PM2.5 National Ambient Air Quality Standards. The objective of the field evaluation is to determine the performance characteristics for the collection of the...

77 FR 43032 - Approval and Promulgation of Implementation Plans; Mississippi: New Source Review-Prevention of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-23

...'' particles (e.g., sulfate and nitrate) form in the atmosphere as a result of various chemical reactions. The... chemical reactions to form secondary PM). In most areas of the country, PM 2.5 precursor emissions are... determinations for PM 2.5 NAAQS. These requirements address air quality modeling and monitoring provisions for...

A statistical model for determining impact of wildland fires on Particulate Matter (PM₂.₅) in Central California aided by satellite imagery of smoke.

PubMed

Preisler, Haiganoush K; Schweizer, Donald; Cisneros, Ricardo; Procter, Trent; Ruminski, Mark; Tarnay, Leland

2015-10-01

As the climate in California warms and wildfires become larger and more severe, satellite-based observational tools are frequently used for studying impact of those fires on air quality. However little objective work has been done to quantify the skill these satellite observations of smoke plumes have in predicting impacts to PM2.5 concentrations at ground level monitors, especially those monitors used to determine attainment values for air quality under the Clean Air Act. Using PM2.5 monitoring data from a suite of monitors throughout the Central California area, we found a significant, but weak relationship between satellite-observed smoke plumes and PM2.5 concentrations measured at the surface. However, when combined with an autoregressive statistical model that uses weather and seasonal factors to identify thresholds for flagging unusual events at these sites, we found that the presence of smoke plumes could reliably identify periods of wildfire influence with 95% accuracy. Published by Elsevier Ltd.

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.

Accurate Measurements of Aircraft Engine Soot Emissions Using a CAPS PMssa Monitor

NASA Astrophysics Data System (ADS)

Onasch, Timothy; Thompson, Kevin; Renbaum-Wolff, Lindsay; Smallwood, Greg; Make-Lye, Richard; Freedman, Andrew

2016-04-01

We present results of aircraft engine soot emissions measurements during the VARIAnT2 campaign using CAPS PMssa monitors. VARIAnT2, an aircraft engine non-volatile particulate matter (nvPM) emissions field campaign, was focused on understanding the variability in nvPM mass measurements using different measurement techniques and accounting for possible nvPM sampling system losses. The CAPS PMssa monitor accurately measures both the optical extinction and scattering (and thus single scattering albedo and absorption) of an extracted sample using the same sample volume for both measurements with a time resolution of 1 second and sensitivity of better than 1 Mm-1. Absorption is obtained by subtracting the scattering signal from the total extinction. Given that the single scattering albedo of the particulates emitted from the aircraft engine measured at both 630 and 660 nm was on the order of 0.1, any inaccuracy in the scattering measurement has little impact on the accuracy of the ddetermined absorption coefficient. The absorption is converted into nvPM mass using a documented Mass Absorption Coefficient (MAC). Results of soot emission indices (mass soot emitted per mass of fuel consumed) for a turbojet engine as a function of engine power will be presented and compared to results obtained using an EC/OC monitor.

African dust contribution to mean ambient PM10 across the Mediterranean Basin: A quantitative approach to investigate spatial and seasonal patterns

NASA Astrophysics Data System (ADS)

Querol, X.; Pandolfi, M.; Pey, J.; Alastuey, A.; Cusack, M.; Pérez, N.; Amato, F.; Moreno, T.; Viana, M.; Mihalopoulos, N.

2009-04-01

The aim of the present study is quantifying African dust contributions to mean PM10 levels recorded across the Mediterranean basin (2001-2008, 1995-2008 in one case) and evidencing spatial variations and seasonal trends. To this end the same methodology has been applied to a number of data sets on PM levels recorded in aerosol research monitoring sites (Montseny-EUSAAR, Spain, Finokalia-EUSAAR, Greece) and from a number of regional background (RB) monitoring sites from the Co-operative Program for Monitoring and Evaluation of the Long-Range Transmission of Air pollutants in Europe (EMEP) and regional air quality monitoring networks available from Airbase-EEA data set. Around 20 data series spread across the whole Mediterranean and bordering regions have been selected and analyzed in the present study. Once the PM data were obtained the days under the influence of African dust outbreaks were identified (using HYSPLIT, DREAM-BSC, SKIRON and NAAPS tools) for each receptor site. Subsequently, a method (Escudero et al., 2007) based on the statistical data treatment of time series of PM levels, without a need of chemical analysis, was used for the quantification of the daily African PM load during dust outbreaks at each site. Finally, PM speciation data available at MSY and FKL were used to differentiate the local/regional from the African mineral contributions across the Mediterranean Basin. Results show a clear W to E and N to S increasing gradients, both on annual PM levels and annual African dust load. In the Eastern Mediterranean the episodes are more intense and are relatively frequent in spring and summer period. However in the western side of the basin, African dust outbreaks are more frequent in summer and winter. In the N, NW and NE sides of the basin 1-2 µgPM10/m3 of mean annual dust contribution was quantified, whereas in the S, SE, SW this annual contribution ranges from 6 to 10 µgPM10/m3. The number of exceedances of the PM10 daily limit value attributable to the African dust contributions was also evaluated fro the whole Mediterranean. Comparison of the African dust annual load with PM10 speciation allowed quantifying regional dust contributions. Thus, in urban areas we are able to discriminate the contribution of African, regional, urban and road dust. References Escudero M. et al., (2007). Atmos. Environ., 41, 5516- 5524. Acknowledgements This study was supported by the Ministry of Science and Innovation (CGL2005-03428-C04-03/CLI, CGL2007-62505/CLI, GRACCIE- CSD2007-00067), the European Union (6th framework CIRCE IP, 036961, EUSAAR RII3-CT-2006-026140). Finally, we would like to express our gratitude to Airbase-EEA for allowing free access to ambient PM levels recorded at a large number of sites in Europe.

Estimating spatiotemporal distribution of PM1 concentrations in China with satellite remote sensing, meteorology, and land use information.

PubMed

Chen, Gongbo; Knibbs, Luke D; Zhang, Wenyi; Li, Shanshan; Cao, Wei; Guo, Jianping; Ren, Hongyan; Wang, Boguang; Wang, Hao; Williams, Gail; Hamm, N A S; Guo, Yuming

2018-02-01

PM 1 might be more hazardous than PM 2.5 (particulate matter with an aerodynamic diameter ≤ 1 μm and ≤2.5 μm, respectively). However, studies on PM 1 concentrations and its health effects are limited due to a lack of PM 1 monitoring data. To estimate spatial and temporal variations of PM 1 concentrations in China during 2005-2014 using satellite remote sensing, meteorology, and land use information. Two types of Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) data, Dark Target (DT) and Deep Blue (DB), were combined. Generalised additive model (GAM) was developed to link ground-monitored PM 1 data with AOD data and other spatial and temporal predictors (e.g., urban cover, forest cover and calendar month). A 10-fold cross-validation was performed to assess the predictive ability. The results of 10-fold cross-validation showed R 2 and Root Mean Squared Error (RMSE) for monthly prediction were 71% and 13.0 μg/m 3 , respectively. For seasonal prediction, the R 2 and RMSE were 77% and 11.4 μg/m 3 , respectively. The predicted annual mean concentration of PM 1 across China was 26.9 μg/m 3 . The PM 1 level was highest in winter while lowest in summer. Generally, the PM 1 levels in entire China did not substantially change during the past decade. Regarding local heavy polluted regions, PM 1 levels increased substantially in the South-Western Hebei and Beijing-Tianjin region. GAM with satellite-retrieved AOD, meteorology, and land use information has high predictive ability to estimate ground-level PM 1 . Ambient PM 1 reached high levels in China during the past decade. The estimated results can be applied to evaluate the health effects of PM 1 . Copyright © 2017 Elsevier Ltd. All rights reserved.

Citizen-Enabled Aerosol Measurements for Satellites (CEAMS): A Network for High-Resolution Measurements of PM2.5 and Aerosol Optical Depth

NASA Astrophysics Data System (ADS)

Pierce, J. R.; Volckens, J.; Ford, B.; Jathar, S.; Long, M.; Quinn, C.; Van Zyl, L.; Wendt, E.

2017-12-01

Atmospheric particulate matter with diameter smaller than 2.5 μm (PM2.5) is a pollutant that contributes to the development of human disease. Satellite-derived estimates of surface-level PM2.5 concentrations have the potential to contribute greatly to our understanding of how particulate matter affects health globally. However, these satellite-derived PM2.5 estimates are often uncertain due to a lack of information about the ratio of surface PM2.5 to aerosol optical depth (AOD), which is the primary aerosol retrieval made by satellite instruments. While modelling and statistical analyses have improved estimates of PM2.5:AOD, large uncertainties remain in situations of high PM2.5 exposure (such as urban areas and in wildfire-smoke plumes) where the health impacts of PM2.5 may be the greatest. Surface monitoring networks for co-incident PM2.5 and AOD measurements are extremely rare, even in the North America. To provide constraints for the PM2.5:AOD relationship, we have developed a relatively low-cost (<$1000) monitor for citizen use that provides sun-photometer AOD measurements and filter-based PM2.5 measurements. The instrument is solar-powered, lightweight (< 1kg), and operated wirelessly via smartphone application (iOS and Android). Sun photometry is performed across 4 discrete wavelengths that match those reported by the Aerosol Robotic Network (AERONET). Aerosol concentration is reported using both time-integrated filter mass (analyzed in an academic laboratory and reported as a 24-48hr average) and a continuous PM sensor within the instrument. Citizen scientists use the device to report daily AOD and PM2.5 measurements made in their backyards to a central server for data display and download. In this presentation, we provide an overview of (1) AOD and PM2.5 measurement calibration; (2) citizen recruiting and training efforts; and (3) results from our pilot citizen-science measurement campaign.

An LUR/BME framework to estimate PM2.5 explained by on road mobile and stationary sources.

PubMed

Reyes, Jeanette M; Serre, Marc L

2014-01-01

Knowledge of particulate matter concentrations <2.5 μm in diameter (PM2.5) across the United States is limited due to sparse monitoring across space and time. Epidemiological studies need accurate exposure estimates in order to properly investigate potential morbidity and mortality. Previous works have used geostatistics and land use regression (LUR) separately to quantify exposure. This work combines both methods by incorporating a large area variability LUR model that accounts for on road mobile emissions and stationary source emissions along with data that take into account incompleteness of PM2.5 monitors into the modern geostatistical Bayesian Maximum Entropy (BME) framework to estimate PM2.5 across the United States from 1999 to 2009. A cross-validation was done to determine the improvement of the estimate due to the LUR incorporation into BME. These results were applied to known diseases to determine predicted mortality coming from total PM2.5 as well as PM2.5 explained by major contributing sources. This method showed a mean squared error reduction of over 21.89% oversimple kriging. PM2.5 explained by on road mobile emissions and stationary emissions contributed to nearly 568,090 and 306,316 deaths, respectively, across the United States from 1999 to 2007.

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.

Atmospheric particulate matter intercepted by moss-bags: Relations to moss trace element uptake and land use.

PubMed

Di Palma, Anna; Capozzi, Fiore; Spagnuolo, Valeria; Giordano, Simonetta; Adamo, Paola

2017-06-01

Particulate matter has to be constantly monitored because it is an important atmospheric transport form of potentially harmful contaminants. The cost-effective method of the moss-bags can be employed to evaluate both loads and chemical composition of PM. PM entrapped by the moss Pseudoscleropodium purum exposed in bags in 9 European sites was characterized for number, size and chemical composition by SEM/EDX. Moreover, moss elemental uptake of 53 elements including rare earth elements was estimated by ICP-MS analysis. All above was aimed to find possible relations between PM profile and moss uptake and to find out eventual element markers of the different land use (i.e. agricultural, urban, industrial) of the selected sites. After exposure, about 12,000 particles, mostly within the inhalable fraction, were counted on P. purum leaves; their number generally increased from the agricultural sites to the urban and industrial ones. ICP analysis indicated that twenty-three elements were significantly accumulated by mosses with different element profile according to the various land uses. The PM from agricultural sites were mainly made of natural/crustal elements or derived from rural activities. Industrial-related PM covered a wider range of sources, from those linked to specific industrial activities, to those related to manufacturing processes or use of heavy-duty vehicles. This study indicates a close association between PM amount and moss element-uptake, which increases in parallel with PM amount. Precious metals and REEs may constitute novel markers of air pollution in urban and agricultural sites, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Source identification of PM10 pollution in subway passenger cabins using positive matrix factorization

NASA Astrophysics Data System (ADS)

Park, Duckshin; Oh, Miseok; Yoon, Younghun; Park, Eunyoung; Lee, Kiyoung

2012-03-01

Monitoring the air quality in subway passenger cabins is important because of the large number of passengers and potentially high levels of air pollution. This report characterized PM10 levels in subway cabins in Seoul, Korea, and identified PM10 sources using elemental analysis and receptor modeling. PM10 levels in subway cabins were continuously measured using a light scattering monitor during rush and non-rush hours. A total of 41 measurements were taken during rush and non-rush hours, and the measurements were repeated in all four seasons. Filter samples were also collected for elemental composition analysis. Major PM10 sources were identified using positive matrix factorization (PMF). The in-cabin PM10 concentrations were the highest in the winter at 152.8 μg m-3 during rush hours and 90.2 μg m-3 during non-rush hours. While PM10 levels were higher during rush hours than during non-rush hours in three seasons (excluding summer), these levels were not associated with number of passenger. Elemental analysis showed that the PM10 was composed of 52.5% inorganic elements, 10.2% anions, and 37.3% other. Fe was the most abundant element and significantly correlated (p < 0.01) with Mn (r = 0.97), Ti (r = 0.91), Cr (r = 0.88), Ni (r = 0.89), and Cu (r = 0.88). Fe, Mn, Cr, and Cu are indicators of railroad-related PM10 sources. The PM10 sources characterized by PMF were soil and road dust sources (27.2%), railroad-related sources (47.6%), secondary nitrate sources (16.2%), and a chlorine factor mixed with a secondary sulfate source (9.1%). Overall, railroad-related sources contributed the most PM10 to subway cabin air.

Real-time dissemination of air quality information using data streams and Web technologies: linking air quality to health risks in urban areas.

PubMed

Davila, Silvije; Ilić, Jadranka Pečar; Bešlić, Ivan

2015-06-01

This article presents a new, original application of modern information and communication technology to provide effective real-time dissemination of air quality information and related health risks to the general public. Our on-line subsystem for urban real-time air quality monitoring is a crucial component of a more comprehensive integrated information system, which has been developed by the Institute for Medical Research and Occupational Health. It relies on a StreamInsight data stream management system and service-oriented architecture to process data streamed from seven monitoring stations across Zagreb. Parameters that are monitored include gases (NO, NO2, CO, O3, H2S, SO2, benzene, NH3), particulate matter (PM10 and PM2.5), and meteorological data (wind speed and direction, temperature and pressure). Streamed data are processed in real-time using complex continuous queries. They first go through automated validation, then hourly air quality index is calculated for every station, and a report sent to the Croatian Environment Agency. If the parameter values exceed the corresponding regulation limits for three consecutive hours, the web service generates an alert for population groups at risk. Coupled with the Common Air Quality Index model, our web application brings air pollution information closer to the general population and raises awareness about environmental and health issues. Soon we intend to expand the service to a mobile application that is being developed.

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.

An empirical relationship between PM2.5 and aerosol optical depth in Delhi Metropolitan

PubMed Central

Kumar, Naresh; Chu, Allen; Foster, Andrew

2011-01-01

Atmospheric remote sensing offers a unique opportunity to compute indirect estimates of air quality, which are critically important for the management and surveillance of air quality in megacities of developing countries, particularly in India and China, which have experienced elevated concentration of air pollution but lack adequate spatial–temporal coverage of air pollution monitoring. This article examines the relationship between aerosol optical depth (AOD) estimated from satellite data at 5 km spatial resolution and the mass of fine particles ≤2.5 μm in aerodynamic diameter (PM2.5) monitored on the ground in Delhi Metropolitan where a series of environmental laws have been instituted in recent years. PM2.5 monitored at 113 sites were collocated by time and space with the AOD computed using the data from Moderate Resolution Imaging Spectroradiometer (MODIS onboard the Terra satellite). MODIS data were acquired from NASA’s Goddard Space Flight Center Earth Sciences Distributed Active Archive Center (DAAC). Our analysis shows a significant positive association between AOD and PM2.5. After controlling for weather conditions, a 1% change in AOD explains 0.52±0.202% and 0.39±0.15% change in PM2.5 monitored within ±45 and 150 min intervals of AOD data. This relationship will be used to estimate air quality surface for previous years, which will allow us to examine the time–space dynamics of air pollution in Delhi following recent air quality regulations, and to assess exposure to air pollution before and after the regulations and its impact on health. PMID:22180723

The Development of Time-Based Prospective Memory in Childhood: The Role of Working Memory Updating

ERIC Educational Resources Information Center

Voigt, Babett; Mahy, Caitlin E. V.; Ellis, Judi; Schnitzspahn, Katharina; Krause, Ivonne; Altgassen, Mareike; Kliegel, Matthias

2014-01-01

This large-scale study examined the development of time-based prospective memory (PM) across childhood and the roles that working memory updating and time monitoring play in driving age effects in PM performance. One hundred and ninety-seven children aged 5 to 14 years completed a time-based PM task where working memory updating load was…

2015 Soft Condensed Matter Physics: Self-Assembly and Active Matter GRC/GRS

DTIC Science & Technology

2015-10-20

or decision, unless so designated by other documentation. 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS (ES) U.S. Army Research Office P.O...were Minorities – 0% Hispanic, 14% Asian and 0% African American. Approximately 29% of the participants at the 2015 meeting were women. In designing ...Trees" 8:10 pm - 8:30 pm Discussion 8:30 pm - 9:10 pm Todd Yeates (University of California, Los Angeles, USA) "Using Ideas in Symmetry to Design

40 CFR Table E-1 to Subpart E of... - Summary of Test Requirements for Reference and Class I Equivalent Methods for PM 2.5 and PM 10-2.5

Code of Federal Regulations, 2014 CFR

2014-07-01

.... accuracy 3. Filter temp. control accuracy, sampling and non-sampling 1. 2 °C2. 2 °C 3. Not more than 5 °C... Reference and Class I Equivalent Methods for PM 2.5 and PM 10-2.5 E Table E-1 to Subpart E of Part 53... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance...

40 CFR Table E-1 to Subpart E of... - Summary of Test Requirements for Reference and Class I Equivalent Methods for PM2.5 and PM10-2.5

Code of Federal Regulations, 2011 CFR

2011-07-01

.... accuracy 3. Filter temp. control accuracy, sampling and non-sampling 1. 2 °C2. 2 °C 3. Not more than 5 °C... Reference and Class I Equivalent Methods for PM2.5 and PM10-2.5 E Table E-1 to Subpart E of Part 53... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance...

40 CFR Table E-1 to Subpart E of... - Summary of Test Requirements for Reference and Class I Equivalent Methods for PM2.5 and PM10-2.5

Code of Federal Regulations, 2012 CFR

2012-07-01

.... accuracy 3. Filter temp. control accuracy, sampling and non-sampling 1. 2 °C2. 2 °C 3. Not more than 5 °C... Reference and Class I Equivalent Methods for PM2.5 and PM10-2.5 E Table E-1 to Subpart E of Part 53... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance...

40 CFR Table E-1 to Subpart E of... - Summary of Test Requirements for Reference and Class I Equivalent Methods for PM 2.5 and PM 10-2.5

Code of Federal Regulations, 2013 CFR

2013-07-01

.... accuracy 3. Filter temp. control accuracy, sampling and non-sampling 1. 2 °C2. 2 °C 3. Not more than 5 °C... Reference and Class I Equivalent Methods for PM 2.5 and PM 10-2.5 E Table E-1 to Subpart E of Part 53... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance...

Indoor exposures to particulate matter emissions in various types of households using different cooking fuels in rural areas of south India

NASA Astrophysics Data System (ADS)

Deepthi, Y.; Nagendra, S. S.; Gummadi, S. N.

2017-12-01

Exposure to Particulate Matter (PM) that are typically generated from heavy biomass usage in cooking and from unpaved roads is a major health risk in the rural areas of developing countries. To understand the exposure levels in such areas, PM (PM10, PM2.5 and PM1) characterizations was carried out through indoor monitoring in a rural site of south India with varied cooking fuels such as only biomass, biomass plus LPG and only LPG in different types of housing namely indoor kitchen without partition (IKWO), indoor kitchen with partition (IKWP), separate enclosed kitchen outside house (SEKO) and open kitchen (OK). Results indicated that use of biomass resulted in the highest PM10 concentrations of 179.51±21µg/m3 followed by combination of biomass and LPG (101.99±21 µg/m3) and LPG (77.48±9µg/m3). Similar patterns were observed in PM2.5 and PM1 with highest emissions from biomass burning. The PM concentrations of biomass households and combination of biomass and LPG households were 233.7 % and 80.2 % respectively higher than those using cleaner fuels (LPG). The monitoring also revealed that kitchen configuration is an important determinant for indoor exposures especially for biomass households. Among biomass users, average PM10, PM2.5 and PM1 concentrations in all type of houses were above the human permissible limit with IKWP having highest concentrations followed by IKWO>SEKO>OK. Thus, biomass household have high concentrations compared to LPG because of nature of combustion of solid biomass. Also, PM concentrations were higher in enclosed indoor kitchens (IKWO and IKWP) compared to SEKO and OK type kitchen configurations. It is evident from above discussions that type of fuel and kitchen setups are major attributes impacting Indoor air pollution (IAP) in rural areas and any policy intervention to minimize IAP must give due consideration to these two factors.

Monitoring of cotton dust and health risk assessment in small-scale weaving industry.

PubMed

Tahir, Muhammad Wajid; Mumtaz, Muhammad Waseem; Tauseef, Shanza; Sajjad, Muqadas; Nazeer, Awais; Farheen, Nazish; Iqbal, Muddsar

2012-08-01

The present study describes the estimation of particulate matter (cotton dust) with different sizes, i.e., PM(1.0), PM(2.5), PM(4.0), and PM(10.0 μm) in small-scale weaving industry (power looms) situated in district Hafizabad, Punjab, Pakistan, and the assessment of health problems of workers associated with these pollutants. A significant difference was found in PM(1.0), PM(2.5), PM(4.0), and PM(10.0) with reference to nine different sampling stations with p values <0.05. Multiple comparisons of particulate matter with respect to size, i.e. PM(1.0), PM(2.5), PM(4.0), and PM(10.0), depict that PM(1.0) differs significantly from PM(2.5), PM(4.0), and PM(10.0), with p values <0.05 and that PM(2.5) differs significantly from PM(1.0) and PM(10.0), with p values <0.05, whereas PM(2.5) differs non-significantly from PM(4.0), with a p value >0.05 in defined sampling stations on an average basis. Majority of the workers were facing several diseases due to interaction with particulate matter (cotton dust) during working hours. Flue, cough, eye, and skin infections were the most common diseases among workers caused by particulate matter (cotton dust).

Environmental and occupational particulate matter exposures and ectopic heart beats in welders

PubMed Central

Cavallari, Jennifer M.; Fang, Shona C.; Eisen, Ellen A.; Mittleman, Murray A.; Christiani, David C.

2016-01-01

Objectives Links between arrhythmias and particulate matter exposures have been found among sensitive populations. We examined the relationship between personal PM2.5 (particulate matter ≤ 2.5μm aerodynamic diameter) exposures and ectopy in a panel study of healthy welders. Methods Simultaneous ambulatory electrocardiogram (ECG) and personal PM2.5 exposure monitoring with DustTrak™ Aerosol Monitor was performed on 72 males during work and non-work periods for 5–90 hours (median 40 hours). ECGs were summarized hourly for supraventricular ectopy (SVE) and ventricular ectopy (VE). PM2.5 exposures both work and non-work periods were averaged hourly with lags from 0- to 7-hours. Generalized linear mixed-effects models with a random participant intercept were used to examine the relationship between PM2.5 exposure and the odds of SVE or VE. Sensitivity analyses were performed to assess whether relationships differed by work period and current smokers. Results Participants had a mean(SD) age of 38(11) years and were monitored over 2,993 person-hours. The number of hourly ectopic events was highly skewed with mean(sd) of 14(69) VE and 1(4) SVE. We found marginally significant increases in VE with PM2.5 exposures in the 6th and 7th hour lags, yet no association with SVE. For every 100μg/m3 increase in 6th hour lagged PM2.5, the adjusted OR(95% CI) for VE was 1.03(1.00, 1.05). Results persisted in work or non-work exposure periods and non-smokers had increased odds of VE associated with PM2.5 as compared to smokers. Conclusions A small increase in the odds of ventricular ectopy with short term PM2.5 exposure was observed among relatively healthy men with environmental and occupational exposures. PMID:27052768

Effect of poverty on the relationship between personal exposures and ambient concentrations of air pollutants in Ho Chi Minh City

NASA Astrophysics Data System (ADS)

Mehta, Sumi; Sbihi, Hind; Dinh, Tuan Nguyen; Xuan, Dan Vu; Le Thi Thanh, Loan; Thanh, Canh Truong; Le Truong, Giang; Cohen, Aaron; Brauer, Michael

2014-10-01

Socioeconomic factors often affect the distribution of exposure to air pollution. The relationships between health, air pollution, and poverty potentially have important public health and policy implications, especially in areas of Asia where air pollution levels are high and income disparity is large. The objective of the study was to characterize the levels, determinants of exposure, and relationships between children personal exposures and ambient concentrations of multiple air pollutants amongst different socioeconomic segments of the population of Ho Chi Minh City, Vietnam. Using repeated (N = 9) measures personal exposure monitoring and determinants of exposure modeling, we compared daily average PM2.5, PM10, PM2.5 absorbance and NO2 concentrations measured at ambient monitoring sites to measures of personal exposures for (N = 64) caregivers of young children from high and low socioeconomic groups in two districts (urban and peri-urban), across two seasons. Personal exposures for both PM sizes were significantly higher among the poor compared to non-poor participants in each district. Absolute levels of personal exposures were under-represented by ambient monitors with median individual longitudinal correlations between personal exposures and ambient concentrations of 0.4 for NO2, 0.6 for PM2.5 and PM10 and 0.7 for absorbance. Exposures of the non-poor were more highly correlated with ambient concentrations for both PM size fractions and absorbance while those for NO2 were not significantly affected by socioeconomic position. Determinants of exposure modeling indicated the importance of ventilation quality, time spent in the kitchen, air conditioner use and season as important determinant of exposure that are not fully captured by the differences in socioeconomic position. Our results underscore the need to evaluate how socioeconomic position affects exposure to air pollution. Here, differential exposure to major sources of pollution, further influenced by characteristics of Ho Chi Minh City's rapidly urbanizing landscape, resulted in systematically higher PM exposures among the poor.

PM2.5 Gravimetric Lab Training (2016 NAAMC)

EPA Pesticide Factsheets

This training focused on understanding/applying the PM2.5 FRM in 40 CFR part 50, Appendix L and the updated QA Guidance Document 2.12. it was geared primarily for monitoring and QA managers and staff.

Monitoring and source apportionment of trace elements in PM2.5: Implications for local air quality management.

PubMed

Li, Yueyan; Chang, Miao; Ding, Shanshan; Wang, Shiwen; Ni, Dun; Hu, Hongtao

2017-07-01

Fine particulate matter (PM 2.5 ) samples were collected simultaneously every hour in Beijing between April 2014 and April 2015 at five sites. Thirteen trace elements (TEs) in PM 2.5 were analyzed by online X-ray fluorescence (XRF). The annual average PM 2.5 concentrations ranged from 76.8 to 102.7 μg m -3 . TEs accounted for 5.9%-8.7% of the total PM 2.5 mass with Cl, S, K, and Si as the most dominant elements. Spearman correlation coefficients of PM 2.5 or TE concentrations between the background site and other sites showed that PM 2.5 and some element loadings were affected by regional and local sources, whereas Cr, Si, and Ni were attributed to substantial local emissions. Temporal variations of TEs in PM 2.5 were significant and provided information on source profiles. The PM 2.5 concentrations were highest in autumn and lowest in summer. Mn and Cr showed similar variation. Fe, Ca, Si, and Ti tended to show higher concentrations in spring, whereas concentrations of S peaked in summer. Concentrations of Cl, K, Pb, Zn, Cu, and Ni peaked in winter. PM 2.5 and TE median concentrations were higher on Saturdays than on weekdays. The diurnal pattern of PM 2.5 and TE median concentrations yielded similar bimodal patterns. Five dominant sources of PM 2.5 mass were identified via positive matrix factorization (PMF). These sources included the regional and local secondary aerosols, traffic, coal burning, soil dust, and metal processing. Air quality management strategies, including regional environmental coordination and collaboration, reduction in secondary aerosol precursors, restrictive vehicle emission standards, promotion of public transport, and adoption of clean energy, should be strictly implemented. High time-resolution measurements of TEs provided detailed source profiles, which can greatly improve precision in interpreting source apportionment calculations; the PMF analysis of online XRF data is a powerful tool for local air quality management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Two Methods to Derive Ground-level Concentrations of PM2.5 with Improved Accuracy in the North China, Calibrating MODIS AOD and CMAQ Model Predictions

NASA Astrophysics Data System (ADS)

Lyu, Baolei; Hu, Yongtao; Chang, Howard; Russell, Armistead; Bai, Yuqi

2016-04-01

Reliable and accurate characterizations of ground-level PM2.5 concentrations are essential to understand pollution sources and evaluate human exposures etc. Monitoring network could only provide direct point-level observations at limited locations. At the locations without monitors, there are generally two ways to estimate the pollution levels of PM2.5. One is observations of aerosol properties from the satellite-based remote sensing, such as Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD). The other one is from deterministic atmospheric chemistry models, such as the Community Multi-Scale Air Quality Model (CMAQ). In this study, we used a statistical spatio-temporal downscaler to calibrate the two datasets to monitor observations to derive fine-scale ground-level concentrations of PM2.5 with improved accuracy. We treated both MODIS AOD and CMAQ model predictions as biased proxy estimations of PM2.5 pollution levels. The downscaler proposed a Bayesian framework to model the spatially and temporally varying coefficients of the two types of estimations in the linear regression setting, in order to correct biases. Especially for calibrating MODIS AOD, a city-specific linear model was established to fill the missing AOD values, and a novel interpolation-based variable, i.e. PM2.5 Spatial Interpolator, was introduced to account for the spatial dependence among grid cells. We selected the heavy polluted and populated North China as our study area, in a grid setting of 81×81 12-km cells. For the evaluation of calibration performance for retrieved MODIS AOD, the R2 was 0.61 by the full model with PM2.5 Spatial Interpolator being presented, and was 0.48 with PM2.5 Spatial Interpolator not being presented. The constructed AOD values effectively predicted PM2.5 concentrations under our model structure, with R2=0.78. For the evaluation of calibrated CMAQ predictions, the R2 was 0.51, a little less than that of calibrated AOD. Finally we obtained two sets of calibrated estimations of ground-level PM2.5 concentrations with complete spatial coverage. By comparing the two datasets, we found that the prediction from AOD have a little smoother texture than that from CMAQ. The former also predicted larger heavy pollution area in the southern Hebei province than the latter, but in a small margin. In general, they have pretty similar spatial patterns, indicating the reliability of our data fusion method. In summary, the statistical spatio-temporal downscaler could provide improvements on MODIS AOD and CMAQ's predictions on PM2.5 pollution levels. Future work would focus on fusing three datasets, as aforementioned monitor observations, MODIS AOD and CMAQ predictions, to derive predictions of ground-level PM2.5 pollution levels with even increased accuracy.

STEMS-Air: a simple GIS-based air pollution dispersion model for city-wide exposure assessment.

PubMed

Gulliver, John; Briggs, David

2011-05-15

Current methods of air pollution modelling do not readily meet the needs of air pollution mapping for short-term (i.e. daily) exposure studies. The main limiting factor is that for those few models that couple with a GIS there are insufficient tools for directly mapping air pollution both at high spatial resolution and over large areas (e.g. city wide). A simple GIS-based air pollution model (STEMS-Air) has been developed for PM(10) to meet these needs with the option to choose different exposure averaging periods (e.g. daily and annual). STEMS-Air uses the grid-based FOCALSUM function in ArcGIS in conjunction with a fine grid of emission sources and basic information on meteorology to implement a simple Gaussian plume model of air pollution dispersion. STEMS-Air was developed and validated in London, UK, using data on concentrations of PM(10) from routinely available monitoring data. Results from the validation study show that STEMS-Air performs well in predicting both daily (at four sites) and annual (at 30 sites) concentrations of PM(10). For daily modelling, STEMS-Air achieved r(2) values in the range 0.19-0.43 (p<0.001) based solely on traffic-related emissions and r(2) values in the range 0.41-0.63 (p<0.001) when adding information on 'background' levels of PM(10). For annual modelling of PM(10), the model returned r(2) in the range 0.67-0.77 (P<0.001) when compared with monitored concentrations. The model can thus be used for rapid production of daily or annual city-wide air pollution maps either as a screening process in urban air quality planning and management, or as the basis for health risk assessment and epidemiological studies. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

Monitoring Particulate Matter with Commodity Hardware

NASA Astrophysics Data System (ADS)

Holstius, David

Health effects attributed to outdoor fine particulate matter (PM 2.5) rank it among the risk factors with the highest health burdens in the world, annually accounting for over 3.2 million premature deaths and over 76 million lost disability-adjusted life years. Existing PM2.5 monitoring infrastructure cannot, however, be used to resolve variations in ambient PM2.5 concentrations with adequate spatial and temporal density, or with adequate coverage of human time-activity patterns, such that the needs of modern exposure science and control can be met. Small, inexpensive, and portable devices, relying on newly available off-the-shelf sensors, may facilitate the creation of PM2.5 datasets with improved resolution and coverage, especially if many such devices can be deployed concurrently with low system cost. Datasets generated with such technology could be used to overcome many important problems associated with exposure misclassification in air pollution epidemiology. Chapter 2 presents an epidemiological study of PM2.5 that used data from ambient monitoring stations in the Los Angeles basin to observe a decrease of 6.1 g (95% CI: 3.5, 8.7) in population mean birthweight following in utero exposure to the Southern California wildfires of 2003, but was otherwise limited by the sparsity of the empirical basis for exposure assessment. Chapter 3 demonstrates technical potential for remedying PM2.5 monitoring deficiencies, beginning with the generation of low-cost yet useful estimates of hourly and daily PM2.5 concentrations at a regulatory monitoring site. The context (an urban neighborhood proximate to a major goods-movement corridor) and the method (an off-the-shelf sensor costing approximately USD $10, combined with other low-cost, open-source, readily available hardware) were selected to have special significance among researchers and practitioners affiliated with contemporary communities of practice in public health and citizen science. As operationalized by correlation with 1h data from a Federal Equivalent Method (FEM) beta-attenuation data, prototype instruments performed as well as commercially available equipment costing considerably more, and as well as another reference instrument under similar conditions at the same timescale (R2 = 0.6). Correlations were stronger when 24 h integrating times were used instead (R2 = 0.72). Chapter 4 replicates and extends the results of Chapter 3, showing that similar calibrations may be reasonably exchangeable between near-roadway and background monitoring sites. Chapter 4 also employs triplicate sensors to obtain data consistent with near-field (< 50 m) observations of plumes from a major highway (I-880). At 1 minute timescales, maximum PM2.5 concentrations on the order of 100 mug m-3 to 200 mug m-3 were observed, commensurate with the magnitude of plumes from wildfires on longer timescales, as well as the magnitude of plumes that might be expected near other major highways on the same timescale. Finally, Chapter 4 quantifies variance among calibration parameters for a large sample of the sensors, as well as the error associated with the remote transfer of calibrations between two sufficiently large sets (+/- 10 % for n = 12). These findings suggest that datasets generated with similar sensors could also improve upstream scientific understandings of fluxes resulting from indoor and outdoor emissions, atmospheric transformations, and transport, and may also facilitate timely and empirical verification of interventions to reduce emissions and exposures, in many important contexts (e.g., the provision of improved cookstoves; congestion pricing; mitigation policies attached to infill development; etc.). They also demonstrate that calibrations against continuous reference monitoring equipment could be remotely transferred, within practical tolerances, to reasonably sized and adequately resourced participatory monitoring campaigns, with minimal risk of disruption to existing monitoring infrastructure (i.e., established monitoring sites). Given a collaborator with a short window of access to a reference monitoring site, this would overcome a nominally important barrier associated with non-gravimetric, in-situ calibration of continuous PM2.5 monitors. Progressive and disruptive prospects linked to a proliferation of comparable sensing technologies based on commodity hardware are discussed in Chapter 5.

Acquiring Data by Mining the Past: Pairing Communities with Environmental Monitoring Methods through Open Online Collaborative Replication

NASA Astrophysics Data System (ADS)

Lippincott, M.; Lewis, E. S.; Gehrke, G. E.; Wise, A.; Pyle, S.; Sinatra, V.; Bland, G.; Bydlowski, D.; Henry, A.; Gilberts, P. A.

2016-12-01

Community groups are interested in low-cost sensors to monitor their environment. However, many new commercial sensors are unknown devices without peer-reviewed evaluations of data quality or pathways to regulatory acceptance, and the time to achieve these outcomes may be beyond a community's patience and attention. Rather than developing a device from scratch or validating a new commercial product, a workflow is presented whereby existing technologies, especially those that are out of patent, are replicated through open online collaboration between communities affected by environmental pollution, volunteers, academic institutions, and existing open hardware and open source software projects. Technology case studies will be presented, focusing primarily on a passive PM monitor based on the UNC Passive Monitor. Stages of the project will be detailed moving from identifying community needs, reviewing existing technology, partnership development, technology replication, IP review and licensing, data quality assurance (in process), and field evaluation with community partners (in process), with special attention to partnership development and technology review. We have leveraged open hardware and open source software to lower the cost and access barriers of existing technologies for PM10-2.5 and other atmospheric measures that have already been validated through peer review. Existing validation of and regulatory familiarity with a technology enables a rapid pathway towards collecting data, shortening the time it takes for communities to leverage data in environmental management decisions. Online collaboration requires rigorous documentation that aids in spreading research methods and promoting deep engagement by interested community researchers outside academia. At the same time, careful choice of technology and the use of small-scale fabrication through laser cutting, 3D printing, and open, shared repositories of plans and software enables educational engagement that broadens a project's reach.

76 FR 27290 - Approval and Promulgation of Air Quality Implementation Plans; West Virginia; Kentucky; Ohio...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-11

...EPA is proposing to make two determinations regarding the tri- state Huntington-Ashland, West Virginia-Kentucky-Ohio fine particulate matter (PM2.5) nonattainment Area (hereafter referred to as ``the Huntington-Ashland Area'' or ``Area''). First, EPA is proposing to determine that the Area has attained the 1997 annual average PM2.5 National Ambient Air Quality Standard (NAAQS). This proposed determination of attainment is based upon complete, quality- assured and certified ambient air monitoring data for the 2007-2009 period showing that the Area has attained the 1997 annual PM2.5 NAAQS, and data available to date for 2010 in EPA's Air Quality System (AQS) database that show the area continues to attain. If EPA finalizes this proposed determination of attainment, the requirements for the Area to submit attainment demonstrations and associated reasonably available control measures (RACM), a reasonable further progress (RFP) plan, contingency measures, and other planning State Implementation Plan (SIP) revisions related to attainment of the standard shall be suspended for so long as the Area continues to attain the annual PM2.5 NAAQS. Second, EPA is also proposing to determine, based on quality-assured and certified monitoring data for the 2007-2009 monitoring period, that the Area has attained the 1997 annual PM2.5 NAAQS by its applicable attainment date of April 5, 2010.

Indoor air quality in university classrooms and relative environment in terms of mass concentrations of particulate matter.

PubMed

Gaidajis, George; Angelakoglou, Komninos

2009-10-01

The mass concentrations of coarse (PM10) and fine (PM2.5) particulate matter were measured in different classrooms and relevant indoors areas of Democritus University, School of Engineering, Xanthi, with portable aerosol monitoring equipment. Two sampling campaigns were conducted in different seasons. The results indicated that the average concentrations in classrooms ranged from 32-188 microg/m3 and 25-151 microg/m3 for PM10 and PM2.5, respectively. Concentration levels above 300 microg/m3 were usually recorded, while the PM2.5/PM10 ratio was about 0.8. As expected, PM10 and PM2.5 average concentrations were significantly higher in the open-access meeting place of common use, indicating the significance of student trespassing and occasional smoking in the deterioration of indoors air quality.

Fine particulate matter (PM2.5) air pollution and selected causes of postneonatal infant mortality in California.

PubMed

Woodruff, Tracey J; Parker, Jennifer D; Schoendorf, Kenneth C

2006-05-01

Studies suggest that airborne particulate matter (PM) may be associated with postneonatal infant mortality, particularly with respiratory causes and sudden infant death syndrome (SIDS). To further explore this issue, we examined the relationship between long-term exposure to fine PM air pollution and postneonatal infant mortality in California. We linked monitoring data for PM

THE SUPERSITES PROGRAM

EPA Science Inventory

The PM2.5 monitoring program is dominated by gravimetric measurements (over 1000 mass samplers nationwide) specific for indicator mass, where the primary objective is comparisons with the PM2.5 National Ambient Air Quality Standards (NAAQS). The other major component of the net...

77 FR 45965 - Determination of Attainment for the Paul Spur/Douglas PM10

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-02

... plans, and based on the findings of our technical system audit report, ADEQ's monitoring network meets... to EPA's Air Quality System (AQS) database as quality- assured. Next, we reviewed the ambient PM 10...

PERKINELMER ELM

EPA Science Inventory

The PerkinElmer Elm (formerly the AirBase CanarIT) is a multi-sensor air quality monitoring device that measures particulate matter (PM), total volatile organic compounds (VOCs), nitrogen dioxide (NO₂), and several other atmospheric components. PM, VOCs, and NO₂

A new approach to developing a fugitive road dust emission inventory and emission trend from 2006 to 2010 in the beijing metropolitan area, china.

PubMed

Fan, Shoubin; Tian, Gang; Cheng, Shuiyuan; Qin, Jianping

2013-07-01

The USEPA emission factor (AP-42) of fugitive road dust (FRD) is widely used in establishing emission inventories. However, road silt loading sampling for AP-42 is expensive, time consuming, and dangerous. Therefore, a new method for establishing emission inventories based on road dust-fall (DF) monitors is described. Between January 2006 and December 2010, DF was monitored at 40 sites (80 samples), and background dust fall (DF) was monitored at 14 sites in the Beijing metropolitan area. Also during this period, 58 samples of road silt loadings were taken and used in the AP-42 emission factor equation to calculate FRD with particulate matter ≤10 μm in diameter [FRD(PM)] emission from the roads. Simultaneous measurement of FRD(PM) emissions calculated by AP-42 and ΔDF (i.e., the difference between the DF and DF) measured using gauges showed that the FRD(PM) emission for road dust was proportional to the ΔDF ( = 0.92). The FRD(PM) emission (kg km × 30 d) was calculated using the monitored ΔDF (t km × 30 d) by the formulation FRD(PM) = 278.3 × ΔDF - 1151.2. The ΔDF showed a general decline from 2006 to 2010. In particular, there was a sharp decline in August, September, and October 2008 due to strict dust controls enforced during the 2008 Olympic Games. Although there was a small increase in ΔDF after the Games, by the end of 2010 values were still lower than those before the Games. Using the 2006 ΔDF value as a benchmark, ΔDF values declined by 24.7, 33.0, 38.3, and 31.4% in 2007, 2008, 2009, and 2010, respectively. Based on using AP-42 calculations from silt loading and traffic information in 2007, the FRD(PM) emission distribution in the Beijing metropolitan area was mapped, and there were 2.05 × 10 tons of FRD(PM) emitted in 2007. The FRD(PM) from 2006 to 2010 was calculated by the ΔDF values. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Associations of PM2.5 and black carbon concentrations with traffic, idling, background pollution, and meteorology during school dismissals.

PubMed

Richmond-Bryant, J; Saganich, C; Bukiewicz, L; Kalin, R

2009-05-01

An air quality study was performed outside a cluster of schools in the East Harlem neighborhood of New York City. PM(2.5) and black carbon concentrations were monitored using real-time equipment with a one-minute averaging interval. Monitoring was performed at 1:45-3:30 PM during school days over the period October 31-November 17, 2006. The designated time period was chosen to capture vehicle emissions during end-of-day dismissals from the schools. During the monitoring period, minute-by-minute volume counts of idling and passing school buses, diesel trucks, and automobiles were obtained. These data were transcribed into time series of number of diesel vehicles idling, number of gasoline automobiles idling, number of diesel vehicles passing, and number of automobiles passing along the block adjacent to the school cluster. Multivariate regression models of the log-transform of PM(2.5) and black carbon (BC) concentrations in the East Harlem street canyon were developed using the observation data and data from the New York State Department of Environmental Conservation on meteorology and background PM(2.5). Analysis of variance was used to test the contribution of each covariate to variability in the log-transformed concentrations as a means to judge the relative contribution of each covariate. The models demonstrated that variability in background PM(2.5) contributes 80.9% of the variability in log[PM(2.5)] and 81.5% of the variability in log[BC]. Local traffic sources were demonstrated to contribute 5.8% of the variability in log[BC] and only 0.43% of the variability in log[PM(2.5)]. Diesel idling and passing were both significant contributors to variability in log[BC], while diesel passing was a significant contributor to log[PM(2.5)]. Automobile idling and passing did not contribute significant levels of variability to either concentration. The remainder of variability in each model was explained by temperature, along-canyon wind, and cross-canyon wind, which were all significant in the models.

Characterization of traffic-related air pollutant metrics at four schools in El Paso, Texas, USA: Implications for exposure assessment and siting schools in urban areas

NASA Astrophysics Data System (ADS)

Raysoni, Amit U.; Stock, Thomas H.; Sarnat, Jeremy A.; Montoya Sosa, Teresa; Ebelt Sarnat, Stefanie; Holguin, Fernando; Greenwald, Roby; Johnson, Brent; Li, Wen-Whai

2013-12-01

Children spend substantial amount of time within school microenvironments; therefore, assessing school-based exposures is essential for characterizing and preventing children's health risks to air pollutants. Indeed, the importance of characterizing children's exposures in schools is recognized by the US Environmental Protection Agency's recent initiative to promote outdoor air monitoring networks near schools. As part of a health effects study investigating the impact of traffic-related air pollution on asthmatic children along the US-Mexico border, this research examines children's exposures to, and spatio-temporal heterogeneity in concentrations of, traffic-related air pollutants at four elementary schools in El Paso, Texas. Three schools were located in an area of high traffic density and one school in an area of low traffic density. Paired indoor and outdoor concentrations of 48-h fine and coarse particulate matter (PM2.5 and PM10-2.5), 48-h black carbon (BC), 96-h nitrogen dioxide (NO2), and 96-h volatile organic compounds (VOCs) were measured for 13 weeks at each school. Outdoor concentrations of PM, NO2, BC, and BTEX (benzene, toluene, ethylbenzene, m,p-xylene, o-xylene) compounds were similar among the three schools in the high-traffic zone in contrast to the school in the low-traffic zone. Results from this study and previous studies in this region corroborate the fact that PM pollution in El Paso is dominated by coarse PM (PM10-2.5) and fine fraction (PM2.5) accounts for only 25-30% of the total PM mass in PM10. BTEX species and BC are better surrogates for traffic air pollution in this region. Correlation analyses indicate a range of association between indoor and outdoor pollutant concentrations due to uncontrollable factors like student foot traffic and varying building and ventilation configurations across the four schools. Results suggest the need of micro-scale monitoring for children's exposure assessment, which may not be adequately characterized by the measurements from a centralized monitoring site.

Assessment of different route choice on commuters' exposure to air pollution in Taipei, Taiwan.

PubMed

Li, Hsien-Chih; Chiueh, Pei-Te; Liu, Shi-Ping; Huang, Yu-Yang

2017-01-01

The purposes of this study are to develop a healthy commute map indicating cleanest route in Taipei metropolitan area for any given journey and to evaluate the pollutant doses exposed in different commuting modes. In Taiwan, there are more than 13.6 million motorcycles and 7.7 million vehicles among the 23 million people. Exposure to traffic-related air pollutants can thus cause adverse health effects. Moreover, increasing the level of physical activity during commuting and longer distances will result in inhalation of more polluted air. In this study, we utilized air pollution monitoring data (CO, SO 2 , NO 2 , PM 10 , and PM 2.5 ) from Taiwan EPA's air quality monitoring stations in Taipei metropolitan area to estimate each pollutant exposure while commuting by different modes (motorcycling, bicycling, and walking). Spatial interpolation methods such as inverse distance weighting (IDW) were used to estimate each pollutant's distribution in Taipei metropolitan area. Three routes were selected to represent the variety of different daily commuting pathways. The cleanest route choice was based upon Dijkstra's algorithm to find the lowest cumulative pollutant exposure. The IDW interpolated values of CO, SO 2 , NO 2 , PM 10 , and PM 2.5 ranged from 0.42-2.2 (ppm), 2.6-4.8 (ppb), 17.8-42.9 (ppb), 32.4-65.6 (μg/m 3 ), and 14.2-38.9 (μg/m 3 ), respectively. To compare with the IDW results, concentration of particulate matter (PM 10 , PM 2.5 , and PM 1 ) along the motorcycle route was measured in real time. In conclusion, the results showed that the shortest commuting route for motorcyclists resulted in a much higher cumulative dose (PM 2.5 3340.8 μg/m 3 ) than the cleanest route (PM 2.5 912.5 μg/m 3 ). The mobile personal monitoring indicated that the motorcyclists inhaled significant high pollutants during commuting as a result of high-concentration exposure and short-duration peaks. The study could effectively present less polluted commuting routes for citizen health benefits.

Sequential Measurement of Intermodal Variability in Public Transportation PM2.5 and CO Exposure Concentrations.

PubMed

Che, W W; Frey, H Christopher; Lau, Alexis K H

2016-08-16

A sequential measurement method is demonstrated for quantifying the variability in exposure concentration during public transportation. This method was applied in Hong Kong by measuring PM2.5 and CO concentrations along a route connecting 13 transportation-related microenvironments within 3-4 h. The study design takes into account ventilation, proximity to local sources, area-wide air quality, and meteorological conditions. Portable instruments were compacted into a backpack to facilitate measurement under crowded transportation conditions and to quantify personal exposure by sampling at nose level. The route included stops next to three roadside monitors to enable comparison of fixed site and exposure concentrations. PM2.5 exposure concentrations were correlated with the roadside monitors, despite differences in averaging time, detection method, and sampling location. Although highly correlated in temporal trend, PM2.5 concentrations varied significantly among microenvironments, with mean concentration ratios versus roadside monitor ranging from 0.5 for MTR train to 1.3 for bus terminal. Measured inter-run variability provides insight regarding the sample size needed to discriminate between microenvironments with increased statistical significance. The study results illustrate the utility of sequential measurement of microenvironments and policy-relevant insights for exposure mitigation and management.

Spatial and Temporal Trends of Polycyclic Aromatic Hydrocarbons and Other Traffic-Related Airborne Pollutants in New York City

PubMed Central

NARVÁEZ, RAFAEL F.; HOEPNER, LORI; CHILLRUD, STEVEN N.; YAN, BEIZHAN; GARFINKEL, ROBIN; WHYATT, ROBIN; CAMANN, DAVID; PERERA, FREDERICA P.; KINNEY, PATRICK L.; MILLER, RACHEL L.

2008-01-01

Traffic-related air pollutants have been associated with adverse health effects. We hypothesized that exposure to polycyclic aromatic hydrocarbons (PAHs), elemental carbon (EC, diesel indicator), particulate matter (PM2.5), and a suite of metals declined from 1998 to 2006 in NYC due to policy interventions. PAH levels from personal monitoring of pregnant mothers participating in the Columbia’s Center for Children’s Environmental Health birth cohort study, and EC, PM2.5, and metal data from five New York State Department of Environmental Conservation stationary monitors were compared across sites and over time (1998–2006). Univariate analysis showed a decrease in personal PAHs exposures from 1998 to 2006 (p < 0.0001). After controlling for environmental tobacco smoke, indoor heat, and cooking, year of personal monitoring remained a predictor of decline in Σ8PAHs (β = −0.269, p < 0.001). Linear trend analysis also suggested that PM2.5 declined (p = 0.09). Concentrations of EC and most metals measured by stationary site monitors, as measured by ANOVA, did not decline. Across stationary sites, levels of airborne EC and metals varied considerably. By contrast PM2.5 levels were highly intercorrelated (values ranged from 0.725 to 0.922, p < 0.01). Further policy initiatives targeting traffic-related air pollutants may be needed for a greater impact on public health. PMID:18939566

Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies.

PubMed

de Hoogh, Kees; Korek, Michal; Vienneau, Danielle; Keuken, Menno; Kukkonen, Jaakko; Nieuwenhuijsen, Mark J; Badaloni, Chiara; Beelen, Rob; Bolignano, Andrea; Cesaroni, Giulia; Pradas, Marta Cirach; Cyrys, Josef; Douros, John; Eeftens, Marloes; Forastiere, Francesco; Forsberg, Bertil; Fuks, Kateryna; Gehring, Ulrike; Gryparis, Alexandros; Gulliver, John; Hansell, Anna L; Hoffmann, Barbara; Johansson, Christer; Jonkers, Sander; Kangas, Leena; Katsouyanni, Klea; Künzli, Nino; Lanki, Timo; Memmesheimer, Michael; Moussiopoulos, Nicolas; Modig, Lars; Pershagen, Göran; Probst-Hensch, Nicole; Schindler, Christian; Schikowski, Tamara; Sugiri, Dorothee; Teixidó, Oriol; Tsai, Ming-Yi; Yli-Tuomi, Tarja; Brunekreef, Bert; Hoek, Gerard; Bellander, Tom

2014-12-01

Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the performance of these methods. Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5. The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20-40 ESCAPE monitoring sites in each area. The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19-0.89), 0.39 (0.23-0.66) and 0.29 (0.22-0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519 (4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74 (0.09-0.86) for NO2; 0.58 (0.36-0.88) for PM10 and 0.58 (0.39-0.66) for PM2.5. LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5. Copyright © 2014 Elsevier Ltd. All rights reserved.

An integrated system for the determination of the local, regional and long-transport contributions to Particulate Matter concentrations

NASA Astrophysics Data System (ADS)

Amodio, M.; Andriani, E.; Daresta, B. E.; de Gennaro, G.; di Gilio, A.; Ielpo, P.,; Placentino, C. M.; Trizio, L.; Tutino, M.

2010-05-01

Several epidemiological studies have shown the negative effects of air pollution on human health, which range from respiratory and cardiovascular disease to neurotoxic effects, and cancer. Most recent investigations have been focused on health toxicological features of Particulate Matter (PM) and its interactions with other pollutants: it was found that fine particles (PM2.5) could be an effective media to transport these pollutants deeply into the lung and to cause many kind of reactions which include oxidative stress, local pulmonary and systemic inflammatory responses (Künzli and Perez, 2009). Based on these implications on public health, many countries have developed plans to suggest effective control strategies which involve the identification of Particulate Matter sources, the quantitative estimation of the emission rates of the pollutants, the understanding of PM transport, mixing and transformation processes and the identification of main factors influencing PM concentrations. In this field, receptor models can be useful tools to estimate sources contributions to PM collected in an area under investigations. Different approaches to receptor model analysis can be distinguished on basis of whether chemical characteristics of emission sources are required to be known before the source apportionment. The multivariate approach could be preferred when a lack of information concerning sources profiles occurred (Hopke, 2003). In this work, the results obtained by applying an integrated approach in the monitoring of PM using several typologies of instrumentations will be shown. A prototype for the determination of the contributions of a single source (‘fugitive emission') on the fine PM concentrations has been developed: it consists of a Swam dual-channel sampler, an OPC Monitor, a sonic anemometer and a PBL Mixing monitor. The investigated site chosen for the application of prototype will be the iron and steel pole of Taranto (Apulia Region, South of Italy). Fugitive emission campaign will be performed by using three different positions around the Taranto industrial area; the main interest on Taranto is due to the presence of several activities of high impact as very wide industrial area close to the town and the numerous maritime and military activities in the harbour area (Amodio et al., 2008). The aim is to triangulate the area of the examined source on the basis of the prevalent directions of the wind. The investigation will be completed by chemical-physical characterization of PM2.5 and PM10 samples collected by the prototype in order to have additional information about the possible emissive sources. The statistical analysis, performed by Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF), will be used for a detailed study of the impact of the local emissive source on the neighboring areas. Finally, the prototype will allow to identify and distinguish long range transport, regional and other local contributions on the fine PM concentrations. This work was supported by the Strategic Project PS_122 founded by Apulia Region. References Künzli, N., Perez, L., 2009. Swiss Medical Weekly 139(17-18), 242-250. Hopke, P.K., 2003. Journal of Chemometrics 17(5), 255-265. Amodio, M., Caselli, M., Daresta, B.E., de Gennaro, G., Ielpo, P., Placentino, C.M., Tutino, 2008. Chemical Engineering Transactions 16, 193-199.

Predicting Remembering: Judgments of Prospective Memory After Traumatic Brain Injury.

PubMed

O'Brien, Katy H; Kennedy, Mary R T

2018-06-19

Adults with traumatic brain injuries (TBIs) often struggle with prospective memory (PM), the ability to remember to complete tasks in the future, such as taking medicines on a schedule. Metamemory judgments (or how well we think we will do at remembering) are linked to strategy use and are critical for managing demands of daily living. The current project used an Internet-based virtual reality tool to assess metamemory judgments of PM following TBI. Eighteen adults with moderate to severe TBI and 20 healthy controls (HCs) played Tying the String, a virtual reality game with PM items embedded across the course of a virtual work week. Participants studied PM items and made two judgments of learning about the likelihood of recognizing the CUE, that is, when the task should be done, and of recalling the TASK, that is, what needed to be done. Participants with TBI adjusted their metamemory expectations downward, but not enough to account for poorer recall performance. Absolute difference scores of metamemory accuracy showed that healthy adults were underconfident across PM components, whereas adults with TBI were markedly overconfident about their ability to recall TASKs. Adults with TBI appear to have a general knowledge that PM tasks will be difficult but are poor monitors of actual levels of success. Because metamemory monitoring is linked to strategy use, future work should examine using this link to direct PM intervention approaches.

Source apportionment of particulate matter in a South Asian Mega City: A case study of Karachi

NASA Astrophysics Data System (ADS)

Shahid, imran

2016-04-01

Pakistan is facing unabated air pollution as a major issue and its cities are more vulnerable as compared to urban centers in the developed world. During the last few decades, there has been a rapid increase in population, urbanization, industrialization, transportation and other human activities. In year June 2015 heat wave in largest South Asian mega city Karachi more than 1500 people died in one week. Unfortunately no air quality monitoring system is operation in any city of Pakistan. There is a sharp increase in both the variety and quantity of air pollutants and their corresponding sources. In this study contributions of different sources to particulate matter concentration has estimated in urban area of Karachi. Carbonaceous species (elemental carbon, organic carbon, carbonate carbon), soluble ions (Ca++, Mg++, Na+, K+, NH4+, Cl-, NO3-, SO4--), saccharides (levoglucosan, galactosan, mannosan, sucrose, fructose, glucose, arabitol and mannitol) were measured in atmospheric fine (PM2.5) and coarse (PM10) particles collected under pre-monsoon conditions (March - April 2009) at an urban site in Karachi (Pakistan). Average concentrations of PM2.5 were 75μg/m3 and of PM10 437μg/m3. The large difference between PM10 and PM2.5 originated predominantly from mineral dust. "Calcareous dust" and „siliceous dust" were the overall dominating material in PM, with 46% contribution to PM2.5 and 78% to PM10-2.5. 20 Combustion particles and secondary organics (EC+OM) comprised 23% of PM2.5 and 6% of PM10-2.5. EC, as well as OC ambient levels were higher (59% and 56%) in PM10-2.5 than in 22 PM2.5. Biomass burning contributed about 3% to PM2.5, and had a share of about 13% of "EC+OM" in PM2.5. The impact of bioaerosol (fungal spores) was minor and had a share of 1 and 2% of the OC in the PM2.5 and PM10-2.5 size fractions. Of secondary inorganic constituents (NH4)2SO4 contributes 4.4% to PM2.5 and no detectable quantity to PM10-2.5. The sea salt contribution is about 2% both to PM2.5 and PM10-2.5. In order to make air quality better and risk free in South Asian cities a comprehensive and integrated regional effort is required that include continuous air quality monitoring, source apportionment and implementation of regional air quality policies.

Fine Particulate Pollution and Source Apportionment in the Urban Centers for Africa, Asia and Latin America

NASA Astrophysics Data System (ADS)

Guttikunda, S. K.; Johnson, T. M.; Procee, P.

2004-12-01

Fossil fuel combustion for domestic cooking and heating, power generation, industrial processes, and motor vehicles are the primary sources of air pollution in the developing country cities. Over the past twenty years, major advances have been made in understanding the social and economic consequences of air pollution. In both industrialized and developing countries, it has been shown that air pollution from energy combustion has detrimental impacts on human health and the environment. Lack of information on the sectoral contributions to air pollution - especially fine particulates, is one of the typical constraints for an effective integrated urban air quality management program. Without such information, it is difficult, if not impossible, for decision makers to provide policy advice and make informed investment decisions related to air quality improvements in developing countries. This also raises the need for low-cost ways of determining the principal sources of fine PM for a proper planning and decision making. The project objective is to develop and verify a methodology to assess and monitor the sources of PM, using a combination of ground-based monitoring and source apportionment techniques. This presentation will focus on four general tasks: (1) Review of the science and current activities in the combined use of monitoring data and modeling for better understanding of PM pollution. (2) Review of recent advances in atmospheric source apportionment techniques (e.g., principal component analysis, organic markers, source-receptor modeling techniques). (3) Develop a general methodology to use integrated top-down and bottom-up datasets. (4) Review of a series of current case studies from Africa, Asia and Latin America and the methodologies applied to assess the air pollution and its sources.

[Sampling methods for PM2.5 from stationary sources: a review].

PubMed

Jiang, Jing-Kun; Deng, Jian-Guo; Li, Zhen; Li, Xing-Hua; Duan, Lei; Hao, Ji-Ming

2014-05-01

The new China national ambient air quality standard has been published in 2012 and will be implemented in 2016. To meet the requirements in this new standard, monitoring and controlling PM2,,5 emission from stationary sources are very important. However, so far there is no national standard method on sampling PM2.5 from stationary sources. Different sampling methods for PM2.5 from stationary sources and relevant international standards were reviewed in this study. It includes the methods for PM2.5 sampling in flue gas and the methods for PM2.5 sampling after dilution. Both advantages and disadvantages of these sampling methods were discussed. For environmental management, the method for PM2.5 sampling in flue gas such as impactor and virtual impactor was suggested as a standard to determine filterable PM2.5. To evaluate environmental and health effects of PM2.5 from stationary sources, standard dilution method for sampling of total PM2.5 should be established.

Fact Sheets and Additional information Regarding the 2012 Particulate Matter (PM) National Ambient Air Quality Standards (NAAQS)

EPA Pesticide Factsheets

Find tools for particulate matter, maps of nonattainment areas, an overview of the proposal, and information on designations, monitoring and permitting requirements and a presentation on the 2012 PM NAAQS revision.

DETROIT EXPOSURE AND AEROSOL RESEARCH STUDY

EPA Science Inventory

The DEARS is a three-year field monitoring study that will be conducted in Detroit, Michigan and is designed to measure exposure and describe exposure relationships for air toxics, PM components, PM from specific sources, and criteria pollutants. Detroit, Michigan was considered ...

Silenced science: air pollution decision-making at the EPA threatens public health.

PubMed

Rest, Kathleen

2007-01-01

The saga of the Environmental Protection Agency's new particulate matter (PM) rule is yet another example of this Administration's disregard for and disrespect of science and scientists--and may signal the beginning of a disturbing trend to reduce the role of science in protecting the quality of our air. Political interference in the PM case is clear. And more trouble may be in the wings when it comes to acceptable levels of ozone pollution and the process for setting the National Ambient Air Quality Standards (NAAQS). For several years, the Union of Concerned Scientists has been actively monitoring and documenting the misuse of science in public policy-making. Consider this a call to arms. Now is the time to engage your elected officials on these issues.

New Approach to Monitor Transboundary Particulate Pollution over Northeast Asia

NASA Technical Reports Server (NTRS)

Park, M. E.; Song, C. H.; Park, R. S.; Lee, Jaehwa; Kim, J.; Lee, S.; Woo, J. H.; Carmichael, G. R.; Eck, Thomas F.; Holben, Brent N.;

New approach to monitor transboundary particulate pollution over Northeast Asia

NASA Astrophysics Data System (ADS)

Park, M. E.; Song, C. H.; Park, R. S.; Lee, J.; Kim, J.; Lee, S.; Woo, J.-H.; Carmichael, G. R.; Eck, T. F.; Holben, B. N.; Lee, S.-S.; Song, C. K.; Hong, Y. D.

2014-01-01

A new approach to more accurately monitor and evaluate transboundary particulate matter (PM) pollution is introduced based on aerosol optical products from Korea's Geostationary Ocean Color Imager (GOCI). The area studied is Northeast Asia (including eastern parts of China, the Korean peninsula and Japan), where GOCI has been monitoring since June 2010. The hourly multi-spectral aerosol optical data that were retrieved from GOCI sensor onboard geostationary satellite COMS (Communication, Ocean, and Meteorology Satellite) through the Yonsei aerosol retrieval algorithm were first presented and used in this study. The GOCI-retrieved aerosol optical data are integrated with estimated aerosol distributions from US EPA Models-3/CMAQ (Community Multi-scale Air Quality) v4.5.1 model simulations via data assimilation technique, thereby making the aerosol data spatially continuous and available even for cloud contamination cells. The assimilated aerosol optical data are utilized to provide quantitative estimates of transboundary PM pollution from China to the Korean peninsula and Japan. For the period of 1 April to 31 May, 2011 this analysis yields estimates that AOD as a proxy for PM2.5 or PM10 during long-range transport events increased by 117-265% compared to background average AOD (aerosol optical depth) at the four AERONET sites in Korea, and average AOD increases of 121% were found when averaged over the entire Korean peninsula. This paper demonstrates that the use of multi-spectral AOD retrievals from geostationary satellites can improve estimates of transboundary PM pollution. Such data will become more widely available later this decade when new sensors such as the GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI-2 are scheduled to be launched.

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.

The dark side of the tradition: the polluting effect of Epiphany folk fires in the eastern Po Valley (Italy).

PubMed

Masiol, Mauro; Formenton, Gianni; Giraldo, Giorgia; Pasqualetto, Alberto; Tieppo, Paulo; Pavoni, Bruno

2014-03-01

In the Veneto Region (Po Valley, Northeastern Italy) on the eve of Epiphany, an important religious celebration, during the night between January 5th and 6th thousands of folk fires traditionally burn wooden material. The object of this study is to characterize the 2013 episode, by monitoring the effects on the air quality in the region's lowlands. The daily concentrations of PM2.5 and PM10 exceeded 250 and 300 μg m(-3), respectively and the PM10 hourly values were above 600 μg m(-3) in many sites. The levels of total carbon, major inorganic ions, polycyclic aromatic hydrocarbons and biomass burning tracers (levoglucosan and K(+)) were measured in 84 samples of PM10 and 38 of PM2.5 collected at 32 sites between January 4th and 7th. Total carbon ranged from 11 μg m(-3) before the pollution episode to 131 μg m(-3) a day afterwards, K(+) from 0.6 to 5.1μg m(-3), benzo(a)pyrene from 2 to 23 ng m(-3), and levoglucosan from 0.5 to 8.3 μg m(-3). The dispersion of the particulate matter was traced by analyzing the levels of PM10 and PM2.5 in 133 and 51 sites, respectively, in the Veneto and neighboring regions. In addition to biomass burning the formation of secondary inorganic aerosol was revealed to be a key factor on a multivariate statistical data processing. By providing direct information on the effects of an intense and widespread biomass burning episode in the Po Valley, this study also enables some general considerations on biomass burning practices. Copyright © 2013 Elsevier B.V. All rights reserved.

The effect of semantic context on prospective memory performance.

PubMed

Thomas, Brandon J; McBride, Dawn M

2016-01-01

The current study provides evidence for spontaneous processing in prospective memory (PM) or memory for intentions. Discrepancy-plus-search is the spontaneous processing of PM cues via disruptions in processing fluency of ongoing task items. We tested whether this mechanism can be demonstrated in an ongoing rating task with a dominant semantic context. Ongoing task items were manipulated such that the PM cues were members of a semantic category (i.e., Body Parts) that was congruent or discrepant with the dominant semantic category in the ongoing task. Results showed that participants correctly responded to more PM cues when there was a category discrepancy between the PM cues and ongoing task items. Moreover, participants' identification of PM cues was accompanied by faster ongoing task reaction times when PM cues were discrepant with ongoing task items than when they were congruent. These results suggest that a discrepancy-plus-search process supports PM retrieval in certain contexts, and that some discrepancy-plus-search mechanisms may result from the violation of processing expectations within a semantic context.

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.

Personal exposures to fine particulate matter and black carbon in households cooking with biomass fuels in rural Ghana

PubMed Central

Van Vliet, Eleanne D.S.; Asante, Kwakupoku; Jack, Darby W.; Kinney, Patrick L.; Whyatt, Robin M.; Chillrud, Steven N.; Abokyi, Livesy; Zandoh, Charles; Owusu-Agyei, Seth

2014-01-01

Objective To examine cooking practices and 24-h personal and kitchen area exposures to fine particulate matter (PM2.5) and black carbon in cooks using biomass in Ghana. Methods Researchers administered a detailed survey to 421 households. In a sub-sample of 36 households, researchers collected 24-h integrated PM2.5 samples (personal and kitchen area); in addition, the primary cook was monitored for real-time PM2.5. All filters were also analyzed for black carbon using a multi-wavelength reflectance method. Predictors of PM2.5 exposure were analyzed, including cooking behaviors, fuel, stove and kitchen type, weather, demographic factors and other smoke sources. Results The majority of households cooked outdoors (55%; 231/417), used biomass (wood or charcoal) as their primary fuel (99%; 412/413), and cooked on traditional fires (77%, 323/421). In the sub-sample of 29 households with complete, valid exposure monitoring data, the 24-h integrated concentrations of PM2.5 were substantially higher in the kitchen sample (mean 446.8 μg/m3) than in the personal air sample (mean 128.5 μg/m3). Black carbon concentrations followed the same pattern such that concentrations were higher in the kitchen sample (14.5 μg/m3) than in the personal air sample (8.8 μg/m3). Spikes in real-time personal concentrations of PM2.5 accounted for the majority of exposure; the most polluted 5%, or 72 min, of the 24-h monitoring period accounted for 75% of all exposure. Two variables that had some predictive power for personal PM2.5 exposures were primary fuel type and ethnicity, while reported kerosene lantern use was associated with increased personal and kitchen area concentrations of black carbon. Conclusion Personal concentrations of PM2.5 exhibited considerable inter-subject variability across kitchen types (enclosed, semi-enclosed, outdoor), and can be elevated even in outdoor cooking settings. Furthermore, personal concentrations of PM2.5 were not associated with kitchen type and were not predicted by kitchen area samples; rather they were driven by spikes in PM2.5 concentrations during cooking. Personal exposures were more enriched with black carbon when compared to kitchen area samples, underscoring the need to explore other sources of incomplete combustion such as roadway emissions, charcoal production and kerosene use. PMID:24176411

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

Bocci, Valerio; Chiodi, Giacomo; Iacoangeli, Francesco

The necessity to use Photo Multipliers (PM) as light detector limited in the past the use of crystals in radiation handled device preferring the Geiger approach. The Silicon Photomultipliers (SiPMs) are very small and cheap, solid photon detectors with good dynamic range and single photon detection capability, they are usable to supersede cumbersome and difficult to use Photo Multipliers (PM). A SiPM can be coupled with a scintillator crystal to build efficient, small and solid radiation detector. A cost effective and easily replicable Hardware software module for SiPM detector readout is made using the ArduSiPM solution. The ArduSiPM is anmore » easily battery operable handled device using an Arduino DUE (an open Software/Hardware board) as processor board and a piggy-back custom designed board (ArduSiPM Shield), the Shield contains all the blocks features to monitor, set and acquire the SiPM using internet network. (authors)« less

HIERARCHIAL BAYESIAN CALIBRATION: AN APPLICATION TO AIRBORNE PARTICULATE MATTER MONITORING DATA

EPA Science Inventory

In studies of the relationship between airborne fine particulate matter (PM2.5) and health, researchers frequently use monitoring data with the most extensive temporal coverage. Such data may come from a monitor that is not a federal reference monitor (FRM), a monitor that is d...

Response of consumer and research grade indoor air quality monitors to residential sources of fine particles.

PubMed

Singer, B C; Delp, W W

2018-04-23

The ability to inexpensively monitor PM 2.5 to identify sources and enable controls would advance residential indoor air quality (IAQ) management. Consumer IAQ monitors incorporating low-cost optical particle sensors and connections with smart home platforms could provide this service if they reliably detect PM 2.5 in homes. In this study, particles from typical residential sources were generated in a 120 m 3 laboratory and time-concentration profiles were measured with 7 consumer monitors (2-3 units each), 2 research monitors (Thermo pDR-1500, MetOne BT-645), a Grimm Mini Wide-Range Aerosol Spectrometer (GRM), and a Tapered Element Oscillating Microbalance with Filter Dynamic Measurement System (FDMS), a Federal Equivalent Method for PM 2.5 . Sources included recreational combustion (candles, cigarettes, incense), cooking activities, an unfiltered ultrasonic humidifier, and dust. FDMS measurements, filter samples, and known densities were used to adjust the GRM to obtain time-resolved mass concentrations. Data from the research monitors and 4 of the consumer monitors-AirBeam, AirVisual, Foobot, Purple Air-were time correlated and within a factor of 2 of the estimated mass concentrations for most sources. All 7 of the consumer and both research monitors substantially under-reported or missed events for which the emitted mass was comprised of particles smaller than 0.3 μm diameter. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

48 CFR 301.607-76 - FAC-P/PM application process.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 4 2010-10-01 2010-10-01 false FAC-P/PM application... 301.607-76 FAC-P/PM application process. The P/PM Handbook contains application procedures and forms...; recertification; and certification waiver. Applicants for HHS FAC-P/PM certification actions shall comply with the...

48 CFR 301.607-76 - FAC-P/PM application process.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 4 2011-10-01 2011-10-01 false FAC-P/PM application... 301.607-76 FAC-P/PM application process. The P/PM Handbook contains application procedures and forms...; recertification; and certification waiver. Applicants for HHS FAC-P/PM certification actions shall comply with the...

48 CFR 301.607-76 - FAC-P/PM application process.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 48 Federal Acquisition Regulations System 4 2014-10-01 2014-10-01 false FAC-P/PM application... 301.607-76 FAC-P/PM application process. The P/PM Handbook contains application procedures and forms...; recertification; and certification waiver. Applicants for HHS FAC-P/PM certification actions shall comply with the...

48 CFR 301.607-76 - FAC-P/PM application process.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 48 Federal Acquisition Regulations System 4 2012-10-01 2012-10-01 false FAC-P/PM application... 301.607-76 FAC-P/PM application process. The P/PM Handbook contains application procedures and forms...; recertification; and certification waiver. Applicants for HHS FAC-P/PM certification actions shall comply with the...

48 CFR 301.607-76 - FAC-P/PM application process.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 48 Federal Acquisition Regulations System 4 2013-10-01 2013-10-01 false FAC-P/PM application... 301.607-76 FAC-P/PM application process. The P/PM Handbook contains application procedures and forms...; recertification; and certification waiver. Applicants for HHS FAC-P/PM certification actions shall comply with the...

In Vivo Monitoring Program Manual, PNL-MA-574

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

Lynch, Timothy P.

2010-07-01

An overview of the administration for the In Vivo Monitoring Program (IVMP) for Hanford. This includes organizational structure and program responsibilities; coordination of in vivo measurements; scheduling measurements; performing measurements; reporting results; and quality assurance. Overall responsibility for the management of the IVMP rests with the Program Manager (PM). The PM is responsible for providing the required in vivo counting services for Hanford Site contractor employees in accordance with Department of Energy (DOE) requirements and the specific statements of work.

Biomagnetic Monitoring of Atmospheric Pollution: A Review of Magnetic Signatures from Biological Sensors.

PubMed

Hofman, Jelle; Maher, Barbara A; Muxworthy, Adrian R; Wuyts, Karen; Castanheiro, Ana; Samson, Roeland

2017-06-20

Biomagnetic monitoring of atmospheric pollution is a growing application in the field of environmental magnetism. Particulate matter (PM) in atmospheric pollution contains readily measurable concentrations of magnetic minerals. Biological surfaces, exposed to atmospheric pollution, accumulate magnetic particles over time, providing a record of location-specific, time-integrated air quality information. This review summarizes current knowledge of biological material ("sensors") used for biomagnetic monitoring purposes. Our work addresses the following: the range of magnetic properties reported for lichens, mosses, leaves, bark, trunk wood, insects, crustaceans, mammal and human tissues; their associations with atmospheric pollutant species (PM, NO x , trace elements, PAHs); the pros and cons of biomagnetic monitoring of atmospheric pollution; current challenges for large-scale implementation of biomagnetic monitoring; and future perspectives. A summary table is presented, with the aim of aiding researchers and policy makers in selecting the most suitable biological sensor for their intended biomagnetic monitoring purpose.

EVALUATION OF A PERSONAL NEPHELOMETER FOR HUMAN EXPOSURE MONITORING

EPA Science Inventory

Current particulate matter (PM) exposure studies are using continuous personal nephelometers (pDR-1000, MIE, Inc.) to measure human exposure to PM. The personal nephelometer is a passive sampler which uses light scattering technology to measure particles ranging in size from 0....

FORT HALL SOURCE APPORTIONMENT STUDY (FINAL REPORT)

EPA Science Inventory

Air quality monitoring on the Fort Hall Indian Reservation has revealed numerous exceedances of the National Ambient Air Quality Standard (NAAQS) for 24-h averaged PM10 mass. Wind-directional analysis coupled with PM10 measurements have identified the FMC elemental phosphorus p...

National-scale exposure prediction for long-term concentrations of particulate matter and nitrogen dioxide in South Korea.

PubMed

Kim, Sun-Young; Song, Insang

2017-07-01

The limited spatial coverage of the air pollution data available from regulatory air quality monitoring networks hampers national-scale epidemiological studies of air pollution. The present study aimed to develop a national-scale exposure prediction model for estimating annual average concentrations of PM 10 and NO 2 at residences in South Korea using regulatory monitoring data for 2010. Using hourly measurements of PM 10 and NO 2 at 277 regulatory monitoring sites, we calculated the annual average concentrations at each site. We also computed 322 geographic variables in order to represent plausible local and regional pollution sources. Using these data, we developed universal kriging models, including three summary predictors estimated by partial least squares (PLS). The model performance was evaluated with fivefold cross-validation. In sensitivity analyses, we compared our approach with two alternative approaches, which added regional interactions and replaced the PLS predictors with up to ten selected variables. Finally, we predicted the annual average concentrations of PM 10 and NO 2 at 83,463 centroids of residential census output areas in South Korea to investigate the population exposure to these pollutants and to compare the exposure levels between monitored and unmonitored areas. The means of the annual average concentrations of PM 10 and NO 2 for 2010, across regulatory monitoring sites in South Korea, were 51.63 μg/m3 (SD = 8.58) and 25.64 ppb (11.05), respectively. The universal kriging exposure prediction models yielded cross-validated R 2 s of 0.45 and 0.82 for PM 10 and NO 2 , respectively. Compared to our model, the two alternative approaches gave consistent or worse performances. Population exposure levels in unmonitored areas were lower than in monitored areas. This is the first study that focused on developing a national-scale point wise exposure prediction approach in South Korea, which will allow national exposure assessments and epidemiological research to answer policy-related questions and to draw comparisons among different countries. Copyright © 2017 Elsevier Ltd. All rights reserved.

Characterization of traffic-related PM concentration distribution and fluctuation patterns in near-highway urban residential street canyons.

PubMed

Hahn, Intaek; Brixey, Laurie A; Wiener, Russell W; Henkle, Stacy W; Baldauf, Richard

2009-12-01

Analyses of outdoor traffic-related particulate matter (PM) concentration distribution and fluctuation patterns in urban street canyons within a microscale distance of less than 500 m from a highway source are presented as part of the results from the Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study. Various patterns of spatial and temporal changes in the street canyon PM concentrations were investigated using time-series data of real-time PM concentrations measured during multiple monitoring periods. Concurrent time-series data of local street canyon wind conditions and wind data from the John F. Kennedy (JFK) International Airport National Weather Service (NWS) were used to characterize the effects of various wind conditions on the behavior of street canyon PM concentrations.Our results suggest that wind direction may strongly influence time-averaged mean PM concentration distribution patterns in near-highway urban street canyons. The rooftop-level wind speeds were found to be strongly correlated with the PM concentration fluctuation intensities in the middle sections of the street blocks. The ambient turbulence generated by shifting local wind directions (angles) showed a good correlation with the PM concentration fluctuation intensities along the entire distance of the first and second street blocks only when the wind angle standard deviations were larger than 30 degrees. Within-canyon turbulent shearing, caused by fluctuating local street canyon wind speeds, showed no correlation with PM concentration fluctuation intensities. The time-averaged mean PM concentration distribution along the longitudinal distances of the street blocks when wind direction was mostly constantly parallel to the street was found to be similar to the distribution pattern for the entire monitoring period when wind direction fluctuated wildly. Finally, we showed that two different PM concentration metrics-time-averaged mean concentration and number of concentration peaks above a certain threshold level-can possibly lead to different assessments of spatial concentration distribution patterns.

A land use regression application into assessing spatial variation of intra-urban fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations in City of Shanghai, China.

PubMed

Liu, Chao; Henderson, Barron H; Wang, Dongfang; Yang, Xinyuan; Peng, Zhong-Ren

2016-09-15

Intra-urban assessment of air pollution exposure has become a priority study while international attention was attracted to PM2.5 pollution in China in recent years. Land Use Regression (LUR), which has previously been proved to be a feasible way to describe the relationship between land use and air pollution level in European and American cities, was employed in this paper to explain the correlations and spatial variations in Shanghai, China. PM2.5 and NO2 concentrations at 35-45 monitoring locations were selected as dependent variables, and a total of 44 built environmental factors were extracted as independent variables. Only five factors showed significant explanatory value for both PM2.5 and NO2 models: longitude, distance from monitors to the ocean, highway intensity, waterbody area, and industrial land area for PM2.5 model; residential area, distance to the coast, industrial area, urban district, and highway intensity for NO2 model. Respectively, both PM2.5 and NO2 showed anti-correlation with coastal proximity (an indicator of clean air dilution) and correlation with highway and industrial intensity (source indicators). NO2 also showed significant correlation with local indicators of population density (residential intensity and urban classification), while PM2.5 showed significant correlation with regional dilution (longitude as a indicator of distance from polluted neighbors and local water features). Both adjusted R squared values were strong with PM2.5 (0.88) being higher than NO2 (0.62). The LUR was then used to produce continuous concentration fields for NO2 and PM2.5 to illustrate the features and, potentially, for use by future studies. Comparison to PM2.5 studies in New York and Beijing show that Shanghai PM2.5 pollutant distribution was more sensitive to geographic location and proximity to neighboring regions. Copyright © 2015. Published by Elsevier B.V.

Modeling of the chemical composition of fine particulate matter: Development and performance assessment of EASYWRF-Chem

NASA Astrophysics Data System (ADS)

Mendez, M.; Lebègue, P.; Visez, N.; Fèvre-Nollet, V.; Crenn, V.; Riffault, V.; Petitprez, D.

2016-03-01

The European emission Adaptation SYstem for the WRF-Chem model (EASYWRF-Chem) has been developed to generate chemical information supporting the WRF-Chem requirements from any emission inventory based on the CORINAIR methodology. Using RADM2 and RACM2 mechanisms, "emission species" are converted into "model species" thanks to the SAPRC methodology for gas phase pollutant and the PM10 and PM2.5 fractions. Furthermore, by adapting US EPA PM2.5 profiles, the processing of aerosol chemical speciation profiles separates the unspeciated PM2.5 emission into five chemical families: sulfates, nitrates, elemental carbon, organic aerosol and unspeciated aerosol. The evaluation of the model has been performed by separately comparing model outcomes with (i) meteorological measurements; (ii) NO2, O3, PM10 and PM2.5 mass concentrations from the regional air quality monitoring network; (iii) hourly-resolved data from four field campaign measurements, in winter and in summer, on two sites in the French northern region. In the latter, a High Resolution - Time of Flight - Aerosol Mass Spectrometer (HR-ToF-AMS) provided non-refractory PM1 concentrations of sulfate, nitrate and ammonium ions as well as organic matter (OM), while an aethalometer provided black carbon (BC) concentrations in the PM2.5 fraction. Meteorological data (temperature, wind, relative humidity) are well simulated for all the time series data except for specific events as wind direction changes or rainfall. For particulate matter, results are presented by considering firstly the total mass concentration of PM2.5 and PM10. EASYWRF-Chem simulations overestimated the PM10 mass concentrations by + 22% and + 4% for summer and winter periods respectively, whereas for the finer PM2.5 fraction, mass concentrations were overestimated by + 20% in summer and underestimated by - 13% in winter. Simulated sulfate concentrations were underestimated and nitrate concentrations were overestimated but hourly variations were well represented. Ammonium particulate matter was well simulated for all seasons. Although simulated particulate OM concentrations in PM2.5 were underestimated, their hourly variations were well reproduced by the model. At least BC measurements revealed that EASYWRF-Chem forecast performance was higher in winter than during summer when BC concentrations were very low.

Asthma management practices in adults--findings from the German Health Update (GEDA) 2010 and the German National Health Interview and Examination Survey (DEGS1) 2008-2011.

PubMed

Steppuhn, Henriette; Langen, Ute; Mueters, Stephan; Dahm, Stefan; Knopf, Hildtraud; Keil, Thomas; Scheidt-Nave, Christa

2016-01-01

In Germany, population-wide data on adherence to national asthma management guidelines are lacking, and performance measures (PM) for quality assurance in asthma care are systematically monitored for patients with German national asthma disease management program (DMP) enrollment only. We used national health survey data to assess variation in asthma care PM with respect to patient characteristics and care context, including DMP enrollment. Among adults 18-79 years with self-reported physician-diagnosed asthma in the past 12 months identified from a recent German National Health Interview Survey (GEDA 2010: N = 1096) and the German National Health interview and Examination Survey 2008-2011 (DEGS1: N = 333), variation in asthma care PM was analyzed using logistic regression analysis. Overall, 38.4% (95% confidence interval: 32.5-44.6%) of adults with asthma were on current inhaled corticosteroid therapy. Regarding non-drug asthma management, low coverage was observed for inhaler technique monitoring (35.2%; 31.2-39.3%) and for provision of an asthma management plan (27.3%; 24.2-30.7%), particularly among those with low education. Specific PM were more complete among persons with than without asthma DMP enrollment (adjusted odds ratios ranging up to 10.19; 5.23-19.86), even if asthma patients were regularly followed in a different care context. Guideline adherence appears to be suboptimal, particularly with respect to PM related to patient counseling. Barriers to the translation of recommendations into practice need to be identified and continuous monitoring of asthma care PM at the population level needs to be established.

Size distribution of PM at Cape Verde - Santiago Island

NASA Astrophysics Data System (ADS)

Pio, C.; Nunes, T.; Cardoso, J.; Caseiro, A.; Cerqueira, M.; Custodio, D.; Freitas, M. C.; Almeida, S. M.

2012-04-01

The archipelago of Cape Verde is located on the eastern North Atlantic, about 500 km west of the African coast. Its geographical location, inside the main area of dust transport over tropical Atlantic and near the coast of Africa, is strongly affected by mineral dust from the Sahara and the Sahel regions. In the scope of the CVDust project a surface field station was implemented in the surroundings of Praia City, Santiago Island (14° 55' N e 23° 29' W, 98 m at sea level), where aerosol sampling throughout different samplers was performed during one year. To study the size distribution of aerosol, an optical dust monitor (Grimm 180), from 0.250 to 32 μm in 31 size channels, was running almost continuously from January 2011 to December 2011. The performance of Grimm 180 to quantify PM mass concentration in an area affected by the transport of Saharan dust particles was evaluated throughout the sampling period by comparison with PM10 mass concentrations obtained with the gravimetric reference method (PM10 TSI High-Volume, PM10 Partisol and PM10 TCR-Tecora). PM10 mass concentration estimated with the Grimm 180 dust monitor, an optical counter, showed a good correlation with the reference gravimetric method, with R2= 0.94 and a linear regression equation of PM10Grimm = 0.81PM10TCR- 5.34. The number and mass size distribution of PM at ground level together with meteorological and back trajectories were analyzed and compared for different conditions aiming at identifying different signatures related to sources and dust transport. January and February, the months when most Saharan dust events occurred, showed the highest concentrations, with PM10 daily average of 66.6±60.2 μg m-3 and 91.6±97.4 μg m-3, respectively. During these months PM1 and PM2.5 accounted for less than 11% and 47% of PM10 respectively, and the contribution of fine fractions (PM1 and PM2.5) to PM mass concentrations tended to increase for the other months. During Saharan dust events, the PM2.5 hourly average could reach mass concentrations higher than 200 μg m-3 whereas PM10 overpass 600 μg m-3. Acknowledgement: This work was funded by the Portuguese Science Foundation (FCT) through the project PTDD/AAC-CLI/100331/2008 and FCOMP-01-0124-FEDER-008646 (CV-Dust). J. Cardoso acknowledges the PhD grant SFRH-BD-6105-2009 from FCT.

A framework to spatially cluster air pollution monitoring sites in US based on the PM2.5 composition

PubMed Central

Austin, Elena; Coull, Brent A.; Zanobetti, Antonella; Koutrakis, Petros

2013-01-01

Background Heterogeneity in the response to PM2.5 is hypothesized to be related to differences in particle composition across monitoring sites which reflect differences in source types as well as climatic and topographic conditions impacting different geographic locations. Identifying spatial patterns in particle composition is a multivariate problem that requires novel methodologies. Objectives Use cluster analysis methods to identify spatial patterns in PM2.5 composition. Verify that the resulting clusters are distinct and informative. Methods 109 monitoring sites with 75% reported speciation data during the period 2003–2008 were selected. These sites were categorized based on their average PM2.5 composition over the study period using k-means cluster analysis. The obtained clusters were validated and characterized based on their physico-chemical characteristics, geographic locations, emissions profiles, population density and proximity to major emission sources. Results Overall 31 clusters were identified. These include 21 clusters with 2 or more sites which were further grouped into 4 main types using hierarchical clustering. The resulting groupings are chemically meaningful and represent broad differences in emissions. The remaining clusters, encompassing single sites, were characterized based on their particle composition and geographic location. Conclusions The framework presented here provides a novel tool which can be used to identify and further classify sites based on their PM2.5 composition. The solution presented is fairly robust and yielded groupings that were meaningful in the context of air-pollution research. PMID:23850585

Dealing with prospective memory demands while performing an ongoing task: Shared processing, increased on-task focus, or both?

PubMed

Rummel, Jan; Smeekens, Bridget A; Kane, Michael J

2017-07-01

Prospective memory (PM) is the cognitive ability to remember to fulfill intended action plans at the appropriate future moment. Current theories assume that PM fulfillment draws on attentional processes. Accordingly, pending PM intentions interfere with other ongoing tasks to the extent to which both tasks rely on the same processes. How do people manage the competition between PM and ongoing-task demands? Based on research relating mind wandering and attentional control (Kane & McVay, 2012), we argue that people may not only change the way they process ongoing-task stimuli when given a PM intention, but they may also engage in less off-task thinking than they otherwise would. That is, people focus more strongly on the tasks at hand and dedicate considerable conscious thought to the PM goal. We tested this hypothesis by asking subjects to periodically report on their thoughts during prototypical PM (and control) tasks. Task-unrelated thought rates dropped when participants performed an ongoing task while holding a PM intention versus performing the ongoing task alone (Experiment 1), even when PM demands were minimized (Experiment 2) and more so when PM execution was especially rewarded (Experiment 3). Our findings suggest that PM demands not only elicit a cost to ongoing-task processing, but they also induce a stronger on-task focus and promote conscious thoughts about the PM intention. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Estimation of daily PM10 concentrations in Italy (2006-2012) using finely resolved satellite data, land use variables and meteorology.

PubMed

Stafoggia, Massimo; Schwartz, Joel; Badaloni, Chiara; Bellander, Tom; Alessandrini, Ester; Cattani, Giorgio; De' Donato, Francesca; Gaeta, Alessandra; Leone, Gianluca; Lyapustin, Alexei; Sorek-Hamer, Meytar; de Hoogh, Kees; Di, Qian; Forastiere, Francesco; Kloog, Itai

2017-02-01

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM 10 measurements, land-use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM 10 concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2=0.65 and little bias (average slope of predicted VS observed PM 10 =0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PM 10 levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM 10 concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exposure to hazardous volatile organic compounds, PM 10 and CO while walking along streets in urban Guangzhou, China

NASA Astrophysics Data System (ADS)

Zhao, Lirong; Wang, Xinming; He, Qiusheng; Wang, Hao; Sheng, Guoying; Chan, L. Y.; Fu, Jiamo; Blake, D. R.

Toxic air pollutants in street canyons are important issues concerning public health especially in some large Asian cities like Guangzhou. In 1998 <18% of Guangzhou citizens used public transportation modes, with a majority commuting on foot (42%) or by bicycle (22%). Of the pedestrians, 57% were either senior citizens or students. In the present study, we measured toxic air pollutants while walking along urban streets in Guangzhou to evaluate pedestrian exposure. Volatile organic compounds (VOCs) were collected with sorbent tubes, and PM 10 and CO were measured simultaneously with portable analyzers. Our results showed that pedestrian exposure to PM 10 (with an average of 303 μg m -3 for all samples) and some toxic VOCs (for example, benzene) was relatively high. Monocyclic aromatic hydrocarbons were found to be the most abundant VOCs, and 71% of the samples had benzene levels higher than 30 μg m -3. Benzene, PM 10 and CO in walk-only streets were significantly lower ( p<0.05) than in traffic streets, and the differences in exposure levels between new urban streets and old urban streets were highly significant ( p<0.01). Pedestrian exposure to toxic VOCs and PM 10 was higher than those reported in other public transportation modes (bus and subway). The good correlations between BTEX, PM 10 and CO in the streets indicated that automotive emission might be their major source. Our study also showed that the risk to pedestrians due to air pollution was misinterpreted by the reported air quality index based on measurement of SO 2, NO x and PM 10 in the government monitoring stations. An urban roadside monitoring station might be needed by air quality monitoring networks in large Asian cities like Guangzhou, in order to survey exposure to air toxics in urban roadside microenvironments.

Monitoring of air pollution levels related to Charilaos Trikoupis Bridge.

PubMed

Sarigiannis, D A; Handakas, E J; Kermenidou, M; Zarkadas, I; Gotti, A; Charisiadis, P; Makris, K; Manousakas, M; Eleftheriadis, K; Karakitsios, S P

2017-12-31

Charilaos Trikoupis bridge is the longest cable bridge in Europe that connects Western Greece with the rest of the country. In this study, six air pollution monitoring campaigns (including major regulated air pollutants) were carried out from 2013 to 2015 at both sides of the bridge, located in the urban areas of Rio and Antirrio respectively. Pollution data were statistically analyzed and air quality was characterized using US and European air quality indices. From the overall campaign, it was found that air pollution levels were below the respective regulatory thresholds, but once at the site of Antirrio (26.4 and 52.2μg/m 3 for PM 2.5 and ΡΜ 10 , respectively) during the 2nd winter period. Daily average PM 10 and PM 2.5 levels from two monitoring sites were well correlated to gaseous pollutant (CO, NO, NO 2 , NO x and SO 2 ) levels, meteorological parameters and factor scores from Positive Matrix Factorization during the 3-year period. Moreover, the elemental composition of PM 10 and PM 2.5 was used for source apportionment. That analysis revealed that major emission sources were sulfates, mineral dust, biomass burning, sea salt, traffic and shipping emissions for PM 10 and PM 2.5 , for both Rio and Antirrio. Seasonal variation indicates that sulfates, mineral dust and traffic emissions increased during the warm season of the year, while biomass burning become the dominant during the cold season. Overall, the contribution of the Charilaos Trikoupis bridge to the vicinity air pollution is very low. This is the result of the relatively low daily traffic volume (~10,000 vehicles per day), the respective traffic fleet composition (~81% of the traffic fleet are private vehicles) and the speed limit (80km/h) which does not favor traffic emissions. In addition, the strong and frequent winds further contribute to the rapid dispersion of the emitted pollutants. Copyright © 2017. Published by Elsevier B.V.

The impact of working memory and the “process of process modelling” on model quality: Investigating experienced versus inexperienced modellers

NASA Astrophysics Data System (ADS)

Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R.; Weber, Barbara

2016-05-01

A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling.

The impact of working memory and the “process of process modelling” on model quality: Investigating experienced versus inexperienced modellers

PubMed Central

Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R.; Weber, Barbara

2016-01-01

A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling. PMID:27157858

The impact of working memory and the "process of process modelling" on model quality: Investigating experienced versus inexperienced modellers.

PubMed

Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R; Weber, Barbara

2016-05-09

A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling.

Two-Step Single Particle Mass Spectrometry for On-Line Monitoring of Polycyclic Aromatic Hydrocarbons Bound to Ambient Fine Particulate Matter

NASA Astrophysics Data System (ADS)

Zimmermann, R.; Bente, M.; Sklorz, M.

2007-12-01

Polycyclic aromatic hydrocarbons (PAH) are formed as trace products in combustion processes and are emitted to the atmosphere. Larger PAH have low vapour pressure and are predominantly bound to the ambient fine particulate matter (PM). Upon inhalation, PAH show both, chronic human toxicity (i.e. many PAH are potent carcinogens) as well as acute human toxicity (i.e. inflammatory effects due to oxi-dative stress) and are discussed to be relevant for the observed health effect of ambient PM. Therefore a better understanding of the occurrence, dynamics and particle size dependence of particle bound-PAH is of great interest. On-line aerosol mass spectrometry in principle is the method of choice to investigate the size resolved changes in the chemical speciation of particles as well the status of internal vs. external mixing of chemical constituents. However the present available aerosol mass spectrometers (ATOFMS and AMS) do not allow detection of PAH from ambient air PM. In order to allow a single particle based monitoring of PAH from ambient PM a new single particle laser ionisation mass spectrometer was built and applied. The system is based on ATOFMS principle but uses a two- step photo-ionization. A tracked and sized particle firstly is laser desorbed (LD) by a IR-laser pulse (CO2-laser, λ=10.2 μm) and subsequently the released PAH are selectively ionized by an intense UV-laser pulse (ArF excimer, λ=248 nm) in a resonance enhanced multiphoton ionisation process (REMPI). The PAH-ions are detected in a time of flight mass spectrometer (TOFMS). A virtual impactor enrichment unit is used to increase the detection frequency of the ambient particles. With the current inlet system particles from about 400 nm to 10 μm are accessible. Single particle based temporal profiles of PAH containing particles ion (size distribution and PAH speciation) have been recorded in Oberschleissheim, Germany from ambient air. Furthermore profiles of relevant emission sources (e.g. gasoline and diesel engine, wood combustion) and the obtained chemical profiles were compared with the ones from the ambient PAH containing particles.

Comparison between air pollution concentrations measured at the nearest monitoring station to the delivery hospital and those measured at stations nearest the residential postal code regions of pregnant women in Fukuoka.

PubMed

Michikawa, Takehiro; Morokuma, Seiichi; Nitta, Hiroshi; Kato, Kiyoko; Yamazaki, Shin

2017-06-13

Numerous earlier studies examining the association of air pollution with maternal and foetal health estimated maternal exposure to air pollutants based on the women's residential addresses. However, residential addresses, which are personally identifiable information, are not always obtainable. Since a majority of pregnant women reside near their delivery hospitals, the concentrations of air pollutants at the respective delivery hospitals may be surrogate markers of pollutant exposure at home. We compared air pollutant concentrations measured at the nearest monitoring station to Kyushu University Hospital with those measured at the closest monitoring stations to the respective residential postal code regions of pregnant women in Fukuoka. Aggregated postal code data for the home addresses of pregnant women who delivered at Kyushu University Hospital in 2014 was obtained from Kyushu University Hospital. For each of the study's 695 women who resided in Fukuoka Prefecture, we assigned pollutant concentrations measured at the nearest monitoring station to Kyushu University Hospital and pollutant concentrations measured at the nearest monitoring station to their respective residential postal code regions. Among the 695 women, 584 (84.0%) resided in the proximity of the nearest monitoring station to hospital or one of the four other stations (as the nearest stations to their respective residential postal code region) in Fukuoka city. Pearson's correlation for daily mean concentrations among the monitoring stations in Fukuoka city was strong for fine particulate matter (PM 2.5 ), suspended particulate matter (SPM), and photochemical oxidants (Ox) (coefficients ≥0.9), but moderate for coarse particulate matter (the result of subtracting the PM 2.5 from the SPM concentrations), nitrogen dioxide, and sulphur dioxide. Hospital-based and residence-based concentrations of PM 2.5 , SPM, and Ox were comparable. For PM 2.5 , SPM, and Ox, exposure estimation based on the delivery hospital is likely to approximate that based on the home of pregnant women.

Joint OSNR monitoring and modulation format identification in digital coherent receivers using deep neural networks.

PubMed

Khan, Faisal Nadeem; Zhong, Kangping; Zhou, Xian; Al-Arashi, Waled Hussein; Yu, Changyuan; Lu, Chao; Lau, Alan Pak Tao

2017-07-24

We experimentally demonstrate the use of deep neural networks (DNNs) in combination with signals' amplitude histograms (AHs) for simultaneous optical signal-to-noise ratio (OSNR) monitoring and modulation format identification (MFI) in digital coherent receivers. The proposed technique automatically extracts OSNR and modulation format dependent features of AHs, obtained after constant modulus algorithm (CMA) equalization, and exploits them for the joint estimation of these parameters. Experimental results for 112 Gbps polarization-multiplexed (PM) quadrature phase-shift keying (QPSK), 112 Gbps PM 16 quadrature amplitude modulation (16-QAM), and 240 Gbps PM 64-QAM signals demonstrate OSNR monitoring with mean estimation errors of 1.2 dB, 0.4 dB, and 1 dB, respectively. Similarly, the results for MFI show 100% identification accuracy for all three modulation formats. The proposed technique applies deep machine learning algorithms inside standard digital coherent receiver and does not require any additional hardware. Therefore, it is attractive for cost-effective multi-parameter estimation in next-generation elastic optical networks (EONs).

A KPI-based process monitoring and fault detection framework for large-scale processes.

PubMed

Zhang, Kai; Shardt, Yuri A W; Chen, Zhiwen; Yang, Xu; Ding, Steven X; Peng, Kaixiang

2017-05-01

Large-scale processes, consisting of multiple interconnected subprocesses, are commonly encountered in industrial systems, whose performance needs to be determined. A common approach to this problem is to use a key performance indicator (KPI)-based approach. However, the different KPI-based approaches are not developed with a coherent and consistent framework. Thus, this paper proposes a framework for KPI-based process monitoring and fault detection (PM-FD) for large-scale industrial processes, which considers the static and dynamic relationships between process and KPI variables. For the static case, a least squares-based approach is developed that provides an explicit link with least-squares regression, which gives better performance than partial least squares. For the dynamic case, using the kernel representation of each subprocess, an instrument variable is used to reduce the dynamic case to the static case. This framework is applied to the TE benchmark process and the hot strip mill rolling process. The results show that the proposed method can detect faults better than previous methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

INTERPOLATING VANCOUVER'S DAILY AMBIENT PM 10 FIELD

EPA Science Inventory

In this article we develop a spatial predictive distribution for the ambient space- time response field of daily ambient PM10 in Vancouver, Canada. Observed responses have a consistent temporal pattern from one monitoring site to the next. We exploit this feature of the field b...

RECRUITING AND RETAINING PARTICIPANTS FOR AN EXPOSURE STUDY IN SOUTHEAST RALEIGH

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) recently completed a study of African-Americans' exposure to particulate matter (PM) in Southeast Raleigh. A primary goal was to compare PM levels measured at ambient and residential sites with those from personal exposure monitors...

An evaluation of indoor and outdoor biological particulate matter (BioPM)

EPA Science Inventory

Monitoring of indoor and ambient particulate matter (PM) and the characterization of the content for biological aerosol concentrations has not been extensively performed. Samples from urban and rural North Carolina, and Denver, CO, were collected and analyzed as the goal of this ...

(TUCSON) STUDY DESIGN AND PRELIMINARY EXPOSURE FINDINGS ASSOCIATED WITH THE DEARS

EPA Science Inventory

The Detroit Exposure and Aerosol Research Study (DEARS) is a three-year field monitoring study initiated in 2004 that is designed to measure exposure and describe exposure relationships for air toxics, PM components, PM from specific sources, and criteria pollutants. Detroit, Mic...

A new technique for online measurement of total and water-soluble copper (Cu) in coarse particulate matter (PM).

PubMed

Wang, Dongbin; Shafer, Martin M; Schauer, James J; Sioutas, Constantinos

2015-04-01

This study presents a novel system for online, field measurement of copper (Cu) in ambient coarse (2.5-10 μm) particulate matter (PM). This new system utilizes two virtual impactors combined with a modified liquid impinger (BioSampler) to collect coarse PM directly as concentrated slurry samples. The total and water-soluble Cu concentrations are subsequently measured by a copper Ion Selective Electrode (ISE). Laboratory evaluation results indicated excellent collection efficiency (over 85%) for particles in the coarse PM size ranges. In the field evaluations, very good agreements for both total and water-soluble Cu concentrations were obtained between online ISE-based monitor measurements and those analyzed by means of inductively coupled plasma mass spectrometry (ICP-MS). Moreover, the field tests indicated that the Cu monitor could achieve near-continuous operation for at least 6 consecutive days (a time resolution of 2-4 h) without obvious shortcomings. Copyright © 2015 Elsevier Ltd. All rights reserved.

Aerosol Pollution from Small Combustors in a Village

PubMed Central

Zwozdziak, A.; Samek, L.; Sowka, I.; Furman, L.; Skrętowicz, M.

2012-01-01

Urban air pollution is widely recognized. Recently, there have been a few projects that examined air quality in rural areas (e.g., AUPHEP project in Austria, WOODUSE project in Denmark). Here we present the results within the International Cooperation Project RER/2/005 targeted at studying the effect of local combustion processes to air quality in the village of Brzezina in the countryside north-west of Wroclaw (south western Poland). We identified the potential emission sources and quantified their contributions. The ambient aerosol monitoring (PM10 and elemental concentrations) was performed during 4 measurement cycles, in summer 2009, 2010 and in winter 2010, 2011. Some receptor modeling techniques, factor analysis-multiple linear regression analysis (FA-MLRA) and potential source localization function (PSLF), have been used. Different types of fuel burning along with domestic refuse resulted in an increased concentration of PM10 particle mass, but also by an increased in various other compounds (As, Pb, Zn). Local combustion sources contributed up to 80% to PM10 mass in winter. The effect of other sources was small, from 6 to 20%, dependently on the season. Both PM10 and elemental concentrations in the rural settlement were comparable to concentrations at urban sites in summer and were much higher in winter, which can pose asignificant health risk to its inhabitants. PMID:22629226

Correlation Between Hierarchical Bayesian and Aerosol ...

EPA Pesticide Factsheets

Tools to estimate PM2.5 mass have expanded in recent years, and now include: 1) stationary monitor readings, 2) Community Multi-Scale Air Quality (CMAQ) model estimates, 3) Hierarchical Bayesian (HB) estimates from combined stationary monitor readings and CMAQ model output; and, 4) calibrated Aerosol Optical Depth (AOD) readings from two Moderate Resolution Imaging Spetroradiometer (MODIS) units on National Aeronautics and Space Administration’s (NASA) Terra and Aqua satellites. Case-crossover design and conditional logistic regression were used to determine concentration response (CR) functions for three different PM2.5 levels on asthma emergency department (ED) visits and acute myocardial infarction (MI) inpatient hospitalizations in ninety-nine, 12 km2 grids in Baltimore, MD (2005 data). HB analyses for asthma ED visits produced significant results at 3-day lags for the main effect (OR=1.002, 95% CI=1.000-1.005), and two effect modifiers for females (OR=1.003, 95% CI=1.000-1.006), and non-Caucasian/non-African American persons (OR=1.010, 95% CI=1.001-1.019). HB analyses for acute MI inpatient hospitalizations also consistently produced a significant outcome for persons of other race (OR=1.031, 95% CI=1.006-1.056). Correlation coefficients computed between stationary monitor and satellite AOD PM2.5 values were significant for both asthma (rxy=0.944) and acute MI (rxy=0.940). Both monitor and AOD PM2.5 values were higher in February and June through Aug

Investigation of time-resolved atmospheric conditions and indoor/outdoor particulate matter concentrations in homes with gas and biomass cook stoves in Nogales, Sonora, Mexico.

PubMed

Holmes, Heather A; Pardyjak, Eric R

2014-07-01

This paper reports findings from a case study designed to investigate indoor and outdoor air quality in homes near the United States-Mexico border During the field study, size-resolved continuous particulate matter (PM) concentrations were measured in six homes, while outdoor PM was simultaneously monitored at the same location in Nogales, Sonora, Mexico, during March 14-30, 2009. The purpose of the experiment was to compare PM in homes using different fuels for cooking, gas versus biomass, and to obtain a spatial distribution of outdoor PM in a region where local sources vary significantly (e.g., highway, border crossing, unpaved roads, industry). Continuous PM data were collected every 6 seconds using a valve switching system to sample indoor and outdoor air at each home location. This paper presents the indoor PM data from each home, including the relationship between indoor and outdoor PM. The meteorological conditions associated with elevated ambient PM events in the region are also discussed. Results indicate that indoor air pollution has a strong dependence on cooking fuel, with gas stoves having hourly averaged median PM3 concentrations in the range of 134 to 157 microg m(-3) and biomass stoves 163 to 504 microg m(-1). Outdoor PM also indicates a large spatial heterogeneity due to the presence of microscale sources and meteorological influences (median PM3: 130 to 770 microg m(-3)). The former is evident in the median and range of daytime PM values (median PM3: 250 microg m(-3), maximum: 9411 microg m(-3)), while the meteorological influences appear to be dominant during nighttime periods (median PM3: 251 microg m(-3), maximum: 10,846 microg m(-3)). The atmospheric stability is quantified for three nighttime temperature inversion episodes, which were associated with an order of magnitude increase in PM10 at the regulatory monitor in Nogales, AZ (maximum increase: 12 to 474 microg m(-3)). Implications: Regulatory air quality standards are based on outdoor ambient air measurements. However, a large fraction of time is typically spent indoors where a variety of activities including cooking, heating, tobacco smoking, and cleaning can lead to elevated PM concentrations. This study investigates the influence of meteorology, outdoor PM, and indoor activities on indoor air pollution (IAP) levels in the United States-Mexico border region. Results indicate that cooking fuel type and meteorology greatly influence the IAP in homes, with biomass fuel use causing the largest increase in PM concentration.

Particle size distribution and composition in a mechanically ventilated school building during air pollution episodes.

PubMed

Parker, J L; Larson, R R; Eskelson, E; Wood, E M; Veranth, J M

2008-10-01

Particle count-based size distribution and PM(2.5) mass were monitored inside and outside an elementary school in Salt Lake City (UT, USA) during the winter atmospheric inversion season. The site is influenced by urban traffic and the airshed is subject to periods of high PM(2.5) concentration that is mainly submicron ammonium and nitrate. The school building has mechanical ventilation with filtration and variable-volume makeup air. Comparison of the indoor and outdoor particle size distribution on the five cleanest and five most polluted school days during the study showed that the ambient submicron particulate matter (PM) penetrated the building, but indoor concentrations were about one-eighth of outdoor levels. The indoor:outdoor PM(2.5) mass ratio averaged 0.12 and particle number ratio for sizes smaller than 1 microm averaged 0.13. The indoor submicron particle count and indoor PM(2.5) mass increased slightly during pollution episodes but remained well below outdoor levels. When the building was occupied the indoor coarse particle count was much higher than ambient levels. These results contribute to understanding the relationship between ambient monitoring station data and the actual human exposure inside institutional buildings. The study confirms that staying inside a mechanically ventilated building reduces exposure to outdoor submicron particles. This study supports the premise that remaining inside buildings during particulate matter (PM) pollution episodes reduces exposure to submicron PM. New data on a mechanically ventilated institutional building supplements similar studies made in residences.

Validation of Satellite AOD Data with the Ground PM10 Data over Islamabad Pakistan

NASA Astrophysics Data System (ADS)

Bulbul, Gufran; Shahid, Imran

2016-07-01

Introduction The issue of air pollution affects the entire globe, but the countries having huge urban growth and industries are specially confronted with high amounts of suspended particles in atmosphere. According to WHO, for the areas where air pollution is monitored in Pakistan, the air pollution is deteriorating the air quality as time is passing. Pakistan, during the last decade, has seen an extensive rise in population growth, urbanization, and industrialization, together with a great increase in motorization and energy use. As a result, rise has taken place in the emission of various air pollutants. However, due to the lack of air quality management, the country is suffering from deterioration of air quality. From the air quality point of view, spatial and temporal distribution of aerosols and its variations are very important. The variations in the atmospheric aerosol, land surface properties, greenhouse gases, solar radiations and climatic changes alter the energy balance of the earth's atmospheric system. The addition of aerosol particles to the atmosphere is not only dependent upon the anthropogenic sources but these are also formed by physical and chemical atmospheric processes. Aerosols are a mixture of particles and these are characterized by their shape, their size (from nanometers (nm) to micrometers (µm) in radius) and their chemical composition. PM10 is the designation for particulate matter in the atmosphere that has an aerodynamic diameter of 10µm or less. The sources of PM10 may be natural (volcanoes, dust, storms, forest and grassland fires, living vegetation, or anthropogenic (burning of fossil fuels in vehicles, power plants and industrialization). The current interest in atmospheric particulate matter (PM10) is mainly due to its effect on human health and its role in climate change. Therefore, the particulate matter must be monitored continuously to understand their likely impact on the atmosphere, environment and particularly human health. In this study, concentrations of PM10 will be monitored at different sites in H-12 sector and Kashmir Highway Islamabad using High volume air sampler and its chemical characterization will be done using Energy Dispersive XRF. The first application of satellite remote sensing for aerosol monitoring began in the mid-1970s to detect the desert particles above the ocean using data from Landsat, GOES, and AVHRR remote sensing satellites. Maps of Aerosol Optical Depth (AOD) over the ocean were produced using the 0.63 µm channel of Advanced Very High Resolution Radiometer (AVHRR) . Aerosols properties were retrieved using AVHRR. The useable range of wavelengths of spectrum (shorter wavelengths and the longer wavelengths) for the remote sensing of the aerosols particles is mostly restricted due to ozone and gaseous absorptions. The purpose of the study is to validate the satellite Aerosol Optical Depth (AOD) data for the regional and local scale for Pakistan Objectives • To quantify the concentration of PM10 • To investigate their elemental composition • To find out their possible sources • Validation with MODIS satellite AOD Methodology: PM10 concentration will be measured at different sites of NUST Islamabad, Pakistan using High volume air sampler an Air sampling equipment capable of sampling high volumes of air (typically 57,000 ft3 or 1,600 m3) at high flow rates (typically 1.13 m3/min or 40 ft3/min) over an extended sampling duration (typically 24 hrs). The sampling period will be of 24 hours. Particles in the PM10 size range are then collected on the filter(s) during the specified 24-h sampling period. Each sample filter will be weighed before and after sampling to determine the net weight (mass) gain of the collected PM10 sample (40 CFR Part 50, Appendix M, US EPA). Next step will be the chemical characterization. Element concentrations will be determined by energy dispersive X-ray fluorescence (ED-XRF) technique. The ED-XRF system uses an X-ray tube to excite the sample - which is located in a vacuum chamber - and a high-resolution semiconductor detector to measure the characteristic X-lines emitted by the sample. Comparison with Satellite AOD MODIS data The AOD data from Terra- MODIS was used to compare and generate a good relationship between ground PM10 data with satellite AOD data. The data of specific days (in accordance to ground sampling) from MODIS website was downloaded. The data was processed and mask by using Arc-GIS tool. All MODIS data were downloaded from the NASA Earth Observatory, NEO web site allowed queries of the spatial, temporal, spectral characteristics and conversion of the data to GeoTiFF format.

Effects of thoracic and fine PM and their components on heart rate and pulmonary function in COPD patients.

PubMed

Hsu, Sha O-I; Ito, Kazuhiko; Lippmann, Morton

2011-01-01

Population-based personal exposures to particulate matter (PM) and personal-ambient relationships of PM and component concentrations for outpatients with COPD and/or asthma were investigated in New York City (NYC) and Seattle for thoracic PM (PM(10)) and fine PM (PM(2.5)). Measurements of outdoor, indoor, and personal PM(10) and PM(2.5) concentrations were made concurrently for 12-consecutive days at 24 patients' residences. Filters were analyzed for elemental components, using XRF and black carbon (BC), by reflectance. Daily morning and evening measurements of heart rate (HR) and blood oxygen saturation (SpO(2)) by pulse oximeter, and forced expiratory volume in 1 s (FEV(1)) and peak expiratory flowrate (PEF) by spirometry were also measured, and symptom data were collected. Central monitoring site, outdoor, indoor, and personal concentration-response relationships of PM(2.5), PM(10-2.5), and their components were examined using mixed-effect models. The relatively small sample size of the study limited the interpretation of results, but of the PM chemical components examined, only nickel concentrations showed consistent associations, and only with HR in the NYC COPD patients.

Feasibility of Measuring Tobacco Smoke Air Pollution in Homes: Report from a Pilot Study

PubMed Central

Rosen, Laura; Zucker, David; Hovell, Melbourne; Brown, Nili; Ram, Amit; Myers, Vicki

2015-01-01

Tobacco smoke air pollution (TSAP) measurement may persuade parents to adopt smoke-free homes and thereby reduce harm to children from tobacco smoke in the home. In a pilot study involving 29 smoking families, a Sidepak was used to continuously monitor home PM2.5 during an 8-h period, Sidepak and/or Dylos monitors provided real-time feedback, and passive nicotine monitors were used to measure home air nicotine for one week. Feedback was provided to participants in the context of motivational interviews. Home PM2.5 levels recorded by continuous monitoring were not well-accepted by participants because of the noise level. Also, graphs from continuous monitoring showed unexplained peaks, often associated with sources unrelated to indoor smoking, such as cooking, construction, or outdoor sources. This hampered delivery of a persuasive message about the relationship between home smoking and TSAP. By contrast, immediate real-time PM2.5 feedback (with Sidepak or Dylos monitor) was feasible and provided unambiguous information; the Dylos had the additional advantages of being more economical and quieter. Air nicotine sampling was complicated by the time-lag for feedback and questions regarding shelf-life. Improvement in the science of TSAP measurement in the home environment is needed to encourage and help maintain smoke-free homes and protect vulnerable children. Recent advances in the use of mobile devices for real-time feedback are promising and warrant further development, as do accurate methods for real-time air nicotine air monitoring. PMID:26633440

Comparison of exposure estimation methods for air pollutants: ambient monitoring data and regional air quality simulation.

PubMed

Bravo, Mercedes A; Fuentes, Montserrat; Zhang, Yang; Burr, Michael J; Bell, Michelle L

2012-07-01

Air quality modeling could potentially improve exposure estimates for use in epidemiological studies. We investigated this application of air quality modeling by estimating location-specific (point) and spatially-aggregated (county level) exposure concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM(2.5)) and ozone (O(3)) for the eastern U.S. in 2002 using the Community Multi-scale Air Quality (CMAQ) modeling system and a traditional approach using ambient monitors. The monitoring approach produced estimates for 370 and 454 counties for PM(2.5) and O(3), respectively. Modeled estimates included 1861 counties, covering 50% more population. The population uncovered by monitors differed from those near monitors (e.g., urbanicity, race, education, age, unemployment, income, modeled pollutant levels). CMAQ overestimated O(3) (annual normalized mean bias=4.30%), while modeled PM(2.5) had an annual normalized mean bias of -2.09%, although bias varied seasonally, from 32% in November to -27% in July. Epidemiology may benefit from air quality modeling, with improved spatial and temporal resolution and the ability to study populations far from monitors that may differ from those near monitors. However, model performance varied by measure of performance, season, and location. Thus, the appropriateness of using such modeled exposures in health studies depends on the pollutant and metric of concern, acceptable level of uncertainty, population of interest, study design, and other factors. Copyright © 2012 Elsevier Inc. All rights reserved.

Investigation of air pollution of Shanghai subway stations in ventilation seasons in terms of PM2.5 and PM10.

PubMed

Guo, Erbao; Shen, Henggen; He, Lei; Zhang, Jiawen

2017-07-01

In November 2015, the PM 2.5 and PM 10 particulate matter (PM) levels in platforms, station halls, and rail areas of the Shangcheng and Jiashan Road Station were monitored to investigate air pollution in the Shanghai subway system. The results revealed that in subway stations, PM 2.5 and PM 10 concentrations were significantly higher than those in outdoor environments. In addition, particle concentrations in the platforms exceeded maximum levels that domestic safety standards allowed. Particularly on clear days, PM 2.5 and PM 10 concentrations in platforms were significantly higher than maximum standards levels. Owing to the piston effect, consistent time-varying trends were exhibited by PM 2.5 concentrations in platforms, station halls, and rail areas. Platform particle concentrations were higher than the amount in station halls, and they were higher on clear days than on rainy days. The time-varying trends of PM 10 and PM 2.5 concentrations in platforms and station halls were similar to each other. Activities within the station led to most of the inhalable particles within the station area. The mass concentration ratios of PM 2.5 and PM 10 in platforms were within 0.65-0.93, and fine particles were the dominant components.

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

RECRUITING AND RETAINING AFRICAN-AMERICANS FOR AN EXPOSURE STUDY IN SOUTHEAST RALEIGH

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) recently completed a study of African-Americans' exposure to particulate matter (PM) in Southeast Raleigh. A primary goal was to compare PM levels measured at ambient and residential sites with those from personal exposure monitors...

INDOOR AND OUTDOOR PM10 AND ASSOCIATED METALS AND PESTICIDES IN ARIZONA

EPA Science Inventory

The National Human Exposure Assessment Survey study in Arizona (AZ NHEXAS) sampled trace metals in multimedia in and outside of 176 representative homes in Arizona. PM10 was collected using low-flow impactors indoors and out. Primary metals evaluated from monitoring of indoor...

( DETROIT, MI ) STUDY DESIGN AND PRELIMINARY EXPOSURE FINDINGS ASSOCIATED WITH THE DEARS

EPA Science Inventory

The Detroit Exposure and Aerosol Research Study (DEARS) is a three-year field monitoring study initiated in 2004 that is designed to measure exposure and describe exposure relationships for air toxics, PM components, PM from specific sources, and criteria pollutants. Detroit, Mic...

Fine Particulate Matter and Cardiovascular Disease: Comparison of Assessment Methods for Long-term Exposure

EPA Science Inventory

Background Adverse cardiovascular events have been linked with PM2.5 exposure obtained primarily from air quality monitors, which rarely co-locate with participant residences. Modeled PM2.5 predictions at finer resolution may more accurately predict residential exposure; however...

Method to Select Metropolitan Areas of Epidemiologic Interest for Enhanced Air Quality Monitoring

EPA Science Inventory

The U.S. Environmental Protection Agency’s current Speciation Trends Network (STN) covers most major U.S. metropolitan areas and a wide range of particulate matter (PM) constituents and gaseous co-pollutants. However, using filter-based methods, most PM constituents are measured ...

40 CFR 53.52 - Leak check test.

Code of Federal Regulations, 2014 CFR

2014-07-01

... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance Characteristics of Reference Methods and Class I and Class II Equivalent Methods for PM 2.5 or PM 10-2.5 § 53.52... to include the facility, including components, instruments, operator controls, a written procedure...

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.

Evaluation of physical dimension changes as nondestructive measurements for monitoring rigor mortis development in broiler muscles.

PubMed

Cavitt, L C; Sams, A R

2003-07-01

Studies were conducted to develop a non-destructive method for monitoring the rate of rigor mortis development in poultry and to evaluate the effectiveness of electrical stimulation (ES). In the first study, 36 male broilers in each of two trials were processed at 7 wk of age. After being bled, half of the birds received electrical stimulation (400 to 450 V, 400 to 450 mA, for seven pulses of 2 s on and 1 s off), and the other half were designated as controls. At 0.25 and 1.5 h postmortem (PM), carcasses were evaluated for the angles of the shoulder, elbow, and wing tip and the distance between the elbows. Breast fillets were harvested at 1.5 h PM (after chilling) from all carcasses. Fillet samples were excised and frozen for later measurement of pH and R-value, and the remainder of each fillet was held on ice until 24 h postmortem. Shear value and pH means were significantly lower, but R-value means were higher (P < 0.05) for the ES fillets compared to the controls, suggesting acceleration of rigor mortis by ES. The physical dimensions of the shoulder and elbow changed (P < 0.05) during rigor mortis development and with ES. These results indicate that physical measurements of the wings maybe useful as a nondestructive indicator of rigor development and for monitoring the effectiveness of ES. In the second study, 60 male broilers in each of two trials were processed at 7 wk of age. At 0.25, 1.5, 3.0, and 6.0 h PM, carcasses were evaluated for the distance between the elbows. At each time point, breast fillets were harvested from each carcass. Fillet samples were excised and frozen for later measurement of pH and sacromere length, whereas the remainder of each fillet was held on ice until 24 h PM. Shear value and pH means (P < 0.05) decreased, whereas sarcomere length means (P < 0.05) increased over time, indicating rigor mortis development. Elbow distance decreased (P < 0.05) with rigor development and was correlated (P < 0.01) with shear value (r = 0.2581), sarcomere length (r = -0.3079), and pH (r = 0.6303). These results suggest that elbow distance could be used in conjunction with other detection methods for optically automating measurement of rigor mortis development in broiler carcasses.

Water soluble aerosols and gases at a UK background site - Part 1: Controls of PM2.5 and PM10 aerosol composition

NASA Astrophysics Data System (ADS)

Twigg, M. M.; Di Marco, C. F.; Leeson, S.; van Dijk, N.; Jones, M. R.; Leith, I. D.; Morrison, E.; Coyle, M.; Proost, R.; Peeters, A. N. M.; Lemon, E.; Frelink, T.; Braban, C. F.; Nemitz, E.; Cape, J. N.

2015-07-01

There is limited availability of long-term, high temporal resolution, chemically speciated aerosol measurements which can provide further insight into the health and environmental impacts of particulate matter. The Monitor for AeRosols and Gases (MARGA, Applikon B.V., NL) allows for the characterisation of the inorganic components of PM10 and PM_{2.5 (NH4+, NO3-, SO42-, Cl-, Na+, K+, Ca2+, Mg2+) and inorganic reactive gases (NH3, SO2, HCl, HONO and HNO3) at hourly resolution. The following study presents 6.5 years (June 2006 to December 2012) of quasi-continuous observations of PM2.5 and PM10 using the MARGA at the UK EMEP supersite, Auchencorth Moss, SE Scotland. Auchencorth Moss was found to be representative of a remote European site with average total water soluble inorganic mass of PM2.5 of 3.82 μg m-3. Anthropogenically derived secondary inorganic aerosols (sum of NH4+, NO3- and nss-SO42-) were the dominating species (63 %) of PM2.5. In terms of equivalent concentrations, NH4+ provided the single largest contribution to PM2.5 fraction in all seasons. Sea salt was the main component (73 %) of the PMcoarse fraction (PM10-PM2.5), though NO3- was also found to make a relatively large contribution to the measured mass (17 %) providing evidence of considerable processing of sea salt in the coarse mode. There was on occasions evidence of aerosol from combustion events being transported to the site in 2012 as high K+ concentrations (deviating from the known ratio in sea salt) coincided with increases in black carbon at the site. Pollution events in PM10 (defined as concentrations > 12 μg m-3) were on average dominated by NH4+ and NO3-, where smaller loadings at the site tended to be dominated by sea salt. As with other western European sites, the charge balance of the inorganic components resolved were biased towards cations, suggesting the aerosol was basic or more likely that organic acids contributed to the charge balance. This study demonstrates the UK background atmospheric composition is primarily driven by meteorology with sea salt dominating air masses from the Atlantic Ocean and the Arctic, whereas secondary inorganic aerosols tended to dominate air masses from continental Europe.}

Relative roles of emissions and meteorology in the diurnal pattern of urban PM10: analysis of the daylight saving time effect.

PubMed

Muñoz, Ricardo C

2012-06-01

Daylight saving time (DST) is a common practice in many countries, in which Official Time (OT) is abruptly shifted 1 hour with respect to solar time on two occasions every year (in fall and spring). All anthropogenic emitting processes tied to OT like job and school commuting traffic, abruptly change in this moment their timing with respect to solar time, inducing a sudden shift between emissions and the meteorological factors that control the dispersion and transport of air pollutants. Analyzing 13 years of hourly particulate matter (PM10) concentrations measured in Santiago, Chile, we demonstrate that the DST practice has observable non-trivial effects in the PM10 diurnal cycle. The clearest impact is in the morning peak of PM10 during the fall DST change, which occurs later and has on average a significant smaller magnitude in the days after the DST change as compared to the days before it. This decrease in magnitude is most remarkable because it occurs in a period of the year when overall PM10 concentrations increase due to generally worsening of the dispersion conditions. Results are shown for seven monitoring stations around the city, and for the fall and spring DST changes. They show clearly the interplay of emissions and meteorology in conditioning urban air pollution problems, highlighting the role of the morning and evening transitions of the atmospheric boundary layer in shaping the diurnal pattern of urban air pollutant concentrations.

Comparison of real-time instruments and gravimetric method when measuring particulate matter in a residential building.

PubMed

Wang, Zuocheng; Calderón, Leonardo; Patton, Allison P; Sorensen Allacci, MaryAnn; Senick, Jennifer; Wener, Richard; Andrews, Clinton J; Mainelis, Gediminas

2016-11-01

This study used several real-time and filter-based aerosol instruments to measure PM 2.5 levels in a high-rise residential green building in the Northeastern US and compared performance of those instruments. PM 2.5 24-hr average concentrations were determined using a Personal Modular Impactor (PMI) with 2.5 µm cut (SKC Inc., Eighty Four, PA) and a direct reading pDR-1500 (Thermo Scientific, Franklin, MA) as well as its filter. 1-hr average PM 2.5 concentrations were measured in the same apartments with an Aerotrak Optical Particle Counter (OPC) (model 8220, TSI, Inc., Shoreview, MN) and a DustTrak DRX mass monitor (model 8534, TSI, Inc., Shoreview, MN). OPC and DRX measurements were compared with concurrent 1-hr mass concentration from the pDR-1500. The pDR-1500 direct reading showed approximately 40% higher particle mass concentration compared to its own filter (n = 41), and 25% higher PM 2.5 mass concentration compared to the PMI 2.5 filter. The pDR-1500 direct reading and PMI 2.5 in non-smoking homes (self-reported) were not significantly different (n = 10, R 2 = 0.937), while the difference between measurements for smoking homes was 44% (n = 31, R 2 = 0.773). Both OPC and DRX data had substantial and significant systematic and proportional biases compared with pDR-1500 readings. However, these methods were highly correlated: R 2 = 0.936 for OPC versus pDR-1500 reading and R 2 = 0.863 for DRX versus pDR-1500 reading. The data suggest that accuracy of aerosol mass concentrations from direct-reading instruments in indoor environments depends on the instrument, and that correction factors can be used to reduce biases of these real-time monitors in residential green buildings with similar aerosol properties. This study used several real-time and filter-based aerosol instruments to measure PM 2.5 levels in a high-rise residential green building in the northeastern United States and compared performance of those instruments. The data show that while the use of real-time monitors is convenient for measurement of airborne PM at short time scales, the accuracy of those monitors depends on a particular instrument. Bias correction factors identified in this paper could provide guidance for other studies using direct-reading instruments to measure PM concentrations.

Local source impacts on primary and secondary aerosols in the Midwestern United States

NASA Astrophysics Data System (ADS)

Jayarathne, Thilina; Rathnayake, Chathurika M.; Stone, Elizabeth A.

2016-04-01

Atmospheric particulate matter (PM) exhibits heterogeneity in composition across urban areas, leading to poor representation of outdoor air pollutants in human exposure assessments. To examine heterogeneity in PM composition and sources across an urban area, fine particulate matter samples (PM2.5) were chemically profiled in Iowa City, IA from 25 August to 10 November 2011 at two monitoring stations. The urban site is the federal reference monitoring (FRM) station in the city center and the peri-urban site is located 8.0 km to the west on the city edge. Measurements of PM2.5 carbonaceous aerosol, inorganic ions, molecular markers for primary sources, and secondary organic aerosol (SOA) tracers were used to assess statistical differences in composition and sources across the two sites. PM2.5 mass ranged from 3 to 26 μg m-3 during this period, averaging 11.2 ± 4.9 μg m-3 (n = 71). Major components of PM2.5 at the urban site included organic carbon (OC; 22%), ammonium (14%), sulfate (13%), nitrate (7%), calcium (2.9%), and elemental carbon (EC; 2.2%). Periods of elevated PM were driven by increases in ammonium, sulfate, and SOA tracers that coincided with hot and dry conditions and southerly winds. Chemical mass balance (CMB) modeling was used to apportion OC to primary sources; biomass burning, vegetative detritus, diesel engines, and gasoline engines accounted for 28% of OC at the urban site and 24% of OC at the peri-urban site. Secondary organic carbon from isoprene and monoterpene SOA accounted for an additional 13% and 6% of OC at the urban and peri-urban sites, respectively. Differences in biogenic SOA across the two sites were associated with enhanced combustion activities in the urban area and higher aerosol acidity at the urban site. Major PM constituents (e.g., OC, ammonium, sulfate) were generally well-represented by a single monitoring station, indicating a regional source influence. Meanwhile, nitrate, biomass burning, food cooking, suspended dust, and biogenic SOA were not well-represented by a single site and demonstrated local influences. For isoprene SOA, product distributions indicated a larger role for the high-NOx pathway at the urban site. These local sources are largely responsible for differences in population exposures to outdoor PM in the study domain located within the Midwestern US.

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.

A multi-factor designation method for mapping particulate-pollution control zones in China.

PubMed

Qin, Y; Xie, S D

2011-09-01

A multi-factor designation method for mapping particulate-pollution control zones was brought out through synthetically considering PM(10) pollution status, PM(10) anthropogenic emissions, fine particle pollution, long-range transport and economic situation. According to this method, China was divided into four different particulate-pollution control regions: PM Suspended Control Region, PM(10) Pollution Control Region, PM(2.5) Pollution Control Region and PM(10) and PM(2.5) Common Control Region, which accounted for 69.55%, 9.66%, 4.67% and 16.13% of China's territory, respectively. The PM(10) and PM(2.5) Common Control Region was mainly distributed in Bohai Region, Yangtze River Delta, Pearl River Delta, eastern of Sichuan province and Chongqing municipality, calling for immediate control of both PM(10) and PM(2.5). Cost-effective control effects can be achieved through concentrating efforts on PM(10) and PM(2.5) Common Control Region to address 60.32% of national PM(10) anthropogenic emissions. Air quality in districts belonging to PM(2.5) Pollution Control Region suggested that Chinese national ambient air quality standard for PM(10) was not strict enough. The result derived from application to China proved that this approach was feasible for mapping pollution control regions for a country with vast territory, complicated pollution characteristics and limited available monitoring data. Copyright © 2011 Elsevier B.V. All rights reserved.

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

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.

Spatiotemporal prediction of fine particulate matter using high resolution satellite images in the southeastern U.S 2003–2011

PubMed Central

Lee, Mihye; Kloog, Itai; Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie; Melly, Steven; Coull, Brent; Koutrakis, Petros; Schwartz, Joel

2016-01-01

Numerous studies have demonstrated that fine particulate matter (PM2.5, particles smaller than 2.5 μm in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM2.5 to assess personal exposure; however, induces measurement error. Land use regression provides spatially resolved predictions but land use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM2.5 exposures. In this paper, we used AOD data with other PM2.5 variables such as meteorological variables, land use regression, and spatial smoothing to predict daily concentrations of PM2.5 at a 1 km2 resolution of the southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 through 2011. We divided the study area into 3 regions and applied separate mixed-effect models to calibrate AOD using ground PM2.5 measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors (RMSPE) of 2.89, 2.51, and 2.82 μg/m3 for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM2.5 concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM2.5. Our model results will also extend the existing studies on PM2.5 which have mostly focused on urban areas due to the paucity of monitors in rural areas. PMID:26082149

Spatiotemporal Prediction of Fine Particulate Matter Using High-Resolution Satellite Images in the Southeastern US 2003-2011

NASA Technical Reports Server (NTRS)

Lee, Mihye; Kloog, Itai; Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie; Melly, Steven; Coull, Brent; Koutrakis, Petros; Schwartz, Joel

2016-01-01

Numerous studies have demonstrated that fine particulate matter (PM(sub 2.5), particles smaller than 2.5 micrometers in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM(sub 2.5) to assess personal exposure, however, induces measurement error. Land-use regression provides spatially resolved predictions but land-use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM(sub 2.5) exposures. In this paper, we used AOD data with other PM(sub 2.5) variables, such as meteorological variables, land-use regression, and spatial smoothing to predict daily concentrations of PM(sub 2.5) at a 1 sq km resolution of the Southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 to 2011. We divided the study area into three regions and applied separate mixed-effect models to calibrate AOD using ground PM(sub 2.5) measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors of 2.89, 2.51, and 2.82 cu micrograms for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM(sub 2.5) concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM(sub 2.5). Our model results will also extend the existing studies on PM(sub 2.5) which have mostly focused on urban areas because of the paucity of monitors in rural areas.

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.

Levels of outdoor PM 2.5, absorbance and sulphur as surrogates for personal exposures among post-myocardial infarction patients in Barcelona, Spain

NASA Astrophysics Data System (ADS)

Jacquemin, Bénédicte; Lanki, Timo; Sunyer, Jordi; Cabrera, Laia; Querol, Xavier; Bellander, Tom; Moreno, Natalia; Peters, Annette; Pey, Jorge; Pekkanen, Juha

Outdoor levels of fine particles (PM 2.5; particles <2.5 μm) have been associated with cardiovascular health. Persons with existing cardiovascular disease have been suggested to be especially vulnerable. It is unclear, how well outdoor concentrations of PM 2.5 and its constituents measured at a central site reflect personal exposures in Southern European countries. The objective of the study was to assess the relationship between outdoor and personal concentrations of PM 2.5, absorbance and sulphur among post-myocardial infarction patients in Barcelona, Spain. Thirty-eight subjects carried personal PM 2.5 monitors for 24-h once a month (2-6 repeated measurements) between November 2003 and June 2004. PM 2.5 was measured also at a central outdoor monitoring site. Light absorbance (a proxy for elemental carbon) and sulphur content of filter samples were determined as markers of combustion originating and long-range transported PM 2.5, respectively. There were 110, 162 and 88 measurements of PM 2.5, absorbance and sulphur, respectively. Levels of outdoor PM 2.5 (median 17 μg m 3) were lower than personal PM 2.5 even after excluding days with exposure to environmental tobacco smoke (ETS) (median after exclusion 27 μg m 3). However, outdoor concentrations of absorbance and sulphur were similar to personal concentrations after exclusion of ETS. When repeated measurements were taken into account, there was a statistically significant association between personal and outdoor absorbance when adjusting for ETS (slope 0.66, p<0.001), but for PM 2.5 the association was weaker (slope 0.51, p=0.066). Adjustment for ETS had little effect on the respective association of S (slope 0.69, p<0.001). Our results suggest that outdoor measurements of absorbance and sulphur can be used to estimate both the daily variation and levels of personal exposures also in Southern European countries, especially when exposure to ETS has been taken into account. For PM 2.5, indoor sources need to be carefully considered.

Summary and analysis of approaches linking visual range, PM2.5 concentrations, and air quality health impact indices for wildfires.

PubMed

O'Neill, Susan M; Lahm, Peter W; Fitch, Mark J; Broughton, Mike

2013-09-01

Several U.S. state and tribal agencies and other countries have implemented a methodology developed in the arid intermountain western U.S. where short-term (1- to 3-hr) particulate matter (PM) with aerodynamic diameters less than 2.5 microm (PM2.5) concentrations are estimated from an observed visual range (VR) measurement. This PM2.5 concentration estimate is then linked to a public health warning scale to inform the public about potential health impacts from smoke from wildfire. This methodology is often used where monitoring data do not exist (such as many rural areas). This work summarizes the various approaches, highlights the potential for wildfire smoke impact messaging conflicts at state and international borders, and highlights the need to define consistent short-term health impact category breakpoint categories. Is air quality "unhealthy" when 1- to 3-hr PM2.5 is > or = 139 microg/m3 as specified in the Wildfire Smoke, A Guide for Public Health Officials? Or is air quality unhealthy when 1- to 3-hr PM2.5 is > or = 88.6 microg/m3 as specified in the Montana categorizations? This work then examines the relationship between visual range and PM2.5 concentrations using data from the Interagency Monitoring of PROtected Visual Environments (IMPROVE) program and the IMPROVE extinction coefficient (beta ext) equation to simulate an atmosphere dominated by smoke for sites in the arid intermountain western U.S. and great plains. This was accomplished by rearranging the beta ext equation to solve for organic mass as a function of VR. The results show that PM2.5 and VR are related by PM2.5 = 622 * VR(-0.98) with a correlation of 0.99 and that at low VR values (<10 km) a small change in VR results in a large change in PM2.5 concentrations. The results also show that relative humidity and the presence of hygroscopic pollutants from sources other than fire can change the VR/PM2.5 relationships, especially at PM2.5 concentrations less than approximately 90 microg/m3.

The impact of infield biomass burning on PM levels and its chemical composition.

PubMed

Dambruoso, P; de Gennaro, G; Di Gilio, A; Palmisani, J; Tutino, M

2014-12-01

In the South of Italy, it is common for farmers to burn pruning waste from olive trees in spring. In order to evaluate the impact of the biomass burning source on the physical and chemical characteristics of the particulate matter (PM) emitted by these fires, a PM monitoring campaign was carried out in an olive grove. Daily PM10 samples were collected for 1 week, when there were no open fires, and when biomass was being burned, and at two different distances from the fires. Moreover, an optical particle counter and a polycyclic aromatic hydrocarbon (PAH) analyzer were used to measure the high time-resolved dimensional distribution of particles emitted and total PAHs concentrations, respectively. Chemical analysis of PM10 samples identified organic and inorganic components such as PAHs, ions, elements, and carbonaceous fractions (OC, EC). Analysis of the collected data showed the usefulness of organic and inorganic tracer species and of PAH diagnostic ratios for interpreting the impact of biomass fires on PM levels and on its chemical composition. Finally, high time-resolved monitoring of particle numbers and PAH concentrations was performed before, during, and after biomass burning, and these concentrations were seen to be very dependent on factors such as weather conditions, combustion efficiency, and temperature (smoldering versus flaming conditions), and moisture content of the wood burned.

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.

PM10 and gaseous pollutants trends from air quality monitoring networks in Bari province: principal component analysis and absolute principal component scores on a two years and half data set

PubMed Central

2014-01-01

Background The chemical composition of aerosols and particle size distributions are the most significant factors affecting air quality. In particular, the exposure to finer particles can cause short and long-term effects on human health. In the present paper PM10 (particulate matter with aerodynamic diameter lower than 10 μm), CO, NOx (NO and NO2), Benzene and Toluene trends monitored in six monitoring stations of Bari province are shown. The data set used was composed by bi-hourly means for all parameters (12 bi-hourly means per day for each parameter) and it’s referred to the period of time from January 2005 and May 2007. The main aim of the paper is to provide a clear illustration of how large data sets from monitoring stations can give information about the number and nature of the pollutant sources, and mainly to assess the contribution of the traffic source to PM10 concentration level by using multivariate statistical techniques such as Principal Component Analysis (PCA) and Absolute Principal Component Scores (APCS). Results Comparing the night and day mean concentrations (per day) for each parameter it has been pointed out that there is a different night and day behavior for some parameters such as CO, Benzene and Toluene than PM10. This suggests that CO, Benzene and Toluene concentrations are mainly connected with transport systems, whereas PM10 is mostly influenced by different factors. The statistical techniques identified three recurrent sources, associated with vehicular traffic and particulate transport, covering over 90% of variance. The contemporaneous analysis of gas and PM10 has allowed underlining the differences between the sources of these pollutants. Conclusions The analysis of the pollutant trends from large data set and the application of multivariate statistical techniques such as PCA and APCS can give useful information about air quality and pollutant’s sources. These knowledge can provide useful advices to environmental policies in order to reach the WHO recommended levels. PMID:24555534

Using Advanced Monitoring Tools to Evaluate PM PM2.5 2.5 in San Joaquin Valley

EPA Science Inventory

One of the primary data deficiencies that prevent the advance of policy relevant research on particulate matter, ozone, and associated precursors is the lack of measurement data and knowledge on the true vertical profile and synoptic-scale spatial distributions of the pollutants....

SEASONAL ABUNDANCE OF ORGANIC MOLECULAR MARKERS IN URBAN PARTICULATE MATTER FROM PHILADELPHIA, PA

EPA Science Inventory

Organic molecular markers were measured in airborne particulate matter (PM₁₀) from the City of Philadelphia North Broad Street air quality monitoring site to identify the seasonal abundances of key tracer compounds together with their dominant sources. Daily PM_10...

Association Between Satellite-based Estimates of Long-term PM2.5 Exposure and Coronary Artery Disease

EPA Science Inventory

Background: Epidemiological studies have identified associations between long-term PM2.5 exposure and cardiovascular events, though most have relied on concentrations from central-site air quality monitors. Methods: We utilized a cohort of 5679 patients who had undergone cardiac ...

PM 2.5 CHEMICAL SPECIATION SAMPLER EVALUATION FIELD PROGRAM: RESULTS FROM THE FOUR CITY STUDY

EPA Science Inventory

The objective of this sampler intercomparison field study is to determine the performance characteristics for the collection of the chemical components of PM2.5 by the chemical speciation monitors developed for the national network relative to each other, to the Federal Referen...

INTEGRATING LIDAR AND SATELLITE OPTICAL DEPTH WITH AMBIENT MONITORING FOR 3-DIMENSIONAL PARTICULATE CHARACTERIZATION

EPA Science Inventory

A combination of in-situ PM2.5, sunphotometers, upward pointing lidar and satellite aerosol optical depth (AOD) instruments have been employed to better understand variability in the correlation between AOD and PM2.5 at the surface. Previous studies have shown good correlation be...

DEVELOPMENT OF A CONTINUOUS MONITORING SYSTEM FOR PM10 AND COMPONENTS OF PM2.5. (R825305)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

40 CFR 53.52 - Leak check test.

Code of Federal Regulations, 2011 CFR

2011-07-01

... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance Characteristics of Reference Methods and Class I and Class II Equivalent Methods for PM2.5 or PM10â2.5 § 53.52... to include the facility, including components, instruments, operator controls, a written procedure...

40 CFR 53.52 - Leak check test.

Code of Federal Regulations, 2012 CFR

2012-07-01

... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance Characteristics of Reference Methods and Class I and Class II Equivalent Methods for PM2.5 or PM10â2.5 § 53.52... to include the facility, including components, instruments, operator controls, a written procedure...

40 CFR 53.52 - Leak check test.

Code of Federal Regulations, 2010 CFR

2010-07-01

... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance Characteristics of Reference Methods and Class I and Class II Equivalent Methods for PM2.5 or PM10â2.5 § 53.52... to include the facility, including components, instruments, operator controls, a written procedure...

Influence of exposure differences on city-to-city heterogeneity in PM2.5-mortality associations in US cities

EPA Science Inventory

Multi-city population-based epidemiological studies have observed heterogeneity between city-specific fine particulate matter (PM2.5)-mortality effect estimates. These studies typically use ambient monitoring data as a surrogate for exposure leading to potential exposure misclass...

Spatial distribution of particulate matter (PM10 and PM2.5) in Seoul Metropolitan Subway stations.

PubMed

Kim, Ki Youn; Kim, Yoon Shin; Roh, Young Man; Lee, Cheol Min; Kim, Chi Nyon

2008-06-15

The aims of this study are to examine the concentrations of PM10 and PM2.5 in areas within the Seoul Metropolitan Subway network and to provide fundamental data in order to protect respiratory health of subway workers and passengers from air pollutants. A total of 22 subway stations located on lines 1-4 were selected based on subway official's guidance. At these stations both subway worker areas (station offices, rest areas, ticket offices and driver compartments) and passengers areas (station precincts, subway carriages and platforms) were the sites used for measuring the levels of PM. The mean concentrations of PM10 and PM2.5 were relatively higher on platforms, inside subway carriages and in driver compartments than in the other areas monitored. The levels of PM10 and PM2.5 for station precincts and platforms exceeded the 24-h acceptable threshold limits of 150 microg/m3 for PM10 and 35 microg/m3 for PM2.5, which are regulated by the U.S. Environmental Protection Agency (EPA). However, levels measured in station and ticket offices fell below the respective threshold. The mean PM10 and PM2.5 concentrations on platforms located underground were significantly higher than those at ground level (p<0.05).

Indoor/outdoor relationships of PM10, PM2.5, and PM1 mass concentrations and their water-soluble ions in a retirement home and a school dormitory

NASA Astrophysics Data System (ADS)

Hassanvand, Mohammad Sadegh; Naddafi, Kazem; Faridi, Sasan; Arhami, Mohammad; Nabizadeh, Ramin; Sowlat, Mohammad Hossein; Pourpak, Zahra; Rastkari, Noushin; Momeniha, Fatemeh; Kashani, Homa; Gholampour, Akbar; Nazmara, Shahrokh; Alimohammadi, Mahmood; Goudarzi, Gholamreza; Yunesian, Masud

2014-01-01

Indoor/outdoor particulate matter (PM10, PM2.5, and PM1) and their water-soluble ions were measured in a retirement home and a school dormitory in Tehran, from May 2012 to January 2013. Hourly indoor/outdoor PM concentrations were measured using GRIMM dust monitors and 24-h aerosol samples were collected by low-volume air samplers. Water-soluble ions were determined using an ion chromatography (IC) instrument. Although the mean outdoor PM concentrations in both sampling sites were almost equal, the mean indoor PM10 in the school dormitory was approximately 1.35 times higher than that in the retirement home. During a Middle Eastern dust storm, the 24-h average PM10, PM2.5, and PM1 concentrations were respectively 3.4, 2.9, and 1.9 times as high as those in normal days outdoors and 3.4, 2.8, and 1.6 times indoors. The results indicated that secondary inorganic aerosols were the dominant water-soluble ions of indoor and outdoor PM. We found that the smaller the particle, the higher the percentage of secondary inorganic aerosols. Except for PM10 in the school dormitory, strong correlations were found between indoor and outdoor PM. We estimated that nearly 45% of PM10, 67% of PM2.5, and 79% of PM1 in the retirement home, and 32% of PM10, 76% of PM2.5, and 83% of PM1 in the school dormitory originated from outdoor environment.

Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework

PubMed Central

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-01-01

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859

Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (WSN) framework.

PubMed

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-11-27

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.

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 10, PM 2.5 and PM 1.0—Emissions from industrial plants—Results from measurement programmes in Germany

NASA Astrophysics Data System (ADS)

Ehrlich, C.; Noll, G.; Kalkoff, W.-D.; Baumbach, G.; Dreiseidler, A.

Emission measurement programmes were carried out at industrial plants in several regions of Germany to determine the fine dust in the waste gases; the PM 10, PM 2.5 and PM 1.0 fractions were sampled using a cascade impactor technique. The installations tested included plants used for: combustion (brown coal, heavy fuel oil, wood), cement production, glass production, asphalt mixing, and processing plants for natural stones and sand, ceramics, metallurgy, chemical production, spray painting, wood processing/chip drying, poultry farming and waste treatment. In addition waste gas samples were taken from small-scale combustion units, like domestic stoves, firing lignite briquettes or wood. In total 303 individual measurement results were obtained during 106 different measurement campaigns. In the study it was found that in more than 70% of the individual emission measurement results from industrial plants and domestic stoves the PM 10 portion amounted to more than 90% and the PM 2.5 portion between 50% and 90% of the total PM (particulate matter) emission. For thermal industrial processes the PM 1.0 portion constituted between 20% and 60% of the total PM emission. Typical particle size distributions for different processes were presented as cumulative frequency distributions and as frequency distributions. The particle size distributions determined for the different plant types show interesting similarities and differences depending on whether the processes are thermal, mechanical, chemical or mixed. Consequently, for the groups of plant investigated, a major finding of this study has been that the particle size distribution is a characteristic of the industrial process. Attempts to correlate particle size distributions of different plants to different gas cleaning technologies did not lead to usable results.

Calibrating MODIS aerosol optical depth for predicting daily PM2.5 concentrations via statistical downscaling

PubMed Central

Chang, Howard H.; Hu, Xuefei; Liu, Yang

2014-01-01

There has been a growing interest in the use of satellite-retrieved aerosol optical depth (AOD) to estimate ambient concentrations of PM2.5 (particulate matter <2.5 μm in aerodynamic diameter). With their broad spatial coverage, satellite data can increase the spatial–temporal availability of air quality data beyond ground monitoring measurements and potentially improve exposure assessment for population-based health studies. This paper describes a statistical downscaling approach that brings together (1) recent advances in PM2.5 land use regression models utilizing AOD and (2) statistical data fusion techniques for combining air quality data sets that have different spatial resolutions. Statistical downscaling assumes the associations between AOD and PM2.5 concentrations to be spatially and temporally dependent and offers two key advantages. First, it enables us to use gridded AOD data to predict PM2.5 concentrations at spatial point locations. Second, the unified hierarchical framework provides straightforward uncertainty quantification in the predicted PM2.5 concentrations. The proposed methodology is applied to a data set of daily AOD values in southeastern United States during the period 2003–2005. Via cross-validation experiments, our model had an out-of-sample prediction R2 of 0.78 and a root mean-squared error (RMSE) of 3.61 μg/m3 between observed and predicted daily PM2.5 concentrations. This corresponds to a 10% decrease in RMSE compared with the same land use regression model without AOD as a predictor. Prediction performances of spatial–temporal interpolations to locations and on days without monitoring PM2.5 measurements were also examined. PMID:24368510

Calibrating MODIS aerosol optical depth for predicting daily PM2.5 concentrations via statistical downscaling.

PubMed

Chang, Howard H; Hu, Xuefei; Liu, Yang

2014-07-01

There has been a growing interest in the use of satellite-retrieved aerosol optical depth (AOD) to estimate ambient concentrations of PM2.5 (particulate matter <2.5 μm in aerodynamic diameter). With their broad spatial coverage, satellite data can increase the spatial-temporal availability of air quality data beyond ground monitoring measurements and potentially improve exposure assessment for population-based health studies. This paper describes a statistical downscaling approach that brings together (1) recent advances in PM2.5 land use regression models utilizing AOD and (2) statistical data fusion techniques for combining air quality data sets that have different spatial resolutions. Statistical downscaling assumes the associations between AOD and PM2.5 concentrations to be spatially and temporally dependent and offers two key advantages. First, it enables us to use gridded AOD data to predict PM2.5 concentrations at spatial point locations. Second, the unified hierarchical framework provides straightforward uncertainty quantification in the predicted PM2.5 concentrations. The proposed methodology is applied to a data set of daily AOD values in southeastern United States during the period 2003-2005. Via cross-validation experiments, our model had an out-of-sample prediction R(2) of 0.78 and a root mean-squared error (RMSE) of 3.61 μg/m(3) between observed and predicted daily PM2.5 concentrations. This corresponds to a 10% decrease in RMSE compared with the same land use regression model without AOD as a predictor. Prediction performances of spatial-temporal interpolations to locations and on days without monitoring PM2.5 measurements were also examined.

Integrating genomics into clinical oncology: ethical and social challenges from proponents of personalized medicine.

PubMed

McGowan, Michelle L; Settersten, Richard A; Juengst, Eric T; Fishman, Jennifer R

2014-02-01

The use of molecular tools to individualize health care, predict appropriate therapies, and prevent adverse health outcomes has gained significant traction in the field of oncology under the banner of "personalized medicine" (PM). Enthusiasm for PM in oncology has been fueled by success stories of targeted treatments for a variety of cancers based on their molecular profiles. Though these are clear indications of optimism for PM, little is known about the ethical and social implications of personalized approaches in clinical oncology. The objective of this study is to assess how a range of stakeholders engaged in promoting, monitoring, and providing PM understand the challenges of integrating genomic testing and targeted therapies into clinical oncology. The study involved the analysis of in-depth interviews with 117 stakeholders whose experiences and perspectives on PM span a wide variety of institutional and professional settings. Despite their considerable enthusiasm for this shift, promoters, monitors, and providers of PM identified 4 domains that provoke heightened ethical and social concerns: (1) informed consent for cancer genomic testing, (2) privacy, confidentiality, and disclosure of genomic test results, (3) access to genomic testing and targeted therapies in oncology, and (4) the costs of scaling up pharmacogenomic testing and targeted cancer therapies. These specific concerns are not unique to oncology, or even genomics. However, those most invested in the success of PM view oncologists' responses to these challenges as precedent setting because oncology is farther along the path of clinical integration of genomic technologies than other fields of medicine. This study illustrates that the rapid emergence of PM approaches in clinical oncology provides a crucial lens for identifying and managing potential frictions and pitfalls that emerge as health care paradigms shift in these directions. © 2014 Published by Elsevier Inc.

[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.

Pilot Intervention Study of Household Ventilation and Fine Particulate Matter Concentrations in a Low-Income Urban Area, Dhaka, Bangladesh.

PubMed

Weaver, Anne M; Parveen, Shahana; Goswami, Doli; Crabtree-Ide, Christina; Rudra, Carole; Yu, Jihnhee; Mu, Lina; Fry, Alicia M; Sharmin, Iffat; Luby, Stephen P; Ram, Pavani K

2017-08-01

Fine particulate matter (PM 2.5 ) is a risk factor for pneumonia; ventilation may be protective. We tested behavioral and structural ventilation interventions on indoor PM 2.5 in Dhaka, Bangladesh. We recruited 59 good ventilation (window or door in ≥ 3 walls) and 29 poor ventilation (no window, one door) homes. We monitored baseline indoor and outdoor PM 2.5 for 48 hours. We asked all participants to increase ventilation behavior, including opening windows and doors, and operating fans. Where permitted, we installed windows in nine poor ventilation homes, then repeated PM 2.5 monitoring. We estimated effects using linear mixed-effects models and conducted qualitative interviews regarding motivators and barriers to ventilation. Compared with poor ventilation homes, good ventilation homes were larger, their residents wealthier and less likely to use biomass fuel. In multivariable linear mixed-effects models, ventilation structures and opening a door or window were inversely associated with the number of hours PM 2.5 concentrations exceeded 100 and 250 μg/m 3 . Outdoor air pollution was positively associated with the number of hours PM 2.5 concentrations exceeded 100 and 250 μg/m 3 . Few homes accepted window installation, due to landlord refusal and fear of theft. Motivators for ventilation behavior included cooling of the home and sunlight; barriers included rain, outdoor odors or noise, theft risk, mosquito entry, and, for fan use, perceptions of wasting electricity or unavailability of electricity. We concluded that ventilation may reduce indoor PM 2.5 concentrations but, there are barriers to increasing ventilation and, in areas with high ambient PM 2.5 concentrations, indoor concentrations may remain above recommended levels.

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.

Characterizing Intra-Urban Air Quality Gradients with a Spatially-Distributed Network

NASA Astrophysics Data System (ADS)

Zimmerman, N.; Ellis, A.; Schurman, M. I.; Gu, P.; Li, H.; Snell, L.; Gu, J.; Subramanian, R.; Robinson, A. L.; Apte, J.; Presto, A. A.

2016-12-01

City-wide air pollution measurements have typically relied on regulatory or research monitoring sites with low spatial density to assess population-scale exposure. However, air pollutant concentrations exhibit significant spatial variability depending on local sources and features of the built environment, which may not be well captured by the existing monitoring regime. To better understand urban spatial and temporal pollution gradients at 1 km resolution, a network of 12 real-time air quality monitoring stations was deployed beginning July 2016 in Pittsburgh, PA. The stations were deployed at sites along an urban-rural transect and in urban locations with a range of traffic, restaurant, and tall building densities to examine the impact of various modifiable factors. Measurements from the stationary monitoring stations were further supported by mobile monitoring, which provided higher spatial resolution pollutant measurements on nearby roadways and enabled routine calibration checks. The stationary monitoring measurements comprise ultrafine particle number (Aerosol Dynamics "MAGIC" CPC), PM2.5 (Met One Neighborhood PM Monitor), black carbon (Met One BC 1050), and a new low-cost air quality monitor, the Real-time Affordable Multi-Pollutant (RAMP) sensor package for measuring CO, NO2, SO2, O3, CO2, temperature and relative humidity. High time-resolution (sub-minute) measurements across the distributed monitoring network enable insight into dynamic pollutant behaviour. Our preliminary findings show that our instruments are sensitive to PM2.5 gradients exceeding 2 micro-grams per cubic meter and ultrafine particle gradients exceeding 1000 particles per cubic centimeter. Additionally, we have developed rigorous calibration protocols to characterize the RAMP sensor response and drift, as well as multiple linear regression models to convert sensor response into pollutant concentrations that are comparable to reference instrumentation.

The sensitivities of emissions reductions for the mitigation of UK PM2.5

NASA Astrophysics Data System (ADS)

Vieno, M.; Heal, M. R.; Williams, M. L.; Carnell, E. J.; Nemitz, E.; Stedman, J. R.; Reis, S.

2016-01-01

The reduction of ambient concentrations of fine particulate matter (PM2.5) is a key objective for air pollution control policies in the UK and elsewhere. Long-term exposure to PM2.5 has been identified as a major contributor to adverse human health effects in epidemiological studies and underpins ambient PM2.5 legislation. As a range of emission sources and atmospheric chemistry transport processes contribute to PM2.5 concentrations, atmospheric chemistry transport models are an essential tool to assess emissions control effectiveness. The EMEP4UK atmospheric chemistry transport model was used to investigate the impact of reductions in UK anthropogenic emissions of primary PM2.5, NH3, NOx, SOx or non-methane VOC on surface concentrations of PM2.5 in the UK for a recent year (2010) and for a future current legislation emission (CLE) scenario (2030). In general, the sensitivity to UK mitigation is rather small. A 30 % reduction in UK emissions of any one of the above components yields (for the 2010 simulation) a maximum reduction in PM2.5 in any given location of ˜ 0.6 µg m-3 (equivalent to ˜ 6 % of the modelled PM2.5). On average across the UK, the sensitivity of PM2.5 concentrations to a 30 % reduction in UK emissions of individual contributing components, for both the 2010 and 2030 CLE baselines, increases in the order NMVOC, NOx, SOx, NH3 and primary PM2.5; however there are strong spatial differences in the PM2.5 sensitivities across the UK. Consequently, the sensitivity of PM2.5 to individual component emissions reductions varies between area and population weighting. Reductions in NH3 have the greatest effect on area-weighted PM2.5. A full UK population weighting places greater emphasis on reductions of primary PM2.5 emissions, which is simulated to be the most effective single-component control on PM2.5 for the 2030 scenario. An important conclusion is that weighting corresponding to the average exposure indicator metric (using data from the 45 model grids containing a monitor whose measurements are used to calculate the UK AEI) further increases the emphasis on the effectiveness of primary PM2.5 emissions reductions (and of NOx emissions reductions) relative to the effectiveness of NH3 emissions reductions. Reductions in primary PM2.5 have the largest impact on the AEI in both 2010 and the 2030 CLE scenario. The summation of the modelled reductions to the UK PM2.5 AEI from 30 % reductions in UK emissions of primary PM2.5, NH3, SOx, NOx and VOC totals 1.17 and 0.82 µg m-3 for the 2010 and 2030 CLE simulations, respectively (not accounting for non-linearity).