Particulate matter dynamics in naturally ventilated freestall dairy barns

NASA Astrophysics Data System (ADS)

Joo, H. S.; Ndegwa, P. M.; Heber, A. J.; Ni, J.-Q.; Bogan, B. W.; Ramirez-Dorronsoro, J. C.; Cortus, E. L.

2013-04-01

Particulate matter (PM) concentrations and ventilation rates, in two naturally ventilated freestall dairy barns, were continuously monitored for two years. The first barn (B1) housed 400 fresh lactating cows, while the second barn (B2) housed 835 non-fresh lactating cows and 15 bulls. The relationships between PM concentrations and accepted governing parameters (environmental conditions and cattle activity) were examined. In comparison with other seasons, PM concentrations were lowest in winter. Total suspended particulate (TSP) concentrations in spring and autumn were relatively higher than those in summer. Overall: the concentrations in the barns and ambient air, for all the PM categories (PM2.5, PM10, and TSP), exhibited non-normal positively skewed distributions, which tended to overestimate mean or average concentrations. Only concentrations of PM2.5 and PM10 increased with ambient air temperature (R2 = 0.60-0.82), whereas only concentrations of TSP increased with cattle activity. The mean respective emission rates of PM2.5, PM10, and TSP for the two barns ranged between 1.6-4.0, 11.9-15.0, and 48.7-52.5 g d-1 cow-1, indicating similar emissions from the two barns.

Quantitative association analysis between PM2.5 concentration and factors on industry, energy, agriculture, and transportation.

PubMed

Zhang, Nan; Huang, Hong; Duan, Xiaoli; Zhao, Jinlong; Su, Boni

2018-06-21

Rapid urbanization is causing serious PM 2.5 (particulate matter ≤2.5 μm) pollution in China. However, the impacts of human activities (including industrial production, energy production, agriculture, and transportation) on PM 2.5 concentrations have not been thoroughly studied. In this study, we obtained a regression formula for PM 2.5 concentration based on more than 1 million PM 2.5 recorded values and data from meteorology, industrial production, energy production, agriculture, and transportation for 31 provinces of mainland China between January 2013 and May 2017. We used stepwise regression to process 49 factors that influence PM 2.5 concentration, and obtained the 10 primary influencing factors. Data of PM 2.5 concentration and 10 factors from June to December, 2017 was used to verify the robustness of the model. Excluding meteorological factors, production of natural gas, industrial boilers, and ore production have the highest association with PM 2.5 concentration, while nuclear power generation is the most positive factor in decreasing PM 2.5 concentration. Tianjin, Beijing, and Hebei provinces are the most vulnerable to high PM 2.5 concentrations caused by industrial production, energy production, agriculture, and transportation (IEAT).

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Tire tread wear particles in ambient air--a previously unknown source of human exposure to the biocide 2-mercaptobenzothiazole.

PubMed

Avagyan, Rozanna; Sadiktsis, Ioannis; Bergvall, Christoffer; Westerholm, Roger

2014-10-01

Urban particulate matter (PM), asphalt, and tire samples were investigated for their content of benzothiazole and benzothiazole derivates. The purpose of this study was to examine whether wear particles, i.e., tire tread wear or road surface wear, could contribute to atmospheric concentrations of benzothiazole derivatives. Airborne particulate matter (PM10) sampled at a busy street in Stockholm, Sweden, contained on average 17 pg/m(3) benzothiazole and 64 pg/m(3) 2-mercaptobenzothiazole, and the total suspended particulate-associated benzothiazole and 2-mercaptobenzothiazole concentrations were 199 and 591 pg/m(3), respectively. This indicates that tire tread wear may be a major source of these benzothiazoles to urban air PM in Stockholm. Furthermore, 2-mercaptobenzothiazole was determined in urban air particulates for the first time in this study, and its presence in inhalable PM10 implies that the human exposure to this biocide is underestimated. This calls for a revision of the risk assessments of 2-mercaptobenzothiazole exposure to humans which currently is limited to occupational exposure.

Density functional theoretical modeling, electrostatic surface potential and surface enhanced Raman spectroscopic studies on biosynthesized silver nanoparticles: observation of 400 PM sensitivity to explosives.

PubMed

Sil, Sanchita; Chaturvedi, Deepika; Krishnappa, Keerthi B; Kumar, Srividya; Asthana, S N; Umapathy, Siva

2014-04-24

Interaction of adsorbate on charged surfaces, orientation of the analyte on the surface, and surface enhancement aspects have been studied. These aspects have been explored in details to explain the surface-enhanced Raman spectroscopic (SERS) spectra of 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (HNIW or CL-20), a well-known explosive, and 2,4,6-trinitrotoluene (TNT) using one-pot synthesis of silver nanoparticles via biosynthetic route using natural precursor extracts of clove and pepper. The biosynthesized silver nanoparticles (bio Ag Nps) have been characterized using UV-vis spectroscopy, scanning electron microscopy and atomic force microscopy. SERS studies conducted using bio Ag Nps on different water insoluble analytes, such as CL-20 and TNT, lead to SERS signals at concentration levels of 400 pM. The experimental findings have been corroborated with density functional computational results, electrostatic surface potential calculations, Fukui functions and ζ potential measurements.

Configuration of Air Microfluidic Chip for Separating and Grading Respirable Dust

NASA Astrophysics Data System (ADS)

Zhu, Xiaofeng; Jia, Yiting; Sun, Jianhai; Zhao, Peiyue; Liu, Jinhua; Zhang, Yanni; Ning, Zhanwu

2018-03-01

Particulate matter (PM) is a category of airborne pollutants, and fine particles that have a diameter of 2.5 μm (PM2.5) or smaller are especially damaging to human health because of their ability to penetrate deep into our respiratory system, Therefore, Monitoring of PM is very important. In this work, an air micro- fluidic PM sensor based on MEMS was proposed, and numerical model of the sensor was simulated accurately. The sensor was able to separate particles according to their sizes, and then transports and deposits the selected particles using thermophoretic precipitation onto the surface of a microfabricated mass-sensitive film bulk acoustic resonator (FBAR), precisely weighing and providing the concentration of PM. The PM sensor has double stage separation function, and the primary separator can separate the particles with size of less 10 μm from the particles, and the secondary can separate particles with size of less 2.5 μm from the particles.

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.

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.

The contributions to long-term health-relevant particulate matter at the UK EMEP supersites between 2010 and 2013: Quantifying the mitigation challenge.

PubMed

Malley, Christopher S; Heal, Mathew R; Braban, Christine F; Kentisbeer, John; Leeson, Sarah R; Malcolm, Heath; Lingard, Justin J N; Ritchie, Stuart; Maggs, Richard; Beccaceci, Sonya; Quincey, Paul; Brown, Richard J C; Twigg, Marsailidh M

2016-10-01

Human health burdens associated with long-term exposure to particulate matter (PM) are substantial. The metrics currently recommended by the World Health Organization for quantification of long-term health-relevant PM are the annual average PM10 and PM2.5 mass concentrations, with no low concentration threshold. However, within an annual average, there is substantial variation in the composition of PM associated with different sources. To inform effective mitigation strategies, therefore, it is necessary to quantify the conditions that contribute to annual average PM10 and PM2.5 (rather than just short-term episodic concentrations). PM10, PM2.5, and speciated water-soluble inorganic, carbonaceous, heavy metal and polycyclic aromatic hydrocarbon components are concurrently measured at the two UK European Monitoring and Evaluation Programme (EMEP) 'supersites' at Harwell (SE England) and Auchencorth Moss (SE Scotland). In this work, statistical analyses of these measurements are integrated with air-mass back trajectory data to characterise the 'chemical climate' associated with the long-term health-relevant PM metrics at these sites. Specifically, the contributions from different PM concentrations, months, components and geographic regions are detailed. The analyses at these sites provide policy-relevant conclusions on mitigation of (i) long-term health-relevant PM in the spatial domain for which these sites are representative, and (ii) the contribution of regional background PM to long-term health-relevant PM. At Harwell the mean (±1 sd) 2010-2013 annual average concentrations were PM10=16.4±1.4μgm(-3) and PM2.5=11.9±1.1μgm(-3) and at Auchencorth PM10=7.4±0.4μgm(-3) and PM2.5=4.1±0.2μgm(-3). The chemical climate state at each site showed that frequent, moderate hourly PM10 and PM2.5 concentrations (defined as approximately 5-15μgm(-3) for PM10 and PM2.5 at Harwell and 5-10μgm(-3) for PM10 at Auchencorth) determined the magnitude of annual average PM10 and PM2.5 to a greater extent than the relatively infrequent high, episodic PM10 and PM2.5 concentrations. These moderate PM10 and PM2.5 concentrations were derived across the range of chemical components, seasons and air-mass pathways, in contrast to the highest PM concentrations which tended to associate with specific conditions. For example, the largest contribution to moderate PM10 and PM2.5 concentrations - the secondary inorganic aerosol components, specifically NO3(-) - were accumulated during the arrival of trajectories traversing the spectrum of marine, UK, and continental Europe areas. Mitigation of the long-term health-relevant PM impact in the regions characterised by these two sites requires multilateral action, across species (and hence source sectors), both nationally and internationally; there is no dominant determinant of the long-term PM metrics to target. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

The PM2.5 threshold for aerosol extinction in the Beijing megacity

NASA Astrophysics Data System (ADS)

Kong, Lingbin; Xin, Jinyuan; Liu, Zirui; Zhang, Kequan; Tang, Guiqian; Zhang, Wenyu; Wang, Yuesi

2017-10-01

Particulate pollution has remained at a high level in the megacity of Beijing in the past decade. The PM2.5, PM10, aerosol optical depth (AOD), Angstrom exponent(α), and PM2.5/PM10 ratio (the proportion of PM2.5 in PM10) in Beijing were 70±6 μg m-3, 128±6 μg m-3, 0.57 ± 0.05, 1.10 ± 0.08, 45 ± 4%, respectively, from 2005 to 2014. The annual means of PM concentration, AOD, α, and PM2.5/PM10 ratio decreased slightly during this decade, meanwhile PM concentration increased in the winter. Furthermore, we found there were thresholds of PM2.5 concentration for aerosol extinction. When the PM concentration was lower than a certain threshold, AOD decreased quickly with the decline of PM concentration. To make the improvement of the particle pollution more noticeable, the PM concentration should be controlled under the threshold. The annual averaged threshold is 63 μg m-3, and the threshold values reached the maximum of 74 μg m-3 in spring, ranged from 54 to 56 μg m-3 in the three other seasons. The threshold values ranged from 55 to 77 μg m-3 under other relevant factors, including air masses directions and relative humidity.

Overview of surface measurements and spatial characterization of submicrometer particulate matter during the DISCOVER-AQ 2013 campaign in Houston, TX.

PubMed

Leong, Y J; Sanchez, N P; Wallace, H W; Karakurt Cevik, B; Hernandez, C S; Han, Y; Flynn, J H; Massoli, P; Floerchinger, C; Fortner, E C; Herndon, S; Bean, J K; Hildebrandt Ruiz, L; Jeon, W; Choi, Y; Lefer, B; Griffin, R J

2017-08-01

The sources of submicrometer particulate matter (PM 1 ) remain poorly characterized in the industrialized city of Houston, TX. A mobile sampling approach was used to characterize PM 1 composition and concentration across Houston based on high-time-resolution measurements of nonrefractory PM 1 and trace gases during the DISCOVER-AQ Texas 2013 campaign. Two pollution zones with marked differences in PM 1 levels, character, and dynamics were established based on cluster analysis of organic aerosol mass loadings sampled at 16 sites. The highest PM 1 mass concentrations (average 11.6 ± 5.7 µg/m 3 ) were observed to the northwest of Houston (zone 1), dominated by secondary organic aerosol (SOA) mass likely driven by nighttime biogenic organonitrate formation. Zone 2, an industrial/urban area south/east of Houston, exhibited lower concentrations of PM 1 (average 4.4 ± 3.3 µg/m 3 ), significant organic aerosol (OA) aging, and evidence of primary sulfate emissions. Diurnal patterns and backward-trajectory analyses enable the classification of airmass clusters characterized by distinct PM sources: biogenic SOA, photochemical aged SOA, and primary sulfate emissions from the Houston Ship Channel. Principal component analysis (PCA) indicates that secondary biogenic organonitrates primarily related with monoterpenes are predominant in zone 1 (accounting for 34% of the variability in the data set). The relevance of photochemical processes and industrial and traffic emission sources in zone 2 also is highlighted by PCA, which identifies three factors related with these processes/sources (~50% of the aerosol/trace gas concentration variability). PCA reveals a relatively minor contribution of isoprene to SOA formation in zone 1 and the absence of isoprene-derived aerosol in zone 2. The relevance of industrial amine emissions and the likely contribution of chloride-displaced sea salt aerosol to the observed variability in pollution levels in zone 2 also are captured by PCA. This article describes an urban-scale mobile study to characterize spatial variations in submicrometer particulate matter (PM 1 ) in greater Houston. The data set indicates substantial spatial variations in PM 1 sources/chemistry and elucidates the importance of photochemistry and nighttime oxidant chemistry in producing secondary PM 1 . These results emphasize the potential benefits of effective control strategies throughout the region, not only to reduce primary emissions of PM 1 from automobiles and industry but also to reduce the emissions of important secondary PM 1 precursors, including sulfur oxides, nitrogen oxides, ammonia, and volatile organic compounds. Such efforts also could aid in efforts to reduce mixing ratios of ozone.

The Effect of a Receding Saline Lake (The Salton Sea) on Airborne Particulate Matter Composition.

PubMed

Frie, Alexander L; Dingle, Justin H; Ying, Samantha C; Bahreini, Roya

2017-08-01

The composition of ambient particulate matter (PM) and its sources were investigated at the Salton Sea, a shrinking saline lake in California. To investigate the influence of playa exposure on PM composition, PM samples were collected during two seasons and at two sites around the Salton Sea. To characterize source composition, soil samples were collected from local playa and desert surfaces. PM and soil samples were analyzed for 15 elements using mass spectrometry and X-ray diffraction. The contribution of sources to PM mass and composition was investigated using Al-referenced enrichment factors (EFs) and source factors resolved from positive matrix factorization (PMF). Playa soils were found to be significantly enriched in Ca, Na, and Se relative to desert soils. PMF analysis resolved the PM 10 data with four source factors, identified as Playa-like, Desert-like, Ca-rich, and Se. Playa-like and desert-like sources were estimated to contribute to a daily average of 8.9% and 45% of PM 10 mass, respectively. Additionally, playa sources were estimated to contribute to 38-68% of PM 10 Na. PM 10 Se concentrations showed strong seasonal variations, suggesting a seasonal cycle of Se volatilization and recondensation. These results support the importance of playas as a source of PM mass and a controlling factor of PM composition.

Pollution characteristics and influencing factors of atmospheric particulate matter (PM2.5) in Chang-Zhu-Tan area

NASA Astrophysics Data System (ADS)

Zhang, Yong; Jiang, Wulin

2018-01-01

Using the same time data of PM2.5 concentration and meteorology from May 1st to May 31st in 2013 in Chang-Zhu-Tan area. This paper analyses the variation characteristics of PM2.5 concentration and the correlations between the variation characteristics and meteorological factors. In view of time, the results showed that the 24-h PM2.5 concentration varied with the two peaks and two valleys styles in Chang-Zhu-Tan area. And the daily PM2.5 concentration tends to the instability and great variation characteristics with the multi-peaks and multi-valleys style. In view of space, PM2.5 concentration values of the three cities from high to low are Zhuzhou>Xiangtan>Changsha. For cities and suburbs, PM2.5 concentration values of central towns are greater than that of the suburbs in Changsha and Xiangtan; however, the PM2.5 concentration values of the central town in Zhuzhou are slightly lower than the suburbs. At the same time, the correlation analysis between PM2.5 concentration and meteorological factors showed that the correlation from high to low was the relative air humidity>soil temperature>air temperature>soil humidity> wind velocity>rainfall. Among the above meteorological factors, wind velocity, rainfall, air temperature, soil temperature and soil humidity are negatively correlated with PM2.5 concentration, but the relationship between relative air humidity and PM2.5 concentration is a positive correlation.

Mass concentration, optical depth and carbon composition of particulate matter in the major southern West African cities of Cotonou (Benin) and Abidjan (Côte d'Ivoire)

NASA Astrophysics Data System (ADS)

Djossou, Julien; Léon, Jean-François; Barthélemy Akpo, Aristide; Liousse, Cathy; Yoboué, Véronique; Bedou, Mouhamadou; Bodjrenou, Marleine; Chiron, Christelle; Galy-Lacaux, Corinne; Gardrat, Eric; Abbey, Marcellin; Keita, Sékou; Bahino, Julien; Touré N'Datchoh, Evelyne; Ossohou, Money; Awanou, Cossi Norbert

2018-05-01

Air quality degradation is a major issue in the large conurbations on the shore of the Gulf of Guinea. We present for the first time PM2.5 time series collected in Cotonou, Benin, and Abidjan, Côte d'Ivoire, from February 2015 to March 2017. Measurements were performed in the vicinity of major combustion aerosol sources: Cotonou/traffic (CT), Abidjan/traffic (AT), Abidjan/landfill (AL) and Abidjan/domestic fires (ADF). We report the weekly PM2.5 mass and carbonaceous content as elemental (EC) and organic (OC) carbon concentrations. We also measure the aerosol optical depth (AOD) and the Ångström exponent in both cities. The average PM2.5 mass concentrations were 32 ± 32, 32 ± 24 and 28 ± 19 µg m-3 at traffic sites CT and AT and landfill site AL, respectively. The domestic fire site shows a concentration of 145 ± 69 µg m-3 due to the contribution of smoking and roasting activities. The highest OC and EC concentrations were also measured at ADF at 71 ± 29 and 15 ± 9 µg m-3, respectively, while the other sites present OC concentration between 8 and 12 µg m-3 and EC concentrations between 2 and 7 µg m-3. The OC / EC ratio is 4.3 at CT and 2.0 at AT. This difference highlights the influence of two-wheel vehicles using gasoline in Cotonou compared to that of four-wheel vehicles using diesel fuel in Abidjan. AOD was rather similar in both cities, with a mean value of 0.58 in Cotonou and of 0.68 in Abidjan. The seasonal cycle is dominated by the large increase in surface mass concentration and AOD during the long dry season (December-February) as expected due to mineral dust advection and biomass burning activities. The lowest concentrations are observed during the short dry season (August-September) due to an increase in surface wind speed leading to a better ventilation. On the other hand, the high PM2.5 / AOD ratio in the short wet season (October-November) indicates the stagnation of local pollution.

Particulate matter oxidative potential from waste transfer station activity.

PubMed

Godri, Krystal J; Duggan, Sean T; Fuller, Gary W; Baker, Tim; Green, David; Kelly, Frank J; Mudway, Ian S

2010-04-01

Adverse cardiorespiratory health is associated with exposure to ambient particulate matter (PM). The highest PM concentrations in London occur in proximity to waste transfer stations (WTS), sites that experience high numbers of dust-laden, heavy-duty diesel vehicles transporting industrial and household waste. Our goal was to quantify the contribution of WTS emissions to ambient PM mass concentrations and oxidative potential. PM with a diameter < 10 microm (PM10) samples were collected daily close to a WTS. PM10 mass concentrations measurements were source apportioned to estimate local versus background sources. PM oxidative potential was assessed using the extent of antioxidant depletion from a respiratory tract lining fluid model. Total trace metal and bioavailable iron concentrations were measured to determine their contribution to PM oxidative potential. Elevated diurnal PM10 mass concentrations were observed on all days with WTS activity (Monday-Saturday). Variable PM oxidative potential, bioavailable iron, and total metal concentrations were observed on these days. The contribution of WTS emissions to PM at the sampling site, as predicted by microscale wind direction measurements, was correlated with ascorbate (r = 0.80; p = 0.030) and glutathione depletion (r = 0.76; p = 0.046). Increased PM oxidative potential was associated with aluminum, lead, and iron content. PM arising from WTS activity has elevated trace metal concentrations and, as a consequence, increased oxidative potential. PM released by WTS activity should be considered a potential health risk to the nearby residential community.

A new paradigm for constraining PM2.5 speciation by combining multiangular and polarimetric remote sensing with chemical transport model information

NASA Astrophysics Data System (ADS)

Kalashnikova, O.; Xu, F.; Ge, C.; Wang, J.; Garay, M. J.; Diner, D. J.

2014-12-01

Exposure to ambient particulate matter (PM) has been consistently linked to cardiovascular and respiratory health effects. Although PM is currently monitored by a network of surface stations, these are too sparsely distributed to provide the level of spatial detail needed to link different aerosol species to given health effects, and expansion to denser coverage is impractical and cost prohibitive. We present a methodology for combining Chemical Transport Model (CTM) aerosol type information and multiangular spectropolarimetric data to establish the signature of specific aerosol types in top-of-atmosphere measurements, and relate it to speciated surface PM2.5 loadings. In particular, we employ the WRF-Chem model run at the University of Nebraska, and remote sensing data from the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) to explore the feasibility of this approach. We demonstrate that the CTM does well in predicting the types of aerosols present at a given location and time, however large uncertainties currently exist in CTM estimates of the concentration of the various aerosol species (e.g., black carbon, sulfate, dust, etc.) leading to large uncertainties to model-derived speciated PM 2.5. In order to constrain CTM aerosol surface concentrations we use AirMSPI UV-VIS-NIR observations of intensity, and blue, red, and NIR observations of the Q and U Stokes parameters. We select specific scenes observed by AirMSPI and use WRF-Chem to generate an initial distribution of aerosol composition. The relevant optical properties for each aerosol species are used to calculate aerosol light scattering information. This is then used in a vector (polarized) 1-D radiative transfer model to determine at-instrument Stokes parameters for the specific AirMSPI viewing geometries. As a first step, a match is sought between the CTM-predicted radiances and the AirMSPI observations. Then, the total aerosol optical depth and fractions of various aerosol species are modified via optimization to produce a better match to the observations, and converted to PM2.5 speciated loadings using CTM aerosol vertical profiles. Finally, the results are compared to available ground-based and in situ data to validate this approach.

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.

Variations of PM2.5, PM10 mass concentration and health assessment in Islamabad, Pakistan

NASA Astrophysics Data System (ADS)

Memhood, Tariq; Tianle, Z.; Ahmad, I.; Li, X.; Shen, F.; Akram, W.; Dong, L.

2018-04-01

Sparse information appears in lack of awareness among the people regarding the linkage between particulate matter (PM) and mortality in Pakistan. The current study is aimed to investigate the seasonal mass concentration level of PM2.5 and PM10 in ambient air of Islamabad to assess the health risk of PM pollution. The sampling was carried out with two parallel medium volume air samplers on Whatman 47 mm quartz filter at a flow rate of 100L/min. Mass concentration was obtained by gravimetric analysis. A noticeable seasonal change in PM10 and PM2.5 mass concentration was observed. In case of PM2.5, the winter was a most polluted and spring was the cleanest season of 2017 in Islamabad with 69.97 and 40.44 μgm‑3 mean concentration. Contrary, highest (152.42 μgm‑3) and lowest (74.90 μgm‑3) PM10 mass concentration was observed in autumn and summer respectively. Air Quality index level for PM2.5 and PM10 was remained moderated to unhealthy and good to sensitive respectively. Regarding health risk assessment, using national data for mortality rates, the excess mortality due to PM2.5 and PM10 exposure has been calculated and amounts to over 198 and 98 deaths annually for Islamabad. Comparatively estimated lifetime risk for PM2.5 (1.16×10-6) was observed higher than PM10 (7.32×10-8).

2010-2011 Performance of the AirNow Satellite Data Processor

NASA Astrophysics Data System (ADS)

Pasch, A. N.; DeWinter, J. L.; Haderman, M. D.; van Donkelaar, A.; Martin, R. V.; Szykman, J.; White, J. E.; Dickerson, P.; Zahn, P. H.; Dye, T. S.

2012-12-01

The U.S. Environmental Protection Agency's (EPA) AirNow program provides maps of real time hourly Air Quality Index (AQI) conditions and daily AQI forecasts nationwide (http://www.airnow.gov). The public uses these maps to make health-based decisions. The usefulness of the AirNow air quality maps depends on the accuracy and spatial coverage of air quality measurements. Currently, the maps use only ground-based measurements, which have significant gaps in coverage in some parts of the United States. As a result, contoured AQI levels have high uncertainty in regions far from monitors. To improve the usefulness of air quality maps, scientists at EPA, Dalhousie University, and Sonoma Technology, Inc. have been working in collaboration with the National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA) to incorporate satellite-estimated surface PM2.5 concentrations into the maps via the AirNow Satellite Data Processor (ASDP). These satellite estimates are derived using NASA/NOAA satellite aerosol optical depth (AOD) retrievals and GEOS-Chem modeled ratios of surface PM2.5 concentrations to AOD. GEOS-Chem is a three-dimensional chemical transport model for atmospheric composition driven by meteorological input from the Goddard Earth Observing System (GOES). The ASDP can fuse multiple PM2.5 concentration data sets to generate AQI maps with improved spatial coverage. The goal of ASDP is to provide more detailed AQI information in monitor-sparse locations and augment monitor-dense locations with more information. We will present a statistical analysis for 2010-2011 of the ASDP predictions of PM2.5 focusing on performance at validation sites. In addition, we will present several case studies evaluating the ASDP's performance for multiple regions and seasons, focusing specifically on days when large spatial gradients in AQI and wildfire smoke impact were observed.

A Coffee Ring Aptasensor for Rapid Protein Detection

PubMed Central

Wen, Jessica T.; Ho, Chih-Ming; Lillehoj, Peter B.

2013-01-01

We introduce a new biosensing platform for rapid protein detection that combines one of the simplest methods for biomolecular concentration, coffee ring formation, with a sensitive aptamer-based optical detection scheme. In this approach, aptamer beacons are utilized for signal transduction where a fluorescence signal is emitted in the presence of the target molecule. Signal amplification is achieved by concentrating aptamer-target complexes within liquid droplets, resulting in the formation of coffee ring “spots”. Surfaces with various chemical coatings were utilized to investigate the correlation between surface hydrophobicity, concentration efficiency and signal amplification. Based on our results, we found that the increase in coffee ring diameter with larger droplet volumes is independent of surface hydrophobicity. Furthermore, we show that highly hydrophobic surfaces produce enhanced particle concentration, via coffee ring formation, resulting in signal intensities 6-fold greater than those on hydrophilic surfaces. To validate this biosensing platform for the detection of clinical samples, we detected α-thrombin in human serum and 4x diluted whole blood. Based on our results, coffee ring spots produced detection signals 40x larger than samples in liquid droplets. Additionally, this biosensor exhibits a lower limit of detection of 2 ng/mL (54 pM) in serum, and 4 ng/mL (105 pM) in blood. Based on its simplicity and high performance, this platform demonstrates immense potential as an inexpensive diagnostic tool for the detection of disease biomarkers, particularly for use in developing countries that lack the resources and facilities required for conventional biodetection practices. PMID:23540796

Climate change impacts on human health over Europe through its effect on air quality.

PubMed

Doherty, Ruth M; Heal, Mathew R; O'Connor, Fiona M

2017-12-05

This review examines the current literature on the effects of future emissions and climate change on particulate matter (PM) and O 3 air quality and on the consequent health impacts, with a focus on Europe. There is considerable literature on the effects of climate change on O 3 but fewer studies on the effects of climate change on PM concentrations. Under the latest Intergovernmental Panel on Climate Change (IPCC) 5th assessment report (AR5) Representative Concentration Pathways (RCPs), background O 3 entering Europe is expected to decrease under most scenarios due to higher water vapour concentrations in a warmer climate. However, under the extreme pathway RCP8.5 higher (more than double) methane (CH 4 ) abundances lead to increases in background O 3 that offset the O 3 decrease due to climate change especially for the 2100 period. Regionally, in polluted areas with high levels of nitrogen oxides (NO x ), elevated surface temperatures and humidities yield increases in surface O 3 - termed the O 3 climate penalty - especially in southern Europe. The O 3 response is larger for metrics that represent the higher end of the O 3 distribution, such as daily maximum O 3 . Future changes in PM concentrations due to climate change are much less certain, although several recent studies also suggest a PM climate penalty due to high temperatures and humidity and reduced precipitation in northern mid-latitude land regions in 2100.A larger number of studies have examined both future climate and emissions changes under the RCP scenarios. Under these pathways the impact of emission changes on air quality out to the 2050s will be larger than that due to climate change, because of large reductions in emissions of O 3 and PM pollutant precursor emissions and the more limited climate change response itself. Climate change will also affect climate extreme events such as heatwaves. Air pollution episodes are associated with stagnation events and sometimes heat waves. Air quality during the 2003 heatwave over Europe has been examined in numerous studies and mechanisms for enhancing O 3 have been identified.There are few studies on health effects associated with climate change impacts alone on air quality, but these report higher O 3 -related health burdens in polluted populated regions and greater PM 2.5 health burdens in these emission regions. Studies that examine the combined impacts of climate change and anthropogenic emissions change under the RCP scenarios report reductions in global and European premature O 3 -respiratory related and PM mortalities arising from the large decreases in precursor emissions. Under RCP 8.5 the large increase in CH 4 leads to global and European excess O 3 -respiratory related mortalities in 2100. For future health effects, besides uncertainty in future O 3 and particularly PM concentrations, there is also uncertainty in risk estimates such as effect modification by temperature on pollutant-response relationships and potential future adaptation that would alter exposure risk.

Emissions from residential energy use dominate exposure to ambient fine particulate matter in India

NASA Astrophysics Data System (ADS)

Conibear, L.; Butt, E. W.; Knote, C. J.; Arnold, S.; Spracklen, D. V.

2017-12-01

Exposure to ambient particulate matter of less than 2.5 µm in diameter (PM2.5) is a leading cause of disease burden in India. Information on the source contributions to the burden of disease attributable to ambient PM2.5 exposure is critical to support the national and sub-national control of air pollution. Previous studies analysing the contributions of different emission sectors to disease burden in India have been limited by coarse model resolutions and a lack of extensive PM2.5 observations before 2016. We use a regional numerical weather prediction model online-coupled with chemistry, evaluated against extensive surface observations, to make the first high resolution study of the contributions of seven emission sectors to the disease burden associated with ambient PM2.5 exposure in India. We find that residential energy use is the dominant contributing emission sector. Removing air pollution emissions from residential energy use would reduce population-weighted annual mean ambient PM2.5 concentrations by 52%, reducing the number of premature mortalities caused by exposure to ambient PM2.5 by 26%, equivalent to 268,000 (95% uncertainty interval (95UI): 167,000-360,000) lives every year. The smaller fractional reduction in mortality burden is due to the non-linear exposure-response relationship at the high PM2.5 concentrations observed across India and consequently large reductions in emissions are required to reduce the health burden from ambient PM2.5 exposure in India. Keywords: ambient air quality, India, residential energy use, health impact, particulate matter, WRF-Chem

April 2008 Saharan dust event: Its contribution to PM10 concentrations over the Anatolian Peninsula and relation with synoptic conditions.

PubMed

Kabatas, B; Pierce, R B; Unal, A; Rogal, M J; Lenzen, A

2018-08-15

An online-coupled regional Weather Research and Forecasting model with chemistry (WRF-Chem) is utilized incorporating 0.1°×0.1° spatial resolution HTAP (Hemispheric Transport of Air Pollution) anthropogenic emissions to investigate the spatial and temporal distribution of a Saharan dust outbreak, which contributed to high levels (>50μg/m 3 ) of daily PM 10 concentrations over Turkey in April 2008. Aerosol optical depth and cloud optical thickness retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board of Aqua satellite are used to better analyze the synoptic conditions that generated the dust outbreak in April 2008. A "Sharav" low pressure system, which transports the dust from Saharan source region over Turkey along the cold front, tends to move faster in WRF-Chem simulations than observed. This causes the predicted dust event to arrive earlier than observed leading to an overestimation of surface PM 10 concentrations in WRF-Chem simulation at the beginning of the event. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Variability of aerosols and chemical composition of PM10, PM2.5 and PM1 on a platform of the Prague underground metro

NASA Astrophysics Data System (ADS)

Cusack, M.; Talbot, N.; Ondráček, J.; Minguillón, M. C.; Martins, V.; Klouda, K.; Schwarz, J.; Ždímal, V.

2015-10-01

Measurements of PM10, PM2.5 and PM1 and particle number concentration and size distribution were measured for 24 h on a platform of the Prague underground metro in October 2013. The three PM fractions were analysed for major and minor elements, secondary inorganic aerosols (SIA) and total carbon (TC). Measurements were performed both when the metro was inoperative and closed to the public (referred to as background), and when the metro was in operation and open to passengers. PM concentrations were elevated during both periods, but were substantially increased in the coarse fraction during hours when the metro was in operation. Average PM concentrations were 214.8, 93.9 and 44.8 μg m-3 for PM10, PM2.5 and PM1, respectively (determined gravimetrically). Average particle number concentrations were 8.5 × 103 cm-3 for background hours and 11.5 × 103 cm-3 during operational hours. Particle number concentrations were found to not vary as significantly as PM concentrations throughout the day. Variations in PM were strongly governed by passing trains, with highest concentrations recorded during rush hour. When trains were less frequent, PM concentrations were shown to fluctuate in unison with the entrance and exit of trains (as shown by wind velocity measured on the platform). PM was found to be highly enriched with iron, especially in the coarse fraction, comprising 46% of PM10 (98.9 μg m-3). This reduces to 6.7 μg m-3 during background hours, proving that the trains themselves were the main source of iron, most probably from wheel-rail mechanical abrasion. Other enriched elements relative to background hours included Ba, Cu, Mn, Cr, Mo, Ni and Co, among others. Many of these elements exhibited a similar size distribution, further indicating their sources were common and were attributed to train operations.

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

PubMed

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

2005-03-01

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

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.

Feasibility of using low-cost portable particle monitors for measurement of fine and coarse particulate matter in urban ambient air.

PubMed

Han, Inkyu; Symanski, Elaine; Stock, Thomas H

2017-03-01

Exposure to ambient particulate matter (PM) is known as a significant risk factor for mortality and morbidity due to cardiorespiratory causes. Owing to increased interest in assessing personal and community exposures to PM, we evaluated the feasibility of employing a low-cost portable direct-reading instrument for measurement of ambient air PM exposure. A Dylos DC 1700 PM sensor was collocated with a Grimm 11-R in an urban residential area of Houston Texas. The 1-min averages of particle number concentrations for sizes between 0.5 and 2.5 µm (small size) and sizes larger than 2.5 µm (large size) from a DC 1700 were compared with the 1-min averages of PM 2.5 (aerodynamic size less than 2.5 µm) and coarse PM (aerodynamic size between 2.5 and 10 µm) concentrations from a Grimm 11-R. We used a linear regression equation to convert DC 1700 number concentrations to mass concentrations, utilizing measurements from the Grimm 11-R. The estimated average DC 1700 PM 2.5 concentration (13.2 ± 13.7 µg/m 3 ) was similar to the average measured Grimm 11-R PM 2.5 concentration (11.3 ± 15.1 µg/m 3 ). The overall correlation (r 2 ) for PM 2.5 between the DC 1700 and Grimm 11-R was 0.778. The estimated average coarse PM concentration from the DC 1700 (5.6 ± 12.1 µg/m 3 ) was also similar to that measured with the Grimm 11-R (4.8 ± 16.5 µg/m 3 ) with an r 2 of 0.481. The effects of relative humidity and particle size on the association between the DC 1700 and the Grimm 11-R results were also examined. The calculated PM mass concentrations from the DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM 2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM 2.5 . The performance of a low-cost particulate matter (PM) sensor was evaluated in an urban residential area. Both PM 2.5 and coarse PM (PM 10-2.5 ) mass concentrations were estimated using a DC1700 PM sensor. The calculated PM mass concentrations from the number concentrations of DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM 2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM 2.5 .

Modelling road dust emission abatement measures using the NORTRIP model: Vehicle speed and studded tyre reduction

NASA Astrophysics Data System (ADS)

Norman, M.; Sundvor, I.; Denby, B. R.; Johansson, C.; Gustafsson, M.; Blomqvist, G.; Janhäll, S.

2016-06-01

Road dust emissions in Nordic countries still remain a significant contributor to PM10 concentrations mainly due to the use of studded tyres. A number of measures have been introduced in these countries in order to reduce road dust emissions. These include speed reductions, reductions in studded tyre use, dust binding and road cleaning. Implementation of such measures can be costly and some confidence in the impact of the measures is required to weigh the costs against the benefits. Modelling tools are thus required that can predict the impact of these measures. In this paper the NORTRIP road dust emission model is used to simulate real world abatement measures that have been carried out in Oslo and Stockholm. In Oslo both vehicle speed and studded tyre share reductions occurred over a period from 2004 to 2006 on a major arterial road, RV4. In Stockholm a studded tyre ban on Hornsgatan in 2010 saw a significant reduction in studded tyre share together with a reduction in traffic volume. The model is found to correctly simulate the impact of these measures on the PM10 concentrations when compared to available kerbside measurement data. Importantly meteorology can have a significant impact on the concentrations through both surface and dispersion conditions. The first year after the implementation of the speed reduction on RV4 was much drier than the previous year, resulting in higher mean concentrations than expected. The following year was much wetter with significant rain and snow fall leading to wet or frozen road surfaces for 83% of the four month study period. This significantly reduced the net PM10 concentrations, by 58%, compared to the expected values if meteorological conditions had been similar to the previous years. In the years following the studded tyre ban on Hornsgatan road wear production through studded tyres decreased by 72%, due to a combination of reduced traffic volume and reduced studded tyre share. However, after accounting for exhaust contributions and the impact of meteorological conditions in the model calculations then the net mean reduction in PM10 concentrations was only ∼50%, in agreement with observations. The NORTRIP model is shown to be able to reproduce the impacts of both traffic measures and meteorology on traffic induced PM10 concentrations, making it a unique and valuable tool for predicting the impact of measures for air quality management applications.

Factors determining the concentration and chemical composition of particulate matter in the air of selected service facilities

NASA Astrophysics Data System (ADS)

Rogula-Kopiec, Patrycja; Pastuszka, Józef; Mathews, Barbara; Widziewicz, Kamila

2018-01-01

The link between increased morbidity and mortality and increasing concentrations of particulate matter (PM) resulted in great attention being paid to the presence and physicochemical properties of PM in closed rooms, where people spends most of their time. The least recognized group of such indoor environments are small service facilities. The aim of this study was to identify factors which determine the concentration, chemical composition and sources of PM in the air of different service facilities: restaurant kitchen, printing office and beauty salon. The average PM concentration measured in the kitchen was 5-fold (PM4, particle fraction ≥ 4 μm) and 5.3-fold (TSP, total PM) greater than the average concentration of these PM fractions over the same period. During the same measurement period in the printing office and in the beauty salon, the mean PM concentration was 10- and 4-fold (PM4) and 8- and 3-fold (TSP) respectively greater than the mean concentration of these PM fractions in outdoor air. In both facilities the main source of PM macro-components, especially organic carbon, were chemicals, which are normally used in such places - solvents, varnishes, paints, etc. The influence of some metals inflow from the outdoor air into indoor environment of those facilities was also recognized.

Expanding the Estimation of Surface PM2.5 from Aqua and Terra MODIS Aerosol Optical Depth in the EPA's AirNow Satellite Data Processor to Suomi NPP VIIRS

NASA Astrophysics Data System (ADS)

Szykman, J.; Kondragunta, S.; Zhang, H.; Dickerson, P.; van Donkelaar, A.; Martin, R. V.; Pasch, A. N.; White, J. E.; DeWinter, J. L.; Zahn, P. H.; Dye, T. S.; Haderman, M. D.

2012-12-01

The U.S. Environmental Protection Agency's (EPA) Air Quality Index (AQI) relies on hourly measurements of ground-based surface PM2.5 (particles smaller than 2.5 μm in median diameter) to develop daily AQI index maps. The EPA is improving the accuracy of AQI information and extending its coverage for reporting to the public by incorporating National Aeronautics and Space Administration (NASA) satellite-derived surface PM2.5 concentrations into daily AQI maps. The additional coverage will provide air quality information in regions without dense monitoring networks. The AirNow Satellite Data Processor (ASDP) uses daily PM2.5 estimates and uncertainties derived from average Aqua and Terra MODerate resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) in near real-time over the United States. The algorithm to derive surface PM2.5 from MODIS AOD relies on linear relationships between AOD and PM2.5 generated from multi-year GEOS-Chem model simulations (van Donkelaar et al., 2012). Parameters from the regression equation (slopes and intercepts) are saved in a lookup table (LUT) with 4 km spatial resolution for each day of a given year. To improve data accuracy and continuity, a filter is applied to remove MODIS AOD with low accuracy (e.g., over bright surfaces) and an inverse distance weighted average is applied to fill in gaps created by cloud coverage. Daily surface PM2.5 estimates and their uncertainties are generated at the National Oceanic and Atmospheric Administration (NOAA) using the van Donkelaar et al. algorithm and near real-time MODIS AOD products from Terra and Aqua and are provided to the EPA through its Infusing satellite Data into Environmental Applications (IDEA) website. The Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on October 28, 2011, and similar to MODIS, provides AOD products for real-time applications. NOAA plans to explore the value of VIIRS AOD products to improve AQI. This presentation will focus on a description of ASDP, including an overview of the algorithm used to estimate surface PM2.5 using satellite data and examples of high resolution VIIRS AOD products and their value to the ASDP. Disclaimer: Although this work was reviewed by the U.S. Environmental Protection Agency and approved for publication, it may not necessarily reflect official Agency policy.

Providing Context for Ambient Particulate Matter and Estimates of Attributable Mortality.

PubMed

McClellan, Roger O

2016-09-01

Four papers on fine particulate matter (PM2.5 ) by Anenberg et al., Fann et al., Shin et al., and Smith contribute to a growing body of literature on estimated epidemiological associations between ambient PM2.5 concentrations and increases in health responses relative to baseline notes. This article provides context for the four articles, including a historical review of provisions of the U.S. Clean Air Act as amended in 1970, requiring the setting of National Ambient Air Quality Standards (NAAQS) for criteria pollutants such as particulate matter (PM). The substantial improvements in both air quality for PM and population health as measured by decreased mortality rates are illustrated. The most recent revision of the NAAQS for PM2.5 in 2013 by the Environmental Protection Agency distinguished between (1) uncertainties in characterizing PM2.5 as having a causal association with various health endpoints, and as all-cause mortality, and (2) uncertainties in concentration--excess health response relationships at low ambient PM2.5 concentrations below the majority of annual concentrations studied in the United States in the past. In future reviews, and potential revisions, of the NAAQS for PM2.5 , it will be even more important to distinguish between uncertainties in (1) characterizing the causal associations between ambient PM2.5 concentrations and specific health outcomes, such as all-source mortality, irrespective of the concentrations, (2) characterizing the potency of major constituents of PM2.5 , and (3) uncertainties in the association between ambient PM2.5 concentrations and specific health outcomes at various ambient PM2.5 concentrations. The latter uncertainties are of special concern as ambient PM2.5 concentrations and health morbidity and mortality rates approach background or baseline rates. © 2016 Society for Risk Analysis.

Ambient Air Pollution and Atherosclerosis in Los Angeles

PubMed Central

Künzli, Nino; Jerrett, Michael; Mack, Wendy J.; Beckerman, Bernardo; LaBree, Laurie; Gilliland, Frank; Thomas, Duncan; Peters, John; Hodis, Howard N.

2005-01-01

Associations have been found between long-term exposure to ambient air pollution and cardiovascular morbidity and mortality. The contribution of air pollution to atherosclerosis that underlies many cardiovascular diseases has not been investigated. Animal data suggest that ambient particulate matter (PM) may contribute to atherogenesis. We used data on 798 participants from two clinical trials to investigate the association between atherosclerosis and long-term exposure to ambient PM up to 2.5 μm in aerodynamic diameter (PM2.5). Baseline data included assessment of the carotid intima-media thickness (CIMT), a measure of subclinical atherosclerosis. We geocoded subjects’ residential areas to assign annual mean concentrations of ambient PM2.5. Exposure values were assigned from a PM2.5 surface derived from a geostatistical model. Individually assigned annual mean PM2.5 concentrations ranged from 5.2 to 26.9 μg/m3 (mean, 20.3). For a cross-sectional exposure contrast of 10 μg/m3 PM2.5, CIMT increased by 5.9% (95% confidence interval, 1–11%). Adjustment for age reduced the coefficients, but further adjustment for covariates indicated robust estimates in the range of 3.9–4.3% (p-values, 0.05–0.1). Among older subjects (≥60 years of age), women, never smokers, and those reporting lipid-lowering treatment at baseline, the associations of PM2.5 and CIMT were larger with the strongest associations in women ≥60 years of age (15.7%, 5.7–26.6%). These results represent the first epidemiologic evidence of an association between atherosclerosis and ambient air pollution. Given the leading role of cardiovascular disease as a cause of death and the large populations exposed to ambient PM2.5, these findings may be important and need further confirmation. PMID:15687058

Estimating ground-level PM2.5 in eastern China using aerosol optical depth determined from the GOCI satellite instrument

NASA Astrophysics Data System (ADS)

Xu, J.-W.; Martin, R. V.; van Donkelaar, A.; Kim, J.; Choi, M.; Zhang, Q.; Geng, G.; Liu, Y.; Ma, Z.; Huang, L.; Wang, Y.; Chen, H.; Che, H.; Lin, P.; Lin, N.

2015-11-01

We determine and interpret fine particulate matter (PM2.5) concentrations in eastern China for January to December 2013 at a horizontal resolution of 6 km from aerosol optical depth (AOD) retrieved from the Korean geostationary ocean color imager (GOCI) satellite instrument. We implement a set of filters to minimize cloud contamination in GOCI AOD. Evaluation of filtered GOCI AOD with AOD from the Aerosol Robotic Network (AERONET) indicates significant agreement with mean fractional bias (MFB) in Beijing of 6.7 % and northern Taiwan of -1.2 %. We use a global chemical transport model (GEOS-Chem) to relate the total column AOD to the near-surface PM2.5. The simulated PM2.5 / AOD ratio exhibits high consistency with ground-based measurements in Taiwan (MFB = -0.52 %) and Beijing (MFB = -8.0 %). We evaluate the satellite-derived PM2.5 versus the ground-level PM2.5 in 2013 measured by the China Environmental Monitoring Center. Significant agreement is found between GOCI-derived PM2.5 and in situ observations in both annual averages (r2 = 0.66, N = 494) and monthly averages (relative RMSE = 18.3 %), indicating GOCI provides valuable data for air quality studies in Northeast Asia. The GEOS-Chem simulated chemical composition of GOCI-derived PM2.5 reveals that secondary inorganics (SO42-, NO3-, NH4+) and organic matter are the most significant components. Biofuel emissions in northern China for heating increase the concentration of organic matter in winter. The population-weighted GOCI-derived PM2.5 over eastern China for 2013 is 53.8 μg m-3, with 400 million residents in regions that exceed the Interim Target-1 of the World Health Organization.

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.

Mass concentration and elemental composition of indoor PM 2.5 and PM 10 in University rooms in Thessaloniki, northern Greece

NASA Astrophysics Data System (ADS)

Gemenetzis, Panagiotis; Moussas, Panagiotis; Arditsoglou, Anastasia; Samara, Constantini

The mass concentration and the elemental composition of PM 2.5 and PM 10 were measured in 40 rooms (mainly offices or mixed office-lab rooms, and photocopying places) of the Aristotle University of Thessaloniki, northern Greece. A total of 27 major, minor and trace elements were determined by ED-XRF analysis. The PM 2.5/PM 10 concentration ratios averaged 0.8±0.2, while the corresponding elemental ratios ranged between 0.4±0.2 and 0.9±0.2. The concentrations of PM 2.5 and PM 10 were significantly higher (by 70% and 50%, respectively) in the smokers' rooms compared to the non-smokers' places. The total elemental concentrations were also higher in the smokers' rooms (11.5 vs 8.2 μg m -3 for PM 2.5, and 10.3 vs 7.6 μg m -3 for PM 2.5-10). Fine particle concentrations (PM 2.5) were found to be quite proportional to smoking strength. On the contrary, the two environments exhibited similar coarse (PM 2.5-10) particle fractions not related to the number of cigarettes smoked. A slight decrease of particle concentrations with increasing the floor level was also observed, particularly for PM 2.5, suggesting that high-level floors are less impacted by near ground-level sources like traffic emissions. Finally, the removal efficiency of air purification systems was evaluated.

Effects of haze pollution on microbial community changes and correlation with chemical components in atmospheric particulate matter.

PubMed

Sun, Yujiao; Xu, Shangwei; Zheng, Danyang; Li, Jie; Tian, Hezhong; Wang, Yong

2018-05-10

In this study, particulate matter (PM) with aerodynamic diameters of ≤2.5 and ≤10 μm (PM 2.5 and PM 10 , respectively), which was found at different concentrations in spring, was collected in Beijing. The chemical composition and bacterial community diversity of PM were determined, and the relationship between them was studied by 16S rRNA sequencing and mathematical statistics. Chemical composition analysis revealed greater relative percentages of total organic compounds (TOC) and secondary ions (NO 3 - , SO 4 2- , and NH 4 + ). The concentrations of Ca 2+ , Na + , Mg 2+ , K + and SO 4 2- increased in high-concentration PM, which was associated with the contribution of soil, dust and soot. Microbiological analysis revealed 1191 operational taxonomic units. Microbial community structure was stable at the phylum level. The most abundant phyla were Proteobacteria, Actinobacteria, Firmicutes, Bacteroidetes and Cyanobacteria. Community clustering analysis at the genus level showed that the difference in bacterial community structure between different PM concentrations (clean air vs. smog) was greater than that between different particle sizes. The dominant genera varied in different concentrations of PM. An unclassified genus of Cyanobacteria and Comamonadaceae were most abundant in low- and high-concentration PM, respectively. The microbial community structure was dynamic at the genus level due to different environmental factors. The dominant bacteria in high-concentration PM were widely distributed in soils, indicating that the soil contributed more to the increase in the PM. The individual microbes that were detected did not increase significantly as the PM concentration increased. The bacterial community structure was strongly correlated with K + , Ca 2+ , Na + , Mg 2+ , SO 4 2- and TOC in high-concentration PM and had a good correlation with NO 3 - , Cl - , NH 4 + and TIC in low-concentration PM. Soil and dust contributed to the increase in the concentration of the particles, and the relevant chemical components also produced differences in the bacterial community structure in different concentrations of PM. Copyright © 2018. Published by Elsevier B.V.

Particulate emissions from a beef cattle feedlot using the flux-gradient technique.

PubMed

Bonifacio, Henry F; Maghirang, Ronaldo G; Trabue, Steven L; McConnell, Laura L; Prueger, John H; Razote, Edna B

2013-09-01

Data on air emissions from open-lot beef cattle () feedlots are limited. This research was conducted to determine fluxes of particulate matter with an aerodynamic diameter ≤10 μm (PM) from a commercial beef cattle feedlot in Kansas using the flux-gradient technique, a widely used micrometeorological method for air emissions from open sources. Vertical PM concentration profiles and micrometeorological parameters were measured at the feedlot using tapered element oscillating microbalance PM samplers and eddy covariance instrumentations (i.e., sonic anemometer and infrared hygrometer), respectively, from May 2010 through September 2011, representing feedlot conditions with air temperatures ranging from -24 to 39°C. Calculated hourly PM fluxes varied diurnally and seasonally, ranging up to 272 mg m h, with an overall median of 36 mg m h. For warm conditions (air temperature of 21 ± 10°C), the highest hourly PM fluxes (range 116-146 mg m h) were observed during the early evening period, from 2000 to 2100 h. For cold conditions (air temperature of -2 ± 8°C), the highest PM fluxes (range 14-27 mg m h) were observed in the afternoon, from 1100 to 1500 h. Changes in the hourly trend of PM fluxes coincided with changes in friction velocity, air temperature, sensible heat flux, and surface roughness. The PM emission was also affected by the pen surface water content, where a water content of at least 20% (wet basis) would be sufficient to effectively reduce PM emissions from pens by as much as 60%. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Spatial and indoor/outdoor gradients in urban concentrations of ultrafine particles and PM2.5 mass and chemical components

NASA Astrophysics Data System (ADS)

Zauli Sajani, Stefano; Ricciardelli, Isabella; Trentini, Arianna; Bacco, Dimitri; Maccone, Claudio; Castellazzi, Silvia; Lauriola, Paolo; Poluzzi, Vanes; Harrison, Roy M.

2015-02-01

In order to investigate relationships between outdoor air pollution and concentrations indoors, a novel design of experiment has been conducted at two sites, one heavily trafficked and the other residential. The novel design aspect involves the introduction of air directly to the centre of an unoccupied room by use of a fan and duct giving a controlled air exchange rate and allowing an evaluation of particle losses purely due to uptake on indoor surfaces without the losses during penetration of the building envelope which affect most measurement programmes. The rooms were unoccupied and free of indoor sources, and consequently reductions in particle concentration were due to deposition processes within the room alone. Measurements were made of indoor and outdoor concentrations of PM2.5, major chemical components and particle number size distributions. Despite the absence of penetration losses, indoor to outdoor ratios were very similar to those in other studies showing that deposition to indoor surfaces is likely to be the major loss process for indoor air. The results demonstrated a dramatic loss of nitrate in the indoor atmosphere as well as a selective loss of particles in the size range below 50 nm, in comparison to coarser particles. Depletion of indoor particles was greater during a period of cold weather with higher outdoor concentrations probably due to an enhancement of semi-volatile materials in the outdoor particulate matter. Indoor/outdoor ratios for PM2.5 were generally higher at the trafficked site than the residential site, but for particle number were generally lower, reflecting the different chemical composition and size distributions of particles at the two sites.

Measurements of size-fractionated concentration and bulk dry deposition of atmospheric particulate bound mercury

NASA Astrophysics Data System (ADS)

Fang, G. C.; Zhang, L.; Huang, C. S.

2012-12-01

Daily samples of size-fractionated (18, 10, 2.5 and 1.0 μm) particulate-bound mercury Hg(p) were collected using Micro-Orifice Uniform Deposition Impactors (MOUDI), on randomly selected days each month between November 2010 and July 2011, at a traffic site (Hungkuang), a wetland site (Gaomei), and an industrial site (Quanxing) in central Taiwan. Bulk dry deposition was also collected simultaneously using a surrogate surface. The nine-month average (±standard deviation) Hg(p) concentrations were 0.57 (±0.90), 0.17 (±0.27), and 0.94 (±0.92) ng m-3 at Hungkuang, Gaomei, and Quanxing, respectively. Concentrations in November and December were much higher than in the other months due to a combination of high local emissions and meteorological conditions. PM1.0 contributed more than 50% to the bulk concentration at the traffic and the industrial sites, but only contributed 25% at the wetland site. PM1.0-2.5 contributed 25%-50%, depending on location, to the bulk mass. Coarse fraction (PM2.5-18) contributed 7% at Hungkuang, 25% at Gaomei, and 19% at Quanxing. Samples with very high bulk concentrations had large fine fractions. Annual dry deposition estimated from the surrogate surface measurements was in the range of 30-85 μg m-2 yr-1 at the three sites. Coarse particulate Hg(p) were estimated to contribute 50-85% of the total Hg(p) dry deposition. Daily dry deposition velocities (Vd) ranged from 0.01 to 7.7 cm s-1. The annual Vd generated from the total measured fluxes was 0.34, 0.60 and 0.29 cm s-1 at Hungkuang, Gaomei, and Quanxing, respectively. These values can be reasonably reproduced using a size-resolved model and measured size fractions.

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.

Monitoring the impact of straw burning on particulate pollution using satellite and in-situ observations in the North China Plain

NASA Astrophysics Data System (ADS)

Zeng, C.

2015-12-01

The North China Plain is one of the main grain producing areas of China, but is also a severe straw burning zone. Winter wheat and summer corn harvests in this area usually occur from the beginning of Jun and Oct, respectively. After harvest, farmers usually burn out the remaining straw for convenience. However, straw burning can release a large quantity of air pollutants and can consequently result in a significant deterioration in regional air quality. To monitor the impact of straw burning on particulate pollution, daily MODIS thermal anomaly products (MOD14 and MYD14) were used to identify dates and regions of straw burning. Then the corresponding MODIS AOD products (MOD04 and MYD04) and particulate matter (PM) concentration observations from ground stations were integrated using a geostatistical method. By combining the accurate station-based PM observations and satellite data of well spatial coverage, PM concentration distribution maps were generated. Meanwhile, NCEP reanalysis data were used to obtain the corresponding surface wind pattern maps. Preliminary results show that satellite and station-based observations can indicate the impact of straw burning on PM pollution during harvest time. Air qualities during these times are obviously affected by the straw burning and surface wind field. Moreover, the air quality of the southeast study region is susceptible to the straw burning in adjacent areas due to the characteristic of the terrain.

Air quality in Delhi during the Commonwealth Games

NASA Astrophysics Data System (ADS)

Marrapu, P.; Cheng, Y.; Beig, G.; Sahu, S.; Srinivas, R.; Carmichael, G. R.

2014-10-01

Air quality during the Commonwealth Games (CWG, held in Delhi in October 2010) is analyzed using a new air quality forecasting system established for the games. The CWG stimulated enhanced efforts to monitor and model air quality in the region. The air quality of Delhi during the CWG had high levels of particles with mean values of PM2.5 and PM10 at the venues of 111 and 238 μg m-3, respectively. Black carbon (BC) accounted for ~ 10% of the PM2.5 mass. It is shown that BC, PM2.5 and PM10 concentrations are well predicted, but with positive biases of ~ 25%. The diurnal variations are also well captured, with both the observations and the modeled values showing nighttime maxima and daytime minima. A new emissions inventory, developed as part of this air quality forecasting initiative, is evaluated by comparing the observed and predicted species-species correlations (i.e., BC : CO; BC : PM2.5; PM2.5 : PM10). Assuming that the observations at these sites are representative and that all the model errors are associated with the emissions, then the modeled concentrations and slopes can be made consistent by scaling the emissions by 0.6 for NOx, 2 for CO, and 0.7 for BC, PM2.5, and PM10. The emission estimates for particles are remarkably good considering the uncertainty in the estimates due to the diverse spread of activities and technologies that take place in Delhi and the rapid rates of change. The contribution of various emission sectors including transportation, power, domestic and industry to surface concentrations are also estimated. Transport, domestic and industrial sectors all make significant contributions to PM levels in Delhi, and the sectoral contributions vary spatially within the city. Ozone levels in Delhi are elevated, with hourly values sometimes exceeding 100 ppb. The continued growth of the transport sector is expected to make ozone pollution a more pressing air pollution problem in Delhi. The sector analysis provides useful inputs into the design of strategies to reduce air pollution levels in Delhi. The contribution for sources outside of Delhi on Delhi air quality range from ~ 25% for BC and PM to ~ 60% for day time ozone. The significant contributions from non-Delhi sources indicates that in Delhi (as has been show elsewhere) these strategies will also need a more regional perspective.

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.

A GIS Based Approach for Assessing the Association between Air Pollution and Asthma in New York State, USA

PubMed Central

Gorai, Amit K.; Tuluri, Francis; Tchounwou, Paul B.

2014-01-01

Studies on asthma have shown that air pollution can lead to increased asthma prevalence. The aim of this study is to examine the association between air pollution (fine particulate matter (PM2.5), sulfur dioxide (SO2) and ozone (O3)) and human health (asthma emergency department visit rate (AEVR) and asthma discharge rate (ADR)) among residents of New York, USA during the period 2005 to 2007. Annual rates of asthma were calculated from population estimates for 2005, 2006, and 2007 and number of asthma hospital discharge and emergency department visits. Population data for New York were taken from US Bureau of Census, and asthma data were obtained from New York State Department of Health, National Asthma Survey surveillance report. Data on the concentrations of PM2.5, SO2 and ground level ozone were obtained from various air quality monitoring stations distributed in different counties. Annual means of these concentrations were compared to annual variations in asthma prevalence by using Pearson correlation coefficient. We found different associations between the annual mean concentration of PM2.5, SO2 and surface ozone and the annual rates of asthma discharge and asthma emergency visit from 2005 to 2007. A positive correlation coefficient was observed between the annual mean concentration of PM2.5, and SO2 and the annual rates of asthma discharge and asthma emergency department visit from 2005 to 2007. However, the correlation coefficient between annual mean concentrations of ground ozone and the annual rates of asthma discharge and asthma emergency visit was found to be negative from 2005 to 2007. Our study suggests that the association between elevated concentrations of PM2.5 and SO2 and asthma prevalence among residents of New York State in USA is consistent enough to assume concretely a plausible and significant association. PMID:24806193

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.

THE EXPOSURE PARADOX IN PARTICULATE MATTER COMMUNITY TIME-SERIES EPIDEMIOLOGY: CAN AMBIENT CONCENTRATIONS OF PM BE USED AS A SURROGATE FOR PERSONAL EXPOSURE TO PM ?

EPA Science Inventory

Objective: Explain why epidemiologic studies find a statistically significant relationship between ambient concentrations of PM and health effects even though only a near-zero correlation is found between ambient concentrations of PM and personal exposures to PM. Method: Consider...

Analysing temporal variability of particulate matter and possible contributing factors over Mahabaleshwar, a high-altitude station in Western Ghats, India

NASA Astrophysics Data System (ADS)

Leena, P. P.; Vijayakumar, K.; Anilkumar, V.; Pandithurai, G.

2017-11-01

Airborne particulate matter (PM) plays a vital role on climate change as well as human health. In the present study, temporal variability associated with mass concentrations of PM10, PM2.5, and PM1.0 were analysed using ground observations from Mahabaleswar (1348 m AMSL, 17.56 0N, 73.4 0E), a high-altitude station in the Western Ghats, India from June 2012 to May 2013. Concentrations of PM10, PM2.5, and PM1.0 showed strong diurnal, monthly, seasonal and weekday-weekend trends. The seasonal variation of PM1.0 and PM2.5 has showed highest concentrations during winter season compared to monsoon and pre-monsoon, but in the case of PM10 it showed highest concentrations in pre-monsoon season. Similarly, slightly higher PM concentrations were observed during weekends compared to weekdays. In addition, possible contributing factors to this temporal variability has been analysed based on the variation of secondary pollutants such as NO2, SO2, CO and O3 and long range transport of dust.

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.

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.

Preliminary analysis of variability in concentration of fine particulate matter - PM1.0, PM2.5 and PM10 in area of Poznań city

NASA Astrophysics Data System (ADS)

Sówka, Izabela; Chlebowska-Styś, Anna; Mathews, Barbara

2018-01-01

It is commonly known, that suspended particulate matter pose a threat to human life and health, negatively influence the flora, climate and also materials. Especially dangerous is the presence of high concentration of particulate matter in the area of cities, where density of population is high. The research aimed at determining the variability of suspended particulate matter concentration (PM1.0, PM2.5 and PM10) in two different thermal seasons, in the area of Poznań city. As a part of carried out work we analyzed the variability of concentrations and also performed a preliminary analysis of their correlation. Measured concentrations of particulate matter were contained within following ranges: PM10 - 8.7-69.6 μg/m3, PM2.5 - 2.2-88.5 μg/m3, PM1.0 - 2.5-22.9 μg/m3 in the winter season and 1.0-42.8 μg/m3 (PM10), 1.2-40.3 μg/m3 (PM2.5) and 2.7-10.4 (PM1.0) in the summer season. Preliminary correlative analysis indicated interdependence between the temperature of air, the speed of wind and concentration of particulate matter in selected measurement points. The values of correlation coefficients between the air temperature, speed of wind and concentrations of particulate matter were respectively equal to: for PM10: -0.59 and -0.55 (Jana Pawła II Street), -0.53 and -0.53 (Szymanowskiego Street), for PM2.5: -0.60 and -0.53 (Jana Pawła II Street) and for PM1.0 -0.40 and -0.59 (Jana Pawła II Street).

Modeling the feedback between aerosol and boundary layer processes: a case study in Beijing, China.

PubMed

Miao, Yucong; Liu, Shuhua; Zheng, Yijia; Wang, Shu

2016-02-01

Rapid development has led to frequent haze in Beijing. With mountains and sea surrounding Beijing, the pollution is found to be influenced by the mountain-plain breeze and sea-land breeze in complex ways. Meanwhile, the presence of aerosols may affect the surface energy balance and impact these boundary layer (BL) processes. The effects of BL processes on aerosol pollution and the feedback between aerosol and BL processes are not yet clearly understood. Thus, the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) is used to investigate the possible effects and feedbacks during a haze episode on 23 September 2011. Influenced by the onshore prevailing wind, sea-breeze, and upslope breeze, about 45% of surface particulate matter (PM)2.5 in Beijing are found to be contributed by its neighbor cities through regional transport. In the afternoon, the development of upslope breeze suppresses the growth of BL in Beijing by imposing a relatively low thermal stable layer above the BL, which exacerbates the pollution. Two kinds of feedback during the daytime are revealed as follows: (1) as the aerosols absorb and scatter the solar radiation, the surface net radiation and sensible heat flux are decreased, while BL temperature is increased, resulting in a more stable and shallower BL, which leads to a higher surface PM2.5 concentration in the morning and (2) in the afternoon, as the presence of aerosols increases the BL temperature over plains, the upslope breeze is weakened, and the boundary layer height (BLH) over Beijing is heightened, resulting in the decrease of the surface PM2.5 concentration there.

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.

Characterizing the Indoor-Outdoor Relationship of Fine Particulate Matter in Non-Heating Season for Urban Residences in Beijing

PubMed Central

Huang, Lihui; Pu, Zhongnan; Li, Mu; Sundell, Jan

2015-01-01

Objective Ambient fine particulate matter (PM2.5) pollution is currently a major public health concern in Chinese urban areas. However, PM2.5 exposure primarily occurs indoors. Given such, we conducted this study to characterize the indoor-outdoor relationship of PM2.5 mass concentrations for urban residences in Beijing. Methods In this study, 24-h real-time indoor and ambient PM2.5 mass concentrations were concurrently collected for 41 urban residences in the non-heating season. The diurnal variation of pollutant concentrations was characterized. Pearson correlation analysis was used to examine the correlation between indoor and ambient PM2.5 mass concentrations. Regression analysis with ordinary least square was employed to characterize the influences of a variety of factors on PM2.5 mass concentration. Results Hourly ambient PM2.5 mass concentrations were 3–280 μg/m3 with a median of 58 μg/m3, and hourly indoor counterpart were 4–193 μg/m3 with a median of 34 μg/m3. The median indoor/ambient ratio of PM2.5 mass concentration was 0.62. The diurnal variation of residential indoor and ambient PM2.5 mass concentrations tracked with each other well. Strong correlation was found between indoor and ambient PM2.5 mass concentrations on the community basis (coefficients: r≥0.90, p<0.0001), and the ambient data explained ≥84% variance of the indoor data. Regression analysis suggested that the variables, such as traffic conditions, indoor smoking activities, indoor cleaning activities, indoor plants and number of occupants, had significant influences on the indoor PM2.5 mass concentrations. Conclusions PM2.5 of ambient origin made dominant contribution to residential indoor PM2.5 exposure in the non-heating season under the high ambient fine particle pollution condition. Nonetheless, the large inter-residence variability of infiltration factor of ambient PM2.5 raised the concern of exposure misclassification when using ambient PM2.5 mass concentrations as exposure surrogates. PM2.5 of indoor origin still had minor influence on indoor PM2.5 mass concentrations, particularly at 11:00–13:00 and 22:00–0:00. The predictive models suggested that particles from traffic emission, secondary aerosols, particles from indoor smoking, resuspended particles due to indoor cleaning and particles related to indoor plants contributed to indoor PM2.5 mass concentrations in this study. Real-time ventilation measurements and improvement of questionnaire design to involve more variables subject to built environment were recommended to enhance the performance of the predictive models. PMID:26397734

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

NASA Astrophysics Data System (ADS)

Cobourn, W. Geoffrey

2010-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

The influence of model spatial resolution on simulated ozone and fine particulate matter for Europe: implications for health impact assessments

NASA Astrophysics Data System (ADS)

Fenech, Sara; Doherty, Ruth M.; Heaviside, Clare; Vardoulakis, Sotiris; Macintyre, Helen L.; O'Connor, Fiona M.

2018-04-01

We examine the impact of model horizontal resolution on simulated concentrations of surface ozone (O3) and particulate matter less than 2.5 µm in diameter (PM2.5), and the associated health impacts over Europe, using the HadGEM3-UKCA chemistry-climate model to simulate pollutant concentrations at a coarse (˜ 140 km) and a finer (˜ 50 km) resolution. The attributable fraction (AF) of total mortality due to long-term exposure to warm season daily maximum 8 h running mean (MDA8) O3 and annual-average PM2.5 concentrations is then calculated for each European country using pollutant concentrations simulated at each resolution. Our results highlight a seasonal variation in simulated O3 and PM2.5 differences between the two model resolutions in Europe. Compared to the finer resolution results, simulated European O3 concentrations at the coarse resolution are higher on average in winter and spring (˜ 10 and ˜ 6 %, respectively). In contrast, simulated O3 concentrations at the coarse resolution are lower in summer and autumn (˜ -1 and ˜ -4 %, respectively). These differences may be partly explained by differences in nitrogen dioxide (NO2) concentrations simulated at the two resolutions. Compared to O3, we find the opposite seasonality in simulated PM2.5 differences between the two resolutions. In winter and spring, simulated PM2.5 concentrations are lower at the coarse compared to the finer resolution (˜ -8 and ˜ -6 %, respectively) but higher in summer and autumn (˜ 29 and ˜ 8 %, respectively). Simulated PM2.5 values are also mostly related to differences in convective rainfall between the two resolutions for all seasons. These differences between the two resolutions exhibit clear spatial patterns for both pollutants that vary by season, and exert a strong influence on country to country variations in estimated AF for the two resolutions. Warm season MDA8 O3 levels are higher in most of southern Europe, but lower in areas of northern and eastern Europe when simulated at the coarse resolution compared to the finer resolution. Annual-average PM2.5 concentrations are higher across most of northern and eastern Europe but lower over parts of southwest Europe at the coarse compared to the finer resolution. Across Europe, differences in the AF associated with long-term exposure to population-weighted MDA8 O3 range between -0.9 and +2.6 % (largest positive differences in southern Europe), while differences in the AF associated with long-term exposure to population-weighted annual mean PM2.5 range from -4.7 to +2.8 % (largest positive differences in eastern Europe) of the total mortality. Therefore this study, with its unique focus on Europe, demonstrates that health impact assessments calculated using modelled pollutant concentrations, are sensitive to a change in model resolution by up to ˜ ±5 % of the total mortality across Europe.

Exposure Assessment for Atmospheric Ultrafine Particles (UFPs) and Implications in Epidemiologic Research

PubMed Central

Sioutas, Constantinos; Delfino, Ralph J.; Singh, Manisha

2005-01-01

Epidemiologic research has shown increases in adverse cardiovascular and respiratory outcomes in relation to mass concentrations of particulate matter (PM) ≤2.5 or ≤10 μm in diameter (PM2.5, PM10, respectively). In a companion article [Delfino RJ, Sioutas C, Malik S. 2005. Environ Health Perspect 113(8):934–946]), we discuss epidemiologic evidence pointing to underlying components linked to fossil fuel combustion. The causal components driving the PM associations remain to be identified, but emerging evidence on particle size and chemistry has led to some clues. There is sufficient reason to believe that ultrafine particles < 0.1 μm (UFPs) are important because when compared with larger particles, they have order of magnitudes higher particle number concentration and surface area, and larger concentrations of adsorbed or condensed toxic air pollutants (oxidant gases, organic compounds, transition metals) per unit mass. This is supported by evidence of significantly higher in vitro redox activity by UFPs than by larger PM. Although epidemiologic research is needed, exposure assessment issues for UFPs are complex and need to be considered before undertaking investigations of UFP health effects. These issues include high spatial variability, indoor sources, variable infiltration of UFPs from a variety of outside sources, and meteorologic factors leading to high seasonal variability in concentration and composition, including volatility. To address these issues, investigators need to develop as well as validate the analytic technologies required to characterize the physical/chemical nature of UFPs in various environments. In the present review, we provide a detailed discussion of key characteristics of UFPs, their sources and formation mechanisms, and methodologic approaches to assessing population exposures. PMID:16079062

Estimation of inhaled airborne particle number concentration by subway users in Seoul, Korea.

PubMed

Kim, Minhae; Park, Sechan; Namgung, Hyeong-Gyu; Kwon, Soon-Bark

2017-12-01

Exposure to airborne particulate matter (PM) causes several diseases in the human body. The smaller particles, which have relatively large surface areas, are actually more harmful to the human body since they can penetrate deeper parts of the lungs or become secondary pollutants by bonding with other atmospheric pollutants, such as nitrogen oxides. The purpose of this study is to present the number of PM inhaled by subway users as a possible reference material for any analysis of the hazards to the human body arising from the inhalation of such PM. Two transfer stations in Seoul, Korea, which have the greatest number of users, were selected for this study. For 0.3-0.422 μm PM, particle number concentration (PNC) was highest outdoors but decreased as the tester moved deeper underground. On the other hand, the PNC between 1 and 10 μm increased as the tester moved deeper underground and showed a high number concentration inside the subway train as well. An analysis of the particles to which subway users are actually exposed to (inhaled particle number), using particle concentration at each measurement location, the average inhalation rate of an adult, and the average stay time at each location, all showed that particles sized 0.01-0.422 μm are mostly inhaled from the outdoor air whereas particles sized 1-10 μm are inhaled as the passengers move deeper underground. Based on these findings, we expect that the inhaled particle number of subway users can be used as reference data for an evaluation of the hazards to health caused by PM inhalation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Particulate Matter Exposure in a Police Station Located near a Highway.

PubMed

Chen, Yu-Cheng; Hsu, Chin-Kai; Wang, Chia C; Tsai, Perng-Jy; Wang, Chun-Yuan; Chen, Mei-Ru; Lin, Ming-Yeng

2015-11-13

People living or working near roadways have experienced an increase in cardiovascular or respiratory diseases due to vehicle emissions. Very few studies have focused on the PM exposure of highway police officers, particularly for the number concentration and size distribution of ultrafine particles (UFP). This study evaluated exposure concentrations of particulate matter (PM) in the Sinying police station near a highway located in Tainan, Taiwan, under different traffic volumes, traffic types, and shift times. We focused on periods when the wind blew from the highway toward the police station and when the wind speed was greater than or equal to 0.5 m/s. PM2.5, UFP, and PM-PAHs concentrations in the police station and an upwind reference station were measured. Results indicate that PM2.5, UFP, and PM-PAHs concentrations in the police station can be on average 1.13, 2.17, and 5.81 times more than the upwind reference station concentrations, respectively. The highest exposure level for PM2.5 and UFP was observed during the 12:00 PM-4:00 PM shift while the highest PAHs concentration was found in the 4:00 AM-8:00 AM shift. Thus, special attention needs to be given to protect police officers from exposure to high PM concentration.

Study on the relationship between PM2.5 concentration and visibility in Beijing based on light scattering theory

NASA Astrophysics Data System (ADS)

Yang, YuFeng; Li, Ting

2018-02-01

The study of the relationship between transmittance visibility and PM2.5 concentration under the haze conditions has important theoretical significance for Free Space Optical communication (FSO). In this paper, the influence of PM2.5 concentration on the transmittance, attenuation coefficient and visibility was studied by light scattering theory, and the results by Mie theory and Monte Carlo method were analyzed. At the same time, the effect of PM2.5 particle size distribution on visibility was also analyzed, and the visibility calculated by light scattering method was compared with the visibility measured in Beijing from 2014 to 2016. The result shows that the higher PM2.5 concentration is the more obvious the multiple scattering effect is. When the mass concentration of PM2.5 is constant, the larger the geometric mean of the particle diameter is, the larger the visibility is. By comparing the visibility measured and the visibility calculated, we can see that when PM2.5 concentration is higher than 100μg/m3 , PM2.5 is the main factor affecting the visibility; and when PM2.5 concentration is lower than 100μg/m3, other factors (such as PM10, wind speed, air pressure and gas molecules) should also need to be considered.

Characterizations of atmospheric fungal aerosol in Beijing, China

NASA Astrophysics Data System (ADS)

Liang, Linlin; Engling, Guenter; He, Kebin; Du, Zhenyu

2013-04-01

Fungal aerosols constitute the most abundant fraction of biological aerosols in the atmosphere, influencing human health, the biosphere, atmospheric chemistry and climate. However, the total abundance of fungal spores in the atmosphere is still poorly understood and quantified. PM10 and PM2.5 samples were collected by high volume samplers simultaneously at a rural site (MY) and an urban site (THU) in Beijing, China. Various carbohydrates were quantified by high-performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD), including the sugar alcohols mannitol and arabitol, proposed as molecular tracers for fungal aerosol. The annual average concentrations of arabitol in PM2.5 and PM10 at the THU site were 7.4±9.4 ng/m3 and 10.3±9.5 ng/m3, and the respective mannitol concentrations were 21.0±20.4 ng/m3 and 31.9±26.9 ng/m3. Compared to PM10, the monthly average concentrations of arabitol and mannitol in PM2.5 did not vary significantly and were present at nearly consistent levels in the different seasons. Moreover, during summer and autumn higher arabitol and mannitol levels than during spring and winter were observed in coarse particles, probably due to different dominant sources of fungal spores in different seasons. In the dry period (i.e., winter and spring) in Beijing, probably only the suspension from exposed surfaces, (e.g., soil resuspension, transported dust, etc.) can be regarded as the main sources for fungal aerosols. On the other hand, in summer and autumn, fungal spores in the atmosphere can be derived from more complex sources, including plants, vegetation decomposition and agricultural activity, such as ploughing; these fungal spore sources may contribute more to coarse PM. Mannitol and arabitol correlated well with each other, both in PM10 (R2 = 0.71) and PM2.5 (R2 = 0.81). Although fungal spore levels at rural sites were consistently higher than those at urban sites in other studies, the findings in our study were reversed, indicating a high abundance of fungal spores in the urban area of Beijing, China. Meteorological conditions were shown to have complex effects on the ambient concentrations of fungal spores: the concentrations of arabitol exhibited positive correlation with temperature below 30.0 °C, negative correlation with wind speed higher than 0.6 m/s, no relationship with solar radiation and the highest arabitol levels were mainly associated with RH in the range of 51-70%.

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

NASA Technical Reports Server (NTRS)

Chudnovsky, Alexandra A.; Koutrakis, Petros; Kloog, Itai; Melly, Steven; Nordio, Francesco; Lyapustin, Alexei; Wang, Jujie; Schwartz, Joel

2014-01-01

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

Distribution and transportation of mercury from glacier to lake in the Qiangyong Glacier Basin, southern Tibetan Plateau, China.

PubMed

Sun, Shiwei; Kang, Shichang; Huang, Jie; Li, Chengding; Guo, Junming; Zhang, Qianggong; Sun, Xuejun; Tripathee, Lekhendra

2016-06-01

The Tibetan Plateau is home to the largest aggregate of glaciers outside the Polar Regions and is a source of fresh water to 1.4 billion people. Yet little is known about the transportation and cycling of Hg in high-elevation glacier basins on Tibetan Plateau. In this study, surface snow, glacier melting stream water and lake water samples were collected from the Qiangyong Glacier Basin. The spatiotemporal distribution and transportation of Hg from glacier to lake were investigated. Significant diurnal variations of dissolved Hg (DHg) concentrations were observed in the river water, with low concentrations in the morning (8:00am-14:00pm) and high concentrations in the afternoon (16:00pm-20:00pm). The DHg concentrations were exponentially correlated with runoff, which indicated that runoff was the dominant factor affecting DHg concentrations in the river water. Moreover, significant decreases of Hg were observed during transportation from glacier to lake. DHg adsorption onto particulates followed by the sedimentation of particulate-bound Hg (PHg) could be possible as an important Hg removal mechanism during the transportation process. Significant decreases in Hg concentrations were observed downstream of Xiao Qiangyong Lake, which indicated that the high-elevation lake system could significantly affect the distribution and transportation of Hg in the Qiangyong Glacier Basin. Copyright © 2016. Published by Elsevier B.V.

Respiratory Effects of Fine and Ultrafine Particles from Indoor Sources—A Randomized Sham-Controlled Exposure Study of Healthy Volunteers

PubMed Central

Soppa, Vanessa J.; Schins, Roel P. F.; Hennig, Frauke; Hellack, Bryan; Quass, Ulrich; Kaminski, Heinz; Kuhlbusch, Thomas A. J.; Hoffmann, Barbara; Weinmayr, Gudrun

2014-01-01

Particulate air pollution is linked to impaired respiratory health. We analyzed particle emissions from common indoor sources (candles burning (CB), toasting bread (TB), frying sausages (FS)) and lung function in 55 healthy volunteers (mean age 33.0 years) in a randomized cross-over controlled exposure study. Lung-deposited particle surface area concentration (PSC), size-specific particle number concentration (PNC) up to 10 µm, and particle mass concentration (PMC) of PM1, PM2.5 and PM10 were determined during exposure (2 h). FEV1, FVC and MEF25%–75% was measured before, 4 h and 24 h after exposure. Wilcoxon-rank sum tests (comparing exposure scenarios) and mixed linear regression using particle concentrations and adjusting for personal characteristics, travel time and transportation means before exposure sessions were performed. While no effect was seen comparing the exposure scenarios and in the unadjusted model, inverse associations were found for PMC from CB and FS in relation to FEV1 and MEF25%–75%. with a change in 10 µg/m3 in PM2.5 from CB being associated with a change in FEV1 of −19 mL (95%-confidence interval:−43; 5) after 4 h. PMC from TB and PNC of UFP were not associated with lung function changes, but PSC from CB was. Elevated indoor fine particles from certain sources may be associated with small decreases in lung function in healthy adults. PMID:25000149

Evolution of the spatiotemporal pattern of PM2.5 concentrations in China - A case study from the Beijing-Tianjin-Hebei region

NASA Astrophysics Data System (ADS)

Yan, Dan; Lei, Yalin; Shi, Yukun; Zhu, Qing; Li, Li; Zhang, Zhien

2018-06-01

Atmospheric haze pollution has become a global concern because of its severe effects on human health and the environment. The Beijing-Tianjin-Hebei urban agglomeration is located in northern China, and its haze is the most serious in China. The high concentration of PM2.5 is the main cause of haze pollution, and thus investigating the temporal and spatial characteristics of PM2.5 is important for understanding the mechanisms underlying PM2.5 pollution and for preventing haze. In this study, the PM2.5 concentration status in 13 cities from the Beijing-Tianjin-Hebei region was statistically analyzed from January 2016 to November 2016, and the spatial variation of PM2.5 was explored via spatial autocorrelation analysis. The research yielded three overall results. (1) The distribution of PM2.5 concentrations in this area varied greatly during the study period. The concentrations increased from late autumn to early winter, and the spatial range expanded from southeast to northwest. In contrast, the PM2.5 concentration decreased rapidly from late winter to early spring, and the spatial range narrowed from northwest to southeast. (2) The spatial dependence degree, by season from high to low, was in the order winter, autumn, spring, summer. Winter (from December to February of the subsequent year) and summer (from June to August) were, respectively, the highest and lowest seasons with regard to the spatial homogeneity of PM2.5 concentrations. (3) The PM2.5 concentration in the Beijing-Tianjin-Hebei region has significant spatial spillovers. Overall, cities far from Bohai Bay, such as Shijiazhuang and Hengshui, demonstrated a high-high concentration of PM2.5 pollution, while coastal cities, such as Chengde and Qinhuangdao, showed a low-low concentration.

The classification of PM10 concentrations in Johor Based on Seasonal Monsoons

NASA Astrophysics Data System (ADS)

Hamid, Hazrul Abdul; Hanafi Rahmat, Muhamad; Aisyah Sapani, Siti

2018-04-01

Air is the most important living resource in life. Contaminated air could adversely affect human health and the environment, especially during the monsoon season. Contamination occurs as a result of human action and haze. There are several pollutants present in the air where one of them is PM10. Secondary data was obtained from the Department of Environment from 2010 until 2014 and was analyzed using the hourly average of PM10 concentrations. This paper examined the relation between PM10 concentrations and the monsoon seasons (Northeast Monsoon and Southwest Monsoon) in Larkin and Pasir Gudang. It was expected that the concentration of PM10 would be higher during the Southwest Monsoon as it is a dry season. The data revealed that the highest PM10 concentrations were recorded between 2010 to 2014 during this particular monsoon season. The characteristics of PM10 concentration were compared using descriptive statistics based on the monsoon seasons and classified using the hierarchical cluster analysis (Ward Methods). The annual average of PM10 concentration during the Southwest Monsoon had exceeded the standard set by the Malaysia Ambient Air Quality Guidelines (50 μg/m3) while the PM10 concentration during the Northeast Monsoon was below the acceptable level for both stations. The dendrogram displayed showed two clusters for each monsoon season for both stations excepted for the PM10 concentration during the Northeast Monsoon in Larkin which was classified into three clusters due to the haze in 2010. Overall, the concentration of PM10 in 2013 was higher based on the clustering shown for every monsoon season at both stations according to the characteristics in the descriptive statistics.

Source apportionment of speciated PM2.5 over Halifax, Nova Scotia, during BORTAS-B, using pragmatic mass closure and principal component analysis

NASA Astrophysics Data System (ADS)

Gibson, Mark D.; Kuchta, James; Chisholm, Lucy; Duck, Tom; Hopper, Jason; Beauchamp, Stephen; Waugh, David; King, Gavin; Pierce, Jeffrey; Li, Zhengyan; Leaitch, Richard; Ward, Tony J.; Haelssig, Jan; Palmer, Paul I.

2013-04-01

During BORTAS-B, 42 days of contiguous PM2.5 filter samples were collected during the summer of 2011 in Halifax, Nova Scotia. The aim of the PM2.5 filter sampling was to apportion the source contribution to the total PM2.5 mass concentration in Halifax to inform and validate other surface measurements and chemical transport models related to BORTAS-B. Sampling was conducted on the roof of a Dalhousie University building at a height of 15 m. The building is located in a residential area of Halifax. Continuous black carbon (BC) was measured using a Magee AE-42 aethalometer. Continuous organic carbon was measured using an Aerodyne, Aerosol Chemical Speciation Monitor. Daily teflon filter samples were collected for the determination of fine particulate with a median aerodynamic diameter less than or equal to 2.5 microns (PM2.5). An additional, daily, nylon filter was used for the determination of PM2.5 cations and anions by IC. The PM2.5 teflon filter was analysed for 33 metals by XRF and 10 trace metals by ICP-MS. The biomass burning marker levoglucosan was analysed by GC-MS following derivatization. Excellent agreement (R2 = 0.88) was observed between continuous and filter based measurements with a gradient of 2.76. The median (min : max) PM2.5 mass concentration during BORTAS-B = 3.9 (0.08 : 13.7) μg-m3. The median (min : max) continuous BC = 0.39 (0.12 : 1.03); SO4 = 0.47 (0.14 : 5.59); NO3 = 0.067 (0.007 : 0.64); OC = 0.77 (0.18 : 2.77); NH4 = 0.15 (0:003 : 1.45); Cl = 0.011 (0.0019 : 0.32); Fe = 0.018 (0.0011 : 0.097); Al = 0.011 (0.0091 : 0.086); Si = 0.03 (0.0044 : 0.29); V = 0.0026 (0.0016 : 0.017) and Ni = 0.0007 (0.0005 : 0.0037) μg-m3 respectively. Absolute principal component scores (APCS) and pragmatic mass closure (PMC) will be used to identify the sources driving the observed PM2.5 variability over Halifax, during BORTAS-B. A comparison of APCS and PMC PM2.5 receptor model output results will be presented. These model data will provide further insight into the source contribution to summertime surface PM2.5 mass in Halifax, Nova Scotia, Canada.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Daily Kilometer-Scale MODIS Satellite Maps of PM2.5 Describe Wintertime Episodes

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Sorek Hamer, Meytar; Lyapustin, Alexei; Wang, Yujie

2017-01-01

The San Joaquin Valley (SJV) suffers from severe health-endangering episodes of PM2.5 aerosol loadings in wintertime; episodes last approximately 5 days and differ in geographical distribution and composition. PM2.5 stations are scattered; consequently the use of remote sensing to map variable regional patterns of these varying respirable aerosol concentrations is desirable. High-precision AOT retrievals can capture column particulate loading. However,PM2.5 mapping is challenging due to several reasons: particularly thin mixed layers (ML) and thus relatively low aerosol optical thickness (AOT) close to current measurement limits, variable and a typical composition of the aerosols, and complex surface bidirectional reflectance. However, the West does present some advantages in analysis. Air basins are isolated from long-distance transport, and experience predominant strong meteorological subsidence. Thus these Western basin regions have fewer problematic cases of overriding aerosol layers detached from the surface. To counter such local overriding, Chu et al. have described an approach for the Eastern US, and He et al have described a synoptic classification approach useful in Shanghai. The Bay Area Air Quality Management District (BAAQMD) expands our experience with the use of AOT, with lower PM2.5 and several isolated sub-basins. We have prepared daily maps of episodes in each region. We present also a sequence of increasingly detailed statistical models, AOT initially appears to contribute little information; however, inclusion of weather information reveals its utility. Lyapustin and Wang's MultiAngle Implementation of Atmospheric Correction (MAIAC) retrieval for AOT provided the most useful operational remote sensing information for these regions. It provides high (1-km) spatial resolution maps and a high percentage of availability. Empirical regression methods have found that random effects regression models (aka mixed effects models, ME) employing AOT provide good estimates of ground PM2.5 concentrations.Here, we attempt to extend these methods and evaluate the usefulness of AOT with greater physical analysis, based on DISCOVER-AQ4 experience.

Influence of haze pollution on water-soluble chemical species in PM2.5 and size-resolved particles at an urban site during fall.

PubMed

Yu, Geun-Hye; Zhang, Yan; Cho, Sung-Yong; Park, Seungshik

2017-07-01

To investigate the influence of haze on the chemical composition and formation processes of ambient aerosol particles, PM 2.5 and size-segregated aerosol particles were collected daily during fall at an urban site of Gwangju, Korea. During the study period, the total concentration of secondary ionic species (SIS) contributed an average of 43.9% to the PM 2.5 , whereas the contribution of SIS to the PM 2.5 during the haze period was 62.3%. The NO 3 - and SO 4 2- concentrations in PM 2.5 during the haze period were highly elevated, being 13.4 and 5.0 times higher than those during non-haze period, respectively. The PM, NO 3 - , SO 4 2- , oxalate, water-soluble organic carbon (WSOC), and humic-like substances (HULIS) had tri-modal size distributions peaks at 0.32, 1.0, and 5.2μm during the non-haze and haze periods. However, during the non-haze period they exhibited dominant size distributions at the condensation mode peaking at 0.32μm, while on October 21 when the heaviest haze event occurred, they had predominant droplet mode size distributions peaking at 1.00μm. Moreover, strong correlations of WSOC and HULIS with SO 4 2- , oxalate, and K + at particle sizes of <1.8μm indicate that secondary processes and emissions from biomass burning could be responsible for WSOC and HULIS formations. It was found that the factors affecting haze formation could be the local stable synoptic conditions, including the weak surface winds and high surface pressures, the long-range transportation of haze from eastern China and upwind regions of the Korean peninsula, as well as the locally emitted and produced aerosol particles. Copyright © 2016. Published by Elsevier B.V.

Normal and anomalous diffusion in fluctuations of dust concentration nearby emission source

NASA Astrophysics Data System (ADS)

Szczurek, Andrzej; Maciejewska, Monika; Wyłomańska, Agnieszka; Sikora, Grzegorz; Balcerek, Michał; Teuerle, Marek

2018-02-01

Particulate matter (PM) is an important component of air. Nowadays, major attention is payed to fine dust. It has considerable environmental impact, including adverse effect on human health. One of important issues regarding PM is the temporal variation of its concentration. The variation contains information about factors influencing this quantity in time. The work focuses on the character of PM concentration dynamics indoors, in the vicinity of emission source. The objective was to recognize between the homogeneous or heterogeneous dynamics. The goal was achieved by detecting normal and anomalous diffusion in fluctuations of PM concentration. For this purpose we used anomalous diffusion exponent, β which was derived from Mean Square Displacement (MSD) analysis. The information about PM concentration dynamics may be used to design sampling strategy, which serves to attain representative information about PM behavior in time. The data analyzed in this work was collected from single-point PM concentration monitoring in the vicinity of seven emission sources in industrial environment. In majority of cases we observed heterogeneous character of PM concentration dynamics. It confirms the complexity of interactions between the emission sources and indoor environment. This result also votes against simplistic approach to PM concentration measurement indoors, namely their occasional character, short measurement periods and long term averaging.

Particulate Matter over the Western Mediterranean sea: new insights gained from data collected during the 2011, 2012 and 2015 CNR research cruise campaigns

NASA Astrophysics Data System (ADS)

Castagna, Jessica; D'Amore, Francesco; Naccarato, Attilio; Moretti, Sacha; Mannarino, Valentino; Bencardino, Mariantonia; Sprovieri, Francesca; Pirrone, Nicola

2017-04-01

The Mediterranean basin, due to its unique geographic position and its peculiar meteo-climatic conditions, appears to be an area with a relevant pollution load. Significant is the contribution of dense ship traffic and highly industrialized population centres surrounding the basin itself but a large influence is also due to geological sources like Saharan dust and volcanic ashes. The transport of both natural dust and anthropogenic aerosols into the marine environment involves considerable interest, not least for its potential impact on marine ecosystems, world climate and air quality. However, whereas there is already a large monitoring database measuring air pollution at surface land-based sites and in ports, there is a relatively little information on atmospheric aerosol directly measured at sea. In order to fill in the gap of observations in the Mediterranean basin and to gain more insight into the atmospheric dynamical and chemical mechanisms leading to high surface Particulate Matter (PM) levels, the Institute of Atmospheric Pollution of the National Research Council (CNR-IIA), since 2003, has started regular ship-borne measurements over the Mediterranean Sea. In the present work we will specifically focus on PM observations obtained, travelling on the sea, during three cruise campaigns performed during autumn 2011, summer 2012 and summer 2015, along different tracks and almost covering the Western Mediterranean sector. We specifically recorded two, gravimetrically determined, PM size fraction mass concentrations (PM2.5 and PM10), whose major and trace elemental composition was subsequently obtained by chemical analysis with an Inductively Coupled Plasma Mass Spectrometer (ICP-MS). Overall, we obtained 40 days of data observations whose analysis contributes to investigate the causes of aerosol pollution in this area. Data on PM mass concentrations showed a quite high variability ranging from 10.5 to 38.8 μg.m-3 for the PM10, and from 5.5 to 29.7 μg.m-3 for the PM2.5 size fraction, respectively. Meteorological conditions, at both local and synoptic scales, were jointly investigated with PM levels to highlight seasonal influence and to identify potential long-range transport events. Data on elemental composition were also used as input data for a Principal Component Analysis (PCA), whose results gave us some qualitative understanding on the sources with major impact on the investigated Mediterranean sector.

Comprehensive characterization of PM2.5 aerosols in Singapore

NASA Astrophysics Data System (ADS)

Balasubramanian, R.; Qian, W.-B.; Decesari, S.; Facchini, M. C.; Fuzzi, S.

2003-08-01

A comprehensive characterization of PM2.5 aerosols collected in Singapore from January through December 2000 is presented. The annual average mass concentration of PM2.5 was 27.2 μg/m3. The atmospheric loading of PM2.5 was elevated sporadically from March through May, mainly due to advection of biomass burning (deliberate fires to clear plantation areas) impacted air masses from Sumatra, Indonesia. Satellite images of the area, trajectory calculations, and surface wind direction data are in support of the transport of pyrogenic products from Sumatra toward Singapore. Aerosol samples collected during the dry season were analyzed for water-soluble ions, water-soluble organic compounds (WSOC), elemental carbon (EC), organic carbon, and trace elements using a number of analytical techniques. The major components were sulfate, EC, water-soluble carbonaceous materials, and water-insoluble carbonaceous materials. Aerosol WSOC were characterized based on a combination of chromatographic separations by ion exchange chromatography, functional group investigation by proton nuclear magnetic resonance, and total organic carbon determination. The comprehensive chemical characterization of PM2.5 particles revealed that both non-sea-salt sufate (nss-SO42-) and carbonaceous aerosols mainly contributed to the increase in the mass concentration of aerosols during the smoke haze period. Using a mass closure test (a mass balance), we determined whether the physical measurement of gravimetric fine PM concentration of a sample is equal to the summed concentrations of the individually identified chemical constituents (measured or inferred) in the sample. The sum of the determined groups of aerosol components and the gravimetrically determined mass agreed reasonably well. Principal component analysis was performed from the combined data set, and five factors were observed: a soil dust component, a metallurgical industry factor, a factor representing emissions from biomass burning and automobiles, a sea-salt component, and an oil combustion factor.

Evaluating the influences of biomass burning during 2006 BASE-ASIA: a regional chemical transport modeling

NASA Astrophysics Data System (ADS)

Fu, J. S.; Hsu, N. C.; Gao, Y.; Huang, K.; Li, C.; Lin, N.-H.; Tsay, S.-C.

2011-12-01

To evaluate the impact of biomass burning from Southeast Asia to East Asia, this study conducted numerical simulations during NASA's 2006 Biomass-burning Aerosols in South-East Asia: Smoke Impact Assessment (BASE-ASIA). Two typical episode periods (27-28 March and 13-14 April) were examined. Two emission inventories, FLAMBE and GFED, were used in the simulations. The influences during two episodes in the source region (Southeast Asia) contributed to the surface CO, O3 and PM2.5 concentrations as high as 400 ppbv, 20 ppbv and 80 μg m-3, respectively. The perturbations with and without biomass burning of the above three species during the intense episodes were in the range of 10 to 60%, 10 to 20% and 30 to 70%, respectively. The impact due to long-range transport could spread over the southeastern parts of East Asia and could reach about 160 to 360 ppbv, 8 to 18 ppbv and 8 to 64 μg m-3 on CO, O3 and PM2.5, respectively; the percentage impact could reach 20 to 50% on CO, 10 to 30% on O3, and as high as 70% on PM2.5. In March, the impact of biomass burning was mainly concentrated in Southeast Asia and Southern China, while in April the impact becomes slightly broader, potentially including the Yangtze River Delta region. Two cross-sections at 15° N and 20° N were used to compare the vertical flux of biomass burning. In the source region (Southeast Asia), CO, O3 and PM2.5 concentrations had a strong upward transport from surface to high altitudes. The eastward transport becomes strong from 2 to 8 km in the free troposphere. The subsidence process during the long-range transport contributed 60 to 70%, 20 to 50%, and 80% to CO, O3 and PM2.5, respectively to surface in the downwind area. The study reveals the significant impact of Southeastern Asia biomass burning on the air quality in both local and downwind areas, particularly during biomass burning episodes. This modeling study might provide lower limit constraints. An additional study is underway for an active biomass burning year to obtain an upper limit and climate effects.

Evaluating the influences of biomass burning during 2006 BASE-ASIA: a regional chemical transport modeling

NASA Astrophysics Data System (ADS)

Fu, J. S.; Hsu, N. C.; Gao, Y.; Huang, K.; Li, C.; Lin, N.-H.; Tsay, S.-C.

2012-05-01

To evaluate the impact of biomass burning from Southeast Asia to East Asia, this study conducted numerical simulations during NASA's 2006 Biomass-burning Aerosols in South-East Asia: Smoke Impact Assessment (BASE-ASIA). Two typical episode periods (27-28 March and 13-14 April) were examined. Two emission inventories, FLAMBE and GFED, were used in the simulations. The influences during two episodes in the source region (Southeast Asia) contributed to the surface CO, O3 and PM2.5 concentrations as high as 400 ppbv, 20 ppbv and 80 μg m-3, respectively. The perturbations with and without biomass burning of the above three species during the intense episodes were in the range of 10 to 60%, 10 to 20% and 30 to 70%, respectively. The impact due to long-range transport could spread over the southeastern parts of East Asia and could reach about 160 to 360 ppbv, 8 to 18 ppbv and 8 to 64 μg m-3 on CO, O3 and PM2.5, respectively; the percentage impact could reach 20 to 50% on CO, 10 to 30% on O3, and as high as 70% on PM2.5. In March, the impact of biomass burning mainly concentrated in Southeast Asia and southern China, while in April the impact becomes slightly broader and even could go up to the Yangtze River Delta region. Two cross-sections at 15° N and 20° N were used to compare the vertical flux of biomass burning. In the source region (Southeast Asia), CO, O3 and PM2.5 concentrations had a strong upward transport from surface to high altitudes. The eastward transport becomes strong from 2 to 8 km in the free troposphere. The subsidence process during the long-range transport contributed 60 to 70%, 20 to 50%, and 80% on CO, O3 and PM2.5, respectively to surface in the downwind area. The study reveals the significant impact of Southeastern Asia biomass burning on the air quality in both local and downwind areas, particularly during biomass burning episodes. This modeling study might provide constraints of lower limit. An additional study is underway for an active biomass burning year to obtain an upper limit and climate effects.

Comparison of Hourly PM2.5 Observations Between Urban and Suburban Areas in Beijing, China.

PubMed

Yao, Ling; Lu, Ning; Yue, Xiafang; Du, Jia; Yang, Cundong

2015-09-29

Hourly PM2.5 observations collected at 12 stations over a 1-year period are used to identify variations between urban and suburban areas in Beijing. The data demonstrates a unique monthly variation form, as compared with other major cities. Urban areas suffer higher PM2.5 concentration (about 92 μg/m³) than suburban areas (about 77 μg/m³), and the average PM2.5 concentration in cold season (about 105 μg/m³) is higher than warm season (about 78 μg/m³). Hourly PM2.5 observations exhibit distinct seasonal, diurnal and day-of-week variations. The diurnal variation of PM2.5 is observed with higher concentration at night and lower value at daytime, and the cumulative growth of nighttime (22:00 p.m. in winter) PM2.5 concentration maybe due to the atmospheric stability. Moreover, annual average PM2.5 concentrations are about 18 μg/m³ higher on weekends than weekdays, consistent with driving restrictions on weekdays. Additionally, the nighttime peak in weekdays (21:00 p.m.) is one hour later than weekends (20:00 p.m.) which also shows the evidence of human activity. These observed facts indicate that the variations of PM2.5 concentration between urban and suburban areas in Beijing are influenced by complex meteorological factors and human activities.

Comparison of Hourly PM2.5 Observations Between Urban and Suburban Areas in Beijing, China

PubMed Central

Yao, Ling; Lu, Ning; Yue, Xiafang; Du, Jia; Yang, Cundong

2015-01-01

Hourly PM2.5 observations collected at 12 stations over a 1-year period are used to identify variations between urban and suburban areas in Beijing. The data demonstrates a unique monthly variation form, as compared with other major cities. Urban areas suffer higher PM2.5 concentration (about 92 μg/m3) than suburban areas (about 77 μg/m3), and the average PM2.5 concentration in cold season (about 105 μg/m3) is higher than warm season (about 78 μg/m3). Hourly PM2.5 observations exhibit distinct seasonal, diurnal and day-of-week variations. The diurnal variation of PM2.5 is observed with higher concentration at night and lower value at daytime, and the cumulative growth of nighttime (22:00 p.m. in winter) PM2.5 concentration maybe due to the atmospheric stability. Moreover, annual average PM2.5 concentrations are about 18 μg/m3 higher on weekends than weekdays, consistent with driving restrictions on weekdays. Additionally, the nighttime peak in weekdays (21:00 p.m.) is one hour later than weekends (20:00 p.m.) which also shows the evidence of human activity. These observed facts indicate that the variations of PM2.5 concentration between urban and suburban areas in Beijing are influenced by complex meteorological factors and human activities. PMID:26426035

Contribution of mycosporine-like amino acids and colored dissolved and particulate matter to sea ice optical properties and ultraviolet attenuation

PubMed Central

Uusikivi, Jari; Vähätalo, Anssi V.; Granskog, Mats A.; Sommaruga, Ruben

2010-01-01

In the Baltic Sea ice, the spectral absorption coefficients for particulate matter (PM) were about two times higher at ultraviolet wavelengths than at photosynthetically available radiation (PAR) wavelengths. PM absorption spectra included significant absorption by mycosporine-like amino acids (MAAs) between 320 and 345 nm. In the surface ice layer, the concentration of MAAs (1.37 μg L−1) was similar to that of chlorophyll a, resulting in a MAAs-to-chlorophyll a ratio as high as 0.65. Ultraviolet radiation (UVR) intensity and the ratio of UVR to PAR had a strong relationship with MAAs concentration (R2 = 0.97, n = 3) in the ice. In the surface ice layer, PM and especially MAAs dominated the absorption (absorption coefficient at 325 nm: 0.73 m−1). In the columnar ice layers, colored dissolved organic matter was the most significant absorber in the UVR (< 380 nm) (absorption coefficient at 325 nm: 1.5 m−1). Our measurements and modeling of UVR and PAR in Baltic Sea ice show that organic matter, both particulate and dissolved, influences the optical properties of sea ice and strongly modifies the UVR exposure of biological communities in and under snow-free sea ice. PMID:20585592

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

PubMed

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

2018-05-30

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

Improve EPA's AIRNow Air Quality Index Maps with NASA/NOAA Satellite Data

NASA Astrophysics Data System (ADS)

Pasch, A.; Zahn, P. H.; DeWinter, J. L.; Haderman, M. D.; White, J. E.; Dickerson, P.; Dye, T. S.; Martin, R. V.

2011-12-01

The U.S. Environmental Protection Agency's (EPA) AIRNow program provides maps of real-time hourly Air Quality Index (AQI) conditions and daily AQI forecasts nationwide (http://www.airnow.gov). The public uses these maps to make decisions concerning their respiratory health. The usefulness of the AIRNow air quality maps depends on the accuracy and spatial coverage of air quality measurements. Currently, the maps use only ground-based measurements, which have significant gaps in coverage in some parts of the United States. As a result, contoured AQI levels have high uncertainty in regions far from monitors. To improve the usefulness of air quality maps, scientists at EPA and Sonoma Technology, Inc. are working in collaboration with the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and university researchers on a project to incorporate additional measurements into the maps via the AIRNow Satellite Data Processor (ASDP). These measurements include estimated surface PM

High Proportions of Sub-micron Particulate Matter in Icelandic Dust Storms in 2015

NASA Astrophysics Data System (ADS)

Dagsson Waldhauserova, Pavla; Arnalds, Olafur; Olafsson, Haraldur; Magnusdottir, Agnes

2017-04-01

Iceland is extremely active dust region and desert areas of over 44,000 km2 acknowledge Iceland as the largest Arctic and European desert. Frequent dust events, up to 135 dust days annually, transport dust particles far distances towards the Arctic and Europe. Satellite MODIS pictures have revealed dust plumes exceeding 1,000 km. The annual dust deposition was calculated as 40.1 million tons yr-1. Two dust storms were measured in transverse horizontal profile about 90 km far from different dust sources in southwestern Iceland in the summer of 2015. Aerosol monitor DustTrak DRX 8533EP was used to measure PM mass concentrations corresponding to PM1, PM2.5, PM4, PM10 and the total PM15 at several places within the dust plume. Images from camera network operated by the Icelandic Road and Coastal Administration were used to estimate the visibility and spatial extent of measured dust events. A numerical simulation of surface winds was carried out with the numerical model HIRLAM with horizontal resolution of 5 km and used to calculate the total dust flux from the sources. The in situ measurements inside the dust plumes showed that aeolian dust can be very fine. The study highlights that suspended volcanic dust in Iceland causes air pollution with extremely high PM1 concentrations comparable to the polluted urban stations in Europe or Asia rather than reported dust event observations from around the world. The PM1/PM2.5 ratios are generally low during dust storms outside of Iceland, much lower than > 0.9 and PM1/PM10 ratios of 0.34-0.63 found in our study. It shows that Icelandic volcanic dust consists of higher proportion of submicron particles compared to crustal dust. The submicron particles are predicted to travel long distances. Moreover, such submicron particles pose considerable health risk because of high potential for entering the lungs. Icelandic volcanic glass has often fine pipe-vesicular structures known from asbestos and high content of heavy metals. Previous in situ measurements at the dust source in 2013 revealed extremely high number concentrations of submicron particles, specifically in the size range 0.3-0.337 μm. The PM2.5/PM10 ratios of mass concentrations seem to be lower at the dust sources that in some distance from the sources as measured in 2015. Common dust storms in Iceland are of several hundred thousand tons of magnitude from relatively well defined main dust sources. Numerical simulations were used calculate the total dust flux from the sources as 180,000 - 280,000 tons in this study. The mean PM1 (PM10) concentrations inside of the dust plumes varied from 97 to 241 µg m-3 (PM10 = 158 to 583 µg m-3). The extent of moderate dust events was calculated as 2.450 km2 to 4.220 km2 of the land area suggesting the regional scale of the events. Dust plumes reported here passed the most densely inhabited areas of Iceland, health risk warnings for the general public were, however, not issued. The data provided stresses the need for such warning system and is an important step towards its development.

Investigation of fluorine content in PM2.5 airborne particles of Istanbul, Turkey.

PubMed

Ozbek, Nil; Baltaci, Hakki; Baysal, Asli

2016-07-01

Fluorine determination in airborne samples is important due to its spread into the air from both natural and artificial sources. It can travel by wind over large distances before depositing on the Earth's surface. Its concentration in various matrices are limited and controlled by the regulations for causing health risks associated with environmental exposures. In this work, fluorine was determined in PM2.5 airborne samples by high-resolution continuum source electrothermal atomic absorption spectrometry. For these purpose, the PM2.5 airborne particulates were collected on quartz filters using high-volume samplers (500 L/min) in Istanbul (Turkey) for 96 h during January to June in 2 years. Then, instrumental and experimental parameters were optimized for the analyte in airborne samples. The validity of the method for the analyte was tested using standard reference material, and certified values were found in the limits of 95 % confidence level. The fluorine concentrations and meteorological conditions were compared statistically.

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.

Temporal Variation of Ambient PM10 Concentration within an Urban-Industrial Environment

NASA Astrophysics Data System (ADS)

Wong, Yoon-Keaw; Noor, Norazian Mohamed; Izzah Mohamad Hashim, Nur

2018-03-01

PM10 concentration in the ambient air has been reported to be the main pollutant affecting human health, particularly in the urban areas. This research is conducted to study the variation of PM10 concentration at the three urban-industrial areas in Malaysia, namely Shah Alam, Kuala Terengganu and Melaka. In addition, the association and correlation between PM10 concentration and other air pollutants will be distinguished. Five years interval dataset (2008-2012) consisting of PM10, SOX, NOX and O3 concentrations and other weather parameters such as wind speed, humidity and temperature were obtained from Department of Environment, Malaysia. Shah Alam shows the highest average of PM10 concentration with the value of 62.76 μg/m3 in June, whereas for Kuala Terengganu was 59.29 μg/m3 in February and 46.61 μg/m3 in August for Melaka. Two peaks were observed from the time series plot using the averaged monthly PM10 concentration. First peak occurs when PM10 concentration rises from January to February and the second peak is reached in June and remain high for the next two consecutive months for Shah Alam and Kuala Terengganu. Meanwhile the second peak for Melaka is only achieved in August as a result of the transboundary of smoke from forest fires in the Sumatra region during dry season from May to September. Both of the pollutants can be sourced from rapid industrial activities at Shah Alam. PM10 concentration is strongly correlated with carbon monoxide concentration in Kuala Terengganu and Melaka with value of r2 = 0.1725 and 0.2744 respectively. High carbon monoxide and PM10 concentration are associated with burning of fossil fuel from increased number of vehicles at these areas.

Particulate matter (PM) concentrations in underground and ground-level rail systems of the Los Angeles Metro

NASA Astrophysics Data System (ADS)

Kam, Winnie; Cheung, Kalam; Daher, Nancy; Sioutas, Constantinos

2011-03-01

Elevated concentrations of particulate matter (PM) have been found in a number of worldwide underground transit systems, with major implications regarding exposure of commuters to PM and its associated health effects. An extensive sampling campaign was conducted in May-August 2010 to measure PM concentrations in two lines of the Los Angeles Metro system - an underground subway line (Metro red line) and a ground-level light-rail line (Metro gold line). The campaign goals were to: 1) determine personal PM exposure of commuters of both lines, and 2) measure and compare PM concentrations at station platforms and inside the train. Considering that a commuter typically spent 75% of time inside the train and 25% of time waiting at a station, subway commuters were exposed on average to PM 10 and PM 2.5 concentrations that were 1.9 and 1.8 times greater than the light-rail commuters. The average PM 10 concentrations for the subway line at station platforms and inside the train were 78.0 μg m -3 and 31.5 μg m -3, respectively; for the light-rail line, corresponding PM 10 concentrations were 38.2 μg m -3 and 16.2 μg m -3. Regression analysis demonstrated that personal exposure concentrations for the light-rail line are strongly associated with ambient PM levels ( R2 = 0.61), while PM concentrations for the subway line are less influenced by ambient conditions ( R2 = 0.38) and have a relatively stable background level of about 21 μg m -3. Our findings suggest that local emissions (i.e., vehicular traffic, road dust) are the main source of airborne PM for the light-rail line. The subway line, on the other hand, has an additional source of PM, most likely generated from the daily operation of trains. Strong inter-correlation of PM 10 between the train and station microenvironments shows that airborne PM at stations are the main source of PM inside the trains for both lines ( R2 = 0.91 and 0.81 for subway and light-rail line, respectively). In addition, PM 2.5 and coarse PM (PM 10-2.5) are also strongly correlated for the subway line ( R2 = 0.89) and the light-rail line ( R2 = 0.52-0.92), suggesting that PM 2.5 and coarse PM originate from a common source. Finally, in comparison to worldwide subway systems, the L.A. Metro system is relatively 'clean'. Since the system is comparatively new (in operation since 1993), its ventilation system and braking technology are probably more efficient and more advanced than older subway systems.

Baseline Air Quality Assessment of Goods Movement Activities before the Port of Charleston Expansion: A Community–University Collaborative

PubMed Central

Wilson, Sacoby M.; Tarver, Siobhan L.; Svendsen, Erik; Jiang, Chengsheng; Ogunsakin, Olalekan A.; Zhang, Hongmei; Campbell, Dayna; Fraser-Rahim, Herbert

2017-01-01

Abstract As the demand for goods continues to increase, a collective network of transportation systems is required to facilitate goods movement activities. This study examines air quality near the Port of Charleston before its expansion and briefly describes the establishment and structure of a community–university partnership used to monitor existing pollution. Particulate matter (PM) concentrations (PM2.5 and PM10) were measured using the Thermo Fisher Scientific Partisol 2000i-D Dichotomous Air Sampler, Thermo Scientific Dichotomous Sequential Air Sampler Partisol-Plus 2025-D, and Rupprecht & Patashnick TEOM Series 1400 Sampler at neighborhood (Union Heights, Rosemont, and Accabee) and reference (FAA2.5 and Jenkins Street) sites. Descriptive statistics were performed and an ANOVA (analysis of variance) was calculated to find the difference in overall mean 24-hour PM average concentrations in communities impacted by environmental injustice. PM2.5 (15.2 μg/m3) and PM10 (27.2 μg/m3) maximum concentrations were highest in neighborhoods such as Union Heights neighborhoods due to more goods movement activities. Nevertheless, there was no statistically significant difference in mean concentrations of PM2.5 and PM10 across neighborhood sites. In contrast, mean PM10 neighborhood concentrations were significantly lower than mean PM10 reference concentrations for Union Heights (p = 0.00), Accabee (p ≤ 0.0001), and Rosemont (p = 0.01). Although PM concentrations were lower than current National Ambient Air Quality Standards, this study demonstrated how community–university partners can work collectively to document baseline PM concentrations that will be used to examine changes in air quality after the port expansion brings additional goods movement activities to the area. PMID:29576842

Improving satellite-driven PM2.5 models with Moderate Resolution Imaging Spectroradiometer fire counts in the southeastern U.S.

PubMed

Hu, Xuefei; Waller, Lance A; Lyapustin, Alexei; Wang, Yujie; Liu, Yang

2014-10-16

Multiple studies have developed surface PM 2.5 (particle size less than 2.5 µm in aerodynamic diameter) prediction models using satellite-derived aerosol optical depth as the primary predictor and meteorological and land use variables as secondary variables. To our knowledge, satellite-retrieved fire information has not been used for PM 2.5 concentration prediction in statistical models. Fire data could be a useful predictor since fires are significant contributors of PM 2.5 . In this paper, we examined whether remotely sensed fire count data could improve PM 2.5 prediction accuracy in the southeastern U.S. in a spatial statistical model setting. A sensitivity analysis showed that when the radius of the buffer zone centered at each PM 2.5 monitoring site reached 75 km, fire count data generally have the greatest predictive power of PM 2.5 across the models considered. Cross validation (CV) generated an R 2 of 0.69, a mean prediction error of 2.75 µg/m 3 , and root-mean-square prediction errors (RMSPEs) of 4.29 µg/m 3 , indicating a good fit between the dependent and predictor variables. A comparison showed that the prediction accuracy was improved more substantially from the nonfire model to the fire model at sites with higher fire counts. With increasing fire counts, CV RMSPE decreased by values up to 1.5 µg/m 3 , exhibiting a maximum improvement of 13.4% in prediction accuracy. Fire count data were shown to have better performance in southern Georgia and in the spring season due to higher fire occurrence. Our findings indicate that fire count data provide a measurable improvement in PM 2.5 concentration estimation, especially in areas and seasons prone to fire events.

Uncertainties in estimates of mortality attributable to ambient PM2.5 in Europe

NASA Astrophysics Data System (ADS)

Kushta, Jonilda; Pozzer, Andrea; Lelieveld, Jos

2018-06-01

The assessment of health impacts associated with airborne particulate matter smaller than 2.5 μm in diameter (PM2.5) relies on aerosol concentrations derived either from monitoring networks, satellite observations, numerical models, or a combination thereof. When global chemistry-transport models are used for estimating PM2.5, their relatively coarse resolution has been implied to lead to underestimation of health impacts in densely populated and industrialized areas. In this study the role of spatial resolution and of vertical layering of a regional air quality model, used to compute PM2.5 impacts on public health and mortality, is investigated. We utilize grid spacings of 100 km and 20 km to calculate annual mean PM2.5 concentrations over Europe, which are in turn applied to the estimation of premature mortality by cardiovascular and respiratory diseases. Using model results at a 100 km grid resolution yields about 535 000 annual premature deaths over the extended European domain (242 000 within the EU-28), while numbers approximately 2.4% higher are derived by using the 20 km resolution. Using the surface (i.e. lowest) layer of the model for PM2.5 yields about 0.6% higher mortality rates compared with PM2.5 averaged over the first 200 m above ground. Further, the calculation of relative risks (RR) from PM2.5, using 0.1 μg m‑3 size resolution bins compared to the commonly used 1 μg m‑3, is associated with ±0.8% uncertainty in estimated deaths. We conclude that model uncertainties contribute a small part of the overall uncertainty expressed by the 95% confidence intervals, which are of the order of ±30%, mostly related to the RR calculations based on epidemiological data.

Improving satellite-driven PM2.5 models with Moderate Resolution Imaging Spectroradiometer fire counts in the southeastern U.S

PubMed Central

Hu, Xuefei; Waller, Lance A.; Lyapustin, Alexei; Wang, Yujie; Liu, Yang

2017-01-01

Multiple studies have developed surface PM2.5 (particle size less than 2.5 µm in aerodynamic diameter) prediction models using satellite-derived aerosol optical depth as the primary predictor and meteorological and land use variables as secondary variables. To our knowledge, satellite-retrieved fire information has not been used for PM2.5 concentration prediction in statistical models. Fire data could be a useful predictor since fires are significant contributors of PM2.5. In this paper, we examined whether remotely sensed fire count data could improve PM2.5 prediction accuracy in the southeastern U.S. in a spatial statistical model setting. A sensitivity analysis showed that when the radius of the buffer zone centered at each PM2.5 monitoring site reached 75 km, fire count data generally have the greatest predictive power of PM2.5 across the models considered. Cross validation (CV) generated an R2 of 0.69, a mean prediction error of 2.75 µg/m3, and root-mean-square prediction errors (RMSPEs) of 4.29 µg/m3, indicating a good fit between the dependent and predictor variables. A comparison showed that the prediction accuracy was improved more substantially from the nonfire model to the fire model at sites with higher fire counts. With increasing fire counts, CV RMSPE decreased by values up to 1.5 µg/m3, exhibiting a maximum improvement of 13.4% in prediction accuracy. Fire count data were shown to have better performance in southern Georgia and in the spring season due to higher fire occurrence. Our findings indicate that fire count data provide a measurable improvement in PM2.5 concentration estimation, especially in areas and seasons prone to fire events. PMID:28967648

Quality-assured measurements of animal building emissions: particulate matter concentrations.

PubMed

Heber, Albert J; Lim, Teng-Teeh; Ni, Ji-Qin; Tao, Pei-Chun; Schmidt, Amy M; Koziel, Jacek A; Hoff, Steven J; Jacobson, Larry D; Zhang, Yuanhui; Baughman, Gerald B

2006-12-01

Federally funded, multistate field studies were initiated in 2002 to measure emissions of particulate matter (PM) < 10 microm (PM10) and total suspended particulate (TSP), ammonia, hydrogen sulfide, carbon dioxide, methane, nonmethane hydrocarbons, and odor from swine and poultry production buildings in the United States. This paper describes the use of a continuous PM analyzer based on the tapered element oscillating microbalance (TEOM). In these studies, the TEOM was used to measure PM emissions at identical locations in paired barns. Measuring PM concentrations in swine and poultry barns, compared with measuring PM in ambient air, required more frequent maintenance of the TEOM. External screens were used to prevent rapid plugging of the insect screen in the PM10 preseparator inlet. Minute means of mass concentrations exhibited a sinusoidal pattern that followed the variation of relative humidity, indicating that mass concentration measurements were affected by water vapor condensation onto and evaporation of moisture from the TEOM filter. Filter loading increased the humidity effect, most likely because of increased water vapor adsorption capacity of added PM. In a single layer barn study, collocated TEOMs, equipped with TSP and PM10 inlets, corresponded well when placed near the inlets of exhaust fans in a layer barn. Initial data showed that average daily mean concentrations of TSP, PM10, and PM2.5 concentrations at a layer barn were 1440 +/- 182 microg/m3 (n = 2), 553 +/- 79 microg/m3 (n = 4), and 33 +/- 75 microg/m3 (n = 1), respectively. The daily mean TSP concentration (n = 1) of a swine barn sprinkled with soybean oil was 67% lower than an untreated swine barn, which had a daily mean TSP concentration of 1143 +/- 619 microg/m3. The daily mean ambient TSP concentration (n = 1) near the swine barns was 25 +/- 8 microg/m3. Concentrations of PM inside the swine barns were correlated to pig activity.

Indoor-outdoor relationships of PM2.5 in four residential dwellings in winter in the Yangtze River Delta, China.

PubMed

Wang, Fang; Meng, Dan; Li, Xiuwei; Tan, Junjie

2016-08-01

Indoor and outdoor air PM2.5 concentrations in four residential dwellings characterized with different building envelope air tightness levels and HVAC-filter configurations in Yangtze River Delta (YRD) were measured during winter periods in 2014-2015. Steady-state models for indoor PM2.5 were developed for each of the tested dwellings, based on mass balance equation. The indoor air PM2.5 concentrations in the four tested apartments were significantly different. The lowest geometric mean values of indoor air PM2.5 concentrations, I/O ratios, and infiltration factor were observed in D3 with high air tightness and without HVAC-filter system (26.0 μg/m(3), 0.197, and 0.167, respectively), while the highest geometric mean values of indoor air PM2.5 concentrations, I/O ratios, and infiltration factor were observed in D1 (64.9 μg/m(3), 0.876, and 0.867, respectively). For apartment D1 with normal air tightness and without any HVAC-filter system, indoor air PM2.5 concentrations were significantly correlated with outdoor PM2.5 concentrations, especially in severe ambient pollution days, when closed windows can only play a very weak role on the decline of indoor PM2.5 concentrations. With the enhancement of building air tightness, the indoor air PM2.5 concentrations can be decreased effectively and don't vary as much in response to fluctuations in ambient concentrations. For buildings with normal air tightness, the use of HVAC-filter combinations will decrease the indoor PM2.5 significantly. However, for buildings with enhanced air tightness, the only use of fresh makeup air supply system with filter may increase the indoor PM2.5 concentrations. The improvement of filter efficiency for both fresh makeup air and indoor recirculated air are very important. However, purifiers for indoor recirculated air were highly recommended for all buildings. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessing Provincial PM2.5 Trends in China from 2001 to 2015 Using High-Resolution Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Lin, C.; Lau, A. K. H.; LI, Y.; Li, C.

2017-12-01

Given the vast territory of China, control efforts for air pollution and the long-term PM2.5 trends may substantially differ among the provinces. In this study, we aim to assess the provincial PM2.5 trends in China during the past few Five-Year Plan (FYP) periods. The lack of long-term PM2.5 measurements, however, makes such assessment difficult. Satellite remote sensing of PM2.5 concentration is an important step toward filling this data gap. In this study, a PM2.5 data set was built over China at a resolution of 1 km from 2001 to 2015 using satellite remote sensing. Analyses show that the national average of PM2.5 concentration increased by 0.11 µg·m-3·yr-1 during the 10th FYP period (2001 to 2005) and started to decline by -0.75 µg·m-3·yr-1 and -2.20 µg·m-3·yr-1 during the 11th (2006 to 2010) and the 12th (2011 to 2015) FYP period, respectively. In addition, substantial differences in the PM2.5 trends were observed among the provinces. Although PM2.5 concentrations remained steady or worsened in most provinces during the 10th FYP period, PM2.5 concentrations substantially declined for provinces in the Beijing-Tianjin-Hebei (BTH) region, suggesting that these provinces were the most successful in their control efforts during this period. The most substantial decline in provincial PM2.5 concentration during the 12th FYP period was also observed in the BTH region. In contrast, PM2.5 concentrations remained steady for provinces in eastern and southeastern China (e.g., Shanghai) during the 12th FYP period, suggesting that these provinces have been less successful in controlling PM2.5 concentrations since 2011 and therefore require more efforts to effectively reduce the PM2.5 concentrations in future.

EPA AirNow Satellite Data Processor (ASDP) for Improving Air Quality Information

NASA Astrophysics Data System (ADS)

White, J. E.; Dickerson, P.; Szykman, J.; Chu, D.; Kondragunta, S.; Zhang, H.; Martin, R. V.; van Donkelaar, A.; Pasch, A. N.; Dye, T. S.; Zahn, P. H.; Haderman, M. D.; DeWinter, J. L.

2012-12-01

The US Environmental Protection Agency (EPA) AirNow program provides Air Quality Index (AQI) information to the public, decision-makers, researchers and the media (data and forecasts) mainly for ozone and PM2.5 (particles smaller than 2.5 μm in median diameter). EPA wants to provide the best information available to the public and integrating NASA satellite-derived surface PM2.5 concentrations with ground-level PM2.5 observations has proved promising. The AirNow Satellite Data Processor (ASDP) uses daily PM2.5 estimates and uncertainties derived from average Aqua and Terra MODerate resolution Imaging Spectrometer (MODIS) AOD in near-real-time over the United States and fuses the results with observed PM2.5 measurements to create several air quality products for evaluation. In addition to the description of the AirNow program and the AirNow ASDP, several case studies will be presented to show the value that NASA satellite information adds to maps of air quality.

Airborne endotoxin concentrations in indoor and outdoor particulate matter and their predictors in an urban city.

PubMed

Yoda, Y; Tamura, K; Shima, M

2017-09-01

Endotoxins are an important biological component of particulate matter and have been associated with adverse effects on human health. There have been some recent studies on airborne endotoxin concentrations. We collected fine (PM 2.5 ) and coarse (PM 10-2.5 ) particulate matter twice on weekdays and weekends each for 48 hour, inside and outside 55 homes in an urban city in Japan. Endotoxin concentrations in both fractions were measured using the kinetic Limulus Amebocyte Lysate assay. The relationships between endotoxin concentrations and household characteristics were evaluated for each fraction. Both indoor and outdoor endotoxin concentrations were higher in PM 2.5 than in PM 10-2.5 . In both PM 2.5 and PM 10-2.5 , indoor endotoxin concentrations were higher than outdoor concentrations, and the indoor endotoxin concentrations significantly correlated with outdoor concentrations in each fraction (R 2 =0.458 and 0.198, respectively). Indoor endotoxin concentrations in PM 2.5 were significantly higher in homes with tatami or carpet flooring and in homes with pets, and lower in homes that used air purifiers. Indoor endotoxin concentrations in PM 10-2.5 were significantly higher in homes with two or more children and homes with tatami or carpet flooring. These results showed that the indoor endotoxin concentrations were associated with the household characteristics in addition to outdoor endotoxin concentrations. © 2017 The Authors. Indoor Air Published by John Wiley & Sons Ltd.

[Characteristics of atmospheric visibility change and its influence factors in Hefei City, Anhui, China.

PubMed

Shi, Min Min; Zhang, Qing Guo; Zhang, Hao; Wang, Feng Wen

2017-02-01

Using the observation data of Hefei atmospheric visibility and meteorological elements and PM 2.5 and PM 10 concentrations at same period from October 2013 to June 2015, based on comprehensive analysis of the impact factors on atmospheric visibility, the relationships among the relative humidity (RH), PM 2.5 and PM 10 concentrations and visibility were explored. The results showed that the correlation between RH and Hefei atmospheric visibility was most significant during the period of study. When RH<60%, the coefficients of correlation between PM 2.5 , PM 10 concentrations and atmospheric visibility increased gradually with the increasing RH. When RH>60%, the coefficients of correlation between the particles concentration in atmosphere and atmospheric visibility showed a decreasing trend. When 50%≤RH<60%, the coefficients of correlation between PM 2.5 , PM 10 concentrations and atmosphere visibility were higher. When RH was relatively higher, the atmospheric visibility was mainly affected by the relative humidity, on the contrary, the concentration of particles had a greater influence on the visibility. When RH>70%, the change amplitude of contour line of atmospheric visibility was larger, and the impacts of RH on atmospheric visibility were intensified. According to the formula fitted by the data of RH, PM 2.5 , PM 10 concentrations and atmospheric visibility, the nonlinear fitting model was better than multivariate linear fitting model in simulating the change of atmospheric visibility.

Effects of wind direction on coarse and fine particulate matter concentrations in southeast Kansas.

PubMed

Guerra, Sergio A; Lane, Dennis D; Marotz, Glen A; Carter, Ray E; Hohl, Carrie M; Baldauf, Richard W

2006-11-01

Field data for coarse particulate matter ([PM] PM10) and fine particulate matter (PM2.5) were collected at selected sites in Southeast Kansas from March 1999 to October 2000, using portable MiniVol particulate samplers. The purpose was to assess the influence on air quality of four industrial facilities that burn hazardous waste in the area located in the communities of Chanute, Independence, Fredonia, and Coffeyville. Both spatial and temporal variation were observed in the data. Variation because of sampling site was found to be statistically significant for PM10 but not for PM2.5. PM10 concentrations were typically slightly higher at sites located within the four study communities than at background sites. Sampling sites were located north and south of the four targeted sources to provide upwind and downwind monitoring pairs. No statistically significant differences were found between upwind and downwind samples for either PM10 or PM2.5, indicating that the targeted sources did not contribute significantly to PM concentrations. Wind direction can frequently contribute to temporal variation in air pollutant concentrations and was investigated in this study. Sampling days were divided into four classifications: predominantly south winds, predominantly north winds, calm/variable winds, and winds from other directions. The effect of wind direction was found to be statistically significant for both PM10 and PM2.5. For both size ranges, PM concentrations were typically highest on days with predominantly south winds; days with calm/variable winds generally produced higher concentrations than did those with predominantly north winds or those with winds from "other" directions. The significant effect of wind direction suggests that regional sources may exert a large influence on PM concentrations in the area.

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

Klasen, Elizabeth M.; Wills, Beatriz; Naithani, Neha

Household air pollution from the burning of biomass fuels is recognized as the third greatest contributor to the global burden of disease. Incomplete combustion of biomass fuels releases a complex mixture of carbon monoxide (CO), particulate matter (PM) and other toxins into the household environment. Some investigators have used indoor CO concentrations as a reliable surrogate of indoor PM concentrations; however, the assumption that indoor CO concentration is a reasonable proxy of indoor PM concentration has been a subject of controversy. We sought to describe the relationship between indoor PM{sub 2.5} and CO concentrations in 128 households across three resource-poormore » settings in Peru, Nepal, and Kenya. We simultaneously collected minute-to-minute PM{sub 2.5} and CO concentrations within a meter of the open-fire stove for approximately 24 h using the EasyLog-USB-CO data logger (Lascar Electronics, Erie, PA) and the personal DataRAM-1000AN (Thermo Fisher Scientific Inc., Waltham, MA), respectively. We also collected information regarding household construction characteristics, and cooking practices of the primary cook. Average 24 h indoor PM{sub 2.5} and CO concentrations ranged between 615 and 1440 μg/m{sup 3}, and between 9.1 and 35.1 ppm, respectively. Minute-to-minute indoor PM{sub 2.5} concentrations were in a safe range (<25 μg/m{sup 3}) between 17% and 65% of the time, and exceeded 1000 μg/m{sup 3} between 8% and 21% of the time, whereas indoor CO concentrations were in a safe range (<7 ppm) between 46% and 79% of the time and exceeded 50 ppm between 4%, and 20% of the time. Overall correlations between indoor PM{sub 2.5} and CO concentrations were low to moderate (Spearman ρ between 0.59 and 0.83). There was also poor agreement and evidence of proportional bias between observed indoor PM{sub 2.5} concentrations vs. those estimated based on indoor CO concentrations, with greater discordance at lower concentrations. Our analysis does not support the notion that indoor CO concentration is a surrogate marker for indoor PM{sub 2.5} concentration across all settings. Both are important markers of household air pollution with different health and environmental implications and should therefore be independently measured. - Highlights: • We summarized indoor PM2.5 and CO concentrations across three resource-poor settings. • Overall correlations between indoor PM2.5 and CO were low to moderate. • Agreement between observed indoor PM2.5 vs. those estimated based on indoor CO was poor.« less

Particulate Matter Exposure in a Police Station Located near a Highway

PubMed Central

Chen, Yu-Cheng; Hsu, Chin-Kai; Wang, Chia C.; Tsai, Perng-Jy; Wang, Chun-Yuan; Chen, Mei-Ru; Lin, Ming-Yeng

2015-01-01

People living or working near roadways have experienced an increase in cardiovascular or respiratory diseases due to vehicle emissions. Very few studies have focused on the PM exposure of highway police officers, particularly for the number concentration and size distribution of ultrafine particles (UFP). This study evaluated exposure concentrations of particulate matter (PM) in the Sinying police station near a highway located in Tainan, Taiwan, under different traffic volumes, traffic types, and shift times. We focused on periods when the wind blew from the highway toward the police station and when the wind speed was greater than or equal to 0.5 m/s. PM2.5, UFP, and PM-PAHs concentrations in the police station and an upwind reference station were measured. Results indicate that PM2.5, UFP, and PM-PAHs concentrations in the police station can be on average 1.13, 2.17, and 5.81 times more than the upwind reference station concentrations, respectively. The highest exposure level for PM2.5 and UFP was observed during the 12:00 PM–4:00 PM shift while the highest PAHs concentration was found in the 4:00 AM–8:00 AM shift. Thus, special attention needs to be given to protect police officers from exposure to high PM concentration. PMID:26580641

Impact of crop field burning and mountains on heavy haze in the North China Plain: a case study

NASA Astrophysics Data System (ADS)

Long, Xin; Tie, Xuexi; Cao, Junji; Huang, Rujin; Feng, Tian; Li, Nan; Zhao, Suyu; Tian, Jie; Li, Guohui; Zhang, Qiang

2016-08-01

With the provincial statistical data and crop field burning (CFB) activities captured by Moderate Resolution Imaging Spectroradiometer (MODIS), we extracted a detailed CFB emission inventory in the North China Plain (NCP). The WRF-CHEM model was applied to investigate the impact of CFB on air pollution during the period from 6 to 12 October 2014, corresponding to a heavy haze incident with high concentrations of PM2.5 (particulate matter with aerodynamic diameter less than 2.5 µm). The WRF-CHEM model generally performed well in simulating the surface species concentrations of PM2.5, O3 and NO2 compared to the observations; in addition, it reasonably reproduced the observed temporal variations of wind speed, wind direction and planetary boundary layer height (PBLH). It was found that the CFB that occurred in southern NCP (SNCP) had a significant effect on PM2.5 concentrations locally, causing a maximum of 34 % PM2.5 increase. Under continuous southerly wind conditions, the CFB pollution plume went through a long-range transport to northern NCP (NNCP; with several mega cities, including Beijing, the capital city of China), where few CFBs occurred, resulting in a maximum of 32 % PM2.5 increase. As a result, the heavy haze in Beijing was enhanced by the CFB, which occurred in SNCP. Mountains also play significant roles in enhancing the PM2.5 pollution in NNCP through the blocking effect. The mountains blocked and redirected the airflows, causing the pollutant accumulations along the foothills of mountains. This study suggests that the prohibition of CFB should be strict not only in or around Beijing, but also on the ulterior crop growth areas of SNCP. PM2.5 emissions in SNCP should be significantly limited in order to reduce the occurrences of heavy haze events in the NNCP region.

Improvement of PM concentration predictability using WRF-CMAQ-DLM coupled system and its applications

NASA Astrophysics Data System (ADS)

Lee, Soon Hwan; Kim, Ji Sun; Lee, Kang Yeol; Shon, Keon Tae

2017-04-01

Air quality due to increasing Particulate Matter(PM) in Korea in Asia is getting worse. At present, the PM forecast is announced based on the PM concentration predicted from the air quality prediction numerical model. However, forecast accuracy is not as high as expected due to various uncertainties for PM physical and chemical characteristics. The purpose of this study was to develop a numerical-statistically ensemble models to improve the accuracy of prediction of PM10 concentration. Numerical models used in this study are the three dimensional atmospheric model Weather Research and Forecasting(WRF) and the community multiscale air quality model (CMAQ). The target areas for the PM forecast are Seoul, Busan, Daegu, and Daejeon metropolitan areas in Korea. The data used in the model development are PM concentration and CMAQ predictions and the data period is 3 months (March 1 - May 31, 2014). The dynamic-statistical technics for reducing the systematic error of the CMAQ predictions was applied to the dynamic linear model(DLM) based on the Baysian Kalman filter technic. As a result of applying the metrics generated from the dynamic linear model to the forecasting of PM concentrations accuracy was improved. Especially, at the high PM concentration where the damage is relatively large, excellent improvement results are shown.

Indoor air quality modeling for PM 10, PM 2.5, and PM 1.0 in naturally ventilated classrooms of an urban Indian school building.

PubMed

Goyal, Radha; Khare, Mukesh

2011-05-01

Assessment of indoor air quality (IAQ) in classrooms of school buildings is of prime concern due to its potential effects on student's health and performance as they spend a substantial amount of their time (6-7 h per day) in schools. A number of airborne contaminants may be present in urban school environment. However, respirable suspended particulate matter (RSPM) is of great significance as they may significantly affect occupants' health. The objectives of the present study are twofold, one, to measure the concentrations of PM(10) (<10 microm), PM(2.5) (<2.5 microm), and PM(1.0) (<1.0 microm) in naturally ventilated classrooms of a school building located near a heavy-traffic roadway (9,755 and 4,296 vehicles/hour during weekdays and weekends, respectively); and second, to develop single compartment mass balance-based IAQ models for PM(10) (NVIAQM(pm10)), PM(2.5) (NVIAQM(pm2.5)), and PM(1.0) (NVIAQM(pm1.0)) for predicting their indoor concentrations. Outdoor RSPM levels and classroom characteristics, such as size, occupancy level, temperature, relative humidity, and CO(2) concentrations have also been monitored during school hours. Predicted indoor PM(10) concentrations show poor correlations with observed indoor PM(10) concentrations (R (2) = 0.028 for weekdays, and 0.47 for weekends). However, a fair degree of agreement (d) has been found between observed and predicted concentrations, i.e., 0.42 for weekdays and 0.59 for weekends. Furthermore, NVIAQM(pm2.5) and NVIAQM(pm1.0) results show good correlations with observed concentrations of PM(2.5) (R(2) = 0.87 for weekdays and 0.9 for weekends) and PM(1.0) (R(2) = 0.86 for weekdays and 0.87 for weekends). NVIAQM(pm10) shows the tendency to underpredict indoor PM(10) concentrations during weekdays as it does not take into account the occupant's activities and its effects on the indoor concentrations during the class hours. Intense occupant's activities cause resuspension or delayed deposition of PM(10). The model results further suggests conductance of experimental and physical simulation studies on dispersion of particulates indoors to investigate their resuspension and settling behavior due to occupant's activities/movements. The models have been validated at three different classroom locations of the school site. Sensitivity analysis of the models has been performed by varying the values of mixing factor (k) and newly introduced parameter R(c). The results indicate that the change in values of k (0.33 to 1.00) does not significantly affect the model performance. However, change in value of R(c) (0.001 to 0.500) significantly affects the model performance.

Particulate Matter Mass and Number Concentrations Inside a Naturally Ventilated School Building Located Adjacent to an Urban Roadway

NASA Astrophysics Data System (ADS)

Chithra, V. S.; Shiva Nagendra, S. M.

2014-09-01

This work presents the temporal characteristics of Particulate Matter (PM) mass and number concentrations measured inside a naturally ventilated school building, located close to a busy roadway in Chennai city. Two environmental dust monitor instruments (GRIMM Model 107 and Model 108) were used for measuring PM mass and number concentrations. The 1-h mean values of PM10, PM2.5 and PM1 mass concentrations were found to be 262 ± 161, 68 ± 24, 40 ± 15 µg/m3 and 81 ± 26, 56 ± 2, 45 ± 19 µg/m3 during working hours (8am-4pm) and non-working hours (4pm-8am)/holidays, respectively. The PM number concentrations inside the room during working hours were found to be 2.4 × 105, 2.2 × 103 and 8.1 × 102 particles/l in the size range of 0.3-1, 1-3 and 3-10 µm, respectively. The present study reveals that during working hours, indoor PM concentrations of the classroom were influenced by the activities of occupants and during non working hours it was affected by outdoor vehicular emissions.

A multivariate study for characterizing particulate matter (PM(10), PM(2.5), and PM(1)) in Seoul metropolitan subway stations, Korea.

PubMed

Kwon, Soon-Bark; Jeong, Wootae; Park, Duckshin; Kim, Ki-Tae; Cho, Kyung Hwa

2015-10-30

Given that around eight million commuters use the Seoul Metropolitan Subway (SMS) each day, the indoor air quality (IAQ) of its stations has attracted much public attention. We have monitored the concentration of particulate matters (PMx) (i.e., PM10, PM2.5, and PM1) in six major transfer stations per minute for three weeks during the summer, autumn, and winter in 2014 and 2015. The data were analyzed to investigate the relationship between PMx concentration and multivariate environmental factors using statistical methods. The average PM concentration observed was approximately two or three times higher than outdoor PM10 concentration, showing similar temporal patterns at concourses and platforms. This implies that outdoor PM10 is the most significant factor in controlling indoor PM concentration. In addition, the station depth and number of trains passing through stations were found to be additional influences on PMx. Principal component analysis (PCA) and self-organizing map (SOM) were employed, through which we found that the number of trains influences PM concentration in the vicinity of platforms only, and PMx hotspots were determined. This study identifies the external and internal factors affecting PMx characteristics in six SMS stations, which can assist in the development of effective IAQ management plans to improve public health. Copyright © 2015 Elsevier B.V. All rights reserved.

Global Air Quality and Health Co-benefits of Mitigating Near-term Climate Change Through Methane and Black Carbon Emission Controls

NASA Technical Reports Server (NTRS)

Anenberg, Susan C.; Schwartz, Joel; Shindell, Drew Todd; Amann, Markus; Faluvegi, Gregory S.; Klimont, Zbigniew; Janssens-Maenhout, Greet; Pozzoli, Luca; Dingenen, Rita Van; Vignati, Elisabetta;

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

PubMed

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

2018-02-01

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

Genotoxic assessment and optimization of pressmud with the help of exotic earthworm Eisenia fetida.

PubMed

Bhat, Sartaj Ahmad; Singh, Jaswinder; Vig, Adarsh Pal

2014-01-01

Genotoxicity of pressmud (PM) to Allium cepa was investigated to assess its toxic potential and to elucidate the effect of vermicomposting to reduce its toxicity. The PM produced as a waste by product of the sugar cane industry was mixed with cow dung (CD) at different ratios of 0:100 (V₀), 25:75 (V₂₅), 50:50 (V₅₀), 75:25 (V₇₅) and 100:0 (V100) (PM:CD) on a dry weight basis for vermicomposting with Eisenia fetida. Different concentrations of 100% PM sludge extract (10%, 20%, 40%, 60%, 80% and 100%) and negative control (distilled water) and positive control (maleic hydrazide) were analyzed with A. cepa assay to evaluate frequency of chromosomal aberrations before and after vermicomposting. Percent aberration was greatest (30.8%) after exposure to 100% PM extract after 6 h but was reduced to 20.3% after vermicomposting. Exposure to the extract induced c-mitosis, delayed anaphase, laggards, stickiness and vagrant aberrations. Microscopic examination of root meristem exposed to PM sludge extract showed significant inhibition of mitotic index. Also, the mitotic index decreased with increase in concentration of PM sludge extract. After vermicomposting the mitotic index was increased. However, increasing percentages of PM significantly affected the growth and fecundity of the worms and maximum population size was reached in the 25:75 (PM:CD) feed mixture. Nitrogen, phosphorus, sodium, electrical conductivity (EC) and pH increased from initial feed mixture to the final products (i.e., vermicompost), while organic carbon, C/N ratio and potassium declined in all products of vermicomposting. Scanning electron microscopy (SEM) was recorded to identify the changes in texture with numerous surface irregularities and high porosity that proves to be good vermicompost manure. It could be concluded that vermicomposting could be an important tool to reduce the toxicity of PM as evidenced by the results of genotoxicity.

Short-Term Deposition of PM2.5 Particles on Contact Lens Surfaces: Effect on Oxygen Permeability and Refractive Index.

PubMed

Dong, Zhizhang; Ding, Xiaoyan; Li, Yong; Gan, Yifeng; Wang, Yanhui; Xu, Libin; Wang, Yahong; Zhou, Ying; Li, Juan

2018-05-22

To identify the deposition of fine (≤2.5 μm diameter) particulate matter (PM) particles (PM 2.5 ) on contact lens surfaces and to investigate the effects of such deposition on the oxygen permeability (OP) and refractive index (RI) of contact lenses. A total of 36 contact lenses, including rigid gas permeable (RGP) lens and soft contact lens (SCL), were investigated. RGP lens (n=12) and SCL (n=12) (experimental group) were incubated in a PM 2.5 solution for 24 h, after which PM 2.5 -treated RGP lens (n=6) and SCL (n=6) were further washed for 1 h in phosphate-buffered saline (PBS). All lenses were examined by field emission scanning electron microscopy. OP and RI of all lenses were measured. Average-sized PM 2.5 particles deposited on RGP contact lens and SCL surfaces after immersion in the PM 2.5 solution were 3.192 ± 1.637 and 2.158 ± 1.187/100 μm 2 , respectively. On RGP lens surfaces, we observed both large (≥2.5 µm diameter) and small (PM 2.5 ) particles. PM 2.5 particles were deposited in diffuse patterns, primarily along the honeycomb structural border of SCL, while no PM 2.5 particles were found in the honeycomb hole of SCL surfaces. Washing in PBS removed the larger PM particles from RGP lens surfaces, but left copious amounts of PM 2.5 particles. In contrast, nearly all PM particles were removed from SCL surfaces after PBS washing. OP values of RGP lens and SCL appeared to be unchanged by PM 2.5 deposition. RI values increased in both RGP lens and SCL groups after PM 2.5 deposition. However, these increases were not statistically significant, suggesting that PM 2.5 deposition itself does not cause fluctuations in contact lens RI. Deposition of PM 2.5 particles on contact lens surfaces varies according to lens material. PM 2.5 particles deposited on SCL, but only large particles on RGP surfaces were able to be removed by washing in PBS and did not appear to alter OP and RI of either lens type.

Addressing Emerging Risks: Scientific and Regulatory Challenges Associated with Environmentally Persistent Free Radicals.

PubMed

Dugas, Tammy R; Lomnicki, Slawomir; Cormier, Stephania A; Dellinger, Barry; Reams, Margaret

2016-06-08

Airborne fine and ultrafine particulate matter (PM) are often generated through widely-used thermal processes such as the combustion of fuels or the thermal decomposition of waste. Residents near Superfund sites are exposed to PM through the inhalation of windblown dust, ingestion of soil and sediments, and inhalation of emissions from the on-site thermal treatment of contaminated soils. Epidemiological evidence supports a link between exposure to airborne PM and an increased risk of cardiovascular and pulmonary diseases. It is well-known that during combustion processes, incomplete combustion can lead to the production of organic pollutants that can adsorb to the surface of PM. Recent studies have demonstrated that their interaction with metal centers can lead to the generation of a surface stabilized metal-radical complex capable of redox cycling to produce ROS. Moreover, these free radicals can persist in the environment, hence their designation as Environmentally Persistent Free Radicals (EPFR). EPFR has been demonstrated in both ambient air PM2.5 (diameter < 2.5 µm) and in PM from a variety of combustion sources. Thus, low-temperature, thermal treatment of soils can potentially increase the concentration of EPFR in areas in and around Superfund sites. In this review, we will outline the evidence to date supporting EPFR formation and its environmental significance. Furthermore, we will address the lack of methodologies for specifically addressing its risk assessment and challenges associated with regulating this new, emerging contaminant.

Addressing Emerging Risks: Scientific and Regulatory Challenges Associated with Environmentally Persistent Free Radicals

PubMed Central

Dugas, Tammy R.; Lomnicki, Slawomir; Cormier, Stephania A.; Dellinger, Barry; Reams, Margaret

2016-01-01

Airborne fine and ultrafine particulate matter (PM) are often generated through widely-used thermal processes such as the combustion of fuels or the thermal decomposition of waste. Residents near Superfund sites are exposed to PM through the inhalation of windblown dust, ingestion of soil and sediments, and inhalation of emissions from the on-site thermal treatment of contaminated soils. Epidemiological evidence supports a link between exposure to airborne PM and an increased risk of cardiovascular and pulmonary diseases. It is well-known that during combustion processes, incomplete combustion can lead to the production of organic pollutants that can adsorb to the surface of PM. Recent studies have demonstrated that their interaction with metal centers can lead to the generation of a surface stabilized metal-radical complex capable of redox cycling to produce ROS. Moreover, these free radicals can persist in the environment, hence their designation as Environmentally Persistent Free Radicals (EPFR). EPFR has been demonstrated in both ambient air PM2.5 (diameter < 2.5 µm) and in PM from a variety of combustion sources. Thus, low-temperature, thermal treatment of soils can potentially increase the concentration of EPFR in areas in and around Superfund sites. In this review, we will outline the evidence to date supporting EPFR formation and its environmental significance. Furthermore, we will address the lack of methodologies for specifically addressing its risk assessment and challenges associated with regulating this new, emerging contaminant. PMID:27338429

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

[Pollution of Halogenated Polycyclic Aromatic Hydrocarbons in Atmospheric Particulate Matters of Shenzhen].

PubMed

Sun, Jian-lin; Chang, Wen-jing; Chen, Zheng-xia; Zeng, Hui

2015-05-01

Concentrations of halogenated polycyclic aromatic hydrocarbons ( HPAHs) in atmospheric PM10 and PM2.5 samples collected from Shenzhen were determined using GC-MS. Total concentrations of nine HPAHs in atmospheric PM10 and PM2.5 samples ranged from 118 to 1,476 pg · m(-3) and 89 to 407 pg · m(-3), respectively. In PM10 and PM(2.5) samples, the concentration of 9-BrAnt was the highest, followed by 7-BrBaA and 9, 10-Br2Ant. Seasonal levels of total HPAHs in atmospheric PM10 and PM2.5 samples in Shenzhen decreased in the following order: winter > autumn > spring > summer, whereas concentrations of individual HPAHs showed different seasonal levels. Meteorological conditions, including temperature, precipitation, and relative humidity, might be important factors affecting the seasonal levels of HPAHs in atmospheric PM10 and PM2.5 In addition, there were significant correlations between concentrations of HPAHs and parent PAHs. Finally, the toxic equivalency quotients (TEQs) of HPAHs were estimated. The TEQs of HPAHs in atmospheric PM10 and PM2.5 samples ranged from 17.6 to 86.2 pg · m(-3) and 14.6 to 70.4 pg · m(-3), respectively. Among individual HPAHs, 7-BrBaA contributed greatly to the total TEQs of HPAHs. Our results indicated that the total TEQs of HPAHs were lower than parent PAHs in atmospheric PM10 and PM2.5 samples in Shenzhen.

Assessment and statistical modeling of the relationship between remotely sensed aerosol optical depth and PM2.5 in the eastern United States.

PubMed

Paciorek, Christopher J; Liu, Yang

2012-05-01

Research in scientific, public health, and policy disciplines relating to the environment increasingly makes use of high-dimensional remote sensing and the output of numerical models in conjunction with traditional observations. Given the public health and resultant public policy implications of the potential health effects of particulate matter (PM*) air pollution, specifically fine PM with an aerodynamic diameter < or = 2.5 pm (PM2.5), there has been substantial recent interest in the use of remote-sensing information, in particular aerosol optical depth (AOD) retrieved from satellites, to help characterize variability in ground-level PM2.5 concentrations in space and time. While the United States and some other developed countries have extensive PM monitoring networks, gaps in data across space and time necessarily occur; the hope is that remote sensing can help fill these gaps. In this report, we are particularly interested in using remote-sensing data to inform estimates of spatial patterns in ambient PM2.5 concentrations at monthly and longer time scales for use in epidemiologic analyses. However, we also analyzed daily data to better disentangle spatial and temporal relationships. For AOD to be helpful, it needs to add information beyond that available from the monitoring network. For analyses of chronic health effects, it needs to add information about the concentrations of long-term average PM2.5; therefore, filling the spatial gaps is key. Much recent evidence has shown that AOD is correlated with PM2.5 in the eastern United States, but the use of AOD in exposure analysis for epidemiologic work has been rare, in part because discrepancies necessarily exist between satellite-retrieved estimates of AOD, which is an atmospheric-column average, and ground-level PM2.5. In this report, we summarize the results of a number of empirical analyses and of the development of statistical models for the use of proxy information, in particular satellite AOD, in predicting PM2.5 concentrations in the eastern United States. We analyzed the spatiotemporal structure of the relationship between PM2.5 and AOD, first using simple correlations both before and after calibration based on meteorology, as well as large-scale spatial and temporal calibration to account for discrepancies between AOD and PM2.5. We then used both raw and calibrated AOD retrievals in statistical models to predict PM2.5 concentrations, accounting for AOD in two ways: primarily as a separate data source contributing a second likelihood to a Bayesian statistical model, as well as a data source on which we could directly regress. Previous consideration of satellite AOD has largely focused on the National Aeronautics and Space Administration (NASA) moderate resolution imaging spectroradiometer (MODIS) and multiangle imaging spectroradiometer (MISR) instruments. One contribution of our work is more extensive consideration of AOD derived from the Geostationary Operational Environmental Satellite East Aerosol/Smoke Product (GOES GASP) AOD and its relationship with PM2.5. In addition to empirically assessing the spatiotemporal relationship between GASP AOD and PM2.5, we considered new statistical techniques to screen anomalous GOES reflectance measurements and account for background surface reflectance. In our statistical work, we developed a new model structure that allowed for more flexible modeling of the proxy discrepancy than previous statistical efforts have had, with a computationally efficient implementation. We also suggested a diagnostic for assessing the scales of the spatial relationship between the proxy and the spatial process of interest (e.g., PM2.5). In brief, we had little success in improving predictions in our eastern-United States domain for use in epidemiologic applications. We found positive correlations of AOD with PM2.5 over time, but less correlation for long-term averages over space, unless we used calibration that adjusted for large-scale discrepancy between AOD and PM2.5 (see sections 3, 4, and 5). Statistical models that combined AOD, PM2.5 observations, and land-use and meteorologic variables were highly predictive of PM2.5 observations held out of the modeling, but AOD added little information beyond that provided by the other sources (see sections 5 and 6). When we used PM2.5 data estimates from the Community Multiscale Air Quality model (CMAQ) as the proxy instead of using AOD, we similarly found little improvement in predicting held-out observations of PM2.5, but when we regressed on CMAQ PM2.5 estimates, the predictions improved moderately in some cases. These results appeared to be caused in part by the fact that large-scale spatial patterns in PM2.5 could be predicted well by smoothing the monitor values, while small-scale spatial patterns in AOD appeared to weakly reflect the variation in PM2.5 inferred from the observations. Using a statistical model that allowed for potential proxy discrepancy at both large and small spatial scales was an important component of our modeling. In particular, when our models did not include a component to account for small-scale discrepancy, predictive performance decreased substantially. Even long-term averages of MISR AOD, considered the best, albeit most sparse, of the AOD products, were only weakly correlated with measured PM2.5 (see section 4). This might have been partly related to the fact that our analysis did not account for spatial variation in the vertical profile of the aerosol. Furthermore, we found evidence that some of the correlation between raw AOD and PM2.5 might have been a function of surface brightness related to land use, rather than having been driven by the detection of aerosol in the AOD retrieval algorithms (see sections 4 and 7). Difficulties in estimating the background surface reflectance in the retrieval algorithms likely explain this finding. With regard to GOES, we found moderate correlations of GASP AOD and PM2.5. The higher correlations of monthly and yearly averages after calibration reflected primarily the improved large-scale correlation, a necessary result of the calibration procedure (see section 3). While the results of this study's GOES reflectance screening and surface reflection correction appeared sensible, correlations of our proposed reflectance-based proxy with PM2.5 were no better than GASP AOD correlations with PM2.5 (see section 7). We had difficulty improving spatial prediction of monthly and yearly average PM2.5 using AOD in the eastern United States, which we attribute to the spatial discrepancy between AOD and measured PM2.5, particularly at smaller scales. This points to the importance of paying attention to the discrepancy structure of proxy information, both from remote-sensing and deterministic models. In particular, important statistical challenges arise in accounting for the discrepancy, given the difficulty in the face of sparse observations of distinguishing the discrepancy from the component of the proxy that is informative about the process of interest. Associations between adverse health outcomes and large-scale variation in PM2.5 (e.g., across regions) may be confounded by unmeasured spatial variation in factors such as diet. Therefore, one important goal was to use AOD to improve predictions of PM2.5 for use in epidemiologic analyses at small-to-moderate spatial scales (within urban areas and within regions). In addition, large-scale PM2.5 variation is well estimated from the monitoring data, at least in the United States. We found little evidence that current AOD products are helpful for improving prediction at small-to-moderate scales in the eastern United States and believe more evidence for the reliability of AOD as a proxy at such scales is needed before making use of AOD for PM2.5 prediction in epidemiologic contexts. While our results relied in part on relatively complicated statistical models, which may be sensitive to modeling assumptions, our exploratory correlation analyses (see sections 3 and 5) and relatively simple regression-style modeling of MISR AOD (see section 4) were consistent with the more complicated modeling results. When assessing the usefulness of AOD in the context of studying chronic health effects, we believe efforts need to focus on disentangling the temporal from the spatial correlations of AOD and PM2.5 and on understanding the spatial scale of correlation and of the discrepancy structure. While our results are discouraging, it is important to note that we attempted to make use of smaller-scale spatial variation in AOD to distinguish spatial variations of relatively small magnitude in long-term concentrations of ambient PM2.5. Our efforts pushed the limits of current technology in a spatial domain with relatively low PM2.5 levels and limited spatial variability. AOD may hold more promise in areas with higher aerosol levels, as the AOD signal would be stronger there relative to the background surface reflectance. Furthermore, for developing countries with high aerosol levels, it is difficult to build statistical models based on PM2.5 measurements and land-use covariates, so AOD may add more incremental information in those contexts. More generally, researchers in remote sensing are involved in ongoing efforts to improve AOD products and develop new approaches to using AOD, such as calibration with model-estimated vertical profiles and the use of speciation information in MISR AOD; these efforts warrant continued investigation of the usefulness of remotely sensed AOD for public health research.

Characteristics of PM1 over Shanghai, relationships with precursors and meteorological variables and impacts on visibility

NASA Astrophysics Data System (ADS)

Zhou, Guangqiang; Xu, Jianming; Gao, Wei; Gu, Yixuan; Mao, Zhuocheng; Cui, Linli

2018-07-01

The long-term characteristics of submicron particles (PM1) over Shanghai and their contributing factors (including precursor gases and meteorological variables), as well as their impact on visibility, were investigated using in situ measurements from Jan 1st, 2015, to Dec 31st, 2016. A discretization method was introduced to identify the impact of each contributing factor on PM1. The results show that the annual mean PM1 concentration over Shanghai is ∼28 μgm-3, which accounts for 69% of fine particles (PM2.5). The PM1 concentration shows obvious temporal variations on the scales of days, weeks, months, and years. Its diurnal pattern shows higher values in the daytime (with two peaks) than in the nighttime, which is different from the pattern for PM2.5 with high/low values in the nighttime/daytime. During a week, the PM1 concentration is the lowest on Tuesday and the highest on Friday. The discretized approach reveals that PM1 shows good linear relationships with its gaseous precursors and with meteorological variables under most conditions. The concentration of PM1 increases with increases in SO2, NO2, and NO (<34 ppb) with slopes of 3.37, 1.17, and 1.08 μgm-3 per ppb precursor, respectively. This approach and the slopes were confirmed by the comparison of the observed and calculated PM1 changes with the day of the week. PM1 is negatively (positively) correlated with ozone (O3) when O3 is <30 (>30) ppb. PM1 are negatively correlated with precipitation intensity, relative humidity (RH, >35%), and wind speed (>1.5 ms-1), and their rates of decrease are 3.3, 0.26, and 5.9 μgm-3 per 1 mmh-1, 1%, and 1 ms-1, respectively. Other factors (e.g., temperature and pressure) show nonlinear relationships with PM1 concentration, presumably due to their indirect influence on the transport, formation, or accumulation of PM1. The PM1 concentration has a distinct impact on visibility, and the PM1/PM2.5 ratio is a key indicator to represent the impact of particulate matter hygroscopicity on visibility. The PM1/PM2.5 ratio shows an exponential relationship (i.e., PM1/PM2.5 = 0.76 [(1-RH)/(1-40%)]0.11) with RH with a determination coefficient of 0.98. This parameter combined with the PM2.5 concentration well describes the impact of particulate matter and its hygroscopicity on visibility.

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.

Source Apportionment and Influencing Factor Analysis of Residential Indoor PM2.5 in Beijing

PubMed Central

Yang, Yibing; Liu, Liu; Xu, Chunyu; Li, Na; Liu, Zhe; Wang, Qin; Xu, Dongqun

2018-01-01

In order to identify the sources of indoor PM2.5 and to check which factors influence the concentration of indoor PM2.5 and chemical elements, indoor concentrations of PM2.5 and its related elements in residential houses in Beijing were explored. Indoor and outdoor PM2.5 samples that were monitored continuously for one week were collected. Indoor and outdoor concentrations of PM2.5 and 15 elements (Al, As, Ca, Cd, Cu, Fe, K, Mg, Mn, Na, Pb, Se, Tl, V, Zn) were calculated and compared. The median indoor concentration of PM2.5 was 57.64 μg/m3. For elements in indoor PM2.5, Cd and As may be sensitive to indoor smoking, Zn, Ca and Al may be related to indoor sources other than smoking, Pb, V and Se may mainly come from outdoor. Five factors were extracted for indoor PM2.5 by factor analysis, explained 76.8% of total variance, outdoor sources contributed more than indoor sources. Multiple linear regression analysis for indoor PM2.5, Cd and Pb was performed. Indoor PM2.5 was influenced by factors including outdoor PM2.5, smoking during sampling, outdoor temperature and time of air conditioner use. Indoor Cd was affected by factors including smoking during sampling, outdoor Cd and building age. Indoor Pb concentration was associated with factors including outdoor Pb and time of window open per day, building age and RH. In conclusion, indoor PM2.5 mainly comes from outdoor sources, and the contributions of indoor sources also cannot be ignored. Factors associated indoor and outdoor air exchange can influence the concentrations of indoor PM2.5 and its constituents. PMID:29621164

Source Apportionment and Influencing Factor Analysis of Residential Indoor PM2.5 in Beijing.

PubMed

Yang, Yibing; Liu, Liu; Xu, Chunyu; Li, Na; Liu, Zhe; Wang, Qin; Xu, Dongqun

2018-04-05

In order to identify the sources of indoor PM 2.5 and to check which factors influence the concentration of indoor PM 2.5 and chemical elements, indoor concentrations of PM 2.5 and its related elements in residential houses in Beijing were explored. Indoor and outdoor PM 2.5 samples that were monitored continuously for one week were collected. Indoor and outdoor concentrations of PM 2.5 and 15 elements (Al, As, Ca, Cd, Cu, Fe, K, Mg, Mn, Na, Pb, Se, Tl, V, Zn) were calculated and compared. The median indoor concentration of PM 2.5 was 57.64 μg/m³. For elements in indoor PM 2.5 , Cd and As may be sensitive to indoor smoking, Zn, Ca and Al may be related to indoor sources other than smoking, Pb, V and Se may mainly come from outdoor. Five factors were extracted for indoor PM 2.5 by factor analysis, explained 76.8% of total variance, outdoor sources contributed more than indoor sources. Multiple linear regression analysis for indoor PM 2.5 , Cd and Pb was performed. Indoor PM 2.5 was influenced by factors including outdoor PM 2.5 , smoking during sampling, outdoor temperature and time of air conditioner use. Indoor Cd was affected by factors including smoking during sampling, outdoor Cd and building age. Indoor Pb concentration was associated with factors including outdoor Pb and time of window open per day, building age and RH. In conclusion, indoor PM 2.5 mainly comes from outdoor sources, and the contributions of indoor sources also cannot be ignored. Factors associated indoor and outdoor air exchange can influence the concentrations of indoor PM 2.5 and its constituents.

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.

Effects of synoptic weather on ground-level PM2.5 concentrations in the United States

NASA Astrophysics Data System (ADS)

Liu, Ying; Zhao, Naizhuo; Vanos, Jennifer K.; Cao, Guofeng

2017-01-01

It is known that individual meteorological factors affect the concentrations of fine particulate matter with aerodynamic diameters ≤2.5 μm (PM2.5), yet the specific meteorological effects found in previous studies are largely inconsistent and even conflicting. This study investigates influences of daily and short term changes in synoptic weather on ground-level PM2.5 concentrations in a large geographical area (75 cities across the contiguous United States (U.S.)) by using ten-year (2001-2010) spatial synoptic classification (SSC) data. We find that in the spring, summer, and fall the presence of the tropical weather types (i.e., dry-tropical (DT) and moist-tropical (MT)) is likely to associate with significantly higher levels of PM2.5 as compared to an all-weather-type-day average, and the presence of the polar weather types (i.e., dry-polar (DP) and moist-polar (MP)) is associated with significantly lower PM2.5 concentrations. The short-term (day to day) changes in synoptic weather types in a region are also likely to lead to significant variance in PM2.5 concentrations. For example, the largest increase in PM2.5 concentration occurs with the synoptic weather type changing from DP-to-MT. Conversely, a MT-to-DP weather type change results in the largest decrease in PM2.5 concentrations. Compared to air temperature, the effects of atmospheric moisture on PM2.5 concentration tend to be subtle, demonstrating that in conjunction with moderate temperature, neither the dry nor the moist air (except moist-moderate (MM) in summer) are associated with significantly high or low PM2.5 concentrations. Finally, we find that the effects of the synoptic weather type on PM2.5 concentrations may vary for different seasons and geographical areas. These findings suggest that interactions between atmospheric factors and seasonal and/or geographical factors have considerable impacts on the PM2.5 concentrations, and therefore should be considered in addition to the SSC when conducting environment health assessments.

Determinants of black carbon, particle mass and number concentrations in London transport microenvironments

NASA Astrophysics Data System (ADS)

Rivas, Ioar; Kumar, Prashant; Hagen-Zanker, Alex; Andrade, Maria de Fatima; Slovic, Anne Dorothee; Pritchard, John P.; Geurs, Karst T.

2017-07-01

We investigated the determinants of personal exposure concentrations of commuters' to black carbon (BC), ultrafine particle number concentrations (PNC), and particulate matter (PM1, PM2.5 and PM10) in different travel modes. We quantified the contribution of key factors that explain the variation of the previous pollutants in four commuting routes in London, each covered by four transport modes (car, bus, walk and underground). Models were performed for each pollutant, separately to assess the effect of meteorology (wind speed) or ambient concentrations (with either high spatial or temporal resolution). Concentration variations were mainly explained by wind speed or ambient concentrations and to a lesser extent by route and period of the day. In multivariate models with wind speed, the wind speed was the common significant predictor for all the pollutants in the above-ground modes (i.e., car, bus, walk); and the only predictor variable for the PM fractions. Wind speed had the strongest effect on PM during the bus trips, with an increase in 1 m s-1 leading to a decrease in 2.25, 2.90 and 4.98 μg m-3 of PM1, PM2.5 and PM10, respectively. PM2.5 and PM10 concentrations in car trips were better explained by ambient concentrations with high temporal resolution although from a single monitoring station. On the other hand, ambient concentrations with high spatial coverage but lower temporal resolution predicted better the concentrations in bus trips, due to bus routes passing through streets with a high variability of traffic intensity. In the underground models, wind speed was not significant and line and type of windows on the train explained 42% of the variation of PNC and 90% of all PM fractions. Trains in the district line with openable windows had an increase in concentrations of 1 684 cm-3 for PNC and 40.69 μg m-3 for PM2.5 compared with trains that had non-openable windows. The results from this work can be used to target efforts to reduce personal exposures of London commuters.

Modeling analysis of secondary inorganic aerosols over China: pollution characteristics, and meteorological and dust impacts.

PubMed

Fu, Xiao; Wang, Shuxiao; Chang, Xing; Cai, Siyi; Xing, Jia; Hao, Jiming

2016-10-26

Secondary inorganic aerosols (SIA) are the predominant components of fine particulate matter (PM 2.5 ) and have significant impacts on air quality, human health, and climate change. In this study, the Community Multiscale Air Quality modeling system (CMAQ) was modified to incorporate SO 2 heterogeneous reactions on the surface of dust particles. The revised model was then used to simulate the spatiotemporal characteristics of SIA over China and analyze the impacts of meteorological factors and dust on SIA formation. Including the effects of dust improved model performance for the simulation of SIA concentrations, particularly for sulfate. The simulated annual SIA concentration in China was approximately 10.1 μg/m 3 on domain average, with strong seasonal variation: highest in winter and lowest in summer. High SIA concentrations were concentrated in developed regions with high precursor emissions, such as the North China Plain, Yangtze River Delta, Sichuan Basin, and Pearl River Delta. Strong correlations between meteorological factors and SIA pollution levels suggested that heterogeneous reactions under high humidity played an important role on SIA formation, particularly during severe haze pollution periods. Acting as surfaces for heterogeneous reactions, dust particles significantly affected sulfate formation, suggesting the importance of reducing dust emissions for controlling SIA and PM 2.5 pollution.

Modeling analysis of secondary inorganic aerosols over China: pollution characteristics, and meteorological and dust impacts

NASA Astrophysics Data System (ADS)

Fu, Xiao; Wang, Shuxiao; Chang, Xing; Cai, Siyi; Xing, Jia; Hao, Jiming

2016-10-01

Secondary inorganic aerosols (SIA) are the predominant components of fine particulate matter (PM2.5) and have significant impacts on air quality, human health, and climate change. In this study, the Community Multiscale Air Quality modeling system (CMAQ) was modified to incorporate SO2 heterogeneous reactions on the surface of dust particles. The revised model was then used to simulate the spatiotemporal characteristics of SIA over China and analyze the impacts of meteorological factors and dust on SIA formation. Including the effects of dust improved model performance for the simulation of SIA concentrations, particularly for sulfate. The simulated annual SIA concentration in China was approximately 10.1 μg/m3 on domain average, with strong seasonal variation: highest in winter and lowest in summer. High SIA concentrations were concentrated in developed regions with high precursor emissions, such as the North China Plain, Yangtze River Delta, Sichuan Basin, and Pearl River Delta. Strong correlations between meteorological factors and SIA pollution levels suggested that heterogeneous reactions under high humidity played an important role on SIA formation, particularly during severe haze pollution periods. Acting as surfaces for heterogeneous reactions, dust particles significantly affected sulfate formation, suggesting the importance of reducing dust emissions for controlling SIA and PM2.5 pollution.

Modeling analysis of secondary inorganic aerosols over China: pollution characteristics, and meteorological and dust impacts

PubMed Central

Fu, Xiao; Wang, Shuxiao; Chang, Xing; Cai, Siyi; Xing, Jia; Hao, Jiming

2016-01-01

Secondary inorganic aerosols (SIA) are the predominant components of fine particulate matter (PM2.5) and have significant impacts on air quality, human health, and climate change. In this study, the Community Multiscale Air Quality modeling system (CMAQ) was modified to incorporate SO2 heterogeneous reactions on the surface of dust particles. The revised model was then used to simulate the spatiotemporal characteristics of SIA over China and analyze the impacts of meteorological factors and dust on SIA formation. Including the effects of dust improved model performance for the simulation of SIA concentrations, particularly for sulfate. The simulated annual SIA concentration in China was approximately 10.1 μg/m3 on domain average, with strong seasonal variation: highest in winter and lowest in summer. High SIA concentrations were concentrated in developed regions with high precursor emissions, such as the North China Plain, Yangtze River Delta, Sichuan Basin, and Pearl River Delta. Strong correlations between meteorological factors and SIA pollution levels suggested that heterogeneous reactions under high humidity played an important role on SIA formation, particularly during severe haze pollution periods. Acting as surfaces for heterogeneous reactions, dust particles significantly affected sulfate formation, suggesting the importance of reducing dust emissions for controlling SIA and PM2.5 pollution. PMID:27782166

Retrieval of AOD and PM2.5 Concentrations over Urban Areas of Shenyang City using MODIS Data

NASA Astrophysics Data System (ADS)

Wang, Z.

2016-12-01

Atmospheric aerosols play an important part in the Earth's radiation balance as well as global climate change, aerosols also have very important impact on environment as well as human and other organisms' health, PM2.5 and other small particle aerosols, can enter bronchi directly, thus causing bronchitis, cardiovascular disease, asthma and so on.Detection of AOD by satellite and remote sensing is currently one of the hotest issues , diffierent from the traditional monitoring method, this method has much more advantanges, for emample wide area coverage, fast and convenient etc. So it is possible for people to know the regional changes of AOD real time over large area. Now, detection aerosol by RS technology has reached a high level in marine and dense vegetation land areas, but result is not ideal for urban areas, the higher surface reflectance in urban areas is a bottleneck of AOD retrieval. Focus on the high surface reflectance and low accuracy of the AOD products of urban areas, this paper propose an algorithm coupled with surface reflectance to get red band surface reflectance, based on Dens Dark Vegetation algorithm and geometrical optics model theory, to distinguish urban reflectivity from other targets. Considering the appropriate aerosol model which adapt to season and other proper parameters, this paper uses 6S model to establish look-up table, thus retrieve AOD for urban as well as other high reflectance areas. This paper take Shenyang region as pilot area, then retrieve the AOD and PM2.5 concentration of Shenyang in 2015 based on MODIS data, thus get 1km resolution distribution map, and then analyzed the results in spatial, intensity and temporal. At last, real-time monitoring data from the ground monitor station is used to verify the outcome, the results have good accuracy and the the correlation reached 0.9004 when the weather is sunny. The research shows that this algorithm has relatively higher precision and certain universality. This method has better applicability to retrieve AOD and PM2.5 concentration by remote sensing in Shenyang and Liaoning Provience, and owes guiding and reference significance, and it has a high value in terms of atmospheric environment monitoring.

The Effect of Economic Growth, Urbanization, and Industrialization on Fine Particulate Matter (PM2.5) Concentrations in China.

PubMed

Li, Guangdong; Fang, Chuanglin; Wang, Shaojian; Sun, Siao

2016-11-01

Rapid economic growth, industrialization, and urbanization in China have led to extremely severe air pollution that causes increasing negative effects on human health, visibility, and climate change. However, the influence mechanisms of these anthropogenic factors on fine particulate matter (PM 2.5 ) concentrations are poorly understood. In this study, we combined panel data and econometric methods to investigate the main anthropogenic factors that contribute to increasing PM 2.5 concentrations in China at the prefecture level from 1999 to 2011. The results showed that PM 2.5 concentrations and three anthropogenic factors were cointegrated. The panel Fully Modified Least Squares and panel Granger causality test results indicated that economic growth, industrialization, and urbanization increased PM 2.5 concentrations in the long run. The results implied that if China persists in its current development pattern, economic growth, industrialization and urbanization will inevitably lead to increased PM 2.5 emissions in the long term. Industrialization was the principal factor that affected PM 2.5 concentrations for the total panel, the industry-oriented panel and the service-oriented panel. PM 2.5 concentrations can be reduced at the cost of short-term economic growth and industrialization. However, reducing the urbanization level is not an efficient way to decrease PM 2.5 pollutions in the short term. The findings also suggest that a rapid reduction of PM 2.5 concentrations relying solely on adjusting these anthropogenic factors is difficult in a short-term for the heavily PM 2.5 -polluted panel. Moreover, the Chinese government will have to seek much broader policies that favor a decoupling of these coupling relationships.

Potential impacts of electric vehicles on air quality in Taiwan.

PubMed

Li, Nan; Chen, Jen-Ping; Tsai, I-Chun; He, Qingyang; Chi, Szu-Yu; Lin, Yi-Chiu; Fu, Tzung-May

2016-10-01

The prospective impacts of electric vehicle (EV) penetration on the air quality in Taiwan were evaluated using an air quality model with the assumption of an ambitious replacement of current light-duty vehicles under different power generation scenarios. With full EV penetration (i.e., the replacement of all light-duty vehicles), CO, VOCs, NOx and PM2.5 emissions in Taiwan from a fleet of 20.6 million vehicles would be reduced by 1500, 165, 33.9 and 7.2Ggyr(-1), respectively, while electric sector NOx and SO2 emissions would be increased by up to 20.3 and 12.9Ggyr(-1), respectively, if the electricity to power EVs were provided by thermal power plants. The net impacts of these emission changes would be to reduce the annual mean surface concentrations of CO, VOCs, NOx and PM2.5 by about 260, 11.3, 3.3ppb and 2.1μgm(-3), respectively, but to increase SO2 by 0.1ppb. Larger reductions tend to occur at time and place of higher ambient concentrations and during high pollution events. Greater benefits would clearly be attained if clean energy sources were fully encouraged. EV penetration would also reduce the mean peak-time surface O3 concentrations by up to 7ppb across Taiwan with the exception of the center of metropolitan Taipei where the concentration increased by <2ppb. Furthermore, full EV penetration would reduce annual days of O3 pollution episodes by ~40% and PM2.5 pollution episodes by 6-10%. Our findings offer important insights into the air quality impacts of EV and can provide useful information for potential mitigation actions. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

[Variation characteristics of fine particulate matter PM2.5 concentration in three urban recreational forests in Hui Mountain of Wuxi City, Jiangsu Province of East China].

PubMed

Gu, Lin; Wang, Cheng; Wang, Xiao-Lei; Wang, Yan-Ying; Wang, Qian

2013-09-01

It is of significance to understand the controlling effects of urban forest on atmospheric fine particulate matter PM2.5 pollution. This paper monitored the variations of atmospheric PM2.5 concentrations in three typical urban recreational forests (Cinnamomum camphora, Pinus elliotii, and Quercus variabilis ) in the Hui Mountain of Wuxi City during the day time (5:00 am-19:00 pm) in autumn and winter, 2011 and in spring and summer, 2012. The meteorological factors were observed simultaneously. The average annual PM2.5 concentration in the three recreational forests was lower than that above the nearby roads, and this concentration in C. camphora and P. elliotii forests was lower than that in Q. variabilis forest. The average annual PM2.5 concentration in the forests and above the nearby roads was lower than the background value in the downtown area of the City. The PM2.5 concentration in the three recreational forests was the lowest in summer, followed by in autumn, and the highest in spring. In addition, the PM2.5 concentration was the lowest in P. elliotii forest in spring, summer, and winter, and in C. camphora forest in autumn, but relatively higher in Q. variabilis forest in all seasons. The diurnal variation of the PM2.5 concentration in the three forests in four seasons all showed nearly "one peak and one vale", with the peak and vale appeared at 7:00-9:00 and 15:00-19:00, respectively. The PM2.5 concentration was significantly correlated with the air moisture and temperature in four seasons, and significantly correlated with the light intensity in winter. Mild winds throughout the seasons had little effects on the PM2.5 concentration.

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.

Characterization of fine particulate matter in Ohio: Indoor, outdoor, and personal exposures

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

Crist, Kevin C.; Liu, Bian; Kim, Myoungwoo

2008-01-15

Ambient, indoor, and personal PM{sub 2.5} concentrations were assessed based on an exhaustive study of PM{sub 2.5} performed in Ohio from 1999 to 2000. Locations in Columbus, one in an urban corridor and the other in a suburban area were involved. A third rural location in Athens, Ohio, was also established. At all three locations, elementary schools were utilized to determine outdoor, indoor, and personal PM{sub 2.5} concentrations for fourth and fifth grade students using filter-based measurements. Three groups of 30 students each were used for personal sampling at each school. Continuous ambient PM{sub 2.5} mass concentrations were also measuredmore » with tapered element oscillating microbalances (TEOMs). At all three sites, personal and indoor PM{sub 2.5} concentrations exceeded outdoor levels. This trend is consistent on all week days and most evident in the spring as compared to fall and winter. The ambient PM{sub 2.5} concentrations were similar among the three sites, suggesting the existence of a common regional source influence. At all the three sites, larger variations were found in personal and indoor PM{sub 2.5} than ambient levels. The strongest correlations were found between indoor and personal concentrations, indicating that personal PM{sub 2.5} exposures were significantly affected by indoor PM{sub 2.5} than by ambient PM{sub 2.5}. This was further confirmed by the indoor to outdoor (I/O) ratios of PM{sub 2.5} concentrations, which were greater when school was in session than non-school days when the students were absent.« less

Measurement and modeling of particulate matter concentrations: Applying spatial analysis and regression techniques to assess air quality.

PubMed

Sajjadi, Seyed Ali; Zolfaghari, Ghasem; Adab, Hamed; Allahabadi, Ahmad; Delsouz, Mehri

2017-01-01

This paper presented the levels of PM 2.5 and PM 10 in different stations at the city of Sabzevar, Iran. Furthermore, this study was an attempt to evaluate spatial interpolation methods for determining the PM 2.5 and PM 10 concentrations in the city of Sabzevar. Particulate matters were measured by Haz-Dust EPAM at 48 stations. Then, four interpolating models, including Radial Basis Functions (RBF), Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and Universal Kriging (UK) were used to investigate the status of air pollution in the city. Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) were employed to compare the four models. The results showed that the PM 2.5 concentrations in the stations were between 10 and 500 μg/m 3 . Furthermore, the PM 10 concentrations for all of 48 stations ranged from 20 to 1500 μg/m 3 . The concentrations obtained for the period of nine months were greater than the standard limits. There was difference in the values of MAPE, RMSE, MBE, and MAE. The results indicated that the MAPE in IDW method was lower than other methods: (41.05 for PM 2.5 and 25.89 for PM 10 ). The best interpolation method for the particulate matter (PM 2.5 and PM 10 ) seemed to be IDW method. •The PM 10 and PM 2.5 concentration measurements were performed in the period of warm and risky in terms of particulate matter at 2016.•Concentrations of PM 2.5 and PM 10 were measured by a monitoring device, environmental dust model Haz-Dust EPAM 5000.•Interpolation is used to convert data from observation points to continuous fields to compare spatial patterns sampled by these measurements with spatial patterns of other spatial entities.

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.

Satellite-based retrieval of particulate matter concentrations over the United Arab Emirates (UAE)

NASA Astrophysics Data System (ADS)

Zhao, Jun; Temimi, Marouane; Hareb, Fahad; Eibedingil, Iyasu

2016-04-01

In this study, an empirical algorithm was established to retrieve particulate matter (PM) concentrations (PM2.5 and PM10) using satellite-derived aerosol optical depth (AOD) over the United Arab Emirates (UAE). Validation of the proposed algorithm using ground truth data demonstrates its good accuracy. Time series of in situ measured PM concentrations between 2014 and 2015 showed high values in summer and low values in winter. Estimated and in situ measured PM concentrations were higher in 2015 than 2014. Remote sensing is an essential tool to reveal and back track the seasonality and inter-annual variations of PM concentrations and provide valuable information on the protection of human health and the response of air quality to anthropogenic activities and climate change.

Emission Sectoral Contributions of Foreign Emissions to Particulate Matter Concentrations over South Korea

NASA Astrophysics Data System (ADS)

Kim, E.; Kim, S.; Kim, H. C.; Kim, B. U.; Cho, J. H.; Woo, J. H.

2017-12-01

In this study, we investigated the contributions of major emission source categories located upwind of South Korea to Particulate Matter (PM) in South Korea. In general, air quality in South Korea is affected by anthropogenic air pollutants emitted from foreign countries including China. Some studies reported that foreign emissions contributed 50 % of annual surface PM total mass concentrations in the Seoul Metropolitan Area, South Korea in 2014. Previous studies examined PM contributions of foreign emissions from all sectors considering meteorological variations. However, little studies conducted to assess contributions of specific foreign source categories. Therefore, we attempted to estimate sectoral contributions of foreign emissions from China to South Korea PM using our air quality forecasting system. We used Model Inter-Comparison Study in Asia 2010 for foreign emissions and Clean Air Policy Support System 2010 emission inventories for domestic emissions. To quantify contributions of major emission sectors to South Korea PM, we applied the Community Multi-scale Air Quality system with brute force method by perturbing emissions from industrial, residential, fossil-fuel power plants, transportation, and agriculture sectors in China. We noted that industrial sector was pre-dominant over the region except during cold season for primary PMs when residential emissions drastically increase due to heating demand. This study will benefit ensemble air quality forecasting and refined control strategy design by providing quantitative assessment on seasonal contributions of foreign emissions from major source categories.

Assessment of heavy metals in the particulate matter of two Brazilian metropolitan areas by using Tillandsia usneoides as atmospheric biomonitor.

PubMed

Vianna, Nelzair A; Gonçalves, Daniel; Brandão, Flavia; de Barros, Roberta P; Amado Filho, Gilberto M; Meire, Rodrigo O; Torres, João Paulo M; Malm, Olaf; D'Oliveira Júnior, Argemiro; Andrade, Leonardo R

2011-03-01

The aims of this paper were to quantify the heavy metals (HM) in the air of different sites in Rio de Janeiro (RJ) and Salvador (SA) using Tillandsia usneoides (Bromeliaceae) as a biomonitor, and to study the morphology and elemental composition of the air particulate matter (PM) retained on the Tillandsia surface. Tillandsia samples were collected in a noncontaminated area and exposed to the air of five sites in RJ State and seven in SA for 45 days, in two seasons. Samples were prepared to HM quantification by flame atomic absorption spectrophotometry, while morphological and elemental characterizations were studied by using scanning electron microscopy. HM concentrations were significantly higher when compared to control sites. We found an increasing metal concentration as follows: Cd < Cr < Pb < Cu < Zn. PM exhibited a morphology varying from amorphous- to polygonal-shaped particles. Size measurements indicated that more than 80% of particles were less than 10 μm. PM contained aluminosilicates iron-rich particles, but Zn, Cu, Cr, and Ba were also detected. HM input in the atmosphere was mainly associated with anthropogenic sources such as vehicle exhaust. Elemental analysis detected HM in the inhalable particles, indicating that those HMs may intensify the toxic effects of PM on human health. Our results indicated T. usneoides as an adequate biomonitor of HM in the PM belonging to the inhalable fraction.

Redox speciation of dissolved iron in the northeastern atlantic ocean.

NASA Astrophysics Data System (ADS)

Ussher, S. J.; Achterberg, E. P.; Worsfold, P. J.

2003-04-01

Dissolved iron (<0.2 micron) and iron(II) (<0.2 micron) distributions were determined during the Iron from Below and Iron from Above research cruises in the North Eastern Atlantic Ocean. The cruises were part of the EU Ironages project. Iron(II) was measured on-board ship using an iron(II) specific, automated flow injection analyser with luminol chemiluminescence detection [1]. Total dissolved iron (DFe) was determined in a land-based laboratory, using the same FI technique but with prior reduction of iron(III) to iron(II) [2]. The limits of detection for the methods were 5 -15 pM and 35 pM respectively, the analysis time was 8 - 10 minutes per sample (minimum of 3 replicates). The Iron from Below expedition took place over the European Continental Shelf, 200 km South West of Brittany (France) in March 2002. A transect between 47.61°N, 4.24°W and 46.00°N, 8.01°W was completed. Over the transect, the depth increased from 100 m to 5000 m. Iron(II) concentrations ranged between 10 and 100 pM and DFe between 0.2 and 1 nM, with the higher concentrations (Fe(II) ca. > 50 pM and DFe ca. > 0.8 nM) generally found in the shallow shelf waters. These observations imply that benthic inputs and sediment resuspension may form important inputs of dissolved iron and iron(II) in the shelf waters. Iron speciation measurements were also made for underway surface and shallow cast samples during the Iron from Above cruise October 2002. Fe(II) and DFe concentrations were typically 5 to 50 pM and 0.2 to 0.6 nM, respectively. Sampling was carried out within a grid in the Canary Basin around 5 degrees W of the Canary Islands, an area assumed to be strongly influenced by the Saharan dust plume. Observed Fe(II) concentrations are compared and ratioed to the DFe concentrations, and indicate that iron(II) forms an important fraction (between 5 and 15%) of the total dissolved iron concentration in the study areas. Data plots for surface samples are presented with the corresponding physical oceanographic and solar irradiance data. The concentrations of Fe(II) observed during our studies exceed the values predicted from thermodynamic equilibrium modelling. This indicates that there is a steady supply of Fe(II) (possibly from photoreduction and/or biological origins) and/or Fe(II) is prevented from oxidation through stabilisation mechanisms (possibly by organic ligands). [1] A. R. Bowie, E. P. Achterberg, P. N. Sedwick, S. Ussher, P. J. Worsfold, Environ. Sci. Technol., 36, (2002) 4600. [2] A. R. Bowie, E. P. Achterberg, R. F. C. Mantoura, P. J. Worsfold, Anal. Chim. Acta, 377, (1998) 113.

Exposure of Trucking Company Workers to Particulate Matter during the Winter

PubMed Central

Lee, Byeong-Kyu; Smith, Thomas J.; Garshick, Eric; Natkin, Jonathan; Reaser, Paul; Lane, Kevin; Lee, Haengah Kim

2006-01-01

This study analyzed the workplace area concentrations and the personal exposure concentrations to fine particulate (PM2.5), elemental carbon (EC), and organic carbon (OC) measured during the winter period in trucking companies. The averaged personal exposure concentrations at breathing zones of workers are much greater than those of the microenvironment concentrations. The highest difference between the area (microenvironment) and personal exposure concentrations was in the PM2.5 concentrations followed by the OC concentrations. The area concentrations of PM2.5, EC, and OC at a large terminal were higher than those at a small one. The highest area concentrations of PM2.5, EC, and OC were observed in the shop areas followed by pick-up and delivery (P&D) areas. The area concentrations and personal exposure to PM2.5, EC, and OC in the shop and P&D areas which are highly affected by diesel engine exhaust emissions were much higher than those in the docks which are significantly affected by liquefied petroleum gas (LPG) engine exhaust emissions. The highest EC fraction to the total carbon (EC + OC) concentrations was observed in the shops, while the lowest one was identified in the offices. The personal exposure of the smoking workers to PM2.5 and OC was much higher than that of the non-smoking workers. However, the smoking might not significantly contribute to the personal exposure to EC. There were significant correlations between the PM2.5 and OC concentrations in both the area and personal exposure concentrations. However, significant correlations between the PM2.5 and EC concentrations and between the OC and EC concentrations were not identified. PMID:15913707

Distribution and sources of particulate mercury and other trace elements in PM2.5 and PM10 atop Mount Tai, China.

PubMed

Qie, Guanghao; Wang, Yan; Wu, Chen; Mao, Huiting; Zhang, Ping; Li, Tao; Li, Yaxin; Talbot, Robert; Hou, Chenxiao; Yue, Taixing

2018-06-01

The concentrations of particulate mercury (PHg) and other trace elements in PM 2.5 and PM 10 in the atmosphere were measured at the summit of Mount Tai during the time period of 15 June - 11 August 2015. The average PHg concentrations were 83.33 ± 119.1 pg/m 3 for PM 2.5 and 174.92 ± 210.5 pg/m 3 for PM 10 . Average concentrations for other trace elements, including Al, Ca, Fe, K, Mg, Na, Pb, As, Se, Cu, Cd, Cr, V, Mo, Co, Ag, Ba, Mn, Zn and Ni ranged from 0.06 ng/m 3 (Ag) to 354.33 ng/m 3 (Ca) in PM 2.5 and 0.11 ng/m 3 (Co) to 592.66 ng/m 3 (Ca) in PM 10 . The average concentrations of PHg were higher than those at other domestic mountain sites and cities in other counties, lower than those at domestic city sites. Other trace elements showed concentrations lower than those at the domestic mountain sites. Due possibly to increased control of emissions and the proportion of new energy, the PHg and trace element concentrations decreased, but the PHg showed concentrations higher than those at the Mountain sites, this showed that the reasons was not only severely affected by anthropogenic emissions, but also associated with other sources. The concentration changed trend of the main trace elements indicated that PHg, trace elements and particle matters present positive correlation and fine particulate matter has a greater surface area which was conductive to adsorption of Hg and trace elements to particles. On June 19, June 27 and July 6, according to the peak of mercury and trace elements, we can predict the potential sources of these three days. The results of principal component analysis (PCA) suggested that, crustal dust, coal combustion, and vehicle emissions were the main emission sources of PHg and other trace elements in Mount Tai. The 24-h backward trajectories and potential source contribution function (PSCF) analysis revealed that air masses arriving at Mount Tai were mainly affected by Shandong province. Mount Tai was subjected to five main airflow trajectories. Clusters 1, 2, 3, and 5 represented four pathways for local and regional sources and cluster 4 originated long-distance transportation. Central Shandong was the main source regions of PHg, Pb, Se, As, Cu and Cd. Southeastern and northwestern Shandong province and northern Jiangsu province were the most polluted source regions of Mn, Zn, and Ni. The crustal elements Fe and Ca had similar distributions of potential source regions, suggested by the highest PSCF values in southeastern Shandong and northern Jiangsu. Copyright © 2018 Elsevier Ltd. All rights reserved.

External contribution to urban air pollution.

PubMed

Grima, Ramon; Micallef, Alfred; Colls, Jeremy J

2002-02-01

Elevated particulate matter concentrations in urban locations have normally been associated with local traffic emissions. Recently it has been suggested that such episodes are influenced to a high degree by PM10 sources external to urban areas. To further corroborate this hypothesis, linear regression was sought between PM10 concentrations measured at eight urban sites in the U.K., with particulate sulphate concentration measured at two rural sites, for the years 1993-1997. Analysis of the slopes, intercepts and correlation coefficients indicate a possible relationship between urban PM10 and rural sulphate concentrations. The influences of wind direction and of the distance of the urban from the rural sites on the values of the three statistical parameters are also explored. The value of linear regression as an analysis tool in such cases is discussed and it is shown that an analysis of the sign of the rate of change of the urban PM10 and rural sulphate concentrations provides a more realistic method of correlation. The results indicate a major influence on urban PM10 concentrations from the eastern side of the United Kingdom. Linear correlation was also sought using PM10 data from nine urban sites in London and nearby rural Rochester. Analysis of the magnitude of the gradients and intercepts together with episode correlation analysis between the two sites showed the effect of transported PM10 on the local London concentrations. This article also presents methods to estimate the influence of rural and urban PM10 sources on urban PM10 concentrations and to obtain a rough estimate of the transboundary contribution to urban air pollution from the PM10 concentration data of the urban site.

Effect of climate variability and change on winter haze over eastern China in recent decades

NASA Astrophysics Data System (ADS)

Liao, Hong; Yang, Yang

2017-04-01

In recent years, eastern China has frequently experienced persistent and severe winter haze pollution episodes with high aerosol concentrations, which have affected half of the 1.3 billion people in China. In this work, the increases in wintertime aerosol concentrations and severe haze events in eastern China over 1985-2015 were quantified by using observed atmospheric visibility from the National Climatic Data Center Global Summary of Day database, observed PM2.5 concentrations from the network of China National Environmental Monitoring Centre (CNEMC), and simulated PM2.5 concentrations from the Goddard Earth-Observing System (GEOS) chemical transport model (GEOS-Chem). Observed winter haze days (defined as days with atmospheric visibility less than 10 km and relative humidity less than 80%) averaged over eastern China (105-122.5°E, 20-45°N) increased from 21 days in 1980 to 42 days in 2014. Observed severe haze days (defined as days with PM2.5 >150 μg m-3) occurred mainly over Northern China. Considering variations in both anthropogenic emissions and meteorological parameters, the GEOS-Chem model simulated an increasing trend in wintertime surface-layer PM2.5 concentrations of 10.5 (±6.2) μg m-3 decade-1 over eastern China in the past decades. Sensitivity studies showed that changes in anthropogenic emissions and in climate contributed 87% and 17% to this increasing trend, respectively. Wintertime severe haze events over eastern China showed large interannual variations, driven by climate variability. Process analyses were performed to identify the key meteorological parameters that determined the interannual variations of wintertime severe haze events.

Air quality in Delhi during the CommonWealth Games

NASA Astrophysics Data System (ADS)

Marrapu, P.; Cheng, Y.; Beig, G.; Sahu, S.; Srinivas, R.; Carmichael, G. R.

2014-04-01

Air quality during The CommonWealth Games (CWG, held in Delhi in October 2010) is analyzed using a new air quality forecasting system established for the Games. The CWG stimulated enhanced efforts to monitor and model air quality in the region. The air quality of Delhi during the CWG had high levels of particles with mean values of PM2.5 and PM10 at the venues of 111 and 238 μg m-3, respectively. Black carbon (BC) accounted for ∼10% of the PM2.5 mass. It is shown that BC, PM2.5 and PM10 concentrations are well predicted, but with positive biases of ∼25%. The diurnal variations are also well captured, with both the observations and the modeled values showing nighttime maxima and daytime minima. A new emissions inventory, developed as part of this air quality forecasting initiative, is evaluated by comparing the observed and predicted species-species correlations (i.e., BC : CO; BC : PM2.5; PM2.5 : PM10). Assuming that the observations at these sites are representative and that all the model errors are associated with the emissions, then the modeled concentrations and slopes can be made consistent by scaling the emissions by: 0.6 for NOx, 2 for CO, and 0.7 for BC, PM2.5 and PM10. The emission estimates for particles are remarkably good considering the uncertainty in the estimates due to the diverse spread of activities and technologies that take place in Delhi and the rapid rates of change. The contribution of various emission sectors including transportation, power, domestic and industry to surface concentrations are also estimated. Transport, domestic and industrial sectors all make significant contributions to PM levels in Delhi, and the sectoral contributions vary spatially within the city. Ozone levels in Delhi are elevated, with hourly values sometimes exceeding 100 ppb. The continued growth of the transport sector is expected to make ozone pollution a more pressing air pollution problem in Delhi. The sector analysis provides useful inputs into the design of strategies to reduce air pollution levels in Delhi. The contribution for sources outside of Delhi on Delhi air quality range from ∼25% for BC and PM to ∼60% for day time ozone. The significant contributions from non-Delhi sources indicates that in Delhi (as has been show elsewhere) these strategies will also need a more regional perspective.

PM(10) episodes in Greece: Local sources versus long-range transport-observations and model simulations.

PubMed

Matthaios, Vasileios N; Triantafyllou, Athanasios G; Koutrakis, Petros

2017-01-01

Periods of abnormally high concentrations of atmospheric pollutants, defined as air pollution episodes, can cause adverse health effects. Southern European countries experience high particulate matter (PM) levels originating from local and distant sources. In this study, we investigated the occurrence and nature of extreme PM 10 (PM with an aerodynamic diameter ≤10 μm) pollution episodes in Greece. We examined PM 10 concentration data from 18 monitoring stations located at five sites across the country: (1) an industrial area in northwestern Greece (Western Macedonia Lignite Area, WMLA), which includes sources such as lignite mining operations and lignite power plants that generate a high percentage of the energy in Greece; (2) the greater Athens area, the most populated area of the country; and (3) Thessaloniki, (4) Patra, and (5) Volos, three large cities in Greece. We defined extreme PM 10 pollution episodes (EEs) as days during which PM 10 concentrations at all five sites exceeded the European Union (EU) 24-hr PM 10 standards. For each EE, we identified the corresponding prevailing synoptic and local meteorological conditions, including wind surface data, for the period from January 2009 through December 2011. We also analyzed data from remote sensing and model simulations. We recorded 14 EEs that occurred over 49 days and could be grouped into two categories: (1) Local Source Impact (LSI; 26 days, 53%) and (2) African Dust Impact (ADI; 23 days, 47%). Our analysis suggested that the contribution of local sources to ADI EEs was relatively small. LSI EEs were observed only in the cold season, whereas ADI EEs occurred throughout the year, with a higher frequency during the cold season. The EEs with the highest intensity were recorded during African dust intrusions. ADI episodes were found to contribute more than local sources in Greece, with ADI and LSI fraction contribution ranging from 1.1 to 3.10. The EE contribution during ADI fluctuated from 41 to 83 μg/m 3 , whereas during LSI it varied from 14 to 67 μg/m 3 . This paper examines the occurrence and nature of extreme PM 10 pollution episodes (EEs) in Greece during a 3-yr period (2009-2011). Fourteen EEs were found of 49 days total duration, classified into two main categories: Local Source Impact (53%) and African Dust Impact (47%). All the above extreme PM 10 air pollution episodes were the result of specific synoptic prevailing conditions. Specific information on the linkages between the synoptic weather patterns and PM 10 concentrations could be used in the development of weather/health-warning system to alert the public that a synoptic episode is imminent.

Aerosol loading in the Southeastern United States: reconciling surface and satellite observations

NASA Astrophysics Data System (ADS)

Ford, B.; Heald, C. L.

2013-04-01

We investigate the seasonality in aerosols over the Southeastern United States using observations from several satellite instruments (MODIS, MISR, CALIOP) and surface network sites (IMPROVE, SEARCH, AERONET). We find that the strong summertime enhancement in satellite-observed aerosol optical depth (factor 2-3 enhancement over wintertime AOD) is not present in surface mass concentrations (25-55% summertime enhancement). Goldstein et al. (2009) previously attributed this seasonality in AOD to biogenic organic aerosol; however, surface observations show that organic aerosol only accounts for ~35% of PM2.5 mass and exhibits similar seasonality to total PM2.5. The GEOS-Chem model generally reproduces these surface aerosol measurements, but under represents the AOD seasonality observed by satellites. We show that seasonal differences in water uptake cannot sufficiently explain the magnitude of AOD increase. As CALIOP profiles indicate the presence of additional aerosol in the lower troposphere (below 700 hPa), which cannot be explained by vertical mixing; we conclude that the discrepancy is due to a missing source of aerosols above the surface in summer.

Experimental studies about the impact of traction sand on urban road dust composition.

PubMed

Kupiainen, Kaarle; Tervahattu, Heikki; Räisänen, Mika

2003-06-01

Traffic causes enhanced PM(10) resuspension especially during spring in the US, Japan, Norway, Sweden and Finland, among other countries. The springtime PM(10) consists primarily of mineral matter from tyre-induced paved road surface wear and traction sand. In some countries, the majority of vehicles are equipped with studded tyres to enhance traction, which additionally increases road surface wear. Because the traction sand and the mineral matter from the pavement aggregate can have a similar mineralogical composition, it has been difficult to determine the source of the mineral fraction in the PM(10). In this study, homogenous traction sand and pavement aggregate with different mineralogical compositions were chosen to determine the sources of PM(10) particles by single particle analysis (SEM/EDX). This study was conducted in a test facility, which made it possible to rule out dust contributions from other sources. The ambient PM(10) concentrations were higher when traction sand was used, regardless of whether the tyres were studded or not. Surprisingly, the use of traction sand greatly increased the number of the particles originating from the pavement. It was concluded that sand must contribute to pavement wear. This phenomenon is called the sandpaper effect. An understanding of this is important to reduce harmful effects of springtime road dust in practical winter maintenance of urban roads

Spatiotemporal prediction of continuous daily PM2.5 concentrations across China using a spatially explicit machine learning algorithm

NASA Astrophysics Data System (ADS)

Zhan, Yu; Luo, Yuzhou; Deng, Xunfei; Chen, Huajin; Grieneisen, Michael L.; Shen, Xueyou; Zhu, Lizhong; Zhang, Minghua

2017-04-01

A high degree of uncertainty associated with the emission inventory for China tends to degrade the performance of chemical transport models in predicting PM2.5 concentrations especially on a daily basis. In this study a novel machine learning algorithm, Geographically-Weighted Gradient Boosting Machine (GW-GBM), was developed by improving GBM through building spatial smoothing kernels to weigh the loss function. This modification addressed the spatial nonstationarity of the relationships between PM2.5 concentrations and predictor variables such as aerosol optical depth (AOD) and meteorological conditions. GW-GBM also overcame the estimation bias of PM2.5 concentrations due to missing AOD retrievals, and thus potentially improved subsequent exposure analyses. GW-GBM showed good performance in predicting daily PM2.5 concentrations (R2 = 0.76, RMSE = 23.0 μg/m3) even with partially missing AOD data, which was better than the original GBM model (R2 = 0.71, RMSE = 25.3 μg/m3). On the basis of the continuous spatiotemporal prediction of PM2.5 concentrations, it was predicted that 95% of the population lived in areas where the estimated annual mean PM2.5 concentration was higher than 35 μg/m3, and 45% of the population was exposed to PM2.5 >75 μg/m3 for over 100 days in 2014. GW-GBM accurately predicted continuous daily PM2.5 concentrations in China for assessing acute human health effects.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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=).

Sensitivity of WRF-Chem model to land surface schemes: Assessment in a severe dust outbreak episode in the Central Mediterranean (Apulia Region)

NASA Astrophysics Data System (ADS)

Rizza, Umberto; Miglietta, Mario Marcello; Mangia, Cristina; Ielpo, Pierina; Morichetti, Mauro; Iachini, Chiara; Virgili, Simone; Passerini, Giorgio

2018-03-01

The Weather Research and Forecasting model with online coupled chemistry (WRF-Chem) is applied to simulate a severe Saharan dust outbreak event that took place over Southern Italy in March 2016. Numerical experiments have been performed applying a physics-based dust emission model, with soil properties generated from three different Land Surface Models, namely Noah, RUC and Noah-MP. The model performance in reproducing the severe desert dust outbreak is analysed using an observational dataset of aerosol and desert dust features that includes optical properties from satellite and ground-based sun-photometers, and in-situ particulate matter mass concentration (PM) data. The results reveal that the combination of the dust emission model with the RUC Land Surface Model significantly over-predicts the emitted mineral dust; on the other side, the combination with Noah or Noah-MP Land Surface Model (LSM) gives better results, especially for the daily averaged PM10.

Ambient fine particulate matter in China: Its negative impacts and possible countermeasures.

PubMed

Qi, Zihan; Chen, Tingjia; Chen, Jiang; Qi, Xiaofei

2018-03-01

In recent decades, China has experienced rapid economic development accompanied by increasing concentrations of ambient PM 2.5 , particulate matter of less than 2.5 μm in diameter. PM 2.5 is now believed to be a carcinogen, causing higher lung cancer risks and generating losses to the economy and society. This meta-analysis evaluates the losses generated by ambient PM 2.5 in Suzhou from 2014 to 2016 and predicts losses at different concentrations. Estimations of total losses in Beijing, Shanghai, Hangzhou, Guangzhou, Dalian, and Xiamen are also presented, with a total national loss in 2015. The authors then demonstrate that lowering ambient PM 2.5 concentrations would be a realistic way for China to reduce the evaluated social losses in the short term. Possible legal measures are listed for lowering ambient PM 2.5 concentrations. The present findings quantify the economic effects of ambient PM 2.5 due to the increased incidence rate and mortality rate of lung cancer. Lowering ambient PM 2.5 concentrations would be the most realistic way for China to reduce tghe evaluated social losses in the short term. Possible legal measures for lowering ambient PM 2.5 concentrations to reduce the total losses are identified.

Concentration variations in primary and secondary particulate matter near a major road in Korea

DOE PAGES

Ghim, Young Sung; Won, Soo Ran; Choi, Yongjoo; ...

2016-03-31

Here, particle-phase concentrations were measured at 10, 80, and 200 m from the roadside of a national highway near Seoul in January and May 2008. The highway has two lanes each way, with an average hourly traffic volume of 1,070 vehicles. In January 2008, PM 10 concentrations decreased from 10 to 80 m but increased at 200 m. Black carbon (BC) decreased only slightly with distance due to the influence of biomass burning and open burning from the surrounding areas. In May 2008, the effect of secondary formation on both PM 10 and PM 2.5 was significant due to highmore » temperatures compared with January. Because on-road emissions had little effect on secondary formation for a short time, variations in PM 10 concentrations became smaller, and PM 2.5 concentrations increased with distance. The effects of fugitive dust on PM concentrations were greater in May than in January when the mean temperature was below freezing. In the composition variations, the amounts of primary ions, organic carbon (OC), and BC were larger in January, while those of secondary ions and others were larger in PM 10, as well as PM 2.5 in May.« less

Concentration variations in primary and secondary particulate matter near a major road in Korea

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

Ghim, Young Sung; Won, Soo Ran; Choi, Yongjoo

Here, particle-phase concentrations were measured at 10, 80, and 200 m from the roadside of a national highway near Seoul in January and May 2008. The highway has two lanes each way, with an average hourly traffic volume of 1,070 vehicles. In January 2008, PM 10 concentrations decreased from 10 to 80 m but increased at 200 m. Black carbon (BC) decreased only slightly with distance due to the influence of biomass burning and open burning from the surrounding areas. In May 2008, the effect of secondary formation on both PM 10 and PM 2.5 was significant due to highmore » temperatures compared with January. Because on-road emissions had little effect on secondary formation for a short time, variations in PM 10 concentrations became smaller, and PM 2.5 concentrations increased with distance. The effects of fugitive dust on PM concentrations were greater in May than in January when the mean temperature was below freezing. In the composition variations, the amounts of primary ions, organic carbon (OC), and BC were larger in January, while those of secondary ions and others were larger in PM 10, as well as PM 2.5 in May.« less

Pollution of PM10 in an underground enclosed loading dock in Malaysia

NASA Astrophysics Data System (ADS)

Abualqumboz, M. S.; Mohammed, N. I.; Malakahmad, A.; Nazif, A. N.; Albattniji, A. T.

2016-06-01

The enclosed nature of underground loading docks results in accumulation of motor vehicles emissions. Thus, concentration of numerous harmful air pollutants including PM10 particles can increase and reach dangerous levels. This paper aims to study short-term and long-term exposure of PM10 particles inside an underground loading dock located in Malaysia. In addition, the correlation with indoor temperature, relative humidity and vehicles flow will be measured. The concentrations of PM10 were measured for three consecutive weeks using the real-time air quality monitoring instrument AQM60. Series of statistical tests and multiple linear regression analysis were applied on the data using SPSS software and MATLAB R2013a. The results illustrated that PM10 daily average concentration was in compliance with the Malaysian guideline of 150 µg/m3. Actually, 95% of instantaneous PM10 concentration readings were below 75 μg/m3. In addition, significant correlation were found between PM10 concentration and indoor temperature, relative humidity and the previous concentration. The multiple R and R2 were 0.91 and 0.83, respectively. PM10 concentration was also correlated with motor vehicles flow. In conclusion, health effects of long-term exposure to small repetitive doses of air pollutant inside underground facilities should be studied and appropriate control measures need to be implemented.

Vertical profiles and ground-based measurements of Black Carbon, Particulate matter and Optical properties over New Delhi during the foggy winters of 2015-16

NASA Astrophysics Data System (ADS)

Tiwari, S.; Bisht, D. S.; Srivastava, A. K.; Hopke, P. K.; Chakrabarty, R. K.

2016-12-01

Ground level and vertical observations of particulate matter were made as part of a pilot experiment using an air-quality monitory tethered balloon flown in the lower troposphere (1000 m) during the foggy winters of New Delhi, India. Measurements of black carbon (BC), the dominant absorber of visible light, particulate matter (PM), and the particulate optical properties along with meteorological parameters were conducted during the winter of 2015-16 in Delhi. During the study period, the mean concentrations of PM2.5, BC370nm, and BC880nm were observed to be 144.0 ± 39.7, 25.3 ± 8.5, and 19.4 ± 6.9 μg/m3, respectively. The mean value of PM2.5 is 12 times higher than the daily US-EPA air quality standard. The contribution of BC370nm in PM2.5 is 18 %. During the foggy period, the ground level concentrations of fine (PM2.5) and soot (BC370nm) particles increased substantially (59% and 26%, respectively) in comparison to clear days. Also, the aerosol light extinction coefficient (σext) was much higher (mean: 610 Mm-1) indicating that atmosphere was not transparent resulting in lower visibility. High concentrations of PM2.5 (89 µg/m3) and BC880nm (25.7 µg/m3) were observed up to 200 m (fog persists in this layer) in January. The BC880nm and PM2.5 concentrations near 1 km were significantly higher ( 1.9 and 12 µg/m3), respectively. Direct radiative forcing (DRF) due to BC was estimated at the top of the atmosphere (TOA), surface (SFC), and atmospheric (ATM) and its resultant forcing were - 46.2 Wm-2 at SFC indicates the cooling effect. However, a positive value ( 20.8 Wm-2) of BC DRF at TOA indicates the warming effect over the study region. The resultant ATM DRF due to BC was positive (67.0 Wm-2) indicating a net warming effect in the atmosphere. The contribution of fossil fuel climate forcing due to BC was 79% and 21% was due to burning of biomass/biofuels. The higher mean atmospheric heating rate (2.05 K day-1) by BC in the winter season would probably strengthen the temperature inversion leading to poor dispersion and affecting the formation of clouds. Based on this study, serious detrimental impacts of high concentrations of BC and PM (especially PM2.5) on regional climate are likely, thereby highlighting the need for immediate, stringent measures to improve the regional air quality in northern India.

Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China.

PubMed

Yang, Haiou; Chen, Wenbo; Liang, Zhaofeng

2017-04-26

Fine particulate matter (PM 2.5 ) pollution has become one of the greatest urban issues in China. Studies have shown that PM 2.5 pollution is strongly related to the land use pattern at the micro-scale and optimizing the land use pattern has been suggested as an approach to mitigate PM 2.5 pollution. However, there are only a few researches analyzing the effect of land use on PM 2.5 pollution. This paper employed land use regression (LUR) models and statistical analysis to explore the effect of land use on PM 2.5 pollution in urban areas. Nanchang city, China, was taken as the study area. The LUR models were used to simulate the spatial variations of PM 2.5 concentrations. Analysis of variance and multiple comparisons were employed to study the PM 2.5 concentration variances among five different types of urban functional zones. Multiple linear regression was applied to explore the PM 2.5 concentration variances among the same type of urban functional zone. The results indicate that the dominant factor affecting PM 2.5 pollution in the Nanchang urban area was the traffic conditions. Significant variances of PM 2.5 concentrations among different urban functional zones throughout the year suggest that land use types generated a significant impact on PM 2.5 concentrations and the impact did not change as the seasons changed. Land use intensity indexes including the building volume rate, building density, and green coverage rate presented an insignificant or counter-intuitive impact on PM 2.5 concentrations when studied at the spatial scale of urban functional zones. Our study demonstrates that land use can greatly affect the PM 2.5 levels. Additionally, the urban functional zone was an appropriate spatial scale to investigate the impact of land use type on PM 2.5 pollution in urban areas.

Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China

PubMed Central

Yang, Haiou; Chen, Wenbo; Liang, Zhaofeng

2017-01-01

Fine particulate matter (PM2.5) pollution has become one of the greatest urban issues in China. Studies have shown that PM2.5 pollution is strongly related to the land use pattern at the micro-scale and optimizing the land use pattern has been suggested as an approach to mitigate PM2.5 pollution. However, there are only a few researches analyzing the effect of land use on PM2.5 pollution. This paper employed land use regression (LUR) models and statistical analysis to explore the effect of land use on PM2.5 pollution in urban areas. Nanchang city, China, was taken as the study area. The LUR models were used to simulate the spatial variations of PM2.5 concentrations. Analysis of variance and multiple comparisons were employed to study the PM2.5 concentration variances among five different types of urban functional zones. Multiple linear regression was applied to explore the PM2.5 concentration variances among the same type of urban functional zone. The results indicate that the dominant factor affecting PM2.5 pollution in the Nanchang urban area was the traffic conditions. Significant variances of PM2.5 concentrations among different urban functional zones throughout the year suggest that land use types generated a significant impact on PM2.5 concentrations and the impact did not change as the seasons changed. Land use intensity indexes including the building volume rate, building density, and green coverage rate presented an insignificant or counter-intuitive impact on PM2.5 concentrations when studied at the spatial scale of urban functional zones. Our study demonstrates that land use can greatly affect the PM2.5 levels. Additionally, the urban functional zone was an appropriate spatial scale to investigate the impact of land use type on PM2.5 pollution in urban areas. PMID:28445430

Physicochemical and optical properties of combustion-generated particles from Ship Diesel Engines

NASA Astrophysics Data System (ADS)

Kim, H.; Jeong, S.; Jin, H. C.; Kim, J. Y.

2015-12-01

Shipping contributes significantly to the anthropogenic burden of particulate matter (PM), and is among the world's highest polluting combustion sources per fuel consumed. Moreover, ships are a highly concentrated source of pollutants which are emitted into clean marine environments (e.g., Artic region). Shipping utilizes heavy fuel oil (HFO) which is less distilled compared to fuels used on land and few investigations on shipping related PM properties are available. BC is one of the dominant combustion products of ship diesel engines and its chemical and microphysical properties have a significant impact on climate by influencing the amount of albedo reduction on bright surfaces such as in polar regions. We have carried out a campaign to characterize the PM emissions from medium-sized marine engines in Gunsan, Jeonbuk Institute of Automotive Technology. The properties of ship-diesel PM have characterized depending on (1) fuel sulfur content (HFO vs. ULSD) and (2) engine conditions (Running state vs. Idling state). Scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), energy-dispersive X-ray spectroscopy (EDX) equipped with HRTEM and Raman spectroscopy were used for physicochemical analysis. Optical properties, which are ultimately linked to the snow/ice albedo decrease impacting climate, were assessed as well. PM generated under high engine temperature conditions had typical features of soot, e.g., concentric circles comprised of closely packed graphene layers, however PM generated by the idling state at low combustion temperature was characterized by amorphous and droplet-like carbonaceous particles with no crystalline structure. Significant differences in optical properties depending on the combustion conditions were also observed. Particles from running conditions showed wavelength-independent absorbing properties, whereas the particles from idling conditions showed enhanced absorption at shorter wavelengths, which is characteristic of brown carbon. Regarding different fuel types, distinctive structure differences were not observed, but EDX results showed that PM generated by HFO combustion has sulfur content in PM whereas ULSD generated 100% carbon composed PM.

Indoor air quality in urban nurseries at Porto city: Particulate matter assessment

NASA Astrophysics Data System (ADS)

Branco, P. T. B. S.; Alvim-Ferraz, M. C. M.; Martins, F. G.; Sousa, S. I. V.

2014-02-01

Indoor air quality in nurseries is an interesting case of study mainly due to children's high vulnerability to exposure to air pollution (with special attention to younger ones), and because nursery is the public environment where young children spend most of their time. Particulate matter (PM) constitutes one of the air pollutants with greater interest. In fact, it can cause acute effects on children's health, as well as may contribute to the prevalence of chronic respiratory diseases like asthma. Thus, the main objectives of this study were: i) to evaluate indoor concentrations of particulate matter (PM1, PM2.5, PM10 and PMTotal) on different indoor microenvironments in urban nurseries of Porto city; and ii) to analyse those concentrations according to guidelines and references for indoor air quality and children's health. Indoor PM measurements were performed in several class and lunch rooms in three nurseries on weekdays and weekends. Outdoor PM10 concentrations were also obtained to determine I/O ratios. PM concentrations were often found high in the studied classrooms, especially for the finer fractions, reaching maxima hourly mean concentrations of 145 μg m-3 for PM1 and 158 μg m-3 PM2.5, being often above the limits recommended by WHO, reaching 80% of exceedances for PM2.5, which is concerning in terms of exposure effects on children's health. Mean I/O ratios were always above 1 and most times above 2 showing that indoor sources (re-suspension phenomena due to children's activities, cleaning and cooking) were clearly the main contributors to indoor PM concentrations when compared with the outdoor influence. Though, poor ventilation to outdoors in classrooms affected indoor air quality by increasing the PM accumulation. So, enhancing air renovation rate and performing cleaning activities after the occupancy period could be good practices to reduce PM indoor air concentrations in nurseries and, consequently, to improve children's health and welfare.

Organic and elemental carbon bound to particulate matter in the air of printing office and beauty salon

NASA Astrophysics Data System (ADS)

Rogula-Kopiec, Patrycja; Pastuszka, Józef S.; Rogula-Kozłowska, Wioletta; Mucha, Walter

2017-11-01

The aim of this study was to determine the role of internal sources of emissions on the concentrations of total suspended particulate matter (TSP) and its sub-fraction, so-called respirable PM (PM4; fraction of particles with particle size ≤ 4 µm) and to estimate to which extent those emissions participate in the formation of PM-bound elemental (EC) and organic (OC) carbon in two facilities - one beauty salon and one printing office located in Bytom (Upper Silesia, Poland). The average concentration of PM in the printing office and beauty salon during the 10-day measurement period was 10 and 4 (PM4) and 8 and 3 (TSP) times greater than the average concentration of PM fractions recorded in the same period in the atmospheric air; it was on average: 204 µg/m3 (PM4) and 319 µg/m3 (TSP) and 93 µg/m3 (PM4) and 136 µg/m3 (TSP), respectively. OC concentrations determined in the printing office were 38 µg/m3 (PM4) and 56 µg/m3 (TSP), and those referring to EC: 1.8 µg/m3 (PM4) and 3.5 µg/m3 (TSP). In the beauty salon the average concentration of OC for PM4 and TSP were 58 and 75 µg/m3, respectively and in case of EC - 3.1 and 4.7 µg/m3, respectively. The concentrations of OC and EC within the those facilities were approximately 1.7 (TSP-bound EC, beauty salon) to 4.7 (TSP-bound OC, printing office) times higher than the average atmospheric concentrations of those compounds measured in both PM fractions at the same time. In both facilities the main source of TSP-and PM4-bound OC in the indoor air were the chemicals - solvents, varnishes, paints, etc.

SCIENCE VERSION OF PM CHEMISTRY MODEL

EPA Science Inventory

PM chemistry models containing detailed treatments of key chemical processes controlling ambient concentrations of inorganic and organic compounds in PM2.5 are needed to develop strategies for reducing PM2.5 concentrations. This task, that builds on previous research conducted i...

Development of a job-exposure matrix for exposure to total and fine particulate matter in the aluminum industry.

PubMed

Noth, Elizabeth M; Dixon-Ernst, Christine; Liu, Sa; Cantley, Linda; Tessier-Sherman, Baylah; Eisen, Ellen A; Cullen, Mark R; Hammond, S Katharine

2014-01-01

Increasing evidence indicates that exposure to particulate matter (PM) at environmental concentrations increases the risk of cardiovascular disease, particularly PM with an aerodynamic diameter of less than 2.5 μm (PM(2.5)). Despite this, the health impacts of higher occupational exposures to PM(2.5) have rarely been evaluated. In part, this research gap derives from the absence of information on PM(2.5) exposures in the workplace. To address this gap, we have developed a job-exposure matrix (JEM) to estimate exposure to two size fractions of PM in the aluminum industry. Measurements of total PM (TPM) and PM(2.5) were used to develop exposure metrics for an epidemiologic study. TPM exposures for distinct exposure groups (DEGs) in the JEM were calculated using 8385 personal TPM samples collected at 11 facilities (1980-2011). For eight of these facilities, simultaneous PM(2.5) and TPM personal monitoring was conducted from 2010 to 2011 to determine the percent of TPM that is composed of PM(2.5) (%PM(2.5)) in each DEG. The mean TPM from the JEM was then multiplied by %PM(2.5) to calculate PM(2.5) exposure concentrations in each DEG. Exposures in the smelters were substantially higher than in fabrication units; mean TPM concentrations in smelters and fabrication facilities were 3.86 and 0.76 mg/m(3), and the corresponding mean PM(2.5) concentrations were 2.03 and 0.40 mg/m(3). Observed occupational exposures in this study generally exceeded environmental PM(2.5) concentrations by an order of magnitude.

Development of a job-exposure matrix for exposure to total and fine particulate matter in the aluminum industry

PubMed Central

Noth, Elizabeth M.; Dixon-Ernst, Christine; Liu, Sa; Cantley, Linda; Tessier-Sherman, Baylah; Eisen, Ellen A.; Cullen, Mark R.; Hammond, S. Katharine

2014-01-01

Increasing evidence indicates that exposure to particulate matter (PM) at environmental concentrations increases the risk of cardiovascular disease, particularly PM with an aerodynamic diameter of less than 2.5μm (PM2.5). Despite this, the health impacts of higher occupational exposures to PM2.5 have rarely been evaluated. In part, this research gap derives from the absence of information on PM2.5 exposures in the workplace. To address this gap, we have developed a job-exposure matrix (JEM) to estimate exposure to two size fractions of PM in the aluminum industry. Measurements of total PM (TPM) and PM2.5 were used to develop exposure metrics for an epidemiologic study. TPM exposures for distinct exposure groups (DEGs) in the JEM were calculated using 8,385 personal TPM samples collected at 11 facilities (1980-2011). For 8 of these facilities, simultaneous PM2.5 and TPM personal monitoring was conducted from 2010-2011 to determine the percent of TPM that is composed of PM2.5 (%PM2.5) in each DEG. The mean TPM from the JEM was then multiplied by %PM2.5 to calculate PM2.5 exposure concentrations in each DEG. Exposures in the smelters were substantially higher than in fabrication units; mean TPM concentrations in smelters and fabrication facilities were 3.86 mg/m3 and 0.76 mg/m3, and the corresponding mean PM2.5 concentrations were 2.03 mg/m3 and 0.40 mg/m3. Observed occupational exposures in this study generally exceeded environmental PM2.5 concentrations by an order of magnitude. PMID:24022670

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.

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.

Experimental and statistical analyses to characterize in-vehicle fine particulate matter behavior inside public transit buses operating on B20-grade biodiesel fuel

NASA Astrophysics Data System (ADS)

Vijayan, Abhilash; Kumar, Ashok

2010-11-01

This paper presents results from an in-vehicle air quality study of public transit buses in Toledo, Ohio, involving continuous monitoring, and experimental and statistical analyses to understand in-vehicle particulate matter (PM) behavior inside buses operating on B20-grade biodiesel fuel. The study also focused on evaluating the effects of vehicle's fuel type, operating periods, operation status, passenger counts, traffic conditions, and the seasonal and meteorological variation on particulates with aerodynamic diameter less than 1 micron (PM 1.0). The study found that the average PM 1.0 mass concentrations in B20-grade biodiesel-fueled bus compartments were approximately 15 μg m -3, while PM 2.5 and PM 10 concentration averages were approximately 19 μg m -3 and 37 μg m -3, respectively. It was also observed that average hourly concentration trends of PM 1.0 and PM 2.5 followed a "μ-shaped" pattern during transit hours. Experimental analyses revealed that the in-vehicle PM 1.0 mass concentrations were higher inside diesel-fueled buses (10.0-71.0 μg m -3 with a mean of 31.8 μg m -3) as compared to biodiesel buses (3.3-33.5 μg m -3 with a mean of 15.3 μg m -3) when the windows were kept open. Vehicle idling conditions and open door status were found to facilitate smaller particle concentrations inside the cabin, while closed door facilitated larger particle concentrations suggesting that smaller particles were originating outside the vehicle and larger particles were formed within the cabin, potentially from passenger activity. The study also found that PM 1.0 mass concentrations at the back of bus compartment (5.7-39.1 μg m -3 with a mean of 28.3 μg m -3) were higher than the concentrations in the front (5.7-25.9 μg m -3 with a mean of 21.9 μg m -3), and the mass concentrations inside the bus compartment were generally 30-70% lower than the just-outside concentrations. Further, bus route, window position, and time of day were found to affect the in-vehicle PM concentrations significantly. Overall, the in-vehicle PM 1.0 concentrations inside the buses operating on B20-grade biodiesel ranged from 0.7 μg m -3 to 243 μg m -3, with a median of 11.6 μg m -3. Statistical models developed to study the effects of vehicle operation and ambient conditions on in-vehicle PM concentrations suggested that while open door status was the most important influencing variable for finer particles and higher passenger activity resulted in higher coarse particles concentrations inside the vehicle compartments, ambient PM concentrations contributed to all PM fractions inside the bus irrespective of particle size.

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

PubMed Central

2012-01-01

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

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.

Airborne pollutant characteristics in an urban, industrial and agricultural complex metroplex with high emission loading and ammonia concentration.

PubMed

Tsai, Jiun-Horng; Chang, Li-Peng; Chiang, Hung-Lung

2014-10-01

The size distribution of particulate mass and water-soluble ionic constituents and their gaseous precursors was investigated in a subtropical area, southern Taiwan. Field sampling and chemical analysis of particulate matter (PM) were conducted using a Micro Orifice Uniform Deposition Impactor (MOUDI) and a Nano-MOUDI, and gaseous pollutants were determined by a denuder-filter pack system. PM size mass distribution, mass concentration and ionic species concentration were measured during the day and at night in the winter and summer. Average PM concentrations in the winter were as high as 132 ± 42 μg/m(3), and PM mass concentrations in the summer were as low as 38 ± 19 μg/m(3). Generally, PM concentration was 111 ± 60 μg/m(3) at night, which was 20% higher than that in the daytime. The size-segregated mass distribution of PM mass concentration was over 85% in the 0.1-3.2 μm range. Ammonium, nitrate, and sulfate were the dominant water-soluble ionic species in PM, contributing 34%-48% of PM mass. High ammonia (12.9-49 μg/m(3)) and SO2 (2.6-27 μg/m(3)) were observed in the gas precursors. The molar ratio [Formula: see text] was 3.18 ± 1.20 at PM1.0, which indicated that the PM was rich in ammonium. Therefore, the excess ammonium could neutralize nitrate to form ammonium nitrate, after the more stable ammonium sulfate and ammonium bisulfate formation. Copyright © 2014 Elsevier B.V. All rights reserved.

Spatio-temporal variability of particulate matter in the key part of Gansu Province, Western China.

PubMed

Guan, Qingyu; Cai, Ao; Wang, Feifei; Yang, Liqin; Xu, Chuanqi; Liu, Zeyu

2017-11-01

To investigate the spatial and temporal behaviors of particulate matter in Lanzhou, Jinchang and Jiayuguan during 2014, the hourly concentrations of PM2.5 and PM10 were collected from the Ministry of Environmental Protection (MEP) in this study. The analysis indicated that the mean annual PM10 (PM2.5) concentrations during 2014 were 115 ± 52 μg/m 3 (57 ± 28 μg/m 3 ), 104 ± 75 μg/m 3 (38 ± 22 μg/m 3 ) and 114 ± 72 μg/m 3 (32 ± 17 μg/m 3 ) in Lanzhou, Jinchang and Jiayuguan, respectively, all of which exceeded the Chinese national ambient air quality II standards for PM. Higher values for both PM fractions were generally observed in spring and winter, and lower concentrations were found in summer and autumn. Besides, the trend of seasonal variation of particulate matter (PM) in each city monitoring site is consistent with the average of the corresponding cities. Anthropogenic activities along with the boundary layer height and wind scale contributed to diurnal variations in PM that varied bimodally (Lanzhou and Jinchang) or unimodally (Jiayuguan). With the arrival of dust events, the PM10 concentrations changed dramatically, and the PM10 concentrations during dust storm events were, respectively, 19, 43 and 17 times higher than the levels before dust events in Lanzhou, Jinchang and Jiayuguan. The ratios (PM2.5/PM10) were lowest, while the correlations were highest, indicating that dust events contributed more coarse than fine particles, and the sources of PM are similar during dust storms. The relationships between local meteorological parameters and PM concentrations suggest a clear association between the highest PM concentrations, with T ≤ 7 °C, and strong winds (3-4 scale). However, the effect of relative humidity is complicated, with more PM10 and PM2.5 exceedances being registered with a relative humidity of less than 40% and 40-60% in Lanzhou, while higher exceedances in Jinchang appeared at a relative humidity of 80-100%. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of Summer and Winter California Central Valley Aerosol Distributions from Lidar and MODIS Measurements

NASA Technical Reports Server (NTRS)

Lewis, Jasper R., Jr.; DeYoung, Russell J.; Chu, D. Allen

2010-01-01

Aerosol distributions from two aircraft lidar campaigns conducted in the California Central Valley are compared in order to identify seasonal variations. Aircraft lidar flights were conducted in June 2003 and February 2008. While the PM2.5 concentration is highest in the winter, the aerosol optical depth measured from MODIS is highest in the summer. A seasonal comparison shows that PM2.5 in the winter can exceed summer PM2.5 by 55%, while summer AOD exceeds winter AOD by 43%. Higher temperatures wildfires in the summer produce elevated aerosol layers that are detected by satellite measurements, but not surface particulate matter monitors. Measurements of the boundary layer height from lidar instruments are necessary to incorporate satellite measurements with air quality measurements.

Enzyme-enhanced fluorescence detection of DNA on etched optical fibers.

PubMed

Niu, Shu-yan; Li, Quan-yi; Ren, Rui; Zhang, Shu-sheng

2009-05-15

A novel DNA biosensor based on enzyme-enhanced fluorescence detection on etched optical fibers was developed. The hybridization complex of DNA probe and biotinylated target was formed on the etched optical fiber, and was then bound with streptavidin labeled horseradish peroxidase (streptavidin-HRP). The target DNA was quantified through the fluorescent detection of bi-p,p'-4-hydroxyphenylacetic acid (DBDA) generated from the substrate 4-hydroxyphenylacetic acid (p-HPA) under the catalysis of HRP, with a detection limit of 1 pM and a linear range from 1.69 pM to 169 pM. It is facile to regenerate this sensor through surface treatment with concentrated urea solution. It was discovered that the sensor can retain 70% of its original activity after three detection-regeneration cycles.

Analysis of traffic and meteorology on airborne particulate matter in Münster, northwest Germany.

PubMed

Gietl, Johanna K; Klemm, Otto

2009-07-01

The importance of street traffic and meteorological conditions on the concentrations of particulate matter (PM) with an aerodynamic diameter smaller than 10 microm (PM10) was studied in the city of Münster in northwest Germany. The database consisted of meteorological data, data of PM10 mass concentrations and fine particle number (6-225 nm diameter) concentrations, and traffic intensity data as counted with tally hand counters at a four- to six-lane road. On working days, a significant correlation could be found between the diurnal mean PM10 mass concentration and vehicle number. The lower number of heavy-duty vehicles compared with passenger cars contributed more to the particle number concentration on working days than on weekend days. On weekends, when the vehicle number was very low, the correlation between PM10 mass concentration and vehicle number changed completely. Other sources of PM and the meteorology dominated the PM concentration. Independent of the weekday, by decreasing the traffic by approximately 99% during late-night hours, the PM10 concentration was reduced by 12% of the daily mean value. A correlation between PM10 and the particle number concentration was found for each weekday. In this study, meteorological parameters, including the atmospheric stability of the boundary layer, were also accounted for. The authors deployed artificial neural networks to achieve more information on the influence of various meteorological parameters, traffic, and the day of the week. A multilayer perceptron network showed the best results for predicting the PM10 concentration, with the correlation coefficient being 0.72. The influence of relative humidity, temperature, and wind was strong, whereas the influence of atmospheric stability and the traffic parameters was weak. Although traffic contributes a constant amount of particles in a daily and weekly cycle, it is the meteorology that drives most of the variability.

Comparison of wildfire smoke estimation methods and associations with cardiopulmonary-related hospital admissions.

PubMed

Gan, Ryan W; Ford, Bonne; Lassman, William; Pfister, Gabriele; Vaidyanathan, Ambarish; Fischer, Emily; Volckens, John; Pierce, Jeffrey R; Magzamen, Sheryl

2017-03-01

Climate forecasts predict an increase in frequency and intensity of wildfires. Associations between health outcomes and population exposure to smoke from Washington 2012 wildfires were compared using surface monitors, chemical-weather models, and a novel method blending three exposure information sources. The association between smoke particulate matter ≤2.5 μm in diameter (PM 2.5 ) and cardiopulmonary hospital admissions occurring in Washington from 1 July to 31 October 2012 was evaluated using a time-stratified case-crossover design. Hospital admissions aggregated by ZIP code were linked with population-weighted daily average concentrations of smoke PM 2.5 estimated using three distinct methods: a simulation with the Weather Research and Forecasting with Chemistry (WRF-Chem) model, a kriged interpolation of PM 2.5 measurements from surface monitors, and a geographically weighted ridge regression (GWR) that blended inputs from WRF-Chem, satellite observations of aerosol optical depth, and kriged PM 2.5 . A 10 μg/m 3 increase in GWR smoke PM 2.5 was associated with an 8% increased risk in asthma-related hospital admissions (odds ratio (OR): 1.076, 95% confidence interval (CI): 1.019-1.136); other smoke estimation methods yielded similar results. However, point estimates for chronic obstructive pulmonary disease (COPD) differed by smoke PM 2.5 exposure method: a 10 μg/m 3 increase using GWR was significantly associated with increased risk of COPD (OR: 1.084, 95%CI: 1.026-1.145) and not significant using WRF-Chem (OR: 0.986, 95%CI: 0.931-1.045). The magnitude (OR) and uncertainty (95%CI) of associations between smoke PM 2.5 and hospital admissions were dependent on estimation method used and outcome evaluated. Choice of smoke exposure estimation method used can impact the overall conclusion of the study.

PARTICULATE MATTER CONCENTRATIONS MEASURED IN A RESIDENTIAL NEIGHBORHOOD IN BROOKLYN, NEW YORK CITY DURING THE TRAFFIC-RELATED EXPOSURE STUDY (T-REX)

EPA Science Inventory

PM₁₀, PM_10-2.5, and PM_2.5 concentrations has been measured daily in the Sunset Park neighborhood of Brooklyn, NY from April 21 to May 17, 2005. Results showed the average concentrations of PM fractions were higher when measured closet to the majo...

Aryl hydrocarbon receptor-mediated activity of atmospheric particulate matter from an urban and a rural site in Switzerland

NASA Astrophysics Data System (ADS)

Wenger, Daniela; Gerecke, Andreas C.; Heeb, Norbert V.; Hueglin, Christoph; Seiler, Cornelia; Haag, Regula; Naegeli, Hanspeter; Zenobi, Renato

Atmospheric particulate matter (PM) is an air-suspended mixture of solid and liquid particles that vary in size, shape, and chemical composition. Long-term exposure to elevated concentrations of fine atmospheric particles is considered to pose a health threat to humans and animals. In this context, it has been hypothesized that toxic chemicals such as polycyclic aromatic hydrocarbons (PAHs) play an important role. Some PAHs are known to be carcinogenic and it has been shown that carcinogenic effects of PAHs are mediated by the aryl hydrocarbon receptor (AhR). In this study, PM1 was collected at a rural and an urban traffic site during an intense winter smog period, in which concentration of PM1 often exceeded 50 μg m -3. We applied an in vitro reporter gene assay (DR-CALUX) to detect and quantify PM1-associated chemicals that induce AhR-mediated gene expression. This activity was expressed as CALUX equivalents of 2,3,7,8-tetrachlorodibenzodioxin (PM-TCDD-CEQs). In addition, concentrations of PAHs in the PM1 extracts were determined using gas chromatography/high-resolution mass spectrometry. Concentrations of PM-TCDD-CEQs ranged from 10 to 85 pg m -3 and from 19 to 87 pg m -3 at the urban and rural site, respectively. By the use of known relative potency factors, the measured concentration of a PAH was converted into a PAH-TCDD-CEQ concentration. ΣPAH-TCDD-CEQ and PM-TCDD-CEQ were highly correlated at both sites ( r2 = 0.90 and 0.69). The calculated ΣPAH-TCDD-CEQs explain between 2% and 20% of the measured PM-TCDD-CEQs. Benzo[ k]fluoranthene was the most important PAH causing approximately 60% of the total ΣPAH-TCDD-CEQ activity. In contrast to NO, CO, PM10, and PM1, the concentration of PM-TCDD-CEQs showed no significant difference between the two sites. No indications were found that road traffic emissions caused elevated concentrations of PM-TCDD-CEQs at the urban traffic site.

Assessment of indoor and outdoor particulate air pollution at an urban background site in Iran.

PubMed

Mohammadyan, Mahmoud; Ghoochani, Mahboobeh; Kloog, Itai; Abdul-Wahab, Sabah Ahmed; Yetilmezsoy, Kaan; Heibati, Behzad; Godri Pollitt, Krystal J

2017-05-01

The relationship between indoor and outdoor particulate air pollution was investigated at an urban background site on the Payambar Azam Campus of Mazandaran University of Medical Sciences in Sari, Northern Iran. The concentration of particulate matter sized with a diameter less than 1 μm (PM 1.0 ), 2.5 μm (PM 2.5 ), and 10 μm (PM 10 ) was evaluated at 5 outdoor and 12 indoor locations. Indoor sites included classrooms, corridors, and office sites in four university buildings. Outdoor PM concentrations were characterized at five locations around the university campus. Indoor and outdoor PM measurements (1-min resolution) were conducted in parallel during weekday mornings and afternoons. No difference found between indoor PM 10 (50.1 ± 32.1 μg/m 3 ) and outdoor PM 10 concentrations (46.5 ± 26.0 μg/m 3 ), indoor PM 2.5 (22.6 ± 17.4 μg/m 3 ) and outdoor PM 2.5 concentration (22.2 ± 15.4 μg/m 3 ), or indoor PM 1.0 (14.5 ± 13.4 μg/m 3 ) and outdoor mean PM 1.0 concentrations (14.2 ± 12.3 μg/m 3 ). Despite these similar concentrations, no correlations were found between outdoor and indoor PM levels. The present findings are not only of importance for the potential health effects of particulate air pollution on people who spend their daytime over a period of several hours in closed and confined spaces located at a university campus but also can inform regulatory about the improvement of indoor air quality, especially in developing countries.

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

PubMed

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

2017-01-01

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

Low correlation between household carbon monoxide and particulate matter concentrations from biomass-related pollution in three resource-poor settings.

PubMed

Klasen, Elizabeth M; Wills, Beatriz; Naithani, Neha; Gilman, Robert H; Tielsch, James M; Chiang, Marilu; Khatry, Subarna; Breysse, Patrick N; Menya, Diana; Apaka, Cosmas; Carter, E Jane; Sherman, Charles B; Miranda, J Jaime; Checkley, William

2015-10-01

Household air pollution from the burning of biomass fuels is recognized as the third greatest contributor to the global burden of disease. Incomplete combustion of biomass fuels releases a complex mixture of carbon monoxide (CO), particulate matter (PM) and other toxins into the household environment. Some investigators have used indoor CO concentrations as a reliable surrogate of indoor PM concentrations; however, the assumption that indoor CO concentration is a reasonable proxy of indoor PM concentration has been a subject of controversy. We sought to describe the relationship between indoor PM2.5 and CO concentrations in 128 households across three resource-poor settings in Peru, Nepal, and Kenya. We simultaneously collected minute-to-minute PM2.5 and CO concentrations within a meter of the open-fire stove for approximately 24h using the EasyLog-USB-CO data logger (Lascar Electronics, Erie, PA) and the personal DataRAM-1000AN (Thermo Fisher Scientific Inc., Waltham, MA), respectively. We also collected information regarding household construction characteristics, and cooking practices of the primary cook. Average 24h indoor PM2.5 and CO concentrations ranged between 615 and 1440 μg/m(3), and between 9.1 and 35.1 ppm, respectively. Minute-to-minute indoor PM2.5 concentrations were in a safe range (<25 μg/m(3)) between 17% and 65% of the time, and exceeded 1000 μg/m(3) between 8% and 21% of the time, whereas indoor CO concentrations were in a safe range (<7 ppm) between 46% and 79% of the time and exceeded 50 ppm between 4%, and 20% of the time. Overall correlations between indoor PM2.5 and CO concentrations were low to moderate (Spearman ρ between 0.59 and 0.83). There was also poor agreement and evidence of proportional bias between observed indoor PM2.5 concentrations vs. those estimated based on indoor CO concentrations, with greater discordance at lower concentrations. Our analysis does not support the notion that indoor CO concentration is a surrogate marker for indoor PM2.5 concentration across all settings. Both are important markers of household air pollution with different health and environmental implications and should therefore be independently measured. Published by Elsevier Inc.

Application of WRF/Chem over East Asia: Part I. Model evaluation and intercomparison with MM5/CMAQ

NASA Astrophysics Data System (ADS)

Zhang, Yang; Zhang, Xin; Wang, Litao; Zhang, Qiang; Duan, Fengkui; He, Kebin

2016-01-01

In this work, the application of the online-coupled Weather Research and Forecasting model with chemistry (WRF/Chem) version 3.3.1 is evaluated over East Asia for January, April, July, and October 2005 and compared with results from a previous application of an offline model system, i.e., the Mesoscale Model and Community Multiple Air Quality modeling system (MM5/CMAQ). The evaluation of WRF/Chem is performed using multiple observational datasets from satellites and surface networks in mainland China, Hong Kong, Taiwan, and Japan. WRF/Chem simulates well specific humidity (Q2) and downward longwave and shortwave radiation (GLW and GSW) with normalized mean biases (NMBs) within 24%, but shows moderate to large biases for temperature at 2-m (T2) (NMBs of -9.8% to 75.6%) and precipitation (NMBs of 11.4-92.7%) for some months, and wind speed at 10-m (WS10) (NMBs of 66.5-101%), for all months, indicating some limitations in the YSU planetary boundary layer scheme, the Purdue Lin cloud microphysics, and the Grell-Devenyi ensemble scheme. WRF/Chem can simulate the column abundances of gases reasonably well with NMBs within 30% for most months but moderately to significantly underpredicts the surface concentrations of major species at all sites in nearly all months with NMBs of -72% to -53.8% for CO, -99.4% to -61.7% for NOx, -84.2% to -44.5% for SO2, -63.9% to -25.2% for PM2.5, and -68.9% to 33.3% for PM10, and aerosol optical depth in all months except for October with NMBs of -38.7% to -16.2%. The model significantly overpredicts surface concentrations of O3 at most sites in nearly all months with NMBs of up to 160.3% and NO3- at the Tsinghua site in all months. Possible reasons for large underpredictions include underestimations in the anthropogenic emissions of CO, SO2, and primary aerosol, inappropriate vertical distributions of emissions of SO2 and NO2, uncertainties in upper boundary conditions (e.g., for O3 and CO), missing or inaccurate model representations (e.g., secondary organic aerosol formation, gas/particle partitioning, dust emissions, dry and wet deposition), and inaccurate meteorological fields (e.g., overpredictions in WS10 and precipitation, but underpredictions in T2), as well as the large uncertainties in satellite retrievals (e.g., for column SO2). Comparing to MM5, WRF generally gives worse performance in meteorological predictions, in particular, T2, WS10, GSW, GLW, and cloud fraction in all months, as well as Q2 and precipitation in January and October, due to limitations in the above physics schemes or parameterizations. Comparing to CMAQ, WRF/Chem performs better for surface CO, O3, and PM10 concentrations at most sites in most months, column CO and SO2 abundances, and AOD. It, however, gives poorer performance for surface NOx concentrations at most sites in most months, surface SO2 concentrations at all sites in all months, and column NO2 abundances in January and April. WRF/Chem also gives lower concentrations of most secondary PM and black carbon. Those differences in results are attributed to differences in simulated meteorology, gas-phase chemistry, aerosol thermodynamic and dynamic treatments, dust and sea salt emissions, and wet and dry deposition treatments in both models.

Estimating hourly PM1 concentrations from Himawari-8 aerosol optical depth in China.

PubMed

Zang, Lin; Mao, Feiyue; Guo, Jianping; Gong, Wei; Wang, Wei; Pan, Zengxin

2018-06-11

Particulate matter with diameter less than 1 μm (PM 1 ) has been found to be closely associated with air quality, climate changes, and even adverse human health. However, a large gap in our knowledge concerning the large-scale distribution and variability of PM 1 remains, which is expected to be bridged with advanced remote-sensing techniques. In this study, a hybrid model called principal component analysis-general regression neural network (PCA-GRNN) is developed to estimate hourly PM 1 concentrations from Himawari-8 aerosol optical depth in combination with coincident ground-based PM 1 measurements in China. Results indicate that the hourly estimated PM 1 concentrations from satellite agree well with the measured values at national scale, with R 2 of 0.65, root-mean-square error (RMSE) of 22.0 μg/m 3 and mean absolute error (MAE) of 13.8 μg/m 3 . On daily and monthly time scales, R 2 increases to 0.70 and 0.81, respectively. Spatially, highly polluted regions of PM 1 are largely located in the North China Plain and Northeast China, in accordance with the distribution of industrialisation and urbanisation. In terms of diurnal variability, PM 1 concentration tends to peak in rush hours during the daytime. PM 1 exhibits distinct seasonality with winter having the largest concentration (31.5±3.5 μg/m 3 ), largely due to peak combustion emissions. We further attempt to estimate PM 2.5 and PM 10 with the proposed method and find that the accuracies of the proposed model for PM 1 and PM 2.5 estimation are significantly higher than that of PM 10 . Our findings suggest that geostationary data is one of the promising data to estimate fine particle concentration on large spatial scale. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Distribution of dust during two dust storms in Iceland

NASA Astrophysics Data System (ADS)

Ösp Magnúsdóttir, Agnes; Dagsson-Waldhauserova, Pavla; Arnalds, Ólafur; Ólafsson, Haraldur

2017-04-01

Particulate matter mass concentrations and size fractions of PM1, PM2.5, PM4, PM10, and PM15 measured in transversal horizontal profile of two dust storms in southwestern Iceland are presented. Images from a camera network were used to estimate the visibility and spatial extent of measured dust events. Numerical simulations were used to calculate the total dust flux from the sources as 180,000 and 280,000 tons for each storm. The mean PM15 concentrations inside of the dust plumes varied from 10 to 1600 ?g?m?3 (PM10 = 7 to 583 ?g?m?3). The mean PM1 concentrations were 97-241 ?g?m?3 with a maximum of 261 ?g?m?3 for the first storm. The PM1/PM2.5 ratios of >0.9 and PM1/PM10 ratios of 0.34-0.63 show that suspension of volcanic materials in Iceland causes air pollution with extremely high PM1 concentrations, similar to polluted urban areas in Europe or Asia. Icelandic volcanic dust consists of a higher proportion of submicron particles compared to crustal dust. Both dust storms occurred in relatively densely inhabited areas of Iceland. First results on size partitioning of Icelandic dust presented here should challenge health authorities to enhance research in relation to dust and shows the need for public dust warning systems.

Temporal and spatial PM10 concentration distribution using an inverse distance weighted method in Klang Valley, Malaysia

NASA Astrophysics Data System (ADS)

Tarmizi, S. N. M.; Asmat, A.; Sumari, S. M.

2014-02-01

PM10 is one of the air contaminants that can be harmful to human health. Meteorological factors and changes of monsoon season may affect the distribution of these particles. The objective of this study is to determine the temporal and spatial particulate matter (PM10) concentration distribution in Klang Valley, Malaysia by using the Inverse Distance Weighted (IDW) method at different monsoon season and meteorological conditions. PM10 and meteorological data were obtained from the Malaysian Department of Environment (DOE). Particles distribution data were added to the geographic database on a seasonal basis. Temporal and spatial patterns of PM10 concentration distribution were determined by using ArcGIS 9.3. The higher PM10 concentrations are observed during Southwest monsoon season. The values are lower during the Northeast monsoon season. Different monsoon seasons show different meteorological conditions that effect PM10 distribution.

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.

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...

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Physicochemical classification of dust particles observed at Gosan ABC superstation in East Asia

NASA Astrophysics Data System (ADS)

Shang, X.; Lee, M.; Chung, C. E.

2013-12-01

We identified different types of dust particles from long-term measurements of mass and ionic and carbonaceous compositions of PM1.0, PM2.5 and PM10 at Gosan ABC superstation on Jeju Island, Korea from August 2007 to February 2012. The concentration of PM1.0, PM10 mass and PM10 Ca2+ showed clear bimodal distributions, which provided robust criteria to distinguish atmospheric particles in different physiochemical regimes. Dust impacted particles were clearly separated by high PM10 mass over 29μg/m3. Some dust storm often passed over heavily populated areas in China, which made dust particles mixed with pollutants. This type of aerosol showed enhanced concentration of PM1.0 over 22μg/m3. We also recognized high Ca2+ concentration in PM1.0 when air came from northeastern China where salt deposit spreads in dry lakes. The Ca2+ concentration in PM10 was found to be a good indicator for the saline dust particles. In addition, the ratios of mass, SO42-, Mg2+ and organic carbon (OC) to Ca2+ turned out to be useful to distinguish different types of dust-impacted particles.

Effect of meteorological parameters on fine and coarse particulate matter mass concentration in a coal-mining area in Zonguldak, Turkey.

PubMed

Tecer, Lokman Hakan; Süren, Pinar; Alagha, Omar; Karaca, Ferhat; Tuncel, Gürdal

2008-04-01

In this work, the effect of meteorological parameters and local topography on mass concentrations of fine (PM2.5) and coarse (PM2.5-10) particles and their seasonal behavior was investigated. A total of 236 pairs of samplers were collected using an Anderson Dichotomous sampler between December 2004 and October 2005. The average mass concentrations of PM2.5, PM2.5-10, and particulate matter less than 10 microm in aerodynamic diameter (PM10) were found to be 29.38, 23.85, and 53.23 microg/m3, respectively. The concentrations of PM2.5 and PM10 were found to be higher in heating seasons (December to May) than in summer. The increase of relative humidity, cloudiness, and lower temperature was found to be highly related to the increase of particulate matter (PM) episodic events. During non-rainy days, the episodic events for PM2.5 and PM10 were increased by 30 and 10.7%, respectively. This is a result of the extensive use of fuel during winter for heating purposes and also because of stagnant air masses formed because of low temperature and low wind speed over the study area.

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

Evaluation of the AirNow Satellite Data Processor for 2010-2012

NASA Astrophysics Data System (ADS)

Pasch, A. N.; DeWinter, J. L.; Dye, T.; Haderman, M.; Zahn, P. H.; Szykman, J.; White, J. E.; Dickerson, P.; van Donkelaar, A.; Martin, R.

2013-12-01

The U.S. Environmental Protection Agency's (EPA) AirNow program provides the public with real-time and forecasted air quality conditions. Millions of people each day use information from AirNow to protect their health. The AirNow program (http://www.airnow.gov) reports ground-level ozone (O3) and fine particulate matter (PM2.5) with a standardized index called the Air Quality Index (AQI). AirNow aggregates information from over 130 state, local, and federal air quality agencies and provides tools for over 2,000 agency staff responsible for monitoring, forecasting, and communicating local air quality. Each hour, AirNow systems generate thousands of maps and products. The usefulness of the AirNow air quality maps depends on the accuracy and spatial coverage of air quality measurements. Currently, the maps use only ground-based measurements, which have significant gaps in coverage in some parts of the United States. As a result, contoured AQI levels have high uncertainty in regions far from monitors. To improve the usefulness of air quality maps, scientists at EPA, Dalhousie University, and Sonoma Technology, Inc., in collaboration with the National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA), have completed a project to incorporate satellite-estimated surface PM2.5 concentrations into the maps via the AirNow Satellite Data Processor (ASDP). These satellite estimates are derived using NASA/NOAA satellite aerosol optical depth (AOD) retrievals and GEOS-Chem modeled ratios of surface PM2.5 concentrations to AOD. GEOS-Chem is a three-dimensional chemical transport model for atmospheric composition driven by meteorological input from the Goddard Earth Observing System (GEOS). The ASDP can fuse multiple PM2.5 concentration data sets to generate AQI maps with improved spatial coverage. The goals of ASDP are to provide more detailed AQI information in monitor-sparse locations and to augment monitor-dense locations with more information. The ASDP system uses a weighted-average approach using uncertainty information about each data set. Recent improvements in the estimation of the uncertainty of interpolated ground-based monitor data have allowed for a more complete characterization of the uncertainty of the surface measurements. We will present a statistical analysis for 2010-2012 of the ASDP predictions of PM2.5 focusing on performance at validation sites. In addition, we will present several case studies evaluating the ASDP's performance for multiple regions and seasons, focusing specifically on days when large spatial gradients in AQI and wildfire smoke impacts were observed.

Pulmonary diseases induced by ambient ultrafine and engineered nanoparticles in twenty-first century.

PubMed

Xia, Tian; Zhu, Yifang; Mu, Lina; Zhang, Zuo-Feng; Liu, Sijin

2016-12-01

Air pollution is a severe threat to public health globally, affecting everyone in developed and developing countries alike. Among different air pollutants, particulate matter (PM), particularly combustion-produced fine PM (PM 2.5 ) has been shown to play a major role in inducing various adverse health effects. Strong associations have been demonstrated by epidemiological and toxicological studies between increases in PM 2.5 concentrations and premature mortality, cardiopulmonary diseases, asthma and allergic sensitization, and lung cancer. The mechanisms of PM-induced toxicological effects are related to their size, chemical composition, lung clearance and retention, cellular oxidative stress responses and pro-inflammatory effects locally and systemically. Particles in the ultrafine range (<100 nm), although they have the highest number counts, surface area and organic chemical content, are often overlooked due to insufficient monitoring and risk assessment. Yet, ample studies have demonstrated that ambient ultrafine particles have higher toxic potential compared with PM 2.5 . In addition, the rapid development of nanotechnology, bringing ever-increasing production of nanomaterials, has raised concerns about the potential human exposure and health impacts. All these add to the complexity of PM-induced health effects that largely remains to be determined, and mechanistic understanding on the toxicological effects of ambient ultrafine particles and nanomaterials will be the focus of studies in the near future.

Using optimal interpolation to assimilate surface measurements and satellite AOD for ozone and PM2.5: A case study for July 2011.

PubMed

Tang, Youhua; Chai, Tianfeng; Pan, Li; Lee, Pius; Tong, Daniel; Kim, Hyun-Cheol; Chen, Weiwei

2015-10-01

We employed an optimal interpolation (OI) method to assimilate AIRNow ozone/PM2.5 and MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth (AOD) data into the Community Multi-scale Air Quality (CMAQ) model to improve the ozone and total aerosol concentration for the CMAQ simulation over the contiguous United States (CONUS). AIRNow data assimilation was applied to the boundary layer, and MODIS AOD data were used to adjust total column aerosol. Four OI cases were designed to examine the effects of uncertainty setting and assimilation time; two of these cases used uncertainties that varied in time and location, or "dynamic uncertainties." More frequent assimilation and higher model uncertainties pushed the modeled results closer to the observation. Our comparison over a 24-hr period showed that ozone and PM2.5 mean biases could be reduced from 2.54 ppbV to 1.06 ppbV and from -7.14 µg/m³ to -0.11 µg/m³, respectively, over CONUS, while their correlations were also improved. Comparison to DISCOVER-AQ 2011 aircraft measurement showed that surface ozone assimilation applied to the CMAQ simulation improves regional low-altitude (below 2 km) ozone simulation. This paper described an application of using optimal interpolation method to improve the model's ozone and PM2.5 estimation using surface measurement and satellite AOD. It highlights the usage of the operational AIRNow data set, which is available in near real time, and the MODIS AOD. With a similar method, we can also use other satellite products, such as the latest VIIRS products, to improve PM2.5 prediction.

Dynamical Behaviors between the PM10 and the meteorological factor using the detrended cross-correlation analysis method

NASA Astrophysics Data System (ADS)

Kim, Kyungsik; Lee, Dong-In

2013-04-01

There is considerable interest in cross-correlations in collective modes of real data from atmospheric geophysics, seismology, finance, physiology, genomics, and nanodevices. If two systems interact mutually, that interaction gives rise to collective modes. This phenomenon is able to be analyzed using the cross-correlation of traditional methods, random matrix theory, and the detrended cross-correlation analysis method. The detrended cross-correlation analysis method was used in the past to analyze several models such as autoregressive fractionally integrated moving average processes, stock prices and their trading volumes, and taxi accidents. Particulate matter is composed of the organic and inorganic mixtures such as the natural sea salt, soil particle, vehicles exhaust, construction dust, and soot. The PM10 is known as the particle with the aerodynamic diameter (less than 10 microns) that is able to enter the human respiratory system. The PM10 concentration has an effect on the climate change by causing an unbalance of the global radiative equilibrium through the direct effect that blocks the stoma of plants and cuts off the solar radiation, different from the indirect effect that changes the optical property of clouds, cloudiness, and lifetime of clouds. Various factors contribute to the degree of the PM10 concentration. Notable among these are the land-use types, surface vegetation coverage, as well as meteorological factors. In this study, we analyze and simulate cross-correlations in time scales between the PM10 concentration and the meteorological factor (among temperature, wind speed and humidity) using the detrended cross-correlation analysis method through the removal of specific trends at eight cities in the Korean peninsula. We divide time series data into Asian dust events and non-Asian dust events to analyze the change of meteorological factors on the fluctuation of PM10 the concentration during Asian dust events. In particular, our result is compared to analytic findings from references published in all nations. ----------------------------------------------------------------- This work was supported by Center for the ASER (CATER 2012-6110) and by the NRFK through a grant provided by the KMEST(No.K1663000201107900).

Estimating PM2.5 Concentrations in Xi'an City Using a Generalized Additive Model with Multi-Source Monitoring Data

PubMed Central

Song, Yong-Ze; Yang, Hong-Lei; Peng, Jun-Huan; Song, Yi-Rong; Sun, Qian; Li, Yuan

2015-01-01

Particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) represents a severe environmental problem and is of negative impact on human health. Xi'an City, with a population of 6.5 million, is among the highest concentrations of PM2.5 in China. In 2013, in total, there were 191 days in Xi’an City on which PM2.5 concentrations were greater than 100 μg/m3. Recently, a few studies have explored the potential causes of high PM2.5 concentration using remote sensing data such as the MODIS aerosol optical thickness (AOT) product. Linear regression is a commonly used method to find statistical relationships among PM2.5 concentrations and other pollutants, including CO, NO2, SO2, and O3, which can be indicative of emission sources. The relationships of these variables, however, are usually complicated and non-linear. Therefore, a generalized additive model (GAM) is used to estimate the statistical relationships between potential variables and PM2.5 concentrations. This model contains linear functions of SO2 and CO, univariate smoothing non-linear functions of NO2, O3, AOT and temperature, and bivariate smoothing non-linear functions of location and wind variables. The model can explain 69.50% of PM2.5 concentrations, with R2 = 0.691, which improves the result of a stepwise linear regression (R2 = 0.582) by 18.73%. The two most significant variables, CO concentration and AOT, represent 20.65% and 19.54% of the deviance, respectively, while the three other gas-phase concentrations, SO2, NO2, and O3 account for 10.88% of the total deviance. These results show that in Xi'an City, the traffic and other industrial emissions are the primary source of PM2.5. Temperature, location, and wind variables also non-linearly related with PM2.5. PMID:26540446

An insight into the adsorption of diclofenac on different biochars: Mechanisms, surface chemistry, and thermodynamics.

PubMed

Lonappan, Linson; Rouissi, Tarek; Kaur Brar, Satinder; Verma, Mausam; Surampalli, Rao Y

2018-02-01

Biochars were prepared from feedstocks pinewood and pig manure. Biochar microparticles obtained through grinding were evaluated for the removal of emerging contaminant diclofenac (DCF) and the underlying mechanism were thoroughly studied. Characterization of biochar was carried out using particle size analyzer, SEM, BET, FT-IR, XRD, XPS and zeta potential instrument. Pig manure biochar (BC-PM) exhibited excellent removal efficiency (99.6%) over pine wood biochar (BC-PW) at 500 µg L -1 of DCF (environmentally significant concentration). Intraparticle diffusion was found to be the major process facilitated the adsorption. BC-PW followed pseudo first-order kinetics whereas BC-PM followed pseudo second-order kinetics. Pine wood biochar was largely affected by pH variations whereas for pig manure biochar, pH effects were minimal owing to its surface functional groups and DCF hydrophobicity. Thermodynamics, presence of co-existing ions, initial adsorbate concentration and particles size played substantial role in adsorption. Various isotherms models were also studied and results are presented. Copyright © 2017 Elsevier Ltd. All rights reserved.

Air pollution in Polish cities during January 2017 - an episode study

NASA Astrophysics Data System (ADS)

Durka, Pawel; Kaminski, Jacek W.; Struzewska, Joanna

2017-04-01

Poor air quality is a health issue in Poland, especially during winter. Six cities in Poland are in the top 10 and 33 cities are in the top 50 most polluted cities in Europe. In the first days of January 2017, there was a drastic change in the weather patterns over Central Europe. Temperatures dropped below -20oC in only a couple of days with calm wind conditions. Meteorological soundings showed inversions up to hundreds of meters above the surface. In such conditions PM10 and PM2.5 concentrations were unusually high. Thresholds were exceeded in most of the cities in Poland. In some of the cities PM concentrations were very high: reaching 1600 µg/m3 in Rybnik, 1300 µg/m3 in Zabrze, 1000 µg/m3 in Gliwice, 700 µg/m3 in Katowice. Most likely the main source of the pollution event were domestic emissions as well as traffic emissions. High concentration values were due to the stratification of the atmosphere. Nearly all cities issued smog alerts. The majority of the cities introduced free public transportation and schools were closed. We will show the evolution of this episode in the selected cities for the period when the highest concentrations measured and forecasted - from 7 to 11 January 2017. The synoptic situation for the episode will be discussed.

Diurnal variations of aerosol characteristics at a rural measuring site close to the Ruhr-Area, Germany

NASA Astrophysics Data System (ADS)

Kuhlbusch, T. A. J.; John, A. C.; Fissan, H.

PM10, PM2.5, and Black Carbon (BC) mass concentrations as well as number size distributions were measured quasi-online at a rural sampling site from 18 September to 17 October 1997. Average PM10, PM2.5, and BC mass concentrations were 37 ± 25, 25 ± 23, and 2 ± 1 μgm -3, respectively. All determined aerosol characteristics showed significant diurnal variations with generally higher concentrations during daytime compared to nights. Maxima in mass concentrations were around 11 AM and 8 PM during weekdays, most likely caused by commuter traffic. Decreased mass concentrations, changes in chemical composition and size distribution have been observed for the time from 12 to 5 PM. Diurnal variations of the BC/PM2.5 mass ratio revealed a minimum between 12 and 4 PM. The ratio of particle volume (0.5-2.5 μm) to particle mass (PM2.5) called 'potential density' also showed significant diurnal changes. These changes could be attributed to increasing in mixing height and windspeed. The determined diurnal variations in particle mass, composition, and size distribution may be relevant for epidemiological studies. We propose that diurnally weighted averages of relevant aerosol characteristics, which take diurnal patterns of human activities into account, should be used in epidemiological studies.

The Multi-Angle Imager for Aerosols (MAIA) Instrument, the Satellite-Based Element of an Investigation to Benefit Public Health

NASA Astrophysics Data System (ADS)

Diner, D. J.

2016-12-01

Maps of airborne particulate matter (PM) derived from satellite instruments, including MISR and MODIS, have provided key contributions to many health-related investigations. Although it is well established that PM exposure increases the risks of cardiovascular and respiratory disease, adverse birth outcomes, and premature deaths, our understanding of the relative toxicity of specific PM types—mixtures having different size distributions and compositions—is relatively poor. To address this, the Multi-Angle Imager for Aerosols (MAIA) investigation was proposed to NASA's third Earth Venture Instrument (EVI-3) solicitation. MAIA was selected for funding in March 2016. The satellite-based MAIA instrument is one element of the scientific investigation, which will combine WRF-Chem transport model estimates of the abundances of different aerosol types with the data acquired from Earth orbit. Geostatistical models derived from collocated surface and MAIA retrievals will be used to relate retrieved fractional column aerosol optical depths to near-surface concentrations of major PM constituents. Epidemiological analyses of geocoded birth, death, and hospital records will be used to associate exposure to PM types with adverse health outcomes. The MAIA instrument obtains its sensitivity to particle type by building upon the legacies of many satellite sensors; observing in the UV, visible, near-IR, and shortwave-IR regions of the electromagnetic spectrum; acquiring images at multiple angles of view; determining the degree to which the scattered light is polarized; and integrating these capabilities at moderately high spatial resolution. The instrument concept is based on the first and second generation Airborne Multiangle SpectroPolarimetric Imagers, AirMSPI and AirMSPI-2. MAIA incorporates a pair of pushbroom cameras on a two-axis gimbal to provide regional multiangle observations of selected, globally distributed target areas. A set of Primary Target Areas (PTAs) on five continents includes major population centers covering a range of PM concentrations and particle types. MAIA will also collect aerosol and cloud observations over regions of interest to the radiation science, climate, and environmental science communities. Launch of the MAIA instrument is planned for early in the next decade.

Aerosol loading in the Southeastern United States: reconciling surface and satellite observations

NASA Astrophysics Data System (ADS)

Ford, B.; Heald, C. L.

2013-09-01

We investigate the seasonality in aerosols over the Southeastern United States using observations from several satellite instruments (MODIS, MISR, CALIOP) and surface network sites (IMPROVE, SEARCH, AERONET). We find that the strong summertime enhancement in satellite-observed aerosol optical depth (AOD) (factor 2-3 enhancement over wintertime AOD) is not present in surface mass concentrations (25-55% summertime enhancement). Goldstein et al. (2009) previously attributed this seasonality in AOD to biogenic organic aerosol; however, surface observations show that organic aerosol only accounts for ∼35% of fine particulate matter (smaller than 2.5 μm in aerodynamic diameter, PM2.5) and exhibits similar seasonality to total surface PM2.5. The GEOS-Chem model generally reproduces these surface aerosol measurements, but underrepresents the AOD seasonality observed by satellites. We show that seasonal differences in water uptake cannot sufficiently explain the magnitude of AOD increase. As CALIOP profiles indicate the presence of additional aerosol in the lower troposphere (below 700 hPa), which cannot be explained by vertical mixing, we conclude that the discrepancy is due to a missing source of aerosols above the surface layer in summer.

Variation in characteristics of ambient particulate matter at eight locations in the Netherlands - The RAPTES project

NASA Astrophysics Data System (ADS)

Strak, Maciej; Steenhof, Maaike; Godri, Krystal J.; Gosens, Ilse; Mudway, Ian S.; Cassee, Flemming R.; Lebret, Erik; Brunekreef, Bert; Kelly, Frank J.; Harrison, Roy M.; Hoek, Gerard; Janssen, Nicole A. H.

2011-08-01

Numerous epidemiological studies have shown health effects related to short- and long-term exposure to elevated levels of ambient particulate matter (PM). It is not clear however which specific characteristics (e.g., size, components) or sources of PM are responsible for the observed effects. The aim of RAPTES (Risk of Airborne Particles: a Toxicological-Epidemiological hybrid Study) was to investigate which specific physical, chemical or oxidative characteristics of ambient PM are associated with adverse effects of PM on health. This was done by performing experimental exposure of human volunteers to air pollution at several real-world settings that had high contrast and low correlation between several PM characteristics. For this goal, eight sites in the Netherlands that differed in local PM emission sources were chosen for extensive air pollution characterization. Measurement sites included an underground train station, three different road traffic sites, an animal farm, a sea harbor, a site located in the vicinity of steelworks, and an urban background site. Five- to six-hours average concentration measurements at each site were made between June 2007 and October 2009. We measured PM 10, PM 2.5, particle number concentration (PNC), oxidative potential of PM, absorbance, endotoxin content, as well as elemental and chemical composition of PM, and gaseous pollutants concentrations. This paper presents a detailed characterization of particulate air pollution at the sampling sites. We found significant differences in all PM characteristics between the sites. The underground train station, compared to each outdoor location, had substantially higher concentrations of nearly all PM characteristics. The average PM 10 and PM 2.5 mass concentrations at the underground train station were 394 μg m -3 and 137 μg m -3, respectively, which was 14.1 and 7.6 times higher than the urban background. The sum of the concentrations of trace metals in fine and coarse PM was nearly 20 times above the outdoor levels. Elemental carbon (EC) was elevated at the underground site in the fine but also in the coarse mode, in contrast to the traffic sites where EC was predominantly found in fine PM. The highest concentrations and contrasts in PNC were at the traffic sites (between 45,000 and 80,000 particles cm -3), which was several times higher than measured at any other site. Correlations of PNC with metals, PM 10, PM 2.5 and absorbance were low to moderate, while correlations between PM 10, PM 2.5 and the metals Cu and Fe were high. After excluding the underground train station data, correlations between PM10, EC and metals decreased whereas the correlation between PNC and EC increased. We conclude that we were able to successfully identify and characterize real-world situations with very different particle characteristics. High contrast and low correlations between PM characteristics, as well as consistency of these differences across sampling campaigns, provide a good basis for identifying health relevant PM characteristics in the upcoming analysis.

Postprandial changes in leptin concentrations of cerebrospinal fluid in dogs during development of obesity.

PubMed

Nishii, Naohito; Nodake, Hiroyuki; Takasu, Masaki; Soe, Okkar; Ohba, Yasunori; Maeda, Sadatoshi; Ohtsuka, Yoshihiko; Honjo, Tsutomu; Saito, Masayuki; Kitagawa, Hitoshi

2006-12-01

To evaluate postprandial changes in the leptin concentration of CSF in dogs during development of obesity. 4 male Beagles. Weight gain was induced and assessments were made when the dogs were in thin, optimal, and obese body conditions (BCs). The fat area at the level of the L3 vertebra was measured via computed tomography to assess the degree of obesity. Dogs were evaluated in fed and unfed states. Dogs in the fed state received food at 9 AM. Blood and CSF samples were collected at 8 AM, 4 PM, and 10 PM. Baseline CSF leptin concentrations in the thin, optimal, and obese dogs were 24.3 +/- 2.7 pg/mL, 86.1 +/- 14.7 pg/mL, and 116.2 +/- 47.3 pg/mL, respectively. In the thin BC, CSF leptin concentration transiently increased at 4 PM. In the optimal BC, baseline CSF leptin concentration was maintained until 10 PM. In the obese BC, CSF leptin concentration increased from baseline value at 4 PM and 10 PM. Correlation between CSF leptin concentration and fat area was good at all time points. There was a significant negative correlation between the CSF leptin concentration-to-serum leptin concentration ratio and fat area at 4 PM; this correlation was not significant at 8 AM and 10 PM. Decreased transport of leptin at the blood-brain barrier may be 1 mechanism of leptin resistance in dogs. However, leptin resistance at the blood-brain barrier may not be important in development of obesity in dogs.

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

PubMed

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

2016-03-02

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

First assessment of the PM10 and PM2.5 particulate level in the ambient air of Belgrade city.

PubMed

Rajsić, Slavica F; Tasić, Mirjana D; Novaković, Velibor T; Tomasević, Milica N

2004-01-01

As the strong negative health effect of exposure to the inhalable particulate matter PM10 in the urban environment has been confirmed, the study of the mass concentrations, physico-chemical characteristics, sources, as well as spatial and temporal variation of atmospheric aerosol particles becomes very important. This work is a pilot study to assess the concentration level of ambient suspended particulate matter, with an aerodynamic diameter of less than 10 microm, in the Belgrade central urban area. Average daily concentrations of PM10 and PM2.5 have been measured at three representative points in the city between June 2002 and December 2002. The influence of meteorological parameters on PM10 and PM2.5 concentrations was analyzed, and possible pollution sources were identified. Suspended particles were collected on Pure Teflon filters by using a Mini-Vol low-volume air sampler (Airmetrics Co., Inc.; 5 l min(-1) flow rate). Particle mass was determined gravimetrically after 48 h of conditioning in a desiccator, in a Class 100 clean room at the temperature T = 20 degrees C and at about 50% constant relative humidity (RH). Analysis of the PM10 data indicated a marked difference between season without heating--(summer; mean value 56 microg m(-3)) and heating season--(winter; mean value 96 microg m3); 62% of samples exceeded the level of 50 microg m(-3). The impact of meteorological factors on PM concentrations was not immediately apparent, but there was a significant negative correlation with the wind speed. The PM10 and PM2.5 mass concentrations in the Belgrade urban area had high average values (77 microg m(-3) and 61 microg m(-3)) in comparison with other European cities. The main sources of particulate matter were traffic emission, road dust resuspension, and individual heating emissions. When the air masses are coming from the SW direction, the contribution from the Obrenovac power plants is evident. During days of exceptionally severe pollution, in both summer and winter periods, high production of secondary aerosols occurred, as can be seen from an increase in PM2.5 in respect to PM10 mass concentration. The results obtained gave us the first impression of the concentration level of particulate matter, with an aerodynamic diameter of less than 10 microm, in the Belgrade ambient air. Due to measured high PM mass concentrations, it is obvious that it would be very difficult to meet the EU standards (EEC 1999) by 2010. It is necessary to continue with PM10 and PM2.5 sampling; and after comprehensive analysis which includes the results of chemical and physical characterization of particles, we will be able to recommend effective control measures in order to improve air quality in Belgrade.

Particulate matter in rural and urban nursery schools in Portugal.

PubMed

Nunes, R A O; Branco, P T B S; Alvim-Ferraz, M C M; Martins, F G; Sousa, S I V

2015-07-01

Studies have been showing strong associations between exposures to indoor particulate matter (PM) and health effects on children. Urban and rural nursery schools have different known environmental and social differences which make their study relevant. Thus, this study aimed to evaluate indoor PM concentrations on different microenvironments of three rural nursery schools and one urban nursery school, being the only study comparing urban and rural nursery schools considering the PM1, PM2.5 and PM10 fractions (measured continuously and in terms of mass). Outdoor PM2.5 and PM10 were also obtained and I/O ratios have been determined. Indoor PM mean concentrations were higher in the urban nursery than in rural ones, which might have been related to traffic emissions. However, I/O ratios allowed concluding that the recorded concentrations depended more significantly of indoor sources. WHO guidelines and Portuguese legislation exceedances for PM2.5 and PM10 were observed mainly in the urban nursery school. Copyright © 2015 Elsevier Ltd. All rights reserved.

Size-segregated particulate matter inside residences of elderly in the Metropolitan Area of São Paulo, Brazil

NASA Astrophysics Data System (ADS)

Segalin, Bruna; Kumar, Prashant; Micadei, Kaonan; Fornaro, Adalgiza; Gonçalves, Fabio L. T.

2017-01-01

The elderly population spend relatively more time indoors and is more sensitive to air pollution-related health risks but there is limited information on the quality of the air they breathe inside their residences. The objectives of this work are to (i) characterise mass of size-segregated particulate matter (PM) in elderly residences in Metropolitan Area of Sao Paulo (MASP) in Brazil, (ii) assess the impact of the meteorological parameters on the behaviour of indoor PM concentrations, (iii) evaluate the indoor and outdoor relationship of PM mass concentration, and (iv) estimate the respiratory deposition doses (RDD). To achieve these objectives, we measured mass concentrations of size-segregated particles in 59 elderly residences in MASP. The measurements were made in the 0.25-10 μm size range in 5 size bins using a Personal Cascade Impactor Sampler. We evaluated the mass concentration of particles using a gravimetric method and compared our PM10 (sum of all size bins) and PM2.5 (sum of all size bins, except PM10-2.5) concentrations against the 24 h mean guidelines recommended by World Health Organization (WHO). Our results show the mean PM10 and PM2.5 measured in elderly residences in MASP as 35.2 and 27.4 μg m-3, respectively. PM2.5 and PM<0.25 (particles with aerodynamic diameter of less than 0.25 μm) contributed 78% and 38% of total PM10, respectively, clearly suggesting a significantly high exposure to fine particles by the elderly. About 13 and 43% of the measurements exceeded the WHO's PM10 and PM2.5 guidelines, respectively. The samples were clustered into five groups to found the behaviour of indoor PM. The cluster representing the residences with higher PM concentration in all size bins are predominantly residences near the heavy traffic areas during the non-precipitation days. About 68% of residences showed the highest fraction of PM<0.25, indicating a high concentration of ultrafine particles in these residences. We calculated indoor/outdoor (I/O) rates and found them as 1.89 and 1.06 for PM2.5 and PM10, respectively. About 77% and 40% of the residences had higher PM2.5 and PM10 indoors than those in outdoor environments. During seated position, the RDD rates for coarse and fine particles for male elderly were found to be about 20% and 25% higher compared with female elderly, respectively. Our findings suggest a control of indoor sources in the elderly residences to limit adverse health effects of particulate matter, especially fine particles, on elderly.

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 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.

Effect of nitrate and sulfate relative abundance in PM2.5 on liquid water content explored through half-hourly observations of inorganic soluble aerosols at a polluted receptor site

NASA Astrophysics Data System (ADS)

Xue, Jian; Griffith, Stephen M.; Yu, Xin; Lau, Alexis K. H.; Yu, Jian Zhen

2014-12-01

Liquid water content (LWC) is the amount of liquid water on aerosols. It contributes to visibility degradation, provides a surface for gas condensation, and acts as a medium for heterogeneous gas/particle reactions. In this study, 520 half-hourly measurements of ionic chemical composition in PM2.5 at a receptor site in Hong Kong are used to investigate the dependence of LWC on ionic chemical composition, particularly on the relative abundance of sulfate and nitrate. LWC was estimated using a thermodynamic model (AIM-III). Within this data set of PM2.5 ionic compositions, LWC was highly correlated with the multivariate combination of sulfate and nitrate concentrations and RH (R2 = 0.90). The empirical linear regression result indicates that LWC is more sensitive to nitrate mass than sulfate. During a nitrate episode, the highest LWC (80.6 ± 17.9 μg m-3) was observed and the level was 70% higher than that during a sulfate episode despite a similar ionic PM2.5 mass concentration. A series of sensitivity tests were conducted to study LWC change as a function of the relative nitrate and sulfate abundance, the trend of which is expected to shift to more nitrate in China as a result of SO2 reduction and increase in NOx emission. Starting from a base case that uses the average of measured PM2.5 ionic chemical composition (63% SO42-, 11% NO3-, 19% NH4+, and 7% other ions) and an ionic equivalence ratio, [NH4+]/(2[SO42-] + [NO3-]), set constant to 0.72, the results show LWC would increase by 204% at RH = 40% when 50% of the SO42- is replaced by NO3- mass concentration. This is largely due to inhibition of (NH4)3H(SO4)2 crystallization while PM2.5 ionic species persist in the aqueous phase. At RH = 90%, LWC would increase by 12% when 50% of the SO42- is replaced by NO3- mass concentration. The results of this study highlight the important implications to aerosol chemistry and visibility degradation associated with LWC as a result of a shift in PM2.5 ionic chemical composition to more nitrate in atmospheric environments as is expected in many Chinese cities.

Propagation of SH waves in an infinite/semi-infinite piezoelectric/piezomagnetic periodically layered structure.

PubMed

Pang, Yu; Liu, Yu-Shan; Liu, Jin-Xi; Feng, Wen-Jie

2016-04-01

In this paper, SH bulk/surface waves propagating in the corresponding infinite/semi-infinite piezoelectric (PE)/piezomagnetic (PM) and PM/PE periodically layered composites are investigated by two methods, the stiffness matrix method and the transfer matrix method. For a semi-infinite PE/PM or PM/PE medium, the free surface is parallel to the layer interface. Both PE and PM materials are assumed to be transversely isotropic solids. Dispersion equations are derived by the stiffness/transfer matrix methods, respectively. The effects of electric-magnetic (ME) boundary conditions at the free surface and the layer thickness ratios on dispersion curves are considered in detail. Numerical examples show that the results calculated by the two methods are the same. The dispersion curves of SH surface waves are below the bulk bands or inside the frequency gaps. The ratio of the layer thickness has an important effect not only on the bulk bands but also on the dispersion curves of SH surface waves. Electric and magnetic boundary conditions, respectively, determine the dispersion curves of SH surface waves for the PE/PM and PM/PE semi-infinite structures. The band structures of SH bulk waves are consistent for the PE/PM and PM/PE structures, however, the dispersive behaviors of SH surface waves are indeed different for the two composites. The realization of the above-mentioned characteristics of SH waves will make it possible to design PE/PM acoustic wave devices with periodical structures and achieve the better performance. Copyright © 2016 Elsevier B.V. All rights reserved.

PM2.5 mitigation in China: Socioeconomic determinants of concentrations and differential control policies.

PubMed

Luo, Kui; Li, Guangdong; Fang, Chuanglin; Sun, Siao

2018-05-01

Elucidating the key impact factors on PM 2.5 concentrations is crucial to formulate effective mitigation policies. In this study, we employed an extended Stochastic Impacts by Regression on Population Affluence and Technology (STIRPAT) model to identify the socioeconomic determinants of PM 2.5 concentrations for 12 different regions and across China. The evaluation was based on a balanced panel dataset integrating long-term satellite-derived PM 2.5 concentrations and socio-economic data in China from 1999 to 2011. Empirical results indicate that the influencing factors can be ranked in descending order of importance as: proportion of secondary sector of the economy, GDP per capita, urbanization, population, energy intensity, and proportion of tertiary sector. Proportion of secondary sector is the greatest contribution to increasing PM 2.5 concentrations, especially for heavily polluted regions. GDP per capita is secondary in importance, and its impact is weakened by the existence of an EKC relationship between GDP per capita and PM 2.5 concentrations. Therefore, PM 2.5 pollution is an economic development mode problem, rather than a general economic development problem. The impact of urbanization varies across regions; while promoting urbanization will be conducive to decreased PM 2.5 concentrations in Northwest China and Northeast China, it will contribute to increased PM 2.5 concentrations in other regions. Population and energy intensity are significant in most regions, but neither are decisive factors because of the small absolute value of their coefficients. Finally, different combinations of mitigation policies are proposed for different regions in this study to meet the mitigation targets. Copyright © 2018 Elsevier Ltd. All rights reserved.

Impact of coal-carrying trains on particulate matter concentrations in South Delta, British Columbia, Canada.

PubMed

Akaoka, K; McKendry, I; Saxton, J; Cottle, P W

2017-04-01

Transport of coal by train through residential neighborhoods in Metro Vancouver, British Columbia, Canada may increase the possibility of exposure to particulate matter at different size ranges, with concomitant potential negative health impacts. This pilot study identifies and quantifies train impacts on particulate matter (PM) concentrations at a single location. Field work was conducted during August and September 2014, with the attributes of a subset of passing trains confirmed visually, and the majority of passages identified with audio data. In addition to fixed ground based monitors at distances 15 and 50 m from the train tracks, an horizontally pointing mini-micropulse lidar system was deployed on three days to make backscatter and depolarization measurements in an attempt to identify the zone of influence, and sources, of train-generated PM. Ancillary wind and dust fall data were also utilized. Trains carrying coal are associated with a 5.3 (54%), 4.1 (33%), and 2.6 (17%) μgm -3 average increase in concentration over a 14 min period compared to the average concentrations over the 10 min prior to and after a train passage ("control" or "background" conditions), for PM 3 , PM 10 , and PM 20 , respectively. In addition, for PM 10 and PM 20 , concentrations during train passages of non-coal-carrying trains were not found to be significantly different from PM concentrations during control conditions. Presence of coal dust particles at the site was confirmed by dust fall measurements. Although enhancements of PM concentrations during 14 min train passages were generally modest, passing coal trains occasionally enhanced concentrations at 50 m from the tracks by ∼100 μgm -3 . Results showed that not every train passage increased PM concentrations, and the effect appears to be highly dependent on wind direction, local meteorology and load related factors. LiDAR imagery suggests that re-mobilization of track-side PM by train-induced turbulence may be a significant contributor to coarse particle enhancements. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial and temporal variation in endotoxin and PM10 concentrations in ambient air in a livestock dense area.

PubMed

de Rooij, Myrna M T; Heederik, Dick J J; Borlée, Floor; Hoek, Gerard; Wouters, Inge M

2017-02-01

Several studies have reported associations between farming and respiratory health in neighboring residents. Health effects are possibly linked to fine dust and endotoxin emissions from livestock farms. Little is known about levels of these air pollutants in ambient air in livestock dense areas. We aimed to explore temporal and spatial variation of PM10 and endotoxin concentrations, and the association with livestock-related spatial and meteorological temporal determinants. From March till September 2011, one week average PM10 samples were collected using Harvard Impactors at eight sites (residential gardens) representing a variety of nearby livestock-related characteristics. A background site was included in the study area, situated at least 500m away from the nearest farm. PM10 mass was determined by gravimetric analysis and endotoxin level by means of Limulus-Amebocyte-Lysate assay. Data were analyzed using mixed models. The range between sites of geometric mean concentrations was for PM10 19.8-22.3µg/m 3 and for endotoxin 0.46-0.66EU/m 3 . PM10 concentrations and spatial variation were very similar for all sites, while endotoxin concentrations displayed a more variable pattern over time with larger differences between sites. Nonetheless, the temporal pattern at the background location was highly comparable to the sites mean temporal pattern both for PM10 and endotoxin (Pearson correlation: 0.92, 0.62). Spatial variation was larger for endotoxin than for PM10 (within/between site variance ratio: 0.63, 2.03). Spatial livestock-related characteristics of the surroundings were more strongly related to endotoxin concentrations, while temporal determinants were more strongly related to PM10 concentrations. The effect of local livestock-related sources on PM10 concentration was limited in this study carried out in a livestock dense area. The effect on endotoxin concentrations was more profound. To gain more insight in the effect of livestock-related sources on ambient levels of PM10 and endotoxin, measurements should be based on a broader set of locations. Copyright © 2016. Published by Elsevier Inc.

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.

Day-Ahead PM2.5 Concentration Forecasting Using WT-VMD Based Decomposition Method and Back Propagation Neural Network Improved by Differential Evolution

PubMed Central

Wang, Deyun; Liu, Yanling; Luo, Hongyuan; Yue, Chenqiang; Cheng, Sheng

2017-01-01

Accurate PM2.5 concentration forecasting is crucial for protecting public health and atmospheric environment. However, the intermittent and unstable nature of PM2.5 concentration series makes its forecasting become a very difficult task. In order to improve the forecast accuracy of PM2.5 concentration, this paper proposes a hybrid model based on wavelet transform (WT), variational mode decomposition (VMD) and back propagation (BP) neural network optimized by differential evolution (DE) algorithm. Firstly, WT is employed to disassemble the PM2.5 concentration series into a number of subsets with different frequencies. Secondly, VMD is applied to decompose each subset into a set of variational modes (VMs). Thirdly, DE-BP model is utilized to forecast all the VMs. Fourthly, the forecast value of each subset is obtained through aggregating the forecast results of all the VMs obtained from VMD decomposition of this subset. Finally, the final forecast series of PM2.5 concentration is obtained by adding up the forecast values of all subsets. Two PM2.5 concentration series collected from Wuhan and Tianjin, respectively, located in China are used to test the effectiveness of the proposed model. The results demonstrate that the proposed model outperforms all the other considered models in this paper. PMID:28704955

Assessment of dioxin-like activity in PM10 air samples from an industrial location in Algeria, using the DRE-CALUX bioassay.

PubMed

Khedidji, Sidali; Croes, Kim; Yassaa, Noureddine; Ladji, Riad; Denison, Michael S; Baeyens, Willy; Elskens, Marc

2017-05-01

When compared to the European guidelines, PM 10 (particulate matter up to 10-μm size) concentrations in Algeria are often exceeding the maximum limits, and in general, no information exists on the compounds bound on its surface. The objective of this study was to measure the dioxin-like activity of polychlorinated dibenzodioxines and dibenzofurans (PCDD/Fs) and dioxin-like polychlorinated biphenyls (PCBs) in the PM 10 fraction at the Sour El Ghozlane cement plant in Algeria. PM 10 samples (n = 23) were taken between 24 March and 15 April 2013, using a medium volume sampler and 47-mm PTFE filters. The 24-h samples were dried to determine the PM 10 content and afterward extracted, cleaned up, and analyzed with the dioxin-responsive element-chemical-activated luciferase gene expression (DRE-CALUX) bioassay. Our results showed that the measured bioanalytical equivalents (BEQs) were similar to those in other international industrial sites worldwide. The PCDD/Fs and dioxin-like PCBs (dl-PCBs) were positively correlated (rho = 0.6, p = 0.002), indicating that they have similar sources. Furthermore, samples from March showed higher PCDD/F and dl-PCB BEQs and humidity but lower temperatures compared to samples from April, while there was no difference in the PM 10 concentrations between the two months. These results reveal that PM 10 alone is not a good proxy and that meteorological conditions are an important factor in assessing dioxin-like pollution in the atmosphere. It seems that, at present, there is no health hazard through direct airborne human exposure to dioxin-like pollutants in PM 10 from this site. However, it is important to monitor these POPs for a longer period of time and also to gain more insight in their distribution between the particulate and gas phase in relation to meteorological conditions.

Status update: is smoke on your mind? Using social media to assess smoke exposure

NASA Astrophysics Data System (ADS)

Ford, Bonne; Burke, Moira; Lassman, William; Pfister, Gabriele; Pierce, Jeffrey R.

2017-06-01

Exposure to wildland fire smoke is associated with negative effects on human health. However, these effects are poorly quantified. Accurately attributing health endpoints to wildland fire smoke requires determining the locations, concentrations, and durations of smoke events. Most current methods for assessing these smoke events (ground-based measurements, satellite observations, and chemical transport modeling) are limited temporally, spatially, and/or by their level of accuracy. In this work, we explore using daily social media posts from Facebook regarding smoke, haze, and air quality to assess population-level exposure for the summer of 2015 in the western US. We compare this de-identified, aggregated Facebook dataset to several other datasets that are commonly used for estimating exposure, such as satellite observations (MODIS aerosol optical depth and Hazard Mapping System smoke plumes), daily (24 h) average surface particulate matter measurements, and model-simulated (WRF-Chem) surface concentrations. After adding population-weighted spatial smoothing to the Facebook data, this dataset is well correlated (R2 generally above 0.5) with the other methods in smoke-impacted regions. The Facebook dataset is better correlated with surface measurements of PM2. 5 at a majority of monitoring sites (163 of 293 sites) than the satellite observations and our model simulation. We also present an example case for Washington state in 2015, for which we combine this Facebook dataset with MODIS observations and WRF-Chem-simulated PM2. 5 in a regression model. We show that the addition of the Facebook data improves the regression model's ability to predict surface concentrations. This high correlation of the Facebook data with surface monitors and our Washington state example suggests that this social-media-based proxy can be used to estimate smoke exposure in locations without direct ground-based particulate matter measurements.

Source Contributions to Premature Mortality Due to Ambient Particulate Matter in China

NASA Astrophysics Data System (ADS)

Hu, J.; Huang, L.; Ying, Q.; Zhang, H.; Shi, Z.

2016-12-01

Outdoor air pollution is linked to various health effects. Globally it is estimated that ambient air pollution caused 3.3 million premature deaths in 2010. The health risk occurs predominantly in developing countries, particularly in Asia. China has been suffering serious air pollution in recent decades. The annual concentrations of ambient PM2.5 are more than five times higher than the WHO guideline value in many populous Chinese cities. Sustained exposure to high PM2.5 concentrations greatly threatens public health in this country. Recognizing the severity of the air pollution situation, the Chinese government has set a target in 2013 to reduce PM2.5 level by up to 25% in major metropolitan areas by 2017. It is urgently needed for China to assess premature mortality caused by outdoor air pollution, identify source contributions of the premature mortality, and evaluate responses of the premature mortality to air quality improvement, in order to design effective control plans and set priority for air pollution controls to better protect public health. In this study, we determined the spatial distribution of excess mortality (ΔMort) due to adult (> 30 years old) ischemic heart disease (IHD), cerebrovascular disease (CEV), chronic obstructive pulmonary disease (COPD) and lung cancer (LC) at 36-km horizontal resolution for 2013 from the predicted annual-average surface PM2.5 concentrations using an updated source-oriented Community Multiscale Air Quality (CMAQ) model along with an ensemble of four regional and global emission inventories. Observation data fusing was applied to provide additional correction of the biases in the PM2.5 concentration field from the ensemble. Source contributions to ΔMort were determined based on total ΔMort and fractional source contributions to PM2.5 mass concentrations. We estimated that ΔMort due to COPD, LC, IHD and CEV are 0.329, 0.148, 0.239 and 0.953 million in China, respectively, leading to a total ΔMort of 1.669 million. Industries and residential sources were the two leading sources to ΔMort, contributing to 0.508 (30.5%) and 0.366 (21.9%) mp, respectively. Secondary ammonium ion from agriculture sources, secondary organic aerosol and aerosols from power generation sources were responsible for ΔMort of 0.204, 0.179 and 0.172 mp, respectively.

Association between Secondhand Smoke in Hospitality Venues and Urinary 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol Concentrations in Non-Smoking Staff.

PubMed

Kim, Jeonghoon; Lee, Kiyoung; Kwon, Ho-Jang; Lee, Do Hoon; Kim, KyooSang

2016-11-08

The purpose of this study was to determine the relationship between urinary cotinine and total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) concentrations in non-smoking staff and the indoor levels of fine particles (PM 2.5 ) in hospitality venues that allow smoking, with respect to demographic and indoor environmental factors. We evaluated 62 hospitality venues that allowed smoking in Seoul, Korea. A real-time aerosol monitor was used to measure indoor PM 2.5 concentrations. Field technicians recorded indoor environmental characteristics. One non-smoking staff member in each hospitality venue was tested for urinary cotinine and total NNAL concentrations. Demographic characteristics were obtained from self-reported staff questionnaires. Natural-log (ln)-transformed PM 2.5 concentrations were significantly correlated with the ln-transformed cotinine ( r = 0.31) and the total NNAL concentrations ( r = 0.32). In multivariable regression analysis, the urinary cotinine concentrations of the staff members were significantly correlated with indoor PM 2.5 concentrations; those with the highest concentrations were more likely to be women or staff members that worked in venues with a volume <375 m³. Total NNAL concentrations were significantly correlated only with indoor PM 2.5 concentrations. Indoor PM 2.5 may be used as an indicator for urinary cotinine and total NNAL concentrations in non-smoking staff members in hospitality venues that allow smoking.

Association between Secondhand Smoke in Hospitality Venues and Urinary 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol Concentrations in Non-Smoking Staff

PubMed Central

Kim, Jeonghoon; Lee, Kiyoung; Kwon, Ho-Jang; Lee, Do Hoon; Kim, KyooSang

2016-01-01

The purpose of this study was to determine the relationship between urinary cotinine and total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) concentrations in non-smoking staff and the indoor levels of fine particles (PM2.5) in hospitality venues that allow smoking, with respect to demographic and indoor environmental factors. We evaluated 62 hospitality venues that allowed smoking in Seoul, Korea. A real-time aerosol monitor was used to measure indoor PM2.5 concentrations. Field technicians recorded indoor environmental characteristics. One non-smoking staff member in each hospitality venue was tested for urinary cotinine and total NNAL concentrations. Demographic characteristics were obtained from self-reported staff questionnaires. Natural-log (ln)-transformed PM2.5 concentrations were significantly correlated with the ln-transformed cotinine (r = 0.31) and the total NNAL concentrations (r = 0.32). In multivariable regression analysis, the urinary cotinine concentrations of the staff members were significantly correlated with indoor PM2.5 concentrations; those with the highest concentrations were more likely to be women or staff members that worked in venues with a volume <375 m3. Total NNAL concentrations were significantly correlated only with indoor PM2.5 concentrations. Indoor PM2.5 may be used as an indicator for urinary cotinine and total NNAL concentrations in non-smoking staff members in hospitality venues that allow smoking. PMID:27834821

Global distribution and evolvement of urbanization and PM2.5 (1998-2015)

NASA Astrophysics Data System (ADS)

Yang, Dongyang; Ye, Chao; Wang, Xiaomin; Lu, Debin; Xu, Jianhua; Yang, Haiqing

2018-06-01

PM2.5 concentrations increased and have been one of the major social issues along with rapid urbanization in many regions of the world in recent decades. The development of urbanization differed among regions, PM2.5 pollution also presented discrepant distribution across the world. Thus, this paper aimed to grasp the profile of global distribution of urbanization and PM2.5 and their evolutionary relationships. Based on global data for the proportion of the urban population and PM2.5 concentrations in 1998-2015, this paper investigated the spatial distribution, temporal variation, and evolutionary relationships of global urbanization and PM2.5. The results showed PM2.5 presented an increasing trend along with urbanization during the study period, but there was a variety of evolutionary relationships in different countries and regions. Most countries in East Asia, Southeast Asia, South Asia, and some African countries developed with the rapid increase in both urbanization and PM2.5. Under the impact of other socioeconomic factors, such as industry and economic growth, the development of urbanization increased PM2.5 concentrations in most Asian countries and some African countries, but decreased PM2.5 concentrations in most European and American countries. The findings of this study revealed the spatial distributions of global urbanization and PM2.5 pollution and provided an interpretation on the evolution of urbanization-PM2.5 relationships, which can contribute to urbanization policies making aimed at successful PM2.5 pollution control and abatement.

Non-exhaust emission measurement system of the mobile laboratory SNIFFER

NASA Astrophysics Data System (ADS)

Pirjola, L.; Kupiainen, K. J.; Perhoniemi, P.; Tervahattu, H.; Vesala, H.

In this paper we describe and quality assure the sampling system of a mobile research laboratory SNIFFER which was shown to be a useful tool for studying emission levels of respirable dust from street surfaces. The dust plume had bimodal structure; another mode rising to higher altitudes whereas the other mode remained at lower altitudes. The system was tested on a route in Helsinki, Finland, during spring 2005 and 2006. The PM 2.5 and PM 10 were positively correlated and the PM levels increased with the vehicle speed. SNIFFER was able to identify the characteristic emission levels on different streets. A clear downward trend in the concentrations was observed in all street locations between April and June. The composition of the street dust collected by SNIFFER was compared with springtime PM 10 aerosol samples from the air quality monitoring stations in Helsinki. The results showed similarities in the abundance and composition of the mineral fraction but contained significantly more salt particles.

Seasonal variation, risk assessment and source estimation of PM 10 and PM10-bound PAHs in the ambient air of Chiang Mai and Lamphun, Thailand.

PubMed

Pengchai, Petch; Chantara, Somporn; Sopajaree, Khajornsak; Wangkarn, Sunanta; Tengcharoenkul, Urai; Rayanakorn, Mongkon

2009-07-01

Daily PM10 concentrations were measured at four sampling stations located in Chiang Mai and Lamphun provinces, Thailand. The sampling scheme was conducted during June 2005 to June 2006; every 3 days for 24 h in each sampling period. The result revealed that all stations shared the same pattern, in which the PM10 (particulate matters with diameter of less than 10 microm) concentration increased at the beginning of dry season (December) and reached its peak in March before decreasing by the end of April. The maximum PM10 concentration for each sampling station was in the range of 140-182 microg/m(3) which was 1.1-1.5 times higher than the Thai ambient air quality standard of 120 microg/m(3). This distinctly high concentration of PM10 in the dry season (Dec. 05-Mar. 06) was recognized as a unique seasonal pattern for the northern part of Thailand. PM10 concentration had a medium level of negative correlation (r = -0.696 to -0.635) with the visibility data. Comparing the maximum PM10 concentration detected at each sampling station to the permitted PM10 level of the national air quality standard, the warning visibility values for the PM10 pollution-watch system were determined as 10 km for Chiang Mai Province and 5 km for Lamphun Province. From the analysis of PM10 constituents, no component exceeded the national air quality standard. The total concentrations of PM10-bond polycyclic aromatic hydrocarbons (PAHs) are calculated in terms of total toxicity equivalent concentrations (TTECs) using the toxicity equivalent factors (TEFs) method. TTECs in Chiang Mai and Lamphun ambient air was found at a level comparable to those observed in Nagasaki, Bangkok and Rome and at a lower level than those reported at Copenhagen. The annual number of lung cancer cases for Chiang Mai and Lamphun Provinces was estimated at two cases/year which was lower than the number of cases in Bangkok (27 cases/year). The principal component analysis/absolute principal component scores (PCA/APCS) model and multiple regression analysis were applied to the PM10 and its constituents data. The results pointed to the vegetative burning as the largest PM10 contributor in Chiang Mai and Lamphun ambient air. Vegetative burning, natural gas burning & coke ovens, and secondary particle accounted for 46-82%, 12-49%, and 3-19% of the PM10 concentrations, respectively. However, natural gas burning & coke ovens as well as vehicle exhaust also deserved careful attention due to their large contributions to PAHs concentration. In the wet season and transition periods, 42-60% of the total PAHs concentrations originated from vehicle exhaust while 16-37% and 14-38% of them were apportioned to natural gas burning & coke ovens and vegetative burning, respectively. In the dry period, natural gas burning & coke ovens, vehicle exhaust, and vegetative burning accounted for 47-59%, 20-25%, and 19-28% of total PAHs concentrations. The close agreement between the measured and predicted concentrations data (R(2) > 0.8) assured enough capability of PCA/APCS receptor model to be used for the PM10 and PAHs source apportionment.

Evolution of vehicle exhaust particles in the atmosphere.

PubMed

Canagaratna, Manjula R; Onasch, Timothy B; Wood, Ezra C; Herndon, Scott C; Jayne, John T; Cross, Eben S; Miake-Lye, Richard C; Kolb, Charles E; Worsnop, Douglas R

2010-10-01

Aerosol mass spectrometer (AMS) measurements are used to characterize the evolution of exhaust particulate matter (PM) properties near and downwind of vehicle sources. The AMS provides time-resolved chemically speciated mass loadings and mass-weighted size distributions of nonrefractory PM smaller than 1 microm (NRPM1). Source measurements of aircraft PM show that black carbon particles inhibit nucleation by serving as condensation sinks for the volatile and semi-volatile exhaust gases. Real-world source measurements of ground vehicle PM are obtained by deploying an AMS aboard a mobile laboratory. Characteristic features of the exhaust PM chemical composition and size distribution are discussed. PM mass and number concentrations are used with above-background gas-phase carbon dioxide (CO2) concentrations to calculate on-road emission factors for individual vehicles. Highly variable ratios between particle number and mass concentrations are observed for individual vehicles. NRPM1 mass emission factors measured for on-road diesel vehicles are approximately 50% lower than those from dynamometer studies. Factor analysis of AMS data (FA-AMS) is applied for the first time to map variations in exhaust PM mass downwind of a highway. In this study, above-background vehicle PM concentrations are highest close to the highway and decrease by a factor of 2 by 200 m away from the highway. Comparison with the gas-phase CO2 concentrations indicates that these vehicle PM mass gradients are largely driven by dilution. Secondary aerosol species do not show a similar gradient in absolute mass concentrations; thus, their relative contribution to total ambient PM mass concentrations increases as a function of distance from the highway. FA-AMS of single particle and ensemble data at an urban receptor site shows that condensation of these secondary aerosol species onto vehicle exhaust particles results in spatial and temporal evolution of the size and composition of vehicle exhaust PM on urban and regional scales.

On-road emission factors of PM pollutants for light-duty vehicles (LDVs) based on urban street driving conditions

NASA Astrophysics Data System (ADS)

Kam, Winnie; Liacos, James W.; Schauer, James J.; Delfino, Ralph J.; Sioutas, Constantinos

2012-12-01

An on-road sampling campaign was conducted on two major surface streets (Wilshire and Sunset Boulevards) in Los Angeles, CA, to characterize PM components including metals, trace elements, and organic species for three PM size fractions (PM10-2.5, PM2.5-0.25, and PM0.25). Fuel-based emission factors (mass of pollutant per kg of fuel) were calculated to assess the emissions profile of a light-duty vehicle (LDV) traffic fleet characterized by stop-and-go driving conditions that are reflective of urban street driving. Emission factors for metals and trace elements were highest in PM10-2.5 while emission factors for PAHs and hopanes and steranes were highest in PM0.25. PM2.5 emission factors were also compared to previous freeway, roadway tunnel, and dynamometer studies based on an LDV fleet to determine how various environments and driving conditions may influence concentrations of PM components. The on-road sampling methodology deployed in the current study captured substantially higher levels of metals and trace elements associated with vehicular abrasion (Fe, Ca, Cu, and Ba) and crustal origins (Mg and Al) than previous LDV studies. The semi-volatile nature of PAHs resulted in higher levels of PAHs in the particulate phase for LDV tunnel studies (Phuleria et al., 2006) and lower levels of PAHs in the particulate phase for freeway studies (Ning et al., 2008). With the exception of a few high molecular weight PAHs, the current study's emission factors were in between the LDV tunnel and LDV freeway studies. In contrast, hopane and sterane emission factors were generally comparable between the current study, the LDV tunnel, and LDV freeway, as expected given the greater atmospheric stability of these organic compounds. Overall, the emission factors from the dynamometer studies for metals, trace elements, and organic species are lower than the current study. Lastly, n-alkanes (C19-C40) were quantified and alkane carbon preference indices (CPIs) were determined to be in the range of 1-2, indicating substantial anthropogenic source contribution for surface streets in Los Angeles.

Underground and ground-level particulate matter concentrations in an Italian metro system

NASA Astrophysics Data System (ADS)

Cartenì, Armando; Cascetta, Furio; Campana, Stefano

2015-01-01

All around the world, many studies and experimental results have assessed elevated concentrations of Particulate Matter (PM) in underground metro systems, with non-negligible implications for human health due to protracted exposure to fine particles. Starting from this consideration, an intensive particulate sampling campaign was carried out in January 2014 measuring the PM concentrations in the Naples (Italy) Metro Line 1, both at station platforms and inside trains. Naples Metro Line 1 is about 18 km long, with 17 stations (3 ground-level and 14 below-ground ones). Experimental results show that the average PM10 concentrations measured in the underground station platforms range between 172 and 262 μg/m3 whilst the average PM2.5 concentrations range between 45 and 60 μg/m3. By contrast, in ground-level stations no significant difference between stations platforms and urban environment measurements was observed. Furthermore, a direct correlation between trains passage and PM concentrations was observed, with an increase up to 42% above the average value. This correlation is possibly caused by the re-suspension of the particles due to the turbulence induced by trains. The main original finding was the real-time estimations of PM levels inside the trains travelling both in ground-level and underground sections of Line 1. The results show that high concentrations of both PM10 (average values between 58 μg/m3 and 138 μg/m3) and PM2.5 (average values between 18 μg/m3 and 36 μg/m3) were also measured inside trains. Furthermore, measurements show that windows left open on trains caused the increase in PM concentrations inside trains in the underground section, while in the ground-level section the clean air entering the trains produced an environmental "washing effect". Finally, it was estimated that every passenger spends on average about 70 min per day exposed to high levels of PM.

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.

[Study of relationship between atmospheric fine particulate matter concentration and one grade a tertiary hospital emergency room visits during 2012 and 2013 in Beijing].

PubMed

Wang, Xuying; Li, Guoxing; Jin, Xiaobin; Mu, Jing; Pan, Jie; Liang, Fengchao; Tian, Lin; Chen, Shi; Guo, Qun; Dong, Wentan; Pan, Xiaochuan

2016-01-01

To explore the concentration-response relationship between ambient concentration of PM2.5 and daily total hospital emergency room visits in Beijing during 2012 and 2013. This study also examined the effects of ambient PM2.5 during heavy polluted days on emergency room visits compared with the light polluted days. We collected the daily meteorological factors monitoring data and concentrations of air pollutants in Beijing during October 1, 2012 to December 31, 2013. We also collected the daily emergency room visits from a tertiary hospital in Beijing in the same time period. Generalized additive model was fitted to estimate the association between the ambient PM2.5 and the hospital emergency room visits, by using the smooth function to adjust long term trend of time, public holidays and day of week. In addition, constrained piecewise linear function was then used to estimate the excess risk for different segment of concentration-response function. The annual average concentration of PM2.5 was 90.9 µg/m(3) during October 1, 2012 and December 31, 2013. There were total 64 260 cases for total emergency room visits, of which respiratory disease had 9 849 cases and cardiovascular disease had 11 168 cases. PM2.5 was positive related with PM10, NO2 and SO2. The corresponding correlation coefficients were 0.87, 0.78 and 0.62, respectively (P<0.05). And PM2.5 was positively related with relative humidity, with correlation coefficient 0.45 (P<0.05). But PM2.5 was negatively related with mean temperature (r=-0.17, P< 0.05) and wind speed (- 0.32, P<0.05). In the single polluted model, after adjusting the effects of temperature, relative humidity and wind, every 10 µg/m(3) increase of concentration of ambient PM2.5, the corresponding excess risk of daily emergency room visits was 0.25% (95% CI: 0.07-0.43). In the two-pollutant model PM2.5+SO2 and PM2.5+NO2, every 10 µg/m(3) increase of concentration of ambient PM2.5, the corresponding excess risk of daily emergency room visits were 1.07% (95%CI:0.83-1.30) and 0.56% (95%CI: 0.32-0.80) respectively, which were higher than the effect in single pollutant model. Average concentration of ambient particulate matters (PM2.5) was 204.16 µg/m(3) during heavy pollution, higher than control period (85.24 µg/m(3)). When PM2.5 as the primary air pollutants during heavy polluted days, we observed a significant increase in emergency room visits, and the odd ratios was 1.16 (95% CI:1.09-1.22). There were positive correlation between high concentration of ambient particulate matters (PM2.5) and increasing daily emergency room visits. Especially during the heavy polluted days, the effects of elevated concentration of PM2.5 on hospital emergency room visits were much larger.

Particulate matter chemical component concentrations and sources in settings of household solid fuel use.

PubMed

Secrest, M H; Schauer, J J; Carter, E M; Baumgartner, J

2017-11-01

Particulate matter (PM) air pollution derives from combustion and non-combustion sources and consists of various chemical species that may differentially impact human health and climate. Previous reviews of PM chemical component concentrations and sources focus on high-income urban settings, which likely differ from the low- and middle-income settings where solid fuel (ie, coal, biomass) is commonly burned for cooking and heating. We aimed to summarize the concentrations of PM chemical components and their contributing sources in settings where solid fuel is burned. We searched the literature for studies that reported PM component concentrations from homes, personal exposures, and direct stove emissions under uncontrolled, real-world conditions. We calculated weighted mean daily concentrations for select PM components and compared sources of PM determined by source apportionment. Our search criteria yielded 48 studies conducted in 12 countries. Weighted mean daily cooking area concentrations of elemental carbon, organic carbon, and benzo(a)pyrene were 18.8 μg m -3 , 74.0 μg m -3 , and 155 ng m -3 , respectively. Solid fuel combustion explained 29%-48% of principal component/factor analysis variance and 41%-87% of PM mass determined by positive matrix factorization. Multiple indoor and outdoor sources impacted PM concentrations and composition in these settings, including solid fuel burning, mobile emissions, dust, and solid waste burning. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Effect of hydrolysis of N2O5 on nitrate and ammonium formation in Beijing China: WRF-Chem model simulation.

PubMed

Su, Xing; Tie, Xuexi; Li, Guohui; Cao, Junji; Huang, Rujin; Feng, Tian; Long, Xin; Xu, Ruiguang

2017-02-01

Beijing, the capital of China, is a mega city with a population of >20 million. In recent years, the city has experienced heavy air pollution, with particulate matter (PM) being one of its top pollutants. In the last decade, extensive efforts have been made to characterize the sources, properties, and processes of PM in Beijing. Despite progress made by previous studies, there are still some important questions to be answered and addressed. The focus of this research is to study the impact of the heterogeneous hydrolysis of N 2 O 5 on the formation of nitrate (NO 3 - ) and ammonium (NH 4 + ) in Beijing. The results show that during heavy pollution days (e.g., during 14-17 September 2015, with PM 2.5 concentration over 100μg/m 3 ), the concentrations of NO 2 and O 3 were high, with maxima of 90 and 240μg/m 3 , respectively, providing high precursors for the formation of N 2 O 5 . In addition, the aerosol and sulfate concentrations were also high, with maxima of 201μg/m 3 and 23μg/m 3 respectively, providing reacting surface for the heterogeneous reaction. As a result, the hydrolysis of N 2 O 5 led to 21.0% enhancement of nitrate (NO 3 - ) and 7.5% enhancement of ammonium (NH 4 + ). It is worth to note that this important effect only occurred in high pollution days (PM 2.5 concentration over 100μg/m 3 ). During low-pollution periods (PM 2.5 concentration <100μg/m 3 ), the effect of hydrolysis of N 2 O 5 on the formation of nitrate and ammonium was insignificant (variation rate <5%). This study suggests that during heavy pollution periods, the hydrolysis of N 2 O 5 enhances the level of aerosol pollution in Beijing, and needs to be further studied in order to perform efficient air pollution control and mitigation strategies. Copyright © 2016 Elsevier B.V. All rights reserved.

African dust particles and their impact on the solar energy budget in a Caribbean tropical montane cloud forest

NASA Astrophysics Data System (ADS)

Rivera, F. A.; Mayol-Bracero, O. L.; Torres-Delgado, E.

2017-12-01

To understand the impact of aerosols over the atmospheric energy budget it is essential to identify their size and chemical properties. Atmospheric aerosols emitted, for example, from African dust storms, directly affect climate by altering the dynamics of cloud formation and by reducing the amount of radiation reaching vegetation and the soil surface. In this project, we seek to improve our understanding of the variations in the concentrations of African dust and the role it might play in the energy budget at a Tropical Montane Cloud Forest (TMCF). Concentrations of particulate matter with diameters equal or less than 10µm (PM10) and aerosol optical properties (scattering and absorption) for years 2013 and 2014 were studied in northeastern Puerto Rico at the nature reserve of Cabezas de San Juan (CSJ). At CSJ we used an Integrating Nephelometer to measure light scattering at three wavelengths (450, 550 and 700 nm) and calculated the Scattering Angstrom Exponent (SAE), a measure inversely related to the size of the aerosol particle. We also used the Continuous Light Absorption Photometer (CLAP) to measure the light absorption at three wavelengths (450, 550 and 700). Visibility (meters) and radiation (total solar, UV and IR irradiation) were studied at the TMCF of Pico del Este (PE). PM10 data from stations at Cataño, Guaynabo, and Fajardo were also obtained. The PM10 data were used to study the variation in aerosol concentrations during the year and to study whether there was an effect on the incoming solar radiation. The periods under the influence of African dust were identified using the spectral coefficients measured at CSJ and the air mass back trajectories using the HYSPLIT model. During the summer period, an increase in PM10 concentrations, related to African Dust incursions, was observed. Preliminary results suggest that, for 2013 and 2014, in the presence of high concentrations of PM10 and with low SAE, the total radiation at PE decreased. This could be related to the interactions between solar radiation and aerosol particles and will be discussed in the presentation.

Temporal characteristics of black carbon concentrations and its potential emission sources in a southern Taiwan industrial urban area.

PubMed

Cheng, Yu-Hsiang; Lin, Chi-Chi; Liu, Jyh-Jian; Hsieh, Cheng-Ju

2014-03-01

This study investigates the temporal characteristics of black carbon and its potential emission sources, as well as the fractions of BC in PM2.5 levels in Kaohsiung urban area, which is an industrial city in southern Taiwan. Concentrations of BC and PM2.5 are monitored continuously from March 2006 to February 2010, using an aethalometer and a tapered element oscillating microbalance monitor. Additionally, the presence of organic compounds (or UV enhanced species) in particles at the sampling site is determined using the Delta-C (UVBC-BC) value. According to long-term measurement results, BC and PM2.5 concentrations are 3.33 and 34.0 μg m(-3), respectively, in the Kaohsiung urban area. The ratio of BC/PM2.5 is approximately 11 %. Low concentration of BC and PM2.5 in the summer of this study period is mostly likely owing to meteorological conditions that favored dispersion of local air pollutants. Nevertheless, BC concentrations peaked markedly during morning hours (7:00-11:00), likely owing to local traffic congestion. Measurement results suggest that BC is released from local traffic activities and emitted from industrial activities at this sampling site. Additionally, Delta-C values are significantly higher than zero during January-March and November-December periods in this industrial urban area, implying that UV enhanced species can be observed. At this sampling site, these UV enhanced species do not only originate from household activity and solid waste burning but also release from industrial activities. The elevated Delta-C values during nighttime (18:00-6:00) in the autumn and winter seasons are likely related to those UV enhanced species in the atmosphere, which can be condensed on particle surface under low temperature conditions. According to long-term measurement results, significantly positive Delta-C values can be observed under temperatures <20 °C and relative humidity of 60-75 % in this study. Despite the household activity and solid waste burning, the major sources of particles that are bound with UV enhanced species in this sampling site are industrial parks and a coal-fired power plant.

Impact of Saharan dust particles on hospital admissions in Madrid (Spain).

PubMed

Reyes, María; Díaz, Julio; Tobias, Aurelio; Montero, Juan Carlos; Linares, Cristina

2014-01-01

Saharan dust intrusions make a major contribution to levels of particulate matter (PM) present in the atmosphere of large cities. We analysed the impact of different PM fractions during periods with and without Saharan dust intrusions, using time-series analysis with Poisson regression models, based on: concentrations of coarse PM (PM10 and PM10-2.5) and fine PM (PM2.5); and daily all-, circulatory- and respiratory-cause hospital admissions. While periods without Saharan dust intrusions were marked by a statistically significant association between daily mean PM2.5 concentrations and all- and circulatory-cause hospital admissions, periods with such intrusions saw a significant increase in respiratory-cause admissions associated with fractions corresponding to PM10 and PM10-2.5.

An ecologic analysis of county-level PM2.5 concentrations and lung cancer incidence and mortality.

PubMed

Vinikoor-Imler, Lisa C; Davis, J Allen; Luben, Thomas J

2011-06-01

Few studies have explored the relationship between PM2.5 and lung cancer incidence. Although results are mixed, some studies have demonstrated a positive relationship between PM2.5 and lung cancer mortality. Using an ecologic study design, we examined the county-level associations between PM2.5 concentrations (2002-2005) and lung cancer incidence and mortality in North Carolina (2002-2006). Positive trends were observed between PM2.5 concentrations and lung cancer incidence and mortality; however, the R2 for both were <0.10. The slopes for the relationship between PM2.5 and lung cancer incidence and mortality were 1.26 (95% CI 0.31, 2.21, p-value 0.01) and 0.73 (95% CI 0.09, 1.36, p-value 0.03) per 1 μg/m3 PM2.5, respectively. These associations were slightly strengthened with the inclusion of variables representing socioeconomic status and smoking. Although variability is high, thus reflecting the importance of tobacco smoking and other etiologic agents that influence lung cancer incidence and mortality besides PM2.5, a positive trend is observed between PM2.5 and lung cancer incidence and mortality. This suggests the possibility of an association between PM2.5 concentrations and lung cancer incidence and mortality.

An Ecologic Analysis of County-Level PM2.5 Concentrations and Lung Cancer Incidence and Mortality

PubMed Central

Vinikoor-Imler, Lisa C.; Davis, J. Allen; Luben, Thomas J.

2011-01-01

Few studies have explored the relationship between PM2.5 and lung cancer incidence. Although results are mixed, some studies have demonstrated a positive relationship between PM2.5 and lung cancer mortality. Using an ecologic study design, we examined the county-level associations between PM2.5 concentrations (2002–2005) and lung cancer incidence and mortality in North Carolina (2002–2006). Positive trends were observed between PM2.5 concentrations and lung cancer incidence and mortality; however, the R2 for both were <0.10. The slopes for the relationship between PM2.5 and lung cancer incidence and mortality were 1.26 (95% CI 0.31, 2.21, p-value 0.01) and 0.73 (95% CI 0.09, 1.36, p-value 0.03) per 1 μg/m3 PM2.5, respectively. These associations were slightly strengthened with the inclusion of variables representing socioeconomic status and smoking. Although variability is high, thus reflecting the importance of tobacco smoking and other etiologic agents that influence lung cancer incidence and mortality besides PM2.5, a positive trend is observed between PM2.5 and lung cancer incidence and mortality. This suggests the possibility of an association between PM2.5 concentrations and lung cancer incidence and mortality. PMID:21776206

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.

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

PubMed

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

2017-11-13

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

Spatially and chemically resolved source apportionment analysis: Case study of high particulate matter event

NASA Astrophysics Data System (ADS)

Kim, Byeong-Uk; Bae, Changhan; Kim, Hyun Cheol; Kim, Eunhye; Kim, Soontae

2017-08-01

This article presents the results of a detailed source apportionment study of the high particulate matter (PM) event in the Seoul Metropolitan Area (SMA), South Korea, during late February 2014. Using the Comprehensive Air Quality Model with Extensions with its Particulate Source Apportionment Technology (CAMx-PSAT), we defined 10 source regions, including five in China, for spatially and chemically resolved analyses. During the event, the spatially averaged PM10 concentration at all PM10 monitors in the SMA was 129 μg/m3, while the PM10 and PM2.5 concentrations at the BulGwang Supersite were 143 μg/m3 and 123 μg/m3, respectively. CAMx-PSAT showed reasonably good PM model performance in both China and the SMA. For February 23-27, CAMx-PSAT estimated that Chinese contributions to the SMA PM10 and PM2.5 were 84.3 μg/m3 and 80.0 μg/m3, respectively, or 64% and 70% of the respective totals, while South Korea's respective domestic contributions were 36.5 μg/m3 and 23.3 μg/m3. We observed that the spatiotemporal pattern of PM constituent concentrations and contributions did not necessarily follow that of total PM10 and PM2.5 concentrations. For example, Beijing-Tianjin-Hebei produced high nitrate concentrations, but the two most-contributing regions to PM in the SMA were the Near Beijing area and South Korea. In addition, we noticed that the relative contributions from each region changed over time. We found that most ammonium mass that neutralized Chinese sulfate mass in the SMA came from South Korean sources, indicating that secondary inorganic aerosol in the SMA, especially ammonium sulfates, during this event resulted from different major precursors originating from different regions.

Impact of local traffic exclusion on near-road air quality: findings from the New York City "Summer Streets" campaign.

PubMed

Whitlow, Thomas H; Hall, Andrew; Zhang, K Max; Anguita, Juan

2011-01-01

We monitored curbside airborne particulate matter (PM) concentrations and its proinflammatory capacity during 3 weekends when vehicle traffic was excluded from Park. Ave., New York City. Fine PM concentration peaked in the morning regardless of traffic while ultrafine PM was 58% lower during mornings without traffic. Ultrafine PM concentration varied linearly with traffic flow, while fine PM spiked sharply in response to random traffic events that were weakly correlated with the traffic signal cycle. Ultrafine PM concentrations decayed exponentially with distance from a cross street with unrestricted traffic flow, reaching background levels within 100 m of the source. IL-6 induction was typically highest on Friday afternoons but showed no clear relationship to the presence of traffic. The coarse fraction (>2.5 μm) had the greatest intrinsic inflammatory capacity, suggesting that coarse PM still warrants attention even as the research focus is shifting to nano-particles. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

PubMed

Ng, Kar Yong; Awang, Norhashidah

2018-01-06

Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.

Composition of PM2.5 and PM1 on high and low pollution event days and its relation to indoor air quality in a home for the elderly.

PubMed

Buczyńska, Anna J; Krata, Agnieszka; Van Grieken, Rene; Brown, Andrew; Polezer, Gabriela; De Wael, Karolien; Potgieter-Vermaak, Sanja

2014-08-15

Many studies probing the link between air quality and health have pointed towards associations between particulate matter (PM) exposure and decreased lung function, aggravation of respiratory diseases like asthma, premature death and increased hospitalisation admissions for the elderly and individuals with cardiopulmonary diseases. Of recent, it is believed that the chemical composition and physical properties of PM may contribute significantly to these adverse health effects. As part of a Belgian Science Policy project ("Health effects of particulate matter in relation to physical-chemical characteristics and meteorology"), the chemical composition (elemental and ionic compositions) and physical properties (PM mass concentrations) of PM were investigated, indoors and outdoors of old age homes in Antwerp. The case reported here specifically relates to high versus normal/low pollution event periods. PM mass concentrations for PM1 and PM2.5 fractions were determined gravimetrically after collection via impaction. These same samples were hence analysed by EDXRF spectrometry and IC for their elemental and ionic compositions, respectively. During high pollution event days, PM mass concentrations inside the old age home reached 53 μg m(-3) and 32 μg m(-3) whilst outside concentrations were 101 μg m(-3) and 46 μg m(-3) for PM2.5 and PM1, respectively. The sum of nss-sulphate, nitrate and ammonium, dominate the composition of PM, and contribute the most towards an increase in the PM during the episode days constituting 64% of ambient PM2.5 (52 μg m(-3)) compared to 39% on non-episode days (10 μg m(-3)). Other PM components, such as mineral dust, sea salt or heavy metals were found to be considerably higher during PM episodes but relatively less important. Amongst heavy metals Zn and Pb were found at the highest concentrations in both PM2.5 and PM1. Acid-base ionic balance equations were calculated and point to acidic aerosols during event days and acidic to alkaline aerosols during non-event days. No significant sources of indoor pollutants could be identified inside the old-age home as high correlations were found between outdoor and indoor PM, confirming mainly the outdoor origin of indoor air. Copyright © 2014 Elsevier B.V. All rights reserved.

Effect of grinding intensity and pelleting of the diet on indoor particulate matter concentrations and growth performance of weanling pigs.

PubMed

Ulens, T; Demeyer, P; Ampe, B; Van Langenhove, H; Millet, S

2015-02-01

This study evaluated the effect of feed form and grinding intensity of the pig diet and the interaction between both on the particulate matter (PM) concentrations inside a pig nursery and the growth performances of weanling pigs. Four diets were compared: finely ground meal, coarsely ground meal, finely ground pellets, and coarsely ground pellets. Four weaning rounds with 144 pigs per weaning round, divided over 4 identical compartments, were monitored. Within each weaning round, each compartment was randomly assigned to 1 of 4 treatments. A hammer mill with a screen of 1.5 or 6 mm was used to grind the ingredients of the finely ground and coarsely ground feeds, respectively. Indoor concentrations of the following PM fractions were measured: PM that passes through a size-selective inlet with a 50 % efficiency cutoff at 10 (PM10) , 2.5 (PM2.5), or 1 (PM1) μm aerodynamic diameter, respectively (USEPA, 2004). Feeding pelleted diets instead of meal diets gave rise to higher PM10 (P < 0.001), PM2.5 (P < 0.001), and PM1 (P < 0.001) concentrations. Grinding intensity had an effect only on PM10 (P < 0.05) concentrations. No interaction between feed form and grinding intensity was found for any of the PM fractions. Interactions (P < 0.05) between feed form and grinding intensity on ADFI and ADG were found. Grinding intensity had an effect only on the meal diets with higher ADFI for the coarsely ground meal. Pigs fed the finely ground meal had a lower (P < 0.001) ADG than the other 3 diets. Feed efficiency was influenced only by the feed form (P < 0.001) and not by the grinding intensity. Pelleting the feed gave rise to a higher G:F. In conclusion, a contradiction between environmental concerns and performance results was found. Feeding pelleted diets to the piglets improved growth performance but also increased indoor PM concentrations.

High-resolution satellite remote sensing of provincial PM2.5 trends in China from 2001 to 2015

NASA Astrophysics Data System (ADS)

Lin, C. Q.; Liu, G.; Lau, A. K. H.; Li, Y.; Li, C. C.; Fung, J. C. H.; Lao, X. Q.

2018-05-01

Given the vast territory of China, the long-term PM2.5 trends may substantially differ among the provinces. In this study, we aim to assess the provincial PM2.5 trends in China during the past few Five-Year Plan (FYP) periods. The lack of long-term PM2.5 measurements, however, makes such assessment difficult. Satellite remote sensing of PM2.5 concentration is an important step toward filling this data gap. In this study, a PM2.5 data set was built over China at a resolution of 1 km from 2001 to 2015 using satellite remote sensing. Analyses show that the national average of PM2.5 concentration increased by 0.04 μg·m-3·yr-1 during the 10th FYP period (2001-2005) and started to decline by -0.65 μg·m-3·yr-1 and -2.33 μg·m-3·yr-1 during the 11th (2006-2010) and the 12th (2011-2015) FYP period, respectively. In addition, substantial differences in the PM2.5 trends were observed among the provinces. Provinces in the Beijing-Tianjin-Hebei (BTH) region had the largest reduction of PM2.5 concentrations during the 10th and 12th FYP period. The greatest reduction rate of PM2.5 concentration during the 10th and 12th FYP period was observed in Beijing (-3.68 μg·m-3·yr-1) and Tianjin (-6.62 μg·m-3·yr-1), respectively. In contrast, PM2.5 concentrations remained steady for provinces in eastern and southeastern China (e.g., Shanghai) during the 12th FYP period. In overall, great efforts are still required to effectively reduce the PM2.5 concentrations in future.

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Forecasting of particulate matter time series using wavelet analysis and wavelet-ARMA/ARIMA model in Taiyuan, China.

PubMed

Zhang, Hong; Zhang, Sheng; Wang, Ping; Qin, Yuzhe; Wang, Huifeng

2017-07-01

Particulate matter with aerodynamic diameter below 10 μm (PM 10 ) forecasting is difficult because of the uncertainties in describing the emission and meteorological fields. This paper proposed a wavelet-ARMA/ARIMA model to forecast the short-term series of the PM 10 concentrations. It was evaluated by experiments using a 10-year data set of daily PM 10 concentrations from 4 stations located in Taiyuan, China. The results indicated the following: (1) PM 10 concentrations of Taiyuan had a decreasing trend during 2005 to 2012 but increased in 2013. PM 10 concentrations had an obvious seasonal fluctuation related to coal-fired heating in winter and early spring. (2) Spatial differences among the four stations showed that the PM 10 concentrations in industrial and heavily trafficked areas were higher than those in residential and suburb areas. (3) Wavelet analysis revealed that the trend variation and the changes of the PM 10 concentration of Taiyuan were complicated. (4) The proposed wavelet-ARIMA model could be efficiently and successfully applied to the PM 10 forecasting field. Compared with the traditional ARMA/ARIMA methods, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. Wavelet analysis can filter noisy signals and identify the variation trend and the fluctuation of the PM 10 time-series data. Wavelet decomposition and reconstruction reduce the nonstationarity of the PM 10 time-series data, and thus improve the accuracy of the prediction. This paper proposed a wavelet-ARMA/ARIMA model to forecast the PM 10 time series. Compared with the traditional ARMA/ARIMA method, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. The proposed model could be efficiently and successfully applied to the PM 10 forecasting field.

Airborne particulate matter in school classrooms of northern Italy.

PubMed

Rovelli, Sabrina; Cattaneo, Andrea; Nuzzi, Camilla P; Spinazzè, Andrea; Piazza, Silvia; Carrer, Paolo; Cavallo, Domenico M

2014-01-27

Indoor size-fractioned particulate matter (PM) was measured in seven schools in Milan, to characterize their concentration levels in classrooms, compare the measured concentrations with the recommended guideline values, and provide a preliminary assessment of the efficacy of the intervention measures, based on the guidelines developed by the Italian Ministry of Healthand applied to mitigate exposure to undesirable air pollutants. Indoor sampling was performed from Monday morning to Friday afternoon in three classrooms of each school and was repeated in winter 2011-2012 and 2012-2013. Simultaneously, PM2.5 samples were also collected outdoors. Two different photometers were used to collect the PM continuous data, which were corrected a posteriori using simultaneous gravimetric PM2.5 measurements. Furthermore, the concentrations of carbon dioxide (CO2) were monitored and used to determine the Air Exchange Rates in the classrooms. The results revealed poor IAQ in the school environment. In several cases, the PM2.5 and PM10 24 h concentrations exceeded the 24 h guideline values established by the World Health Organization (WHO). In addition, the indoor CO2 levels often surpassed the CO2 ASHRAE Standard. Our findings confirmed that important indoor sources (human movements, personal clouds, cleaning activities) emitted coarse particles, markedly increasing the measured PM during school hours. In general, the mean PM2.5 indoor concentrations were lower than the average outdoor PM2.5 levels, with I/O ratios generally <1. Fine PM was less affected by indoor sources, exerting a major impact on the PM1-2.5 fraction. Over half of the indoor fine particles were estimated to originate from outdoors. To a first approximation, the intervention proposed to reduce indoor particle levels did not seem to significantly influence the indoor fine PM concentrations. Conversely, the frequent opening of doors and windows appeared to significantly contribute to the reduction of the average indoor CO2 levels.

Characteristics of cabin air quality in school buses in Central Texas

NASA Astrophysics Data System (ADS)

Rim, Donghyun; Siegel, Jeffrey; Spinhirne, Jarett; Webb, Alba; McDonald-Buller, Elena

This study assessed in-cabin concentrations of diesel-associated air pollutants in six school buses with diesel engines during a typical route in suburban Austin, Texas. Air exchange rates measured by SF 6 decay were 2.60-4.55 h -1. In-cabin concentrations of all pollutants measured exhibited substantial variability across the range of tests even between buses of similar age, mileage, and engine type. In-cabin NO x concentrations ranged from 44.7 to 148 ppb and were 1.3-10 times higher than roadway NO x concentrations. Mean in-cabin PM 2.5 concentrations were 7-20 μg m -3 and were generally lower than roadway levels. In-cabin concentrations exhibited higher variability during cruising mode than frequent stops. Mean in-cabin ultrafine PM number concentrations were 6100-32,000 particles cm -3 and were generally lower than roadway levels. Comparison of median concentrations indicated that in-cabin ultrafine PM number concentrations were higher than or approximately the same as the roadway concentrations, which implied that, by excluding the bias caused by local traffic, ultrafine PM levels were higher in the bus cabin than outside of the bus. Cabin pollutant concentrations on three buses were measured prior to and following the phased installation of a Donaldson Spiracle Crankcase Filtration System and a Diesel Oxidation Catalyst. Following installation of the Spiracle, the Diesel Oxidation Catalyst provided negligible or small additional reductions of in-cabin pollutant levels. In-cabin concentration decreases with the Spiracle alone ranged from 24 to 37% for NO x and 26 to 62% and 6.6 to 43% for PM 2.5 and ultrafine PM, respectively. Comparison of the ranges of PM 2.5 and ultrafine PM variations between repetitive tests suggested that retrofit installation could not always be conclusively linked to the decrease of pollutant levels in the bus cabin.

Using PM2.5 concentrations to estimate the health burden from solid fuel combustion, with application to Irish and Scottish homes

PubMed Central

2013-01-01

Background This study estimates the potential population health burden from exposure to combustion-derived particulate air pollution in domestic settings in Ireland and Scotland. Methods The study focused on solid fuel combustion used for heating and the use of gas for cooking. PM2.5 (particulate matter with an aerodynamic diameter < 2.5 μm) was used as the pollutant mixture indicator. Measured PM2.5 concentrations in homes using solid fuels were adjusted for other sources of PM2.5 by subtracting PM2.5 concentrations in homes using gas for cooking but not solid fuel heating. Health burden was estimated for exposure indoors 6 pm - midnight, or all day (24-hour), by combining estimated attributable annual PM2.5 exposures with (i) selected epidemiological functions linking PM2.5 with mortality and morbidity (involving some re-scaling from PM10 to PM2.5, and adjustments ‘translating’ from concentrations to exposures) and (ii) on the current population exposed and background rates of morbidity and mortality. Results PM2.5 concentrations in coal and wood burning homes were similar to homes using gas for cooking, used here as a baseline (mean 24-hr PM2.5 concentrations 8.6 μg/m3) and so health impacts were not calculated. Concentrations of PM2.5 in homes using peat were higher (24-hr mean 15.6 μg/m3); however, health impacts were calculated for the exposed population in Ireland only; the proportion exposed in Scotland was very small. The assessment for winter evening exposure (estimated annual average increase of 2.11 μg/m3 over baseline) estimated 21 additional annual cases of all-cause mortality, 55 of chronic bronchitis, and 30,100 and 38,000 annual lower respiratory symptom days (including cough) and restricted activity days respectively. Conclusion New methods for estimating the potential health burden of combustion-generated pollution from solid fuels in Irish and Scottish homes are provided. The methodology involves several approximations and uncertainties but is consistent with a wider movement towards quantifying risks in PM2.5 irrespective of source. Results show an effect of indoor smoke from using peat (but not wood or coal) for heating and cooking; but they do not suggest that this is a major public health issue. PMID:23782423

Using PM2.5 concentrations to estimate the health burden from solid fuel combustion, with application to Irish and Scottish homes.

PubMed

Galea, Karen S; Hurley, J Fintan; Cowie, Hilary; Shafrir, Amy L; Sánchez Jiménez, Araceli; Semple, Sean; Ayres, Jon G; Coggins, Marie

2013-06-19

This study estimates the potential population health burden from exposure to combustion-derived particulate air pollution in domestic settings in Ireland and Scotland. The study focused on solid fuel combustion used for heating and the use of gas for cooking. PM2.5 (particulate matter with an aerodynamic diameter < 2.5 μm) was used as the pollutant mixture indicator. Measured PM2.5 concentrations in homes using solid fuels were adjusted for other sources of PM2.5 by subtracting PM2.5 concentrations in homes using gas for cooking but not solid fuel heating. Health burden was estimated for exposure indoors 6 pm - midnight, or all day (24-hour), by combining estimated attributable annual PM2.5 exposures with (i) selected epidemiological functions linking PM2.5 with mortality and morbidity (involving some re-scaling from PM10 to PM2.5, and adjustments 'translating' from concentrations to exposures) and (ii) on the current population exposed and background rates of morbidity and mortality. PM2.5 concentrations in coal and wood burning homes were similar to homes using gas for cooking, used here as a baseline (mean 24-hr PM2.5 concentrations 8.6 μg/m3) and so health impacts were not calculated. Concentrations of PM2.5 in homes using peat were higher (24-hr mean 15.6 μg/m3); however, health impacts were calculated for the exposed population in Ireland only; the proportion exposed in Scotland was very small. The assessment for winter evening exposure (estimated annual average increase of 2.11 μg/m3 over baseline) estimated 21 additional annual cases of all-cause mortality, 55 of chronic bronchitis, and 30,100 and 38,000 annual lower respiratory symptom days (including cough) and restricted activity days respectively. New methods for estimating the potential health burden of combustion-generated pollution from solid fuels in Irish and Scottish homes are provided. The methodology involves several approximations and uncertainties but is consistent with a wider movement towards quantifying risks in PM2.5 irrespective of source. Results show an effect of indoor smoke from using peat (but not wood or coal) for heating and cooking; but they do not suggest that this is a major public health issue.

Ambient particulate matter and carbon monoxide at an urban site of India: Influence of anthropogenic emissions and dust storms.

PubMed

Yadav, Ravi; Sahu, L K; Beig, G; Tripathi, Nidhi; Jaaffrey, S N A

2017-06-01

Continuous measurements of PM 2.5 , PM 10 and CO were conducted at an urban site of Udaipur in India from April 2011 to March 2012. The annual mean concentrations of PM 2.5, PM 10 and CO were 42 ± 17 μg m -3 , 114 ± 31 μg m -3 and 343 ± 136 ppbv, respectively. Concentrations of both particulate and CO showed high values during winter/pre-monsoon (dry) period and lowest in the monsoon season (wet). Local anthropogenic emission and long-range transport from open biomass burning sources along with favourable synoptic meteorology led to elevated levels of pollutants in the dry season. However, higher values of PM 10 /PM 2.5 ratio during pre-monsoon season were caused by the episodes of dust storm. In the monsoon season, flow of cleaner air, rainfall and negligible emissions from biomass burning resulted in the lowest levels of pollutants. The concentrations of PM 2.5 , PM 10 and CO showed highest values during morning and evening rush hours, while lowest in the afternoon hours. In winter season, reductions of PM 2.5, CO and PM 10 during weekends were highest of 15%, 13% and 9%, respectively. In each season, the highest PM 2.5 /PM 10 ratio coincided with the highest concentrations of pollutants (CO and NO X ) indicating predominant emissions from anthropogenic sources. Exceptionally high concentrations of PM 10 during the episode of dust storm were due to transport from the Arabian Peninsula and Thar Desert. Up to ∼32% enhancements of PM 10 were observed during strong dust storms. Relatively low levels of O 3 and NO x during the storm periods indicate the role of heterogeneous removal. Copyright © 2017 Elsevier Ltd. All rights reserved.

Particulate matter emissions of different brands of mentholated cigarettes.

PubMed

Gerharz, Julia; Bendels, Michael H K; Braun, Markus; Klingelhöfer, Doris; Groneberg, David A; Mueller, Ruth

2018-06-01

Inhaling particulate matter (PM) in environmental tobacco smoke (ETS) endangers the health of nonsmokers. Menthol, an additive in cigarettes, attenuates respiratory irritation of tobacco smoke. It reduces perceptibility of smoke and therefore passive smokers may inhale ETS unnoticed. To investigate a possible effect of menthol on PM concentrations (PM 10 , PM 2.5 , and PM 1 ), ETS of four mentholated cigarette brands (Elixyr Menthol, Winston Menthol, Reyno Classic, and Pall Mall Menthol Blast) with varying menthol content was analyzed. ETS was generated in a standardized way using an automatic environmental tobacco smoke emitter (AETSE), followed by laser aerosol spectrometry. This analysis shows that the tested cigarette brands, despite having different menthol concentrations, do not show differences with regard to PM emissions, with the exception of Reyno Classic, which shows an increased emission, although the menthol level ranged in the midfield. More than 90% of the emitted particles had a size smaller than or equal to 1 µm. Regardless of the menthol level, the count median diameter (CMD) and the mass median diameter (MMD) were found to be 0.3 µm and 0.5 µm, respectively. These results point out that there is no effect of menthol on PM emission and that other additives might influence the increased PM emission of Reyno Classic. Particulate matter (PM) in ETS endangers the health of nonsmokers and smokers. This study considers the effect of menthol, an additive in cigarettes, on PM emissions. Does menthol increase the amount of PM? Due to the exposure to secondhand smoke nearly 900,000 people die each year worldwide. The aim of the study is to measure the particle concentration (L -1 ), mass concentration (µg m -3 ), and dust mass fractions shown as PM 10 , PM 2.5 , and PM 1 of five different cigarette brands, including four with different menthol concentrations and one menthol-free reference cigarette, in a well-established standardized system.

Implications of RCP emissions on future PM2.5 air quality and direct radiative forcing over China

NASA Astrophysics Data System (ADS)

Li, Ke; Liao, Hong; Zhu, Jia; Moch, Jonathan M.

2016-11-01

Severe PM2.5 air pollution in China and the First Grand National Standard (FGNS), implemented in 2016 (annual PM2.5 concentration target of less than 35 µg m-3), necessitate urgent reduction strategies. This study applied the nested-grid version of the Goddard Earth Observing System (GEOS) chemical transport model (GEOS-Chem) to quantify 2000-2050 changes in PM2.5 air quality and related direct radiative forcing (DRF) in China, based on future emission changes under the representative concentration pathway (RCP) scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP8.5. In the near term (2000-2030), a projected maximum increase in PM2.5 concentrations of 10-15 µg m-3 is found over east China under RCP6.0 and RCP8.5 and less than 5 µg m-3 under RCP2.6 and RCP4.5. In the long term (2000-2050), PM2.5 pollution clearly improves, and the largest decrease in PM2.5 concentrations of 15-30 µg m-3 is over east China under all RCPs except RCP6.0. Focusing particularly on highly polluted regions, we find that Beijing-Tianjin-Hebei (BTH) wintertime PM2.5 concentrations meeting the FGNS occur after 2040 under RCP2.6, RCP4.5, and RCP8.5, and summertime PM2.5 concentrations reach this goal by 2030 under RCP2.6 and RCP4.5. In Sichuan Basin (SCB), wintertime PM2.5 concentrations below the FGNS occur only in 2050 under RCP2.6 and RCP4.5, although future summertime PM2.5 will be well controlled. The difficulty in controlling future PM2.5 concentrations relates to unmitigated high levels of nitrate, although NOx and SO2 emissions show substantial reductions during 2020-2040. The changes in aerosol concentrations lead to positive aerosol DRF over east China (20°-45°N, 100°-125°E) by 1.22, 1.88, and 0.66 W m-2 in 2050 relative to 2000 under RCP2.6, RCP4.5, and RCP8.5, respectively. When considering both health and climate effects of PM2.5 over China, for example, PM2.5 concentrations averaged over east China under RCP4.5 (RCP2.6) decrease by 54% (43%) in 2050 relative to 2000, but at the cost of warming with DRF of 1.88 (1.22) W m-2. Our results indicate that it will be possible to mitigate future PM2.5 pollution in China, but it will likely take two decades for polluted regions such as BTH and SCB to meet the FGNS, based on all RCP scenarios. At the same time, the consequent warming effects from reduced aerosols are also significant and inevitable.

Observation-based estimation of aerosol-induced reduction of planetary boundary layer height

NASA Astrophysics Data System (ADS)

Zou, Jun; Sun, Jianning; Ding, Aijun; Wang, Minghuai; Guo, Weidong; Fu, Congbin

2017-09-01

Radiative aerosols are known to influence the surface energy budget and hence the evolution of the planetary boundary layer. In this study, we develop a method to estimate the aerosol-induced reduction in the planetary boundary layer height (PBLH) based on two years of ground-based measurements at a site, the Station for Observing Regional Processes of the Earth System (SORPES), at Nanjing University, China, and radiosonde data from the meteorological station of Nanjing. The observations show that increased aerosol loads lead to a mean decrease of 67.1 W m-2 for downward shortwave radiation (DSR) and a mean increase of 19.2 W m-2 for downward longwave radiation (DLR), as well as a mean decrease of 9.6 Wm-2 for the surface sensible heat flux (SHF) in the daytime. The relative variations of DSR, DLR and SHF are shown as a function of the increment of column mass concentration of particulate matter (PM2.5). High aerosol loading can significantly increase the atmospheric stability in the planetary boundary layer during both daytime and nighttime. Based on the statistical relationship between SHF and PM2.5 column mass concentrations, the SHF under clean atmospheric conditions (same as the background days) is derived. In this case, the derived SHF, together with observed SHF, are then used to estimate changes in the PBLH related to aerosols. Our results suggest that the PBLH decreases more rapidly with increasing aerosol loading at high aerosol loading. When the daytime mean column mass concentration of PM2.5 reaches 200 mg m-2, the decrease in the PBLH at 1600 LST (local standard time) is about 450 m.

Concentration and characterization of airborne particles in Tehran's subway system.

PubMed

Kamani, Hosein; Hoseini, Mohammad; Seyedsalehi, Mahdi; Mahdavi, Yousef; Jaafari, Jalil; Safari, Gholam Hosein

2014-06-01

Particulate matter is an important air pollutant, especially in closed environments like underground subway stations. In this study, a total of 13 elements were determined from PM10 and PM2.5 samples collected at two subway stations (Imam Khomeini and Sadeghiye) in Tehran's subway system. Sampling was conducted in April to August 2011 to measure PM concentrations in platform and adjacent outdoor air of the stations. In the Imam Khomeini station, the average concentrations of PM10 and PM2.5 were 94.4 ± 26.3 and 52.3 ± 16.5 μg m(-3) in the platform and 81.8 ± 22.2 and 35 ± 17.6 μg m(-3) in the outdoor air, respectively. In the Sadeghiye station, mean concentrations of PM10 and PM2.5 were 87.6 ± 23 and 41.3 ± 20.4 μg m(-3) in the platform and 73.9 ± 17.3 and 30 ± 15 μg m(-3), in the outdoor air, respectively. The relative contribution of elemental components in each particle fraction were accounted for 43% (PM10) and 47.7% (PM2.5) in platform of Imam Khomeini station and 15.9% (PM10) and 18.5% (PM2.5) in the outdoor air of this station. Also, at the Sadeghiye station, each fraction accounted for 31.6% (PM10) and 39.8% (PM2.5) in platform and was 11.7% (PM10) and 14.3% (PM2.5) in the outdoor. At the Imam Khomeini station, Fe was the predominant element to represent 32.4 and 36 % of the total mass of PM10 and PM2.5 in the platform and 11.5 and 13.3% in the outdoor, respectively. At the Sadeghiye station, this element represented 22.7 and 29.8% of total mass of PM10 and PM2.5 in the platform and 8.7 and 10.5% in the outdoor air, respectively. Other major crustal elements were 5.8% (PM10) and 5.3% (PM2.5) in the Imam Khomeini station platform and 2.3 and 2.4% in the outdoor air, respectively. The proportion of other minor elements was significantly lower, actually less than 7% in total samples, and V was the minor concentration in total mass of PM10 and PM2.5 in both platform stations.

Fine particulate (PM2.5) dynamics during rapid urbanization in Beijing, 1973–2013

PubMed Central

Han, Lijian; Zhou, Weiqi; Li, Weifeng

2016-01-01

PM2.5 has been given special concern in recent years when the air quality monitoring station started recording. However, long-term PM2.5 concentration dynamic analysis cannot be taken with the limited observations. We therefore estimated the PM2.5 concentration using meteorological visibility data in Beijing. We found that 71 ± 17% of PM10 were PM2.5, which contributed to visibility impairment (y = 332.26e−0.232x; R2 = 0.75, P < 0.05). We then reconstructed a time series of annual PM2.5 from 1973 to 2013, and examined its relationship with urbanization by indicators of population, gross domestic production (GDP), energy consumption, and number of vehicles. Concluded that 1) Meteorological conditions were not the major cause of PM2.5 increase from 1973 to 2013; 2) With population and GDP growth, PM2.5 increased significantly (R2 = 0.5917, P < 0.05; R2 = 0.5426, P < 0.05); 3) Intensive human activity could change air quality in a short period, as observed changes in the correlations of PM2.5 concentration with energy consumption and number of vehicles before and after 2004, respectively. The success of this research provides an easy way in reconstructing long-term PM2.5 concentration with limited PM2.5 observation and meteorological visibility, and insight the impact of urbanization on air quality. PMID:27031598

Benzo(a)pyrene parallel measurements in PM1 and PM2.5 in the coastal zone of the Gulf of Gdansk (Baltic Sea) in the heating and non-heating seasons.

PubMed

Lewandowska, Anita Urszula; Staniszewska, Marta; Witkowska, Agnieszka; Machuta, Magdalena; Falkowska, Lucyna

2018-05-05

Parallel measurements of PM 1 and PM 2.5 aerosols were conducted in the urbanized coastal zone of the southern Baltic Sea. The main aim of the research was to assess and determine annual, seasonal (heating and non-heating), and daily concentration variability of benzo(a)pyrene in aerosols, these being the most dangerous constituents to human health. The average annual concentration of benzo(a)pyrene (B(a)P) was equal to 2.6 ng·m -3 in PM 1 and 4.6 ng·m -3 in PM 2.5 , and both values were several times higher than the level of 1 ng·m -3 which was set out in the CAFE Directive. High mean daily concentrations of B(a)P persisted for 50 and 65% of the study period in PM1 and PM2.5, respectively. In order to determine the sources of B(a)P in both aerosol fractions, organic (OC) and elemental (EC) carbon concentrations were examined. The highest concentrations of all carbon species were reported during the heating season under local or regional land advection and at low air temperatures. The origin of pollutants was the same and was primarily related to the combustion of fossil fuels in the communal-utility sector. During the non-heating period, the role of transportation, both land and marine, increased and may have been significant in creating higher concentrations of carbon compounds in PM 1 and PM 2.5 . Regardless of the size of the aerosol fractions, B(a)P loads introduced into the Baltic coastal zone were several times higher during the heating period compared to the non-heating season. Graphical abstract ᅟ.

Finely Resolved On-Road PM2.5 and Estimated Premature Mortality in Central North Carolina.

PubMed

Chang, Shih Ying; Vizuete, William; Serre, Marc; Vennam, Lakshmi Pradeepa; Omary, Mohammad; Isakov, Vlad; Breen, Michael; Arunachalam, Saravanan

2017-12-01

To quantify the on-road PM 2.5 -related premature mortality at a national scale, previous approaches to estimate concentrations at a 12-km × 12-km or larger grid cell resolution may not fully characterize concentration hotspots that occur near roadways and thus the areas of highest risk. Spatially resolved concentration estimates from on-road emissions to capture these hotspots may improve characterization of the associated risk, but are rarely used for estimating premature mortality. In this study, we compared the on-road PM 2.5 -related premature mortality in central North Carolina with two different concentration estimation approaches-(i) using the Community Multiscale Air Quality (CMAQ) model to model concentration at a coarser resolution of a 36-km × 36-km grid resolution, and (ii) using a hybrid of a Gaussian dispersion model, CMAQ, and a space-time interpolation technique to provide annual average PM 2.5 concentrations at a Census-block level (∼105,000 Census blocks). The hybrid modeling approach estimated 24% more on-road PM 2.5 -related premature mortality than CMAQ. The major difference is from the primary on-road PM 2.5 where the hybrid approach estimated 2.5 times more primary on-road PM 2.5 -related premature mortality than CMAQ due to predicted exposure hotspots near roadways that coincide with high population areas. The results show that 72% of primary on-road PM 2.5 premature mortality occurs within 1,000 m from roadways where 50% of the total population resides, highlighting the importance to characterize near-road primary PM 2.5 and suggesting that previous studies may have underestimated premature mortality due to PM 2.5 from traffic-related emissions. © 2017 Society for Risk Analysis.

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).

Estimating regional spatial and temporal variability of PM(2.5) concentrations using satellite data, meteorology, and land use information.

PubMed

Liu, Yang; Paciorek, Christopher J; Koutrakis, Petros

2009-06-01

Studies of chronic health effects due to exposures to particulate matter with aerodynamic diameters

Apportionment of the sources of high fine particulate matter concentration events in a developing aerotropolis in Taoyuan, Taiwan.

PubMed

Chuang, Ming-Tung; Chen, Yu-Chieh; Lee, Chung-Te; Cheng, Chung-Hao; Tsai, Yu-Jen; Chang, Shih-Yu; Su, Zhen-Sen

2016-07-01

To investigate the characteristics and contributions of the sources of fine particulate matter with a size of up to 2.5 μm (PM2.5) during the period when pollution events could easily occur in Taoyuan aerotropolis, Taiwan, this study conducted sampling at three-day intervals from September 2014 to January 2015. Based on the mass concentration of PM2.5, the sampling days were classified into high PM2.5 concentration event days (PM2.5>35 μg m(-3)) and non-event days (PM2.5<35 μg m(-3)). In addition, the chemical species, including water-soluble inorganic ions, carbonaceous components, and metal elements, were analyzed. The sources of pollution and their contributions were estimated using the positive matrix factorization (PMF) model. Furthermore, the effect of the weather type on the measurement results was also explored based on wind field conditions. The mass fractions of Cl(-) and NO3(-) increased when a high PM2.5 concentration event occurred, and they were also higher under local emitted conditions than under long range transported conditions, indicating that secondary nitrate aerosols were the major increasing local species that caused high PM2.5 concentration events. Seven sources of pollution could be distinguished using the PMF model on the basis of the characteristics of the species. Industrial emissions, coal combustion/urban waste incineration, and local emissions from diesel/gasoline vehicles were the main sources that contributed to pollution on high PM2.5 concentration event days. In order to reduction of high PM2.5 concentration events, the control of diesel and gasoline vehicle emission is important and should be given priority. Copyright © 2016 Elsevier Ltd. All rights reserved.

Increase in dust storm related PM10 concentrations: A time series analysis of 2001-2015.

PubMed

Krasnov, Helena; Katra, Itzhak; Friger, Michael

2016-06-01

Over the last decades, changes in dust storms characteristics have been observed in different parts of the world. The changing frequency of dust storms in the southeastern Mediterranean has led to growing concern regarding atmospheric PM10 levels. A classic time series additive model was used in order to describe and evaluate the changes in PM10 concentrations during dust storm days in different cities in Israel, which is located at the margins of the global dust belt. The analysis revealed variations in the number of dust events and PM10 concentrations during 2001-2015. A significant increase in PM10 concentrations was identified since 2009 in the arid city of Beer Sheva, southern Israel. Average PM10 concentrations during dust days before 2009 were 406, 312, and 364 μg m(-3) (median 337, 269,302) for Beer Sheva, Rehovot (central Israel) and Modi'in (eastern Israel), respectively. After 2009 the average concentrations in these cities during dust storms were 536, 466, and 428 μg m(-3) (median 382, 335, 338), respectively. Regression analysis revealed associations between PM10 variations and seasonality, wind speed, as well as relative humidity. The trends and periodicity are stronger in the southern part of Israel, where higher PM10 concentrations are found. Since 2009 dust events became more extreme with much higher daily and hourly levels. The findings demonstrate that in the arid area variations of dust storms can be quantified easier through PM10 levels over a relatively short time scale of several years. Copyright © 2015 Elsevier Ltd. All rights reserved.

Factors controlling air quality in different European subway systems.

PubMed

Martins, Vânia; Moreno, Teresa; Mendes, Luís; Eleftheriadis, Konstantinos; Diapouli, Evangelia; Alves, Célia A; Duarte, Márcio; de Miguel, Eladio; Capdevila, Marta; Querol, Xavier; Minguillón, María Cruz

2016-04-01

Sampling campaigns using the same equipment and methodology were conducted to assess and compare the air quality at three South European subway systems (Barcelona, Athens and Oporto), focusing on concentrations and chemical composition of PM2.5 on subway platforms, as well as PM2.5 concentrations inside trains. Experimental results showed that the mean PM2.5 concentrations widely varied among the European subway systems, and even among different platforms within the same underground system, which might be associated to distinct station and tunnel designs and ventilation systems. In all cases PM2.5 concentrations on the platforms were higher than those in the urban ambient air, evidencing that there is generation of PM2.5 associated with the subway systems operation. Subway PM2.5 consisted of elemental iron, total carbon, crustal matter, secondary inorganic compounds, insoluble sulphate, halite and trace elements. Of all metals, Fe was the most abundant, accounting for 29-43% of the total PM2.5 mass (41-61% if Fe2O3 is considered), indicating the existence of an Fe source in the subway system, which could have its origin in mechanical friction and wear processes between rails, wheels and brakes. The trace elements with the highest enrichment in the subway PM2.5 were Ba, Cu, Mn, Zn, Cr, Sb, Sr, Ni, Sn, Co, Zr and Mo. Similar PM2.5 diurnal trends were observed on platforms from different subway systems, with higher concentrations during subway operating hours than during the transport service interruption, and lower levels on weekends than on weekdays. PM2.5 concentrations depended largely on the operation and frequency of the trains and the ventilation system, and were lower inside the trains, when air conditioning system was operating properly, than on the platforms. However, the PM2.5 concentrations increased considerably when the train windows were open. The PM2.5 levels inside the trains decreased with the trains passage in aboveground sections. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

[Study on transition metals in airborne particulate matter in Shanghai city's subway].

PubMed

Bao, Liang-Man; Lei, Qian-Tao; Tan, Ming-Guang; Li, Xiao-Lin; Zhang, Gui-Lin; Liu, Wei; Li, Yan

2014-06-01

PM10 and PM2.5 aerosol particle samples were collected at a subway station in Shanghai and their morphology, chemical composition and transition metal species were studied. The mass concentrations of PM10 and PM2.5 inside the subway station were significantly higher than those measured in aboveground ambient air. The PM levels inside subway were much higher than the state control limit. The aerosol composition in the metro station was quite different from that of the aboveground urban particles. Concentrations of Fe, Mn and Cr were higher than the averages of aboveground urban air particles by factors of 8, 2, and 2, respectively, showing a substantial enrichment in subway. Scanning electron microscope (SEM) analysis showed that the subway particles had flat surfaces in combination with parallel scratches and sharp edges and looked like metal sheets or flakes. Furthermore, analysis of the atomic composition of typical subway particles by energy dispersive X-Ray (EDX) spectroscopy showed that oxygen and iron dominated the mass of the particles. The X-ray absorption near-edge structure (XANES) spectroscopy results showed that a fraction (> 26%) of the total iron in the PM10 was in the form of pure Fe, while in the street particles Fe(III) was shown to be a significant fraction of the total iron. The work demonstrated that the underground subway stations in Shanghai were an important microenvironment for exposure to transition metal aerosol for the people taking subway train for commuting every day and those who work in the subway stations, and the metal particle exposure for people in the subway station should not be ignored.

Seasonality of Aerosols the Southeastern United States

NASA Astrophysics Data System (ADS)

Ford, B. J.; Heald, C. L.

2012-12-01

Previous studies have suggested that increases in atmospheric aerosols of biogenic origin may have caused regional cooling over the southeastern United States in recent decades. Understanding the sources and behaviors of these aerosols is important for determining their role in a changing climate and managing their air quality impacts. In this study, we investigate the strong seasonality in aerosol optical depth (AOD) observed by MODIS, MISR, and CALIOP instruments over the southeastern United States and show that this is not simulated by a chemical transport model (GEOS-Chem). However, the model does reproduce surface PM 2.5 concentrations in the region as reported by the IMPROVE and Southeastern Aerosol Research and Characterization (SEARCH) networks, as well as the muted seasonality of these concentrations. In addition, these surface measurements show that organic aerosol makes up a small fraction of total PM 2.5 and has relatively little seasonality, which calls into question the importance of biogenic aerosol as a driver for climate change in the region. Sounding profiles and ground observations of relative humidity suggest that the magnitude of seasonality in AOD cannot be explained by seasonal differences in the hygroscopic growth of aerosols. CALIOP measurements of the vertical profile of aerosol extinction confirm that the likely reconciliation of the differences in seasonality between the surface PM 2.5 and AOD observations is the formation of aerosol aloft, a process not captured by the model. These findings provide initial insights for the Southern Oxidant and Aerosol Study (SOAS) campaign in 2013 which aims to investigate the anthropogenic influence on biogenic aerosol formation in the Southeastern US and elucidate the impact on regional climate and air quality.

Particulate matter in the indoor air of classrooms—exploratory results from Munich and surrounding area

NASA Astrophysics Data System (ADS)

Fromme, H.; Twardella, D.; Dietrich, S.; Heitmann, D.; Schierl, R.; Liebl, B.; Rüden, H.

Numerous epidemiological studies have demonstrated the association between particle mass (PM) concentration in outside air and the occurrence of health related problems and/or diseases. However, much less is known about indoor PM concentrations and associated health risks. In particular, data are needed on air quality in schools, since children are assumed to be more vulnerable to health hazards and spend a large part of their time in classrooms. On this background, we evaluated indoor air quality in 64 schools in the city of Munich and a neighbouring district outside the city boundary. In winter 2004-2005 in 92 classrooms, and in summer 2005 in 75 classrooms, data on indoor air climate parameters (temperature, relative humidity), carbon dioxide (CO 2) and various dust particle fractions (PM 10, PM 2.5) were collected; for the latter both gravimetrical and continuous measurements by laser aerosol spectrometer (LAS) were implemented. In the summer period, the particle number concentration (PNC), was determined using a scanning mobility particle sizer (SMPS). Additionally, data on room and building characteristics were collected by use of a standardized form. Only data collected during teaching hours were considered in analysis. For continuously measured parameters the daily median was used to describe the exposure level in a classroom. The median indoor CO 2 concentration in a classroom was 1603 ppm in winter and 405 ppm in summer. With LAS in winter, median PM concentrations of 19.8 μg m -3 (PM 2.5) and 91.5 μg m -3 (PM 10) were observed, in summer PM concentrations were significantly reduced (median PM 2.5=12.7 μg m -3, median PM 10=64.9 μg m -3). PM 2.5 concentrations determined by the gravimetric method were in general higher (median in winter: 36.7 μg m -3, median in summer: 20.2 μg m -3) but correlated strongly with the LAS-measured results. In explorative analysis, we identified a significant increase of LAS-measured PM 2.5 by 1.7 μg m -3 per increase in humidity by 10%, by 0.5 μg m -3 per increase in CO 2 indoor concentration by 100 ppm, and a decrease by 2.8 μg m -3 in 5-7th grade classes and by 7.3 μg m -3 in class 8-11 compared to 1-4th class. During the winter period, the associations were stronger regarding class level, reverse regarding humidity (a decrease by 6.4 μg m -3 per increase in 10% humidity) and absent regarding CO 2 indoor concentration. The median PNC measured in 36 classrooms ranged between 2622 and 12,145 particles cm -3 (median: 5660 particles cm -3). The results clearly show that exposure to particulate matter in school is high. The increased PM concentrations in winter and their correlation with high CO 2 concentrations indicate that inadequate ventilation plays a major role in the establishment of poor indoor air quality. Additionally, the increased PM concentration in low level classes and in rooms with high number of pupils suggest that the physical activity of pupils, which is assumed to be more pronounced in younger children, contributes to a constant process of resuspension of sedimented particles. Further investigations are necessary to increase knowledge on predictors of PM concentration, to assess the toxic potential of indoor particles and to develop and test strategies how to ensure improved indoor air quality in schools.

Assessment of annual air pollution levels with PM1, PM2.5, PM10 and associated heavy metals in Algiers, Algeria.

PubMed

Talbi, Abdelhamid; Kerchich, Yacine; Kerbachi, Rabah; Boughedaoui, Ménouèr

2018-01-01

Concentrations of particulate matter less than 1  μm, 2.5  μm, 10 μm and their contents of heavy metals were investigated in two different stations, urban and roadside at Algiers (Algeria). Sampling was conducted during two years by a high volume samplers (HVS) equipped with a cascade impactor at four levels stage, for one year sampling. The characterization of the heavy metals associated to the particulate matter (PM) was carried out by X-Ray Fluorescence analysis (XRF). The annual average concentration of PM 1 , PM 2.5 and PM 10 in both stations were 18.24, 32.23 and 60.01 μg m -3 respectively. The PM 1 , PM 2.5 and PM 10 concentrations in roadside varied from 13.46 to 25.59 μg m -3 , 20.82-49.85 μg m -3 and 45.90-77.23 μg m -3 respectively. However in the urban station, the PM 1 , PM 2.5 and PM 10 concentrations varied from 10.45 to 26.24 μg m -3 , 18.53-47.58 μg m -3 and 43.8-91.62 μg m -3 . The heavy metals associated to the PM were confirmed by Scanning Electron Microscopy-Energy Dispersive X-Ray analyses (SEM-EDX). The different spots of PM 2.5 analysis by SEM-EDX shows the presence of nineteen elements with anthropogenic and natural origins, within the heavy metal detected, the lead was found with maximum of 5% (weight percent). In order to determine the source contributions of PM levels at the two sampling sites sampling, principal compound analysis (PCA) was applied to the collected data. Statistical analysis confirmed anthropogenic source with traffic being a significant source and high contribution of natural emissions. At both sites, the PM 2.5 /PM 10 ratio is lower than that usually recorded in developed countries. The study of the back-trajectories of the air masses starting from Sahara shows that desert dust influences the concentration and the composition of the PM measured in Algiers. Copyright © 2017 Elsevier Ltd. All rights reserved.

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).

PM4 crystalline silica emission factors and ambient concentrations at aggregate-producing sources in California.

PubMed

Richards, John R; Brozell, Todd T; Rea, Charles; Boraston, Geoff; Hayden, John

2009-11-01

The California Construction and Industrial Minerals Association and the National Stone, Sand, & Gravel Association have sponsored tests at three sand and gravel plants in California to compile crystalline silica emission factors for particulate matter (PM) of aerodynamic diameter of 4 microm or less (PM4) and ambient concentration data. This information is needed by industrial facilities to evaluate compliance with the Chronic Reference Exposure Level (REL) for ambient crystalline silica adopted in 2005 by the California Office of Environmental Health Hazard Assessment. The REL applies to PM4 respirable PM. Air Control Techniques, P.C. sampled for PM4 crystalline silica using a conventional sampler for PM of aerodynamic diameter of 2.5 microm or less (PM2.5), which met the requirements of 40 Code of Federal Regulations Part 50, Appendix L. The sample flow rate was adjusted to modify the 50% cut size to 4 microm instead of 2.5 microm. The filter was also changed to allow for crystalline silica analyses using National Institute for Occupational Safety and Health (NIOSH) Method 7500. The particle size-capture efficiency curve for the modified Appendix L instrument closely matched the performance curve of NIOSH Method 0600 for PM4 crystalline silica and provided a minimum detection limit well below the levels attainable with NIOSH Method 0600. The results of the tests indicate that PM4 crystalline silica emissions range from 0.000006 to 0.000110 lb/t for screening operations, tertiary crushers, and conveyor transfer points. The PM4 crystalline silica emission factors were proportional to the crystalline silica content of the material handled in the process equipment. Measured ambient concentrations ranged from 0 (below detectable limit) to 2.8 microg/m3. All values measured above 2 microg/m3 were at locations upwind of the facilities being tested. The ambient PM4 crystalline silica concentrations measured during this study were below the California REL of 3 microg/m3. The measured ambient concentrations in the PM4 size range are consistent with previously published ambient crystalline silica data applicable to the PM2.5 and PM of aerodynamic diameter of 10 microm or less (PM10) size ranges.

Spatio-temporal characteristics of PM10 concentration across Malaysia

NASA Astrophysics Data System (ADS)

Juneng, Liew; Latif, Mohd Talib; Tangang, Fredolin T.; Mansor, Haslina

The recurrence of forest fires in Southeast Asia and associated biomass burning, has contributed markedly to the problem of trans-boundary haze and the long-range movement of pollutants in the region. Air pollutants, specifically particulate matter in the atmosphere, have received extensive attention, mainly because of their adverse effect on people's health. In this study, the spatial and temporal variability of the PM10 concentration across Malaysia was analyzed by means of the rotated principal component analysis. The results suggest that the variability of the PM10 concentration can be decomposed into four dominant modes, each characterizing different spatial and temporal variations. The first mode characterizes the southwest coastal region of the Malaysian Peninsular with the PM10 showing a peak concentration during the summer monsoon i.e. when the winds are predominantly southerlies or southwesterlies, and a minimal concentration during the winter monsoon. The second mode features the region of western Borneo with the PM10 exhibiting a concentration surge in August-September, which is likely to be the result of the northward shift of the Inter Tropical Convergence Zone (ITCZ) and the subsequent rapid arrival of the rainy season. The third mode delineates the northern region of the Malaysian Peninsular with strong bimodality in the PM10 concentration. Seasonally, this component exhibits two concentration maxima during the late winter and summer monsoons, as well as two minima during the inter-monsoon periods. The fourth dominant mode characterizes the northern Borneo region which exhibits weaker seasonality of the PM10 concentration. Generally, the seasonal fluctuation of the PM10 concentration is largely associated with the seasonal variation of rainfall in the country. However, in addition to this, the PM10 concentration also fluctuates markedly in two timescale bands i.e. 10-20 days quasi-biweekly (QBW) and 30-60 days lower frequency (LF) band of the intra-seasonal timescales. These intra-seasonal fluctuations show strong seasonality with the largest fraction of variance occurring during the boreal summer and the weakest variance during the winter. Generally, the LF intra-seasonal oscillation is stronger compared to the QBW intra-seasonal band.

Magnetic and SEM-EDS analyses of Tilia cordata leaves and PM10 filters as a complementary source of information on polluted air: Results from the city of Parma (Northern Italy).

PubMed

Mantovani, Luciana; Tribaudino, Mario; Solzi, Massimo; Barraco, Vera; De Munari, Eriberto; Pironi, Claudia

2018-08-01

In this work, both PM 10 filters and leaves have been collected, on a daily basis, over a period of five months and compared systematically. Filters were taken from an air-quality monitoring station and leaves from two Tilia cordata trees, both located near the railway station of Parma. SEM-EDS analysis on the surface and across the leaves shows that magnetic particles are almost entirely made of magnetite, and that they are found invariably on the leaves surface. The saturation isothermal magnetic remanence (SIRM) shows that for both filters and leaves the magnetic fraction mainly consists of a low coercivity, magnetite-like phase. The magnetic signals of filter and leaves and atmospheric PM concentrations are compared. The correlation is better for filters, mostly with parameters related to vehicular pollution, and improved for both filters and leaves once data were averaged on a 10 days basis. Filters and leaves equally show an increase in magnetic signal during the fall-winter period together with PM 10 content. The comparison between leaves and filters shows that: 1) leaves give a qualitative picture, and in our case they could be used as environmental proxies after averaging the results over multiple days; 2) the correlation with PM 10 is weaker, indicating that there is a PM 10 contribution from non-magnetic particles, like calcite and clay minerals, pollen and spores; 3) multidomain particles contribution from filters indicates a strong relation with vehicular polluters, suggesting the important role of larger particles; 4) magnetization from leaves and filters are weakly related, due to the different sampling lapse. Copyright © 2018 Elsevier Ltd. All rights reserved.

Assessment of Population and Microenvironmental Exposure to Fine Particulate Matter (PM2.5)

NASA Astrophysics Data System (ADS)

Jiao, Wan

A positive relationship exists between fine particulate matter (PM 2.5) exposure and adverse health effects. PM2.5 concentration-response functions used in the quantitative risk assessment were based on findings from human epidemiological studies that relied on areawide ambient concentrations as surrogate for actual ambient exposure, which cannot capture the spatial and temporal variability in human exposures. The goal of the study is to assess inter-individual, geographic and seasonal variability in population exposures to inform the interpretation of available epidemiological studies, and to improve the understanding of how exposure-related factors in important exposure microenvironments contribute to the variability in individual PM2.5 exposure. Typically, the largest percentage of time in which an individual is exposed to PM2.5 of ambient origin occurs in indoor residence, and the highest ambient PM2.5 concentrations occur in transportation microenvironments because of the proximity to on-road traffic emissions. Therefore, indoor residence and traffic-related transportation microenvironments were selected for further assessment in the study. Population distributions of individual daily PM2.5 exposures were estimated for the selected regions and seasons using the Stochastic Human Exposure and Dose Simulation Model for Particulate Matter (SHEDS-PM). For the indoor residence, the current practice by assuming the entire residence to be one large single zone for calculating the indoor residential PM 2.5 concentration was evaluated by applying an indoor air quality model, RISK, to compare indoor PM2.5 concentrations between single-zone and multi-zone scenarios. For the transportation microenvironments, one field data collection focused on in-vehicle microenvironment and was conducted to quantify the variability in the in-vehicle PM2.5 concentration with respect to the outside vehicle concentration for a wide range of conditions that affect intra-vehicle variability in exposure concentration, including ventilation air source, window status, fan setting, AC utilization, vehicle speed, road type, travel direction, and time of day. Another field data collection measured PM2.5 exposure concentrations on pre-selected routes across transportation modes of pedestrian, bus, and car to quantify the variability in the transportation mode concentration ratios, and identify factors affecting variability in traffic-related concentrations. In general, population daily average exposure to ambient PM2.5 is less than the ambient concentration by approximately half. The ratio of PM2.5 ambient exposure to ambient concentration (Ea/C) varies by individual, geographic area and season, as a result of regional differences in housing stock and seasonal differences in air exchange rates (ACH). For the indoor residence, the single-zone assumption is biased when any non-ambient source is presented. Bias correction factors are developed for cooking and smoking scenarios, separately, to improve the concentration estimates. Correction factors are most sensitive to changes in ACH but relatively insensitive to variations in source emission rate and duration. In a SHEDS-PM case study, the population daily average total exposure increased by 17% after applying correction factors. Transportation mode exposure concentrations are sensitive to mode, and are affected by factors such as vehicle ventilation and proximity to on-road emission sources. The in-vehicle to outside vehicle concentration (I/O) ratio is highly sensitive to whether windows are open or, for closed windows, to whether fresh air or recirculating air is used. Both model simulations and field studies are needed to inform better understanding of human exposure. Exposure, and not just concentration, should be considered in developing risk management strategies to reduce uncertainty in health effect estimates, and to identify highly exposed groups and possible exposure reduction strategies.

Characterization of PM 2.5 and selected gas-phase compounds at multiple indoor and outdoor sites in Mira Loma, California

NASA Astrophysics Data System (ADS)

Sawant, Aniket A.; Na, Kwangsam; Zhu, Xiaona; Cocker, Kathalena; Butt, Sheraz; Song, Chen; Cocker, David R.

Fine particulate matter (PM 2.5) and gas-phase carbonyls are categories of atmospheric pollutants that have components known to adversely affect human health. This work describes the chemical characterization of PM 2.5 and 13 carbonyl compounds measured inside 20 residences and 7 schoolrooms in Mira Loma, western Riverside County, California. Median PM 2.5 concentrations were 32.2 and 13.2 μg m -3, while median total carbonyl concentrations were 50.8 and 62.9 μg m -3 inside the residences and schoolrooms, respectively. Organic carbon was typically the largest contributor to indoor PM 2.5 concentrations, while formaldehyde, acetaldehyde and acetone were the largest contributors to gas-phase carbonyl concentrations. Indoor/outdoor ratios for PM 2.5 were greater for residences than for schoolrooms, while the reverse was true for these ratios for gas-phase carbonyls. These results are likely due to effective PM 2.5 removal by filtration on the HVAC and the presence of more significant indoor carbonyl sources within the schoolrooms. Regression analysis of indoor and outdoor pollutant concentrations showed that for PM 2.5, sulfate and nitrate were the best- and worst-correlated species, respectively. This suggests that nitrate is a poor tracer for outdoor-to-indoor PM 2.5 transfer. In addition, no significant correlations were observed for any of the carbonyl compounds measured. This further suggests the presence of indoor carbonyl sources inside the schoolrooms, and that indoor air quality especially in terms of carbonyl concentrations may be substantially poorer than outdoor air quality.

Modeling study of PM2.5 concentration change in Beijing-Tianjin-Hebei and Chengdu-Chongqing urban clusters

NASA Astrophysics Data System (ADS)

Wang, Y.; Chen, H.; Wu, Q.; Wang, Z.

2016-12-01

With the rapid economic development, air pollution is becoming more and more serious in China. Fine particulate matter (PM2.5) is one of major air pollution, affecting visibility and human health. In this study, a nested grid air quality model system (NAQPMS) was used to simulate PM2.5 during 2013-2015 in high resolution of 5km in China. Comparison with observations proved that NAQPMS was able to reproduce the temporal and spatial variation of pollutants in China, reasonably. The simulation showed that high levels of PM2.5 concentrated in the mid-eastern and Sichuan Basin, the concentration in the heaviest period was 120μg/m³ . This study focused on the Beijing-Tianjin-Hebei (BTH) and Chengdu-Chongqi urban clusters, the simulation was a little lower in Jing-Jin-Ji region, high concentration of PM2.5 concentrated in south of Hebei, and PM2.5 concentration in this region have gradually decreased over past three years, the best simulation result was 2014 in Beijing (R=0.75). However, the simulation was a bit higher in Chengdu-Chongqi urban cluster, high concentration concentrated in mid-eastern of Sichuan Basin, R increased obviously in 2015 (0.60). More detailed information and a possible cause for this discrepancy will be discussed.

Study of traffic-related pollutant removal from street canyon with trees: dispersion and deposition perspective.

PubMed

Morakinyo, Tobi Eniolu; Lam, Yun Fat

2016-11-01

Numerical experiments involving street canyons of varying aspect ratio with traffic-induced pollutants (PM 2.5 ) and implanted trees of varying aspect ratio, leaf area index, leaf area density distribution, trunk height, tree-covered area, and tree planting pattern under different wind conditions were conducted using a computational fluid dynamics (CFD) model, ENVI-met. Various aspects of dispersion and deposition were investigated, which include the influence of various tree configurations and wind condition on dispersion within the street canyon, pollutant mass at the free stream layer and street canyon, and comparison between mass removal by surface (leaf) deposition and mass enhancement due to the presence of trees. Results revealed that concentration level was enhanced especially within pedestrian level in street canyons with trees relative to their tree-free counterparts. Additionally, we found a dependence of the magnitude of concentration increase (within pedestrian level) and decrease (above pedestrian level) due to tree configuration and wind condition. Furthermore, we realized that only ∼0.1-3 % of PM 2.5 was dispersed to the free stream layer while a larger percentage (∼97 %) remained in the canyon, regardless of its aspect ratio, prevailing wind condition, and either tree-free or with tree (of various configuration). Lastly, results indicate that pollutant removal due to deposition on leaf surfaces is potentially sufficient to counterbalance the enhancement of PM 2.5 by such trees under some tree planting scenarios and wind conditions.

Ion-channel genosensor for the detection of specific DNA sequences derived from Plum Pox Virus in plant extracts.

PubMed

Malecka, Kamila; Michalczuk, Lech; Radecka, Hanna; Radecki, Jerzy

2014-10-09

A DNA biosensor for detection of specific oligonucleotides sequences of Plum Pox Virus (PPV) in plant extracts and buffer is proposed. The working principles of a genosensor are based on the ion-channel mechanism. The NH2-ssDNA probe was deposited onto a glassy carbon electrode surface to form an amide bond between the carboxyl group of oxidized electrode surface and amino group from ssDNA probe. The analytical signals generated as a result of hybridization were registered in Osteryoung square wave voltammetry in the presence of [Fe(CN)6]3-/4- as a redox marker. The 22-mer and 42-mer complementary ssDNA sequences derived from PPV and DNA samples from plants infected with PPV were used as targets. Similar detection limits of 2.4 pM (31.0 pg/mL) and 2.3 pM (29.5 pg/mL) in the concentration range 1-8 pM were observed in the presence of the 22-mer ssDNA and 42-mer complementary ssDNA sequences of PPV, respectively. The genosensor was capable of discriminating between samples consisting of extracts from healthy plants and leaf extracts from infected plants in the concentration range 10-50 pg/mL. The detection limit was 12.8 pg/mL. The genosensor displayed good selectivity and sensitivity. The 20-mer partially complementary DNA sequences with four complementary bases and DNA samples from healthy plants used as negative controls generated low signal.

The role of fog in haze episode in Tianjin, China: A case study for November 2015

NASA Astrophysics Data System (ADS)

Hao, Tianyi; Han, Suqin; Chen, Shucheng; Shan, Xiaolin; Zai, Ziying; Qiu, Xiaobin; Yao, Qing; Liu, Jingle; Chen, Jing; Meng, Lihong

2017-09-01

A severe haze episode that heavy fog appeared in its later stage emerged in Tianjin, east-central China, from November 27 to December 2, 2015. With meteorological data and pollutants monitoring data, the characteristics of this event and the role of fog in haze were investigated. During this process, the visibility was less than 600 m, especially in the haze and fog coexisting period (below 100 m). The peak value of PM2.5 mass concentration appeared in the haze only period was 446 μg/m3. The fog played a role in scavenging and removing PM2.5 during haze and fog coexisting period. The surface high humidity province can match well with the high PM2.5 concentration region in pollutants removal period. The fog top height was reduced to about 200 m by cold air. Although the cold air has arrived in Tianjin high altitude, the saturated layer below 200 m maintained for nearly 12 h. The heavy fog prevented the momentum in upper atmosphere from transmitting downward and caused the high altitude cold air difficult to reach the ground. The latent heat flux was transmitted upward ahead of sensible heat flux in pollutants removal period, indicating the increasing tendency of mechanical turbulence after fog dissipation. Turbulent kinetic energy (Etk) and the surface mean kinetic energy (E) also enhanced after fog dissipation. It demonstrates that the termination of haze was delayed by heavy fog.

Variations of emission characterization of PAHs emitted from different utility boilers of coal-fired power plants and risk assessment related to atmospheric PAHs.

PubMed

Wang, Ruwei; Liu, Guijian; Zhang, Jiamei

2015-12-15

Coal-fired power plants (CFPPs) represent important source of atmospheric PAHs, however, their emission characterization are still largely unknown. In this work, the concentration, distribution and gas-particle partitioning of PM10- and gas-phase PAHs in flue gas emitted from different coal-fired utility boilers were investigated. Moreover, concentration and distribution in airborne PAHs from different functional areas of power plants were studied. People's inhalatory and dermal exposures to airborne PAHs at these sites were estimated and their resultant lung cancer and skin cancer risks were assessed. Results indicated that the boiler capacity and operation conditions have significant effect on PAH concentrations in both PM10 and gas phases due to the variation of combustion efficiency, whereas they take neglected effect on PAH distributions. The wet flue gas desulphurization (WFGD) takes significant effect on the scavenging of PAH in both PM10 and gas phases, higher scavenging efficiency were found for less volatile PAHs. PAH partitioning is dominated by absorption into organic matter and accompanied by adsorption onto PM10 surface. In addition, different partitioning mechanism is observed for individual PAHs, which is assumed arising from their chemical affinity and vapor pressure. Risk assessment indicates that both inhalation and dermal contact greatly contribute to the cancer risk for CFPP workers and nearby residents. People working in workshop are exposed to greater inhalation and dermal exposure risk than people living in nearby vicinity and working office. Copyright © 2015. Published by Elsevier B.V.

No Smoke Without Fire: the hidden costs of early life exposure to landscape fire emissions in Indonesia

NASA Astrophysics Data System (ADS)

Jina, A.; Marlier, M. E.

2012-12-01

Air pollution from landscape fire emissions can have devastating effects upon public health. The consequent health costs place a burden upon the economies of many nations, particularly in developing countries. Recent research has assessed contemporaneous mortality due to respiratory infections or cardiovascular disease, but little has looked at the potential long-term consequences and hidden costs of exposure to fire pollution at a population scale. The difficulty of quantifying these costs is partly due to incomplete or inaccurate health data in many developing countries, and is further compounded by sparse air pollution monitoring data. While satellite data partially compensates for this, there can still be significant gaps in data availability and difficulty in retrieving surface concentrations. In this study, we demonstrate the dramatic long-term health and human development consequences of fine particulate matter (PM2.5) exposure by using modeled PM2.5 to quantify repeated exposure to landscape fire emissions in Indonesia, which is prone to large, catastrophic fires during El Niño conditions. Surface PM2.5 concentrations at 2x2.5° resolution are obtained from GISS-E2-Puccini (the new version of the NASA GISS ModelE general circulation model), run with monthly fire emissions from the Global Fire Emissions Database version 3 (GFED3). 24-hour ambient PM2.5 concentrations across Indonesia are matched to geographically and socioeconomically representative longitudinal surveys conducted by the Indonesian government. We find important medium- to long-term morbidity associated with early life exposure to ambient air pollution from fire emissions. Our analysis indicates that children exposed to high levels of PM2.5 in utero are more likely to suffer from impaired physical and cognitive development. A one standard deviation increase in ambient air pollution, derived from the GISS-E2-Puccini model, leads to effects that are directly comparable to those from indoor air pollution. In addition, income shocks due to pollution-caused family illness can lead to an antenatal amplification of these in utero effects. The impacts of exposure in early life can be difficult to reverse, leading to a persistent effects upon a society which may contribute a significant cost to the more readily demonstrated losses associated with immediate health impacts.

Exposure and toxicity assessment of ultrafine particles from nearby traffic in urban air in seoul, Korea.

PubMed

Yang, Ji-Yeon; Kim, Jin-Yong; Jang, Ji-Young; Lee, Gun-Woo; Kim, Soo-Hwan; Shin, Dong-Chun; Lim, Young-Wook

2013-01-01

We investigated the particle mass size distribution and chemical properties of air pollution particulate matter (PM) in the urban area and its capacity to induce cytotoxicity in human bronchial epithelial (BEAS-2B) cells. To characterize the mass size distributions and chemical concentrations associated with urban PM, PM samples were collected by a 10-stage Micro-Orifice Uniform Deposit Impactor close to nearby traffic in an urban area from December 2007 to December 2009. PM samples for in vitro cytotoxicity testing were collected by a mini-volume air sampler with PM10 and PM2.5 inlets. The PM size distributions were bi-modal, peaking at 0.18 to 0.32 and 1.8 to 3.2 µm. The mass concentrations of the metals in fine particles (0.1 to 1.8 µm) accounted for 45.6 to 80.4% of the mass concentrations of metals in PM10. The mass proportions of fine particles of the pollutants related to traffic emission, lead (80.4%), cadmium (69.0%), and chromium (63.8%) were higher than those of other metals. Iron was the dominant transition metal in the particles, accounting for 64.3% of the PM10 mass in all the samples. We observed PM concentration-dependent cytotoxic effects on BEAS-2B cells. We found that exposure to PM2.5 and PM10 from a nearby traffic area induced significant increases in protein expression of inflammatory cytokines (IL-6 and IL-8). The cell death rate and release of cytokines in response to the PM2.5 treatment were higher than those with PM10. The combined results support the hypothesis that ultrafine particles from vehicular sources can induce inflammatory responses related to environmental respiratory injury.

Seasonal progression of atmospheric particulate matter over an urban coastal region in peninsular India: Role of local meteorology and long-range transport

NASA Astrophysics Data System (ADS)

Mahapatra, P. S.; Sinha, P. R.; Boopathy, R.; Das, T.; Mohanty, S.; Sahu, S. C.; Gurjar, B. R.

2018-01-01

Measurement of particulate matter (PM) over an urban site with relatively high concentration of aerosol particles is critically important owing to its adverse health, environmental and climate impact. Here we present a 3 years' worth of measurements (January 2012 to December 2014) of PM2.5 (aerodynamic diameter of less than 2.5 μm) and PM10 (aerodynamic diameter of less than 10 μm) along with meteorological parameters and seasonal variations at Bhubaneswar an urban-coastal site, in eastern India. The concentrations of PM were determined gravimetrically from the filter samples of PM2.5 and PM10. It revealed remarkable seasonal variations with winter values (55.0 ± 23.4 μg/m3; 147.3 ± 42.4 μg/m3 for PM2.5 and PM10, respectively) about 3.5 times higher than that in pre-monsoon (15.7 ± 6.2 μg/m3; 41.8 ± 15.3 μg/m3). PM2.5 and PM10 were well correlated while PM2.5/PM10 ratios were found to be 0.38 and 0.32 during winter and pre-monsoon, indicating the predominance of coarse particles, mainly originating from long range transport of pollutants from northern and western parts of India and parts of west Asia as well. Concentration weighted trajectory (CWT) analysis revealed the IGP and North Western Odisha as the most potential sources of PM2.5 and PM10 during winter. The PM concentrations at Bhubaneswar were comparable with those at other coastal sites of India reported in the literature, but were lower than few polluted urban sites in India and Asia. Empirical model reproduced the observed seasonal variation of PM2.5 and PM10 very well over Bhubaneswar.

Evaluation of impacts of trees on PM2.5 dispersion in urban streets

NASA Astrophysics Data System (ADS)

Jin, Sijia; Guo, Jiankang; Wheeler, Stephen; Kan, Liyan; Che, Shengquan

2014-12-01

Reducing airborne particulate matter (PM), especially PM2.5 (PM with aerodynamic diameters of 2.5 μm or less), in urban street canyons is critical to the health of central city population. Tree-planting in urban street canyons is a double-edged sword, providing landscape benefits while inevitably resulting in PM2.5 concentrating at street level, thus showing negative environmental effects. Thereby, it is necessary to quantify the impact of trees on PM2.5 dispersion and obtain the optimum structure of street trees for minimizing the PM2.5 concentration in street canyons. However, most of the previous findings in this field were derived from wind tunnel or numerical simulation rather than on-site measuring data. In this study, a seasonal investigation was performed in six typical street canyons in the residential area of central Shanghai, which has been suffering from haze pollution while having large numbers of green streets. We monitored and measured PM2.5 concentrations at five heights, structural parameters of street trees and weather. For tree-free street canyons, declining PM2.5 concentrations were found with increasing height. However, in presence of trees the reduction rate of PM2.5 concentrations was less pronounced, and for some cases, the concentrations even increased at the top of street canyons, indicating tree canopies are trapping PM2.5. To quantify the decrease of PM2.5 reduction rate, we developed the attenuation coefficient of PM2.5 (PMAC). The wind speed was significantly lower in street canyons with trees than in tree-free ones. A mixed-effects model indicated that canopy density (CD), leaf area index (LAI), rate of change of wind speed were the most significant predictors influencing PMAC. Further regression analysis showed that in order to balance both environmental and landscape benefits of green streets, the optimum range of CD and LAI was 50%-60% and 1.5-2.0 respectively. We concluded by suggesting an optimized tree-planting pattern and discussing strategies for a better green streets planning and pruning.

Field assessment of the impacts of landscape structure on different-sized airborne particles in residential areas of Beijing, China

NASA Astrophysics Data System (ADS)

Fan, Shuxin; Li, Xiaopeng; Han, Jing; Cao, Yu; Dong, Li

2017-10-01

In high-density metropolis, residential areas are important human living environments. Aimed at investigating the impacts of landscape structure on the levels of different-sized airborne particle in residential areas, we conducted field monitoring of the levels of TSP, PM10, PM2.5 and PM1 using mobile traverses in 18 residential areas during the daytime in winter (Dec. 2015-Feb. 2016) and summer (Jun.-Aug. 2016) in Beijing, China. The net concentration differences (d) of the four-sized particles (dTSP, dPM10, dPM2.5 and dPM1) between residential environments and nearby corresponding urban backgrounds, which can be regarded as the reduction of particle concentration in residential environments, were calculated. The effects and relative contributions of different landscape structure parameters on these net concentration differences were further investigated. Results showed that the distribution of particle concentrations has great spatial variation in urban environments. Within the residential environment, there were overall lower concentrations of the four-sized particles compared with the nearby urban background. The net concentration differences of the four-sized particles were all significantly different among the 18 studied residential areas. The average dTSP, dPM10, dPM2.5 and dPM1 reached 18.92, 12.28, 2.01 and 0.53 μg/m3 in summer, and 9.91, 7.81, 1.39 and 0.38 μg/m3 in winter, respectively. The impacts and relative contribution of different landscape structure parameters on the reductions of TSP, PM10, PM2.5 and PM1 in residential environments differed and showed seasonal variation. Percentage of vegetation cover (PerVC) and building cover (PerBC) had the greatest impact. A 10% increase in PerVC would increase about 5.03, 8.15, 2.16 and 0.20 μg/m3 of dTSP, dPM10, dPM2.5 and dPM1 in summer, and a 10% increase in PerBC would decreased about 41.37, 16.54, 2.47 and 0.95 μg/m3 of them in winter. Increased vegetation coverage and decreased building construction were found to be conducive to ameliorate airborne particle levels in residential environments. Moreover, landscape structure parameters can be served as indicators for predicting the potential particle reduction at local scale.

Mercury Concentrations in Coastal Sediment from Younger Lagoon, Central California

NASA Astrophysics Data System (ADS)

Hohn, R. A.; Ganguli, P. M.; Swarzenski, P. W.; Richardson, C. M.; Merckling, J.; Johnson, C.; Flegal, A. R.

2013-12-01

Younger Lagoon Reserve, located in northern Monterey Bay, is one of the few relatively undisturbed wetlands that remain along the Central Coast of California. This lagoon system provides protected habitat for more than 100 bird species and for populations of fish, mammals, and invertebrates. Total mercury (HgT) concentrations in water within Younger Lagoon appear to vary with rainfall conditions and range from about 5-15 pM. These concentrations are similar to HgT in water from six nearby lagoon systems. However, Younger Lagoon contains elevated concentrations of dissolved organic carbon (~1 mM) and monomethylmercury (MMHg, ~1 pM) relative to our comparison lagoon sites (DOC < 0.5 mM and MMHg < 0.5 pM). We attribute Younger Lagoon's high DOC and MMHg to its restricted connection to the ocean and minor riverine contribution. Coastal lagoons in this region typically form at the mouth of streams. They behave as small estuaries during the wet season when surface water discharge keeps the mouth of the stream open to the ocean, and then transition into lagoons in the dry season when a sand berm develops and effectively cuts off surface water exchange. At Younger Lagoon, the sand berm remains intact throughout the year, breaching only during particularly high tides or intense rain events. Therefore, the lagoon's connection to nearshore seawater is primarily via surface water - groundwater interaction through the sand berm. Because Younger Lagoon is largely isolated from a surface water connection with the ocean, runoff from upgradient urban and agricultural land has an enhanced impact on water (and presumably sediment) quality. As a result, the lagoon is eutrophic and experiences annual algal blooms. Groundwater surveys suggest surface water, groundwater, and coastal seawater are hydraulically connected at Younger Lagoon, and mixing among these water masses appears to influence water geochemistry. To date, no chemical analyses have been conducted on sediment from Younger Lagoon. To address this data gap we collected sediment samples during a February 2013 field campaign. One set of sediment samples is from the bottom of the lagoon along a transect perpendicular to the shoreline and another set is from an approximately 1 m depth profile on the lagoon side of the sand berm (depth of the groundwater table at the time of collection). These samples are being analyzed for HgT, MMHg, and total organic carbon (TOC) and will provide a first glimpse into the distribution of mercury species and organic carbon in sediments from the Younger Lagoon Reserve. We will also collect and analyze sediment samples from another lagoon site with comparable watershed characteristics.

Children's personal exposure to PM10 and associated metals in urban, rural and mining activity areas.

PubMed

Hinwood, Andrea; Callan, Anna C; Heyworth, Jane; McCafferty, Peter; Sly, Peter D

2014-08-01

There has been limited study of children's personal exposure to PM10 and associated metals in rural and iron ore mining activity areas where PM10 concentrations can be very high. We undertook a small study of 70 children where 13 children were recruited in an area of iron ore mining processing and shipping, 15 children from an area in the same region with no mining activities, and 42 children in an urban area. Each child provided a 24h personal exposure PM10 sample, a first morning void urine sample, a hair sample, time activity diary, and self administered questionnaire. Children's 24h personal PM10 concentrations were low (median of 28 μg m(-3) in the mining area; 48 μg m(-3) in the rural area and 45 μg m(-3) in the urban area) with corresponding outdoor PM10 concentrations also low. Some very high personal PM10 concentrations were recorded for individuals (>300 μg m(-3)) with the highest concentrations recorded in the mining and rural areas in the dry season. PM10 concentrations were highly variable. Hair aluminium, cadmium and manganese concentrations were higher in the iron ore activity area, while hair mercury, copper and nickel concentrations were higher in the urban area. Factors such as season and ventilation appear to be important but this study lacked power to confirm this. These results need to be confirmed by a larger study and the potential for absorption of the metals needs to be established along with the factors that increase exposures and the potential for health risks arising from exposure. Copyright © 2014 Elsevier Ltd. All rights reserved.

Contribution of Biomass Burning to Carbonaceous Aerosols in Mexico City during may 2013

NASA Astrophysics Data System (ADS)

Tzompa Sosa, Z. A.; Sullivan, A.; Kreidenweis, S. M.

2014-12-01

The Mexico City Metropolitan Area (MCMA) is one of the largest megacities in the world with a population of 20 million people. Emissions transported from outside the basin, such as wildfires and agricultural burning, represent a potentially large contribution to air quality degradation. This study analyzed PM10 filter samples from six different stations located across the MCMA from May, 2013, which represented the month with the most reported fire counts in the region between 2002-2013. Two meteorological regimes were established considering the number of satellite derived fire counts, changes in predominant wind direction, ambient concentrations of CO, PM10 and PM2.5, and precipitation patterns inside MCMA. The filter samples were analyzed for biomass burning tracers including levoglucosan (LEV), water-soluble potassium (WSK+); and water-soluble organic carbon (WSOC). Results of these analyses show that LEV concentrations correlated positively with ambient concentrations of PM2.5 and PM10 (R2=0.61 and R2=0.46, respectively). Strong correlations were also found between WSOC and LEV (R2=0.94) and between WSK+ and LEV (R2=0.75). An average LEV/WSOC ratio of 0.0147 was estimated for Regime 1 and 0.0062 for Regime 2. Our LEV concentrations and LEV/WSOC ratios are consistent with results found during the MILAGRO campaign (March, 2006). To the best of our knowledge, only total potassium concentrations have been measured in aerosol samples from MCMA. Therefore, this is the first study in MCMA to measure ambient concentrations of WSK+. Analysis of gravimetric mass concentrations showed that PM2.5 accounted for 60% of the PM10 mass concentration with an estimated PM10/PM2.5 ratio of 1.68. Estimates from our laboratory filter sample characterization indicated that we measured 37% of the total PM10 mass concentration. The missing mass is most likely crustal material (soil or dust) and carbonaceous aerosols that were not segregated into WSOC fraction. Assuming that LEV is inert in the atmosphere, the estimated biomass burning contributions to WSOC ranged from 7-23%. When assuming a LEV lifetime of 1.1 to 5 days, the estimated contributions increased on average 80%. Thus, we conclude that biomass burning sources had a large impact on WSOC and PM2.5 during May 2013, potentially explaining up to half of the measured WSOC.

Analysis of airborne particulate matter (PM2.5) over Hong Kong using remote sensing and GIS.

PubMed

Shi, Wenzhong; Wong, Man Sing; Wang, Jingzhi; Zhao, Yuanling

2012-01-01

Airborne fine particulates (PM(2.5); particulate matter with diameter less than 2.5 μm) are receiving increasing attention for their potential toxicities and roles in visibility and health. In this study, we interpreted the behavior of PM(2.5) and its correlation with meteorological parameters in Hong Kong, during 2007-2008. Significant diurnal variations of PM(2.5) concentrations were observed and showed a distinctive bimodal pattern with two marked peaks during the morning and evening rush hour times, due to dense traffic. The study observed higher PM(2.5) concentrations in winter when the northerly and northeasterly winds bring pollutants from the Chinese mainland, whereas southerly monsoon winds from the sea bring fresh air to the city in summer. In addition, higher concentrations of PM(2.5) were observed in rush hours on weekdays compared to weekends, suggesting the influence of anthropogenic activities on fine particulate levels, e.g., traffic-related local PM(2.5) emissions. To understand the spatial pattern of PM(2.5) concentrations in the context of the built-up environment of Hong Kong, we utilized MODerate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Thickness (AOT) 500 m data and visibility data to derive aerosol extinction profile, then converted to aerosol and PM(2.5) vertical profiles. A Geographic Information Systems (GIS) prototype was developed to integrate atmospheric PM(2.5) vertical profiles with 3D GIS data. An example of the query function in GIS prototype is given. The resulting 3D database of PM(2.5) concentrations provides crucial information to air quality regulators and decision makers to comply with air quality standards and in devising control strategies.

Analysis of Airborne Particulate Matter (PM2.5) over Hong Kong Using Remote Sensing and GIS

PubMed Central

Shi, Wenzhong; Wong, Man Sing; Wang, Jingzhi; Zhao, Yuanling

2012-01-01

Airborne fine particulates (PM2.5; particulate matter with diameter less than 2.5 μm) are receiving increasing attention for their potential toxicities and roles in visibility and health. In this study, we interpreted the behavior of PM2.5 and its correlation with meteorological parameters in Hong Kong, during 2007–2008. Significant diurnal variations of PM2.5 concentrations were observed and showed a distinctive bimodal pattern with two marked peaks during the morning and evening rush hour times, due to dense traffic. The study observed higher PM2.5 concentrations in winter when the northerly and northeasterly winds bring pollutants from the Chinese mainland, whereas southerly monsoon winds from the sea bring fresh air to the city in summer. In addition, higher concentrations of PM2.5 were observed in rush hours on weekdays compared to weekends, suggesting the influence of anthropogenic activities on fine particulate levels, e.g., traffic-related local PM2.5 emissions. To understand the spatial pattern of PM2.5 concentrations in the context of the built-up environment of Hong Kong, we utilized MODerate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Thickness (AOT) 500 m data and visibility data to derive aerosol extinction profile, then converted to aerosol and PM2.5 vertical profiles. A Geographic Information Systems (GIS) prototype was developed to integrate atmospheric PM2.5 vertical profiles with 3D GIS data. An example of the query function in GIS prototype is given. The resulting 3D database of PM2.5 concentrations provides crucial information to air quality regulators and decision makers to comply with air quality standards and in devising control strategies. PMID:22969323

Particulate matter concentrations and their related metal toxicity in rural residential environment of semi-arid region of India

NASA Astrophysics Data System (ADS)

Massey, David D.; Kulshrestha, Aditi; Taneja, Ajay

2013-03-01

The concentration of PM10, PM5.0, PM2.5 and PM1 were measured in the indoor-outdoor environment of rural homes of North central part of India during winter, summer and rainy seasons for the time duration of October 2007 to March 2009. Seven trace metals (Pb, Cd, Ni, Fe, Cr, Mn and Cu) were also determined in PM2.5 from October 2007 to March 2009 in the indoor-outdoor environment. During the study period the annual average concentration for PM10, PM5.0, PM2.5 and PM1 in indoor and outdoor were 242.53 μg m-3 and 217.76 μg m-3, 203.57 μg m-3 and 180.42 μg m-3, 164.60 μg m-3 and 143.07 μg m-3, 106.23 μg m-3 and 105.17 μg m-3 respectively. Concentrations of PM10 and PM2.5 have been compared with prescribed WHO standards and NAAQS standards of India and were found to be much higher. Significant seasonal variations of particulate pollutants were obtained using the monthly average concentration of coarse and fine particulate matter. Indoor/outdoor ratios at the rural sites were also determined with the meteorological parameters like temperature, humidity, wind speed and air exchange rate. Chromium was found to have the highest excess cancer risk in a risk evaluation using an Integrated Risk Information System. Three factors each in indoor and outdoor environment of rural site have been identified using Principal Component Analysis & Positive Matrix Factorization.

Source Apportionment and Elemental Composition of PM2.5 and PM10 in Jeddah City, Saudi Arabia.

PubMed

Khodeir, Mamdouh; Shamy, Magdy; Alghamdi, Mansour; Zhong, Mianhua; Sun, Hong; Costa, Max; Chen, Lung-Chi; Maciejczyk, Polina

2012-07-01

This paper presents the first comprehensive investigation of PM2.5 and PM10 composition and sources in Saudi Arabia. We conducted a multi-week multiple sites sampling campaign in Jeddah between June and September, 2011, and analyzed samples by XRF. The overall mean mass concentration was 28.4 ± 25.4 μg/m 3 for PM2.5 and 87.3 ± 47.3 μg/m 3 for PM10, with significant temporal and spatial variability. The average ratio of PM2.5/PM10 was 0.33. Chemical composition data were modeled using factor analysis with varimax orthogonal rotation to determine five and four particle source categories contributing significant amount of for PM2.5 and PM10 mass, respectively. In both PM2.5 and PM10 sources were (1) heavy oil combustion characterized by high Ni and V; (2) resuspended soil characterized by high concentrations of Ca, Fe, Al, and Si; and (3) marine aerosol. The two other sources in PM2.5 were (4) Cu/Zn source; (5) traffic source identified by presence of Pb, Br, and Se; while in PM10 it was a mixed industrial source. To estimate the mass contributions of each individual source category, the CAPs mass concentration was regressed against the factor scores. Cumulatively, resuspended soil and oil combustion contributed 77 and 82% mass of PM2.5 and PM10, respectively.

Source Apportionment and Elemental Composition of PM2.5 and PM10 in Jeddah City, Saudi Arabia

PubMed Central

Khodeir, Mamdouh; Shamy, Magdy; Alghamdi, Mansour; Zhong, Mianhua; Sun, Hong; Costa, Max; Chen, Lung-Chi; Maciejczyk, Polina

2014-01-01

This paper presents the first comprehensive investigation of PM2.5 and PM10 composition and sources in Saudi Arabia. We conducted a multi-week multiple sites sampling campaign in Jeddah between June and September, 2011, and analyzed samples by XRF. The overall mean mass concentration was 28.4 ± 25.4 μg/m3 for PM2.5 and 87.3 ± 47.3 μg/m3 for PM10, with significant temporal and spatial variability. The average ratio of PM2.5/PM10 was 0.33. Chemical composition data were modeled using factor analysis with varimax orthogonal rotation to determine five and four particle source categories contributing significant amount of for PM2.5 and PM10 mass, respectively. In both PM2.5 and PM10 sources were (1) heavy oil combustion characterized by high Ni and V; (2) resuspended soil characterized by high concentrations of Ca, Fe, Al, and Si; and (3) marine aerosol. The two other sources in PM2.5 were (4) Cu/Zn source; (5) traffic source identified by presence of Pb, Br, and Se; while in PM10 it was a mixed industrial source. To estimate the mass contributions of each individual source category, the CAPs mass concentration was regressed against the factor scores. Cumulatively, resuspended soil and oil combustion contributed 77 and 82% mass of PM2.5 and PM10, respectively. PMID:24634602

Drug concentrations in post-mortem femoral blood compared with therapeutic concentrations in plasma

PubMed Central

Launiainen, Terhi; Ojanperä, Ilkka

2014-01-01

Therapeutic drug concentrations measured in plasma are of limited value as reference intervals for interpretation in post-mortem (PM) toxicology. In this study, drug concentration distributions were studied in PM femoral venous blood from 57 903 Finnish autopsy cases representing all causes of death during an 11-year period. Cause-of-death information was obtained from death certificates issued by forensic pathologists. Median, mean, and upper percentile (90th, 95th, 97.5th) concentrations were calculated for 129 drugs. To illustrate how PM median concentrations relate to established therapeutic ranges in plasma, a PM blood/plasma relationship was calculated for each drug. Males represented 75% of the subjects and showed a lower median age (55 yrs) than females (59 yrs). In 43% of these cases, blood alcohol concentration was higher than 0.2‰, and the median was 1.8‰. Sixty-one (47%) of the 129 drugs showed a PM blood/plasma relationship of 1. For 22 drugs (17%), the relationship was <1, and for 46 drugs (35%), the relationship was >1. No marked correlation was found between the PM blood/plasma relationship and the volume of distribution (Vd). For 36 drugs, more than 10% of cases were fatal poisonings attributed to this drug as the main finding. These drug concentration distributions based on a large database provide a helpful reference not only to forensic toxicologists and pathologists but also to clinical pharmacologists in charge of interpreting drug concentrations in PM cases. © 2013 The Authors. Drug Testing and Analysis published by John Wiley & Sons, Ltd. PMID:23881890

Understanding the PM2.5 imbalance between a far and near-road location: Results of high temporal frequency source apportionment and parameterization of black carbon

NASA Astrophysics Data System (ADS)

Sofowote, U. M.; Healy, R. M.; Su, Y.; Debosz, J.; Noble, M.; Munoz, A.; Jeong, C.-H.; Wang, J. M.; Hilker, N.; Evans, G. J.; Hopke, P. K.

2018-01-01

The differences in PM2.5 concentrations between two relatively close stations, one situated near a major highway and the other much more distant were used to develop a protocol for determining the impact of highway traffic on particulate matter concentrations at the roadside. The roadside station was <15 m away from the edge of a major highway while the other was located ∼170 m away. The roadside station contains a suite of continuous instrumentation capable of near-real-time speciation of PM2.5. The particulate matter difference, formally termed the PM2.5 imbalance was arbitrarily defined as a case wherein |Near-road PM2.5 - Far from road PM2.5|/Near-road PM2.5 ≳50%. Of interest was the variation of multi-time factors based on ME2 analyses of the speciation data from the roadside station during these imbalance events. Of the 7 mass-contributing ME2 factors, a black carbon factor was determined to be the major cause of the PM2.5 imbalance and was especially dominant for the case when PM2.5 concentrations at the roadside station were greater than the farther-station PM2.5. The black carbon concentrations observed during these specific events were further regressed against other traffic-related and meteorological parameters with two nonlinear optimization algorithms (generalized reduced gradient and rules ensemble) in our attempts to model any potential relationships. It was observed that the traffic counts of heavy duty vehicles (predominantly diesel-powered) dominated the relationship with black carbon while contributions from light duty vehicles were negligible during these [PM2.5]Roadside > [PM2.5]Farther events at the roadside station. This work details the most critical ways that highway traffic can contribute to local ambient PM2.5 concentrations that commuters are exposed to and will be important in informing policies and strategies for particulate matter pollution reduction.

Spatiotemporal analysis of particulate air pollution and ischemic heart disease mortality in Beijing, China.

PubMed

Xu, Meimei; Guo, Yuming; Zhang, Yajuan; Westerdahl, Dane; Mo, Yunzheng; Liang, Fengchao; Pan, Xiaochuan

2014-12-12

Few studies have used spatially resolved ambient particulate matter with an aerodynamic diameter of <10 μm (PM10) to examine the impact of PM10 on ischemic heart disease (IHD) mortality in China. The aim of our study is to evaluate the short-term effects of PM10 concentrations on IHD mortality by means of spatiotemporal analysis approach. We collected daily data on air pollution, weather conditions and IHD mortality in Beijing, China during 2008 and 2009. Ordinary kriging (OK) was used to interpolate daily PM10 concentrations at the centroid of 287 township-level areas based on 27 monitoring sites covering the whole city. A generalized additive mixed model was used to estimate quantitatively the impact of spatially resolved PM10 on the IHD mortality. The co-effects of the seasons, gender and age were studied in a stratified analysis. Generalized additive model was used to evaluate the effects of averaged PM10 concentration as well. The averaged spatially resolved PM10 concentration at 287 township-level areas was 120.3 ± 78.1 μg/m3. Ambient PM10 concentration was associated with IHD mortality in spatiotemporal analysis and the strongest effects were identified for the 2-day average. A 10 μg/m3 increase in PM10 was associated with an increase of 0.33% (95% confidence intervals: 0.13%, 0.52%) in daily IHD mortality. The effect estimates using spatially resolved PM10 were larger than that using averaged PM10. The seasonal stratification analysis showed that PM10 had the statistically stronger effects on IHD mortality in summer than that in the other seasons. Males and older people demonstrated the larger response to PM10 exposure. Our results suggest that short-term exposure to particulate air pollution is associated with increased IHD mortality. Spatial variation should be considered for assessing the impacts of particulate air pollution on mortality.

Chemical fractionation and health risk assessment of particulate matter-bound metals in Pune, India.

PubMed

Jan, Rohi; Roy, Ritwika; Yadav, Suman; Satsangi, P Gursumeeran

2018-02-01

The present study deals with the assessment of sequential extraction of particulate matter (PM)-bound metals and the potential health risks associated with them in a growing metropolitan city (Pune) of India. The average mass concentration of both PM 2.5-10 and PM 2.5 exceeded the National Ambient Air Quality Standards. Significant seasonal variation in mass concentration was found for both size fractions of PM with higher values in winter season and lower in monsoon. Chemical species of the studied trace metals in PM exhibited significant differences, due to difference in sources of pollution. Metals such as Cd, Pb, and Cr in both size fractions and Zn and Co in fine fraction were more efficiently extracted in mobile fractions showing their mobile nature while Ni and Fe showed reduced mobility. Fe showed the highest concentrations among all the analyzed elements in both coarse (PM 2.5-10 ) and fine (PM 2.5 ) PM, while Cd showed least concentration in both size fractions. PCA identified industrial emissions, vehicular activity, coal combustion, diesel exhaust, waste incineration, electronic waste processing, constructional activities, soil, and road dust as probable contributors responsible for the metallic fraction of PM. All the metals showed varying contamination in PM samples. The contamination was higher for fine particles than coarse ones. The average global contamination factor was found to be 27.0-34.3 in coarse and fine PM, respectively. The hazard quotient (HQ) estimated for Cd, Co, and Ni (both total and easily accessible concentrations) exceeded the safe level (HQ = 1), indicating that these metals would result in non-carcinogenic health effects to the exposed population. The HQ ranged from 9.1 × 10 -5 for Cu (coarse) to 8.3 for Ni (fine) PM. The cancer risk for Cd, Ni, and Cr in both sized PM were much higher than the acceptable limits of USEPA.

Pulmonary diseases induced by ambient ultrafine and engineered nanoparticles in twenty-first century

PubMed Central

Xia, Tian; Zhu, Yifang; Mu, Lina; Zhang, Zuo-Feng; Liu, Sijin

2016-01-01

Abstract Air pollution is a severe threat to public health globally, affecting everyone in developed and developing countries alike. Among different air pollutants, particulate matter (PM), particularly combustion-produced fine PM (PM2.5) has been shown to play a major role in inducing various adverse health effects. Strong associations have been demonstrated by epidemiological and toxicological studies between increases in PM2.5 concentrations and premature mortality, cardiopulmonary diseases, asthma and allergic sensitization, and lung cancer. The mechanisms of PM-induced toxicological effects are related to their size, chemical composition, lung clearance and retention, cellular oxidative stress responses and pro-inflammatory effects locally and systemically. Particles in the ultrafine range (<100 nm), although they have the highest number counts, surface area and organic chemical content, are often overlooked due to insufficient monitoring and risk assessment. Yet, ample studies have demonstrated that ambient ultrafine particles have higher toxic potential compared with PM2.5. In addition, the rapid development of nanotechnology, bringing ever-increasing production of nanomaterials, has raised concerns about the potential human exposure and health impacts. All these add to the complexity of PM-induced health effects that largely remains to be determined, and mechanistic understanding on the toxicological effects of ambient ultrafine particles and nanomaterials will be the focus of studies in the near future. PMID:28649460

Preclinical Evaluation of Genexol-PM, a Nanoparticle Formulation of Paclitaxel, as a Novel Radiosensitizer for the Treatment of Non-Small Cell Lung Cancer

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

Werner, Michael E.; Cummings, Natalie D.; Sethi, Manish

2013-07-01

Purpose: A key research objective in radiation oncology is to identify agents that can improve chemoradiation therapy. Nanoparticle (NP) chemotherapeutics possess several properties, such as preferential accumulation in tumors, that are uniquely suited for chemoradiation therapy. To facilitate the clinical translation of NP chemotherapeutics in chemoradiation therapy, we conducted preclinical evaluation of Genexol-PM, the only clinically approved NP chemotherapeutic with a controlled drug release profile, as a radiosensitizer using non-small cell lung cancer (NSCLC) as a model disease. Methods and Materials: The physical characteristics and drug release profile of Genexol-PM were characterized. Genexol-PM's efficacy as a radiosensitizer was evaluated inmore » vitro using NSCLC cell lines and in vivo using mouse xenograft models of NSCLC. Paclitaxel dose to normal lung and liver after Genexol-PM administration were quantified and compared with that after Taxol administration. Results: Genexol-PM has a size of 23.91 ± 0.41 nm and surface charge of −8.1 ± 3.1 mV. It releases paclitaxel in a controlled release profile. In vitro evaluation of Genexol-PM as a radiosensitizer showed it is an effective radiosensitizer and is more effective than Taxol, its small molecule counterpart, at the half maximal inhibitory concentration. In vivo study of Genexol-PM as a radiosensitizer demonstrated that it is more effective as a radiosensitizer than Taxol. We also found that Genexol-PM leads to lower paclitaxel exposure to normal lung tissue than Taxol at 6 hours postadministration. Conclusions: We have demonstrated that Genexol-PM is more effective than Taxol as a radiosensitizer in the preclinical setting and holds high potential for clinical translation. Our data support the clinical evaluation of Genexol-PM in chemoradiation therapy for NSCLC.« less

Investigating of spatial variations of PM2.5 concentration in Suzhou using remote sensing imagery

NASA Astrophysics Data System (ADS)

Zhang, Shanzheng; Li, Bailiang

2017-04-01

Suzhou is located at the center of Yangtze Delta, suffering the air pollution from construction of mega city, industrial emission and traffic development. Particulate matter not greater than 2.5 micrometers (PM2.5) is now considered as the most important pollutants in the air in East China. For Suzhou city, some studies on PM2.5 temporal variations based on ground measurements have been conducted. However, until now, there is limited remote sensing based research to investigate the spatial pattern of PM2.5 in Suzhou. MODIS is often used to evaluate the spatial variabiilty of air quality, however, due to its low spatial resolution (250m), we have adopted China launched HJ-1 satellite with 30 m resolution of CCD sensor. Following the solar radiation S6 model and dark object atmospheric correction method (Kaufman,et al., 2000), atmospheric optical depth (AOD) was estimated. A statistical relationship has been built up between AOD and PM2.5. We have retrieved the spatial distribution of PM2.5 across Suzhou city in the winter of 2014. Results indicate that PM2.5 has the highest value in Kunshan (East of Suzhou) and Changshu and Taicang (NE of Suzhou) due to the heavy-polluted industry, while in the island of the Taihu Lake, the PM2.5 is significantly lower than other places maybe because of high deposition rate of PM2.5 over water and forest surfaces. The spatial variation also shows that traffic has less contribution to the PM2.5 generation than the industry. We believe this study will be very useful to identify the causes of local PM2.5 pollution. The findings could also benefit local management and policy making.

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.

Impact of roadside tree lines on indoor concentrations of traffic-derived particulate matter.

PubMed

Maher, Barbara A; Ahmed, Imad A M; Davison, Brian; Karloukovski, Vassil; Clarke, Robert

2013-12-03

Exposure to airborne particulate pollution is associated with premature mortality and a range of inflammatory illnesses, linked to toxic components within the particulate matter (PM) assemblage. The effectiveness of trees in reducing urban PM10 concentrations is intensely debated. Modeling studies indicate PM10 reductions from as low as 1% to as high as ~60%. Empirical data, especially at the local scale, are rare. Here, we use conventional PM10 monitoring along with novel, inexpensive magnetic measurements of television screen swabs to measure changes in PM10 concentrations inside a row of roadside houses, after temporarily installing a curbside line of young birch trees. Independently, the two approaches identify >50% reductions in measured PM levels inside those houses screened by the temporary tree line. Electron microscopy analyses show that leaf-captured PM is concentrated in agglomerations around leaf hairs and within the leaf microtopography. Iron-rich, ultrafine, spherical particles, probably combustion-derived, are abundant, form a particular hazard to health, and likely contribute much of the measured magnetic remanences. Leaf magnetic measurements show that PM capture occurs on both the road-proximal and -distal sides of the trees. The efficacy of roadside trees for mitigation of PM health hazard might be seriously underestimated in some current atmospheric models.

Occupational Exposure to Cobalt and Tungsten in the Swedish Hard Metal Industry: Air Concentrations of Particle Mass, Number, and Surface Area

PubMed Central

Bryngelsson, Ing-Liss; Pettersson, Carin; Husby, Bente; Arvidsson, Helena; Westberg, Håkan

2016-01-01

Exposure to cobalt in the hard metal industry entails severe adverse health effects, including lung cancer and hard metal fibrosis. The main aim of this study was to determine exposure air concentration levels of cobalt and tungsten for risk assessment and dose–response analysis in our medical investigations in a Swedish hard metal plant. We also present mass-based, particle surface area, and particle number air concentrations from stationary sampling and investigate the possibility of using these data as proxies for exposure measures in our study. Personal exposure full-shift measurements were performed for inhalable and total dust, cobalt, and tungsten, including personal real-time continuous monitoring of dust. Stationary measurements of inhalable and total dust, PM2.5, and PM10 was also performed and cobalt and tungsten levels were determined, as were air concentration of particle number and particle surface area of fine particles. The personal exposure levels of inhalable dust were consistently low (AM 0.15mg m−3, range <0.023–3.0mg m−3) and below the present Swedish occupational exposure limit (OEL) of 10mg m−3. The cobalt levels were low as well (AM 0.0030mg m−3, range 0.000028–0.056mg m−3) and only 6% of the samples exceeded the Swedish OEL of 0.02mg m−3. For continuous personal monitoring of dust exposure, the peaks ranged from 0.001 to 83mg m−3 by work task. Stationary measurements showed lower average levels both for inhalable and total dust and cobalt. The particle number concentration of fine particles (AM 3000 p·cm−3) showed the highest levels at the departments of powder production, pressing and storage, and for the particle surface area concentrations (AM 7.6 µm2·cm−3) similar results were found. Correlating cobalt mass-based exposure measurements to cobalt stationary mass-based, particle area, and particle number concentrations by rank and department showed significant correlations for all measures except for particle number. Linear regression analysis of the same data showed statistically significant regression coefficients only for the mass-based aerosol measures. Similar results were seen for rank correlation in the stationary rig, and linear regression analysis implied significant correlation for mass-based and particle surface area measures. The mass-based air concentration levels of cobalt and tungsten in the hard metal plant in our study were low compared to Swedish OELs. Particle number and particle surface area concentrations were in the same order of magnitude as for other industrial settings. Regression analysis implied the use of stationary determined mass-based and particle surface area aerosol concentration as proxies for various exposure measures in our study. PMID:27143598

Analysis of Personal and Home Characteristics Associated with the Elemental Composition of PM2.5 in Indoor, Outdoor, and Personal Air in the RIOPA Study.

PubMed

Ryan, Patrick H; Brokamp, Cole; Fan, Zhi-Hua; Rao, M B

2015-12-01

The complex mixture of chemicals and elements that constitute particulate matter (PM*) varies by season and geographic location because source contributors differ over time and place. The composition of PM having an aerodynamic diameter < 2.5 μm (PM2.5) is hypothesized to be responsible, in part, for its toxicity. Epidemiologic studies have identified specific components and sources of PM2.5 that are associated with adverse health outcomes. The majority of these studies use measures of outdoor concentrations obtained from one or a few central monitoring sites as a surrogate for measures of personal exposure. Personal PM2.5 (and its elemental composition), however, may be different from the PM2.5 measured at stationary outdoor sites. The objectives of this study were (1) to describe the relationships between the concentrations of various elements in indoor, outdoor, and personal PM2.5 samples, (2) to identify groups of individuals with similar exposures to mixtures of elements in personal PM2.5 and to examine personal and home characteristics of these groups, and (3) to evaluate whether concentrations of elements from outdoor PM2.5 samples are appropriate surrogates for personal exposure to PM2.5 and its elements and whether indoor PM2.5 concentrations and information about home characteristics improve the prediction of personal exposure. The objectives of the study were addressed using data collected as part of the Relationships of Indoor, Outdoor, and Personal Air (RIOPA) study. The RIOPA study has previously measured the mass concentrations of PM2.5 and its elemental constituents during 48-hour concurrent indoor, outdoor (directly outside the home), and personal samplings in three urban areas (Los Angeles, California; Houston, Texas; and Elizabeth, New Jersey). The resulting data and information about personal and home characteristics (including air-conditioning use, nearby emission sources, time spent indoors, census-tract geography, air-exchange rates, and other information) for each RIOPA participant were downloaded from the RIOPA study database. We performed three sets of analyses to address the study aims. First, we conducted descriptive analyses to describe the relationships between elemental concentrations in the concurrently gathered indoor, outdoor, and personal air samples. We assessed the correlation between personal exposure and indoor concentrations as well as personal exposure and outdoor concentrations of each element and calculated ratios between them. In addition, we performed principal component analysis (PCA) and calculated principal component scores (PCSs) to examine the heterogeneity of the elemental composition and then tested whether the mixture of elements in indoor, outdoor, and personal PM2.5 was significantly different within each study site and across study sites. Secondly, we performed model-based clustering analysis to group RIOPA participants with similar exposures to mixtures of elements in personal PM2.5. We examined the association between cluster membership and the concentrations of elements in indoor and outdoor PM2.5 samples and personal and home characteristics. Finally, we developed a series of linear regression models and random forest models to examine the association between personal exposure to elements in PM2.5 and (1) outdoor measurements, (2) outdoor and indoor measurements, and (3) outdoor and indoor measurements and home characteristics. As we developed each model, the improvement in prediction of personal exposure when including additional information was assessed. Personal exposures to PM2.5 and to most elements were significantly correlated with both indoor and outdoor concentrations, although concentrations in personal samples frequently exceeded those of indoor and outdoor samples. In general, for most PM2.5 elements indoor concentrations were more highly correlated with personal exposure than were outdoor concentrations. PCA showed that the mixture of elements in indoor, outdoor, and personal PM2.5 varied significantly across sample types within each study site and also across study sites within each sample type. Using model-based clustering, we identified seven clusters of RIOPA participants whose personal PM2.5 samples had similar patterns of elemental composition. Using this approach, subsets of RIOPA participants were identified whose personal exposures to PM2.5 (and its elements) were significantly higher than their indoor and outdoor concentrations (and vice versa). The results of linear and random forest regression models were consistent with our correlation analyses and demonstrated that (1) indoor concentrations were more significantly associated with personal exposure than were outdoor concentrations and (2) participant reports of time spent at their home significantly modified many of the associations between indoor and personal concentrations. In linear regression models, the inclusion of indoor concentrations significantly improved the prediction of personal exposures to Ba, Ca, Cl, Cu, K, Sn, Sr, V, and Zn compared with the use of outdoor elemental concentrations alone. Including additional information on personal and home characteristics improved the prediction for only one element, Pb. Our results support the use of outdoor monitoring sites as surrogates of personal exposure for a limited number of individual elements associated with long-range transport and with a few local or indoor sources. Based on our PCA and clustering analyses, we concluded that the overall elemental composition of PM2.5 obtained at outdoor monitoring sites may not accurately represent the elemental composition of personal PM2.5. Although the data used in these analyses compared outdoor PM2.5 composition collected at the home with indoor and personal samples, our results imply that studies examining the complete elemental composition of PM2.5 should be cautious about using data from central outdoor monitoring sites because of the potential for exposure misclassification. The inclusion of personal and home characteristics only marginally improved the prediction of personal exposure for a small number of elements in PM2.5. We concluded that the additional cost and burden of indoor and personal sampling may be justified for studies examining elements because neither outdoor monitoring nor questionnaire data on home and personal characteristics were able to represent adequately the overall elemental composition of personal PM2.5.

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

Spatiotemporal Changes in Fine Particulate Matter Pollution and the Associated Mortality Burden in China between 2015 and 2016

PubMed Central

Feng, Luwei; Ye, Bo; Feng, Huan; Ren, Fu; Huang, Shichun; Zhang, Xiaotong; Du, Qingyun

2017-01-01

In recent years, research on the spatiotemporal distribution and health effects of fine particulate matter (PM2.5) has been conducted in China. However, the limitations of different research scopes and methods have led to low comparability between regions regarding the mortality burden of PM2.5. A kriging model was used to simulate the distribution of PM2.5 in 2015 and 2016. Relative risk (RR) at a specified PM2.5 exposure concentration was estimated with an integrated exposure–response (IER) model for different causes of mortality: lung cancer (LC), ischaemic heart disease (IHD), cerebrovascular disease (stroke) and chronic obstructive pulmonary disease (COPD). The population attributable fraction (PAF) was adopted to estimate deaths attributed to PM2.5. 72.02% of cities experienced decreases in PM2.5 from 2015 to 2016. Due to the overall decrease in the PM2.5 concentration, the total number of deaths decreased by approximately 10,658 per million in 336 cities, including a decrease of 1400, 1836, 6312 and 1110 caused by LC, IHD, stroke and COPD, respectively. Our results suggest that the overall PM2.5 concentration and PM2.5-related deaths exhibited decreasing trends in China, although air quality in local areas has deteriorated. To improve air pollution control strategies, regional PM2.5 concentrations and trends should be fully considered. PMID:29084175