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Comparative Evaluation Of Ambient Fine Particulate Matter Pm25 Data Obtained From Urban And Rural Monitoring Sites Along The Upper Ohio River Valley
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Book Synopsis COMPARATIVE EVALUATION OF AMBIENT FINE PARTICULATE MATTER (PM2.5) DATA OBTAINED FROM URBAN AND RURAL MONITORING SITES ALONG THE UPPER OHIO RIVER VALLEY. by :
Download or read book COMPARATIVE EVALUATION OF AMBIENT FINE PARTICULATE MATTER (PM2.5) DATA OBTAINED FROM URBAN AND RURAL MONITORING SITES ALONG THE UPPER OHIO RIVER VALLEY. written by and published by . This book was released on 2004 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Technology Systems, Inc. (ATS), with Desert Research Institute (DRI) and Ohio University as subcontractors, was contracted by the NETL in September 1998 to manage the Upper Ohio River Valley Project (UORVP), with a goal of characterizing the ambient fine particulate in this region, including examination of urban/rural variations, correlations between PM{sub 2.5} and gaseous pollutants, and influences of artifacts on PM{sub 2.5} measurements in this region. Two urban and two rural monitoring sites were included in the UORVP. The four sites selected were all part of existing local and/or state air quality programs. One urban site was located in the Lawrenceville section of Pittsburgh, Pennsylvania at an air quality monitoring station operated by the Allegheny County Health Department. A second urban site was collocated at a West Virginia Division of Environmental Protection (WVDEP) monitoring station at the airport in Morgantown, West Virginia. One rural site was collocated with the Pennsylvania Department of Environmental Protection (PADEP) at a former NARSTO-Northeast site near Holbrook, Greene County, Pennsylvania. The other rural site was collocated at a site operated by the Ohio Environmental Protection Agency (OHEPA) and managed by the Ohio State Forestry Division in Gifford State Forest near Athens, Ohio. Previous Semi-Annual Technical Progress Reports presented the following: (1) the median mass and composition of PM{sub 2.5} are similar for both Lawrenceville and Holbrook, suggesting that the sites are impacted more by the regional than by local effects; (2) there was no significant differences in the particulate trending and levels observed at both sites within seasons; (3) sulfate levels predominate at both sites and (4) PM{sub 2.5} and PM10 mass concentration levels are consistently higher in summer than in winter, with intermediate levels being observed in the fall and spring. Analyses of data conducted during the period from April 1, 2003 through September 30, 2003 are presented in this Semi-Annual Technical Progress Report. Report Revision No. 1 includes the additions or removals of text presented in the previous version of this report.
Book Synopsis COMPARATIVE EVALUATION OF AMBIENT FINE PARTICULATE MATTER (PM2.5)DATA OBTAINED FROM URBAN AND RURAL MONITORING SITES ALONG THE UPPER OHIO RIVER VALLEY. by : Robinson P. Khosah
Download or read book COMPARATIVE EVALUATION OF AMBIENT FINE PARTICULATE MATTER (PM2.5)DATA OBTAINED FROM URBAN AND RURAL MONITORING SITES ALONG THE UPPER OHIO RIVER VALLEY. written by Robinson P. Khosah and published by . This book was released on 2003 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Technology Systems, Inc. (ATS), with Desert Research Institute (DRI) and Ohio University as subcontractors, was contracted by the NETL in September 1998 to manage the Upper Ohio River Valley Project (UORVP), with a goal of characterizing the ambient fine particulate in this region, including examination of urban/rural variations, correlations between PM{sub 2.5} and gaseous pollutants, and influences of artifacts on PM{sub 2.5} measurements in this region. Two urban and two rural monitoring sites were included in the UORVP. The four sites selected were all part of existing local and/or state air quality programs. One urban site was located in the Lawrenceville section of Pittsburgh, Pennsylvania at an air quality monitoring station operated by the Allegheny County Health Department. A second urban site was collocated at a West Virginia Division of Environmental Protection (WVDEP) monitoring station at the airport in Morgantown, West Virginia. One rural site was collocated with the Pennsylvania Department of Environmental Protection (PADEP) at a former NARSTO-Northeast site near Holbrook, Greene County, Pennsylvania. The other rural site was collocated at a site operated by the Ohio Environmental Protection Agency (OHEPA) and managed by the Ohio State Forestry Division in Gifford State Forest near Athens, Ohio. Analysis of data collected to date show that: (1) the median mass and composition of PM{sub 2.5} are similar for both Lawrenceville and Holbrook, suggesting that the sites are impacted more by the regional than by local effects; (2) there was no significant differences in the particulate trending and levels observed at both sites within seasons; (3) sulfate levels predominate at both sites, and (4) PM{sub 2.5} and PM{sub 10} mass concentration levels are consistently higher in summer than in winter, with intermediate levels being observed in the fall and spring. Data analysis focusing on relating the aerometric measurements to local and regional scale emissions of sources of primary and secondary fine particles using receptor-based air quality models will follow.
Book Synopsis Evaluation of the Emission, Transport, and Deposition of Mercury and Fine Particulate Matter from Coal-Based Power Plants in the Ohio River Valley Region by :
Download or read book Evaluation of the Emission, Transport, and Deposition of Mercury and Fine Particulate Matter from Coal-Based Power Plants in the Ohio River Valley Region written by and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: As stated in the proposal: Ohio University, in collaboration with CONSOL Energy, Advanced Technology Systems, Inc (ATS) and Atmospheric and Environmental Research, Inc. (AER) as subcontractors, evaluated the impact of emissions from coal-fired power plants in the Ohio River Valley region as they relate to the transport and deposition of mercury and associated fine particulate matter. This evaluation involved two interrelated areas of effort: ambient air monitoring and regional-scale modeling analysis. The scope of work for the ambient air monitoring included the deployment of a surface air monitoring (SAM) station in southeastern Ohio. The SAM station contains sampling equipment to collect and measure mercury (including speciated forms of mercury and wet and dry deposited mercury), particulate matter (PM) mass, PM composition, and gaseous criteria pollutants (CO, NOx, SO2, O3, etc.). Laboratory analyses of time-integrated samples were used to obtain chemical speciation of ambient PM composition and mercury in precipitation. Nearreal- time measurements were used to measure the ambient concentrations of PM mass and all gaseous species including Hg0 and RGM. Approximately 30 months of field data were collected at the SAM site to validate the proposed regional model simulations for episodic and seasonal model runs. The ambient air quality data provides mercury, and fine particulate matter data that can be used by Ohio Valley industries to assess performance on multi-pollutant control systems. The scope of work for the modeling analysis includes (1) development of updated inventories of mercury emissions from coal plants and other important sources in the modeled domain; (2) adapting an existing 3-D atmospheric chemical transport model to incorporate recent advancements in the understanding of mercury transformations in the atmosphere; (3) analyses of the flux of Hg0, RGM, and fine particulate matter in the different sectors of the study region to identify key transport mechanisms; (4) comparison of cross correlations between species from the model results to observations in order to evaluate characteristics of specific air masses associated with long-range transport from a specified source region; and (5) evaluation of the sensitivity of these correlations to emissions from regions along the transport path. This is accomplished by multiple model runs with emissions simulations switched on and off from the various source regions. To the greatest extent possible, model results were compared to field data collected at other air monitoring sites in the Ohio Valley region, operated independently of this project. These sites may include (1) the DOE National Energy Technologies Laboratory's monitoring site at its suburban Pittsburgh, PA facility; (2) sites in Pittsburgh (Lawrenceville) PA and Holbrook, PA operated by ATS; (3) sites in Steubenville, OH and Pittsburgh, PA operated by the USEPA and/or its contractors; and (4) sites operated by State or local air regulatory agencies. Field verification of model results and predictions provides critical information for the development of cost effective air pollution control strategies by the coal-fired power plants in the Ohio River Valley region.
Book Synopsis Evaluating Ambient Fine Particulate Matter Source Regions in the Ohio River Valley Region by : Sujuan Li
Download or read book Evaluating Ambient Fine Particulate Matter Source Regions in the Ohio River Valley Region written by Sujuan Li and published by . This book was released on 2003 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis AMBIENT PM2.5 SAMPLING AND ANALYSIS. by :
Download or read book AMBIENT PM2.5 SAMPLING AND ANALYSIS. written by and published by . This book was released on 2002 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: This interim report summarizes detailed findings and conclusions drawn from evaluations of data obtained from the operation of ambient PM{sub 2.5} speciation sites in a geographical area encompassing southeastern Ohio, western Pennsylvania and northwestern West Virginia. The overall goal of this program, called the Upper Ohio River Valley Project (UORVP), is to better understand the relationship between coal-based power system emissions and ambient air quality in the Upper Ohio River Valley region through the collection of chemically resolved or speciated data. A summary of the sampling activities, sample analyses and the correlation and interpretation of data acquired from February 1999 through March of 2001 are reported. Mass and speciated data from urban and rural sources are compared and seasonal variations in PM{sub 2.5} distribution are also examined. Correlations between meteorological parameters and total PM{sub 2.5} mass are also presented.
Book Synopsis Monitoring Particulate Matter with Commodity Hardware by : David Holstius
Download or read book Monitoring Particulate Matter with Commodity Hardware written by David Holstius and published by . This book was released on 2014 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Health effects attributed to outdoor fine particulate matter (PM2.5) rank it among the risk factors with the highest health burdens in the world, annually accounting for over 3.2 million premature deaths and over 76 million lost disability-adjusted life years. Existing PM2.5 monitoring infrastructure cannot, however, be used to resolve variations in ambient PM2.5 concentrations with adequate spatial and temporal density, or with adequate coverage of human time-activity patterns, such that the needs of modern exposure science and control can be met. Small, inexpensive, and portable devices, relying on newly available off-the-shelf sensors, may facilitate the creation of PM2.5 datasets with improved resolution and coverage, especially if many such devices can be deployed concurrently with low system cost. Datasets generated with such technology could be used to overcome many important problems associated with exposure misclassification in air pollution epidemiology. Chapter 2 presents an epidemiological study of PM2.5 that used data from ambient monitoring stations in the Los Angeles basin to observe a decrease of 6.1 g (95% CI: 3.5, 8.7) in population mean birthweight following in utero exposure to the Southern California wildfires of 2003, but was otherwise limited by the sparsity of the empirical basis for exposure assessment. Chapter 3 demonstrates technical potential for remedying PM2.5 monitoring deficiencies, beginning with the generation of low-cost yet useful estimates of hourly and daily PM2.5 concentrations at a regulatory monitoring site. The context (an urban neighborhood proximate to a major goods-movement corridor) and the method (an off-the-shelf sensor costing approximately USD $10, combined with other low-cost, open-source, readily available hardware) were selected to have special significance among researchers and practitioners affiliated with contemporary communities of practice in public health and citizen science. As operationalized by correlation with 1h data from a Federal Equivalent Method (FEM) [beta]-attenuation data, prototype instruments performed as well as commercially available equipment costing considerably more, and as well as another reference instrument under similar conditions at the same timescale (R2 = 0.6). Correlations were stronger when 24 h integrating times were used instead (R2 = 0.72). Chapter 4 replicates and extends the results of Chapter 3, showing that similar calibrations may be reasonably exchangeable between near-roadway and background monitoring sites. Chapter 4 also employs triplicate sensors to obtain data consistent with near-field (
Book Synopsis Particulate Matter Evaluation and Perceptions of Ambient Air Quality in Lucas County, Ohio by : Ashleigh Taylor Konopka
Download or read book Particulate Matter Evaluation and Perceptions of Ambient Air Quality in Lucas County, Ohio written by Ashleigh Taylor Konopka and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 2018, approximately 137 million people in the United States lived in counties that had one or more pollutants exceeding National Ambient Air Quality Standards. Unhealthy levels of air pollution have been found to be associated with acute and chronic health effects especially among children, older adults, and persons with chronic diseases. Mortality attributed to air pollution remains, however, even when particulate matter levels are below standards. Decisions to protect health and well-being may be influenced by the public's perceptions of air quality. The goal of this study was to 1) examine air quality perceptions; 2) measure and compare particulate matter concentrations from two geographical locations in Lucas County; 3) examine the relationship between air quality perceptions and the air quality index (AQI), as calculated from measured PM. An online survey, adapted from two previous research studies, was distributed to Lucas County, Ohio residents and workers to examine perceptions of air quality in August, 2020. This included how serious a problem air pollution is in Lucas County, sources of air pollution, credible informational sources, the effects of COVID-19 on air quality, daily activities adjusted when air quality is thought to be poor, and whether air quality affects their health. Particulate matter (PM2.5, PM10) was measured at one-hour intervals over the month of August using a DustTrak DRX at two sampling sites in Lucas County. There were 181 participants who were primarily white, female, and college graduates with a mean age of 38 years. Participants' perception of air quality in Lucas County was either unhealthy for sensitive groups (41.0%) or moderate (39.9%) although they indicated that the opioid crisis, crime, and obesity were the very serious problems in the county. They stated the main contributors to air pollution were oil refineries (61.1%), manufacturing (58.3%), and cars and trucks (45.1%). Approximately 40% of participants reported they and their family members had health problems (e.g. allergies, asthma) exacerbated by poor air quality. The top credible sources for air quality information were the Environmental Protection Agency (92.7%), university researchers (88.6%), and news media (82.4%). The smaller particles contributed more to the overall PM mass. The mean PM2.5 concentration was 14.2 μg/m3 at Site 1 and 10.3 μg/m3 at Site 2. Particulate matter concentrations were statistically different between the sites (p
Book Synopsis Regional Characteristics of Fine Particulate Matter Pollution in the Upper Ohio River Valley by : Myoungwoo Kim
Download or read book Regional Characteristics of Fine Particulate Matter Pollution in the Upper Ohio River Valley written by Myoungwoo Kim and published by . This book was released on 2002 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Evaluation of PM2.5 Measurements by Federal Reference Method (FRM) and Continuous Instruments in Cincinnati, Ohio by : Carlos R. Pacas
Download or read book The Evaluation of PM2.5 Measurements by Federal Reference Method (FRM) and Continuous Instruments in Cincinnati, Ohio written by Carlos R. Pacas and published by . This book was released on 2011 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: The filter based methods have been "the gold standard" of PM measurement in spite of its cost and labor intensiveness. Meanwhile many continuous instruments have been employed side by side at many US sites, and the results from the continuous instruments have been used in forecasting air quality index and applications other than compliance. This goal of this study is to evaluate the data agreement of fine particulate matter (PM2.5) concentrations from filter based Federal Reference Method (FRM) and continuous instruments, such as tapered element oscillating microbalance (TEOM), and ss;-gauge-nephelometers (BAM). The study was performed on five sites (Lebanon, Middletown, Batavia, Sycamore, and Taft) managed by the Hamilton County Department of Environmental Service (HCDOES), Ohio. According to EPA, PM2.5is considered as Class III. Class III included all methods related with PM2.5or PM10-2.5 samples from the atmosphere that are base in 24-hour filter sample. The monitoring period ranges from January 2004 to December 2010. The concentrations from continuous monitoring were averaged in 24 hours in order to compare with FRM. Also each data is three day data. To analyze the data a linear regression was performed between continuous and FRM monthly data and seasonal data. Thus, the intercept and the slope of the linear regression were put into an EPA template to evaluate the equivalence of the candidate method vs. the standard FRM. The same approaches were performed with all the instruments of HCDOES. Some continuous instrument exhibited higher correlation with the FRM than others. However, Seasonal changes such as winter and summer resulted in larger statistical differences, especially in March and October. Analyses also were performance such as multi linear and non-linear, where the temperature was part of the analyses.
Book Synopsis Site-Specific PM2.5 Estimation at Three Urban Scales by : Yogita Yashawant Karale
Download or read book Site-Specific PM2.5 Estimation at Three Urban Scales written by Yogita Yashawant Karale and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Fine particulate matter, also known as PM2.5, is one of the major risk factors to human health. Because of their small size, these particles travel deep within human lungs and pose a variety of health problems. A primary source of acquiring PM2.5 exposure is based on the nearest groundlevel air quality monitoring station. However, these stations are often few and sparsely located due to their high costs for installation and maintenance. This study addresses three challenges related to PM2.5. First, the number of air-quality monitoring sites is insufficient to acquire the complex spatial variability of PM2.5. Therefore, in-situ ground observations fail to characterize PM2.5 distribution, and hence exposure, adequately. The shortfall calls for models capable of estimating PM2.5 at unmonitored locations. Satellite-based Aerosol Optical Depth (AOD) serves as a proxy to estimate PM2.5. Second, although satellite data can supplement PM2.5 estimates at unmonitored locations, the spatial resolutions of satellite-based estimates of PM2.5 are in the order of kilometers. These spatial grains are too coarse to capture PM2.50́9s spatial variation caused by contextual geographic factors such as buildings, and subsequently the estimates0́9 applicabilities to support environmental exposome on health effects. Third, the current standards measure PM2.5 in terms of mass per volume, but findings from some recent studies suggest that alternative measures of PM2.5 are also strongly associated with adverse health outcomes. However, observations in terms of these measures are not available. The dissertation research aimed to address the three challenges in three studies. The first study evaluated the potential of the Convolutional Neural Network (CNN) approach to downscale PM2.5 using satellite-based AOD and meteorological data using Dallas-Fort Worth as a case study. The study developed a model capable of estimating PM2.5 corresponding to the hour of satellite overpass time and examined environmental predictors commonly available for all monitored or non-monitored locations. In particular, the study investigated the effect of the spatial extent to which predictors from the surrounding area influenced the PM2.5 estimates at a location. The results showed that the proposed CNN model effectively estimates PM2.5 concentration with correlation coefficient (R) of 0.87 and root mean squared error (RMSE) of 2.57 Îơg/m3 . Moreover, spatially lagged variables from a wider area around an estimation location improved the model performance. As most monitoring stations were in open areas, data from these stations could not be used to examine the effect of contextual factors, such as the building on PM2.5. The second study evaluated the effects of contextual geographic factors on PM2.5 in mass per volume (i.e., standard measures) in pedestrian-friendly areas on the University of Texas at Dallas campus. The study used a mobile sensor to collect spatial and temporal fineresolution PM2.5 data on the campus. The study found very low spatial variation in the study area less than 1km2 . Furthermore, weather-related variables played a dominant role in PM2.5 distribution as temporal variation over-powered spatial variation in PM2.5 data. The study employed a fixed effect model to assess the effect of time-invariant building morphological characteristics on PM2.5 and found that building0́9s morphological characteristics explained 33.22% variation in the fixed effects in the model. Furthermore, openness in the direction of wind elevated the PM2.5 concentration. The third study investigated the potential of AOD to downscale Particle Number (PN) concentration, an alternative measure of PM2.5, and the effect of building morphology on PN concentration using PN measurements collected across the streets of San Francisco by the Google streetcar. The study showed that AOD remained useful to estimate street-level PN concentration across five different particle sizes. The subsequent analysis of variable importance revealed that AOD and AOD-related variables were more important than building morphology but less important than meteorological variables in the estimation of PN concentration.
Download or read book Index Medicus written by and published by . This book was released on 2004 with total page 1938 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vols. for 1963- include as pt. 2 of the Jan. issue: Medical subject headings.
Book Synopsis Factors Influencing Ambient Particulate Matter by : Kanan Patel
Download or read book Factors Influencing Ambient Particulate Matter written by Kanan Patel and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Long term exposure to particulate matter (PM) has been linked to an increase in mortality and cardiorespiratory diseases. In addition, PM affects Earth’s radiative balance, and is one of the main sources of uncertainty in climate change predictions. Hence, it is imperative to understand PM composition and concentrations and the factors contributing to their variability. Different parts of the world experience different levels of air pollution, due to an interplay between various factors including sources, meteorological factors, and chemical transformations. PM can either be directly emitted into the atmosphere (primary) or can be generated as result of oxidation of gas-phase precursors leading to the formation and partitioning of low volatility products to the particle phase (secondary). The nature, sources and dynamics of PM can be estimated by combining ambient field measurements with receptor modeling, machine learning and statistical analysis tools. The objective of my thesis is to understand the factors influencing PM concentration and composition in different environments. In chapter 2, I have reported the results of the measurements in Austin, Texas, one of the fastest growing metropolitan cities in the U.S. I used several modeling and data analysis tools to understand the sources and formation of particulate matter in Austin including positive matrix factorization (PMF), the Extended Aerosol Thermodynamics Model (E-AIM) and air back trajectory analysis using HYSPLIT. Through my analysis, I demonstrated that photochemistry is an important factor in governing PM composition in Austin. We observed rapid photochemical processing of traffic emissions, H2SO4-driven new particle formation (NPF) events, production of organic nitrate, and daytime peaks in the locally formed oxidized organic aerosol during the summer period. My analysis also suggested that SO2 emissions from cement kilns may be the main source of particulate sulfate observed at this receptor site, pointing toward the need for measurements at the source to investigate this further. This chapter has been published in ACS Earth and Space Chemistry. Meanwhile, Delhi (India) is the most polluted megacity in the world and routinely experiences extreme pollution episodes. Our group is one of the first in the world to measure long term PM composition at high time resolution in the city. As part of the Delhi Aerosol Supersite (DAS) study, we have recorded over five years of near-continuous PM composition to understand inter-seasonal as well as inter-annual variability in the PM concentrations and the factors influencing them. I have studied specific “special” events which have implications for policy decisions. In chapter 3, I have investigated the factors influencing high PM concentrations observed during the autumn (~Sep – Nov) season which experiences some of the most extreme pollution episodes observed anywhere in the world. I combined our measurements with data obtained from regulatory monitoring sites (CO, NOx, PM2.5) to gain insights from the temporal trends of the pollutants and to demonstrate the differences between autumn and winter, which also experiences high concentrations. I incorporated receptor models and non-parametric wind regression to understand the nature and sources of PM during this period. Further, I used meteorological data such as temperature, planetary boundary layer height, wind speed/direction and relative humidity to understand their impact on PM using statistical hypothesis testing. Using these tools, I demonstrated the influence of regional agricultural burning (from the neighboring states) and fireworks during the festival of Diwali on PM during this season. Overall, my analysis provided detailed insights into the sources and dynamics of PM during one of the most polluted seasons in Delhi (and in the world) and provided a direction for future studies in the region. This chapter has also been published in ACS Earth and Space Chemistry. In chapter 4, I have investigated the impact of COVID-19 lock-down on Delhi's air quality by combining PM and gas phase data of over four years with robust statistical analysis, including the method of “robust differences” to account for seasonal variability in the pollutant concentrations. My analysis suggests that future large-scale modification of activity restrictions in Delhi may impact the primary pollutants (NOx, CO, black carbon) more than the secondary pollutants, emphasizing the fundamental importance of secondary or regional pollutants on air quality in Delhi. I showed that overall, future strict activity reductions may lead to only a moderate reduction in PM1, reflective of complex PM1 chemistry and the need for integrative, multiscale, and multisectoral policies to address the major air pollution challenge in Delhi. This chapter has been published in ACS Environmental Science & Technology Letters. Because of the interplay between sources and meteorology in Delhi, in chapter 5 I have developed machine learning models incorporating random forest regression that estimate the concentrations of PM1 and its constituents by using meteorology and emission proxies. I have demonstrated the applicability of these models to capture temporal variability of the PM1 species, to understand the influence of individual factors via sensitivity analyses, and to separate impacts of the COVID-19 lockdowns and associated activity restrictions from impacts of other factors. Overall, these models provide new insights into the factors influencing ambient PM1 in New Delhi, India, demonstrating the power of machine learning models in atmospheric science applications. This chapter will be submitted to Aerosol Science and Technology. My research has advanced our understanding about PM formation and processing in different environments. These novel measurements and analyses will help guide future studies aimed at understanding and improving ambient air quality in these regions. Furthermore, the results of my scientific analyses may help guide policy decisions aimed at reducing PM levels in the atmosphere, thus helping improve the lives of millions of people
Book Synopsis Evaluation of PM2.5 Components and Source Apportionment at a Rural Site in the Ohio River Valley Region by :
Download or read book Evaluation of PM2.5 Components and Source Apportionment at a Rural Site in the Ohio River Valley Region written by and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Evaluation of the Emission, Transport, and Deposition of Mercury and Fine Particulate Matter from Coal-based Power Plants in the Ohio River Valley Region by : Ohio University. Athens, Ohio
Download or read book Evaluation of the Emission, Transport, and Deposition of Mercury and Fine Particulate Matter from Coal-based Power Plants in the Ohio River Valley Region written by Ohio University. Athens, Ohio and published by . This book was released on 2008 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Variability in the Fraction of Ambient Fine Particulate Matter in Indoor Air and Implications for Air Pollution Epidemiology by : Natasha Hodas
Download or read book Variability in the Fraction of Ambient Fine Particulate Matter in Indoor Air and Implications for Air Pollution Epidemiology written by Natasha Hodas and published by . This book was released on 2014 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exposure to ambient fine particulate matter (PM2.5) is associated with multiple negative health outcomes. Studies investigating these associations commonly use PM2.5 concentrations measured at outdoor, central-site monitors to estimate exposure. Because people spend the majority of time indoors, however, the variable efficiency with which ambient PM2.5 penetrates and persists indoors is a source of error in epidemiologic analyses. This error generally results in an underestimation of health effects, hampering the detection of associations between ambient PM2.5 exposures and the risk of health outcomes. To reduce this error, practical methods to model indoor concentrations of ambient PM2.5 are needed. This dissertation contributes to exposure science by advancing existing models of residential exposure to ambient PM2.5 and by improving the robustness and accessibility of these tools. First, drivers of variability in the fraction of ambient PM2.5 found indoors (F) are identified and the potential for this variability to explain observed heterogeneity in PM-mediated health-effect estimates is explored. Next, a physically-based mass-balance model and modeling tools that account for variability in human activity patterns (e.g. time spent in various indoor and outdoor environments) are used to compute ambient PM2.5 exposures that account for the modification of PM2.5 with outdoor-to-indoor transport in order to explore whether the use of these refined exposure surrogates reduces error and bias in epidemiologic analyses. Subsequently, this outdoor-to-indoor transport model is evaluated and refined using measured indoor and outdoor PM2.5 concentrations and air exchange rates, providing a practical and robust tool for reducing exposure misclassification in epidemiologic studies. Finally, the volatility basis set is used for the first time to study shifts in the gas-particle partitioning of ambient organics with transport indoors. This dissertation provides guidance regarding measurements and data most critically needed to facilitate the prediction of refined exposure surrogates in large epidemiological studies and, thus, informs the design of future sampling campaigns and epidemiologic studies. It enables a better accounting of ambient particle penetration into and persistence in the indoor environment and constitutes an important advancement in the efforts to reduce exposure error in epidemiologic studies and to elucidate relationships between PM2.5 exposure and adverse health outcomes.
Book Synopsis Interpretation of Ground-Based Measurements from the Surface Particulate Matter Network to Understand the Global Distribution of Fine Particulate Matter by : Crystal Weagle
Download or read book Interpretation of Ground-Based Measurements from the Surface Particulate Matter Network to Understand the Global Distribution of Fine Particulate Matter written by Crystal Weagle and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exposure to ambient fine particulate matter (PM2.5¬) is increasingly recognized as the leading environmental risk factor for global burden of disease. This thesis develops the Surface PARTiculate mAtter Network (SPARTAN) to provide long-term measurements of PM2.5 mass and chemical composition, collocated with existing aerosol optical depth (AOD) observations in highly populated, globally diverse regions. Three projects are presented that interpret SPARTAN measurements to provide insight into the spatial variation in ground-based PM2.5 chemical composition, into the sources contributing to PM2.5, and into the relationship between AOD and PM2.5 used in satellite-based estimates of PM2.5. Analysis of SPARTAN filter samples collected across multiple continents for PM2.5 chemical composition show that absolute concentrations of several major components vary by more than an order of magnitude across sites, and exhibit consistency with available, collocated studies. Elevated Zn:Al ratios reveal an enhanced anthropogenic dust fraction relative to natural sources, signifying the need to include this PM2.5 source in global models and emission inventories. The developed compositional dataset provides much needed long-term chemical data for investigation of sources leading to the spatial variation of PM2.5 mass and chemical composition. Evaluation of the GEOS-Chem model, constrained by satellite-based estimates of PM2.5 and informed by SPARTAN compositional measurements, shows significant spatial consistency for major chemical components. Measured PM2.5 composition corroborate source attribution from sensitivity simulations, providing confidence in utilizing sensitivity simulations to explore the influence of source categories to global population-weighted PM2.5. This approach of coupling observational datasets with modelling at the global scale allows for insight into the main sources determining PM2.5 global variation, but also identification of modelled processes that require development to represent the wide range of PM2.5 and composition observed globally. An initial comparison between empirical and simulated relationships of PM2.5 and columnar AOD ( ) was conducted using the GEOS-Chem global chemical transport model. This comparison is the first to develop empirical, ground-based and provide an evaluation of modelled values widely used in satellite-based estimates. Collocated, modelled values generally fall within a factor of two of measured values and have a mean fractional bias that is an order of magnitude lower than for either PM2.5 or AOD alone. This lower bias in indicates that satellite-derived PM2.5 inferred using is likely to have lower bias than purely simulated PM2.5¬.
Book Synopsis Air Quality Management in the United States by : National Research Council
Download or read book Air Quality Management in the United States written by National Research Council and published by National Academies Press. This book was released on 2004-08-30 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Managing the nation's air quality is a complex undertaking, involving tens of thousands of people in regulating thousands of pollution sources. The authors identify what has worked and what has not, and they offer wide-ranging recommendations for setting future priorities, making difficult choices, and increasing innovation. This new book explores how to better integrate scientific advances and new technologies into the air quality management system. The volume reviews the three-decade history of governmental efforts toward cleaner air, discussing how air quality standards are set and results measured, the design and implementation of control strategies, regulatory processes and procedures, special issues with mobile pollution sources, and more. The book looks at efforts to spur social and behavioral changes that affect air quality, the effectiveness of market-based instruments for air quality regulation, and many other aspects of the issue. Rich in technical detail, this book will be of interest to all those engaged in air quality management: scientists, engineers, industrial managers, law makers, regulators, health officials, clean-air advocates, and concerned citizens.
