Download or read book Determination of the spatial and temporal variability of size resolved PM2 5 composition and mixing state in multiple regions in California written by Kimberly Prather and published by California Air Resources Board. This book was released on 2009-12-01 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Final report for California Air Resources Board contract 04-336. For an abstract and link to full text, please see: http://www.arb.ca.gov/research/single-project.php?row_id=64974

Download or read book Determination of the Spatial and Temporal Variability of Size resolved P 25 Composition and Mixing State in Multiple Regions in California written by and published by . This book was released on 2009 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Determination of the Spatial and Temporal Variability of Size resolved PM2 5 Composition and Mixing State in Multiple Regions in California written by and published by . This book was released on 2009 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modeling PM2 5 Speciation Concentrations Over California Using the MISRV23 Aerosol Product written by Christian Pelayo and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Public health organizations are interested in better understanding the spatiotemporal variability of fine particulate matter (PM2.5) to relate exposure levels to human health effects. High levels of PM2.5 have been attributed to higher rates of human respiratory disease and premature death. While the health effects of total PM2.5 have been extensively studied, the health effects of speciated PM2.5 are poorly understood. The Interagency Monitoring of Protected Visual Environments (IMPROVE) and Chemical Speciation Network (CSN) ground monitor sites are capable of measuring speciated PM2.5. These data sets lack the necessary spatial resolution to capture the complex behavior of speciated PM2.5 because of emission, transport, and mixing processes. Aerosol optical depth (AOD) retrievals by the Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard Terra have previously been incorporated into models to predict ground level PM2.5 concentrations. The newly reprocessed MISRV23 data set has a 4.4 km2 resolution for the entire global MISR record, making it useful for epidemiology studies (Chau et al., 2020).In this study, fractional AOD, spatial, and temporal variable predictors from the MISRV23 data set are coupled with North American Regional Reanalysis (NARR) planetary boundary layer height (PBLH) and colocated with CSN and IMPROVE PM2.5 data into a generalized additive model (GAM) capable of predicting speciated PM2.5 concentrations of elemental carbon, organic carbon, nitrate, and sulfate over the entire state of California. Each model has an R2 of 0.553, 0.37, 0.487, and 0.607 respectively. Model performance summaries indicate that every predictor variable is significant and that the models are capable of incorporating additional parameters to further improve performance. These models are used to generate surface maps of annual averaged speciated PM2.5 concentrations for the state of California.

Download or read book Neural Networks for Pattern Recognition written by Christopher M. Bishop and published by Oxford University Press. This book was released on 1995-11-23 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.

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 Spatial and Temporal Characterization of Particulate Matter written by Charles Lloyd Blanchard and published by . This book was released on 2003 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Spatial and Temporal Characterization of Fine Particulate Matter Mass Concentrations in California 1980 2002 written by Charles Lloyd Blanchard and published by . This book was released on 2005 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 (

Download or read book Variation Patterns and Sources of Air Pollution written by Chong-Le Li and published by . This book was released on 2016 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Air quality is a high priority research area of the United States Environmental Protection Agency (EPA) and research on the changing spatiotemporal patterns of PM2.5 is part of the EPA’s current focus. The EPA is looking for studies on the relationship between long-term exposure to PM2.5 and cardiovascular health in order to to reduce the uncertainty of the concentration – response relationships, especially at low ambient concentration of PM2.5. A comprehensive analysis of a large volume of available PM2.5 data collected at four different regions in Wisconsin was performed to study the spatialtemporal variations, the patterns of the variations and the changes in patterns of ambient PM2.5. A systematic approach was established in the study that enables utilizing the broadely available PM2.5 data for future health research. Spatial and temporal variations of the characteristics and the changes of the discovered patterns of ambient PM2.5 and the aerosol acidity of PM2.5 were studied using statistical and graphical software. The changes in the concentrations of ambient sulfate, nitrate and OC highlight the need for changing PM2.5 reduction strategies. A change in the ambient aerosol acidity trend was observed around 2009 and 2010. P value analysis indicated both the downward and upward trends were not insignificant. A further study to determine if there is a permanent increasing trend is recommended. An ascending trend of aerosol acidity was discovered during winter episodes in Milwaukee from 2002 to 2009, which also needs additional study. A thermodynamic principle-based method was developed using the deliquescent relative humidity (DRH) as a criterion to determine if the inorganic ions in PM2.5 were in aqueous phase. If the relative humidity (RH) on the sampling day was higher than the DRH of the aerosol system, the inorganic ions were in aqueous phase and were selected for modeling. The Extended Aerosol Inorganic Model (EAIM) was used to estimate the in-situ acidity. The calculated in-situ acidity has reasonable correlation with other aerosol acidity indexes used in the study. Pattern changes in ambient PM2.5 were observed. The periods when trends change direction provide valuable opportunities to study the underlying causes of the changes.

Download or read book Spatial and Temporal Distribution of Particle Concentration and Composition in Lake Tahoe California Nevada written by Banu Sunman and published by . This book was released on 2004 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multiscale Spatial Patterns of Outdoor Air Pollution in California written by Sarah Elisabeth Chambliss and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exposure to air pollution causes diseases of the lungs, cardiovascular system, brain, and numerous other systems, and is a leading environmental health risk worldwide. The burden of air pollution exposure is not distributed evenly across the population of the United States, and often falls more heavily on low-income groups and people of color. An accurate understanding of how air pollution levels vary on multiple spatial scales is critical for shaping effective policies to improve air quality for the highest exposed communities. Pollutants with primary and secondary contributions like fine particulate matter (PM2.5) vary significantly within urban areas on length scales of 1 km but are influenced by emissions at scales of 100 km or more, while other pollutant categories exhibit strong near-source decay at length scales of 100 m. In this dissertation I apply two complementary approaches to assess multiscale spatial patterns for five health-relevant pollutants: PM2.5, black carbon (BC), ultrafine particles (UFP), nitrogen oxide (NO), and nitrogen dioxide (NO2). Using a reduced-complexity chemical transport model I show that current emissions patterns lead to significant PM2.5 exposure disparity among racial-ethnic groups, income categories, and other socioeconomic groupings, driven by the systematically higher proximity to emissions from on-road mobile sources, industry, natural gas and petroleum development, and other major sources. To estimate exposure disparity for pollutants that vary at very fine spatial scales and follow difficult-to-model patterns driven by complex characteristics of the urban landscape (BC, UFP, NO, and NO2), I use data collected via mobile monitoring to construct empirical air pollution maps for a variety of neighborhoods in the San Francisco Bay Area. These measurements show high exposure disparities both within and among racial-ethnic groups, with disparity in mean concentrations driven by differences in neighborhood background concentrations but higher within-group disparity driven by highly localized near-source gradients. I also assess sources of uncertainty in mobile monitoring-based mapping techniques. These complementary approaches provide a broad picture of causes of urban exposure disparity in California and can inform future mitigation measures

Download or read book Statistical Methods for Spatio Temporal Systems written by Barbel Finkenstadt and published by CRC Press. This book was released on 2006-10-20 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities. Contributed by leading researchers in the field, each self-contained chapter starts w

Download or read book Air Pollution Modeling and its Application XVII written by Carlos Borrego and published by Springer Science & Business Media. This book was released on 2007-04-05 with total page 750 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 1969 the North Atlantic Treaty Organisation (NATO) established the Committee on Challenges of Modern Society (CCMS). The subject of air pol- tion was from the start, one of the priority problems under study within the fra- work of various pilot studies undertaken by this committee. The organization of a periodic conference dealing with air pollution modeling and its application has become one of the main activities within the pilot study relating to air pollution. The first five international conferences were organized by the United States as the pilot country; the second five by the Federal Republic of Germany; the third five by Belgium; the next four by The Netherlands; and the next five by Denmark; and with this one, the last three by Portugal. th This volume contains the papers and posters presented at the 27 NATO/CCMS International Technical Meeting on Air Pollution Modeling and Its Application held in Banff, Canada, 24-29 October 2004. The key topics at this ITM included: Role of Atmospheric Models in Air Pollution Policy and Abatement Strategies; Integrated Regional Modeling; Effects of Climate Change on Air Quality; Aerosols as Atmospheric Contaminants; New Developments; and Model Assessment and Verification. 104 participants from North and South America, Europe, Africa and Asia attended th the 27 ITM. The conference was jointly organized by the University of Aveiro, Portugal (Pilot Country) and by The University of Calgary, Canada (Host Country). A total of 74 oral and 22 poster papers were presented during the conference.

Download or read book Journal of the Air Waste Management Association written by and published by . This book was released on 2006 with total page 940 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Future of Atmospheric Chemistry Research written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2017-01-29 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our world is changing at an accelerating rate. The global human population has grown from 6.1 billion to 7.1 billion in the last 15 years and is projected to reach 11.2 billion by the end of the century. The distribution of humans across the globe has also shifted, with more than 50 percent of the global population now living in urban areas, compared to 29 percent in 1950. Along with these trends, increasing energy demands, expanding industrial activities, and intensification of agricultural activities worldwide have in turn led to changes in emissions that have altered the composition of the atmosphere. These changes have led to major challenges for society, including deleterious impacts on climate, human and ecosystem health. Climate change is one of the greatest environmental challenges facing society today. Air pollution is a major threat to human health, as one out of eight deaths globally is caused by air pollution. And, future food production and global food security are vulnerable to both global change and air pollution. Atmospheric chemistry research is a key part of understanding and responding to these challenges. The Future of Atmospheric Chemistry Research: Remembering Yesterday, Understanding Today, Anticipating Tomorrow summarizes the rationale and need for supporting a comprehensive U.S. research program in atmospheric chemistry; comments on the broad trends in laboratory, field, satellite, and modeling studies of atmospheric chemistry; determines the priority areas of research for advancing the basic science of atmospheric chemistry; and identifies the highest priority needs for improvements in the research infrastructure to address those priority research topics. This report describes the scientific advances over the past decade in six core areas of atmospheric chemistry: emissions, chemical transformation, oxidants, atmospheric dynamics and circulation, aerosol particles and clouds, and biogeochemical cycles and deposition. This material was developed for the NSF's Atmospheric Chemistry Program; however, the findings will be of interest to other agencies and programs that support atmospheric chemistry research.

Download or read book Air quality Modeling and Source apportionment of Fine Particulate Matter Implications and Applications in Time series Health Studies written by Amit Marmur and published by . This book was released on 2006 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Air-quality modeling tools may be useful in such investigations of the health effects of air-pollution and PM2.5 specifically. Emissions-based three-dimensional air quality models may introduce several benefits when applied in epidemiologic studies, such as improved spatial representativeness and availability/continuity of data, as well as information on source impacts. Receptor-based models are a common tool for apportioning of ambient levels of pollutants among the major contributing sources, and can be useful in discerning the relative health impacts of different sources.