The Experts below are selected from a list of 1461 Experts worldwide ranked by ideXlab platform
Timothy W Collins - One of the best experts on this subject based on the ideXlab platform.
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Hazardous Air Pollutants are associated with worse performance in reading math and science among us primary schoolchildren
Environmental Research, 2020Co-Authors: Sara E Grineski, Timothy W Collins, Daniel E AdkinsAbstract:Abstract Emerging evidence demonstrates that chronic exposure to Air pollution may negatively impact children's cognitive processing and memory. Little is currently known about how Air pollution impacts individual children's academic performance through time. Academic performance is practically important, given its linkage to children's future life course trajectories. Individual-level, longitudinal data from 16,000 US primary school students are combined with a tract-level Hazardous Air Pollutant (HAP) measure to assess how kindergarten exposures are associated with competencies in reading, math and science through third grade. We employed linear mixed models with repeated measures within children (e.g., five math tests across four years), clustering within census tracts, and random effects specified at the child- and census tract-levels. Controlling for a comprehensive list of time variant and time invariant covariates, we found statistically significant associations between higher levels of HAPs and lower reading (b = −0.02; p
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downscaling environmental justice analysis determinants of household level Hazardous Air Pollutant exposure in greater houston
Annals of The Association of American Geographers, 2015Co-Authors: Timothy W Collins, Sara E Grineski, Marilyn Montgomery, Jayajit Chakraborty, Maricarmen HernandezAbstract:Environmental justice (EJ) research has relied on ecological analyses of coarse-scale areal units to determine whether particular populations are disproportionately burdened by toxic risks. This article advances quantitative EJ research by (1) examining whether statistical associations found for geographic units translate to relationships at the household level; (2) testing competing explanations for distributional injustices never before investigated; (3) examining adverse health implications of Hazardous Air Pollutant (HAP) exposures; and (4) applying an underutilized statistical technique appropriate for geographically clustered data. Our study makes these advances by using generalized estimating equations to examine distributive environmental inequities in the Greater Houston (Texas) metropolitan area, based on primary household-level survey data and census block–level cancer risk estimates of HAP exposure from the U.S. Environmental Protection Agency. In addition to main statistical effects, interact...
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downscaling environmental justice analysis determinants of household level Hazardous Air Pollutant exposure in greater houston
Annals of The Association of American Geographers, 2015Co-Authors: Timothy W Collins, Sara E Grineski, Marilyn Montgomery, Jayajit Chakraborty, Maricarmen HernandezAbstract:Environmental justice (EJ) research has relied on ecological analyses of coarse-scale areal units to determine whether particular populations are disproportionately burdened by toxic risks. This article advances quantitative EJ research by (1) examining whether statistical associations found for geographic units translate to relationships at the household level; (2) testing competing explanations for distributional injustices never before investigated; (3) examining adverse health implications of Hazardous Air Pollutant (HAP) exposures; and (4) applying an underutilized statistical technique appropriate for geographically clustered data. Our study makes these advances by using generalized estimating equations to examine distributive environmental inequities in the Greater Houston (Texas) metropolitan area, based on primary household-level survey data and census block–level cancer risk estimates of HAP exposure from the U.S. Environmental Protection Agency. In addition to main statistical effects, interact...
Maricarmen Hernandez - One of the best experts on this subject based on the ideXlab platform.
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downscaling environmental justice analysis determinants of household level Hazardous Air Pollutant exposure in greater houston
Annals of The Association of American Geographers, 2015Co-Authors: Timothy W Collins, Sara E Grineski, Marilyn Montgomery, Jayajit Chakraborty, Maricarmen HernandezAbstract:Environmental justice (EJ) research has relied on ecological analyses of coarse-scale areal units to determine whether particular populations are disproportionately burdened by toxic risks. This article advances quantitative EJ research by (1) examining whether statistical associations found for geographic units translate to relationships at the household level; (2) testing competing explanations for distributional injustices never before investigated; (3) examining adverse health implications of Hazardous Air Pollutant (HAP) exposures; and (4) applying an underutilized statistical technique appropriate for geographically clustered data. Our study makes these advances by using generalized estimating equations to examine distributive environmental inequities in the Greater Houston (Texas) metropolitan area, based on primary household-level survey data and census block–level cancer risk estimates of HAP exposure from the U.S. Environmental Protection Agency. In addition to main statistical effects, interact...
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downscaling environmental justice analysis determinants of household level Hazardous Air Pollutant exposure in greater houston
Annals of The Association of American Geographers, 2015Co-Authors: Timothy W Collins, Sara E Grineski, Marilyn Montgomery, Jayajit Chakraborty, Maricarmen HernandezAbstract:Environmental justice (EJ) research has relied on ecological analyses of coarse-scale areal units to determine whether particular populations are disproportionately burdened by toxic risks. This article advances quantitative EJ research by (1) examining whether statistical associations found for geographic units translate to relationships at the household level; (2) testing competing explanations for distributional injustices never before investigated; (3) examining adverse health implications of Hazardous Air Pollutant (HAP) exposures; and (4) applying an underutilized statistical technique appropriate for geographically clustered data. Our study makes these advances by using generalized estimating equations to examine distributive environmental inequities in the Greater Houston (Texas) metropolitan area, based on primary household-level survey data and census block–level cancer risk estimates of HAP exposure from the U.S. Environmental Protection Agency. In addition to main statistical effects, interact...
Sara E Grineski - One of the best experts on this subject based on the ideXlab platform.
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Hazardous Air Pollutants are associated with worse performance in reading math and science among us primary schoolchildren
Environmental Research, 2020Co-Authors: Sara E Grineski, Timothy W Collins, Daniel E AdkinsAbstract:Abstract Emerging evidence demonstrates that chronic exposure to Air pollution may negatively impact children's cognitive processing and memory. Little is currently known about how Air pollution impacts individual children's academic performance through time. Academic performance is practically important, given its linkage to children's future life course trajectories. Individual-level, longitudinal data from 16,000 US primary school students are combined with a tract-level Hazardous Air Pollutant (HAP) measure to assess how kindergarten exposures are associated with competencies in reading, math and science through third grade. We employed linear mixed models with repeated measures within children (e.g., five math tests across four years), clustering within census tracts, and random effects specified at the child- and census tract-levels. Controlling for a comprehensive list of time variant and time invariant covariates, we found statistically significant associations between higher levels of HAPs and lower reading (b = −0.02; p
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downscaling environmental justice analysis determinants of household level Hazardous Air Pollutant exposure in greater houston
Annals of The Association of American Geographers, 2015Co-Authors: Timothy W Collins, Sara E Grineski, Marilyn Montgomery, Jayajit Chakraborty, Maricarmen HernandezAbstract:Environmental justice (EJ) research has relied on ecological analyses of coarse-scale areal units to determine whether particular populations are disproportionately burdened by toxic risks. This article advances quantitative EJ research by (1) examining whether statistical associations found for geographic units translate to relationships at the household level; (2) testing competing explanations for distributional injustices never before investigated; (3) examining adverse health implications of Hazardous Air Pollutant (HAP) exposures; and (4) applying an underutilized statistical technique appropriate for geographically clustered data. Our study makes these advances by using generalized estimating equations to examine distributive environmental inequities in the Greater Houston (Texas) metropolitan area, based on primary household-level survey data and census block–level cancer risk estimates of HAP exposure from the U.S. Environmental Protection Agency. In addition to main statistical effects, interact...
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downscaling environmental justice analysis determinants of household level Hazardous Air Pollutant exposure in greater houston
Annals of The Association of American Geographers, 2015Co-Authors: Timothy W Collins, Sara E Grineski, Marilyn Montgomery, Jayajit Chakraborty, Maricarmen HernandezAbstract:Environmental justice (EJ) research has relied on ecological analyses of coarse-scale areal units to determine whether particular populations are disproportionately burdened by toxic risks. This article advances quantitative EJ research by (1) examining whether statistical associations found for geographic units translate to relationships at the household level; (2) testing competing explanations for distributional injustices never before investigated; (3) examining adverse health implications of Hazardous Air Pollutant (HAP) exposures; and (4) applying an underutilized statistical technique appropriate for geographically clustered data. Our study makes these advances by using generalized estimating equations to examine distributive environmental inequities in the Greater Houston (Texas) metropolitan area, based on primary household-level survey data and census block–level cancer risk estimates of HAP exposure from the U.S. Environmental Protection Agency. In addition to main statistical effects, interact...
Jawad S Touma - One of the best experts on this subject based on the ideXlab platform.
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1 Projection of Future Year Emissions from a Base-Year Toxics Emission Inventory
2015Co-Authors: Richard Mason, Madeleine L. Strum, Diane Linderman, Jawad S ToumaAbstract:EPA has developed the Emission Modeling System for Hazardous Air Pollutants (EMS-HAP) to prepare Hazardous Air Pollutant emissions for subsequent Air quality modeling and to calculate future year emissions due to projected activity growth and reduction strategy scenarios. This paper focuses on EMS-HAP’s capability to estimate future year emissions. EMS-HAP has the capability to project emissions due to activity growth based on Maximum Achievable Control Technology (MACT) category codes and/or the Standard Industrial Classification (SIC) codes. MACT-based and SIC-based growth can be applied on a national, state, or county-level basis. Based on user-specified options, EMS-HAP can implement emission reduction scenarios in several different manners. Emissions can be reduce
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combining regional and local scale Air quality models with exposure models for use in environmental health studies
Journal of The Air & Waste Management Association, 2009Co-Authors: Vlad Isakov, Jawad S Touma, Janet Burke, Ted Palma, Arlene Rosenbaum, Danelle T Lobdell, Haluk OzkaynakAbstract:Abstract Population-based human exposure models predict the distribution of personal exposures to Pollutants of outdoor origin using a variety of inputs, including Air pollution concentrations; human activity patterns, such as the amount of time spent outdoors versus indoors, commuting, walking, and indoors at home; microenvironmental infiltration rates; and Pollutant removal rates in indoor environments. Typically, exposure models rely upon ambient Air concentration inputs from a sparse network of monitoring stations. Here we present a unique methodology for combining multiple types of Air quality models (the Community Multi-Scale Air Quality [CMAQ] chemical transport model added to the AERMOD dispersion model) and linking the resulting hourly concentrations to population exposure models (the Hazardous Air Pollutant Exposure Model [HAPEM] or the Stochastic Human Exposure and Dose Simulation [SHEDS] model) to enhance estimates of Air pollution exposures that vary temporally (annual and seasonal) and spati...
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combining regional and local scale Air quality models with exposure models for use in environmental health studies
Journal of The Air & Waste Management Association, 2009Co-Authors: Vlad Isakov, Jawad S Touma, Janet Burke, Ted Palma, Arlene Rosenbaum, Danelle T Lobdell, Haluk OzkaynakAbstract:Population-based human exposure models predict the distribution of personal exposures to Pollutants of outdoor origin using a variety of inputs, including Air pollution concentrations; human activity patterns, such as the amount of time spent outdoors versus indoors, commuting, walking, and indoors at home; microenvironmental infiltration rates; and Pollutant removal rates in indoor environments. Typically, exposure models rely upon ambient Air concentration inputs from a sparse network of monitoring stations. Here we present a unique methodology for combining multiple types of Air quality models (the Community Multi-Scale Air Quality [CMAQ] chemical transport model added to the AERMOD dispersion model) and linking the resulting hourly concentrations to population exposure models (the Hazardous Air Pollutant Exposure Model [HAPEM] or the Stochastic Human Exposure and Dose Simulation [SHEDS] model) to enhance estimates of Air pollution exposures that vary temporally (annual and seasonal) and spatially (at census-block-group resolution) in an urban area. The results indicate that there is a strong spatial gradient in the predicted mean exposure concentrations near roadways and industrial facilities that can vary by almost a factor of 2 across the urban area studied. At the high end of the exposure distribution (95th percentile), exposures are higher in the central district than in the suburbs. This is mostly due to the importance of personal mobility factors whereby individuals living in the central area often move between microenvironments with high concentrations, as opposed to individuals residing at the outskirts of the city. Also, our results indicate 20-30% differences due to commuting patterns and almost a factor of 2 difference because of near-roadway effects. These differences are smaller for the median exposures, indicating the highly variable nature of the reflected ambient concentrations. In conjunction with local data on emission sources, microenvironmental factors, and behavioral and socioeconomic characteristics, the combined source-to-exposure modeling methodology presented in this paper can improve the assessment of exposures in future community Air pollution health studies.
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Modeling population exposures to outdoor sources of Hazardous Air Pollutants
Journal of Exposure Science & Environmental Epidemiology, 2008Co-Authors: Haluk Ozkaynak, Jawad S Touma, Ted Palma, James ThurmanAbstract:Accurate assessment of human exposures is an important part of environmental health effects research. However, most Air pollution epidemiology studies rely upon imperfect surrogates of personal exposures, such as information based on available central-site outdoor concentration monitoring or modeling data. In this paper, we examine the limitations of using outdoor concentration predictions instead of modeled personal exposures for over 30 gaseous and particulate Hazardous Air Pollutants (HAPs) in the US. The analysis uses the results from an Air quality dispersion model (the ASPEN or Assessment System for Population Exposure Nationwide model) and an inhalation exposure model (the HAPEM or Hazardous Air Pollutant Exposure Model, Version 5), applied by the US. Environmental protection Agency during the 1999 National Air Toxic Assessment (NATA) in the US. Our results show that the total predicted chronic exposure concentrations of outdoor HAPs from all sources are lower than the modeled ambient concentrations by about 20% on average for most gaseous HAPs and by about 60% on average for most particulate HAPs (mainly, due to the exclusion of indoor sources from our modeling analysis and lower infiltration of particles indoors). On the other hand, the HAPEM/ASPEN concentration ratio averages for onroad mobile source exposures were found to be greater than 1 (around 1.20) for most mobile-source related HAPs (e.g. 1, 3-butadiene, acetaldehyde, benzene, formaldehyde) reflecting the importance of near-roadway and commuting environments on personal exposures to HAPs. The distribution of the ratios of personal to ambient concentrations was found to be skewed for a number of the VOCs and reactive HAPs associated with major source emissions, indicating the importance of personal mobility factors. We conclude that the increase in personal exposures from the corresponding predicted ambient levels tends to occur near locations where there are either major emission sources of HAPs or when individuals are exposed to either on- or nonroad sources of HAPs during their daily activities. These findings underscore the importance of applying exposure-modeling methods, which incorporate information on time–activity, commuting, and exposure factors data, for the purposes of assigning exposures in Air pollution health studies.
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allocation of onroad mobile emissions to road segments for Air toxics modeling in an urban area
Transportation Research Part D-transport and Environment, 2004Co-Authors: E J Kinnee, Jawad S Touma, James Thurman, Chad R Bailey, R Mason, A Beidler, Rich CookAbstract:Abstract Dispersion models are useful tools for setting emission control priorities and developing strategies for reducing Air toxics emissions. Previous methodologies for modeling Hazardous Air Pollutant emissions for onroad mobile sources are based on using spatial surrogates to allocate county level emissions to grid cells. A disadvantage of this process is that it spreads onroad emissions throughout a grid cell instead of along actual road locations. High local concentrations may be underestimated near major roadways, which are often clustered in urban centers. Here, we describe a methodology which utilizes a Geographic Information System to allocate benzene emissions to major road segments in an urban area and model the segments as elongated area sources. The Industrial Source Complex Short Term dispersion model is run using both gridded and link-based emissions to evaluate the effect of improved spatial allocation of emissions on ambient modeled benzene concentrations. Allocating onroad mobile emissions to road segments improves the agreement between modeled concentrations when compared with monitor observations, and also results in higher estimated concentrations in the urban center.
Giuseppe R. Palmese - One of the best experts on this subject based on the ideXlab platform.
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recent advances in plant based vinyl ester resins and reactive diluents
European Polymer Journal, 2018Co-Authors: Santosh Kumar Yadav, Kevin M Schmalbach, Emre Kinaci, Joseph F Stanzione, Giuseppe R. PalmeseAbstract:Abstract Vinyl ester resins (VERs) are used in a variety of applications. However, alternative feedstocks and molecular structures have been recently investigated due to dwindling petroleum reserves and risks associated with bisphenol A (BPA), a leading petroleum-derived precursor for VERs, as well as environmental hazards directly related to the use of petroleum-derived and classified Hazardous Air Pollutant and volatile organic compound reactive diluents (RDs). Plant feedstocks are very common and based on their building blocks, the feedstocks can be categorized into plant oils, cellulose, and lignin. Considerable amount of work has been done on vinyl ester cross-linkers and diluents derived from plant oils, especially those prepared from soybean oil. Carbohydrate biomass-based building blocks, especially isosorbide and furan-based monomers, have a very high potential for use in commercial VERs due to the availability of raw materials and performance of building blocks. Lignin-based vinyl esters have also shown a lot of the potential to compete with their petrochemical counterparts in both cost and performance. This review covers both the topics of bio-based cross-linkers as well as RDs with emphasis on the preparation of monomers and polymers as well as the processing and properties of these materials.
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Emission modeling of styrene from vinyl ester resins with low Hazardous Air Pollutant contents
Clean Technologies and Environmental Policy, 2009Co-Authors: John J. La Scala, Joshua A. Orlicki, Rahul Jain, Chad A. Ulven, Giuseppe R. Palmese, Uday K. Vaidya, James M. SandsAbstract:Styrene is a commonly used co-monomer in vinyl ester (VE) resins, which acts as a reactive diluent and is required in most liquid molding fabrication methods to reduce viscosity and improve overall resin performance. Resins containing low Hazardous Air Pollutant contents have been developed to reduce the styrene emissions during composite fabrication. VE monomers with a bimodal molecular weight distribution have been used to effectively decrease the amount of styrene in the system while maintaining low resin viscosities. Fatty acid vinyl ester (FAVE) resins partially replace styrene with non-volatile fatty acid monomers to reduce styrene emissions. The emissions from bimodal and FAVE resins were measured as a function of time and various parameters, including styrene content, VE molecular weight, and fatty acid monomer content and chain length. The initial emission rate from VE resins is only dependent on styrene content for constant evaporation geometry. Furthermore, the evaporation rate constant was the same regardless of VE molecular weight, styrene content, or the use of co-reactive diluent (MFA monomers). The diffusivity was not dependent on the styrene content in the resin, but decreased linearly as the VE molecular weight increased because of a corresponding increase in the resin viscosity. The diffusivity also increased as the content of MFA increased because of a decrease in the resin viscosity with high MFA content at high emission time. Furthermore, the emission profiles were accurately modeled using a modified version of 1D diffusion through a planar sheet that accounts for the depth change as a function of styrene evaporation. Overall, the model predicted emission profiles similar to the experimentally measured profiles as a function of time for various styrene contents, VE molecular weights, and fatty acid monomer contents.
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composites based on bimodal vinyl ester resins with low Hazardous Air Pollutant contents
Composites Science and Technology, 2008Co-Authors: John J. La Scala, James M. Sands, Matthew S Logan, Giuseppe R. PalmeseAbstract:Abstract Vinyl ester (VE) resins with a bimodal distribution of molecular weights were prepared via methacrylation of epoxy monomers. Bimodal VE resins and neat polymers had viscosities and mechanical properties similar to that of commercial resins. E-glass composites were prepared and also found to have similar mechanical and thermo-mechanical properties relative to composites fabricated using commercial resins. However, the fracture toughness of the bimodal resins was superior to that of the commercial resins partially as a result of increased molecular relaxations that were manifested in a broader glass transition. Overall, bimodal resins allow for the use of low styrene content (∼33 wt%), while maintaining excellent thermal, mechanical, and fracture properties for the neat resins and composites.
