Grantee Research Project Results
2021 Progress Report: SEARCH: Solutions to Energy, AiR, Climate, and Health
EPA Grant Number: R835871Center: Solutions for Energy, AiR, Climate and Health Center (SEARCH)
Center Director: Bell, Michelle L.
Title: SEARCH: Solutions to Energy, AiR, Climate, and Health
Investigators: Bell, Michelle L. , Hobbs, Benjamin F.
Current Investigators: Bell, Michelle L. , Hobbs, Benjamin F. , Peng, Roger D. , Esty, Daniel C.
Institution: Yale University , Northeastern University , Stanford University , University of Chicago , University of Michigan , North Carolina State University , The Johns Hopkins University , Centers for Disease Control and Prevention , Pacific Northwest National Laboratory
EPA Project Officer: Callan, Richard
Project Period: October 1, 2015 through September 30, 2020 (Extended to September 30, 2022)
Project Period Covered by this Report: October 1, 2020 through September 30,2021
Project Amount: $9,999,990
RFA: Air, Climate And Energy (ACE) Centers: Science Supporting Solutions (2014) RFA Text | Recipients Lists
Research Category: Climate Change , Air Quality and Air Toxics , Airborne Particulate Matter Health Effects , Particulate Matter , Air
Objective:
The main objectives of the SEARCH Center are to investigate energy-related transitions underway across the U.S. by combining state-of-the-science modeling of energy systems, air quality, climate, and health. SEARCH aims to characterize factors contributing to emissions, air quality and health associated with key energy-related transitions in order to understand how these factors affect regional and local differences in air pollution and public health effects today and under a changing climate. In addition, we investigate and identify key modifiable factors (e.g., transportation, land-use, power generation) and how those factors and their air pollution impacts are likely to change over time. SEARCH has four main projects, two research support units (Environmental Data Science Support Unit and the Policy and Decision-Making Support Unit), and an Administrative Unit. Below we summarize the progress on each of these four main research projects, along with the collaborative cross-center projects. No all-Centers meeting was held in 2021 due to the COVID-19 pandemic. We held a virtual two-day Scientific Advisory Committee (SAC) meeting in March 2021. This meeting was held virtually due to travel and safety concerns of in-person meetings at that time due to the COVID-19 global pandemic. The feedback from the SAC Committee was extremely positive and valuable, and we have taken steps to be as responsive as possible when their advice aligned with the scientific goals and specific aims of the Center. The SAC members showed strong support for SEARCH overall, with particular interest in the added value of the Policy Unit and the uniqueness of this component in our Center. The pandemic also affected Project 2, which could not implement all of its initially planned research due to safety concerns. We pivoted the direction of this portion of the Project in coordination with the SAC and EPA. Still we have made substantial progress on our objectives in all projects and units. We also have investigated how the pandemic intersects with environmental conditions and have published several COVID-19 related articles, with more relevant manuscripts in process.
Project 1: Modeling Emissions from Energy Transitions
In Project 1, researchers are collaborating with the SEARCH Center Policy and Decision-Making Support Unit and state air regulatory agencies to develop a suite of energy transition scenarios representing many drivers and shifts in the energy sector that could impact regional emissions and air quality. These transitions are being modeled using the National Energy Modeling System (NEMS). NEMS results will be downscaled and combined with emissions from indirect energy use determined through lifecycle cost assessment (LCA), for input into air quality simulation models, performed by collaborators in Project 3.
Project 2: Assessment of Energy-Related Sources, Factors, and Transitions Using Novel High-Resolution Ambient Air Monitoring Networks and Personal Monitors
The objectives are: Objective 1) develop novel online multipollutant monitors to simultaneously measure air pollutants and GHGs (i.e., CO, CO2, CH4, PM2.5, NO2, O3, SO2, VOCs); Objective 2) develop a network of sites for stationary monitors during field deployment and protocols for the personal sampling; and Objective 3) measure temporally resolved in-home exposures with detailed time-activity information using novel portable multipollutant monitors. Objective 3 was modified from the original research plan due to the COVID-19 pandemic.
Project 3: Improving Projections of the Spatial and Temporal Changes of Multi-Pollutants to Enhance Assessment of Public Health in a Changing World
The main goal of Project 3 is to make critical improvements to online-coupled air quality models (AQMs) and their inputs and outputs, and apply the improved AQMs to estimate the concentrations resulting from energy and emission scenarios (Project 1) to be used in health risk assessments (Project 4). During this reporting period, we have four specific objectives: 1) Complete the simulations at 36-km over the contiguous U.S. (CONUS) under various energy transition scenario provided by Project 1 and examine the impact of emissions changes on future air quality under these scenarios; 2) Update the anthropogenic emissions from National Emissions Inventory (NEI) 2011 to NEI 2017 and perform and evaluate the model simulations for July 2019 over the triple-nested domains centered over Baltimore using observations from EPA AirNow and Project 2; 3) Assess the health impacts of PM2.5 using two approaches: chemical transport model + BenMAP (CTM-based) and reduced complexity models (RCMs) (RCM-based) based on the SEARCH-CACES collaboration project; and 4) Understand the impacts of wildfires on air quality.
Project 4: Human Health Impacts of Energy Transitions: Today and Under a Changing
Decision-makers who protect health from air pollution are faced with complex systems involving multiple emission sources, variation in health response by population and region, and temporal changes such as climate change and economic development. The overall goal of Project 4 is to provide scientific evidence to aid sound policy by investigating: 1) factors that could influence air pollution-health associations, including modifiable factors and factors that could account for regional variability in observed associations (e.g., urbanicity, land-use), for PM2.5 and O3 on risk of cardiovascular and respiratory hospital admissions, including understudied rural populations;
Progress Summary:
Project 1:
Development of transition scenarios: The Project 1 and Policy and Decision-Making Support Unit teams held webinars and conference calls to discuss project progress and plans to implement transition scenarios in NEMS. In particular, we have implemented five scenarios in NEMS: the abundant natural gas scenario, the electric vehicle scenario, the port electrification scenario, the building energy efficiency scenario, and the distributed generation/demand response scenario. All five of the scenarios have been fully simulated in NEMS, and emissions for all energy sectors have been downscaled for four of the five scenarios. We are also implementing additional scenarios suggested by air quality regulators using AEO 2021.
Modeling transition scenarios in NEMS: In Year 1, we focused on getting a working version of the National Energy Modeling System (NEMS) running. In Year 2, we set up a working version of NEMS running in our purchased computer, with runs replicating both the Annual Energy Outlook 2016 and the Annual Energy Outlook 2017. The original version of the model acquired from Energy Information Agency required additional work to adapt to our purposes. We sorted out the compilation issues and developed the model in a way so that as later versions of NEMS become available in the future, we can easily adapt those changes to the newer model In Year 3, we completed three of the five scenarios and are nearly complete with a fourth. In Year 4, we completed a fourth scenario, and the development of last scenario is in final stages. In Year 5, we completed the final scenario and are bringing the academic papers to fruition as well as engaging in state-level policymaker outreach. In Year 6, we published an additional academic paper, continued state-level policymaker outreach, presented work to the U.S. EPA and updated NEMS to the AEO2021 version. The Yale team has provided NEMS modeling results for all scenarios to the JHU team for downscaling. The team has also generated NEMS results for the LCA analysis at Northeastern University.
Downscaling: The output data from NEMS are used for downscaling. In previous years, we have built software and processes to downscale NEMS results, using standard and non-standard results from the Yale-NEMS model produced by our colleagues. This downscaling method produces a set of emission change rates differentiated by location, sector, and emission species that are being used by our partners in Project 3 for processing and air quality simulation for most economic sectors. Year 5’s efforts focused on publishing a comparison of the new “site-and-grow” method for downscaling new EGU capacity with the standard “grow-in-place method”. Progress continued on developing a temporal downscaling method that accounts for how meteorological timeseries considered in Project 3’s air quality analyses simultaneously affect renewable energy production, electricity demands, and ultimately EGU emissions.
Life Cycle Assessment (LCA): The emphasis in Year 6 has been on continuing to harness the NEMS and LCA modeling platform to assess current and future economy-wide emissions associated with physical resource use and technology transitions. In this reporting period, the LCA team worked primarily in three topical areas: (1) projections of air toxics and inter-model comparisons of the health damages of those emissions; (2) identifying opportunities for reducing industrial energy use, emissions and associated health damages through material efficiency and reuse of industrial byproducts. and (3) in-depth analysis of resource use, emissions, and health care damages associated with the health care sector.
Project 2:
The sixth year of Project 2 has focused on the continued deployment of the stationary multipollutant monitoring network and continued in-field/lab testing, development of network data calibrations, analysis of network data, IRB approvals, and preparations for the in-home measurements in Objective 3. The first stationary monitor was deployed in October 2018 and currently we have 43 monitors deployed. Year 6 also included extensive activity on the inter-SEARCH and CACES-SEARCH collaborative projects, which is already yielding manuscripts with continued analysis the data from a successful month-long field and lab campaign in Pittsburgh and Baltimore at the end of Year 4.
Objective 1:
Doctoral student Colby Buehler’s first author paper “Stationary and Portable Multipollutant Monitors for High Spatiotemporal Resolution Air Quality Studies including Online Calibration” was accepted for publication in Atmospheric Measurement Techniques disseminating the affordable monitoring and calibration techniques used in the SEARCH project.
Objective 2:
Multipollutant measurements with the stationary monitoring network continued throughout Year 6 of the project. Analysis of the continuously collected data has been underway in Year 6 with multiple publications submitted or in preparation advancing both low-cost measurement methods and spatiotemporally-resolved studies of urban air pollution (Objectives 1 and 2). One of our core activities for Objective 2 has focused on the calibration of all sensors in the monitors to be able to produce maps and other outputs of the monitoring network data. Postdoctoral Fellow Misti Zamora has also been evaluating calibrations for sensors in the multipollutant monitor and a manuscript “Comparison of calibration methods using co-located reference and sensor measurements for a multi-pollutant low-cost sensor network in real-world conditions” is currently under review at ACS ES&T Engineering. All five sensors studied exhibited responses to environmental factors, and three sensors exhibited cross-sensitives to another air pollutant. We compared the root mean squared error (RMSE) from models that used co-located regulatory instruments and co-located sensors as covariates to address the cross-sensitivities, and the corresponding model RMSEs were all within 0.5 ppb. This indicates that low-cost sensor networks can yield valuable data if the monitoring package is designed to co-measure key covariates. This is key for the utilization of low-cost sensors by diverse audiences since this does not require continual access to regulatory grade instruments.
Objective 3:
At the 2021 SAC meeting, we presented an alternative strategy for Objective 3 to overcome limitations related to COVID-19. In our modified approach, we will deploy the novel portable multipollutant monitors to measure temporally resolved in-home exposures with detailed time-activity information for approximately 20 households over a 4-week period. In this study we will seek to address how modifiable factors influence in-home exposure to air pollutants. This will include estimating the degree to which proximity to outdoor energy-related sources impact in-home exposures to air pollutants. This alternate research plan was developed in consultation with SAC and EPA.
Additional Center activities:
In response to a request from the SAC, an inter-project collaboration with SEARCH Project 1 was initiated to evaluate the tradeoffs between building energy efficiency measures and outdoor versus indoor air quality, with an estimation of the potential resulting health effects. This work was published by Gillingham et al. “The Climate and Health Benefits from Intensive Building Energy Efficiency Improvements” in Science Advances in 2021.
Activities in the SEARCH-CACES collaborative study in Year 6 included a focus on data analysis and interpretation, and results have begun to be disseminated via conference presentations and manuscripts by the team members. This data analysis has leveraged both online (CACES) and offline (SEARCH) measurements of gases and particles collected (a) in Pittsburgh and Baltimore using the CACES mobile laboratory (amongst the high-spatiotemporal measurement networks deployed by SEARCH) and (b) in experiments conducted in the CACES oxidation chambers. Multiple manuscripts are underway using this data and follow-up lab experiments in Year 6 yielded additional measurements to further expanded on those initial experiments. Ongoing preparation of manuscripts include examining the oxidation products and SOA formation from the reactions of common oxygenated volatile chemical products (VCPs); gas and particle emissions from urban cooking sources and variations with cooking type; and spatiotemporal variations in PM concentrations and composition using the SEARCH network, reference sites, and CACES mobile lab in the greater Baltimore region. Additionally, we published a paper on evaluating indoor air chemical diversity, indoor-to-outdoor emissions, and surface reservoirs using high-resolution mass spectrometry in Environmental Science and Technology.
Project 3:
During this project year, we generated model-ready emissions using the final sets of emission change factors and SMOKE for multi-decades (i.e., 2020, 2030, 2040, and 2050) under five energy transition scenarios including the reference scenario without the clean power plan (refnocpp), the “abundant natural gas” scenario (highNG), the “high electric vehicles penetration” scenario (highEV), the “port electrification” scenario (port), and “high energy efficiency” scenario (highEE). The emissions from 2011 to 2050 under these scenarios are projected to decrease for all species and all scenarios with a few exceptions, which are mainly due to the combined impacts of transitions from traditional fossil fuels to natural gases/oils and renewable energy in the energy consumption in industrial, commercial, and residential sectors, the retirement of coal-fired power plants, and replacement of light-duty vehicles by EVs.
We performed simulations for the current period (2012-2018) with baseline emissions based on the NEI 2011 and future period (2048-2052) using projected emissions under the above scenarios. Under the refnocpp scenario, the projected domain-mean reductions in future period relative to current period are 1.5 ppb (4.0%) for max 8-h O3 and up to 1.0 mg m-3 (16.3%) for 24-h average PM2.5. While the PM2.5 concentrations are projected to decrease over CONUS, max 8-h O3 concentrations are projected to decrease in most areas in CONUS but increase in major cities, especially those in the northeastern U.S., Midwest, and CA. Compared to the refnocpp scenario, highEV, port, and highEE show wide-spread decreases of max 8-h O3. The highNG scenario shows heterogeneity with larger increases of the max 8-h O3 over several states and regions where higher natural gas/oil production is projected, but decreases in the southeastern U.S. where large decreases of NOx emissions occur. Overall, the highEE scenario shows the largest decrease of both O3 and PM2.5, indicating that this scenario has potentially the largest human health benefits.
For the WRF/Chem application over the triple-nested domains centering over Baltimore for July 2019, the use of NEI2017 to replace NEI2011 reduces the overpredictions in both O3 and PM2.5 because anthropogenic emissions of most species are significantly reduced in NEI2017 relative to NEI2011, which represent more realistically the emissions for the year of 2019.
To address the need for improving prediction of fire emissions, we constructed a machine learning (ML) model with game-theory interpretation to estimate monthly fire emissions at 0.25o resolution over the CONUS and to understand the controlling factors of fire emissions. The model is trained using monthly fire PM2.5 emission data obtained from the Global Fire Emissions Database (GFED) at 0.25 o spatial resolution. Overall, the ML model can reproduce the interannual variability of fire emissions at 0.25° resolution over CONUS, with a mean correlation of 0.58 and more than 70% of the grids having correlations larger than 0.4. Besides comparing the predicted fire PM2.5 emissions from the interpretable ML model with the GFED observations, the ML model predictions are also compared with those from process-based models in the Fire Modeling Intercomparison Project (FireMIP) to diagnose the process-based models and inform future development. Results show promising performance for the ML model, in reproducing the spatial distributions, seasonality, and interannual variability of fire emissions over CONUS. Regional analysis shows that the ML model can simulate the realistic interannual variability of fire emissions for most of the subregions
SEARCH-CACES Collaborative Project:
The health impacts of PM2.5 are estimated using two methods: 1) complex chemical transport models (CTMs) +health model (CTM-based method) vs. reduced complexity models (RCM-based method). We evaluate PM2.5-related mortality using two CTMs (online WRF/Chem and offline WRF-CMAQ) with the Environmental Benefits Mapping and Analysis Program Community Edition (BenMAP-CE) and two RCMs including the AirPollution Emission Experiments and Policy Analysis Version 3 (AP3) and the Intervention Model for Air Pollution (InMAP). For each model, we estimate the health effects and benefit costs induced by PM2.5 over the CONUS under baseline emission scenario (NEI2011) and future energy transition scenarios (2050). In general, the CTM-based method using WRF/Chem and WRF-CMAQ with BenMAP gives consistent estimates in terms of both the total mortality changes and their spatial distributions. Compared to the CTM-based method, AP3 gives similar total mortality changes but somewhat different spatial distributions. InMAP gives smaller mortality changes than those from the two CTMs and AP3. Both AP3 and InMAP estimate increased mortality in a few areas with increased emissions whereas the CTM method estimates decreased mortality in the CONUS.
Project 4:
We have accomplished several key tasks related to Project 4. Below we highlight key accomplishments and preliminary results. This represents a subset of our work.
We completed several papers on the relationship between temperature and health and how these associations differ by subpopulation, region, and other factors. Examples of recent published work includes studies of how the temperature-mortality relationship differs based on urbanicity (Choi et al., 2021; Lee et al., accepted); how exposure to heat during pregnancy impacts risk of pre-term birth including disparities by residential greenness and socio-economic position (Son et al., 2022); and how the association between temperature and risk of hospitalization changes over time in relation to greenspace (Heo et al., 2021). As an example, our study of the relationship between temperature and risk of mortality for North Carolina showed the anticipated non-linear relationship between temperature and mortality, with different levels of risk depending on contextual factors such as urbanicity (e.g., higher cold effect for the most urban areas) and region (e.g., lowest cold effect for the Mountain Region) (Choi et al., 2021).
We completed a Collaborative Project with the Harvard/MIT Center on the temporal trend in the effect estimates of PM2.5 on hospital admissions. This work included key recommendations from the SAC. This work, which has been accepted (Chen et al.) examines whether the temporal trend of associations between short-term exposure to PM2.5 and risk of hospitalizations differ by subpopulation and urbanicity. In this cohort with understudied less-urban areas without regulatory monitors, we still found positive association between circulatory and respiratory hospitalization and short-term exposure to PM2.5, with higher effect estimates towards the end of study period. Consistent with current literature, we identified significant disparity in associations by race, socioeconomic status and urbanicity. We observed significant differences in temporal trends of associations across socioeconomic status, sex, and age, indicating a possible widening in disparity of PM2.5-related health burden. This study raises the importance of considering environmental justice issues in PM2.5-related health impacts with respect to how associations may change over time.
A key feature of our work in Project 4 is consideration of the environment broadly, beyond the traditionally studied exposures of air pollution and weather, although these are also critically important. As an example, we have recently published two studies on the impacts of concentrated animal feeding operations (CAFOs). These facilities have emerged as an environmental justice issue due to disproportionate siting in low-income and minority communities. However, CAFOs' impact on health is not fully understood. In the first paper (Son et al., 2021), we examined disparities with respect to exposure to CAFOs for North Carolina and in the second paper we linked these exposures to risk of mortality using individual-level data (Son et al., 2021). We have several related papers underway in this area.
Another key feature of Project 4 is systematic review and meta-analysis. We have made substantial progress on our work on systematic reviews and meta-analyses to investigate which subpopulations are most vulnerable or susceptible to environmental conditions including air pollution and temperature. In particular, we published multiple systematic reviews and/or meta-analyses within the past year. One such review examines the scientific literature on associations between exposure to air pollution and ambient temperature in relation to risk of suicide (Heo et al., 2021). Another recently published systematic analysis presents our assessment of the literature on greenness as a potential effect modifier for associations between particulate matter air pollution and health (Son et al., 2021). Ongoing systematic review and meta-analysis projects include analysis of sex/gender as a potential effect modifier for associations between air pollution and cardiovascular health (Heo et al., in revisions). In earlier reports we noted that we have expanded our study of environmental justice to include understudied disadvantaged populations such as immigrants. We have also completed a review of the scientific literature on immigrants and environmental health. This paper is also in revisions (Fong et al.)
Given the pandemic, we have shifted some research to investigate the links between COVID-19 and air pollution. Publications in the past year on this topic include an assessment of racial/ethnic disparities in COVID-19 outcomes for a national study of 3108 US counties (Kim et al., 2021).
We also conducted cross-sectional analysis to investigate the association between long-term exposure to PM2.5 and O3 and COVID-19 confirmed mortality in 177 neighborhoods (i.e., five-digit modified ZIP code tabulation areas [MZCTAs]) in New York City, New York (Kim and Bell, 2021). Our findings also support the theory of disproportionate health burden of COVID-19 by socioeconomic conditions and race/ethnicity. Our third recent paper on COVID-19 and the environment (Lee et al., 2021) considered three Eastern states (New Jersey, Connecticut, and New York).
Other key accomplishments in the past year include two key papers on stormwater control measures including links to disease vectors (Chan et al., accepted) and environmental justice implications of displacement of racially and ethnically minority groups after installation of green infrastructure (Chan et al., 2021). As an example, we investigated the change in the population of residents in a Census block group that are a given race/ethnicity subpopulation comparing the periods before and after green infrastructure installation for Washington, DC.
Future Activities:
Project 1:
Our next steps include completing the analyses and publishing the results from the last scenarios and the new additional scenarios we are implementing in AEO2021.
Downscaling: We will apply the basic growth factor calculation methodology to the fifth scenario (distributed energy resources) and continue to coordinate with Project 3 on procedures for sharing and conducting QA/QC and downscaled change factors. We will implement and test the temporal downscaling method for determining hourly EGU emissions that are weather-dependent.
Life Cycle Assessment: Using the NEMS-linked air toxics model developed under the SEARCH project, the project will examine regional differences in predicted emissions and health damages, disaggregated by region (US census division) and pollutant, which can be used to aid prioritization of pollution prevention and control activities. Also, a statistical comparison will be made of environmental justice communities’ exposure to air toxics in Massachusetts, identifying major drivers of inequalities in terms of proximity and type of industrial facilities.
Project 2:
Year 7 of the project primarily includes continued maintenance and analysis of the data from the fixed stationary network (Objective 2) and the in-home exposure monitoring (Objective 3) with the modified deployment strategy. This includes the completion of our calibration approaches and finalizing of datasets to conduct analyses related to spatiotemporal variability and indoor/outdoor source attribution. Relevant data analysis sub-objectives from Objective 2 and 3 will then utilize incoming data from the networks. All IRB approvals will be renewed, as required.
Project 3:
We will complete the model simulations for multiple future 5-yr periods using projected emissions under future energy transition scenarios to evaluate the impact of projected changes in emissions on future air quality and human health. The health impact assessment will be completed with two CTMs and two-three RCMs. We will complete the triple-nested simulation of 2019 over Baltimore, and also perform sensitivity simulations considering energy transition and climate change. We will also combine the ML models of wildfire burned area and emissions with climate simulations of the present-day and future to evaluate the changes of wildfire frequency, burned area, and emissions in the U.S. We plan to publish several journal papers on these topics.
Project 4:
In Year 7, we aim to complete our ongoing epidemiological analyses, systematic review and meta-analysis projects, and collaborations with other Projects and Units of SEARCH. As a key example, we are currently working with Project 3 to analyze changes in air pollution levels for PM2.5 anticipated in 2050 compared to the present day for five energy emissions scenarios in relation to a baseline scenario for scenarios based on Project 1, including a scenario that involved work with Project 2. This brings all four SEARCH Projects together. The five scenarios are abundant natural gas, port electrification, energy efficiency, electric vehicles, and distributed generation, as well as a baseline scenario for comparison. These gridded air pollution estimates will be analyzed for changes in exposure to various subpopulations (e.g., by region) as well as health impacts (e.g., mortality) to estimate how these different emissions scenarios could influence public health through air quality. The SAC encouraged SEARCH to complete many analyses included in this project, such as the implications for environmental disparities by energy policy.
Journal Articles: 74 Displayed | Download in RIS Format
| Other center views: | All 119 publications | 74 publications in selected types | All 74 journal articles |
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Armstrong B, Bell ML, de Sousa Zanotti Stagliorio Coelho M, Leon Guo YL, Guo Y, Goodman P, Hashizume M, Honda Y, Kim H, Lavigne E, Michelozzi P. Longer-term impact of high and low temperature on mortality:an international study to clarify length of mortality displacement. Environmental Health Perspectives.2017 Oct 27;125(10):107009 |
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Bell M, Banerjee G, Pereira G. Residential mobility of pregnant women and implications for assessment of spatially-varying environmental exposures. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2018;28(5):470-480. |
R835871 (2021) |
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Bravo MA, Anthopolos R, Bell ML, Miranda ML. Racial isolation and exposure to airborne particulate matter and ozone in understudied US populations: environmental justice applications of downscaled numerical model output. Environment International 2016;92-93:247-255. |
R835871 (2016) R835871 (2017) R835871 (2020) R835871C004 (2016) |
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Bravo MA, Ebisu K, Dominici F, Wang Y, Peng RD, Bell ML. Airborne fine particles and risk of hospital admissions for understudied populations: effects by urbanicity and short-term cumulative exposures in 708 U.S. counties. Environmental Health Perspectives 2017;125(4):594-601. |
R835871 (2016) R835871 (2017) R835871 (2018) R835871 (2020) R835871C004 (2016) R835871C004 (2017) R833863 (Final) R834798 (Final) |
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Gentner DR, Xiong F. Tracking pollutant emissions. Nature Geoscience 2017;10(12):883-884. |
R835871 (2018) R835871 (2019) R835871 (2020) R835871C002 (2017) |
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Glotfelty T, He J, Zhang Y. Improving organic aerosol treatments in CESM/CAM5: development, application, and evaluation. Journal of Advances in Modeling Earth Systems 2017;9(2):1506-1539. |
R835871 (2017) R835871 (2020) |
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Goldberg DL, Lamsal LN, Loughner CP, Swartz WH, Lu Z, Streets DG. A high-resolution and observationally constrained OMI NO2 satellite retrieval. Atmospheric Chemistry & Physics 2017;17(18):11403-11421. |
R835871 (2017) R835871 (2020) |
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Goldberg DL, Lu Z, Oda T, Lamsal LN, Liu F, Griffin D, McLinden CA, Krotkov NA, Duncan BN, Streets DG. Exploiting OMI NO2 satellite observations to infer fossil-fuel CO2 emissions from US megacities. Science of the Total Environment 2019;695:133805. |
R835871 (2019) R835871 (2020) |
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Guo Y, Gasparrini A, Li S, Sera F, Vicedo-Cabrera AM, Coelho MD, Saldiva PH, Lavigne E, Tawatsupa B, Punnasiri K, Overcenco A. Quantifying excess deaths related to heatwaves under climate change scenarios: a multicountry time series modelling study. PLoS Medicine 2018;15(7). |
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He J, He R, Zhang Y. Impacts of Air–sea Interactions on Regional Air Quality Predictions Using a Coupled Atmosphere-Ocean Model in Southeastern US. Aerosol and Air Quality Research. 2018 Apr 1;18:1044-67. |
R835871 (2018) R835871 (2020) |
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Heo S, Li L, Son J, Koutrakis P, Bell M. Associations Between Gestational Residential Radon Exposure and Term Low Birthweight in Connecticut, USA. EPIDEMIOLOGY 2024;35(6):834-843 |
R835871 (Final) |
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Humes M, Wang M, Kim S, Machesky J, Gentner D, Robinson A, Donahue N, Presto A. Limited Secondary Organic Aerosol Production from Acyclic Oxygenated Volatile Chemical Products. ENVIRONMENTAL SCIENCE TECHNOLOGY 2022;56(8):4806-4815. |
R835871 (2021) R835873 (2020) |
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Jin L, Berman JD, Warren JL, Levy JI, Thurston G, Zhang Y, Xu X, Wang S, Zhang Y, Bell ML. A land use regression model of nitrogen dioxide and fine particulate matter in a complex urban core in Lanzhou, China. Environmental Research 2019;177:108597. |
R835871 (2019) R835871 (2020) |
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Keet CA, Keller JP, Peng RD. Long-term coarse particulate matter exposure is associated with asthma among children in Medicaid. American Journal of Respiratory & Critical Care Medicine 2018;197(6):737-746. |
R835871 (2017) R835871 (2020) |
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Keller JP, Peng RD. Error in estimating area‐level air pollution exposures for epidemiology. Environmetrics 2019;30(8):e2573. |
R835871 (2019) R835871 (2020) |
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Khare P, Gentner DR. Considering the future of anthropogenic gas-phase organic compound emissions and the increasing influence of non-combustion sources on urban air quality. Atmospheric Chemistry and Physics 2018;18(8):5391-5413. |
R835871 (2018) R835871 (2019) R835871 (2020) |
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Krall JR, Hackstadt AJ, Peng RD. A hierarchical modeling approach to estimate regional acute health effects of particulate matter sources. Statistics in Medicine 2017;36(9):1461-1475. |
R835871 (2017) R835871 (2020) |
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Li H, Dailey J, Kale T, Besar K, Koehler K, Katz HE. Sensitive and selective NO2 sensing based on alkyl- and alkylthio-thiophene polymer conductance and conductance ratio changes from differential chemical doping. ACS Applied Materials & Interfaces 2017;9(24):20501-20507. |
R835871 (2017) R835871 (2018) R835871 (2019) R835871 (2020) R835871C002 (2017) |
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Li L, Blomberg A, Lawrence J, Requia W, Wei Y, Liu M, Peralta A, Koutrakis P. A spatiotemporal ensemble model to predict gross beta particulate radioactivity across the contiguos United States. ENVIRONMENTAL INTERNATIONAL 2021;456(106643). |
R835871 (2021) |
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Lim CC, Hayes RB, Ahn J, Shao Y, Silverman DT, Jones RR, Garcia C, Bell ML, Thurston GD. Long-term exposure to ozone and cause-specific mortality risk in the United States. American Journal of Respiratory and Critical Care Medicine 2019;200(8):1022-1031. |
R835871 (2019) R835871 (2020) R831697 (Final) R838300 (2020) |
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Liu JC, Wilson A, Mickley LJ, Dominici F, Ebisu K, Wang Y, Sulprizio MP, Peng RD, Yue X, Son JY, Anderson GB, Bell ML. Wildfire-specific fine particulate matter and risk of hospital admissions in urban and rural counties. Epidemiology 2017;28(1):77-85. |
R835871 (2017) R835871 (2018) R835871 (2020) R834798 (Final) |
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Liu JC, Wilson A, Mickley LJ, Ebisu K, Sulprizio MP, Wang Y, Peng RD, Yue X, Dominici F, Bell ML. Who among the elderly is most vulnerable to exposure to and health risks of fine particulate matter from wildfire smoke? American Journal of Epidemiology 2017;186(6):730-735. |
R835871 (2017) R835871 (2018) R835871 (2020) R834798 (Final) R835875 (2017) R835875 (2018) R835875 (2019) |
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Liu JC, Peng RD. The impact of wildfire smoke on compositions of fine particulate matter by ecoregion in the Western US. Journal of exposure science & environmental epidemiology. 2018 Sep 5:1. |
R835871 (2018) R835871 (2020) |
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Shi W, Zheng Y, Taylor AD, Yu J, Katz HE. Increased mobility and on/off ratio in organic field-effect transistors using low-cost guanine-pentacene multilayers. Applied Physics Letters 2017;111(4):043301. |
R835871 (2017) R835871 (2020) |
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Shi W, Yu J, Katz HE. Sensitive and selective pentacene-guanine field-effect transistor sensing of nitrogen dioxide and interferent vapor analytes. Sensors and Actuators B: Chemical 2018;254:940-948. |
R835871 (2017) R835871 (2020) |
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Silva GS, Warren JL, Deziel NC. Spatial modeling to identify sociodemographic predictors of hydraulic fracturing wastewater injection wells in Ohio census block groups. Environmental Health Perspectives 2018;126(6):067008 (8 pp.). |
R835871 (2018) R835871 (2020) CR839249 (2018) CR839249 (2019) CR839249 (Final) |
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Son JY, Liu JC, Bell ML. Temperature-related mortality:a systematic review and investigation of effect modifiers. Environmental Research Letters 2019;14(7):073004. |
R835871 (2019) R835871 (2020) R835871 (2021) |
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Son J-Y, Lane KJ, Lee J-T, Bell ML. Urban vegetation and heat-related mortality in Seoul, Korea. Environmental Research 2016;151:728-733. |
R835871 (2017) R835871 (2020) |
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Son J-Y, Lee HJ, Koutrakis P, Bell ML. Pregnancy and lifetime exposure to fine particulate matter and infant mortality in Massachusetts, 2001–2007. American Journal of Epidemiology 2017;186(11):1268-1276. |
R835871 (2017) R835871 (2018) R835871 (2020) |
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Son J-Y, Lee J-T, Bell ML. Is ambient temperature associated with risk of infant mortality? A multi-city study in Korea. Environmental Research 2017;158:748-752. |
R835871 (2017) R835871 (2020) |
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Vicedo-Cabrera A, Guo Y, Sera F, Huber V, Schlesner C, Mitchell D, Tong S, Coelho M, Saldiva P, Lavigne E, Correa P, Ortega N, Kan H, Osorio S, Kysely J, Urban A, Jaakkola J, Ryti N, Pascal M, Goodman PG, Zeka A, Michelozzi P, Scortichini M, Hashizume M, Honda Y, Hurtado-Diaz M, Cruz J, Seposo X, Kim H, Tobias A, Iniguez C, Forsberg B, Astrom DO, Ragettli MS, Roosli M, Guo YL, Wu CF, Zanobetti A, Schwartz J, Bell ML, Dang TN, Van DD, Heaviside C, Vardoulakis S, Hajat S, Haines A, Armstrong B, Ebi KL, Gasparrini A. Temperature-related mortality impacts under and beyond Paris Agreement climate change scenarios. CLIMATIC CHANGE 2018;150(3-4):391-402. |
R835871 (2021) |
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Warren J, Son JY, Leaderer BP, Bell ML. Investigating the impact of maternal residential mobility on identifying critical windows of susceptibility to ambient air pollution during pregnancy. American Journal of Epidemiology 2017; 187(5):992-1000. |
R835871 (2018) R835871 (2019) R835871 (2020) |
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Yahya K, Glotfelty T, Wang K, Zhang Y, Nenes A. Modeling regional air quality and climate: improving organic aerosol and aerosol activation processes in WRF/Chem version 3.7.1. Geoscientific Model Development 2017;10(6):2333-2363. |
R835871 (2017) R835871 (2020) |
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Zhang J, Gao Y, Luo K, Leung LR, Zhang Y, Wang K, Fan J. Impacts of compound extreme weather events on ozone in the present and future. Atmospheric Chemistry and Physics (Online). 2018 Jul 13;18(PNNL-SA-135886). |
R835871 (2018) R835871 (2020) |
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Esty DC, ML Bell. Business Leadership in Global Climate Change Responses . American Journal of Public Health2018;108(S2):S80-S84. |
R835871 (2018) R835871 (2020) |
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Levy Zamora M, Xiong F, Gentner D, Kerkez B, Kohrman-Glaser J, Koehler K. Field and laboratory evaluations of the low-cost plantower particulate matter sensor. Environmental Science & Technology 2018;53(2):838-849. |
R835871 (2018) R835871 (2019) R835871 (2020) |
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Keet CA, Keller JP, Peng RD. Long-term coarse particulate matter exposure is associated with asthma among children in Medicaid. American Journal of Respiratory and Critical Care Medicine. 2018 Mar 15;197(6):737-46. |
R835871 (2018) R835871 (2020) |
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Gong X, Lin Y, Bell ML, Zhan FB. Associations between maternal residential proximity to air emissions from industrial facilities and low birth weight in Texas, USA. Environment International 2018;120:181-198. |
R835871 (2019) R835871 (2020) |
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Tang Z, Zhang H, Bai H, Chen Y, Zhao N, Zhou M, Cui H, Lerro C, Lin X, Lv L, Zhang C. Residential mobility during pregnancy in Urban Gansu, China. Health & Place 2018;53:258-263. |
R835871 (2019) R835871 (2020) |
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Heo S, Bell ML, Lee JT. Comparison of health risks by heat wave definition: applicability of wet-bulb globe temperature for heat wave criteria. Environmental Research 2019;168:158-170. |
R835871 (2018) R835871 (2019) R835871 (2020) |
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Gillingham K, Huang P. Is abundant natural gas a bridge to a low-carbon future or a dead-end?. The Energy Journal 2019;40(2). |
R835871 (2018) R835871 (2019) R835871 (2020) |
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Nori-Sarma A, Benmarhnia T, Rajiva A, Azhar GS, Gupta P, Pednekar MS, Bell ML. Advancing our understanding of heat wave criteria and associated health impacts to improve heat wave alerts in developing country settings. International Journal of Environmental Research and Public Health 2019;16(12):2089. |
R835871 (2019) R835871 (2020) |
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Berman JD, Jin L, Bell ML, Curriero FC. Developing a geostatistical simulation method to inform the quantity and placement of new monitors for a follow-up air sampling campaign. Journal of exposure science & environmental epidemiology. 2019 Mar;29(2):248. |
R835871 (2018) R835871 (2020) |
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Berman JD, Jin L, Bell ML, Curriero FC. Developing a geostatistical simulation method to inform the quantity and placement of new monitors for a follow-up air sampling campaign. Journal of Exposure Science & Environmental Epidemiology 2019;29(2):248-257. |
R835871 (2019) |
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Goldberg DL, Lu Z, Streets DG, de Foy B, Griffin D, McLinden CA, Lamsal LN, Krotkov NA, Eskes H. Enhanced capabilities of TROPOMI NO2:estimating NOx from North American cities and power plants. Environmental Science & Technology 2019;53(21):12594-12601. |
R835871 (2019) R835871 (2020) |
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Heo S, Bell ML. Heat waves in South Korea:differences of heat wave characteristics by thermal indices. Journal of Exposure Science & Environmental Epidemiology 2019;29(6):790-805. |
R835871 (2019) R835871 (2020) |
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Sera F, Armstrong B, Tobias A, Vicedo-Cabrera AM, Åström C, Bell ML, Chen BY, de Sousa Zanotti Stagliorio Coelho M, Matus Correa P, Cruz JC, Dang TN. How urban characteristics affect vulnerability to heat and cold:a multi-country analysis. International Journal of Epidemiology 2019;48(4):1101-1112. |
R835871 (2019) R835871 (2020) |
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Son JY, Lee JT, Lane KJ, Bell ML. Impacts of high temperature on adverse birth outcomes in Seoul, Korea:disparities by individual-and community-level characteristics. Environmental Research 2019;168:460-466. |
R835871 (2019) R835871 (2020) |
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Chen G, Wang A, Li S, Zhao X, Wang Y, Li H, Meng X, Knibbs LD, Bell ML, Abramson MJ, Wang Y. Long-term exposure to air pollution and survival after ischemic stroke:the China national stroke registry cohort. Stroke 2019;50(3):563-570. |
R835871 (2019) R835871 (2020) |
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Heo S, Fong KC, Bell ML. Risk of particulate matter on birth outcomes in relation to maternal socio-economic factors:a systematic review. Environmental Research Letters 2019;14(12):123004. |
R835871 (2019) R835871 (2020) |
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Anderson GB, Barnes EA, Bell ML, Dominici F. The future of climate epidemiology:opportunities for advancing health research in the context of climate change. American Journal of Epidemiology 2019;188(5):866-872. |
R835871 (2019) R835871 (2020) R835872 (2019) |
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Nori-Sarma A, Anderson GB, Rajiva A, ShahAzhar G, Gupta P, Pednekar MS, Son JY, Peng RD, Bell ML. The impact of heat waves on mortality in Northwest India. Environmental Research 2019;176:108546. |
R835871 (2019) R835871 (2020) |
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Heo S, Bell ML. The influence of green space on the short-term effects of particulate matter on hospitalization in the US for 2000–2013. Environmental Research 2019;174:61-68. |
R835871 (2019) R835871 (2020) |
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Yan M, Wilson A, Bell ML, Peng RD, Sun Q, Pu W, Yin X, Li T, Anderson GB. The shape of the concentration-response association between fine particulate matter pollution and human mortality in Beijing, China, and its implications for health impact assessment. Environmental Health Perspectives 2019;127(6):067007. |
R835871 (2019) R835871 (2020) |
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Heo S, Nori-Sarma A, Lee K, Benmarhnia T, Dominici F, Bell ML. The use of a quasi-experimental study on the mortality effect of a heat wave warning system in Korea. International Journal of Environmental Research and Public Health 2019;16(12):2245. |
R835871 (2019) R835871 (2020) |
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Goldberg DL, Gupta P, Wang K, Jena C, Zhang Y, Lu Z, Streets DG. Using gap-filled MAIAC AOD and WRF-Chem to estimate daily PM2.5 concentrations at 1 km resolution in the Eastern United States. Atmospheric Environment 2019;199:443-452. |
R835871 (2019) R835871 (2020) |
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Baklanov A, Zhang Y. Advances in air quality modeling and forecasting. Global Transitions 2020;2:261-70. |
R835871 (2020) |
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Woo SH, Liu JC, Yue X, Mickley LJ, Bell ML. Air pollution from wildfires and human health vulnerability in Alaskan communities under climate change. Environmental Research Letters 2020;15(9):094019. |
R835871 (2020) |
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Khare P, Machesky J, Soto R, He M, Presto AA, Gentner DR. Asphalt-related emissions are a major missing nontraditional source of secondary organic aerosol precursors. Science advances 2020;6(36):eabb9785. |
R835871 (2020) |
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Fong KC, Mehta NK, Bell ML. Disparities in exposure to surrounding greenness related to proportion of the population that were immigrants to the United States. International Journal of Hygiene and Environmental Health 2020;224:113434. |
R835871 (2019) R835871 (2020) |
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Rogers HM, Ditto JC, Gentner DR. Evidence for impacts on surface-level air quality in the northeastern US from long-distance transport of smoke from North American fires during the Long Island Sound Tropospheric Ozone Study (LISTOS) 2018. Atmospheric Chemistry and Physics 2020;20(2):671-82. |
R835871 (2020) |
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Zhang Y, Yang P, Gao Y, Leung RL, Bell ML. Health and economic impacts of air pollution induced by weather extremes over the continental US. Environment International 2020;143:105921. |
R835871 (2020) |
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Sheu R, Stonner C, Ditto JC, Klüpfel T, Williams J, Gentner DR. Human transport of thirdhand tobacco smoke:a prominent source of hazardous air pollutants into indoor nonsmoking environments. Science Advances 2020;6(10):eaay4109. |
R835871 (2019) R835871 (2020) |
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Gillingham KT, Huang P. Long-Run Environmental and Economic Impacts of Electrifying Waterborne Shipping in the United States. Environmental Science & Technology 2020;54(16):9824-33. |
R835871 (2020) |
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Nori-Sarma A, Thimmulappa RK, Venkataramana GV, Fauzie AK, Dey SK, Venkareddy LK, Berman JD, Lane KJ, Fong KC, Warren JL, Bell ML. Low-cost NO2 monitoring and predictions of urban exposure using universal kriging and land-use regression modelling in Mysore, India. Atmospheric Environment 2020;226:117395. |
R835871 (2020) |
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Shinozuka Y, Saide PE, Ferrada GA, Burton SP, Ferrare R, Doherty SJ, Gordon H, Longo K, Mallet M, Feng Y, Wang Q. Modeling the smoky troposphere of the southeast Atlantic:a comparison to ORACLES airborne observations from September of 2016. Atmospheric Chemistry and Physics 2020;20(19):11491-526. |
R835871 (2020) |
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Gao Y, Zhang J, Yan F, Leung LR, Luo K, Zhang Y, Bell ML. Nonlinear effect of compound extreme weather events on ozone formation over the United States. Weather and Climate Extremes 2020;30:100285. |
R835871 (2020) |
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Heo S, Lim CC, Bell ML. Relationships between Local Green Space and Human Mobility Patterns during COVID-19 for Maryland and California, USA. Sustainability 2020;12(22):9401. |
R835871 (2020) |
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Datta A, Saha A, Zamora ML, Buehler C, Hao L, Xiong F, Gentner DR, Koehler K. Statistical field calibration of a low-cost PM2. 5 monitoring network in Baltimore. Atmospheric Environment 2020;242:117761. |
R835871 (2020) |
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Schilling K, Gentner DR, Wilen L, Medina A, Buehler C, Perez-Lorenzo LJ, Pollitt KJ, Bergemann R, Bernardo N, Peccia J, Wilczynski V. An accessible method for screening aerosol filtration identifies poor-performing commercial masks and respirators. Journal of exposure science & environmental epidemiology 2020:1-0. |
R835871 (2020) |
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Berman JD, Ebisu K, Peng RD, Dominici F, Bell ML. Drought and the risk of hospital admissions and mortality in older adults in western USA from 2000 to 2013:a retrospective study. The Lancet Planetary Health. 2017 Apr 1;1(1):e17-25. |
R835871 (2018) R835871 (2020) |
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Son JY, Lane KJ, Miranda ML, Bell ML. Health disparities attributable to air pollutant exposure in North Carolina:Influence of residential environmental and social factors. Health & Place 2020;62:102287. |
R835871 (2020) |
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Gasparrini A, Guo Y, Sera F, Vicedo-Cabrera AM, Huber V, Tong S, Coelho MD, Saldiva PH, Lavigne E, Correa PM, Ortega NV. Projections of temperature-related excess mortality under climate change scenarios. The Lancet Planetary Health. 2017 Dec 1;1(9):e360-7. |
R835871 (2018) R835871 (2020) |
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Armstrong B, Sera F, Vicedo-Cabrera AM, Abrutzky R, Åström DO, Bell ML, Chen BY, de Sousa Zanotti Stagliorio Coelho M, Correa PM, Dang TN, Diaz MH. The role of humidity in associations of high temperature with mortality:a multicountry, multicity study. Environmental Health Perspectives 2019;127(9):097007. |
R835871 (2019) R835871 (2020) |
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Supplemental Keywords:
energy systems modeling, downscaling, life cycle assessment, personal exposure monitoring, personal exposure, air monitoring, Regional modeling, air quality, O3, PM2.5, offline/online air quality models, emission change factors, wildfire emissions, and ML wildfire model, environmental justice, health analysis, COVID-19, PM2.5, NO2, air pollution, temperatureProgress and Final Reports:
Original Abstract Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R835871C001 Project 1: Modeling Emissions from Energy Transitions
R835871C002 Project 2: Assessment of Energy-Related Sources, Factors and Transitions Using Novel High-Resolution Ambient Air Monitoring Networks and Personal Monitors
R835871C003 Project 3: Air Quality and Climate Change Modeling: Improving Projections of the Spatial and Temporal Changes of Multipollutants to Enhance Assessment of Public Health in a Changing World
R835871C004 Project 4: Human Health Impacts of Energy Transitions: Today and Under a Changing World
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.
Project Research Results
- Final Report
- 2020 Progress Report
- 2019 Progress Report
- 2018 Progress Report
- 2017 Progress Report
- 2016 Progress Report
- Original Abstract
74 journal articles for this center