2019 Progress Report: SEARCH: Solutions to Energy, AiR, Climate, and Health

EPA Grant Number: R835871
Center: 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. , Koehler, Kirsten , Gentner, Drew R. , Zhang, Yang , Gillingham, Ken
Current Investigators: Bell, Michelle L. , Hobbs, Benjamin F.
Institution: Yale University , Centers for Disease Control and Prevention , The Johns Hopkins University , North Carolina State University , Stanford University , Northeastern University , University of Chicago , Pacific Northwest National Laboratory , University of Michigan
Current 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, 2018 through September 30,2019
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:

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, oxidative potential, VOCs); Objective 2) developing a network of sites for stationary monitors during field deployment and protocols for the personal sampling; and Objective 3) measure temporally resolved personal exposures with detailed time-activity information using novel personal multipollutant monitors.

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 three specific objectives: 1) Perform final regional air quality baseline simulations using FINN fire emissions and test simulations using the emission change factors under various energy transition scenarios; 2) Understand the impacts of wildfires on air quality by analyzing global simulations in order to improve the representation of wildfire emissions for air quality simulations; 3) Generate high resolution snapshots of PM2.5 using WRF/Chem output, MAIAC aerosol optical depth, and other inputs to be used for health assessment studies

Project 4: Human Health Impacts of Energy Transitions: Today and Under a Changing World

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; 2) health impacts from energy transitions using the most up-to-date scientific information on the multipollutant mixture, regional variation, and sensitive subpopulations; and 3) how climate change could affect health impacts of energy transitions and the co-benefits/costs of air quality policies by calculating their climate change impact.

Progress Summary:

Project 1: Modeling Emissions from Energy Transitions

Development of transition scenarios: The Project 1 and Policy and Decision Making Support Unit teams held webinar 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. Four of the five scenarios have been fully simulated, and the fifth is in progress.

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 and reduce the time to solve compatibility issues. We also adopted a version control platform "Git" to document every change applied to the model. We can easily switch to previous working versions and various scenarios to replicate model results without adding storage burdens. In Year 3, we have completed three of the five scenarios and are nearly complete with a fourth. In Year 4, we have completed a fourth scenario, and the development of last scenario is in final stages. The Yale team has provided NEMS modeling results for the abundant natural gas, electrical vehicles, and port electrification 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 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 will be used by our partners in Project 3 for processing and air quality simulation for most economic sectors. This year, as summarized below, a practical method for downscaling NEMS transportation results was tested and implemented; the basic "grow in place" downscaling of all energy sector emissions for four transition scenarios was completed; and the site-and-grow method for EGU emissions was tested and enhanced.

Life Cycle Assessment: During the reporting year, the SEARCH subaward team at Northeastern has incorporated annual emissions reduction rates into the effort on appending hazardous air pollutants to NEMS, based on historical trends and pollution control technology pathways from multiple integrated assessment efforts. We have also initiated a cross-model statistical comparison of characterization factors (fate+transport+damage) for hazardous air pollutants used in the USEtox life cycle impact assessment method adopted by USEPA, in comparison to those derived from the National Air Toxics Assessment. Currently, 147 air toxics have been compared, revealing a one-log difference in characterization factors used for the parameterization of USEtox with North American landscape and demographic features.

Project 2: Assessment of Energy-Related Sources, Factors, and Transitions Using Novel High-Resolution Ambient Air Monitoring Networks and Personal Monitors

The fourth year of Project 2 has focused on the completion of the stationary and portable multipollutant monitor assembly including development of a novel system for on-board calibrations of the stationary monitors (Obj. 1), deployment of 42 nodes of the network to date (Obj. 2), and continued in-field/lab testing, IRB approvals, and preparations for the field measurements of Obj. 3. The first monitor was deployed in October 2018 and we expect all monitors will be deployed by November 30, 2019. Year 4 also included the start of the CACES-SEARCH collaborative project, which is already yielding publications and a successful month-long field and lab campaign in Pittsburgh and Baltimore.

Objective 1:

All electrical systems for the multipollutant monitor were designed, assembled, and tested as reported in previous years. Efforts this year have primarily focused on troubleshooting and developing the patented on-board calibration system. We have also completed troubleshooting for our network design and have high fidelity of the online system. The data assimilation network draws on current collaborations and powerful existing tools (e.g. Grafana). The full set of sensors in the monitors have been tested at sites with reference instrumentation as part of validation efforts and progress towards upcoming publications. Examples have been shown in past reports and presentations, and more are in preparation for upcoming manuscripts (e.g. Figure 3.1). Initial analysis of network data has been used to further evaluate monitor and network performance.

A manuscript describing the detailed laboratory and field evaluation of the Plantower sensor was published in Environmental Science & Technology in 2019. In brief summary, we evaluated three Plantower PMS A003 sensors in controlled laboratory conditions and also residential air over several days and ambient outdoor air in Baltimore, MD over a 1-month period). The PM2.5 sensors exhibited a high degree of precision and R2 values greater than 0.86 for all sources. The three sensors were co-located with reference instruments in downtown Baltimore near a major intersection and showed good agreement over time after adjustment for temperature and humidity effects.

In collaboration with Dr. Abhirup Datta in the Department of Biostatistics and the Quantitative Methods Facility Support Unit, we have been developing a statistical calibration approach that allows us to compare the monitor data with the regulatory monitoring data collected by the Maryland Department of the Environment (MDE) to develop calibrations that would be applicable to all monitors. The method starts with our laboratory-based temperature and humidity corrections, but adds additional terms for temperature and humidity interaction, and binary variables for daylight or nighttime hours and weekday or weekend. When holding out a 10% validation dataset, we find that our root mean square error is reduced to about 3.5 ug/m3 for hourly averages and about 1.5 ug/m3 for daily averages. Moreover, we found good agreement applying the model developed at the Old Town MDE site to data collected at the Essex site, showing the applicability of the statistical model to all monitors. In Levy-Zamora et al. (in prep.), we are also working to improve the accuracy of calibrations through determining the amount of time necessary to improve calibrations through co-locations.

Objective 2:

Previously, we designed a network design strategy that uses weighted random sampling to site monitors. To date, we have installed boxes at 42 of these locations and expect full deployment by November 30, 2019. We have begun analyzing the initial data that has been collected from the SEARCH stationary network. These preliminary analyses have pursued relevant objectives to those in the proposal, as shown in the figures below. Variations in PM2.5 site-to-site correlations for a selection of sites demonstrates convergence in some, but divergence and spatial heterogeneity in others indicating more diversity in sources or other modifying factors. Preliminary source attribution studies with a comparison of tracers provides insights on PM primary vs. secondary sources.

Objective 3:

A Postdoctoral Fellow in Kirsten Kohler's group at JHU was recently awarded an NIH K99/R00 that will add health measures for a subset of participants recruited through Objective 3. This add-on study will allow her to evaluate whether there is a significant association between exposure levels and acute health endpoints and whether this association is modified by mode of transport. Preliminary data has been collected in advance of this full measurement campaign (see above). Portable units will be deployed with study participants starting January 2020, with recruitment and subject survey/interviews starting December 2019. We have made connections with numerous local community and national groups that have an interest in personal exposures and air pollution, which has led to successful recruiting efforts. Calibration protocols and duplicate measurement methods are under development for stationary and personal monitors, both before deployment and in-field calibration (both between units and with in-field zero and span checks).

SEARCH-CACES Collaborative Project:

The collaborative project with the CACES center began in Year 4 with a focus on traditional combustion and non-traditional sources of air pollutants and reactive precursors via a combination of mobile field measurements and laboratory studies on emissions and oxidation chemistry of reactive precursors to secondary pollution. In summary, Year 4 has included: (i) field measurements in Pittsburgh and Baltimore using the CACES mobile van lab that included a novel combination of online (CACES) and offline measurements (SEARCH) of gases and particles, with the mobile lab moving within the high-spatiotemporal measurement networks deployed by SEARCH and CACES; (ii) laboratory studies on emissions, oxidation chemistry, and secondary pollutant formation from non-traditional sources; (iii) related data analysis; and (iv) the preparation and submission of manuscripts achieving the objectives of the collaborative project and SEARCH project 2, including a submitted paper on the emissions of third hand tobacco smoke from contaminated persons into non-smoking environments where occupants are exposed to hazardous organic pollutants (Sheu et al.) and a manuscript in preparation on emissions of complex mixtures of organic gases from non-traditional sources.

Project 3: Improving Projections of the Spatial and Temporal Changes of Multi-Pollutants to Enhance Assessment of Public Health in a Changing World

During this project year, we continued to improve the model performance for the four regional models (i.e., WRF/Chem, WRF-CAM5, WRF/Chem-ROMS, WRF-CMAQ). Based on Year 3 simulation results, we attributed underpredictions in PM2.5 over northwestern U.S. to the underestimation of wildfire emissions. In this project year, we performed 2008-2012 simulations with FINN fire emissions using WRF/Chem. Predicted PM2.5 concentrations increase in most U.S., especially S.E. US and Pacific NW due to higher wildfire emissions from FINN than the NEI. The use of FINN led to a net overall improvement. To address SAC's comment, we have also completed 2008-2012 simulations using offline-coupled WRF and CMAQ and compare it with online WRF-CMAQ. The inclusion of chemistry-meteorology feedbacks reduces domain-wide annual average surface CO by 3.0 ppb (3.1%), O3 by 1.7 ppb (4.1%), PM2.5 by 0.34 mg m-3 (8.6%), and PM10 by 1.1 mg m-3 (11.1%) mainly due to reduction of radiation, temperature, and wind speed. These results indicate that the impacts of chemistry-meteorology feedbacks especially aerosol effects on the U.S. air quality are important in some cases and should be considered in developing future model applications and policy-making.

We have made good progress in processing emission change factors (ECFs) provided by Project 1 under various energy scenarios such as the reference scenario without the clean power plan (refnocpp), the "abundant natural gas" scenario (highNG), the "high electric vehicles" scenario (highEV), and the "port electrification" scenario (port). We completed processing and testing of ECFs for energy and mobile sectors and generated model-ready emissions using these ECFs and SMOKE for future simulations. The combined emission changes are more dominant by mobile sectors for CO, NOx, and VOCs and by energy sectors for SO2 and PM2.5. The projected net emission reductions are ~18040 kton/year (~30.8%), ~3018 kton/year (~27.2%), ~2362 kton/year (~30.1%), ~1017 kton/year (~7.0%), and ~120 kton/year (~4.6%) for CO, NO, SO2, VOCs, and PM2.5 respectively. The preliminary results show large decreases for CO, SO2, NOx, VOCs, and PM2.5 mainly due to their emission reductions. The changes for O3 are more complicated with wide-spread decreases in most areas but increases in northeastern U.S.

SEARCH-CACES Collaborative Project:

For SEARCH-CACES collaboration project on the comparison of health impacts estimated based on complex online models +health model vs. reduced complexity models, we have developed the methodology by performing BenMAP simulations to assess health impacts of O3 and PM2.5 under weather and climate extremes, which will be used in this collaboration project once we complete the simulations under various energy transitions. We have also participated in another SEARCH-CACES collaboration project on the comparison of estimated air pollutants using all models and provided our model results to CACES collaborators.

We have been performing analysis of a set of global simulations with and without wildfire emissions and with and without wildfire induced ecosystem changes performed by unfunded collaborators. Based on the two-way coupled fire-climate-ecosystem simulations, wildfire-induced PM2.5 concentrations are projected to nearly double over NA by the mid-21st century compared to the present. More strikingly, the percentage contribution of wildfire-pollution over the eastern U.S. will surpass that over the western U.S. in the 2050s. This is mainly attributed to increased wildfires in Canada and western U.S. and subsequent downwind transport of their smoke particles. For a wildfire emission-free future, PM2.5 and visibility in most regions are projected to stay below the regulatory standards by the 2050s. However, the improvements in PM2.5 due to regulatory-reductions in anthropogenic emissions are significantly compensated by increases in wildfire emissions, inadvertently reducing the effectiveness of regulatory efforts. In addition, the EPA Haze Index values in a wildfire emission inclusive future are projected to exceed 14 Deci views in the entire boreal Canada, northwestern and eastern U.S., so wildfire-induced pollution can also hamper the regulatory targets of the EPA's Regional Haze Program.

We developed a daily PM2.5 product at 1 × 1 km2 spatial resolution across the eastern U.S. for 2008 - 2012 with the aid of daily WRF/Chem output at 36-km, satellite (MAIAC) AOD data at 1-km, land-use type from the National Land Cover Database at 1-km, and ERA-Interim re-analysis meteorology at 0.125°. The model developed herein generates high-fidelity estimates (r2 = 0.75 using a 10-fold cross-validation) of daily PM2.5 over a large area at a high spatial resolution. WRF/Chem and gap-filled satellite AOD are the two largest contributors to the skill of our model. This 1 × 1 km2 PM2.5 product has been provided to Project 4 for their epidemiological studies. We developed a daily speciated PM2.5 product based on daily output from the above statistical model and daily speciation fractions from WRF/Chem. We intend on comparing these estimates to speciation data from IMPROVE in the future.

Project 4: Human Health Impacts of Energy Transitions: Today and Under a Changing World

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.

A key feature of Project 4 is systematic review and meta-analysis. We continue 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. Weather impacts on human mortality are a critical public health concern with respect to climate change. We are assessing the sensitivity of subpopulations to weather mortality associations in previously published literature, and have completed a systematic search using a MEDLINE/PubMed database for population-based studies of exposure to heat or high temperature, cold, and heat waves. In the past year, we have published two systematic reviews.

SEARCH Collaborative Project:

Other representative projects include a study of the temporal trend in the effect estimates of PM2.5 on hospital admissions. As part of our Collaborative Project with Harvard University, we are working with Joel Schwartz of the Harvard/MIT Center to examine these temporal effects in areas without monitors using Dr. Schwartz's modeled estimates of PM2.5.

Future Activities:

Project 1: Modeling Emissions from Energy Transitions

Modeling transition scenarios in NEMS: Our next steps include completing the final transition scenario on distributed generation + demand response. The results from these scenarios will be passed on to be downscaled.

Downscaling: We will apply the basic growth factor calculation methodology to the fifth (distributed energy resources scenarios) and continue to coordinate with Project 3 on procedures for sharing and conducting QA/QC and downscaled change factors. We will also continue to implement the site-and-grow technique and to ensure the new downscaling methods can be implemented by the air quality simulation team. Issues to be addressed include finalization of methods for projecting unplanned retirements and for determining hourly emissions that are weather-dependent. Anticipating that we will have more NEMS transition runs than will ultimately be analyzed for air quality impacts, our team will develop prioritize which transitions are most significant from a public health perspective. These will likely be scenarios that show relatively larger growth or more significant changes in spatial distribution for ozone precursors and particulate matter.

Life Cycle Assessment: In the coming year, we will publish the methodology for evaluating characterization factors (fate+transport+damage) for hazardous air pollutants used in the USEtox life cycle impact assessment method adopted by USEPA, in comparison to those derived from the National Air Toxics Assessment. The overall intent is to derive new characterization factors for future years to be used in life cycle assessment modeling that is based on the state-of-the-science modeling in the SEARCH Center.

Project 2: Assessment of Energy-Related Sources, Factors, and Transitions Using Novel High-Resolution Ambient Air Monitoring Networks and Personal Monitors

Year 5 of the project will primarily include detailed analysis of the data collected through the fixed stationary network (Objective 2), the personal exposure monitoring study (Objective 3), and the SEARCH-CACES collaborative study. This will include the source apportionment, evaluation of air pollution events, development of new statistical calibration approaches, and a consideration of environmental injustice in Baltimore City. We will also provide data to Project 3 to do a comparison of our network measures and the high-resolution modeling. All IRB approvals will be renewed, as required.

Project 3: Improving Projections of the Spatial and Temporal Changes of Multi-Pollutants to Enhance Assessment of Public Health in a Changing World

We plan to complete final production simulations for the current 5-yr period to obtain the best possible performance for air quality and human exposure studies. We will conduct for a future 5-yr period using projected emissions under future energy transition scenarios to evaluate the impact of projected changes in emissions on future air quality and perform sensitivity simulations considering energy/mobile sectors and climate change. For wildfire emissions, we will implement a machine learning wildfire emissions model in WRF/Chem to evaluate the impacts of climate and land use land cover change on air quality in the U.S. We will analyze WRF/Chem simulations to investigate the relative impacts of climate change and biogenic emission changes on PM2.5 in the U.S. and evaluate the relative contributions of climate change and emission changes on weather extremes and air quality. Finally, we will complete the estimates of daily 1 km speciated PM2.5 in the eastern U.S. using a fusion of WRF/Chem and MAIAC AOD.

Project 4: Human Health Impacts of Energy Transitions: Today and Under a Changing World

In the upcoming year, we plan to complete several meta-analysis projects that are currently ongoing. Work will continue on the coordination with Project 3 to link estimates of air pollution under a changing climate, generated through Project 3's air quality and climate change modeling systems as described above, to epidemiological assessment to estimate the health impacts of increased (or decreased) levels of air pollution. Work is moving forward on the collaborative project, which is a joint effort between Project 4 and the Harvard/MIT Center. This work involves joining estimated PM2.5 concentrations for the continental United States with our models of the long-term temporal change of the association of PM2.5 with risk of hospital admissions for the Medicare population. This collaborative project builds on our original aims, but adds benefit to the Centers' work by allowing inclusion of more suburban and rural areas, as compared to the more urban centers that are more likely to have U.S. government monitors.


Journal Articles: 69 Displayed | Download in RIS Format

Other center views: All 114 publications 69 publications in selected types All 69 journal articles
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Journal Article 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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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article Gentner DR, Xiong F. Tracking pollutant emissions. Nature Geoscience 2017;10(12):883-884.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article Keller JP, Peng RD. Error in estimating area‐level air pollution exposures for epidemiology. Environmetrics 2019;30(8):e2573.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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    R835871 (2017)
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  • Journal Article 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.
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    R835871 (2017)
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  • Journal Article 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.).
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  • Journal Article Son JY, Liu JC, Bell ML. Temperature-related mortality:a systematic review and investigation of effect modifiers. Environmental Research Letters 2019;14(7):073004.
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    R835871 (2019)
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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).
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  • Journal Article Esty DC, ML Bell. Business Leadership in Global Climate Change Responses . American Journal of Public Health2018;108(S2):S80-S84.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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).
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article Baklanov A, Zhang Y. Advances in air quality modeling and forecasting. Global Transitions 2020;2:261-70.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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  • Journal Article 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.
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    R835871 (2019)
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  • Supplemental Keywords:

    energy systems modeling, transportation, life cycle assessment, personal exposure monitoring, personal exposure, air monitoring, regional modeling, air quality, O3, PM2.5, model improvement, sensitivity simulation, climate extremes, wildfire emissions, gap-filling technique, health analysis, NO2, air pollution, temperature

    Relevant Websites:

    Yale- SEARCH Site Exit

    Progress and Final Reports:

    Original Abstract
  • 2016 Progress Report
  • 2017 Progress Report
  • 2018 Progress Report
  • 2020 Progress Report
  • 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