Grantee Research Project Results
2016 Progress Report: Center for Air, Climate, and Energy Solutions (CACES)
EPA Grant Number: R835873Center: Center for Air, Climate, and Energy Solutions
Center Director: Robinson, Allen
Title: Center for Air, Climate, and Energy Solutions (CACES)
Investigators: Robinson, Allen , Pope, Clive Arden , Millet, Dylan B , Marshall, Julian D. , Michalek, Jeremy J. , Azevedo, Inês L , Boies, Adam M. , Pandis, Spyros N. , Coggins, Jay S. , Apte, Joshua S. , Matthews, H. Scott , Burnett, Richard T , Presto, Albert , Hill, Jason , Ezzati, Majid , Brauer, Michael , Donahue, Neil , Muller, Nicholas , Jaramillo, Paulina , Adams, Peter , Polasky, Stephen , Hankey, Steve
Current Investigators: Robinson, Allen , Marshall, Julian D. , Adams, Peter , Apte, Joshua S. , Azevedo, Inês L , Burnett, Richard T , Coggins, Jay S. , Donahue, Neil , Ezzati, Majid , Hankey, Steve , Hill, Jason , Jaramillo, Paulina , Michalek, Jeremy J. , Millet, Dylan B , Muller, Nicholas , Pandis, Spyros N. , Polasky, Stephen , Pope, Clive Arden , Presto, Albert , Boies, Adam M. , Brauer, Michael , Matthews, H. Scott
Institution: Carnegie Mellon University , Health Canada - Ottawa , Imperial College , Virginia Tech , University of British Columbia , University of Minnesota , The University of Texas at Austin , Brigham Young University , Middlebury College
Current Institution: Carnegie Mellon University , Virginia Tech , Brigham Young University , Middlebury College , The University of Texas at Austin , University of Washington , University of Minnesota , University of British Columbia , Health Canada - Ottawa , Imperial College
EPA Project Officer: Chung, Serena
Project Period: May 1, 2016 through April 30, 2021 (Extended to April 30, 2022)
Project Period Covered by this Report: May 1, 2016 through April 30,2017
Project Amount: $10,000,000
RFA: Air, Climate And Energy (ACE) Centers: Science Supporting Solutions (2014) RFA Text | Recipients Lists
Research Category: Airborne Particulate Matter Health Effects , Air , Climate Change , Human Health
Objective:
The Center for Air, Climate, and Energy Solutions (CACES) is a multidisciplinary, multi-institutional research center that is addressing critical questions at the nexus of air, climate, and energy. The Center has overarching themes of regional differences, multiple pollutants, and development and dissemination of tools for air quality impact assessment. Novel measurement and modeling approaches are being applied to understand spatial and temporal differences in human exposures and health outcomes. We are investigating a range of technology and policy scenarios for addressing our nation’s air, climate, and energy challenges, and testing their potential ability to meet policy goals such as improved health outcomes and cost-effectiveness.
The Center is comprised of five thematically and scientifically integrated research projects and one support center. Project 1 is extending existing chemical transport models to high spatial resolution (1 km) with tagged source apportionment and developing a new class of reduced complexity models for air quality and exposure assessment. Project 2 is conducting comprehensive measurements in three cities (Austin, TX; Oakland, CA; and Pittsburgh, PA) to quantify factors influencing gradients in pollutant concentrations and develop mechanistic understanding of how pollutant transformations affect population exposures. Project 3 is developing multi-pollutant land-use regression (LUR) models at high spatial resolution (~0.1 km), national-scale and over multiple decades. Project 4 is using tools developed in other projects to investigate key air, climate, and energy challenges and their interactions focusing on four main elements: electricity generation; transportation; land use; and climate-dependent emissions, transport and chemistry. Project 5 is analyzing nationally representative population-based health data, combined with novel multi-pollutant exposure estimates and source contributions (Projects 1 and 3), to derive new knowledge on multi-pollutant mortality risk and its variability across the United States.
Progress Summary:
Project 1: Mechanistic air quality impact models for assessment of multiple pollutants at high spatial resolution
Project 1 is focused on the development, evaluation and application of mechanistic air quality models, both chemical transport models (CTMs) and reduced-complexity models (RCMs). Major activities in the past reporting period included:
- Historical modeling of exposure to PM2.5 and related pollutants (1980-2015) for the continental United States. During this project period research focused on the development of emissions inventories and meteorological inputs for the historical simulations. Records from 1980 to present of dozens of spatially-resolved activity indicators (e.g., vehicle-miles traveled, acres of agricultural tillage, BTUs of power plant output) have been compiled. Published and measured emission factors have been gathered and compared.
- High-resolution (1 km) modeling of present-day air quality. During this project period research focused on developing high spatial resolution inventories for mobile and cooking sources for Pittsburgh. Using restaurant location data from the Google Places API, we have obtained restaurant data for the Pittsburgh Combined Statistical Area (CSA). Using these data, we demonstrated that the population density (the standard activity surrogate for cooking) is not well correlated with restaurant density at high spatial scales.
- Development of Reduced-Complexity Models (RCMs). During this project period significant progress was made on the development of three RCMs: AP2, EASIUR, and InMap. This included improved treatments of nitrate aerosol in AP2, creation of a source-receptor version of EASIUR, and development of a neural-network based chemical mechanism emulator for InMAP.
- Evaluation of Reduced-Complexity Models (RCMs). During this project period, we compared among the three models the marginal social costs of SO2, NOx, NH3, and inert primary PM2.5 ground-level emissions in each county in the continental United States. We also evaluated all three models using ambient air quality data. Despite fundamental structural differences among the three models, predicted marginal social costs are generally within the same order of magnitude and usually within a factor of 2 or 3. The agreement varies with the complexity of the chemistry that links the emissions to their equivalent ambient PM2.5 concentrations; predictions are most similar for primary PM2.5 and most different for NOx and NH3. Even with these differences, the three models generate robust rankings of national-level air quality policies based on social costs and benefits summed across pollutants and geographical locations.
Project 2: Air quality observatory
Project 2 is collecting and analyzing air quality observations to characterize spatial (intra-city, urban-to-rural, and inter-city) and temporal distributions of multiple air pollutant species in three cities. Major activities in the past reporting period included:
- Evaluate performance of low-cost RAMP monitors. Real-time Affordable Multi-Pollutant (RAMP) monitors measure CO, NO2, SO2, O3, and CO2 using low cost-sensors. Nineteen RAMPs were tested via co-location with the supersite on the Carnegie Mellon University campus and through laboratory calibration. We developed and evaluated three calibration strategies: a standard laboratory calibration; an empirical ambient calibration using a multi-linear regression that included sensor voltage, temperature, and RH as independent variables; and a machine-learning based calibration. The machine learning algorithm performs the best; using it, every RAMP monitor evaluated meets the U.S. EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. We also demonstrated that a 4-week co-location period prior to deployment provides sufficient data for calibration model building.
- Perform case studies of modifiable factors. We deployed RAMPs and additional instrumentation to create a monitoring network to investigate spatial and temporal patterns of air pollution in Pittsburgh. This network was used to conduct two multi-month case studies: (i) urban-rural transect and (ii) downtown business district (high traffic area with street canyons).
- High spatial mobile monitoring around air pollution sources. To complement the network of fixed sites, in-motion sampling with a mobile laboratory equipped with an aerosol mass spectrometer (AMS) and other instrumentation was used to characterize concentrations of a suite of air pollutants at high spatial resource around roads, restaurants, and other sources in Pittsburgh. This monitoring shows greatly elevated (up to a factor of 10) organic aerosol concentrations up to several hundred meters downwind of many restaurants. In contrast, organic aerosol concentrations on heavily-congested highways and other traffic dominated areas are only modestly higher than the urban background. This highlights the importance of cooking as a source for local exposures, especially given that restaurants often are located in residential neighborhoods.
Project 3: Next generation LUR models: Development of nationwide modeling tools for exposure assessment and epidemiology
Project 3 is developing national scale, high spatial resolution (1 km), multi-pollutant (PM2.5, NO2, O3, CO, and subspecies of PM2.5) empirical models of air pollutant concentrations for use in health analysis and investigation of the influence of modifiable factors on human exposure. Major activities in the past reporting period included:
- Data compilation: We completed the assembly and processing of the necessary air pollution and geographic data for the development of empirical air pollution models.
- Development of modeling framework: Our modeling approach employs 2-stage partial least squares (PLS) + Universal Kriging to estimate annual average concentrations. PLS leverages predictive information from a large number of geographic covariates with less concern for model overfitting, while also limiting the impact of geographic covariate outliers. Making predictions at ~8-10 million Census block centroids for 6+ pollutants and 36 years (1980-2015) is a computationally intensive task. Employing PostGIS and parallel processing, we are able to calculate our geographic covariates at all Census block centroids in ~20 days on a 10-node server. The improvement in processing of covariates with PostGIS (~100× faster than our previously published models using Python and ArcGIS) has dramatically improved our (and other researchers) ability to make fine-scale spatial predictions over very large geographic scales.
- Preliminary model building: Preliminary national-scale land use regression (LUR) models have been developed for PM2.5 (1999-2015), NO2 (1979-2015), SO2 (1979-2015), O3 (1979-2015), and CO (1990-2015). The preliminary PM2.5 models exhibit good performance across all years (CV-R2: 0.72-0.90). Preliminary NO2 models exhibit good performance for years 1981-2014 (CV-R2: 0.73-0.89, CCV-R2: 0.45-0.76). Preliminary O3 models exhibit good performance for years 1990-2014 (CV-R2: 0.69-0.79, CCV-R2: 0.52 -0.71), but much poorer performance prior to 1989 (CV-R2: 0.51-0.66, CCV-R2: 0.09-0.39). Preliminary SO2 and CO models exhibit poor-to-moderate model performance. Initial model results for PM2.5 and NO2 have been provided to Project 5 to begin working through linking exposure estimates with health data.
Project 4: Air pollutant control strategies in a changing world
Project 4 is applying chemical transport and reduced-form air quality models to assess the air quality and health impacts of various technology, policy, land-use, and climate scenarios. Major activities in the past reporting period included:
- United States economy-wide PM2.5 damages: We estimated air quality-related health effects for each of 428 sectors of the U.S. economy, the largest fractions of which were physically produced by electricity generation but induced by demand for manufactured goods. This alternative framing of air-quality related health impacts, which reveals the embodied health impacts of economic consumption, offers novel opportunities for strategies of air quality improvement. We used this new framework to explore health equity effects by economic sector, finding that Hispanic and Black populations are disproportionately impacted by electricity generation for manufacturing.
- Greenhouse gas and criteria air pollutant emissions under future policy scenarios: We are comparing the economic efficiency of homogeneous versus heterogeneous air pollution regulations in the presence and absence of greenhouse gas regulations in the United States. Homogeneous regulations treat all emissions the same (what is currently in the United States) versus heterogeneous regulations that vary according to the magnitude of damage caused by the emission of a specific species in a specific location.
- Air pollution impacts of corn production: Using a life-cycle impact analysis and reduced complexity models, we performed spatially explicit analysis to estimate the damages of corn production. We estimate mean damages of $3.27/bu of corn produced in the United States, with 65% from ammonia emissions. Ammonia damages are more than six times larger than damages from GHG emissions. Spatial variation of damages is large, with the least damaging 5% of corn produced with damages less than $1.56/bu, and the most damaging 5% of corn produced with damages more than $6.17/bu.
- VSL and mortality risk age adjustments: We estimated the impact of including age differences in both the value of statistical life (VSL) and the risk of mortality. When we adjust both the VSL and mortality risk by age the total damages are lower than without an age adjustment, but not dramatically lower as conventional wisdom and past estimates indicate.
- Controlling secondary organic aerosol (SOA) production from gasoline vehicle emissions: We found a strongly nonlinear relationship between SOA formation from gasoline vehicle exhaust and the atmospheric ratio of non-methane-organic-gas-to-NOx (NMOG:NOx). We investigated the implications of this relationship for the Los Angeles area. Although organic gas emissions from gasoline vehicles in Los Angeles are expected to fall by almost 80% over the next two decades, we predict no reduction in SOA production due to the effects of rising NMOG:NOx on SOA yields. This highlights the importance of integrated emission control policies for NOx and organic gases.
Project 5: Health effects of air pollution and mitigation scenarios
Project 5’s specific aims include (1) estimate multi-pollutant mortality risk surfaces using two large, unique, population-based U.S. datasets and (2) explore regional and temporal variability in those risk surfaces. Major activities in the past reporting period included:
- Analysis of National Health Interview Survey (NHIS) data: We have conducted a preliminary/preparatory study that evaluated associations between long-term PM2.5 exposure and mortality risk using cohorts of the U.S. adult population constructed from public-use NHIS data. Mortality hazard ratios (HRs) were estimated using Cox proportional hazards regression models, controlling for age, race, sex, income, marital status, education, body mass index, and smoking status. Estimated HRs for all-cause and cardiovascular mortality, associated with a 10 µg/m3 exposure increment of PM2.5, were 1.06 (1.01-1.11) and 1.34 (1.21-1.48), respectively, in models that controlled for various individual risk factors including smoking. This preliminary study demonstrates that the NHIS survey data with mortality linkage can be effectively used to evaluate mortality associations with air pollution.
- County-level mortality space-time study: We have established a time consistent set of data for 3,082 counties (essentially the entire continental U.S.) and carried out test analyses for a suite of models using age- and county-specific death rates based on national mortality and population data.
The Administrative Core provides overall oversight, coordination, and integration of the Center. Since initial funding of the Center, the Administrative Core has developed a quality management structure, which is detailed in the EPA-approved Quality Management Plan. An 11 member Science Advisory Committee was selected and the first annual meeting was held in January 2017 in Pittsburgh. An in-person center meeting was held in September 2016 in Pittsburgh. Finally, the Administrative Core has organized monthly conference calls of the project Executive Committee and weekly to monthly calls for groups of investigators for project-specific meetings.
Future Activities:
Project 1: Mechanistic air quality impact models for assessment of multiple pollutants at high spatial resolution
- Complete and evaluate historical modeling of criteria pollutants for the 1980 to 2015 time period. The results will be passed to Projects 3 and 5.
- Complete the 1 km emissions inventories and modeling for Pittsburgh, evaluating the ability of CTMs to predict intraurban pollution variability against observations collected as part of Project 2.
- Continue enhancements of RCMs including extension of EASIUR to include social cost estimates for VOCs and enhancements to the treatment of difficult species like nitrate PM2.5 will be completed for AP2 and InMAP.
Project 2: Air quality observatory
- Deploy a 50-location, low-cost monitor network in Pittsburgh.
- Conduct mobile sampling in a high exposure, environmental justice area near the port of Oakland in Oakland, CA to quantify magnitude and sources of hotspots of fine particulate matter.
- Measure emission factors from restaurants in Pittsburgh area using mobile measurements and tracer flux techniques.
- Provide quality assured high resolution air quality data collected in Pittsburgh to Projects 1 and 3 for model evaluation.
Project 3: Next generation LUR models: development of nationwide modeling tools for exposure assessment and epidemiology
- Continue model development to assess the geographic covariates selected into each model, particularly for poorer performing pollutants and years.
- Provide Project 5 census block centroid estimates for all years (1980-2015), and county-level population-weighted estimates for years 1982-2013 to correspond with National Center for Health Statistics (NCHS) county mortality data.
Project 4: Air pollutant control strategies in a changing world
- Expand on the EPA US-TIMES model by incorporating region and sector-specific emissions damage values derived from the Estimating Air pollution Social Impact Using Regression (EASIUR) and the Air Pollution Emission Experiments and Policy analysis (AP2) models.
- Evaluate air quality scenarios associated with climate-dependent biogenic and wildfire emissions.
- Perform simulations with PMCAMx for 2050 to evaluate applicability of future-day EASIUR to future scenarios.
Project 5: Health effects of air pollution and mitigation scenarios
- Complete proposal/application to Research Data Center (RDC) to access NHIS data.
- Link CACES generated estimates for census block of residence to health data allowing for much greater spatial resolution.
- Perform preliminary health analyses using linked health and CACES exposure estimates.
Journal Articles: 136 Displayed | Download in RIS Format
| Other center views: | All 148 publications | 136 publications in selected types | All 136 journal articles |
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Bechle MJ, Millet DB, Marshall JD. Does urban form affect urban NO2 ? Satellite-based evidence for more than 1200 cities. Environmental Science & Technology 2017;51(21):12707-12716. |
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Bennett JE, Tamura-Wicks H, Parks RM, Burnett RT, Pope III CA, Bechle MJ, Marshall JD, Danaei G, Ezzati M. Particulate matter air pollution and national and county life expectancy loss in the USA: A spatiotemporal analysis. PLoS medicine. 2019 Jul;16(7). |
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Chambliss SE, Pinon CPR, Messier KP, LaFranchi B, Upperman CR, Lunden MM, Robinson AL Marchall, JD Apte, JS.Local-and regional-scale racial and ethnic disparities in air pollution determined by long-term mobile monitoring.PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE OF AMERICA 2021;118(37):e2109249118 |
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Clark LP, Millet DB, Marshall JD. Changes in transportation-related air pollution exposures by race-ethnicity and socioeconomic status:outdoor nitrogen dioxide in the United States in 2000 and 2010. Environmental Health Perspectives 2017;125(9):097012 (10 pp.). |
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Clark M, Hill J, Tilman D. The diet, health,and environment.Annual Review of Environment and Resources 2019; 43:109–134 |
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Drosatou AD, Skyllakou K, Theodoritsi GN, Pandis SN. Positive matrix factorization of organic aerosol:Insights from a chemical transport model. Atmospheric Chemistry and Physics 2019;19:973–86. |
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Fantke P, McKone TE, Tainio M, Jolliet O, Apte JS, Stylianou KS, et al. Global effect factors for exposure to fine particulate matter. Environmental Science & Technology 2019;53:6855–68 |
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Gilmore EA, Heo J, Muller NZ, Tessum CW, Hill J, Marshall J, Adams PJ. An inter-comparison of air quality social cost estimates from reduced-complexity models. Environmental Research Letters. 2019 Apr 18. |
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Giordano M, Mailings C, Pandis S, Presto A, McNiell V, Wetervelt D, Beekman M, Subrgamanian R. From low-cost sensors to high-quality data:A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors. JOURNAL OF AEROSOL SCIENCE 2021;158. |
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Goodkind AL, Tessum CW, Coggins JS, Hill JD, Marshall JD. Fine-scale damage estimates of particulate matter air pollution reveal opportunities for location-specific mitigation of emissions. Proceedings of the National Academy of Science 2019;116(18):8775-8780 |
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Gordon TD, Presto AA, Nguyen NT, Robertson WH, Na K, Sahay KN, Zhang M, Maddox C, Rieger P, Chattopadhyay S, Maldonado H, Maricq MM, Robinson AL. Secondary organic aerosol production from diesel vehicle exhaust: impact of aftertreatment, fuel chemistry and driving cycle. Atmospheric Chemistry and Physics 2014;14(9):4643-4659. |
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Gu P, Li HZ, Ye Q, Robinson ES, Apte JS, Robinson AL, Presto AA. Intracity variability of particulate matter exposure is driven by carbonaceous sources and correlated with land-use variables. Environmental Science & Technology 2018; 52:11545–11554 |
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Robinson ES, Gu P, Ye Q, Li HZ, Shah RU, Apte JS, Robinson AL, Presto AA. Restaurant impacts on outdoor air quality:Elevated organic aerosol mass from restaurant cooking with neighborhood-scale plume extents. Environmental Science & Technology 2018; 52:9285-9294 |
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Hankey S, Lindsey G, Marshall JD. Population-level exposure to particulate air pollution during active travel: planning for low-exposure, health-promoting cities. Environmental Health Perspectives 2017;125(4):527-534. |
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Hankey S, Marshall JD. Urban form, air pollution, and health. Current Environmental Health Reports 2017;4(4):491-503. |
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Heo J, Adams PJ, Gao HO. Public health costs accounting of inorganic PM2.5 pollution in metropolitan areas of the United States using a risk-based source-receptor model. Environment International 2017;106:119-126. |
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Hill J, Goodkind A, Tessum C, Thakrar S, Tilman D, Polasky S, Smith T, Hunt N, Mullins K, Clark M, Marshall J. Air-quality-related health damages of maize. Nature Sustainability2019:2;397-403 |
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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. |
R835873 (2020) R835871 (2021) |
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Jain S, Presto A, Zimmerman N. Spatial Modeling of Daily PM2.5, NO2, and CO Concentrations Measured by a Low-Cost Sensor Network:Comparison of Linear, Machine Learning, and Hybrid Land Use Models. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021;55(13):8631-8641. |
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Kaltsonoudis C, Kostenidou E, Louvaris E, Psichoudaki M, Tsiligiannis E, Florou K, Liangou A, Pandis SN. Characterization of fresh and aged organic aerosol emissions from meat charbroiling. Atmospheric Chemistry and Physics 2017;17(11):7143-7155. |
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Kelp M, Gould T, Austin E, Marshall JD, Yost M, Simpson C, Larson T. Sensitivity analysis of area-wide, mobile source emission factors to high-emitter vehicles in Los Angeles. Atmospheric Environment 2020;223:117212 |
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Lane HM, Morello-Frosch R, Marshall JD, Apte JS. Historical redlining is associated with present-day air pollution disparities in U.S. cities. Environmental Science \amp; Technology Letters 2022. doi:10.1021/acs.estlett.1c01012. |
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Li HZ, Dallmann TR, Li X, Gu P, Presto AA. Urban organic aerosol exposure:spatial variations in composition and source impacts. Environmental Science & Technology 2018;52(2):415-426. |
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Li HZ, Gu P, Ye Q, Zimmerman N, Robinson ES, Subramanian R, Apte JS, Robinson AL, Presto AA. Spatially dense air pollutant sampling:Implications of spatial variability on the representativeness of stationary air pollutant monitors. Atmospheric Environment:X. 2019 Apr 1;2:100012. |
R835873 (2018) R835873 (Final) R836286 (2018) R836286 (2019) |
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Liu L, Hwang T, Lee S, Ouyang Y, Lee B, Smith SJ, Tessum CW, Marshall JD, Yan F, Daenzer K, Bond TC. Health and climate impacts of future United States land freight modelled with global-to-urban models. Nature Sustainability 2019;2:105; doi:10.1038/s41893-019-0224-3. |
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Malings C, Westervelt DM, Hauryliuk A, Presto AA, Grieshop A, Bittner A, Beekmann M, R. Subramanian. Application of low-cost fine particulate mass monitors to convert satellite aerosol optical depth to surface concentrations in North America and Africa. Atmospheric Measurement Techniques 2020;13:3873–92. doi:10.5194/amt-13-3873-2020. |
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Messier KP, Chambliss SE, Alvarez RA, Brauer M, Choi JJ, Hamburg SP, Kerckhoffs J, LaFranchi B, Lunden MM, Marshall JD, Portier CJ, Roy A, Szpiro AA, Vermeulen RCH, Apte JS. Mapping air pollution with Google Street View cars:Efficient approaches with mobile monitoring and land use regression. Environmental Science & Technology 2018;52:12563-12572 |
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Muller NZ, Jha A. Does environmental policy affect scaling laws between population and pollution? Evidence from American metropolitan areas. PLoS One 2017;12(8):e0181407 (15 pp.). |
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Muller NZ, Matthews PH, Wiltshire-Gordon V. The distribution of income is worse than you think: including pollution impacts into measures of income inequality. PLoS ONE 2018;13(3):e0192461 (15 pp.). |
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Muller NZ. Environmental benefit-cost analysis and the national accounts. Journal of Benefit-Cost Analysis 2018;9(1):27-66. |
R835873 (2017) R835873C004 (2016) |
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Nguyen NP, Marshall JD. Impact, efficiency, inequality, and injustice of urban air pollution: variability by emission location. Environmental Research Letters 2018;13(2):024002 (9 pp.). |
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Paolella DA, Tessum CW, Adams PJ, Apte JS, Chambliss S, Hill J, Muller NZ, Marshall JD. Effect of model spatial resolution on estimates of fine particulate matter exposure and exposure disparities in the United States. Environmental Science & Technology Letters 2018;5(7):436-441. |
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Parks RM, Bennett JE, Foreman KJ, Toumi R, Ezzati M. National and regional seasonal dynamics of all-cause and cause-specific mortality in the USA from 1980 to 2016. eLife 2018; 7:e35500. |
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Pope III CA, Ezzati M, Cannon JB, Allen RT, Jerrett M, Burnett RT. Mortality risk and PM2.5 air pollution in the USA: An analysis of a national prospective cohort. Air Quality, Atmosphere & Health 2018;11(3):245-252. |
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Pope III CA, Lefler JS, Ezzati M, Higbee JD, Marshall JD, Kim SY, Bechle M, Gilliat KS, Vernon SE, Robinson AL, Burnett RT. Mortality Risk and Fine Particulate Air Pollution in a Large, Representative Cohort of US Adults. Environmental health perspectives. 2019 Jul 24;127(7):077007. |
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Robinson ES, Shah RU, Messier K, Gu P, Li HZ, Apte JS, Robinson AL, Presto AA. Land-use regression modeling of source-resolved aerosol components from mobile Sampling. Environmental Science & Technology 2019; 53(15):8925-8937 |
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Saha PK, Robinson ES, Shah RU, Zimmerman N, Apte JS, Robinson AL, Presto AA. Reduced ultrafine particle concentration in urban air: Changes in nucleation and anthropogenic emissions. Environmental Science & Technology 2018;52(12):6798-6806. |
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Saha PK, Zimmerman N, Malings C, Hauryliuk A, Li Z, Snell L, Subramanian R, Lipsky E, Apte JS, Robinson AL, Presto AA. Quantifying high-resolution spatial variations and local source impacts of urban ultrafine particle concentrations. Science of the Total Environment. 2019; 655:473-81 |
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Saha PK, Li HZ, Apte JS, Robinson AL, Presto AA. Urban ultrafine particle exposure assessment with land-use regression:Influence of sampling strategy. Environmental Science & Technology 2019; 53:7326-7336 |
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Sergi B, Davis A, Azevedo I. The effect of providing climate and health information on support for alternative electricity portfolios. Environmental Research Letters 2018;13(2):024026 (10 pp.). |
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Shah RU, Robinson ES, Gu P, Robinson AL, Apte JS, Presto AA. High spatial resolution mapping of aerosol composition and sources in Oakland, California using mobile aerosol mass spectrometry. Atmospheric Chemistry and Physics 2018; 18(22):16325–16344 |
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Skyllakou K, Rivera PG, Dinkelacker B, Karnezi E, Kioutsioukis I, Hernandez C, Adams PJ, Pandis SN. Changes in PM2.5 concentrations and their sources in the US from 1990 to 2010. Atmospheric Chemistry and Physics ;21(22):17115-17132. |
R835873 (2020) |
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Tessum CW, Hill JD, Marshall JD. InMAP: a model for air pollution interventions. PLoS ONE 2017;12(4):e0176131 (26 pp.). |
R835873 (2016) R835873 (2017) R835873 (2018) R835873C001 (2016) |
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Tessum CW, Hil JD, Marshall JD. InMAP:A model for air pollution interventions. PLoS ONE 12, e0176131, 0.1371/journal.pone.0176131, 2017. |
R835873 (Final) R835873C001 (2016) |
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Tessum CW, Apte JS, Goodkind AL, Muller NZ, Mullins KA, Paolella DA, Polasky S, Springer NP, Thakrar SK, Marshall JD, Hill JD. Inequity in consumption of goods and services adds to racial–ethnic disparities in air pollution exposure. Proceedings of the National Academy of Sciences of the United States of America 2019; 116 (13):6001-6006 |
R835873 (2018) R835873 (Final) |
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Thakrar SK, Goodkind AL, Tessum CW, Marshall JD, Hill JD. Life cycle air quality impacts on human health from potential switchgrass production in the United States. Biomass and Bioenergy 2018;114:73-82. |
R835873 (2017) R835873 (2018) R835873 (Final) |
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Thind MPS, Wilson EJ, Azevedo IL, Marshall JD. Marginal emissions factors for electricity generation in the Midcontinent ISO. Environmental Science & Technology 2017;51(24):14445–14452. |
R835873 (2017) R835873 (2018) R835873 (Final) |
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Tschofen P, Azevedo IL, Muller NZ. Fine particulate matter damages and value added in the United States economy. Proceedings of the National Academies of Science 2019; 116(40):19857-19862 |
R835873 (2018) R835873 (Final) |
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Vaishnav P, Horner N, Azevedo IL. Was it worthwhile? Where have the benefits of rooftop solar photovoltaic generation exceeded the cost? Environmental Research Letters 2017;12(9):094015 (14 pp.). |
R835873 (2017) R835873 (2018) R835873 (Final) R833864 (Final) |
Exit Exit Exit |
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Weis A, Jaramillo P, Michalek J. Consequential life cycle air emissions externalities for plug-in electric vehicles in the PJM interconnection. Environmental Research Letters 2016;11(2):024009 (12 pp.). |
R835873 (2016) R835873 (2017) R835873 (2018) R835873C001 (2016) R835873C004 (2016) |
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Ye Q, Gu P, Li HZ, Robinson ES, Lipsky E, Kaltsonoudis C, Lee AKY, Apte JS, Robinson AL, Sullivan RC, Presto AA, Donahue NM. Spatial variability of sources and mixing state of atmospheric particles in a metropolitan area. Environmental Science & Technology 2018;52(12):6807-6815. |
R835873 (2017) R835873 (2018) R835873 (Final) |
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Ye Q, Li HZ, Gu P, Robinson ES, Apte, Sullivan Ryan C., Robinson Allen L., Donahue Neil M., Presto Albert A. Moving beyond fine particle mass:High-spatial resolution exposure to source-resolved atmospheric particle number and chemical mixing state. Environmental Health Perspectives 2020;128:017009. doi:10.1289/EHP5311. |
R835873 (2019) R835873 (Final) |
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Zakoura M, Pandis SN. Overprediction of aerosol nitrate by chemical transport models: the role of grid resolution. Atmospheric Environment 2018;187:390-400. |
R835873 (2017) R835873 (2018) R835873 (Final) |
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Zhao Y, Saleh R, Saliba G, Presto AA, Gordon TD, Drozd GT, Goldstein AH, Donahue NM, Robinson AL. Reducing secondary organic aerosol formation from gasoline vehicle exhaust. Proceedings of the National Academy of Sciences of the United States of America 2017;114(27):6984-6989. |
R835873 (2016) R835873 (2017) R835873 (2018) R835873 (Final) R835873C001 (2016) R835873C004 (2016) |
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Zimmerman N, Presto AA, Kumar SPN, Gu J, Hauryliuk A, Robinson ES, Robinson AL, Subramanian R. A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring. Atmospheric Measurement Techniques 2018;11(1):291-313. |
R835873 (2017) R835873 (2018) R835873 (Final) R836286 (2017) R836286 (2018) R836286 (2019) |
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Zimmerman N, Presto AA, Kumar SPN, Gu J, Hauryliuk A, Robinson ES, Robinson AL, Subramanian R. Closing the gap on lower cost air quality monitoring:machine learning calibration models to improve low-cost sensor performance. Atmospheric Measurement Techniques Discussions August 2017 [In review]. |
R835873 (2016) R836286 (2016) |
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Apte JS, Brauer M, Cohen AJ, Ezzati M, Pope CA. Ambient PM2.5 reduces global and regional life expectancy. Environmental Science & Technology Letters 2018;5:546–51. |
R835873 (2019) R835873 (Final) |
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Lu Q, Zhao Y, Robinson AL. Comprehensive organic emission profiles for gasoline, diesel, and gas-turbine engines including intermediate and semi-volatile organic compound emissions. Atmospheric Chemistry and Physics 2018;18:17637–54; doi:10.5194/acp-18-17637-2018. |
R835873 (2019) R835873 (Final) |
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Knibbs LD, van Donkelaar A, Martin RV, Bechle MJ, Brauer M, Cohen DD, Cowie CT, Dirgawati M, Guo Y, Hanigan IC, Johnston FH, Marks, GB, Marshal JD, Pereira G, Jalaludin B, Heyworth JS, Morgan GG, Barnett AG. Satellite-based land-use regression for continental-scale long-term Ambient PM2.5M exposure assessment in Australia. Environmental Science & Technology 2018;52:12445–55 |
R835873 (2019) R835873 (Final) |
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Zhao Y, Lambe AT, Saleh R, Saliba G, Robinson AL. Secondary organic aerosol production from gasoline vehicle exhaust:Effects of engine technology, cold start, and emission certification standard. Environmental Science & Technology 2018;52:1253–61. doi:10.1021/acs.est.7b05045. |
R835873 (Final) |
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Lefler JS, Higbee JD, Burnett RT, Ezzati M, Coleman NC, Mann DD, Marshall JD, Bechle M, Wang Y, Robinson AL, Pope, CA. Air pollution and mortality in a large, representative U.S. cohort:multiple-pollutant analyses, and spatial and temporal decompositions. Environmental Health 2019; 18:101 |
R835873 (2019) R835873 (Final) |
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Mayfield EN, Cohon JL, Muller NZ, Azevedo IML, Robinson AL. Cumulative environmental and employment impacts of the shale gas boom. Nature Sustainability 2019;2:1122–31. doi:10.1038/s41893-019-0420-1. |
R835873 (Final) |
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Tanzer R, Malings C, Hauryliuk A, Subramanian R, Presto AA. Demonstration of a Low-Cost Multi-Pollutant Network to Quantify Intra-Urban Spatial Variations in Air Pollutant Source Impacts and to Evaluate Environmental Justice. International Journal of Environmental Research and Public Health. 2019 Jan;16(14):2523. |
R835873 (Final) R836286 (2018) |
Exit Exit |
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Tanzer R, Malings C, Hauryliuk A, Subramanian R, Presto AA. Demonstration of a low-cost multi-pollutant network to quantify intra-urban spatial variations in air pollutant source impacts and to evaluate environmental justice. International Journal of Environmental Research and Public Health 2019;16:2523. doi:10.3390/ijerph16142523. |
R835873 (2019) R836286 (2019) |
Exit Exit |
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Ward JW, Michalek JJ, Azevedo IL, Samaras C, Ferreira P. Effects of on-demand ridesourcing on vehicle ownership, fuel consumption, vehicle miles traveled, and emissions per capital in U.S. States. Transportation Research Part C:Emerging Technologies 2019;108:289–301. doi:10.1016/j.trc.2019.07.026. |
R835873 (2019) R835873 (Final) |
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Dimanchev EG, Paltsev S, Yuan M, Rothenberg D, Tessum CW, Marshall JD, Selin NE. Health co-benefits of sub-national renewable energy policy in the US. Environmental Research Letters 2019;14(8):085012 |
R835873 (2019) R835873 (Final) R835872 (2018) R835872 (2019) R835872C005 (Final) |
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Zakoura M, Pandis SN. Improving fine aerosol nitrate predictions using a Plume-in-Grid modeling approach. Atmospheric Environment 2019;215:116887. doi:10.1016/j.atmosenv.2019.116887. |
R835873 (2019) R835873 (Final) |
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Lu T, Lansing J, Zhang W, Bechle MJ, Hankey S. Land use regression models for 60 volatile organic compounds:Comparing Google Point of Interest (POI) and city permit data. Science of The Total Environment 2019;677:131–41; doi:10.1016/j.scitotenv.2019.04.285. |
R835873 (2019) R835873 (Final) |
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Clark MA, Springmann M, Hill J, Tilman D. Multiple health and environmental impacts of foods. Proceedings of the National Academy of Sciences of the United States of America 2019;116:23357–62 |
R835873 (2019) R835873 (Final) |
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Xu H, Bechle MJ, Wang M, Szpiro AA, Vedal S, Bai Y, Marshall JD. National PM2.5 and NO2 exposure models for China based on land use regression, satellite measurements, and universal kriging. Science of The Total Environment 2019;655:423–33. doi:10.1016/j.scitotenv.2018.11.125. |
R835873 (2019) R835873 (Final) |
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Mayfield EN, Cohon JL, Muller NZ, Azevedo IML, Robinson AL. Quantifying the social equity state of an energy system:environmental and labor market equity of the shale gas boom in Appalachia. Environmental Research Letters 2019;14:124072. doi:10.1088/1748-9326/ab59cd. |
R835873 (Final) |
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Sergi B, Azevedo I, Xia T, Davis A, Xu J. Support for emissions reductions based on Immediate and long-term pollution exposure in China. Ecological Economics2019;158:26–33. doi:10.1016/j.ecolecon.2018.12.009. |
R835873 (Final) |
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Muller NZ. The derivation of discount rates with an augmented measure of income. Journal of Environmental Economics and Management 2019;95:87–101. doi:10.1016/j.jeem.2019.02.007. |
R835873 (2019) R835873 (Final) |
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Alotaibi R, Bechle M, Marshall JD, Ramani T, Zietsman J, Nieuwenhuijsen MJ, Khreis H. Traffic related air pollution and the burden of childhood asthma in the contiguous United States in 2000 and 2010. Environment International 2019;127:858–67. |
R835873 (2019) R835873 (Final) |
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Eilenberg SR, Subramanian R, Malings C, Hauryliuk A, Presto AA, Robinson AL. Using a network of lower-cost monitors to identify the influence of modifiable factors driving spatial patterns in fine particulate matter concentrations in an urban environment. Journal of Exposure Science & Environmental Epidemiology 2020;30(6):949-61. |
R835873 (2020) R835873 (Final) R836286 (Final) |
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Kelp MM, Jacob DJ, Kutz JN, Marshall JD, Tessum CW. Toward stable, general machine-learned models of the atmospheric chemical system. Journal of Geophysical Research-Atmospheres 2020;125:e2020JD032759. |
R835873 (2020) R835873 (Final) R840012 (2021) R840012 (2022) R840012 (2023) R840012 (Final) R840014 (2023) R840014 (Final) |
Exit Exit |
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Zimmerman N, Li HZ, Ellis A, Hauryliuk A, Robinson ES, Gu P, Shah RU, Ye Q, Snell L, Subramanian R, Robinson AL, Apte JS, Presto AA. Improving correlations between land use and air pollutant concentrations using wavelet analysis:Insights from a low-cost sensor network. Aerosol Air Quality Resesearch 2020;20:314–28. doi:10.4209/aaqr.2019.03.0124. |
R835873 (2019) R835873 (Final) R836286 (2019) |
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Fabisiak JP, Jackson EM, Brink LL, Presto AA. A risk-based model to assess environmental justice and coronary heart disease burden from traffic-related air pollutants. Environ Health 2020;19:34 |
R835873 (2019) R835873 (Final) |
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Parks RM, Bennett JE, Tamura-Wicks H, Kontis V, Toumi R, Danaei G, Ezzati M. Anomalously warm temperatures are associated with increased injury deaths. Nature Medicine 2020;26:65–70. doi:10.1038/s41591-019-0721-y. |
R835873 (2019) R835873 (Final) |
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Kim S-Y, Bechle M, Hankey S, Sheppard L, Szpiro AA, Marshall JD. Concentrations of criteria pollutants in the contiguous U.S., 1979 – 2015:Role of prediction model parsimony in integrated empirical geographic regression. PLOS ONE 2020;15:e0228535 |
R835873 (2019) R835873 (Final) |
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Goodkind AL, Jones BA, Berrens RP. Cryptodamages:Monetary value estimates of the air pollution and human health impacts of cryptocurrency mining. Energy Research & Social Science 2020;59:101281 |
R835873 (2019) R835873 (Final) |
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Malings C, Tanzer R, Hauryliuk A, Saha PK, Robinson AL, Presto AA, Subramanian R. Fine particle mass monitoring with low-cost sensors:Corrections and long-term performance evaluation. Aerosol Science and Technology 2020;54:160–74. doi:10.1080/02786826.2019.1623863. |
R835873 (2019) R835873 (Final) R836286 (2018) R836286 (2019) |
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Pope CA, Coleman N, Pond ZA, Burnett RT. Fine particulate air pollution and human mortality:25+ years of cohort studies. Environmental Research 2020;183:108924. doi:10.1016/j.envres.2019.108924. |
R835873 (2019) R835873 (Final) |
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Coleman NC, Burnett RT, Ezzati M, Marshall JD, Robinson AL, Pope CA. Fine particulate matter exposure and cancer incidence:Analysis of SEER cancer registry data from 1992-2016. Environmental Health Perspectives 2020;128(10); doi:10.1289/EHP7246. |
R835873 (Final) |
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Jorga SD, Kaltsonoudis C, Liangou A, Pandis SN. Measurement of formation rates of secondary aerosol in the ambient urban atmosphere using a dual smog chamber system. Environmental Science & Technology 2020;54:1336–43 |
R835873 (2019) R835873 (Final) |
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Lu Q, Murphy BN, Qin M, Adams PJ, Zhao Y, Pye HOT, Efstathiou C, Robinson AL. Simulation of organic aerosol formation during the CalNex study:Updated mobile emissions and secondary organic aerosol parameterization for intermediate-volatility organic compounds. Atmospheric Chemistry and Physics 2020;20:4313–32; doi:10.5194/acp-20-4313-2020. |
R835873 (2019) R835873 (Final) |
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Shah RU, Coggon MM, Gkatzelis GI, McDonald BC, Tasoglou A, Huber H, Gilman J, Warneke C, Robinson AL, Presto AA. Urban oxidation flow reactor measurements reveal significant secondary organic aerosol contributions from volatile emissions of emerging Importance. Environmental Science & Technology 2020;54:714–25. doi:10.1021/acs.est.9b06531. . |
R835873 (2019) R835873 (Final) |
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Skyllakou K, Rivera PG, Dinkelacker B, Karnezi E, Kioutsioukis I, Hernandez C, Adams PJ, Pandis SN. Changes in PM2.5 concentrations and their sources in the US from 1990 to 2010. Atmospheric Chemistry and Physics 2021;21:17115–32. doi:10.5194/acp-21-17115-2021. |
R835873 (Final) |
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Li J, Hauryliuk A, Malings C, Eilenberg SR, Subramanian R, Presto AA. Characterizing the aging of Alphasense NO2 sensors in long-term field deployments. ACS Sensors 2021;6:2952–9. doi:10.1021/acssensors.1c00729. |
R835873 (Final) |
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Coleman CJ, Yeager RA, Riggs DW, Coleman NC, Garcia GR, Bhatnagar A, Pope CA. Greenness, air pollution, and mortality risk:A U.S. cohort study of cancer patients and survivors. Environment International 2021;157:106797. doi:10.1016/j.envint.2021.106797. |
R835873 (Final) |
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Lu T, Marshall JD, Zhang W, Hystad P, Kim S-Y, Bechle MJ, Demuzere M, Hankey S. National empirical models of air pollution using microscale measures of the urban environment. Environmental Science & Technology 2021;55:15519–30. doi:10.1021/acs.est.1c04047. |
R835873 (Final) |
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Presto AA, Saha PK, Robinson AL. Past, present, and future of ultrafine particle exposures in North America. Atmospheric Environment:X 2021;10:100109. |
R835873 (Final) |
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Balasubramanian S, Domingo NGG, Hunt ND, Gittlin M, Colgan KK, Marshall JD, Robinson AL, Azevedo IML, Thakrar SK, Clark MA, Tessum CW, Adams PJ, Pandis SN, Hill JD. The food we eat, the air we breathe:A review of the fine particulate matter-induced air quality health impacts of the global food system. Environ Res Lett. 2021;16:103004. doi:10.1088/1748-9326/ac065f. |
R835873 (Final) |
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Liang Y, Sengupta D, Campmier MJ, Lunderberg DM, Apte JS, Goldstein AH. Wildfire smoke impacts on indoor air quality assessed using crowdsourced data in California. Proceedings of the National Academy of Sciences of the United States of America 2021;118:. doi:10.1073/pnas.2106478118. |
R835873 (Final) |
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Parks RM, Benavides J, Anderson GB, Nethery RC, Navas-Acien A, Dominici F, Ezzati M, Kioumourtzoglou M-A. Association of tropical cyclones with county-level mortality in the US. JAMA 2022;327:946–55. doi:10.1001/jama.2022.1682. |
R835873 (Final) |
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Pond ZA, Hernandez CS, Adams PJ, Pandis SN, Garcia GR, Robinson AL, Marshall JD, Burnett R, Skyllakou K, Garcia Rivera P, Karnezi E, Coleman CJ, Pope CA. Cardiopulmonary mortality and fine particulate air pollution by species and source in a national U.S. cohort. Environmental Science & Technology 2022;56:7214–23. doi:10.1021/acs.est.1c04176. |
R835873 (Final) |
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Burnett RT, Spadaro JV, Garcia GR, Pope CA. Designing health impact functions to assess marginal changes in outdoor fine particulate matter. Environmental Research 2022;204:112245. doi:10.1016/j.envres.2021.112245. |
R835873 (Final) |
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Kontis V, Bennett JE, Parks RM, Rashid T, Pearson-Stuttard J, Asaria P, Zhou B, Guillot M, Mathers CD, Khang Y-H, McKee M, Ezzati M. Lessons learned and lessons missed:impact of the coronavirus disease 2019 (COVID-19) pandemic on all-cause mortality in 40 industrialised countries and US states prior to mass vaccination. Wellcome Open Research 2022;6:279. doi:10.12688/wellcomeopenres.17253.2. |
R835873 (Final) |
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Wang Y, Apte JS, Hill JD, Ivey CE, Patterson RF, Tessum CW, Marshall JD. Location-specific strategies for eliminating US national racial-ethnic PM2.5 exposure inequality. Proceedings of the National Academy of Sciences 2022;119(44). doi:10.1073/pnas.2205548119. |
R835873 (Final) |
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Pond ZA, Saha PK, Coleman CJ, Presto AA, Robinson AL, Arden Pope III C. Mortality risk and long-term exposure to ultrafine particles and primary fine particle components in a national U.S. Cohort. Environment International 2022;167:107439. doi:10.1016/j.envint.2022.107439. |
R835873 (Final) |
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Roth MB, Adams PJ, Jaramillo P, Muller NZ. Policy spillovers, technological lock-in, and efficiency gains from regional pollution taxes in the U.S. Energy and Climate Change 2022;3:100077. doi:10.1016/j.egycc.2022.100077. |
R835873 (Final) |
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Saha PK, Presto AA, Hankey S, Marshall JD, Robinson AL. Racial-ethnic exposure disparities to airborne ultrafine particles in the United States. Environmental Resesearch Letters 2022;17:104047. doi:10.1088/1748-9326/ac95af. |
R835873 (Final) |
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Garcia Rivera P, Dinkelacker BT, Kioutsioukis I, Adams PJ, Pandis SN. Source-resolved variability of fine particulate matter and human exposure in an urban area. Atmospheric Chemistry and Physics 2022;22:2011–27. doi:10.5194/acp-22-2011-2022. |
R835873 (Final) |
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Ward JW, Michalek JJ, Samaras C. Air pollution, greenhouse gas, and traffic externality benefits and costs of shifting private vehicle travel to ridesourcing services. Environmental Science & Technology 2021;55:13174–85. doi:10.1021/acs.est.1c01641. |
R835873 (Final) |
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Domingo NG, Balasubramanian S, Thakrar SK, Clark MA, Adams PJ, Marshall JD, Muller NZ, Pandis SN, Polasky S, Robinson AL, Tessum CW. Air quality–related health damages of food. Proceedings of the National Academy of Sciences 2021 ;118(20). |
R835873 (Final) |
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Coleman NC, Burnett RT, Higbee JD, Lefler JS, Merrill RM, Ezzati M, Marshall JD, Kim SY, Bechle M, Robinson AL, Pope CA. Cancer mortality risk, fine particulate air pollution, and smoking in a large, representative cohort of US adults. Cancer Causes & Control 2020:767-76. |
R835873 (Final) |
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Bekbulat B, Apte JS, Millet DB, Robinson AL, Wells KC, Presto AA, Marshall JD. Changes in criteria air pollution levels in the US before, during, and after Covid-19 stay-at-home orders:Evidence from regulatory monitors. Science of the Total Environment 2021;769:144693. |
R835873 (Final) |
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Demuzere M, Hankey S, Mills G, Zhang W, Lu T, Bechtel B. Combining expert and crowd-sourced training data to map urban form and functions for the continental US. Scientific data 2020 ;7(1):1-3.. |
R835873 (Final) |
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Davies B, Parkes BL, Bennett J, Fecht D, Blangiardo M, Ezzati M, Elliott P. Community factors and excess mortality in first wave of the COVID-19 pandemic in England. Nature Communications 2021 ;12(1):1-9. |
R835873 (Final) |
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Chambliss SE, Preble CV, Caubel JJ, Cados T, Messier KP, Alvarez RA, LaFranchi B, Lunden M, Marshall JD, Szpiro AA, Kirchstetter TW. Comparison of mobile and fixed-site black carbon measurements for high-resolution urban pollution mapping. Environmental Science & Technology 2020;54(13):7848-57. |
R835873 (Final) |
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Qin M, Murphy BN, Isaacs KK, McDonald BC, Lu Q, McKeen SA, Koval L, Robinson AL, Efstathiou C, Allen C, Pye HO. Criteria pollutant impacts of volatile chemical products informed by near-field modelling. Nature sustainability 2021 ;4(2):129-37. |
R835873 (Final) |
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Dinkelacker BT, Pandis SN. Effect of chemical aging of monoterpene products on biogenic secondary organic aerosol concentrations. Atmospheric Environment 2021;254:118381. |
R835873 (Final) |
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Bruchon MB, Michalek JJ, Azevedo IL. Effects of Air Emission Externalities on Optimal Ridesourcing Fleet Electrification and Operations. Environmental Science & Technology 2021 ;55(5):3188-200. |
R835873 (Final) |
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Thind MPS, Tessum CW, Azevedo IL, Marshall JD. Fine particulate air pollution from electricity generation in the US:Health impacts by race, income, and geography. Environmental Science & Technology 2019;53:14010–9. doi:10.1021/acs.est.9b02527. |
R835873 (2019) R835873 (Final) |
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Coleman NC, Ezzati M, Marshall JD, Robinson AL, Burnett RT, Pope III CA. Fine particulate matter air pollution and mortality risk among US cancer patients and survivors. JNCI cancer spectrum 2021:pkab001. |
R835873 (Final) |
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Hunt ND, Liebman M, Thakrar SK, Hill JD. Fossil energy use, climate change impacts, and air quality-related human health damages of conventional and diversified cropping systems in Iowa, USA. Environmental Science & Technology 2020 ;54(18):11002-14. |
R835873 (Final) |
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Clark MA, Domingo NG, Colgan K, Thakrar SK, Tilman D, Lynch J, Azevedo IL, Hill JD. Global food system emissions could preclude achieving the 1.5 and 2 C climate change targets. Science 2020;370(6517):705-8. |
R835873 (Final) |
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Tanzer-Gruener R, Li J, Eilenberg SR, Robinson AL, Presto AA. Impacts of modifiable factors on ambient air pollution:A case study of COVID-19 shutdowns. Environmental Science & Technology Letters. 2020 Jun 23;7(8):554-9. |
R835873 (Final) |
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Konstantinoudis G, Padellini T, Bennett J, Davies B, Ezzati M, Blangiardo M. Long-term exposure to air-pollution and COVID-19 mortality in England:a hierarchical spatial analysis. Environment international 2021 ;146:106316. |
R835873 (Final) |
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Tang R, Lu Q, Guo S, Wang H, Song K, Yu Y, Tan R, Liu K, Shen R, Chen S, Zeng L. Measurement report:Distinct emissions and volatility distribution of intermediate-volatility organic compounds from on-road Chinese gasoline vehicles:implication of high secondary organic aerosol formation potential. Atmospheric Chemistry and Physics 2021 ;21(4):2569-83. |
R835873 (Final) |
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Roth MB, Adams PJ, Jaramillo P, Muller NZ. Near term carbon tax policy in the US Economy:limits to deep decarbonization. Environmental Research Communications 2020 ;2(5):051004. |
R835873 (Final) |
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Sergi BJ, Adams PJ, Muller NZ, Robinson AL, Davis SJ, Marshall JD, Azevedo IL. Optimizing emissions reductions from the us power sector for climate and health benefits. Environmental science & technology 2020 ;54(12):7513-23. |
R835873 (Final) |
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Tessum CW, Paolella DA, Chambliss SE, Apte JS, Hill JD, Marshall JD. PM2. 5 polluters disproportionately and systemically affect people of color in the United States. Science Advances 2021 ;7(18):eabf4491. |
R835873 (Final) |
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Gasparik JT, Ye Q, Curtis JH, Presto AA, Donahue NM, Sullivan RC, West M, Riemer N. Quantifying errors in the aerosol mixing-state index based on limited particle sample size. Aerosol Science and Technology 2020 ;54(12):1527-41. |
R835873 (Final) |
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Thakrar SK, Balasubramanian S, Adams PJ, Azevedo IML, Muller NZ, Pandis SN, Polasky S, Pope CA, Robinson AL, Apte JS, Tessum CW, Marshall JD, Hill JD. Reducing mortality from air pollution in the United States by targeting specific emission sources. Environmetnal Science & Technology Letters 2020. doi:10.1021/acs.estlett.0c00424. |
R835873 (2019) R835873 (Final) |
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Sergi B, Azevedo I, Davis SJ, Muller NZ. Regional and county flows of particulate matter damage in the US. Environmental Research Letters 2020 ;15(10):104073. |
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Konstantinoudis G, Padellini T, Bennett J, Davies B, Ezzati M, Blangiardo M. Response to “Re:Long-term exposure to air-pollution and COVID-19 mortality in England:A hierarchical spatial analysis”. Environment International 2021 ;150:106427. |
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Garcia III GR, Coleman NC, Pond ZA, Pope III CA. Shape of BMI–Mortality Risk Associations:Reverse Causality and Heterogeneity in a Representative Cohort of US Adults. Obesity 2021 ;29(4):755-66. |
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Shah RU, Robinson ES, Gu P, Apte JS, Marshall JD, Robinson AL, Presto AA. Socio-economic disparities in exposure to urban restaurant emissions are larger than for traffic. Environmental Research Letters 2020 ;15(11):114039. |
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Saha PK, Sengupta S, Adams P, Robinson AL, Presto AA. Spatial correlation of ultrafine particle number and fine particle mass at urban scales: Implications for health assessment. Environmental Science & Technology 2020;54(15):9295-304. |
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Wang Y, Bechle MJ, Kim S-Y, Adams PJ, Pandis SN, Pope CA, Robinson AL, Sheppard L, Szpiro AA, Marshall JD. Spatial decomposition analysis of NO2 and PM2.5 air pollution in the United States. Atmospheric Environment 2020:117470. doi:10.1016/j.atmosenv.2020.117470. |
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Song R, Presto AA, Saha P, Zimmerman N, Ellis A, Subramanian R. Spatial variations in urban air pollution:Impacts of diesel bus traffic and restaurant cooking at small scales. Air Quality, Atmosphere & Health 2021. doi:10.1007/s11869-021-01078-8. |
R835873 (Final) |
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Ward JW, Michalek JJ, Samaras C, Azevedo IL, Henao A, Rames C, Wenzel T. The impact of Uber and Lyft on vehicle ownership, fuel economy, and transit across US cities. Iscience 2021;24(1):101933. . |
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Lu T, Bechle MJ, Wan Y, Presto AA, Hankey S. Using crowd-sourced low-cost sensors in a land use regression of PM2.5 in 6 US cities. Air Quality, Atmosphere & Health 2022. doi:10.1007/s11869-022-01162-7. |
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Tong F, Azevedo IM. What are the best combinations of fuel-vehicle technologies to mitigate climate change and air pollution effects across the United States?. Environmental Research Letters 2020 ;15(7):074046. Wang Y, Bechle MJ, Kim SY, Adams PJ, Pandis SN, Pope III CA, Robinson AL, Sheppard L, Szpiro AA, Marshall JD. Spatial decomposition analysis of NO2 and PM2. 5 air pollution in the United States. Atmospheric environment 2020 ;241:117470. |
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Cain KP, Liangou A, Davidson ML, Pandis SN. α-Pinene, Limonene, and Cyclohexene Secondary Organic Aerosol Hygroscopicity and Oxidation Level as a Function of Volatility. Aerosol and Air Quality Research 2021 ;21. |
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Supplemental Keywords:
air pollution, climate, energy, health effects, social cost, impact assessmentRelevant Websites:
The Center for Air, Climate, and Energy Solutions Exit
Progress 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).
R835873C001 Mechanistic Air Quality Impact Models for Assessment of Multiple Pollutants at High Spatial Resolution
R835873C002 Air Quality Observatory
R835873C003 Next Generation LUR Models: Development of Nationwide Modeling Tools for
Exposure Assessment and Epidemiology
R835873C004 Air Pollutant Control Strategies in a Changing World
R835873C005 Health Effects of Air Pollution and Mitigation Scenarios
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
- Original Abstract
136 journal articles for this center