These models provide estimates of outdoor concentrations for six criteria pollutants (four gases: O3, CO, SO2, NO2; two aerosols: PM10, PM2.5) throughout the contiguous U.S.; estimates are also available for four non-criteria pollutants (PNC [particle number concentration], COA [cooking organic aerosol], HOA [hydrocarbon-like organic aerosol], and BC [black carbon]). Model estimates are annual-average values for years 1979 – 2020 (SO2, NO2), 1988 – 2020 (PM10), 1990-2020 (CO), 1999-2020 (PM2.5), 2017 (PNC, COA, HOA, BC), and the average during May through September of the daily maximum 8-hour moving average for years 1979-2019 (O3). When downloading data, concentrations are listed as the variable "pred_weight"; units are micrograms per cubic meter for PM2.5, PM10, COA, HOA, and BC; particles per cc for PNC; parts per billion for O3, SO2, and NO2; and parts per million for CO. Users can download data by county, census tract, or census block-group (geographies based on year-2010 Census).
Please see the README file for more information.
Decomposed annual concentrations of four spatial components ("long-range", "mid-range", "neighborhood", "near-source") for PM2.5 and NO2 are also available at the census block group level for years 2000 - 2015.
CACES participants have developed three models that estimate human health impacts from emissions of PM2.5, SO2, NOx, NH3, and VOCs: AP2, EASIUR, and InMAP. This page contains results from the three models in terms of economic damages caused by human exposure to air pollution as a function of the location of emissions ($ per U.S. metric ton).
Please see the RCM User Guide for more information. Also, an inter-comparison of the models is available here.
The InMAP Source-Receptor Matrix (ISRM) estimates the air quality impacts of emissions released from any source location in the contiguous United States to any receptor location. Files linking the ISRM with US Census demographic data and the US EPA National Emissions Inventory are also available. More information on the ISRM is available here.
Contact admin@caces.us for any questions regarding the data or data download tool.
These data are free and publicly available for non-commercial purposes, data may not be used for commercial purposes without prior written permission.
Species- and source-resolved PM2.5 exposure estimates for 2001 and 2010, developed with a Geographically Weighted Regression, are available here. (The readme file, describing the dataset and providing suggested citations, is here.)
Please cite as follows:
"This article includes [concentration/damages] estimates developed by the Center for Air, Climate and Energy Solutions (CACES) using [v1 empirical models/AP2/EASIUR/InMAP] as described in [insert suggested citation]."
Suggested citation:
v1 empirical models for criteria pollutants: Kim S.-Y.; Bechle, M.; Hankey, S.; Sheppard, L.; Szpiro, A. A.; Marshall, J. D. 2020. “Concentrations of criteria pollutants in the contiguous U.S., 1979 – 2015: Role of prediction model parsimony in integrated empirical geographic regression.” PLoS ONE 15(2), e0228535. https://doi.org/10.1371/journal.pone.0228535
spatially-decomposed v1 empirical models for criteria pollutants: Wang Y.; Bechle, M.; Kim, S.-Y.; Adams, P. J.; Pandis, S. N.; Pope III, C. A.; Robinson, A. L.; Sheppard, L.; Szpiro, A. A.; Marshall, J. D. 2020. "Spatial decomposition analysis of NO2 and PM2.5 air pollution in the United States." Atmospheric Environment 241(15), 117470. https://doi.org/10.1016/j.atmosenv.2020.117470
PNC: Saha, P. K.; Hankey, S.; Marshall, J. D.; Robinson, A. L.; Presto, A. A. High-Spatial Resolution Estimates of Ultrafine Particle Concentrations across the Continental United States. Environ. Sci. Technol. 2021, 55 (15), 10320–10331. https://doi.org/10.1021/acs.est.1c03237
HOA and COA: Saha, P. K.; Presto, A. A.; Hankey, S.; Murphy, B. N.; Allen, C.; Zhang, W.; Marshall, J. D.; Robinson, A. L. National Exposure Models for Source-Specific Primary Particulate Matter Concentrations Using Aerosol Mass Spectrometry Data. Environ. Sci. Technol. 2022, 56 (20), 14284–14295. https://doi.org/10.1021/acs.est.2c03398.
BC: Saha, P. K.; Presto, A. A.; Robinson, A. L. Hyper-Local to Regional Exposure Contrast of PM2.5 Components across the Contiguous US: Implications for Health Assessment. J Expo Sci Environ Epidemiol. 2023. https://doi.org/10.1038/s41370-023-00623-0.
AP2: Muller, N. Z. 2014. “Boosting GDP growth by accounting for the environment.” Science 345 (6199), 873-74. https://doi.org/10.1126/science.1253506
EASIUR: Heo, J.; Adams, P. J.; Gao, H. 2016. “Reduced-form modeling of public health impacts of inorganic PM2.5 and precursor emissions.” Atmospheric Environment 137, 80–89. https://doi.org/10.1016/j.atmosenv.2016.04.026
InMAP/ISRM: Tessum, C. W.; Hill, J. D.; Marshall, J. D. 2017. “InMAP: A model for air pollution interventions.” PLoS ONE 12 (4), e0176131. https://doi.org/10.1371/journal.pone.0176131
