A long-term high-resolution air quality reanalysis with a public-facing air quality dashboard over the Contiguous United States (CONUS)

Abstract. We present a 14-year, 12 km, hourly air quality dataset (https://doi.org/10.5065/cfya-4g50, Kumar and He, 2023) created by assimilating satellite observations of aerosol optical depth (AOD) and carbon monoxide (CO) in an air quality model to fill gaps in the contiguous United States (CONUS) air quality monitoring network and help air quality managers understand long-term changes in county-level air quality. Specifically, we assimilate the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD and the Measurement of Pollution in the Troposphere (MOPITT) CO observations in the Community Multiscale Air Quality Model (CMAQ) every day from 1 January 2005 to 31 December 2018 to produce this dataset. Meteorological fields simulated with the Weather Research and Forecasting (WRF) model are used to drive CMAQ offline and to generate meteorology-dependent anthropogenic emissions. Both the weather and air quality (surface fine particulate matter (PM2.5) and ozone) simulations are subjected to a comprehensive evaluation against multi-platform observations to establish the credibility of our dataset and characterize its uncertainties. We show that our dataset captures regional hourly, seasonal, and interannual variability in meteorology very well across the CONUS. The correlation coefficient between the observed and simulated surface ozone and PM2.5 concentrations for different regions defined by the Environmental Protection Agency (EPA) across the CONUS are 0.77–0.91 and 0.49–0.79, respectively. The mean bias and root-mean-square error for modeled ozone are 3.7–6.8 and 7–9 ppbv, respectively, while the corresponding values for PM2.5 are −0.9–5.6 and 3.0–8.3 µg m−3, respectively. We estimate that the annual CONUS-averaged maximum daily 8 h average (MDA8) ozone and PM2.5 trends are −0.30 ppb yr−1 and −0.24 µg m−3 yr−1, respectively. Wintertime MDA8 ozone shows an increasing but statistically insignificant trend at several sites. We also found a decreasing trend in the 95th percentile of MDA8 ozone but an increasing trend in the 5th percentile. Most of the sites in the Pacific Northwest show an increasing but statistically insignificant trend during summer. An ArcGIS air quality dashboard has been developed to enable easy visualization and interpretation of county-level air quality measures and trends by stakeholders, and a Python-based Streamlit application has been developed to allow the download of the air quality data in simplified text and graphic formats.

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Publication Details

Journal
Earth system science data
Published
2025-05-07
DOI
https://doi.org/10.5194/essd-17-1807-2025
Citations
2
Primary Topic
Atmospheric chemistry and aerosols
Type
article
Field-Weighted Citation Impact
2.60
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article

A long-term high-resolution air quality reanalysis with a public-facing air quality dashboard over the Contiguous United States (CONUS)

Matthew Casali, Rajesh Kumar, Stefano Alessandrini, Piyush Bhardwaj et al.
2 citations
Earth system science data
Atmospheric chemistry and aerosols
2.60
article

A long-term high-resolution air quality reanalysis with a public-facing air quality dashboard over the Contiguous United States (CONUS)

Matthew Casali, Rajesh Kumar, Stefano Alessandrini, Piyush Bhardwaj, Jennifer Boehnert, Olga Wilhelmi, Gabriele G. Pfister, H. M. Worden, Cenlin He, Scott Swerdlin, K. M. Sampson, Forrest Lacey, Benjamin Gaubert
article en
2 citations

Abstract

Abstract. We present a 14-year, 12 km, hourly air quality dataset (https://doi.org/10.5065/cfya-4g50, Kumar and He, 2023) created by assimilating satellite observations of aerosol optical depth (AOD) and carbon monoxide (CO) in an air quality model to fill gaps in the contiguous United States (CONUS) air quality monitoring network and help air quality managers understand long-term changes in county-level air quality. Specifically, we assimilate the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD and the Measurement of Pollution in the Troposphere (MOPITT) CO observations in the Community Multiscale Air Quality Model (CMAQ) every day from 1 January 2005 to 31 December 2018 to produce this dataset. Meteorological fields simulated with the Weather Research and Forecasting (WRF) model are used to drive CMAQ offline and to generate meteorology-dependent anthropogenic emissions. Both the weather and air quality (surface fine particulate matter (PM2.5) and ozone) simulations are subjected to a comprehensive evaluation against multi-platform observations to establish the credibility of our dataset and characterize its uncertainties. We show that our dataset captures regional hourly, seasonal, and interannual variability in meteorology very well across the CONUS. The correlation coefficient between the observed and simulated surface ozone and PM2.5 concentrations for different regions defined by the Environmental Protection Agency (EPA) across the CONUS are 0.77–0.91 and 0.49–0.79, respectively. The mean bias and root-mean-square error for modeled ozone are 3.7–6.8 and 7–9 ppbv, respectively, while the corresponding values for PM2.5 are −0.9–5.6 and 3.0–8.3 µg m−3, respectively. We estimate that the annual CONUS-averaged maximum daily 8 h average (MDA8) ozone and PM2.5 trends are −0.30 ppb yr−1 and −0.24 µg m−3 yr−1, respectively. Wintertime MDA8 ozone shows an increasing but statistically insignificant trend at several sites. We also found a decreasing trend in the 95th percentile of MDA8 ozone but an increasing trend in the 5th percentile. Most of the sites in the Pacific Northwest show an increasing but statistically insignificant trend during summer. An ArcGIS air quality dashboard has been developed to enable easy visualization and interpretation of county-level air quality measures and trends by stakeholders, and a Python-based Streamlit application has been developed to allow the download of the air quality data in simplified text and graphic formats.

Earth system science dataVol. 17(5)
NSF National Center for Atmospheric Research (US), Center for Study of Science Technology and Policy (IN)
Openalex Percentile: Top 12%
Atmospheric chemistry and aerosols
2.60
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