Preprints
https://doi.org/10.5194/acp-2021-568
https://doi.org/10.5194/acp-2021-568

  02 Aug 2021

02 Aug 2021

Review status: this preprint is currently under review for the journal ACP.

Source-Resolved Variability of Fine Particulate Matter and Human Exposure in an Urban Area

Pablo Garcia Rivera1, Brian T. Dinkelacker1, Ioannis Kioutsioukis2, Peter J. Adams3,4, and Spyros N. Pandis5,6 Pablo Garcia Rivera et al.
  • 1Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213
  • 2Department of Physics, University of Patras, 26500, Patras, Greece
  • 3Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213
  • 4Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, 15213
  • 5Institute of Chemical Engineering Sciences (FORTH/ICE-HT), 26504, Patras, Greece
  • 6Department of Chemical Engineering, University of Patras, 26500, Patras, Greece

Abstract. Increasing the resolution of chemical transport model (CTM) predictions in urban areas is important to capture sharp spatial gradients in atmospheric pollutant concentrations and better inform air quality and emissions controls policies that protect public health. The chemical transport model PMCAMx was used to assess the impact of increasing model resolution on the ability to predict the source-resolved variability and population exposure to PM2.5 at 36 x 36, 12 x 12, 4 x 4, and 1 x 1 km resolutions over the city of Pittsburgh during typical winter and summer periods (February and July 2017). At the coarse resolution, county-level differences can be observed, while increasing the resolution to 12 x 12 km resolves the urban-rural gradient. Increasing resolution to 4 x 4 km resolves large stationary sources such as power plants and the 1 x 1 km resolution reveals intra-urban variations and individual roadways within the simulation domain. Regional pollutants that exhibit low spatial variability such as PM2.5 nitrate show modest changes when increasing the resolution beyond 12 x 12 km. Predominantly local pollutants such as elemental carbon and organic aerosol have gradients that can only be resolved at the 1 x 1 km scale. Contributions from some local sources are enhanced by weighting the average contribution from each source by the population in each grid cell. The average population weighted PM2.5 concentration does not change significantly with resolution, suggesting that extremely high resolution PM2.5 predictions may not be necessary for effective urban epidemiological analysis.

Pablo Garcia Rivera et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2021-568', Anonymous Referee #1, 29 Aug 2021
  • RC2: 'Comment on acp-2021-568', Anonymous Referee #2, 18 Sep 2021

Pablo Garcia Rivera et al.

Pablo Garcia Rivera et al.

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Short summary
The contribution of various pollution sources to the variability of fine PM in an urban area was examined using as an example the city of Pittsburgh. Biomass burning aerosol shows the largest variability during the winter with local maxima within the city and in the suburbs. During both periods the largest contributing source to the average PM2.5 is particles from outside the modeling domain. The average population weighted PM2.5 concentration does not change significantly with resolution.
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