Articles | Volume 22, issue 3
https://doi.org/10.5194/acp-22-2011-2022
https://doi.org/10.5194/acp-22-2011-2022
Research article
 | 
11 Feb 2022
Research article |  | 11 Feb 2022

Source-resolved variability of fine particulate matter and human exposure in an urban area

Pablo Garcia Rivera, Brian T. Dinkelacker, Ioannis Kioutsioukis, Peter J. Adams, and Spyros N. Pandis

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Evaluation of high-resolution predictions of fine particulate matter and its composition in an urban area using PMCAMx-v2.0
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Predicted and Observed Changes in Summertime Biogenic and Total Organic Aerosol in the Southeast United States from 2001 to 2010
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Revised manuscript not accepted
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Changes in PM2.5 concentrations and their sources in the US from 1990 to 2010
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Cited articles

Anand, S.: The concern for equity in health, J. Epidemiol. Commun. H., 56, 485–487, 2002. 
Arunachalam, S., Holland, A., Do, B., and Abraczinskas, M.: A quantitative assessment of the influence of grid resolution on predictions of future-year air quality in North Carolina, USA, Atmos. Environ., 40, 5010–5026, 2006. 
Carter, W. P. L.: Documentation of the SAPRC-99 chemical mechanism for VOC reactivity assessment, Final Report to California Air Resources Board Contract 92-329 and Contract 95-308, Air Pollution Research Center and College of Engineering Center for Environmental Research and Technology, University of California Riverside, California, 2000. 
Day, M., Pouliot, G., Hunt, S., Baker, K. R., Beardsley, M., Frost, G., Mobley, D., Simon, H., Henderson, B., Yelverton, T., and Rao, V.: Reflecting on progress since the 2005 NARSTO emissions inventory report, J. Air Waste Manage., 69, 1025–1050, 2019. 
Dinkelacker, B. T., Garcia Rivera, P., Kioutsioukis, I., Adams, P., and Pandis, S. N.: Source Code for PMCAMx-v2.0: High-resolution modeling of fine particulate matter in an urban area using PMCAMx-v2.0, Zenodo [code], https://doi.org/10.5281/zenodo.5094477, 2021. 
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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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