Articles | Volume 22, issue 3
https://doi.org/10.5194/acp-22-2011-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-2011-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Feb 2022
Research article |
| 11 Feb 2022
| 11 Feb 2022
Source-resolved variability of fine particulate matter and human exposure in an urban area
Pablo Garcia Rivera
Department of Chemical Engineering, Carnegie Mellon University,
Pittsburgh, PA, 15213, USA
Brian T. Dinkelacker
Department of Chemical Engineering, Carnegie Mellon University,
Pittsburgh, PA, 15213, USA
Ioannis Kioutsioukis
Department of Physics, University of Patras, 26500, Patras, Greece
Peter J. Adams
Department of Civil and Environmental Engineering, Carnegie Mellon
University, Pittsburgh, PA, 15213, USA
Department of Engineering and Public Policy, Carnegie Mellon
University, Pittsburgh, PA, 15213, USA
Spyros N. Pandis
CORRESPONDING AUTHOR
Institute of Chemical Engineering Sciences (FORTH/ICE-HT), 26504,
Patras, Greece
Department of Chemical Engineering, University of Patras, 26500,
Patras, Greece
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Cited
13 citations as recorded by crossref.
- Synergistic generation mechanisms of SOA and ozone from the photochemical oxidation of 1,3,5-trimethylbenzene: Influence of precursors ratio, temperature and radiation intensity H. Zhang et al. 10.1016/j.atmosres.2023.106924
- High spatial resolution estimates of major PM2.5 components and their associated health risks in Hong Kong using a coupled land use regression and health risk assessment approach Z. Li et al. 10.1016/j.scitotenv.2023.167932
- Halation-Based Nighttime PM2.5 Estimation Y. Xiang et al. 10.1109/JSEN.2025.3525712
- Advances in Simulating the Global Spatial Heterogeneity of Air Quality and Source Sector Contributions: Insights into the Global South D. Zhang et al. 10.1021/acs.est.2c07253
- High-resolution WRF forecasts in the SmartAQ system: Evaluation of the meteorological forcing used for PMCAMx predictions in an urban area A. Pappa et al. 10.1016/j.atmosres.2023.107041
- Cooking emissions are a major source of racial-ethnic air pollution exposure disparities in the United States P. Saha et al. 10.1088/1748-9326/ad1721
- Atmospheric aerosol spatial variability: Impacts on air quality and climate change S. Manavi et al. 10.1016/j.oneear.2025.101237
- Optimization of the Efficient Extraction of Organic Components in Atmospheric Particulate Matter by Accelerated Solvent Extraction Technique and Its Application H. Zhang et al. 10.3390/atmos13050818
- The impact of governance indicators, renewable energy demand, industrialization, and travel & transportation on urbanization: A panel study of selected Asian economies M. Akhtar et al. 10.1016/j.cities.2024.105131
- Integrating local climate zones and spatial modeling for carbon emission forecasting in the Guangdong-Hong Kong-Macao Greater Bay Area toward 2060 R. Chen et al. 10.1016/j.uclim.2025.102453
- High-resolution downscaling of source resolved PM2.5 predictions using machine learning models B. Dinkelacker et al. 10.1016/j.atmosenv.2023.119967
- Evaluation of high-resolution predictions of fine particulate matter and its composition in an urban area using PMCAMx-v2.0 B. Dinkelacker et al. 10.5194/gmd-15-8899-2022
- High resolution source-resolved PM2.5 spatial distribution and human exposure in a large urban area E. Siouti et al. 10.1016/j.atmosenv.2025.121277
13 citations as recorded by crossref.
- Synergistic generation mechanisms of SOA and ozone from the photochemical oxidation of 1,3,5-trimethylbenzene: Influence of precursors ratio, temperature and radiation intensity H. Zhang et al. 10.1016/j.atmosres.2023.106924
- High spatial resolution estimates of major PM2.5 components and their associated health risks in Hong Kong using a coupled land use regression and health risk assessment approach Z. Li et al. 10.1016/j.scitotenv.2023.167932
- Halation-Based Nighttime PM2.5 Estimation Y. Xiang et al. 10.1109/JSEN.2025.3525712
- Advances in Simulating the Global Spatial Heterogeneity of Air Quality and Source Sector Contributions: Insights into the Global South D. Zhang et al. 10.1021/acs.est.2c07253
- High-resolution WRF forecasts in the SmartAQ system: Evaluation of the meteorological forcing used for PMCAMx predictions in an urban area A. Pappa et al. 10.1016/j.atmosres.2023.107041
- Cooking emissions are a major source of racial-ethnic air pollution exposure disparities in the United States P. Saha et al. 10.1088/1748-9326/ad1721
- Atmospheric aerosol spatial variability: Impacts on air quality and climate change S. Manavi et al. 10.1016/j.oneear.2025.101237
- Optimization of the Efficient Extraction of Organic Components in Atmospheric Particulate Matter by Accelerated Solvent Extraction Technique and Its Application H. Zhang et al. 10.3390/atmos13050818
- The impact of governance indicators, renewable energy demand, industrialization, and travel & transportation on urbanization: A panel study of selected Asian economies M. Akhtar et al. 10.1016/j.cities.2024.105131
- Integrating local climate zones and spatial modeling for carbon emission forecasting in the Guangdong-Hong Kong-Macao Greater Bay Area toward 2060 R. Chen et al. 10.1016/j.uclim.2025.102453
- High-resolution downscaling of source resolved PM2.5 predictions using machine learning models B. Dinkelacker et al. 10.1016/j.atmosenv.2023.119967
- Evaluation of high-resolution predictions of fine particulate matter and its composition in an urban area using PMCAMx-v2.0 B. Dinkelacker et al. 10.5194/gmd-15-8899-2022
- High resolution source-resolved PM2.5 spatial distribution and human exposure in a large urban area E. Siouti et al. 10.1016/j.atmosenv.2025.121277
Latest update: 01 Jun 2025
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.
The contribution of various pollution sources to the variability of fine PM in an urban area was...
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