Articles | Volume 22, issue 11
https://doi.org/10.5194/acp-22-7389-2022
© 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-22-7389-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jun 2022
Research article |
| 08 Jun 2022
| 08 Jun 2022
Spatial variability of air pollutants in a megacity characterized by mobile measurements
Reza Bashiri Khuzestani
State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and
Engineering, Peking University, Beijing, 100871, China
now at: Faculty of Civil, Water and Environmental Engineering, School of Engineering, Shahid Beheshti University, Tehran, Iran
Keren Liao
State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and
Engineering, Peking University, Beijing, 100871, China
State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and
Engineering, Peking University, Beijing, 100871, China
Ruqian Miao
State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and
Engineering, Peking University, Beijing, 100871, China
Yan Zheng
State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and
Engineering, Peking University, Beijing, 100871, China
Xi Cheng
State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and
Engineering, Peking University, Beijing, 100871, China
Tianjiao Jia
State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and
Engineering, Peking University, Beijing, 100871, China
State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and
Engineering, Peking University, Beijing, 100871, China
Shiyi Chen
State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and
Engineering, Peking University, Beijing, 100871, China
Guancong Huang
State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and
Engineering, Peking University, Beijing, 100871, China
State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and
Engineering, Peking University, Beijing, 100871, China
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Cited
12 citations as recorded by crossref.
- Increasing importance of regional emission controls for further reduction of PM2.5 in Beijing L. Dong et al. https://doi.org/10.1016/j.uclim.2025.102437
- Investigation of atmospheric VOCs sources and ozone formation sensitivity during epidemic closure and control: A case study of Zhengzhou J. Guo et al. https://doi.org/10.1016/j.apr.2023.102035
- Hyperlocal Air Pollution in London: Validating Low-Cost Sensors for Mobile Measurements from Vehicles H. Russell et al. https://doi.org/10.1021/acsestair.3c00043
- Mobile measurements reveal anthropogenic drivers of photochemical pollution and health risks in coastal lines of South China Y. Peng et al. https://doi.org/10.1016/j.jes.2026.05.036
- A spatiotemporal multi-scale network for robust air pollutant forecasting in complex urban environments E. Song et al. https://doi.org/10.1016/j.enbuild.2026.117452
- Spatio-temporal dynamics of aerosol distribution in an urban environment recorded in situ by means of a bike based monitoring system S. Norra et al. https://doi.org/10.3389/fenvs.2023.749477
- Spatial distribution of PM10 concentration at urban cities of Klang Valley, Malaysia using inverse distance weighted and kriging from 2015 to 2016 S. Shukri & A. Asmat https://doi.org/10.1088/1755-1315/1489/1/012053
- Hyperlocal air pollution in London: Nitrogen dioxide measured with a low-cost sensor network and mobile monitoring L. Frederickson et al. https://doi.org/10.1016/j.atmosenv.2025.121561
- Secondary Formation of Submicron and Supermicron Organic and Inorganic Aerosols in a Highly Polluted Urban Area Y. Zheng et al. https://doi.org/10.1029/2022JD037865
- VOC source apportionment: How monitoring characteristics influence positive matrix factorization (PMF) solutions C. Frischmon & M. Hannigan https://doi.org/10.1016/j.aeaoa.2023.100230
- Air pollution and labour productivity: firm-level spatial evidence from China Y. Zhang et al. https://doi.org/10.1088/2515-7620/adeceb
- Comprehensive spatiotemporal analysis of long-term mobile monitoring for traffic-related particles in a complex urban environment B. Yeganeh et al. https://doi.org/10.1016/j.apr.2025.102870
12 citations as recorded by crossref.
- Increasing importance of regional emission controls for further reduction of PM2.5 in Beijing L. Dong et al. https://doi.org/10.1016/j.uclim.2025.102437
- Investigation of atmospheric VOCs sources and ozone formation sensitivity during epidemic closure and control: A case study of Zhengzhou J. Guo et al. https://doi.org/10.1016/j.apr.2023.102035
- Hyperlocal Air Pollution in London: Validating Low-Cost Sensors for Mobile Measurements from Vehicles H. Russell et al. https://doi.org/10.1021/acsestair.3c00043
- Mobile measurements reveal anthropogenic drivers of photochemical pollution and health risks in coastal lines of South China Y. Peng et al. https://doi.org/10.1016/j.jes.2026.05.036
- A spatiotemporal multi-scale network for robust air pollutant forecasting in complex urban environments E. Song et al. https://doi.org/10.1016/j.enbuild.2026.117452
- Spatio-temporal dynamics of aerosol distribution in an urban environment recorded in situ by means of a bike based monitoring system S. Norra et al. https://doi.org/10.3389/fenvs.2023.749477
- Spatial distribution of PM10 concentration at urban cities of Klang Valley, Malaysia using inverse distance weighted and kriging from 2015 to 2016 S. Shukri & A. Asmat https://doi.org/10.1088/1755-1315/1489/1/012053
- Hyperlocal air pollution in London: Nitrogen dioxide measured with a low-cost sensor network and mobile monitoring L. Frederickson et al. https://doi.org/10.1016/j.atmosenv.2025.121561
- Secondary Formation of Submicron and Supermicron Organic and Inorganic Aerosols in a Highly Polluted Urban Area Y. Zheng et al. https://doi.org/10.1029/2022JD037865
- VOC source apportionment: How monitoring characteristics influence positive matrix factorization (PMF) solutions C. Frischmon & M. Hannigan https://doi.org/10.1016/j.aeaoa.2023.100230
- Air pollution and labour productivity: firm-level spatial evidence from China Y. Zhang et al. https://doi.org/10.1088/2515-7620/adeceb
- Comprehensive spatiotemporal analysis of long-term mobile monitoring for traffic-related particles in a complex urban environment B. Yeganeh et al. https://doi.org/10.1016/j.apr.2025.102870
Saved (final revised paper)
Latest update: 07 Jun 2026
Short summary
This work characterized the spatial variabilities of air pollutants in a megacity by advanced mobile measurements. The results show a large spatial heterogeneity in the distributions of PM2.5 composition and volatile organic compounds under non-haze conditions, and relatively uniform spatial distributions under haze conditions that may indicate a chemical homogeneity on an intracity scale. The findings improve our understanding of urban air pollution.
This work characterized the spatial variabilities of air pollutants in a megacity by advanced...
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