Mapping Air Pollution Concentrations on Sidewalks in Central Business Districts Based on Mobile Monitoring

Air pollution on urban sidewalks poses a huge threat to human health. We conducted an air pollution mobile monitoring campaign to measure PM2.5 levels on sidewalks in the Futian CBD area of Shenzhen, using portable air pollution sensors. The campaign involved collecting data during peak commuting times to capture variations in air quality. Calibration of the AirBeam3 devices against a standard instrument ensured data accuracy. Using GIS spatial analysis, we mapped air pollution patterns and identified notable differences between weekdays and weekends, with concentrations ranging from 3-9 μg/m³. Our findings indicate higher pollution levels on weekdays, particularly in the afternoon, correlating with increased traffic and economic activity. The study also highlights spatio-temporal heterogeneity, with morning pollution concentrations more pronounced in the northern financial district and afternoon levels higher in the southern area, characterized by commercial facilities. These patterns suggest that regional industrial distribution and traffic flow significantly influence air quality. By understanding the dynamics of pollution in urban environments, this research contributes to the development of effective strategies for improving air quality and public health in densely populated city centers.

Authors

Publication Details

Journal
Kalpa publications in computing
Published
2025-08-28
DOI
https://doi.org/10.29007/vzrf
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
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article

Mapping Air Pollution Concentrations on Sidewalks in Central Business Districts Based on Mobile Monitoring

Xujing Yu, Jun Ma
Kalpa publications in computing
Air Quality Monitoring and Forecasting
article

Mapping Air Pollution Concentrations on Sidewalks in Central Business Districts Based on Mobile Monitoring

Xujing Yu, Jun Ma
article en

Abstract

Air pollution on urban sidewalks poses a huge threat to human health. We conducted an air pollution mobile monitoring campaign to measure PM2.5 levels on sidewalks in the Futian CBD area of Shenzhen, using portable air pollution sensors. The campaign involved collecting data during peak commuting times to capture variations in air quality. Calibration of the AirBeam3 devices against a standard instrument ensured data accuracy. Using GIS spatial analysis, we mapped air pollution patterns and identified notable differences between weekdays and weekends, with concentrations ranging from 3-9 μg/m³. Our findings indicate higher pollution levels on weekdays, particularly in the afternoon, correlating with increased traffic and economic activity. The study also highlights spatio-temporal heterogeneity, with morning pollution concentrations more pronounced in the northern financial district and afternoon levels higher in the southern area, characterized by commercial facilities. These patterns suggest that regional industrial distribution and traffic flow significantly influence air quality. By understanding the dynamics of pollution in urban environments, this research contributes to the development of effective strategies for improving air quality and public health in densely populated city centers.

Kalpa publications in computingVol. 22
Openalex Percentile: Top 79%
Air Quality Monitoring and Forecasting
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