Paper
27 November 2024 Simulation and analysis of air quality in the main urban area of Chongqing based on GIS and LUR modeling
Xia Li, Lina Dong, Xinyue Wang
Author Affiliations +
Proceedings Volume 13402, International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024); 134021D (2024) https://doi.org/10.1117/12.3048880
Event: International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024), 2024, Zhengzhou, China
Abstract
PM2.5 is a critical physical parameter for characterizing air pollution. Monitoring the spatiotemporal patterns of urban PM2.5 is crucial for environmental health and sustainable development. This study utilizes measured PM2.5 data, MODIS remote sensing data, land use and other data to study the monitoring and simulation of PM2.5 concentration distribution in Chongqing's main urban area using GIS spatial analysis and the Land Use Regression (LUR) model. The results indicate: 1) The 2020 LUR model included variables FL-4000, DEM, and PE5000, with an R2 of 0.789 and an RMSE of 11.84; the 2013 model should include FL-5000, RS5000, DEM, and PE5000, with an R2 of 0.688 and an RMSE of 14.84. 2) The spatial distribution of pollutants is closely related to DEM and the location of green spaces, with greenery mitigating pollution and contributions from traffic emissions being smaller than those from industrial emissions. 3) Compared to 2013, the 2020 PM2.5 concentration significantly decreased, with average concentrations dropping by 13.23%. The spatial distribution of annual average PM2.5 concentrations was generally higher in the central-western part and lower in the southeastern part, aligning with the natural geographic conditions of Chongqing's main urban area as well as its level of socioeconomic development and urbanization.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xia Li, Lina Dong, and Xinyue Wang "Simulation and analysis of air quality in the main urban area of Chongqing based on GIS and LUR modeling", Proc. SPIE 13402, International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024), 134021D (27 November 2024); https://doi.org/10.1117/12.3048880
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KEYWORDS
Environmental monitoring

Data modeling

Modeling

Air contamination

Cross validation

Geographic information systems

Air quality

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