Estimation and spatiotemporal variations of black carbon aerosol over the North China Plain in 2018

Kun Cai; Yongkai Qi; Shenshen Li; Shuo Zhang

doi:10.1117/12.3010722

15 November 2023 Estimation and spatiotemporal variations of black carbon aerosol over the North China Plain in 2018

Kun Cai, Yongkai Qi, Shenshen Li, Shuo Zhang

Proceedings Volume 12815, International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023); 128151O (2023) https://doi.org/10.1117/12.3010722
Event: International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023), 2023, Kaifeng, China

Abstract

With the rapid economic development in the North China Plain, the significant emissions of black carbon (BC) aerosol have exerted notable impacts on climate, environment, and health, making it a hot topic in environmental studies in recent years. To compensate for the insufficient ground monitoring data, the PM2.5 satellite remote sensing inversion data and chemical model simulation data were utilized, applying the proportionality factor method to estimate the satellite concentration of BC. The estimation results were validated using BC monitoring data from seven stations in 2018, and based on this, the spatiotemporal variations of BC satellite concentration was obtained. The results showed that the estimated BC concentration using the proportionality factor method had good accuracy, with a correlation coefficient (R²) of 0.72. The spatial distribution of BC over the North China Plain in 2018 exhibited a decreasing trend from the inner region to the outer region, with high concentration areas mainly located in provinces with high straw burning and steel production. The seasonal variation of BC in the North China Plain in 2018 was pronounced, showing higher concentrations in autumn and winter and lower concentrations in spring and summer.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Kun Cai, Yongkai Qi, Shenshen Li, and Shuo Zhang "Estimation and spatiotemporal variations of black carbon aerosol over the North China Plain in 2018", Proc. SPIE 12815, International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023), 128151O (15 November 2023); https://doi.org/10.1117/12.3010722

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KEYWORDS

Data modeling

Satellites

Atmospheric modeling

Chemical analysis

Combustion

Aerosols

Carbon

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