Contribution of dust emissions from farmland to particulate matter concentrations in North China Plain: Integration of WRF-Chem and WEPS model.

Environ Int

Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, Henan 475004, China; Henan Key Laboratory of Air Pollution Control and Ecological Security (Henan University), Kaifeng, Henan 475004, China. Electronic address:

Published: December 2024

Wind erosion from farmland is a significant contributor to atmospheric particulate matter, particularly PM (atmospheric particulate matter with an aerodynamic diameter ≤ 10 μm), in regions with intensive agricultural activities such as the North China Plain (NCP). However, the specific impact of farmland dust emissions on regional air quality remains underexplored. This study integrated the Wind Erosion Prediction System (WEPS) model with the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to investigate the effect of agricultural dust emissions on PM concentrations in the NCP. Results indicated that wind erosion from agricultural fields in the NCP produced approximately 33.8 × 10 tons of PM annually. These emissions are predominantly concentrated during the winter months from October to next April, with the highest emissions occurring in Hebei, Henan, and Shandong provinces. Using scenario experiments with the WRF-Chem model, we further quantified the contribution of agricultural dust emissions to atmospheric PM concentrations. The findings revealed that farmland emissions contributed approximately 13% of atmospheric PM concentrations during winter months (January and December), underscoring the significant role of agricultural activities in regional air pollution. This study highlights the importance of including farmland wind erosion into chemical transport models to more accurately understand and mitigate the effects of agricultural activities on atmospheric pollution in agricultural regions worldwide.

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Source
http://dx.doi.org/10.1016/j.envint.2024.109191DOI Listing

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