Wind erosion from farmland is a significant contributor to atmospheric particulate matter, particularly PM10 (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 PM10 concentrations in the NCP. Results indicated that wind erosion from agricultural fields in the NCP produced approximately 33.8 × 105 tons of PM10 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 PM10 concentrations. The findings revealed that farmland emissions contributed approximately 13% of atmospheric PM10 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.

中文翻译：

---

华北平原农田扬尘排放对颗粒物浓度的贡献：WRF-Chem 和 WEPS 模型的融合


农田的风蚀是大气颗粒物的重要贡献者，尤其是在华北平原 （NCP） 等农业活动密集的地区，PM10（空气动力学直径≤ 10 μm 的大气颗粒物）。然而，农田扬尘排放对区域空气质量的具体影响仍未得到充分探索。本研究将风蚀预报系统 （WEPS） 模型与天气研究和预报模型相结合，结合化学 （WRF-Chem），以研究农业粉尘排放对 NCP 中 PM10 浓度的影响。结果表明，NCP 农田的风蚀每年产生约 33.8 × 105 吨 PM10。这些排放主要集中在 10 月至次年 4 月的冬季，其中排放量最高的是河北省、河南省和山东省。使用 WRF-Chem 模型的情景实验，我们进一步量化了农业粉尘排放对大气 PM10 浓度的贡献。研究结果显示，在冬季（1 月和 12 月），农田排放约占大气 PM10 浓度的 13%，凸显了农业活动在区域空气污染中的重要作用。本研究强调了将农田风蚀纳入化学传输模型的重要性，以更准确地了解和减轻农业活动对全球农业地区大气污染的影响。