Ye Xinpeng, Yang Jiaer, Chen Zhiwen, Liu Gang, Sun Jian, Jiang Qian, Huang Xin, Gao Yang, Niu Xinyi, Xu Hongmei, Li Guohui, Shen Zhenxing
Department of Environmental Science and Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Jilin Shize Environmental Protection Technology Co., Ltd., Changchun 130001, China.
Environ Int. 2025 Jul;201:109580. doi: 10.1016/j.envint.2025.109580. Epub 2025 Jun 3.
In agricultural regions of northern China, PM (particulate matter with aerodynamic diameter less than 2.5 μm) pollution driven by biomass burning remains a critical environmental challenge, yet uncertainties persist in source apportionment due to methodological limitations and insufficient multi-method validation in agriculturally intensive areas. This study synergistically applied receptor modeling (PMF, Positive Matrix Factorization), emission inventory, and WRF-Chem (Weather Research and Forecasting model coupled with Chemistry) simulations to quantify biomass burning contributions in Siping City, Jilin Province, using year-round PM compositional data (July 2021-June 2022) and localized emission parameters. The PMF model resolved six sources, identifying biomass burning as the dominant contributor (35.10 %), corroborated by emission inventory revisions incorporating satellite-derived burned area mapping (50.73 km), which attributed 37.50 % of total PM emissions to biomass burning. WRF-Chem simulations, driven by the revised inventory, demonstrated that biomass burning sources collectively contributed 40.13 % to ambient PM during an episode, with residential and open burning of biomass accounting for 28.12 % and 12.01 %, respectively. These multi-method results consistently highlight biomass burning's dominance (one-third of total emissions). The findings necessitate prioritizing residential biomass emission controls through clean energy transitions, stricter enforcement of combustion regulations, and integrated management strategies to mitigate air quality degradation in agricultural regions.
在中国北方农业地区，生物质燃烧驱动的细颗粒物（空气动力学直径小于2.5微米的颗粒物）污染仍是一项严峻的环境挑战，但由于方法学限制以及农业密集地区多方法验证不足，源解析仍存在不确定性。本研究综合应用受体模型（正矩阵因子分解法）、排放清单以及WRF-Chem（气象研究与预报模型耦合化学）模拟，利用全年细颗粒物成分数据（2021年7月至2022年6月）和本地化排放参数，量化吉林省四平市生物质燃烧的贡献。正矩阵因子分解模型解析出六个来源，确定生物质燃烧为主要贡献源（35.10%），纳入卫星衍生燃烧面积制图（50.73平方千米）的排放清单修订佐证了这一点，该清单将37.50%的细颗粒物排放归因于生物质燃烧。由修订后的排放清单驱动的WRF-Chem模拟表明，在一次事件期间，生物质燃烧源对环境细颗粒物的总贡献为40.13%，其中生物质的居民燃烧和露天燃烧分别占28.12%和12.01%。这些多方法结果一致凸显了生物质燃烧的主导地位（占总排放量的三分之一）。研究结果表明，有必要通过清洁能源转型、更严格执行燃烧法规以及综合管理策略，优先控制居民生物质排放，以减轻农业地区的空气质量恶化。
