基于多源数据的大理市臭氧污染特征与来源解析研究

Study on Ozone Pollution Characteristics and Source Apportionment in Dali City Based on Multi-Source Data

摘要: 为明确大理市臭氧(O₃)污染特征与主要来源，基于2018~2022年环境空气质量监测数据，结合挥发性有机物(VOCs)和氮氧化物(NO_x)排放清单及WRF-CAMx-PSAT数值模拟系统，对大理市O₃污染的时空分布、气象成因、前体物排放及来源贡献进行了研究。结果表明：大理市O₃污染呈“春高秋低、昼高夜低”特征，3~5月为污染高发期，高值区集中于城区及东部、东南部。VOCs和NO_x排放呈现市中心区域民用排放较为集中空间的分布特征，且VOCs排放的高值区与O₃污染高值区在空间上具有较好的对应关系。数值模拟表明：春季O₃污染分布为，天然源占52.9%、交通源占20.0%和工业源占19.9%为主导；区域传输以本地累积和边界条件为主。建议重点加强大理市主城区、西部工业聚集区及主要交通干道；春季提前启动预警防控，加强移动源、工业源和天然源管控。

Abstract: To clarify the characteristics and major sources of ozone (O₃) pollution in Dali City, this study investigated the spatiotemporal distribution, meteorological drivers, precursor emissions, and source contributions of O₃ pollution based on ambient air quality monitoring data from 2018 to 2022, combined with volatile organic compounds (VOCs) and nitrogen oxides (NO_x) emission inventories and the WRF-CAMx-PSAT numerical modeling system. The results showed that O₃ pollution in Dali exhibited a “high in spring and low in autumn, high in daytime and low at nighttime” pattern, with pollution episodes concentrated in March–May, and high-value areas concentrated in the urban center and the eastern and southeastern regions. VOCs and NO_x emissions showed spatial distribution characteristics with relatively concentrated civil emissions in the central urban area, and high-value zones of VOCs emissions corresponded well spatially with O₃ pollution hotspots. Numerical simulations indicated that natural sources (52.9%), mobile sources (20.0%), and industrial sources (19.9%) were the dominant contributors to spring O₃ pollution, while regional transport was primarily driven by local accumulation and boundary conditions. It is recommended to strengthen control measures in the main urban area, western industrial clusters, and major traffic arteries of Dali City; to initiate early warning and prevention in spring; and to enhance the regulation of mobile sources, industrial sources, and natural sources.