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The typical compound pollution of PM_2.5 and O₃ in Baoding City was investigated in this study. Objective weather classification of sea-level pressure and 10m wind fields in the Beijing-Tianjin-Hebei region during the autumn-winter and spring-summer seasons was conducted using the Principal Component T-mode (PCT) method. Backward trajectory analysis (PSCF, CWT) and meteorological-air quality modeling system (WRF-CAMx) were applied to identify the source contributions and transport pathways of PM_2.5 and O₃ under pollution-related weather types. From 2019 to 2022, the annual average PM_2.5 concentration in Baoding showed a significant decline of 26.9%, whereas O₃ exhibited a fluctuating trend with a slight reduction of only 2.2%, indicating limited improvement. Monthly average concentrations of both pollutants demonstrated pronounced seasonal patterns. In autumn and winter, high-pressure systems dominated, and weather types T5 (eastern high-pressure rear, 11.6%), T6 (saddle-type, 11.6%), and T9 (isobaric field, 5.2%) were most frequently associated with PM_2.5 pollution events. In contrast, low-pressure systems prevailed in spring and summer, with weather types S3 (isobaric field, 12.9%) and S7 (northwest low-pressure rear, 16.8%) contributing notably to O₃ pollution. Local emissions were identified as the dominant source of PM_2.5 during pollution weather types. Under T5, additional contributions originated mainly from Handan and Shijiazhuang; under T6, from Shanxi Province and Shijiazhuang; and under T9, from Shanxi and Inner Mongolia. For O₃ pollution, local sources accounted for the largest share. Under S3, transport from surrounding cities played a secondary role, whereas under S7, contributions from southwestern regions, including Henan, Handan, Shanxi, and Shijiazhuang, were more prominent.

, authors=Xing-yu FU, Shui-yuan CHENG^*, Chuan-da WANG, authorsList=Xing-yu FU, Shui-yuan CHENG, Chuan-da WANG, authorCompany=null, correspAuthors=Shui-yuan CHENG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1314917456548819752, articleId=1314917455798039334, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=保定市不同天气型下PM_2.5和O₃复合污染防治策略, columnId=1241049969449292093, journalTitle=中国环境科学, columnName=臭氧污染与控制, runingTitle=null, highlight=null, articleAbstract=

针对PM_2.5和O₃典型复合污染城市保定，利用PCT客观天气分型方法对秋冬季和春夏季京津冀地区的海平面气压场及10m风场进行天气分型，并通过后向轨迹（PSCF、CWT）及气象-空气质量模式（WRF-CAMx）对污染天气型下的PM_2.5与O₃进行来源解析，研究其贡献比例和传输路径，探究保定市重污染天气应对及不同天气型下复合污染防治策略．结果显示，保定市2019~2022年PM_2.5年平均浓度呈下降趋势，下降幅度为26.9%，O₃呈波动趋势，下降幅度仅为2.2%；月平均浓度呈现明显的季节性特点．秋冬季京津冀地区以高压场型为主，其中T5（东部高压后部，11.6%）、T6（鞍型场，11.6%）和T9（均压场，5.2%）是容易导致保定市PM_2.5污染的污染天气型；春夏季以低压场为主，易导致保定市O₃污染的天气类型为S3（均压场，12.9%）和S7（西北部低压后部，16.8%）；在PM_2.5污染天气型下，保定市的PM_2.5来源贡献均以本地排放为主．T5（东部高压后部）中保定市的PM_2.5其他贡献区域主要以邯郸、石家庄等西南路径为主；T6（鞍型场）中其他贡献区域主要以山西省和石家庄等西南路径为主；T9（均压场）中其他贡献区域主要以山西省及内蒙古地区等西北路径为主．在O₃污染天气型下，保定市的O₃本地贡献最高．在S3（均压场）下，其他地区贡献以保定周边城市传输影响为主；而S7（西北部低压后部）中其他地区贡献主要以河南省、邯郸、山西省、石家庄等西南路径输送为主．

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付兴宇（1999-），男，天津人，北京工业大学硕士研究生，主要从事大气污染防治及环境规划管理方面研究．发表论文1篇．1015789403@qq.com.

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付兴宇（1999-），男，天津人，北京工业大学硕士研究生，主要从事大气污染防治及环境规划管理方面研究．发表论文1篇．1015789403@qq.com.

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