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This study systematically analyzed the evolution of winter air quality and pollutant emissions in Lanzhou through integrated multi-source data, including ground-based ambient monitoring, nighttime light observations, and emission inventories. Utilizing radiosonde data from Yuzhong Station, surface meteorological measurements, and ERA5reanalysis, we quantified changes in upper-atmospheric and surface wind fields alongside atmospheric stability via linear trend analysis and Mann-Kendall tests to identify drivers of the post-pandemic pollution rebound. Significant reductions were observed in SO₂, PM_2.5, and PM₁0 concentrations over the past 15 winters, with post-pandemic (2022~2023) levels rebounding by 6.59% (PM_2.5) and 21.14% (PM₁₀) relative to 2019 baselines. Notable declines in primary pollutant emissions since 2000 were documented, demonstrating effective mitigation measures. Deteriorating meteorological dispersion conditions were characterized by a 20-year trend of declining surface wind speed and increasing inversion frequency, with winter valley cold pool intensity in 2022~2023 reaching 1.2 times the historical average. The synergistic effect of weakened near-surface ventilation and enhanced atmospheric stability was identified as the dominant mechanism driving the post-pandemic particulate matter rebound.

, authors=Yu-xuan HAO¹, Ying WANG^{1, 2, *}, Wei LI¹, Yan-fei DONG¹, Yan-yan ZHOU¹, Jian-xiong LIU¹, authorsList=Yu-xuan HAO, Ying WANG, Wei LI, Yan-fei DONG, Yan-yan ZHOU, Jian-xiong LIU, authorCompany=null, correspAuthors=Ying WANG, 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=1314917603085218723, articleId=1314917600920957857, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=后疫情时期兰州市冬季空气质量变化特征及其影响因素研究, columnId=1234106388364981004, journalTitle=中国环境科学, columnName=大气污染与控制, runingTitle=null, highlight=null, articleAbstract=

利用污染物监测、夜间灯光及排放清单等多源数据，系统分析了兰州市冬季空气质量和污染物排放演变特征，并基于兰州榆中探空站、地面气象站的监测数据与ERA5再分析资料，应用线性趋势分析和Mann-Kendall检验法，定量评估了高低空风速场和大气稳定度的变化趋势，揭示后疫情时期（2022~2023年冬季）污染物浓度反弹的驱动机制．结果表明：近15a冬季SO₂、PM_2.5和PM₁₀浓度显著下降，但后疫情期PM_2.5和PM₁₀浓度较2019年有所反弹（分别约为6.59%和21.14%）；污染物排放量演变特征显示2000年以来主要污染物排放量总体下降，污染减排成效显著．气象分析显示，近20a地面风速显著减弱、强逆温频率上升，2022~2023年冬季山谷热亏损强度达历史均值的 1.2倍．研究揭示，近地面通风能力下降与大气稳定层结增强的协同效应是后疫情期颗粒物浓度反弹的主导因素．

, authors=郝宇轩¹, 王颖^{1, 2, *}, 李伟¹, 董燕飞¹, 周燕艳¹, 刘建雄¹, authorsList=郝宇轩, 王颖, 李伟, 董燕飞, 周燕艳, 刘建雄, authorCompany=null, correspAuthors=王颖, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=0q441s7mJdM0215U9CCmsg==, magXml=M5xqC5oPodHlgL7r49IhOw==, pdfUrl=null, pdf=vBRl8XxPnrLJy30l21ltUQ==, pdfFileSize=3313573, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=BMGSMKqa3PzMnVk9mHCqFQ==, mapNumber=null, fund=null)}, authors=[Author(id=1314918042048488214, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314917600920957857, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=haoyx2023@lzu.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1314918042140762904, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314917600920957857, authorId=1314918042048488214, language=EN, stringName=Yu-xuan HAO, firstName=Yu-xuan, middleName=null, lastName=HAO, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=^1.College of atmospheric Science, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1314918042212066073, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314917600920957857, authorId=1314918042048488214, language=CN, stringName=郝宇轩, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=^1.兰州大学大气科学学院，甘肃 兰州 730000, bio={"content":"

郝宇轩（2000-），女，内蒙古乌海人，兰州大学硕士研究生，主要研究方向为空气污染数值模拟．发表论文1篇．haoyx2023@lzu.edu.cn.

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郝宇轩（2000-），女，内蒙古乌海人，兰州大学硕士研究生，主要研究方向为空气污染数值模拟．发表论文1篇．haoyx2023@lzu.edu.cn.

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