Article(id=1241049964210615177, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241049962679694215, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1717344000000, receivedDateStr=2024-06-03, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773818969061, onlineDateStr=2026-03-18, pubDate=1737302400000, pubDateStr=2025-01-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773818969061, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773818969061, creator=13701087609, updateTime=1773818969061, updator=13701087609, issue=Issue{id=1241049962679694215, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='1', pageStart='1', pageEnd='592', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773818968696, creator=13701087609, updateTime=1773819749443, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241053237428671382, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241049962679694215, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241053237428671383, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241049962679694215, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=11, endPage=18, ext={EN=ArticleExt(id=1241049964474856330, articleId=1241049964210615177, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Evolution characteristics of boundary layer inversion and its pollution effects during haze events in the Sichuan Basin, columnId=1234106386020365051, journalTitle=China Environmental Science, columnName=Air Pollution Control, runingTitle=null, highlight=null, articleAbstract=

Based on the second level sounding data and routine environmental meteorological monitoring data from four regions(Chengdu, Yibin, Dazhou, and Chongqing) of the Sichuan Basin, during the winter of 2014~2017, combined with Mie scattering liDAR detection data in Chengdu during the same period, the boundary layer structure was identified by atmospheric extinction coefficient profile, and the evolution characteristics and pollution effects of atmospheric boundary layer inversion during haze weather were investigated. The results indicated that: Surface Layer Inversion (SLI), Mixed Layer Inversion (MLI), and Aerosol Boundary Layer Inversion (ABI) represented the three fundamental forms of boundary layer inversion. They showed a gradually weakened trend from bottom up and mark spatial variation among different regions. With the evolution of haze events from the formation phase to the persistence phase, the frequency of the three-layer inversions significantly increased. In the process, the intensity and thickness of SLI gradually decreased. However, the intensity and thickness of MLI exhibited quite opposite trend. In the meantime, the base height of MLI also decreased. The intensity and thickness of ABI fluctuated all the time. The coexistence and co-evolution of SLI and MLI not only strongly inhibited the vertical dispersion of ground pollutants, but also contributed to the increased near-surface humidity, which in turn induced the accumulation of particulate matter at the surface and enhanced aerosol hygroscopic properties, thereby reducing ground-level visibility. The above results revealed complex evolutionary patterns of boundary layer inversion during haze episodes in the Sichuan Basin from a new perspective and lay the foundation for integrated studies on the tropospheric lower-level inversion.

, correspAuthors=Liu YANG, 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, authorCompany=null, fund=null, authors=null, authorsList=Li-yuan HE, Liu YANG, Yao ZHU, Chang-jian NI), CN=ArticleExt(id=1241049967641555886, articleId=1241049964210615177, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=四川盆地霾过程边界层逆温的演化特征及其污染效应, columnId=1234106388364981004, journalTitle=中国环境科学, columnName=大气污染与控制, runingTitle=null, highlight=null, articleAbstract=

利用四川盆地2014~2017年冬季4个地区(成都、宜宾、达州和重庆)的秒级探空资料和常规环境气象监测数据,结合同期成都的Mie散射激光雷达探测资料,通过大气消光系数廓线识别边界层结构,探究了霾天气过程中大气边界层逆温演化特征及其污染效应.结果表明:贴地逆温(SLI)、混合层顶逆温(MLI)以及气溶胶分界层逆温(ABI)是边界层逆温的3种基本形态.三层逆温一致表现为自下而上逐渐减弱的形态特征,但在地区之间呈现出明显的空间分异性.随着霾从形成期向发展期和持续期的渐进演化,三层逆温的发生频率显著上升,SLI的强度和厚度逐渐减小,MLI的强度和厚度则不断增加,底高也随之降低,ABI的强度和厚度呈波动变化.SLI和MLI的共存及其协同演变不仅强烈地抑制了地面污染物的垂直扩散,而且有利于近地面湿度的增加,进而诱发地面颗粒物的积聚以及吸湿性的增强,从而导致地面能见度降低.上述成果从新的视角揭示了四川盆地霾过程边界层逆温的复杂演化形态及其影响,也为后续针对对流层低层逆温的一体化研究奠定了基础.

, correspAuthors=杨柳, authorNote=null, correspAuthorsNote=
*责任作者,高级工程师,
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贺丽媛(2001-),女,贵州省毕节市人,硕士研究生,研究方向为大气物理与大气环境,.

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Environmental Science & Technology202144(7):76-83., articleTitle=Research on the relationship between mixed layer height and aerosol layer height in Chengdu, refAbstract=null)], funds=[Fund(id=1241049984171307582, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, awardId=2023YFC3709301, language=CN, fundingSource=国家重点研发计划(2023YFC3709301), fundOrder=null, country=null), Fund(id=1241049984355856970, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, awardId=2024NSFSC1983, language=CN, fundingSource=四川省科技教育联合基金项目(2024NSFSC1983), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241049967935157174, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, xref=1., ext=[AuthorCompanyExt(id=1241049967943545783, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, companyId=1241049967935157174, language=EN, country=null, 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caption=2014~2017年四川盆地冬季霾过程不同地区的逆温统计特征, figureFileSmall=hZdYzGvUROJVWPjnr6iA+Q==, figureFileBig=jJbdHAYxsZw1uM8jKO1Q8Q==, tableContent=null), ArticleFig(id=1241049978794209611, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=EN, label=Fig.4, caption=The correlation coefficients between indices of three-layer inversions and visibility, figureFileSmall=fuVuBtk2pw++Vhqy2jLb+g==, figureFileBig=yN+B+C8HsfDM27W9Ju/AcA==, tableContent=null), ArticleFig(id=1241049979217834335, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=CN, label=图4, caption=三层逆温指标与能见度之间的相关系数, figureFileSmall=fuVuBtk2pw++Vhqy2jLb+g==, figureFileBig=yN+B+C8HsfDM27W9Ju/AcA==, tableContent=null), ArticleFig(id=1241049979565961587, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=EN, label=Fig.5, caption=Variations of PM2.5 mass concentration and relative humidity during haze events, figureFileSmall=0f7L/AekVrs18UcCsUSuEA==, figureFileBig=/v7J8XsNOCgy/7zPONQ+SA==, tableContent=null), ArticleFig(id=1241049980111221116, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=CN, label=图5, caption=霾过程PM2.5质量浓度和相对湿度的变化, figureFileSmall=0f7L/AekVrs18UcCsUSuEA==, figureFileBig=/v7J8XsNOCgy/7zPONQ+SA==, tableContent=null), ArticleFig(id=1241049980467736968, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=EN, label=Table 1, caption=

Statistical characteristics of boundary layer inversion during winter haze events in the Sichuan Basin from 2014 to 2017

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逆温类型强度(℃/100m)厚度(m)频率(%)
SLI1.3110447.0
MLI0.548926.7
ABI0.498622.9
), ArticleFig(id=1241049980601954710, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=CN, label=表1, caption=

四川盆地2014~2017年冬季霾过程边界层逆温统计特征

, figureFileSmall=null, figureFileBig=null, tableContent=
逆温类型强度(℃/100m)厚度(m)频率(%)
SLI1.3110447.0
MLI0.548926.7
ABI0.498622.9
), ArticleFig(id=1241049980715200930, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=EN, label=Table 2, caption=

The boundary layer inversion characteristics during winter haze events in the Sichuan Basin at different time from 2014 to 2017

, figureFileSmall=null, figureFileBig=null, tableContent=
逆温类型08:0020:00
强度(℃/100m)厚度(m)频率(%)强度(℃/100m)厚度(m)频率(%)
SLI1.2813151.81.347742.3
MLI0.6210237.20.467516.1
ABI0.538421.60.458923.9
), ArticleFig(id=1241049980874584495, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=CN, label=表2, caption=

四川盆地2014~2017年冬季霾过程不同时次边界层逆温特征

, figureFileSmall=null, figureFileBig=null, tableContent=
逆温类型08:0020:00
强度(℃/100m)厚度(m)频率(%)强度(℃/100m)厚度(m)频率(%)
SLI1.2813151.81.347742.3
MLI0.6210237.20.467516.1
ABI0.538421.60.458923.9
), ArticleFig(id=1241049981025579452, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=EN, label=Table 3, caption=

The temporal evolution characteristics of the frequency of inversion of the boundary layer during haze events (%)

, figureFileSmall=null, figureFileBig=null, tableContent=
霾过程SLIMLIABI
形成期21.215.522.6
发展期31.023.025.6
持续期38.446.034.3
消亡期9.415.517.5
), ArticleFig(id=1241049981273043399, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=CN, label=表3, caption=

霾过程边界层逆温发生频率的时间演变特征(%)

, figureFileSmall=null, figureFileBig=null, tableContent=
霾过程SLIMLIABI
形成期21.215.522.6
发展期31.023.025.6
持续期38.446.034.3
消亡期9.415.517.5
), ArticleFig(id=1241049981398872534, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=EN, label=Table 4, caption=

The temporal evolution characteristics of boundary layer Inversion mean strength during haze events (℃/100m)

, figureFileSmall=null, figureFileBig=null, tableContent=
霾过程SLIMLIABI
形成期1.440.520.63
发展期1.400.570.41
持续期1.260.610.47
消亡期1.040.480.41
), ArticleFig(id=1241049983026262500, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=CN, label=表4, caption=

霾过程边界层逆温平均强度的时间演变特征(℃/100m)

, figureFileSmall=null, figureFileBig=null, tableContent=
霾过程SLIMLIABI
形成期1.440.520.63
发展期1.400.570.41
持续期1.260.610.47
消亡期1.040.480.41
), ArticleFig(id=1241049983227589102, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=EN, label=Table 5, caption=

The temporal evolution characteristics of boundary layer Inversion mean thickness during haze events (m)

, figureFileSmall=null, figureFileBig=null, tableContent=
霾过程SLIMLIABI
形成期1157799
发展期1108568
持续期1039891
消亡期799279
), ArticleFig(id=1241049983546356224, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=CN, label=表5, caption=

霾过程边界层逆温平均厚度的时间演变特征(m)

, figureFileSmall=null, figureFileBig=null, tableContent=
霾过程SLIMLIABI
形成期1157799
发展期1108568
持续期1039891
消亡期799279
), ArticleFig(id=1241049983793820182, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=EN, label=Table 6, caption=

The temporal evolution characteristics of boundary layer Inversion mean height during haze events (m)

, figureFileSmall=null, figureFileBig=null, tableContent=
霾过程MLI底高ABI底高MLI顶高ABI顶高
形成期2849183611017
发展期2589783431046
持续期2409993381090
消亡期2459373371016
), ArticleFig(id=1241049984020312618, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049964210615177, language=CN, label=表6, caption=

霾过程边界层逆温平均高度的时间演变特征(m)

, figureFileSmall=null, figureFileBig=null, tableContent=
霾过程MLI底高ABI底高MLI顶高ABI顶高
形成期2849183611017
发展期2589783431046
持续期2409993381090
消亡期2459373371016
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四川盆地霾过程边界层逆温的演化特征及其污染效应
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贺丽媛 1, 2 , 杨柳 3, * , 朱瑶 1, 2 , 倪长健 1, 2
中国环境科学 | 大气污染与控制 2025,45(1): 11-18
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中国环境科学 | 大气污染与控制 2025, 45(1): 11-18
四川盆地霾过程边界层逆温的演化特征及其污染效应
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贺丽媛1, 2 , 杨柳3, * , 朱瑶1, 2, 倪长健1, 2
作者信息
  • 1.成都信息工程大学大气科学学院,四川 成都 610225
  • 2.成都平原城市气象与环境四川省野外科学观测研究站,四川 成都 610225
  • 3.成都市气象局,四川 成都 611130
  • 贺丽媛(2001-),女,贵州省毕节市人,硕士研究生,研究方向为大气物理与大气环境,.

通讯作者:

*责任作者,高级工程师,
Evolution characteristics of boundary layer inversion and its pollution effects during haze events in the Sichuan Basin
Li-yuan HE1, 2 , Liu YANG3, * , Yao ZHU1, 2, Chang-jian NI1, 2
Affiliations
  • 1.College of Atmospheric Science, Chengdu University of Information Technology, Chengdu 610225, China
  • 2.Chengdu Plain Urban Meteorology and Environment Observation and Research Station of Sichuan Province, Chengdu 610225, China
  • 3.Chengdu Meteorological Bureau, Chengdu 610072, China
出版时间: 2025-01-20
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利用四川盆地2014~2017年冬季4个地区(成都、宜宾、达州和重庆)的秒级探空资料和常规环境气象监测数据,结合同期成都的Mie散射激光雷达探测资料,通过大气消光系数廓线识别边界层结构,探究了霾天气过程中大气边界层逆温演化特征及其污染效应.结果表明:贴地逆温(SLI)、混合层顶逆温(MLI)以及气溶胶分界层逆温(ABI)是边界层逆温的3种基本形态.三层逆温一致表现为自下而上逐渐减弱的形态特征,但在地区之间呈现出明显的空间分异性.随着霾从形成期向发展期和持续期的渐进演化,三层逆温的发生频率显著上升,SLI的强度和厚度逐渐减小,MLI的强度和厚度则不断增加,底高也随之降低,ABI的强度和厚度呈波动变化.SLI和MLI的共存及其协同演变不仅强烈地抑制了地面污染物的垂直扩散,而且有利于近地面湿度的增加,进而诱发地面颗粒物的积聚以及吸湿性的增强,从而导致地面能见度降低.上述成果从新的视角揭示了四川盆地霾过程边界层逆温的复杂演化形态及其影响,也为后续针对对流层低层逆温的一体化研究奠定了基础.

霾过程  /  边界层  /  逆温  /  污染效应  /  四川盆地

Based on the second level sounding data and routine environmental meteorological monitoring data from four regions(Chengdu, Yibin, Dazhou, and Chongqing) of the Sichuan Basin, during the winter of 2014~2017, combined with Mie scattering liDAR detection data in Chengdu during the same period, the boundary layer structure was identified by atmospheric extinction coefficient profile, and the evolution characteristics and pollution effects of atmospheric boundary layer inversion during haze weather were investigated. The results indicated that: Surface Layer Inversion (SLI), Mixed Layer Inversion (MLI), and Aerosol Boundary Layer Inversion (ABI) represented the three fundamental forms of boundary layer inversion. They showed a gradually weakened trend from bottom up and mark spatial variation among different regions. With the evolution of haze events from the formation phase to the persistence phase, the frequency of the three-layer inversions significantly increased. In the process, the intensity and thickness of SLI gradually decreased. However, the intensity and thickness of MLI exhibited quite opposite trend. In the meantime, the base height of MLI also decreased. The intensity and thickness of ABI fluctuated all the time. The coexistence and co-evolution of SLI and MLI not only strongly inhibited the vertical dispersion of ground pollutants, but also contributed to the increased near-surface humidity, which in turn induced the accumulation of particulate matter at the surface and enhanced aerosol hygroscopic properties, thereby reducing ground-level visibility. The above results revealed complex evolutionary patterns of boundary layer inversion during haze episodes in the Sichuan Basin from a new perspective and lay the foundation for integrated studies on the tropospheric lower-level inversion.

haze event  /  boundary layer  /  inversion  /  pollution effect  /  the Sichuan Basin
贺丽媛, 杨柳, 朱瑶, 倪长健. 四川盆地霾过程边界层逆温的演化特征及其污染效应. 中国环境科学, 2025 , 45 (1) : 11 -18 .
Li-yuan HE, Liu YANG, Yao ZHU, Chang-jian NI. Evolution characteristics of boundary layer inversion and its pollution effects during haze events in the Sichuan Basin[J]. China Environmental Science, 2025 , 45 (1) : 11 -18 .
作为一种特殊的热力结构形态,逆温直接影响动量、热量、水汽和气溶胶在大气中的垂直交换,是区域天气、气候和环境空气质量演化的重要影响因子[1].
受天气系统、边界层过程以及地形等多因素的影响,逆温的成因十分复杂,并呈现出显著的时空变化特征.周书华等[2]将边界层逆温分为贴地逆温、脱地逆温和高悬逆温,并分析了成都地区边界层逆温的统计特征.贴地逆温一般在傍晚日落时形成,早晨日出后消散,并表现为冬季强,夏季弱等特点[3-4].就逆温在我国的空间分布而言,华东、华南沿海地区逆温强度最大,厚度最厚,在盆地发生强逆温的频率更高.Anquetin等[5]通过模拟山谷逆温的演化过程,指出夜间逆温层的垂直范围更多受地面性质和山谷几何形状的影响.对霾过程的WRF模拟试验表明,地形作用可促进高空逆温形成及贴地逆温加强,是导致重霾发生的一个关键因素[6-7].杜荣光等[8]分析了逆温对污染物浓度的影响,发现污染物浓度与逆温的发生频率、强度、厚度呈正相关,与逆温层底高呈负相关.针对重霾的研究表明,相比于逆温频率与厚度,逆温强度与PM2.5浓度之间的相关性更强[9].Miao等[10]的研究发现,边界层上的暖平流会导致平流逆温形成,进而抑制边界层发展并导致污染的加重.由此可见,作为稳定的大气层结,逆温层像盖子一样阻碍污染物在垂直方向的扩散,导致污染物在边界层内大量累积,一直是区域环境空气质量预报的关键污染潜势.
四川盆地紧邻青藏高原,盆地外围与底部的最大高度差超过2500m,深盆地形是四川盆地独特的地形特征.Feng等[11]基于秒级探空资料的分析表明,出现在2200~3500m之间的对流层低层逆温(LTI)频发是四川盆地逆温的独特之处,LTI的形成和演化是地形诱导的不同高度的层状流的协同作用和背风坡的地形遮蔽作用的结果.Ning等[12]分析了四川盆地西北部冬季8次大气重污染过程,指出高原干低值天气系统东移,下沉增温造成边界层顶以上形成强逆温层,从而导致区域大气重污染的形成.危诗敏等[13]指出,四川盆地冬季普遍存在多层逆温现象,多层逆温进一步加大了中度及重度污染出现的可能性.其中,针对成都地区的研究表明,逆温层数对空气污染的指示意义要优于逆温厚度和逆温强度[14].进一步研究指出,作为四川盆地多层逆温的重要组成部分,边界层逆温与气溶胶垂直分布之间存在显著的互馈作用[15].朱育雷等[16-17]研究了大气消光系数的垂直分布形态,提出了识别混合层和气溶胶分界层的新算法,并发现混合层顶以及气溶胶分界层和逆温之间均存在很好的对应关系.虽然已经围绕四川盆地多层逆温及其影响开展了大量的研究,但现有的边界层逆温分层缺乏明确的物理意义,弱化了逆温统计结果对其污染效应的表征能力;另外,迄今为止,针对霾过程边界层逆温演化的细致结构及其配置关系尚不清晰.
着眼于典型霾天气过程的选取以及研究成果的比对,本文利用四川盆地2014~2017年冬季4个地区(成都、宜宾、达州和重庆)的秒级探空资料和常规环境气象监测数据,结合同期位于成都的Mie散射激光雷达探测资料,通过大气消光系数廓线识别边界层结构,探究了贴地逆温(SLI)、混合层顶逆温(MLI)以及气溶胶分界层逆温(ABI)在霾过程中的演化特征,从全新的视角阐明边界层逆温对灰霾演化的响应关系及其污染效应.
本文利用的资料包括四川盆地2014~2017年冬季(12月~次年2月)4个高空气象观测站(成都、宜宾、达州和重庆)每日两次(即北京时间8时、20时)的秒级探空资料,以及该时段同时次大气能见度(V)、相对湿度(RH)、地面细颗粒物质量(PM2.5)浓度和位于西南交通大学九里堤校区的Mie散射激光雷达数据.四川盆地4个高空气象观测站具体位置为成都市温江站、宜宾市宜宾站、重庆市沙坪坝站和达州市达川站,分布情况如图1所示.
首先,剔除出现降水、沙尘以及大风现象所在日的全部数据;其次,剔除仪器烘干后相对湿度仍大于40%的异常数据、超出界限值的数据、连续无变化的数据及缺测数据;最后,根据《霾的观测和预报等级》(QX/T113—2010)[18],排除其它能导致低能见度事件的情况,将霾时判定为满足小时能见度数值低于10km且环境相对湿度低于80%,或当环境相对湿度在80%~95%之间时,PM2.5质量浓度高于75 µg/m3的时次,将日界定为北京时20时,一日不低于1/4个定时观测时次判别为霾,该日记为霾日;当霾跨日界持续时长不低于1/4定时时次,但日界前(或后)持续时长不足1/4定时时次且大于1/8定时时次,则相应的上跨日(或下跨日)也记为霾日.基于上述判定原则,在研究时段内共筛选出四川盆地4个站点36次持续性霾过程.
本文中逆温层定义为逆温强度大于等于0℃/100m且逆温厚度大于40m的大气层结[15].逆温发生频率定义为逆温出现的次数占总探空观测次数的百分比,即F=(n/N)×100%.逆温厚度定义为逆温层顶高度与逆温层底高度之差,即D=H2-H1,其中H1为逆温层底高度,H2为逆温层顶高度,单位:m.逆温强度定义为逆温层中每100m的温度变化值,即I=(t2-t1)/D×100,其中t1为逆温层底温度(℃),t2为逆温层顶温度(℃),单位:℃/100m.
大气消光系数廓线直观反映大气消光能力随高度的变化,并与颗粒物粒径分布、化学组成、密度以及浓度参数密切相关.大气消光系数廓线是地气之间热力和动力综合作用的结果,其形态特征为边界层热力结构的诊断提供新途径.
混合层定义为湍流特征不连续界面以下的大气,表征污染物在垂直方向被热力湍流稀释的范围,即低层空气热力对流与动力湍流输送所能达到的高度.朱育雷等[16]根据混合层顶上下大气消光系数分别表现为整体缓变区与显著下降区的形态特征,据此提出了混合层识别的logistic曲线算法,并指出混合层顶与逆温存在很好的伴生特征,且混合层高度对地面细颗粒物的演化具有很好的指示意义.边界层顶为气溶胶消光系数和分子消光系数之间的过渡区,朱育雷等[17]基于根据大气消光系数在此过渡区S型型态特征,提出了气溶胶分界层Sigmoid函数的计算方案,并指出气溶胶分界层附近同样存在逆温的伴生现象.混合层顶逆温和气溶胶分界层逆温与大气消光系数配置关系的概念模型分别如图2所示[16-17].
为此,将边界层逆温自下而上分为贴地逆温(SLI)、混合层顶逆温(MLI)以及气溶胶分界层逆温(ABI),基于成都地区边界层逆温的识别结果,类比分析其它3个地区霾天气过程中大气边界层逆温演化特征及其污染效应.其中,MLI和ABI的形成和演化主要与边界层湍流过程有关,SLI的形成和演化主要与地气辐射过程有关.
统计了四川盆地2014~2017年冬季4个地区霾过程边界层逆温的结构特征,如表1所示.由表1可见,SLI、MLI以及ABI的发生频率分别为47.0%、26.7%、22.9%,平均厚度分别为104m、89m、86m,平均强度分别为1.31℃/100m、0.54℃/100m、0.49℃/100m,其中SLI的频率、厚度均高于文献[15]针对四川盆地冬季的对应统计结果.这一统计结果表明,SLI、MLI以及ABI不仅具有明确的物理意义,也是霾过程边界层逆温的3种基本形态.为此,本文对霾过程SLI、MLI以及ABI时空演化特征进行了细致的诊断,以期进一步厘清边界层逆温的协同关系及其空气污染效应.
表1还可发现,平均逆温强度表现为SLI最强,MLI次之,ABI最弱;平均逆温厚度表现为SLI最厚,MLI次之,ABI最薄;逆温发生频率表现为SLI最多,MLI次之,ABI最少.因此,三层逆温自下而上一致表现为强度逐渐减弱,厚度逐渐减小,频率逐渐下降.进一步统计了SLI、MLI以及ABI在08:00和20:00的特征,如表2所示.由表2可见,SLI、MLI以及ABI强度自下而上同样呈现出为逐渐减弱的形态特征,这与表1的统计结果一致.就SLI和MLI而言,其强度、厚度和频率均呈现出较为显著的日变化特征,其中08:00逆温的厚度和频率要显著大于20:00,但强度略小;对ABI而言,其厚度和频率在8:00和20:00总体差异不大,但8时的强度要更强;进一步统计表明,08:00和20:00MLI的平均高度分别为236m、283m,即08:00MLI平均高度更低.
分别统计了四川盆地4个地区2014~2017年冬季霾过程边界层逆温结构特征,如图3所示.由图3可见,就SLI而言,成都地区08:00与20:00SLI的发生频率分别高达81.1%、60.5%,强度分别为1.92℃/100m、2.10℃/100m,在4个地区当中成都地区逆温发生频率最高、强度最强,重庆和达州次之,宜宾最弱;4个地区08:00与20:00SLI的厚度总体相当,其中达州地区偏大.成都地区这一统计结果与周书华等[3]的研究结果一致,但其频率、强度与厚度均有显著提升,这体现了霾过程逆温配置关系的特殊性.其中,成都地区逆温强度高达2℃/100m,远高于其他3个地区,与文献[18]的研究结果一致.就MLI而言,达州地区08:00与20:00MLI的发生频率分别为37.4%、22.4%,强度分别为0.84℃/100m、0.47℃/100m,厚度分别为121m、67m,在4个地区当中达州地区MLI日发生频率较高、平均强度较强、平均厚度较大,其余3个地区08:00与20:00MLI的平均发生频率、强度与厚度总体相当.这一空间分布与Feng等[19]针对四川盆地脱地逆温的统计结果一致,但其发生频率总体略有增加.这可能与逆温层划分的方法存在差异有关.就ABI而言,重庆地区8:00与20:00 ABI的强度分别为0.74℃/100m、0.51℃/100m,厚度分别为91m、99m,在4个地区中强度更强、厚度更大.另外,除了重庆20时的ABI发生频率超过30%外,其余ABI的发生频率都保持在20%左右.相比于SLI和MLI而言,ABI距离下垫面最高(均值在1000m左右),其频率、强度和厚度在4个地区中的变化幅度最小.这与文献[1520]针对四川盆地低空逆温的研究结果一致.上述分析表明,四川盆地边界层逆温包括SLI、MLI以及ABI 3种基本的逆温形态,SLI、MLI以及ABI的结构呈现出复杂的空间分布和日变化特征.这是地气之间热力和动力作用的结果,其成因这不仅与区域自然地理背景以及城市化进程有关,霾过程城市气溶胶的温度效应可能也是其中一个关键的影响因素[21-23].
按文献[24]提供的方案,根据大气能见度的变化将四川盆地持续性霾过程分为形成期、发展期、持续期以及消亡期,分别统计了边界层逆温(频率、强度、厚度及高度)的时间演变特征.
统计了霾过程边界层逆温频率的时间演变特征,如表3所示.由表3可见,SLI在霾过程形成期、发展期与持续期的发生频率分别为21.2%、31.0%、38.4%,MLI在霾过程形成期、发展期与持续期的发生频率分别为15.5%、23.0%、46.0%,ABI在霾过程形成期、发展期与持续期的发生频率分别为22.6%、25.6%、34.3%.上述分析结果表明,随着霾过程从形成期到持续期的渐进演变,三层逆温的发生频率均呈显著上升的趋势,并在持续期达到峰值,后在消亡期急剧降低.
统计了霾过程边界层逆温平均强度的时间演变特征,如表4所示.由表4可见,在霾过程形成期、发展期与持续期,SLI的平均逆温强度分别为1.44℃/100m、1.40℃/100m、1.26℃/100m,MLI的平均强度分别为0.52℃/100m、0.57℃/100m、0.61℃/100m,ABI的平均强度分别为0.63℃/100m、0.41℃/100m、0.47℃/100m.上述分析表明,随着霾过程从形成期到持续期的渐进演变,SLI的平均强度在形成期达到峰值后呈不断减弱的趋势,MLI的平均强度则呈不断上升的趋势并在持续期达到峰值,另外,ABI的平均强度在霾过程中呈现波动特征.
统计了霾过程边界层逆温平均厚度的时间演变特征,如表5所示.由表5可见,在霾过程形成期、发展期与持续期,SLI的平均厚度分别为115m、110m、103m,MLI的平均厚度分别为77m、85m、98m,ABI的平均厚度分别为99m、68m、91m.上述分析表明,随着霾过程从形成期到持续期的渐进演变,SLI的平均厚度在形成期达到峰值后呈不断减弱的趋势,MLI的平均厚度则呈持续上升趋势并同样在持续期达到峰值,另外,ABI的平均厚度在霾过程中亦呈现波动特征.即霾过程边界层逆温的强度和厚度的演变呈现出总体一致的特征.
统计了霾过程边界层逆温高度的时间演变特征,如表6所示.由表6可见,在霾过程形成期、发展期与持续期,MLI的平均底高分别为284m、258m、240m,顶高分别为361m、343m、338m,ABI的平均底高分别为918m、978m、999m,顶高分别为1017m、1046m、1090m.上述分析表明,随着霾过程从形成期到持续期的演变,MLI的平均底高与顶高均呈现持续降低的趋势,ABI的平均底高与顶高均呈现不断上升的趋势.消亡期MLI平均底高和顶高略有抬升,ABI平均底高和顶高则有所降低.
综上所述,随着霾过程从形成期向发展期到持续期的渐进演变,三层逆温发生频率均显著上升,SLI的强度和厚度逐渐减小,MLI的强度和厚度则不断增加,底高也呈现出降低的趋势,ABI的强度和厚度呈现波动变化.
已有研究指出[25],虽然污染物的过量排放是造成灰霾的内因,但低大气能见度事件的发生却主要归结为不利于污染物散布的多尺度气象条件.为厘清边界层逆温对灰霾的影响,分析了三层逆温的不同指标(强度、厚度和底高)与大气能见度之间的关系,见图4.由图4可见,SLI、MLI和ABI强度与大气能见度的相关系数分别为-0.19、-0.33、-0.01,SLI、MLI和ABI厚度与大气能见度的相关系数分别为-0.46、-0.18、0.12,MLI和ABI底高与大气能见度的相关系数分别为0.35和-0.10.其中,SLI厚度和MLI底高与大气能见度的相关系数通过了0.05显著性检验,即SLI厚度和MLI底高是影响大气能见度最重要的两个边界层逆温指标.
研究发现[26],大气能见度与颗粒物质量浓度及相对湿度的变化密切相关,低湿度条件下大气能见度的变化主要取决于颗粒物质量浓度的改变,而高湿条件下气溶胶吸湿对大气能见度的影响则显著增加.为此,绘制了PM2.5质量浓度和相对湿度在霾过程的变化图,见图5.由图5可见,在霾过程形成期、发展期与持续期,PM2.5平均质量浓度分别为92μg/m3、127μg/m3、176μg/m³,平均相对湿度的大小分别为76.8%、77.6%、80.2%.即随着霾过程从形成期到持续期的渐进演变,PM2.5平均质量浓度与平均相对湿度均呈现出增长的趋势.
上述分析表明,随灰霾的渐进演变,边界层逆温强度、厚度和高度均有显著的变化,进而诱发颗粒物质量浓度和相对湿度的响应,由此导致大气能见度的相应改变.
在霾的形成期,夜间的辐射冷却导致地面大气迅速降温,形成强而厚的SLI.作为贴地的一种稳定的大气层结,SLI的存在像“顶盖”一样阻止地面污染物向上扩散稀释,颗粒物在近地面不断累积.因此,SLI是灰霾的关键诱发和启动因子.在霾的发展期和持续期,随着颗粒物浓度的渐进累积以及颗粒物廓线形态的改变,气溶胶与边界层的相互作用加强,颗粒物热力作用使得地面长波辐射冷却作用减弱,SLI强度逐渐减小,MLI强度与厚度则不断增加,底高也随之大幅降低[27].混合层为湍流特征不连续界面以下的大气,代表了污染物在垂直方向上被湍流稀释的高度,是表征区域大气环境容量三大污染潜势指标之一.一般情况下,混合层高度越低,环境空气中的污染物浓度就越高.因此,MLI的增强和底高的下降及其与SLI共存进一步压缩了颗粒物的散布空间,降低了近地面物质和能量的交换水平,不仅强烈地抑制地面污染物的垂直扩散,还有利于近地面湿度的增加.刘凡等[28]的研究指出,相对湿度的增加能显著提升硫氧化率和氮氧化率,导致二次颗粒物(硫酸盐、硝酸盐和铵盐)在细粒物中占比的明显上升,由细颗物吸湿性诱发的大气消光效应也显著增强.由此可见,随着灰霾从发展期向持续期的渐进演变,MLI与SLI共同导致地面细颗粒物质量浓度的上升和颗粒物吸湿的加强,进而诱发低大气能见度的出现.因此,MLI与SLI的共存及其协同作用是灰霾演变的关键推动因子.在霾的消亡期,随着大气环流的调整,前期逆温的形态和结构被破坏,大气扩散能力显著增强,细颗粒物质量浓度和相对湿度也随之降低,大气能见度不断改善.
值得注意的是,ABI也是边界层逆温的重要配置,其底高表征气溶胶在大气铅直方向上散布的上限.研究表明[29],受热力对流、机械力和风切变作用的影响,ABI的形成发展较为复杂.目前,尚缺乏针对对ABI形成机制及其污染效应的系统研究,相关工作另文分析.
3.1 四川盆地边界层逆温包括SLI、MLI以及ABI 3种基本的逆温形态,三层逆温自下而上一致呈现出逐渐减弱的形态特征,但在地区之间呈现出明显的的空间分异性.其中,SLI在成都发生频率最高、强度最强,MLI在达州发生频率最高、强度最强,ABI在四个地区中整体变化幅度较小.
3.2 随着霾从形成期向发展期到持续期的渐进演变,三层逆温发生频率均显著上升,SLI的强度和厚度逐渐减小,MLI的强度和厚度则不断增加,底高也呈现出降低的趋势,ABI的强度和厚度呈现波动变化.
3.3 SLI是灰霾的关键诱发和启动因子,MLI与SLI的共存及其协同作用是灰霾演变的关键推动因子.
  • 国家重点研发计划(2023YFC3709301)
  • 四川省科技教育联合基金项目(2024NSFSC1983)
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2025年第45卷第1期
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  • 接收时间:2024-06-03
  • 首发时间:2026-03-18
  • 出版时间:2025-01-20
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  • 收稿日期:2024-06-03
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国家重点研发计划(2023YFC3709301)
四川省科技教育联合基金项目(2024NSFSC1983)
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    1.成都信息工程大学大气科学学院,四川 成都 610225
    2.成都平原城市气象与环境四川省野外科学观测研究站,四川 成都 610225
    3.成都市气象局,四川 成都 611130

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2种不同金属材料的力学参数

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Genus
种数
Number of
species
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species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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