Article(id=1314922992312869020, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314922986466009203, 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=1754582400000, receivedDateStr=2025-08-08, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791431671455, onlineDateStr=2026-10-08, pubDate=1773936000000, pubDateStr=2026-03-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791431671455, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791431671455, creator=13701087609, updateTime=1791431671455, updator=13701087609, issue=Issue{id=1314922986466009203, tenantId=1146029695717560320, journalId=1234093305789726721, year='2026', volume='46', issue='3', pageStart='1185', pageEnd='1776', issueExtLink='null', onlineDate='null', pubDate='1773936000000', pubDateStr='2026-03-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1791431670061, creator='13701087609', updateTime=1791431955369, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1314924183251935526, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314922986466009203, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1314924183251935527, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314922986466009203, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1229, endPage=1237, ext={EN=ArticleExt(id=1314922992522584221, articleId=1314922992312869020, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Spatial distribution of near-surface atmospheric CH
4 and CO
2 concentrations and their carbon isotopic compositions in the coastal region of eastern China, columnId=1234106386020365051, journalTitle=China Environmental Science, columnName=Air Pollution Control, runingTitle=null, highlight=null, articleAbstract=
The concentration and carbon isotope compositions (δ13C-CH4, δ13C-CO2) of methane (CH4) and carbon dioxide (CO2) along the coastal of eastern China were studied using vehicle mounted mobile measurement methods. The results indicated that the CH4 concentration was observed to range from (1.84~2.94) ×10-6, with an average concentration of 2.09×10-6. The highest value was recorded in Jiangmen, Guangdong (2.32×10-6), while the lowest value was recorded in Zhangzhou, Fujian (1.94×10-6). The CO2 concentration was found to range from (420.51~857.33) ×10-6, with an average concentration of 525.70×10-6. The highest value was measured in Shenzhen, Guangdong (599.08×10-6), and the lowest value was measured in Nantong, Jiangsu (477.42×10-6). Both CH4 and CO2 levels in the study area were found to exceed the atmospheric background values. The δ13C-CH4 values ranged from-62.62‰ to -29.70‰, with an average of -43.65‰. The highest value was observed in Qingdao, Shandong (-40.24‰), and the lowest value was observed in Zhangzhou, Fujian (-48.25‰). The δ13C-CO2 values ranged from -28.64‰ to -9.19‰, with an average of -17.53‰. The highest value was recorded in Nantong, Jiangsu (-14.45‰), and the lowest value was recorded in Shenzhen, Guangdong (-19.13‰). In the study area, CH4 concentration was found to be positively correlated with its carbon isotope signature, while CO2 concentration was negatively correlated with its carbon isotope signature. Per capita GDP, the number of civilian vehicles, livestock inventory, and rice cultivation area were all positively correlated with CH4 concentration and its carbon isotope signature. In contrast, the forest coverage rate was negatively correlated with CH4 concentration and its carbon isotope signature. δ13C (CO2) was utilized to trace the sources and sinks of atmospheric CO2 along the coastal regions of Shandong, Jiangsu, Shanghai, Zhejiang, Fujian, and Guangdong. Their respective δ13C (CO2) source signatures (δ13Cs) were determined to be: -37.90‰, -37.67‰, -41.24‰, -34.12‰, -33.99‰, and -32.39‰. These values indicated that the combustion of petroleum and natural gas was identified as the primary contributing source to CO2 emissions in the study area.
, authors=Tian-yu BIAN
1, 2, Xiao-yong DUAN
2, 3, *, Gang TONG
2, 4, Xue LI
2, 3, Ping YIN
2, 3, Ke CAO
2, 3, Bin CHEN
2, 3, Da-hai ZHANG
1, authorsList=Tian-yu BIAN, Xiao-yong DUAN, Gang TONG, Xue LI, Ping YIN, Ke CAO, Bin CHEN, Da-hai ZHANG, authorCompany=null, correspAuthors=Xiao-yong DUAN, 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=1314922992849739934, articleId=1314922992312869020, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=中国东部沿海近地表大气CH
4和CO
2浓度及碳同位素空间分布, columnId=1234106388364981004, journalTitle=中国环境科学, columnName=大气污染与控制, runingTitle=null, highlight=null, articleAbstract=
利用车载移动测量方法研究了中国东部沿海的甲烷(CH4)、二氧化碳(CO2)浓度及其碳同位素组成(δ13C-CH4、δ13C-CO2).结果表明:CH4浓度变化范围为(1.84~2.94)×10-6,平均浓度为2.09×10-6,最高值在广东江门(2.32×10-6);最低值在福建漳州(1.94×10-6).CO2浓度变化范围为(420.51~857.33)×10-6,平均浓度为525.70×10-6,最高值在广东深圳(599.08×10-6);最低值在江苏南通(477.42×10-6).研究区CH4和CO2含量超于大气背景值.δ13C-CH4变化范围为-62.62‰~-29.70‰,平均值为-43.65‰,最高值在山东青岛(-40.24‰);最低值在福建漳州(-48.25‰).δ13C-CO2变化范围为-28.64‰~-9.19‰,平均值为-17.53‰,最高值在江苏南通(-14.45‰);最低值在广东深圳(-19.13‰).研究区CH4浓度和碳同位素呈正相关,CO2浓度和碳同位素呈负相关.人均GDP、民用汽车拥有量、牲畜存栏量、水稻面积与CH4浓度及碳同位素呈正相关,森林覆盖率与CH4浓度及碳同位素呈负相关.利用δ13C(CO2)示踪山东、江苏、上海、浙江、福建、广东的沿海大气CO2源汇特征,其δ13Cs分别为:-37.90‰、-37.67‰、-41.24‰、-34.12‰、-33.99‰、-32.39‰,指示石油与天然气的燃烧是研究区CO2排放的主要贡献源.
, authors=卞天雨
1, 2, 段晓勇
2, 3, *, 仝港
2, 4, 李雪
2, 3, 印萍
2, 3, 曹珂
2, 3, 陈彬
2, 3, 张大海
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1, 2, address=
1.College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, China
2.Qingdao Institute of Marine Geology, China Geological Survey, Qingdao 266237, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1314922995332767922, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314922992312869020, authorId=1314922995156607149, language=CN, stringName=卞天雨, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
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1.中国海洋大学化学化工学院,山东 青岛 266100
2.中国地质调查局青岛海洋地质研究所,山东 青岛 266237, bio={"content":"
卞天雨(1999-),男,山东临沂人,中国海洋大学硕士研究生,研究方向为化学工程.发表论文1篇.17852365158@163.com.
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卞天雨(1999-),男,山东临沂人,中国海洋大学硕士研究生,研究方向为化学工程.发表论文1篇.17852365158@163.com.
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2, 3, *, address=
2.Qingdao Institute of Marine Geology, China Geological Survey, Qingdao 266237, China
3.Zhoushan Field Scientific Observation and Research Station for Marine Geo-hazards, China Geological Survey, Qingdao 266237, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1314922995538288824, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314922992312869020, authorId=1314922995395682484, language=CN, stringName=段晓勇, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
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3.中国地质调查局舟山海洋地质灾害野外科学观测研究站,山东 青岛 266237, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1314922993256587427, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314922992312869020, xref=2., ext=[AuthorCompanyExt(id=1314922993264976036, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314922992312869020, companyId=1314922993256587427, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=
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2.Qingdao Institute of Marine Geology, China Geological Survey, Qingdao 266237, China
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2.中国地质调查局青岛海洋地质研究所,山东 青岛 266237
4.中国海洋大学地球科学学院,山东 青岛 266100, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1314922993256587427, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314922992312869020, xref=2., ext=[AuthorCompanyExt(id=1314922993264976036, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314922992312869020, companyId=1314922993256587427, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=
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2.Qingdao Institute of Marine Geology, China Geological Survey, Qingdao 266237, China
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