Article(id=1242137898485621748, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242137871864377992, articleNumber=null, orderNo=17, doi=10.3981/j.issn.1000-7857.2019.22.015, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1547740800000, receivedDateStr=2019-01-18, revisedDate=1563206400000, revisedDateStr=2019-07-16, acceptedDate=null, acceptedDateStr=null, onlineDate=1575097716983, onlineDateStr=2019-11-30, pubDate=1574870400000, pubDateStr=2019-11-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1575097716983, onlineIssueDateStr=2019-11-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774078352802, creator=sys-migrate, updateTime=1774078352802, updator=sys-migrate, issue=Issue{id=1242137871864377992, tenantId=1146029695717560320, journalId=1146031591421210625, year='2019', volume='37', issue='22', pageStart='1', pageEnd='152', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774078346454, creator=sys-migrate, updateTime=1774078346454, updator=sys-migrate, preIssue=null, nextIssue=null, ext=null, issueFiles=null}, startPage=133, endPage=142, ext={EN=ArticleExt(id=1242137902646370314, articleId=1242137898485621748, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Accounting of construction CO₂ footprint and its mechanism analysis based on PB-LCA in Hunan province, columnId=1150494644690366681, journalTitle=Science & Technology Review, columnName=Papers, runingTitle=null, highlight=null, articleAbstract=Based on PB-LCA method, taking typical hot summer and cold winter areas of Hunan province as an example, this paper sets up a macro-construction CO₂ footprint model at the provincial level, quantitatively measures and compares CO₂ footprints and their changes in each stage of the construction during 2004-2016, and uses geographical detector technology to analyze the influence mechanism of construction CO₂ footprint. Main conclusion is as follows. The construction CO₂ footprint was the trend of the overall fluctuating growth; building materials preparation and construction operations were the two major stages of the construction CO₂ footprint, while the CO₂ footprint of construction and construction demolition stage was relatively small; the CO₂ footprint of building materials preparation stage mainly came from steel and cement, and the CO₂ footprint of public buildings was on the rise. But the CO₂ footprint of residential buildings had a tendency of fluctuating drop. The construction development degree, energy structure and tertiary industry proportion were the three main influencing factors of construction CO 2 footprint. Thus, reducing consumption of building materials, especially steel and cement, reducing the proportion of coal consumption during construction and construction operation, and implementing limits of energy consumption and CO₂ emission on public buildings are the main technical directions of energy-saving and CO₂ reduction in construction., correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=BqZ5XmfZ3BQYSmQ88VZ6ag==, pdfFileSize=2179628, 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=1. College of Urban and Environmental Sciences, Hunan University of Technology Zhuzhou 412007, China;
2. Research Base for Green Industry and Low Carbon Development of City in Hunan Province, Zhuzhou 412007, China, fund=null, authors=ZHANG Wang^1,2, authorsList=ZHANG Wang), CN=ArticleExt(id=1242137901572628484, articleId=1242137898485621748, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=基于PB-LCA的湖南省建筑碳足迹测算及其机理分析, columnId=1146540929516700224, journalTitle=科技导报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=基于PB-LCA方法，以湖南省为例构建了省区层面的宏观建筑碳足迹模型，定量测度和比较2004—2016年建筑各个阶段的碳足迹及其变化情况，采用地理探测器技术分析了建筑碳足迹的影响机理。分析表明：建筑碳足迹整体上呈现波动增长之势，建材准备和建筑运行是产生碳足迹的两个主要阶段，而建造施工和建筑拆除阶段的碳足迹比重则较小；建材准备阶段的碳足迹主要来自钢材和水泥，公共建筑碳足迹处于波动上升的趋势，而居住建筑碳足迹则出现波动式下降之势；建筑业发展度、能源结构和第三产业比重是建筑碳足迹的3个主要影响因素。提出了减少建材特别是钢材和水泥的消耗量、降低建造施工和建筑运行阶段的煤炭类消费比重、实行公共建筑能耗和碳排放限额等3个建筑节能减碳的主要技术方向。关键词PB-LCA方法；建筑碳足迹；地理探测器技术；湖南省, correspAuthors=null, authorNote=张旺,副教授,研究方向为低碳城市、可持续发展经济学等,电子信箱:zhangwang0902@163.com, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=/QumzdEDHaAAHbjqysD4tg==, pdfFileSize=2179628, 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=1. 湖南工业大学城市与环境学院, 株洲 412007;
2. 湖南省绿色工业与城市低碳发展研究基地, 株洲 412007, fund=湖南省哲学社会科学基金项目（17YBA129）, authors=张旺^1,2, authorsList=张旺)}, authors=null, keywords=[Keyword(id=1242137901140616190, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242137898485621748, language=CN, orderNo=1, keyword=PB-LCA方法), Keyword(id=1242137901211919360, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242137898485621748, language=CN, orderNo=1, keyword=建筑碳足迹), Keyword(id=1242137901299998721, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242137898485621748, language=CN, orderNo=1, keyword=地理探测器技术), Keyword(id=1242137901392273410, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242137898485621748, language=CN, orderNo=1, keyword=湖南省), Keyword(id=1242137902205968390, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242137898485621748, language=EN, orderNo=1, keyword=PB-LCA method), Keyword(id=1242137902281465863, 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