Article(id=1314917820312412361, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314917567911788907, 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=1739980800000, receivedDateStr=2025-02-20, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791430438353, onlineDateStr=2026-10-08, pubDate=1758297600000, pubDateStr=2025-09-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791430438353, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791430438353, creator=13701087609, updateTime=1791430438353, updator=13701087609, issue=Issue{id=1314917567911788907, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='9', pageStart='4737', pageEnd='5328', issueExtLink='null', onlineDate='null', pubDate='1758297600000', pubDateStr='2025-09-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1791430378177, creator='13701087609', updateTime=1791431890195, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1314923910001418489, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314917567911788907, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1314923910001418490, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314917567911788907, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=5104, endPage=5116, ext={EN=ArticleExt(id=1314917820530516170, articleId=1314917820312412361, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Spatiotemporal variations and influencing factors of net anthropogenic phosphorus inputs (NAPI) in the Beijing-Tianjin-Hebei region from 1990 to 2022, columnId=1234106388083954308, journalTitle=China Environmental Science, columnName=Environmental Ecology, runingTitle=null, highlight=null, articleAbstract=
To explore the status of net anthropogenic phosphorus input (NAPI) and its influencing factors in the Beijing-Tianjin-Hebei region, this study took 13 prefecture-level cities as research units, collected relevant statistical data and NAPI model parameters from 1990 to 2022, analyzed the spatiotemporal characteristics of NAPI and the variation trends of its components over the 33 years, and used redundancy analysis (RDA) to quantitatively reveal the impacts of different types of factors on NAPI and its components. The results showed that:(1) The overall NAPI in the Beijing-Tianjin-Hebei region showed a fluctuating upward trend, with a significant increase from 1990 to 2006 and a slight decrease from 2006 to 2022. The annual average value was 1906kg/(km2·a), which was 5.6times the national level. Phosphorus input from chemical fertilizers was the most important source, with an average annual contribution rate of 54.90%, followed by phosphorus input from food and feed, with an average annual contribution rate of 41.18%. Affected by terrain, the spatial distribution of NAPI showed a trend of gradually decreasing from south to north. Handan City had the highest NAPI value, accounting for 15.76% of the entire study area, while Chengde City had the lowest NAPI value, accounting for 1.52%. The average uncertainty range of NAPI from 2018 to 2022 was -14.81% to 14.56%. (2) The order of influence of different factors on NAPI and its components was: land use factors > economic factors > social factors, and the combined explanatory rate of the three types of factors was 81.77%. Among them, NAPI and its components were only negatively correlated with the proportion of forest and grassland areas, and positively correlated with other influencing factors. Among the indicators, the proportion of construction land area had the highest individual explanatory rate of 45.70%, and had the strongest positive correlation with food/feed phosphorus and non-food phosphorus, making it the most critical factor affecting NAPI and its components. The increase in the proportion of construction land area is often accompanied by intense human activities, such as the increase in food consumption and detergent use. Therefore, the positive impact of the proportion of construction land on food/feed phosphorus and non-food phosphorus leads to its highest individual explanatory rate.
, authors=Tian-jiao JIA, Wei PEI, Lin-tao WANG, Min LI
*, authorsList=Tian-jiao JIA, Wei PEI, Lin-tao WANG, Min LI, authorCompany=null, correspAuthors=Min LI, 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=1314917820836700363, articleId=1314917820312412361, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=1990~2022年京津冀地区人类活动净磷输入时空变化及影响因素, columnId=1234106388268503686, journalTitle=中国环境科学, columnName=环境生态, runingTitle=null, highlight=null, articleAbstract=
为探究京津冀地区人类活动净磷输入状况及影响因素,以13个地级市为研究单元,收集1990~2022年相关统计数据及人类活动净磷输入(NAPI)模型参数,探究33a内NAPI的时空特征和各组分变化趋势,并采用冗余分析(RDA)定量揭示不同类型因素对NAPI及其组分的影响.结果表明:(1)京津冀地区NAPI整体呈起伏上升的趋势,1990~2006年上升明显,2006~2022年略有下降,年平均值为1906kg/(km2·a),为全国水平的5.6倍,化肥磷输入为最主要输入源,年平均贡献率为54.90%,其次是食品饲料磷输入,年平均贡献率为41.18%;NAPI受地形影响呈现出由南向北逐渐降低的空间分布趋势,邯郸市NAPI值最高,占整个研究区的15.76%,承德市NAPI值最低,占比1.52%.2018~2022年NAPI不确定性范围平均值为-14.81%~14.56%.(2)不同因素对NAPI及其组分的影响大小排序为:土地利用因素>经济因素>社会因素,三类因素共同解释率为81.77%.其中,NAPI及其组分只与林地和草地面积占比呈负相关,与其余影响因素均呈正相关.指标中建设用地面积占比的单独解释率最高,为45.70%,且与食品/饲料磷和非食物磷的正相关性最强,是影响NAPI及其组分的最关键因素.建设用地面积占比的增加往往伴随着强烈的人类活动,如食品消费、洗涤剂使用的增加,因此,建设用地占比对食品/饲料磷与非食物磷的正向影响导致其具有最高的单独解释率.
, authors=贾天娇, 裴玮, 王林涛, 李敏
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贾天娇(2003-),女,北京人,北京林业大学本科生,主要研究方向为流域面源污染.jia_6607@163.com.
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