| 基于APCS-MLR和PMF模型的石煤矿区及周边区域农田土壤重金属污染来源解析 |
| 摘要点击 322 全文点击 25 投稿时间：2024-03-30 修订日期：2024-07-01 |
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| 中文关键词 土壤重金属 石煤 源解析 APCS-MLR模型 PMF模型 |
| 英文关键词 soil heavy metal stone coal source apportionment APCS-MLR model PMF model |
| 作者 | 单位 | E-mail | | 董天浩 | 湖南省农业环境生态研究所, 长沙 410125
中国农业大学土地科学与技术学院, 北京 100193
农业农村部长江中游平原农业环境重点实验室, 长沙 410125
农田土壤重金属污染防控与修复湖南省重点实验室, 长沙 410125 | 576681235@qq.com | | 潘淑芳 | 湖南省农业环境生态研究所, 长沙 410125
农业农村部长江中游平原农业环境重点实验室, 长沙 410125
农田土壤重金属污染防控与修复湖南省重点实验室, 长沙 410125 | | | 张仁杰 | 湖南省农业环境生态研究所, 长沙 410125
农业农村部长江中游平原农业环境重点实验室, 长沙 410125
农田土壤重金属污染防控与修复湖南省重点实验室, 长沙 410125 | | | 姜立恒 | 中国农业大学土地科学与技术学院, 北京 100193 | | | 郭焱 | 中国农业大学土地科学与技术学院, 北京 100193 | | | 纪雄辉 | 湖南省农业环境生态研究所, 长沙 410125
农业农村部长江中游平原农业环境重点实验室, 长沙 410125
农田土壤重金属污染防控与修复湖南省重点实验室, 长沙 410125 | | | 谢运河 | 湖南省农业环境生态研究所, 长沙 410125
农业农村部长江中游平原农业环境重点实验室, 长沙 410125
农田土壤重金属污染防控与修复湖南省重点实验室, 长沙 410125 | 45069794@qq.com |
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| 中文摘要 |
| 为了探究石煤开采带来的农田土壤重金属污染风险,对某石煤矿区及周边区域农田土壤进行了采样分析及污染源解析.结果表明：①该石煤矿区及周边农田土壤重金属污染风险很高.按内梅罗综合污染指数确定的轻污染风险以上的采样点占比为61.6%,其中重污染风险采样点占比达21.9%.研究区土壤Cd污染很严重,超出风险筛选值和风险管制值的采样点占比分别为71.5%和18.5%.②土壤Cd、Zn、Ni、Cu和As之间,As、Hg和Pb之间,Cr与As和Ni,Hg与Zn、Ni和Cu,均存在极显著正相关关系.Cd与Cr和Pb的相关性均不显著,其余重金属元素组合均存在显著正相关关系.③基于不同受体模型对研究区进行土壤重金属污染来源解析,识别出3个污染来源,即石煤开采源,大气沉降源和自然源.APCS-MLR模型判定土壤Cd、As、Cu、Zn和Ni主要受石煤开采源影响,Pb和Hg主要受大气沉降源影响,Cr主要受自然源影响；3个污染源的贡献率依次为43.2%、31.5%和25.3%.PMF模型的源解析结果与之总体上相同,但判定土壤Cd和Hg均受石煤开采-大气沉降混合源影响；3个污染源的贡献率依次为45.0%、34.5%和20.5%.研究表明,石煤矿区及周边区域农田土壤有较大的重金属污染风险,联合使用两种受体模型能够更合理地判别各土壤重金属主要的污染来源. |
| 英文摘要 |
| To investigate the potential risk of heavy metal contamination in agricultural soil resulting from stone coal mining activities, soil samples were collected and analyzed from a stone coal mining site and its surrounding areas. The findings revealed that： ① The risk of heavy metal pollution in the vicinity of the stone coal mining area was notably high, with 61.6% of sampling sites exhibiting moderate to severe pollution as determined by the Nemerow composite pollution index, including 21.9% showing significant levels of contamination. Soil contamination with Cd within the study area was particularly severe, with 71.5% and 18.5% of sampling sites exceeding risk screening and control values, respectively. Some soil samples also indicated potential risks associated with Cu and Zn, while individual samples showed excessive levels of As, Pb, Hg, and Ni. ② There were highly significant positive correlations observed between soil Cd, Zn, Ni, Cu, and As； As-Hg-Pb； as well as Cr-As-Ni-Hg pairs, respectively. No significant correlations were found between the Cd-Cr or Cd-Pb pairs； however, other combinations involving different heavy metals exhibited notable positive associations, suggesting similar sources for their pollution origins. ③ Three distinct sources contributing to soil heavy metal pollution within the study area were identified utilizing two receptor models-namely stone coal mining activities, atmospheric deposition events, and natural sources, such as weathering processes According to APCS-MLR model analysis results, soil concentrations of Cd-As-Cu-Zn-Ni were primarily affected by stone coal mining activities, while Pb-Hg were mainly influenced by atmospheric deposition events, and Cr was predominantly impacted by natural sources alone, with each source contributing approximately 43.2%, 31.5%, and 25.3%. PMF model outcomes generally aligned closely with these findings, suggesting soil Cd and Hg originated from combined effects related to both stone coal-mining activity and atmospheric depositions. Each source contributed rates around 45.0%, 34.5%, and 20.5%. This research underscores a substantial threat posed by heavy metal contamination in farmland soils adjacent to stone coal mines and highlights how employing multiple receptor models can provide more accurate determination regarding primary sources responsible for heavy metal pollutants present within each specific location. |
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