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基于乡镇尺度的地质高背景区耕地土壤重金属来源分析与风险评价
摘要点击 1470  全文点击 571  投稿时间:2022-06-18  修订日期:2022-08-10
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中文关键词  重金属高背景  土壤重金属  来源分析  绝对因子分析-多元线性回归(APCS-MLR)受体模型  风险评价
英文关键词  high background area  heavy metal in soil  source analysis  absolute principal component score-multiple linear regression (APCS-MLR) model  risk assessment
作者单位E-mail
余飞 重庆市地质矿产勘查开发局川东南地质大队, 重庆市土地质量地质调查重点实验室, 重庆 400038 yfcags@126.com 
王佳彬 重庆市地质矿产勘查开发局川东南地质大队, 重庆市土地质量地质调查重点实验室, 重庆 400038 676063702@qq.com 
王锐 重庆市地质矿产勘查开发局川东南地质大队, 重庆市土地质量地质调查重点实验室, 重庆 400038  
王宇 重庆市地质矿产勘查开发局川东南地质大队, 重庆市土地质量地质调查重点实验室, 重庆 400038  
宁墨奂 重庆市地质调查院, 重庆 401122  
张云逸 重庆市地质矿产勘查开发局川东南地质大队, 重庆市土地质量地质调查重点实验室, 重庆 400038  
苏黎明 重庆市地质矿产勘查开发局川东南地质大队, 重庆市土地质量地质调查重点实验室, 重庆 400038  
董金秀 重庆市地质矿产勘查开发局川东南地质大队, 重庆市土地质量地质调查重点实验室, 重庆 400038  
中文摘要
      西南地区由于广泛发育碳酸盐岩导致土壤重金属具有天然的高背景属性,在重金属地质高背景区开展生态风险评价和识别重金属潜在来源对土壤污染防治、农产品安全保障具有重要意义.基于乡镇尺度,在重庆市奉节县青龙镇采集耕地表层土壤样品307件,分析了土壤As、Cd、Cr、Cu、Hg、Ni、Pb和Zn重金属含量及pH,采用地统计学,绝对因子分析-多元线性回归(APCS-MLR)受体模型探讨研究区域内8种重金属污染空间分布特征及来源,利用内梅罗指数(P)和潜在生态风险指数(RI)开展土壤风险评价.结果表明,耕地土壤中As、Cd、Cr、Cu、Hg、Ni和Zn的平均值和中位数超过重庆市土壤背景值,其中Cd、As累积效应较为明显.与农用地土壤筛选值相比,Cd超标率最高,达52.12%.土壤中重金属含量空间分布格局呈现出南部整体高,高值区呈条带状分布;北部整体低,高值区呈点状分布.APCS-MLR模型表明研究区耕地土壤重金属Cr、Zn、Ni和Cu以自然来源为主,主要受地质背景控制,贡献率分别为86.62%、85.46%、76.44%和64.34%;As、Pb和Hg的来源以工业源为主,受煤矿和硫铁矿开发利用活动影响,贡献率分别为74.63%、61.90%和73.49%;Cd受自然源和工业源影响相差不大,贡献率分别为47.74%和39.56%.内梅罗指数显示土壤Cd污染程度最高,轻度以上污染占27.04%;潜在生态危害指数表明,研究区以轻微风险和中等风险为主,中等以上风险区主要位于东南部工业源周边区域,Cd和Hg是主要生态危害元素.总体来看,研究区中等以上风险区主要由矿产和工业活动引起,而地质背景导致的土壤重金属污染主要为轻微-中度污染.
英文摘要
      Due to the extensive development of carbonate rocks in southwest China, heavy metals are naturally occurring elements that have high natural background levels in the environment. Therefore, it is important to conduct ecological risk assessments and identify potential sources of heavy metals in the geological high background area. Based on the township scale, a total of 307 surface soil samples were collected in Qinglong Town, Fengjie County, Chongqing. The concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn and pH were analyzed and determined. The spatial distribution and source of soil heavy metals were discussed using the geostatistical analysis and an absolute principal component score-multiple linear regression (APCS-MLR) model in the studied area. The results showed that the average values of seven heavy metals (As, Cd, Cr, Cu, Hg, Ni, and Zn) in the arable soil exceeded the background values of Chongqing, and the cumulative effect of Cd and As was obvious. The concentrations of Cd significantly exceededthe screening values in The Risk Control Standard for Soil Environmental Quality and Soil Pollution in Agricultural Land (GB 15618-2018), with the over-standard rates of 52.12%. The spatial characteristics of soil heavy metal contents exhibited a pattern of high in the south and low in the north. PCA and APCS-MLR modeling revealed that the contributions of natural sources to Cr, Cu, Ni, and Zn were 86.62%, 64.34%, 76.44%, and 85.46%, respectively. As, Pb, and Hg mainly derived from industrial activities, which accounted for 74.63%, 61.90%, and 73.49%, respectively, and Cd was affected by both natural sources and industrial activities (accounting for 47.74% and 39.56% of the total Cd content, respectively). The evaluation of the soil by the Nemerow comprehensive index (P) showed that Cd pollution was relatively serious, accounting for 27.04% of soil pollution. The potential ecological hazard index showed that Cd and Hg were the main ecological hazard elements, and the distribution range of RI was 51.77 to 2228, indicating mainly mild and moderate risks, and the moderate and above risk areas in the study area were mainly located around the southern industrial source area. Altogether, our results revealed that in the study area, the heavy metal pollution was mainly caused by industrial activities, and the heavy metal pollution caused by geological background was mainly light to moderate. In conclusion, the medium and above risk areas in the study area were mainly caused by mineral and industrial activities, whereas the heavy metal pollution caused by geological background was mainly light to moderate pollution.

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