| 基于APCS-MLR和PMF的污灌与工业复合区农田土壤重金属来源解析 |
| 摘要点击 2289 全文点击 445 投稿时间：2023-08-15 修订日期：2023-11-24 |
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| 中文关键词 污灌与工业复合区 农田土壤 绝对因子得分-多元线性回归（APCS-MLR） 正定矩阵因子分解（PMF） 源解析 |
| 英文关键词 sewage irrigation and industrial complex area farmland soil absolute factor analysis-multiple linear regression （APCS-MLR） positive matrix factorization （PMF） source apportionment |
| 作者 | 单位 | E-mail | | 刘德新 | 河南大学地理与环境学院, 开封 475004
河南大学黄河中下游数字地理技术教育部重点实验室, 开封 475004
河南大学土壤重金属污染控制与修复工程研究中心, 开封 475004 | dxliu@vip.henu.edu.cn | | 孟凡磊 | 河南大学地理与环境学院, 开封 475004 | | | 段海静 | 河南大学地理与环境学院, 开封 475004
河南大学黄河中下游数字地理技术教育部重点实验室, 开封 475004
河南大学土壤重金属污染控制与修复工程研究中心, 开封 475004 | | | 李一蒙 | 河南大学地理与环境学院, 开封 475004 | | | 马建华 | 河南大学地理与环境学院, 开封 475004
河南大学黄河中下游数字地理技术教育部重点实验室, 开封 475004
河南大学土壤重金属污染控制与修复工程研究中心, 开封 475004 | mjh@henu.edu.cn |
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| 中文摘要 |
| 基于开封市污灌与工业复合区农田表土样品,测定8种重金属（Cr、 Ni、 Cu、 Zn、 Cd、 Pb、 As和Hg）含量,利用绝对因子得分-多元线性回归（APCS-MLR）模型和正定矩阵因子分解（PMF）模型,结合相关性分析和系统聚类分析对土壤重金属来源和贡献率进行解析.结果表明：①研究区ω（Cr）、 ω（Ni）、 ω（Cu）、 ω（Zn）、 ω（Cd）、 ω（Pb）、 ω（As）和ω（Hg）平均值分别为52.19、 25.00、 42.03、 323.53、 1.79、 53.45、 9.43和0.20 mg·kg-1,其中Cr、Ni和As低于潮土背景值,Cu、 Zn、 Cd、 Pb和Hg高于潮土背景值. ②8种重金属有4种来源：自然源、农业污水灌溉源、工业大气沉降源和交通运输源,Cr和Ni主要为自然源,Cu、 Zn、 Cd和Pb主要为农业污水灌溉和交通运输,As主要为自然源和农业污水灌溉,Hg主要为工业大气沉降. ③APCS-MLR和PMF源解析结果表明工农业活动是研究区土壤重金属的主要来源.研究区9个采样小区APCS-MLR平均贡献率为76.01%（自然源和农业污水灌溉源）、 22.71%（工业大气沉降源和交通运输源）和1.28%（未知源）,PMF平均贡献率为59.66%（自然源和农业污水灌溉源）和40.34%（工业大气沉降源和交通运输源）,其中LZ、 XZ、 NLT、 PT、 YLZ和BC的两种模型源解析结果基本一致,WL在APCS-MLR模型更优,SG和QT在PMF模型更优.研究结果可为土壤重金属污染防治和环境修复提供科学依据. |
| 英文摘要 |
| The contents of eight heavy metals （Cr, Ni, Cu, Zn, Cd, Pb, As, and Hg） were determined based on the surface soil samples of sewage irrigation and industrial complex in Kaifeng City. The absolute factor analysis-multiple linear regression （APCS-MLR） model and positive matrix factorization （PMF） model were used to analyze the sources and contribution rates of heavy metals in soil combined with correlation analysis and systematic cluster analysis. The results showed that： ① The average values of ω（Cr）, ω（Ni）, ω（Cu）, ω（Zn）, ω（Cd）, ω（Pb）, ω（As）, and ω（Hg） in the study area were 52.19, 25.00, 42.03, 323.53, 1.79, 53.45, 9.43, and 0.20 mg·kg-1, respectively, and Cr, Ni, and As are lower than the background values of tidal soil. Cu, Zn, Cd, Pb, and Hg are higher than the background values of the tidal soil. ② There were four sources of the eight heavy metals： natural sources, agricultural sewage irrigation sources, industrial atmospheric sedimentation sources, and transportation sources. Cr and Ni were mainly from natural sources； Cu, Zn, Cd, and Pb were mainly from agricultural sewage irrigation and transportation sources； As was mainly from natural sources and agricultural sewage irrigation； and Hg was mainly from industrial atmospheric sedimentation. ③ The APCS-MLR and PMF source analysis results indicated that industrial and agricultural activities were the main sources of heavy metals in the soil of the study area. The average contribution rates of APCS-MLR in the nine sampling areas of the research area were 76.01% （natural sources and agricultural sewage irrigation sources）, 22.71% （industrial atmospheric sedimentation sources and transportation sources）, and 1.28% （unknown sources）. The average contribution rates of PMF were 59.66% （natural sources and agricultural sewage irrigation sources） and 40.34% （industrial atmospheric sedimentation sources and transportation sources）. The source analysis results of the LZ, XZ, NLT, PT, YLZ, and BC models were basically consistent, and WL was better in the APCS-MLR model, whereas SG and QT were better in the PMF model. The research results can provide a scientific basis for the prevention and control of soil heavy metal pollution and environmental remediation. |
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