基于PCA-APCS-MLR的地下水污染源定量解析研究

发布时间：2018-01-17 21:32

本文关键词：基于PCA-APCS-MLR的地下水污染源定量解析研究　出处：《中国环境科学》2017年10期 　论文类型：期刊论文

【摘要】：以中国东北地区典型工业基地沈阳浑河冲洪积扇为研究对象,采集区域内43个采样点水质样品,分析了16项地下水质关键指标,在水化学统计和水质分析确定水质等级及特征污染物的基础上,利用主成分分析(PCA)方法确定水质指标主要因子分类,运用Arc GIS软件刻画不同污染源的空间分布规律,利用绝对主成分得分多元线性回归受体模型(APCS-MLR)计算不同公因子对地下水质的贡献程度,并验证污染源解析结果的准确性.结果表明:研究区内地下水氮、磷和铁等元素超标严重,地下水水质演化受人类活动影响较大;4类主要污染因子分别是溶滤迁移作用因子(贡献率34.21%)、农业活动污染因子(贡献率20.13%)、地质环境背景因子(贡献率13.39%)和工业活动影响因子(贡献率8.97%),方差累计贡献率为75.64%;工业生产、生活污废水排放和农业生产中农药化肥使用是地下水主要污染源且多分布于沈阳西部、西北部和南部等地区,淋溶、迁移-富集作用和农业污染对地下水质影响较为明显,PCA-APCS-MLR模型预测浓度与实测浓度一致,该方法对于地下水污染源的计算分配具有良好的针对性,适用于地下水污染源解析.
[Abstract]:Taking Shenyang Hunhe alluvial fan, a typical industrial base in northeast China, as the research object, water quality samples from 43 sampling sites in the area were collected and 16 key indexes of underground water quality were analyzed. On the basis of water chemistry statistics and water quality analysis to determine the grade of water quality and characteristic pollutants, principal component analysis (PCA) was used to determine the classification of main factors of water quality index. Arc GIS software is used to describe the spatial distribution of different pollution sources. The contribution of different common factors to underground water quality was calculated by absolute principal component score multiple linear regression receptor model (APCS-MLR). The results show that the elements of nitrogen, phosphorus and iron in groundwater in the study area exceed the standard seriously, and the evolution of groundwater quality is greatly affected by human activities. The four main pollution factors were lysofiltration migration factors (contribution rate 34.21) and agricultural activity pollution factor (20.13%). The geological environment background factor (contribution rate 13.39%) and the industrial activity influence factor (contribution rate 8.97%), the variance accumulative contribution rate is 75.64; Industrial production, domestic wastewater discharge and pesticide and fertilizer use in agricultural production are the main sources of groundwater pollution and are mainly distributed in the western, northwest and southern areas of Shenyang, leaching. The effects of migration-enrichment and agricultural pollution on underground water quality are obvious. The predicted concentration of PCA-APCS-MLR model is consistent with the measured concentration. This method has good pertinence for the calculation and distribution of groundwater pollution sources and is suitable for the analysis of groundwater pollution sources.
【作者单位】：北京师范大学水科学研究院;地下水污染控制与修复教育部工程研究中心;
【基金】：国家自然科学基金资助项目(41402211,41672228) 国家水体污染控制与治理科技重大专项资助项目(2014ZX07201-010)
【分类号】：X832
【正文快照】： 地下水资源是保障可持续发展不可缺少的重要资源,地下水水质安全及污染防控一直是全球关注的主要环境问题之一[1].随着我国工农业开发、城市化进程加快,地下水污染物的种类和来源呈现复杂化趋势.由于不同区域的污染物来源不同,向地下水系统的输入与输出比重不同且各种污染物对

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