Sun Xue-Fei, Zhang Li-Xia, Dong Yu-Long, Zhu Lin-Yu, Wang Zheng, Lü Jian-Shu
College of Geography and Environment, Shandong Normal University, Ji'nan 250358, China.
Shandong Geological Environmental Monitoring Station, Ji'nan 250014, China.
Huan Jing Ke Xue. 2021 Mar 8;42(3):1093-1104. doi: 10.13227/j.hjkx.202008007.
Identifying the quantitative source and hazardous areas of heavy metals in soils plays a pivotal role in soil pollution research, and can provide a basis for regional soil risk monitoring and environmental management. For this purpose, a total of 175 samples were collected in topsoils from Linzi, a typical petrochemical industrial city in Shandong Province. Positive matrix factorization (PMF) and factor analysis with non-negative constraints (FA-NNC) receptor models were applied to analyze the sources of the heavy metals. Based on the multivariate statistical simulation methods of min/max autocorrelation factors (MAF) and sequential Gaussian simulation (SGS), the distribution of heavy metal and potential pollution areas were determined. As, Co, Cr, and Mn were mainly affected by natural sources, their concentrations were dominated by the parent materials, and the high-value areas were distributed in the south of the study area. Hg was the most serious pollution element among the 10 heavy metals analyzed in Linzi and originated from atmosphere deposition from industrial emissions and coal combustion, and the highest values were distributed in the northeast of the study area. Cd, Cu, Ni, Pb, and Zn were dominated by natural sources and human activities. The hot-spot areas were mainly concentrated in the middle of the study area. The potentially contaminated areas of Cd and Hg were 580.80 km and 666.60 km, about 85.04% and 97.59% of the total area, and should require more attention. The potential pollution area of most elements was small and scattered across the study area, accounting for less than 1%.
识别土壤中重金属的定量来源和危险区域在土壤污染研究中起着关键作用,并可为区域土壤风险监测和环境管理提供依据。为此,在山东省典型石化工业城市临淄的表层土壤中总共采集了175个样本。应用正定矩阵因子分解(PMF)和非负约束因子分析(FA-NNC)受体模型来分析重金属的来源。基于最小/最大自相关因子(MAF)和序贯高斯模拟(SGS)的多元统计模拟方法,确定了重金属的分布和潜在污染区域。砷、钴、铬和锰主要受自然源影响,其浓度由母质主导,高值区域分布在研究区域的南部。汞是临淄分析的10种重金属中污染最严重的元素,源自工业排放和煤炭燃烧的大气沉降,最高值分布在研究区域的东北部。镉、铜、镍、铅和锌受自然源和人类活动的共同影响。热点区域主要集中在研究区域的中部。镉和汞的潜在污染面积分别为580.80平方公里和666.60平方公里,分别约占总面积的85.04%和97.59%,应予以更多关注。大多数元素的潜在污染区域较小,分散在研究区域内,占比不到1%。