College of Resources & Environment, Huazhong Agriculture University, Wuhan, China; Key Laboratory of Arable Land Conservation (Middle & Lower Reaches of Yangtse River), Ministry of Agriculture, China.
Institute of Island & Coastal Ecosystems, Ocean College, Zhejiang University, Hangzhou, China; Department of Geography, San Diego State University, San Diego, CA, USA.
Environ Pollut. 2017 Apr;223:560-566. doi: 10.1016/j.envpol.2017.01.058. Epub 2017 Jan 26.
Assessing the space-time trends and detecting the sources of heavy metal accumulation in soils have important consequences in the prevention and treatment of soil heavy metal pollution. In this study, we collected soil samples in the eastern part of the Qingshan district, Wuhan city, Hubei Province, China, during the period 2010-2014. The Cd, Cu, Pb and Zn concentrations in soils exhibited a significant accumulation during 2010-2014. The spatiotemporal Kriging technique, based on a quantitative characterization of soil heavy metal concentration variations in terms of non-separable variogram models, was employed to estimate the spatiotemporal soil heavy metal distribution in the study region. Our findings showed that the Cd, Cu, and Zn concentrations have an obvious incremental tendency from the southwestern to the central part of the study region. However, the Pb concentrations exhibited an obvious tendency from the northern part to the central part of the region. Then, spatial overlay analysis was used to obtain absolute and relative concentration increments of adjacent 1- or 5-year periods during 2010-2014. The spatial distribution of soil heavy metal concentration increments showed that the larger increments occurred in the center of the study region. Lastly, the principal component analysis combined with the multiple linear regression method were employed to quantify the source apportionment of the soil heavy metal concentration increments in the region. Our results led to the conclusion that the sources of soil heavy metal concentration increments should be ascribed to industry, agriculture and traffic. In particular, 82.5% of soil heavy metal concentration increment during 2010-2014 was ascribed to industrial/agricultural activities sources. Using STK and SOA to obtain the spatial distribution of heavy metal concentration increments in soils. Using PCA-MLR to quantify the source apportionment of soil heavy metal concentration increments.
评估土壤中重金属的时空趋势并检测其积累来源，对于防治土壤重金属污染具有重要意义。本研究于 2010-2014 年在湖北省武汉市青山区东部采集土壤样品。研究表明，2010-2014 年土壤中 Cd、Cu、Pb 和 Zn 浓度显著积累。时空克里金技术基于非可分离变异函数模型对土壤重金属浓度变化进行定量描述，用于估计研究区域土壤重金属的时空分布。结果表明，Cd、Cu 和 Zn 浓度从研究区西南向中部呈明显递增趋势，而 Pb 浓度则从北部向中部呈明显递增趋势。然后，采用空间叠加分析获得 2010-2014 年间相邻 1 年或 5 年的绝对和相对浓度增量。土壤重金属浓度增量的空间分布表明，研究区中心的增量较大。最后，采用主成分分析结合多元线性回归方法对研究区土壤重金属浓度增量的源分配进行量化。研究结果表明，土壤重金属浓度增量的来源应归因于工业、农业和交通。特别是，2010-2014 年期间，土壤重金属浓度增量的 82.5%归因于工业/农业活动源。使用 STK 和 SOA 获得土壤重金属浓度增量的空间分布。使用 PCA-MLR 量化土壤重金属浓度增量的源分配。
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