农田土壤重金属污染监测及其空间估值方法研究
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摘要
土壤重金属污染是当前土壤生态环境保护研究的热点问题。受城市工业化及集约化农业发展的影响,城郊土壤重金属污染远比一般农业地区更为显著。本研究选取北京城郊地区——大兴区为研究对象,对土壤景观异质下土壤重金属含量的空间分布规律、重金属积累与景观要素的关联性、污染溯源的可视化表达方法及土壤重金属含量的空间估值几个主要问题进行了探讨,主要研究内容及创新性进展如下：
(1)土壤重金属含量分布及其污染状况。对京郊重点蔬菜产区大兴地区3054个样点的表层土壤重金属取样监测表明,大兴区土壤重金属As、Cu、Pb、Hg、Cd、Cr的平均值分别为6.5mg.kg-1、25.9mg.kg-1、20.6mg.kg-1、0.078mg.kg-1、0.15mg.kg-1、59.3mg.kg-1。6种重金属中Cu、Cd、Cr的累积污染指数平均值都大于1,虽然As、Pb、Hg的累积污染指数均值小于1,但三种重金属的累积污染指数大于1的样点百分数介于12.8%～32.5%。从单因子污染指数评价结果看,6种重金属中只有As、Cu、Pb、Cd有部分样点超过国家二级标准处于污染状态,其中Pb有12.87%的样点处于污染状态,As、Cu、Cd含量超过国家二级标准的处于污染状态的样点较少,分别为0.20%、0.04%、0.38%。内梅罗污染指数评价方法结果显示Hg和Cr处于清洁状态,As、Cu、Cd处于尚清洁状态,Pb元素处于轻度污染状态。该地区应该加强Pb污染的控制。地积累评价的结果显示,As、Hg、Cd、Cr处于无污染的状态,而Cu、Pb轻度～中等污染状态。通过计算6种重金属的潜在生态危害系数,大兴区土壤中Hg处于中度生态危害状态,其余5种重金属均在轻度生态危害状态,大兴区土壤重金属的潜在生态危害指数值为123.79,处于轻度生态危害状态。各评价方法不同及选用的评价标准不同,各土壤重金属的评价结果也略有差异。
(2)土壤重金属积累与潜在污染源的关联性分析。研究提出了一个定量化土壤重金属累积与潜在污染源(土地利用方式、路网、建筑区)的关联性分析方法。研究结果表明,土地利用方式(粮田、蔬菜地、果园)下土壤重金Cu和Hg发生累积的概率置信度要高于As、Pb及Cu三种重金属出现累积的概率置信度。而路网和建筑区对土壤重金属含量累积的影响与样点到路网和建筑区的距离有关,分别以道路及建筑区为中心,在0-1500米范围内按250米步长设置6个缓冲区,总体上在1500米范围内道路及建筑区对大兴区土壤重金As、Pb、Cu及Cr的累积的贡献不大,但对重金属Cd以及Hg含量有影响。
(3)点状土壤重金属污染扩散及溯源的可视化表达。研究建立了一个土壤重金属污染扩散及溯源的可视化表达方法。该方法假设随到污染源的距离增加土壤重金属含量降低。基于此,研究将样点分布图映射成有向图G=(V,E),即每个样点由一个节点表征,表示一个可能潜在的重金属污染源,邻近节点间的有向边表征重金属污染物由一个节点向邻近节点扩散的过程；一个节点是否向其邻近的节点发出一条有向边,由重金属污染物扩散半径R及两节点的污染物含量的差异强度参数δ控制。与传统方法相比,该方法的主要优点在于：①动态地实现重金属污染物的扩散过程的可视化；②便捷地搜索出潜在的污染源；③对多重金属污染源的发生地区,有效地给出重金属污染的扩散方向。
(4)土壤重金属含量的空间估值理论模型。模型假设：影响土壤重金属含量的外源变量,如植被类型、地形地貌、气象、水文及人为扰动等在全局空间上空间异质而在局部空间上空间同质,而土壤重金属含量分布满足相似的空间分布特征。模型实施的核心内容包括：在全局空间上对影响重金属含量的外源因子进行分类,获取不同的土壤单元类；构建空间估值方法,该方法自适应选择在空间同质的土壤单元类内完成对未知位点的空间估值。
Heavy metal pollution of soils is a hot issue of soil ecology and environment Protection. With urban industrialization and intensive agricultural development, the impact of heavy metal pollution in suburban areas is more significant than the outer suburbs. The peri-urban area of Daxing District, Beijing is selected as a research object. In the context of landscape heterogeneity, the spatial distribution of heavy metals, the relationship between heavy metal accumulation and landscape features, visualization and expression of tracing heavy metal pollution sources and theory model of spatial estimating of heavy metal contents are observed. Our works are presented as follows:
(1) Spatial distribution of soil heavy metals contents.
Based on monitoring data of surface soil heavy metals mainly collected in Daxing district, it shows that the average contents of heavy metals of As, Cu, Pb, Hg, Cd,and Cr, are respectively6.5mg-kg-1,25.9mg.kg-1,20.6mg.kg-1,0.078mg.kg-1,0.15mg.kg-4,59.3mg.kg-1. Due to impact of human activities, accumulation of heavy metals occurs in a certain degree. For the elements of Cu, Cd and Cr, their averages of cumulative pollution index are greater than1, while ones of As, Pb, Hg less than1, and percentage of samplers ranged from12.8%to32.5%, whose accumulation pollution index is greater than1. According to a single factor pollution index, the evaluation results show that the As, Cu, Pb and Cd in six kinds of heavy metals, exceed the national secondary standard in a polluted state. There are12.87%of samples with Pb contents in the polluted state, and As, Cu, or Cd concentrations over the national secondary standard pollution are respectively0.20%,0.04%, and0.38%
㏑elationships between soil metal accumulation and potential pollution sources.
Soil metals in Beijing region were considered as a study case. A method is proposed to quantify the relationship between heavy metal accumulation and potential pollution sources (land use, road network, buildings). The results show that the probability confidence which Cu and Hg accumulate more than ones of As, Pb and Cu under there land use types of grain, vegetable, and orchard. The influence of road networks and buildings on the accumulation of soil heavy metals depends on the distances of monitoring samples to the road network and built-up areas, within the1,500meters, roads and construction areas in Daxing District, have no contributions to As, Pb, Cu and Cr accumulation of small, and but affect the contents of Cd and Hg.
(3) Visualization and expression of tracing multi-point Pollution sources of heavy metals.
A novel study method is established to visualize potential contamination sources of soil heavy metals. This method assumes that the pollution source is only one and the contents of soil heavy metals decrease with increasing distance to the source. Based on that, the monitoring samples of heavy metals will be mapped to a direct graph G=(V, E), that is:each sample is characterized by a node, indicating a possible potential sources of heavy metals, and the direct edge between two adjacent nodes stands for the diffusion process of pollutants from one node to neighboring nodes. Whether a node has a connected edge to its neighboring nodes is under control of two parameters of the radius R of pollutants spread and difference coefficient8of pollutants contents in the two adjacent nodes. Compared with traditional methods, the main advantages of this method includes1) dynamic visualization of heavy metal spread;2) easy to search out potential sources of pollution;3) For the occurrence of multiple heavy metal pollution areas, effectively to give the direction of the spread of heavy metal pollutants.
(4) Theory model for spatial estimation of Heavy Metal Contents
The theory model gives an assumption:since exogenous factors affecting soil heavy metal contents, such as vegetation type, topography, meteorology, hydrology and human disturbance have spatial heterogeneity in the global space and spatial homogeneity in the local space, the distributions of heavy metal contents are similar like that of the exogenous factors. The core ideas of the model include: classification of exogenous factors that affect the contents of heavy metals in the global space, and then achieve different soil unit classes; Construction of spatial estimation method, which adaptively restricts the interpolation of an unknown location within a spatial homogeneous soil unit.
(1)土壤重金属含量分布及其污染状况。对京郊重点蔬菜产区大兴地区3054个样点的表层土壤重金属取样监测表明,大兴区土壤重金属As、Cu、Pb、Hg、Cd、Cr的平均值分别为6.5mg.kg-1、25.9mg.kg-1、20.6mg.kg-1、0.078mg.kg-1、0.15mg.kg-1、59.3mg.kg-1。6种重金属中Cu、Cd、Cr的累积污染指数平均值都大于1,虽然As、Pb、Hg的累积污染指数均值小于1,但三种重金属的累积污染指数大于1的样点百分数介于12.8%～32.5%。从单因子污染指数评价结果看,6种重金属中只有As、Cu、Pb、Cd有部分样点超过国家二级标准处于污染状态,其中Pb有12.87%的样点处于污染状态,As、Cu、Cd含量超过国家二级标准的处于污染状态的样点较少,分别为0.20%、0.04%、0.38%。内梅罗污染指数评价方法结果显示Hg和Cr处于清洁状态,As、Cu、Cd处于尚清洁状态,Pb元素处于轻度污染状态。该地区应该加强Pb污染的控制。地积累评价的结果显示,As、Hg、Cd、Cr处于无污染的状态,而Cu、Pb轻度～中等污染状态。通过计算6种重金属的潜在生态危害系数,大兴区土壤中Hg处于中度生态危害状态,其余5种重金属均在轻度生态危害状态,大兴区土壤重金属的潜在生态危害指数值为123.79,处于轻度生态危害状态。各评价方法不同及选用的评价标准不同,各土壤重金属的评价结果也略有差异。
(2)土壤重金属积累与潜在污染源的关联性分析。研究提出了一个定量化土壤重金属累积与潜在污染源(土地利用方式、路网、建筑区)的关联性分析方法。研究结果表明,土地利用方式(粮田、蔬菜地、果园)下土壤重金Cu和Hg发生累积的概率置信度要高于As、Pb及Cu三种重金属出现累积的概率置信度。而路网和建筑区对土壤重金属含量累积的影响与样点到路网和建筑区的距离有关,分别以道路及建筑区为中心,在0-1500米范围内按250米步长设置6个缓冲区,总体上在1500米范围内道路及建筑区对大兴区土壤重金As、Pb、Cu及Cr的累积的贡献不大,但对重金属Cd以及Hg含量有影响。
(3)点状土壤重金属污染扩散及溯源的可视化表达。研究建立了一个土壤重金属污染扩散及溯源的可视化表达方法。该方法假设随到污染源的距离增加土壤重金属含量降低。基于此,研究将样点分布图映射成有向图G=(V,E),即每个样点由一个节点表征,表示一个可能潜在的重金属污染源,邻近节点间的有向边表征重金属污染物由一个节点向邻近节点扩散的过程；一个节点是否向其邻近的节点发出一条有向边,由重金属污染物扩散半径R及两节点的污染物含量的差异强度参数δ控制。与传统方法相比,该方法的主要优点在于：①动态地实现重金属污染物的扩散过程的可视化；②便捷地搜索出潜在的污染源；③对多重金属污染源的发生地区,有效地给出重金属污染的扩散方向。
(4)土壤重金属含量的空间估值理论模型。模型假设：影响土壤重金属含量的外源变量,如植被类型、地形地貌、气象、水文及人为扰动等在全局空间上空间异质而在局部空间上空间同质,而土壤重金属含量分布满足相似的空间分布特征。模型实施的核心内容包括：在全局空间上对影响重金属含量的外源因子进行分类,获取不同的土壤单元类；构建空间估值方法,该方法自适应选择在空间同质的土壤单元类内完成对未知位点的空间估值。
Heavy metal pollution of soils is a hot issue of soil ecology and environment Protection. With urban industrialization and intensive agricultural development, the impact of heavy metal pollution in suburban areas is more significant than the outer suburbs. The peri-urban area of Daxing District, Beijing is selected as a research object. In the context of landscape heterogeneity, the spatial distribution of heavy metals, the relationship between heavy metal accumulation and landscape features, visualization and expression of tracing heavy metal pollution sources and theory model of spatial estimating of heavy metal contents are observed. Our works are presented as follows:
(1) Spatial distribution of soil heavy metals contents.
Based on monitoring data of surface soil heavy metals mainly collected in Daxing district, it shows that the average contents of heavy metals of As, Cu, Pb, Hg, Cd,and Cr, are respectively6.5mg-kg-1,25.9mg.kg-1,20.6mg.kg-1,0.078mg.kg-1,0.15mg.kg-4,59.3mg.kg-1. Due to impact of human activities, accumulation of heavy metals occurs in a certain degree. For the elements of Cu, Cd and Cr, their averages of cumulative pollution index are greater than1, while ones of As, Pb, Hg less than1, and percentage of samplers ranged from12.8%to32.5%, whose accumulation pollution index is greater than1. According to a single factor pollution index, the evaluation results show that the As, Cu, Pb and Cd in six kinds of heavy metals, exceed the national secondary standard in a polluted state. There are12.87%of samples with Pb contents in the polluted state, and As, Cu, or Cd concentrations over the national secondary standard pollution are respectively0.20%,0.04%, and0.38%
㏑elationships between soil metal accumulation and potential pollution sources.
Soil metals in Beijing region were considered as a study case. A method is proposed to quantify the relationship between heavy metal accumulation and potential pollution sources (land use, road network, buildings). The results show that the probability confidence which Cu and Hg accumulate more than ones of As, Pb and Cu under there land use types of grain, vegetable, and orchard. The influence of road networks and buildings on the accumulation of soil heavy metals depends on the distances of monitoring samples to the road network and built-up areas, within the1,500meters, roads and construction areas in Daxing District, have no contributions to As, Pb, Cu and Cr accumulation of small, and but affect the contents of Cd and Hg.
(3) Visualization and expression of tracing multi-point Pollution sources of heavy metals.
A novel study method is established to visualize potential contamination sources of soil heavy metals. This method assumes that the pollution source is only one and the contents of soil heavy metals decrease with increasing distance to the source. Based on that, the monitoring samples of heavy metals will be mapped to a direct graph G=(V, E), that is:each sample is characterized by a node, indicating a possible potential sources of heavy metals, and the direct edge between two adjacent nodes stands for the diffusion process of pollutants from one node to neighboring nodes. Whether a node has a connected edge to its neighboring nodes is under control of two parameters of the radius R of pollutants spread and difference coefficient8of pollutants contents in the two adjacent nodes. Compared with traditional methods, the main advantages of this method includes1) dynamic visualization of heavy metal spread;2) easy to search out potential sources of pollution;3) For the occurrence of multiple heavy metal pollution areas, effectively to give the direction of the spread of heavy metal pollutants.
(4) Theory model for spatial estimation of Heavy Metal Contents
The theory model gives an assumption:since exogenous factors affecting soil heavy metal contents, such as vegetation type, topography, meteorology, hydrology and human disturbance have spatial heterogeneity in the global space and spatial homogeneity in the local space, the distributions of heavy metal contents are similar like that of the exogenous factors. The core ideas of the model include: classification of exogenous factors that affect the contents of heavy metals in the global space, and then achieve different soil unit classes; Construction of spatial estimation method, which adaptively restricts the interpolation of an unknown location within a spatial homogeneous soil unit.
引文
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