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基于 logistic 元胞自动机模型模拟典型制造业中心农田土壤重金属污染的变化。

Simulation of changes in heavy metal contamination in farmland soils of a typical manufacturing center through logistic-based cellular automata modeling.

机构信息

Department of Land Resources Management, College of Resource and Environmental Sciences, China Agricultural University, Beijing, 100193, China.

Guangdong Key Laboratory of Agricultural Environment Pollution Integrated Control, Guangdong Institute of Eco-Environmental and Soil Sciences, Guangzhou, 510650, China.

出版信息

Environ Sci Pollut Res Int. 2016 Jan;23(1):816-30. doi: 10.1007/s11356-015-5334-5. Epub 2015 Sep 5.

Abstract

A customized logistic-based cellular automata (CA) model was developed to simulate changes in heavy metal contamination (HMC) in farmland soils of Dongguan, a manufacturing center in Southern China, and to discover the relationship between HMC and related explanatory variables (continuous and categorical). The model was calibrated through the simulation and validation of HMC in 2012. Thereafter, the model was implemented for the scenario simulation of development alternatives for HMC in 2022. The HMC in 2002 and 2012 was determined through soil tests and cokriging. Continuous variables were divided into two groups by odds ratios. Positive variables (odds ratios >1) included the Nemerow synthetic pollution index in 2002, linear drainage density, distance from the city center, distance from the railway, slope, and secondary industrial output per unit of land. Negative variables (odds ratios <1) included elevation, distance from the road, distance from the key polluting enterprises, distance from the town center, soil pH, and distance from bodies of water. Categorical variables, including soil type, parent material type, organic content grade, and land use type, also significantly influenced HMC according to Wald statistics. The relative operating characteristic and kappa coefficients were 0.91 and 0.64, respectively, which proved the validity and accuracy of the model. The scenario simulation shows that the government should not only implement stricter environmental regulation but also strengthen the remediation of the current polluted area to effectively mitigate HMC.

摘要

建立了定制的基于逻辑的元胞自动机 (CA) 模型,以模拟中国南方制造业中心东莞农田土壤中重金属污染 (HMC) 的变化,并发现 HMC 与相关解释变量(连续变量和分类变量)之间的关系。该模型通过 2012 年 HMC 的模拟和验证进行了校准。此后,该模型用于模拟 2022 年 HMC 发展替代方案的情景。通过土壤测试和协克里金法确定了 2002 年和 2012 年的 HMC。连续变量通过比值比分为两组。正变量(比值比>1)包括 2002 年的内梅罗综合污染指数、线性排水密度、距市中心的距离、距铁路的距离、坡度和单位土地的第二产业产出。负变量(比值比<1)包括海拔、距道路的距离、距重点污染企业的距离、距城镇中心的距离、土壤 pH 值和距水体的距离。根据 Wald 统计,分类变量(包括土壤类型、母质类型、有机含量等级和土地利用类型)也显著影响 HMC。相对工作特征和 kappa 系数分别为 0.91 和 0.64,证明了模型的有效性和准确性。情景模拟表明,政府不仅应实施更严格的环境法规,还应加强对当前污染区域的修复,以有效减轻 HMC。

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