Literature DB >> 26341341

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

Menglong Qiu1, Qi Wang2, Fangbai Li2, Junjian Chen2, Guoyi Yang2, Liming Liu3.   

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.

Entities:  

Keywords:  Cellular automata; Change; Farmland soil; Heavy metal contamination; Logistic regression; Scenario simulation

Mesh:

Substances:

Year:  2015        PMID: 26341341     DOI: 10.1007/s11356-015-5334-5

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  29 in total

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  1 in total

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  1 in total

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