| With the rapid development of social economy and the upgrading and adjustment of industrial structure in China,there are a large number of contaminated sites caused by factory relocation in cities.The steel industry was listed as one of the most severely polluted industries,belonging to industries with high energy consumption,high pollution,and high emissions.Wastes containing pollutants in industrial production may enter the soil,which can seriously threaten the ecological environment security of the region and the human health of surrounding residents.Among the contaminated sites,mega-sites have the characteristics of large area,complex pollution status,and difficult remediation.Therefore,it has greater social,economic,and environmental impacts.However,complex production activities and hydrogeological conditions leads to some problems such as inaccurate characterization of pollution distribution,unclear influence mechanisms,and deviation present in remediation decisions at mega-sites.Therefore,scientifically cognizing the distribution characteristics,identifying mechanism influencing of soil pollution of iron and steel enterprise mega-sites,delineating the spatial distribution of soil pollution,and formulating the optimal remediation plan are of great significance for reducing ecological risks and remediation costs.In order to achieve accurate characterization of the pollutant distribution and fine remediation of the soil pollution at mega-sites,this study selected a typical closed large integrated iron and steel enterprise mega-site in North China as the study area.Based on multi-source information such as soil pollution sample data,production activity data,and hydrogeological condition data,this study adopted methods such as spatial statistics,geographic detectors,geostatistical interpolation,and multi-objective optimization genetic algorithms.This study analyzed the spatial distribution and influencing mechanism of soil polycyclic aromatic hydrocarbons(PAHs),developed a nonstationary interpolation method for soil pollution at sites,and explored multi-objective optimization methods for parameters of soil remediation.The main results and findings were as follows:(1)Based on multi-source information of the site,the spatial differentiation characteristics of typical soil pollutants at steelworks mega-sites were scientifically recognized.This study combined the spatial distribution of soil PAHs,volatile organic compounds(VOCs),and heavy metals(HMs)with multi-source information such as steel production functional zones,soil layers,and pollutant properties to identify horizontal,vertical,and spatial autocorrelation characteristics of pollutants.The horizontal distribution indicated that soil pollution in steelworks mainly occurred at the front end of the steel process chain,PAHs and VOCs were mainly distributed in coking plants,and HMs were mainly distributed in storage yards.The vertical distribution indicated that HMs,PAHs,and VOCs were enriched in the fill,silt,and clay layer,respectively.The autocorrelation of pollutants was significantly positively correlated with the migration ability of pollutants.The autocorrelation order was VOCs>low molecular weight PAHs(L-PAHs)>middle polycyclic aromatic hydrocarbons(MPAHs)>high molecular weight PAHs(H-PAHs)>HMs.(2)Quantitative analysis was conducted on the influencing factors of soil PAHs spatial distribution at a steelworks mega-site.In this study,the geographical detector method was used to analyze the factors affecting the spatial distribution of PAHs from the aspects of spatial heterogeneity,the difference of the impact of various factors on PAHs in different rings,and the main influencing factors of different soil layers.The analytical results indicated that the spatial distribution of PAHs exhibited significant spatial heterogeneity in the soil layers(q=0.16)and the depths(q=0.17),and the main factor influencing the distribution of PAHs was soil organic matter(q=0.17).The analysis results of PAHs with different ring numbers showed that there were differences in the influencing mechanisms of multi-factors on PAHs with different rings.Production activity factors had a greater impact on L-PAHs than M-PAHs and H-PAHs,and the effect of soil environmental factors on M-PAHs and H-PAHs was greater than that of L-PAHs.The detection results of the influencing factors in different soil layers indicated that the main soil factors of fill,silt,clay,gravel and clay layer were organic matter content,horizontal permeability coefficient(Kh),hydrogen ion concentration(pH),and pH,respectively.Finally,based on the results of spatial distribution and identification of influencing factors of PAHs,this study developed a strategy for the prevention and remediation of pollution at the steelworks mega-site,in which the insitu chemical oxidation remediation technology was applicable to all soil layers.(3)A non-stationary interpolation method was constructed for the spatial distribution of soil PAHs at the steelworks mega-site.This study proposed two solutions for the problems of non-stationary variance and non-stationary mean in the interpolation of soil pollution at sites.In order to deal with the non-stationary variance,this study proposed a new spatial deformation method,namely the variance octree kriging(VOK)method.VOK constructed a stationary deformation space(D-space)by stretching and shrinking the original geographic space(G-space)with low and high spatial correlation,respectively.VOK method included spatial segmentation,spatial scaling and mapping,and ordinary Kriging(OK).The interpolation results for PAHs showed that the root mean square error(RMSE)of VOK method was reduced by 8.10%compared to OK method,and the RMSE in clay soil layer was reduced by 14.61%.In addition,this study applied the method of Stratified Heterogeneity Empirical Bayesian Kriging(SHEBK)to solve the problem of non-stationary mean.Compared with the Empirical Bayesian Kriging(EBK)method,the error of SHEBK method was reduced by 0.05%.(4)The multi-objective optimization of in-situ chemical oxidation technology remediation parameters was explored.This study used multi-objective optimization genetic algorithm to determine the parameters of in situ chemical oxidation technology,including reagent content,injection rate,and injection time.The analysis results indicated that the content of the agent was greatly affected by the pollutant contents,while the injection rate and injection time were greatly affected by soil permeability.The cost of single injection was the lowest in the silt layer and the highest in the gravel and clay layers.Compared with traditional remediation plan,the solution proposed in this study could save about 9%in remediation costs. |
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