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Effect of metal fractions on rice grain metal uptake and biological parameters in mica mines waste contaminated soils
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作者 saibal ghosh Sandip Mondal +2 位作者 Jajati Mandal Abhishek Mukherjee Pradip Bhattacharyya 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2024年第2期313-324,共12页
Heavy metals from mica waste not only deteriorate the soil quality but also results in the uptake of metals in the crop.The present investigation was conducted to evaluate the effects of different fractions of metals ... Heavy metals from mica waste not only deteriorate the soil quality but also results in the uptake of metals in the crop.The present investigation was conducted to evaluate the effects of different fractions of metals on the uptake in rice,soil microbial and biochemical properties in mica waste-contaminated soils of Jharkhand,India.From each active mine,soil samples were randomly collected at distances of<50 m(zone 1),50–100 m(zone 2),and>100 m(zone 3).Sequential metal extraction was used to determine the fractions of different metals(nickel(Ni),cadmium(Cd),chromium(Cr)and lead(Pb))including water-soluble(Ws)and exchangeable metals(Ex),carbonate-bound metals(CBD),Fe/Mn oxide(OXD)bound metals,organically bound metals(ORG),and residues(RS).The Ni,Cr,Cd and Pb in rice grain were 0.83±0.41,0.41±0.19,0.21±0.14 and 0.17±0.08 mg/kg respectively.From the variable importance plot of the random forest(RF)algorithm,the Ws fraction of Ni,Cr and Cd and Ex fraction of Pb was the most important predictor for rice grain metal content.Further,the partial dependence plots(PDP)give us an insight into the role of the two most important metal fractions on rice grain metal content.The microbial and enzyme activity was significantly and negatively correlated with Ws and Ex metal fractions,indicating that water-soluble and exchangeable fractions exert a strong inhibitory effect on the soil microbiological parameters and enzyme activities. 展开更多
关键词 Metal fractions Microbial parameters Mica waste soil Soil enzymes Rice Random forest
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Appraisal of pollution and health risks associated with coal mine contaminated soil using multimodal statistical and Fuzzy-TOPSIS approaches
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作者 Sumit Kumar Sonali Banerjee +4 位作者 saibal ghosh Santanu Majumder Jajati Mandal Pankaj Kumar Roy Pradip Bhattacharyya 《Frontiers of Environmental Science & Engineering》 SCIE EI CSCD 2024年第5期101-115,共15页
The present study assesses the concentration,probabilistic risk,source classification,and dietary risk arising from heavy metal(HMs)pollution in agricultural soils affected by coal mining in eastern part of India.Anal... The present study assesses the concentration,probabilistic risk,source classification,and dietary risk arising from heavy metal(HMs)pollution in agricultural soils affected by coal mining in eastern part of India.Analyses of soil and rice plant indicated significantly elevated levels of HMs beyond the permissible limit in the contaminated zones(zone 1:PbSoil:108.24±72.97,CuSoil:57.26±23.91,CdSoil:8.44±2.76,CrSoil:180.05±46.90,NiSoil:70.79±25.06 mg/kg;PbGrain:0.96±0.8,CuGrain:8.6±5.1,CdGrain:0.65±0.42,CrGrain:4.78±1.89,NiGrain:11.74±4.38 mg/kg.zone 2:PbSoil:139.56±69.46,CuSoil:69.89±19.86,CdSoil:8.95±2.57,CrSoil:245.46±70.66,NiSoil:95.46±22.89 mg/kg;PbGrain:1.27±0.84,CuGrain:7.9±4.57,CdGrain:0.76±0.43,CrGrain:8.6±1.58,NiGrain:11.50±2.46 mg/kg)compared to the uncontaminated zone(zone 3).Carcinogenic and non-carcinogenic health risks were computed based on the HMs concentration in the soil and rice grain,with Pb,Cr,and Ni identified as posing a high risk to human health.Monte Carlo simulation,the solubility-free ion activity model(FIAM),and severity adjusted margin of exposure(SAMOE)were employed to predict health risk.FIAM hazard quotient(HQ)values for Ni,Cr,Cd,and Pb were>1,indicating a significant non-carcinogenic risk.SAMOE(risk thermometer)results for contaminated zones ranged from low to moderate risk(CrSAMOE:0.05,and NiSAMOE:0.03).Fuzzy-TOPSIS and variable importance plots(from random forest)showed that Ni and Cr were mostly responsible for the toxicity in the rice plant,respectively.A self-organizing map for source classification revealed common origin for the studied HMs with zone 2 exhibiting the highest contamination.The positive matrix factorization model for the source apportionment identified coal mining and transportation as the predominant sources of HMs.Spatial distribution analysis indicated higher contamination near mining sites as compared to distant sampling sites.Consequently,this study will aid environmental scientists and policymakers controlling HM pollution in agricultural soils near coal mines. 展开更多
关键词 Coal mine Free ion activity model Monto Carlo Simulation Pollution and Health risk Fuzzy-TOPSIS
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