To identify the root causes of heavy metal contamination in soils as well as prevent and control such contamination from its sources,this study explored the accumulation patterns and ecological risks of heavy metals l...To identify the root causes of heavy metal contamination in soils as well as prevent and control such contamination from its sources,this study explored the accumulation patterns and ecological risks of heavy metals like Cd and Pb in solid waste in mining areas and across the water body,sediment,soil and agricultural product ecosystem surrounding the mining areas.Focusing on the residual solid waste samples in lead-zinc deposits in a certain area of Guizhou Province,along with samples of topsoils,irrigation water,river sediments,and crops from surrounding areas.This study analyzed the distributions of eight heavy metals,i.e.,Cd,As,Cr,Hg,Pb,Zn,Cu,and Ni,in the samples through field surveys and sample tests.Furthermore,this study assessed the contamination levels and ecological risks of heavy metals in soils,sediments,and agricultural products using methods such as the single-factor index,Nemerow composite index,and potential ecological risk assessment.The results indicate that heavy metals in the solid waste samples all exhibited concentrations exceeding their risk screening values,with 60%greater than their risk intervention values.The soils and sediments demonstrate slight and moderate comprehensive ecological risks of heavy metals.The single-factor potential ecological risks of heavy metals in both the soil and sediment samples decreased in the order of Hg,Cd,Pb,As,Cu,Zn,Cr,and Ni,suggesting the same sources of heavy metals in the soils and sediments.Most of the agricultural product samples exhibited over-limit concentrations of heavy metals dominated by Cd,Pb,Ni,and Cr,excluding Hg and As.The agricultural product assessment using the Nemerow composite index reveals that 35%of the agricultural product samples reached the heavy metal contamination level,implying that the agricultural products from farmland around the solid waste dumps have been contaminated with heavy metals.The eight heavy metals in the soil,sediment,and agricultural product samples manifested high coefficients of variation(CVs),indicating pronounced spatial variability.This suggests that their concentrations in soils,sediments,and agricultural products are significantly influenced by human mining activities.Additionally,the agricultural products exhibit strong transport and accumulation capacities for Cd,Cu,and Zn.展开更多
Laser-induced breakdown spectroscopy （LIBS） has been applied to the analysis of heavy metals in liquid samples. A new approach was presented to lower the limit of detection （LOD） and minimize the sample matrix eff...Laser-induced breakdown spectroscopy （LIBS） has been applied to the analysis of heavy metals in liquid samples. A new approach was presented to lower the limit of detection （LOD） and minimize the sample matrix effects, in which dried wood pellets absorbed the given amounts of Cr standard solutions and then were baked because they have stronger and rapid absorption properties for liquid samples as well as simple elemental compositions. In this work, we have taken a typical heavy metal Cr element as an example, and investigated the spectral feasibility of Cr solutions and dried wood pellets before and after absorbing Cr solutions at the same experimental conditions. The results were demonstrated to successfully produce a superior analytical response for heavy metal elements by using wood pellet as sample matrix according to the obtained LOD of 0.07 ppm for Cr element in solutions.展开更多
Due to its complicated matrix effects, rapid quantitative analysis of chromium in agricultural soils is difficult without the concentration gradient samples by laser-induced breakdown spectroscopy. To improve the anal...Due to its complicated matrix effects, rapid quantitative analysis of chromium in agricultural soils is difficult without the concentration gradient samples by laser-induced breakdown spectroscopy. To improve the analysis speed and accuracy, two calibration models are built with the support vector machine method： one considering the whole spectra and the other based on the segmental spectra input. Considering the results of the multiple linear regression analysis, three segmental spectra are chosen as the input variables of the support vector regression （SVR） model. Compared with the results of the SVR model with the whole spectra input, the relative standard error of prediction is reduced from 3.18% to 2.61% and the running time is saved due to the decrease in the number of input variables, showing the robustness in rapid soil analysis without the concentration gradient samples.展开更多
文摘To identify the root causes of heavy metal contamination in soils as well as prevent and control such contamination from its sources,this study explored the accumulation patterns and ecological risks of heavy metals like Cd and Pb in solid waste in mining areas and across the water body,sediment,soil and agricultural product ecosystem surrounding the mining areas.Focusing on the residual solid waste samples in lead-zinc deposits in a certain area of Guizhou Province,along with samples of topsoils,irrigation water,river sediments,and crops from surrounding areas.This study analyzed the distributions of eight heavy metals,i.e.,Cd,As,Cr,Hg,Pb,Zn,Cu,and Ni,in the samples through field surveys and sample tests.Furthermore,this study assessed the contamination levels and ecological risks of heavy metals in soils,sediments,and agricultural products using methods such as the single-factor index,Nemerow composite index,and potential ecological risk assessment.The results indicate that heavy metals in the solid waste samples all exhibited concentrations exceeding their risk screening values,with 60%greater than their risk intervention values.The soils and sediments demonstrate slight and moderate comprehensive ecological risks of heavy metals.The single-factor potential ecological risks of heavy metals in both the soil and sediment samples decreased in the order of Hg,Cd,Pb,As,Cu,Zn,Cr,and Ni,suggesting the same sources of heavy metals in the soils and sediments.Most of the agricultural product samples exhibited over-limit concentrations of heavy metals dominated by Cd,Pb,Ni,and Cr,excluding Hg and As.The agricultural product assessment using the Nemerow composite index reveals that 35%of the agricultural product samples reached the heavy metal contamination level,implying that the agricultural products from farmland around the solid waste dumps have been contaminated with heavy metals.The eight heavy metals in the soil,sediment,and agricultural product samples manifested high coefficients of variation(CVs),indicating pronounced spatial variability.This suggests that their concentrations in soils,sediments,and agricultural products are significantly influenced by human mining activities.Additionally,the agricultural products exhibit strong transport and accumulation capacities for Cd,Cu,and Zn.
基金supported by National Natural Science Foundation of China(Nos.11064012,11274254,11364037)the JSPS-NRF-NSFC A3 Foresight Program in the Field of Plasma Physics(No.11261140328)the International Scientic and Technologic Cooperative Project of Gansu Province,China(No.1104WCGA186)
文摘Laser-induced breakdown spectroscopy （LIBS） has been applied to the analysis of heavy metals in liquid samples. A new approach was presented to lower the limit of detection （LOD） and minimize the sample matrix effects, in which dried wood pellets absorbed the given amounts of Cr standard solutions and then were baked because they have stronger and rapid absorption properties for liquid samples as well as simple elemental compositions. In this work, we have taken a typical heavy metal Cr element as an example, and investigated the spectral feasibility of Cr solutions and dried wood pellets before and after absorbing Cr solutions at the same experimental conditions. The results were demonstrated to successfully produce a superior analytical response for heavy metal elements by using wood pellet as sample matrix according to the obtained LOD of 0.07 ppm for Cr element in solutions.
基金Supported by the National High-Technology Research and Development Program of China under Grant Nos 2014AA06A513 and 2013AA065502the National Natural Science Foundation of China under Grant No 61378041the Anhui Province Outstanding Youth Science Fund of China under Grant No 1508085JGD02
文摘Due to its complicated matrix effects, rapid quantitative analysis of chromium in agricultural soils is difficult without the concentration gradient samples by laser-induced breakdown spectroscopy. To improve the analysis speed and accuracy, two calibration models are built with the support vector machine method： one considering the whole spectra and the other based on the segmental spectra input. Considering the results of the multiple linear regression analysis, three segmental spectra are chosen as the input variables of the support vector regression （SVR） model. Compared with the results of the SVR model with the whole spectra input, the relative standard error of prediction is reduced from 3.18% to 2.61% and the running time is saved due to the decrease in the number of input variables, showing the robustness in rapid soil analysis without the concentration gradient samples.
