scholarly journals Heavy Metal Soil Contamination Detection Using Combined Geochemistry and Field Spectroradiometry in the United Kingdom

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 762 ◽  
Author(s):  
Salim Lamine ◽  
George Petropoulos ◽  
Paul Brewer ◽  
Nour-El-Islam Bachari ◽  
Prashant Srivastava ◽  
...  
Keyword(s):  
Heavy Metal ◽  
United Kingdom ◽  
Soil Contamination ◽  
Contaminated Soils ◽  
Prediction Models ◽  
Geochemical Data ◽  
Spectral Features ◽  
Metal Concentrations ◽  
Heavy Metal Concentrations ◽  
Spectral Libraries

Technological advances in hyperspectral remote sensing have been widely applied in heavy metal soil contamination studies, as they are able to provide assessments in a rapid and cost-effective way. The present work investigates the potential role of combining field and laboratory spectroradiometry with geochemical data of lead (Pb), zinc (Zn), copper (Cu) and cadmium (Cd) in quantifying and modelling heavy metal soil contamination (HMSC) for a floodplain site located in Wales, United Kingdom. The study objectives were to: (i) collect field- and lab-based spectra from contaminated soils by using ASD FieldSpec® 3, where the spectrum varies between 350 and 2500 nm; (ii) build field- and lab-based spectral libraries; (iii) conduct geochemical analyses of Pb, Zn, Cu and Cd using atomic absorption spectrometer; (iv) identify the specific spectral regions associated to the modelling of HMSC; and (v) develop and validate heavy metal prediction models (HMPM) for the aforementioned contaminants, by considering their spectral features and concentrations in the soil. Herein, the field- and lab-based spectral features derived from 85 soil samples were used successfully to develop two spectral libraries, which along with the concentrations of Pb, Zn, Cu and Cd were combined to build eight HMPMs using stepwise multiple linear regression. The results showed, for the first time, the feasibility to predict HMSC in a highly contaminated floodplain site by combining soil geochemistry analyses and field spectroradiometry. The generated models help for mapping heavy metal concentrations over a huge area by using space-borne hyperspectral sensors. The results further demonstrated the feasibility of combining geochemistry analyses with filed spectroradiometric data to generate models that can predict heavy metal concentrations.

scholarly journals Estimating the heavy metal concentrations in topsoil in the Daxigou mining area, China, using multispectral satellite imagery

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yun Yang ◽  
Qinfang Cui ◽  
Peng Jia ◽  
Jinbao Liu ◽  
Han Bai
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Back Propagation ◽  
Mining Area ◽  
Shaanxi Province ◽  
Geochemical Data ◽  
M5 Model Tree ◽  
Metal Concentrations ◽  
Heavy Metal Concentrations ◽  
Propagation Network

AbstractA precise estimation of the heavy metal concentrations in soils using multispectral remote sensing technology is challenging. Herein, Landsat8 imagery, a digital elevation model, and geochemical data derived from soil samples are integrated to improve the accuracy of estimating the Cu, Pb, and As concentrations in topsoil, using the Daxigou mining area in Shaanxi Province, China, as a case study. The relationships between the three heavy metals and soil environmental factors were investigated. The optimal combination of factors associated with the elevated concentrations of each heavy metal was determined combining correlation analysis with collinearity tests. A back propagation network optimised using a genetic algorithm was trained with 80% of the data for samples and subsequently employed to estimate the heavy metal concentrations in the area. The validation results show that the RMSE of the proposed model is lower than those of the existing linear model and rule-based M5 model tree. From the spatial distribution map of the three metals concentrations using the proposed method, there are findings that high concentrations of the heavy metals studied occur in the mining area, across the slag storage area, on the sides of the road used for transporting ore materials, and along the base of slopes in the area. These findings are consistent with the survey results in the field. The validation and findings validate the effectiveness of the proposed method.

scholarly journals A Systematic Review of Heavy Metals of Anthropogenic Origin in Environmental Media and Biota in the Context of Gold Mining in Ghana

2014 ◽  
Vol 2014 ◽  
pp. 1-37 ◽  
Author(s):  
Frederick Ato Armah ◽  
Reginald Quansah ◽  
Isaac Luginaah
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Contaminated Soils ◽  
Evidence Synthesis ◽  
Heavy Metal Accumulation ◽  
Metal Exposure ◽  
Metal Concentrations ◽  
Environmental Media ◽  
Heavy Metal Concentrations ◽  
High Degree

Heavy metal accumulation in the food chain is an issue of global concern because it eventually leads to toxic effects on humans through the water we drink, contaminated soils, crops, and animals. Reports of toxicant levels in environmental media (air, water, and soil) and biota in Ghana were sought in SCOPUS, PubMed, MEDLINE, and EMBASE. Of 1004 bibliographic records identified, 54 studies were included in evidence synthesis. A disproportionately large number of papers (about 80%) focused exclusively on environmental media. Papers focusing on biomonitoring and human health were relatively few. Studies reported a high degree of spatial variability for the concentrations of 8 metals in groundwater. Generally, heavy metal concentrations in soil reported by the studies reviewed were higher than metal concentrations in riverine sediments. Urine and hair were the most common biological markers of heavy metal exposure used by the studies reviewed unlike nails, which were sparingly used. By and large, published results on the levels of heavy metals in goldmine and non-mine workers yielded contradictory results. Mostly, concentrations of heavy metals reported by the studies reviewed for nails were higher than for hair. A high degree of variability in the heavy metal concentrations in human subjects in the studies reviewed is likely due to heterogeneity in physiological states, excretion profiles, and body burdens of individuals. These, in turn, may be a product of genetic polymorphisms influencing detoxification efficiency.

Heavy metal concentrations in roadside soils of Lithuania's highways

Geologija ◽  
2008 ◽  
Vol 50 (4) ◽  
pp. 237-245 ◽  
Author(s):  
Audronė Jankaitė ◽  
Pranas Baltrėnas ◽  
Agnė Kazlauskienė
Keyword(s):  
Heavy Metal ◽  
Roadside Soils ◽  
Metal Concentrations ◽  
Heavy Metal Concentrations
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