scholarly journals Spatio-Temporal Analysis of Heavy Metals in Arid Soils at the Catchment Scale Using Digital Soil Assessment and a Random Forest Model

2021 ◽  
Vol 13 (9) ◽  
pp. 1698
Author(s):  
Ruhollah Taghizadeh-Mehrjardi ◽  
Hassan Fathizad ◽  
Mohammad Ali Hakimzadeh Ardakani ◽  
Hamid Sodaiezadeh ◽  
Ruth Kerry ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Random Forest ◽  
Metal Contamination ◽  
Heavy Metal Contamination ◽  
Temporal Trends ◽  
Temporal Analysis ◽  
Catchment Scale ◽  
Spatio Temporal ◽  
The Impact

Predicting the spatio-temporal distribution of absorbable heavy metals in soil is needed to identify the potential contaminant sources and develop appropriate management plans to control these hazardous pollutants. Therefore, our aim was to develop a model to predict soil adsorbable heavy metals in arid regions of Iran from 1986 to 2016. Soil adsorbable heavy metals were measured in 201 samples from locations selected using the Latin hypercube sampling method in 2016. A random forest (RF) model was used to determine the relationship between a suite of geospatial predictors derived from remote sensing and digital elevation model data with georeferenced measurements of soil absorbable heavy metals. The trained RF model from 2016 was used to reconstruct the spatial distribution of soil absorbable heavy metals at three historical timesteps (1986, 1999, and 2010). Results indicated that the RF model was effective at predicting the distribution of heavy metals with coefficients of determination of 0.53, 0.59, 0.41, 0.45, and 0.60 for Fe, Mn, Ni, Pb, and Zn, respectively. The predicted maps showed high spatio-temporal variability; for example, there were substantial increases in Pb (the 1.5–2 mg/kg−1 class) where its distribution increased by ~25% from 1988 to 2016—similar trends were observed for the other heavy metals. This study provides insights into the spatio-temporal trends and the potential causes of soil heavy metal contamination to facilitate appropriate planning and management strategies to prevent, control, and reduce the impact of heavy metal contamination in soils.

scholarly journals Assessment of Heavy Metals in Soil, Paddy Straw and SEM analysis of the soil for the impact of wastewater irrigation in Girudhumal Sub basin of Tamil Nadu, India

2018 ◽  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Metal Contamination ◽  
Soil Structure ◽  
Heavy Metal Contamination ◽  
Sem Analysis ◽  
Wastewater Irrigation ◽  
Urban Region ◽  
Paddy Straw ◽  
The Impact

<p>The objective of the study is to determine accumulation and translocation of heavy metals from soil to paddy straw irrigated with urban sewage wastewater in peri-urban region of Girudhumal subbasin area in Madurai. The soil samples were collected in seven locations irrigated with treated and untreated wastewater and analyzed for physical properties like pH, EC, bulk density, soil type, major (N,P,K) and micronutrients (Fe, Mn, Cu, Zn) and heavy metals Ni, Cd, Pb. SEM analysis showed that soil structure is significantly influenced by wastewater irrigation. It confirms that the wastewater irrigation disturbs soil structure and affecting the plant growth in long run.&nbsp; Pb content was higher than the prescribed safe limits in S5 and S6 location, similarly, Ni also was higher than the safe limit in all the locations. Pollution Load Index values are in the range of 0.08-0.56 for all sites, and it indicated that chance of heavy metal contamination is less. The EF values show moderate enrichment to Ni and Zn, Significant enrichment for Cd and Cu, Extremely high for Pb and deficiency for Mn. All these results confirmed that there is no immediate risk of heavy metal pollution, however with respect to Pb and Ni the plant tissues are showing higher values. The transfer factor for heavy metals from soil to paddy straw is less than 0.5 for Cd and for others is more than 0.5 indicated greater chances for heavy metal contamination.</p>

Feasibility of using environmental covariates and machine learning to predict the spatial variability of selected heavy metals in soils

2020 ◽  
Author(s):  
Mojtaba Zeraatpisheh ◽  
Rouhollah Mirzaei ◽  
Younes Garosi ◽  
Ming Xu ◽  
Gerard B.M. Heuvelink ◽  
...  
Keyword(s):  
Machine Learning ◽  
Heavy Metals ◽  
Heavy Metal ◽  
Spatial Distribution ◽  
Random Forest ◽  
Metal Contamination ◽  
Heavy Metal Contamination ◽  
Prediction Performance ◽  
Anthropogenic Sources ◽  
Environmental Covariates

&lt;p&gt;Heavy metal contamination in soil is a major environmental issue intensified by rapid industrial and population growth. Understanding the spatial distribution of soil contamination by heavy metals in the ecosystem is a necessary precondition to monitor soil health and to assess the ecological risks. The main sources of heavy metals in soil are natural and anthropogenic sources. Natural sources are typically released of heavy metals from rock by weathering and atmospheric precipitation. Anthropogenic sources are related to industrialization, rapid urbanization, agricultural practices, and military activities. We analyzed a total of 358 topsoil samples (0&amp;#8211;30 cm) collected in Golestan province in the northeast of Iran based on a regular square grid networks with 1,700 squares each sized 2.5 km&amp;#178;(random sampling within the grid). From these samples, we determined the spatial distribution of Cd, Cu, Ni, Zn, and Pb using random forest (RF). A multi-spectral image (Landsat 8), and environmental derivatives calculated from terrain attributes, climatic parameters, parent material, land use maps, distances to mine sectors, main roads, industrial sites, and rivers were used as covariates to predict the spatial distribution of concentrations of heavy metals. The multi-collinearity of the predictors was examined by the variance inflation factor (VIF), and a feature selection process (genetic algorithm) was applied to avoid noise and optimize the selected input variables for the final model. The predictive accuracy of RF model was assessed by the mean prediction error (ME), root mean squared error (RMSE), and coefficient of determination (R&lt;sup&gt;2&lt;/sup&gt;) using 5-fold cross-validation technique. The results showed that the concentration levels (mg kg&lt;sup&gt;-1&lt;/sup&gt;) of Cd, Cu, Pb, Ni, and Zn varied from 0.02 to 2.75, 9.70 to 93.70, 6.80 to 114.20, 9.50 to 93.20, and 25.10 to 417.4, respectively. The best prediction performance was for Ni (RMSE=9.9 mg kg&lt;sup&gt;-1 &lt;/sup&gt;and R&lt;sup&gt;2&lt;/sup&gt;=56.6%), and the lowest prediction performance for Cd (RMSE=0.4 mg kg&lt;sup&gt;-1 &lt;/sup&gt;and R&lt;sup&gt;2&lt;/sup&gt;=28.0%). Environmental covariates that control soil moisture and water flow along with climatic factors were the most important variables to define the spatial distribution of soil heavy metals. We conclude that the RF model using easily accessible environmental covariates is a promising, cost-effective and fast approach to monitor the spatial distribution of heavy metal contamination in soils.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords:&lt;/strong&gt; Heavy metals; digital soil mapping; machine learning; random forest; spatial variation; soil pollution.&lt;/p&gt;

scholarly journals Investigate workers' health in the western industrial region, Mosul, Iraq

Bionatura ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 1983-1985
Author(s):  
Salim Rabeea Znad ◽  
Mazin Nazar Fadhel ◽  
Ayça Erdem Ünşar
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Metal Contamination ◽  
Direct Contact ◽  
Heavy Metal Contamination ◽  
Control Group ◽  
Industrial Region ◽  
Industrial Areas ◽  
Northern Iraq ◽  
The Impact

The current study aims to determine the level of heavy metal contamination in the Western Industrial Region of Mosul City, northern Iraq. Heavy metals such as( Pb ،Co ،Hg ) are measured In the blood serum of 40 workers in the main industrial areas of Mosul City. It was compared with the control group of (40) people from Mosul university, Where is Far away from the industrial areas and all activities. The results indicated a highly significant increase of P<0.001 in the serum of the workers in the industrial areas compared with the control group. The study investigates the impact of heavy metals on the workers' health in the industrial areas who are in direct contact with them.

scholarly journals Abundance and Diversity of Archaea in Heavy-Metal-Contaminated Soils

1999 ◽  
Vol 65 (8) ◽  
pp. 3293-3297 ◽  
Author(s):  
Ruth-Anne Sandaa ◽  
Øivind Enger ◽  
Vigdis Torsvik
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Contaminated Soils ◽  
Metal Contamination ◽  
Heavy Metal Contamination ◽  
Denaturing Gradient Gel Electrophoresis ◽  
Gradient Gel Electrophoresis ◽  
Abundance And Diversity ◽  
The Impact ◽  
Globally Distributed

ABSTRACT The impact of heavy-metal contamination on archaean communities was studied in soils amended with sewage sludge contaminated with heavy metals to varying extents. Fluorescent in situ hybridization showed a decrease in the percentage of Archaea from 1.3% ± 0.3% of 4′,6-diamidino-2-phenylindole-stained cells in untreated soil to below the detection limit in soils amended with heavy metals. A comparison of the archaean communities of the different plots by denaturing gradient gel electrophoresis revealed differences in the structure of the archaean communities in soils with increasing heavy-metal contamination. Analysis of cloned 16S ribosomal DNA showed close similarities to a unique and globally distributed lineage of the kingdom Crenarchaeota that is phylogenetically distinct from currently characterized crenarchaeotal species.

A brief Survey of Assessment models to Predict stress Level of Heavy Metals in Soils

2020 ◽  
Vol 13 ◽  
Author(s):  
Sangeetha Annam ◽  
Anshu Singla
Keyword(s):  
Economic Growth ◽  
Heavy Metals ◽  
Heavy Metal ◽  
Ecological Risk ◽  
Stress Level ◽  
Metal Contamination ◽  
Heavy Metal Contamination ◽  
Human Life ◽  
High Stress ◽  
Heavy Metal Stress

Abstract: Soil is a major and important natural resource, which not only supports human life but also furnish commodities for ecological and economic growth. Ecological risk has posed a serious threat to the ecosystem by the degradation of soil. The high-stress level of heavy metals like chromium, copper, cadmium, etc. produce ecological risks which include: decrease in the fertility of the soil; reduction in crop yield & degradation of metabolism of living beings, and hence ecological health. The ecological risk associated, demands the assessment of heavy metal stress levels in soils. As the rate of stress level of heavy metals is exponentially increasing in recent times, it is apparent to assess or predict heavy metal contamination in soil. The assessment will help the concerned authorities to take corrective as well as preventive measures to enhance the ecological and hence economic growth. This study reviews the efficient assessment models to predict soil heavy metal contamination.

scholarly journals TINGKAT BIOKONSENTRASI LOGAM BERAT DAN GAMBARAN HISTOPATOLOGI IKAN MUJAIR (Oreochromis Mossambicus) YANG HIDUP DI PERAIRAN TUKAD BADUNG KOTA DENPASAR

2015 ◽  
Vol 9 (1) ◽  
pp. 25
Author(s):  
Made Rahayu Kusumadewi ◽  
I Wayan Budiarsa Suyasa ◽  
I Ketut Berata
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Hexavalent Chromium ◽  
Metal Contamination ◽  
Heavy Metal Contamination ◽  
Quality Standards ◽  
Oreochromis Mossambicus ◽  
Metal Exposure ◽  
Histopathological Changes ◽  
Food Ingredient

Tukad Badung River is one of the potential contamination of heavy metal sare very highin the city of Denpasar. Tilapia (Oreochromis mossambicus) isa commonspecies of fish found in the river and became the object of fishing by the public. The fish is usually consume das a food ingredient forever yangler. Fish can be used as bio-indicators of chemical contamination in the aquatic environment. Determination of heavy metal bioconcentration and analysis of liver histopathology gills organs and muscles is performed to determine the content of heavy metals Pb, Cd, and Cr+6, and the influence of heavy metal exposure to changes in organ histopathology Tilapia that live in Tukad Badung. In this observational study examined the levels of heavy metal contamination include Pb, Cd and Cr+6 in Tilapia meat with AAS method (Atomic Absorption Spectrofotometric), and observe the histopathological changes in organ preparations gills, liver, and muscle were stained with HE staining (hematoxylin eosin). Low Pb content of the fish that live in Tukad Badung 0.8385 mg/kg and high of 20.2600 mg/kg. The content of heavy metals Pb is above the quality standards specified in ISO 7378 : 2009 in the amount of 0.3 mg / kg. The content of Cr+6 low of 1.1402 mg / kg and the highest Cr+6 is 6.2214 mg / kg. The content of Cr+6 is above the quality standards established in the FAO Fish Circular 764 is equal to 1.0 mg / kg. In fish with Pb bioconcentration of 0.8385 mg / kg and Cr+6 of 1.1402 mg / kg was found that histopathological changes gill hyperplasia and fusion, the liver was found degeneration, necrosis, and fibrosis, and in muscle atrophy found. Histopathologicalchangessuch asedema and necrosis ofthe liveris foundin fishwith Pb bioconcentration of 4.5225mg/kg and Cr+6 amounted to2.5163mg/kg. Bio concentration of heavy metal contamination of lead (Pb) and hexavalent chromium (Cr+6) on Tilapia ( Oreochromis mossambicus ) who lives in Tukad Badung river waters exceed the applicable standard. Histopathological changes occur in organs gills, liver, and muscle as a result of exposure to heavy metals lead and hexavalent chromium. Advised the people not to eat Tilapia that live in Tukad Badung

scholarly journals Study on Heavy Metal Contamination in High Water Table Coal Mining Subsidence Ponds That Use Different Resource Reutilization Methods

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3348
Author(s):  
Min Tan ◽  
Kun Wang ◽  
Zhou Xu ◽  
Hanghe Li ◽  
Junfeng Qu
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Coal Mining ◽  
Control Region ◽  
Metal Contamination ◽  
Heavy Metal Contamination ◽  
High Water ◽  
Aquaculture Pond ◽  
Coal Mining Subsidence ◽  
Resource Reutilization

Heavy metals accumulate in high water table coal mining subsidence ponds, resulting in heavy metal enrichment and destruction of the ecological environment. In this study, subsidence ponds with different resource reutilization methods were used as study subjects, and non-remediated subsidence ponds were collectively used as the control region to analyze the heavy metal distributions in water bodies, sediment, and vegetation. The results revealed the arsenic content in the water bodies slightly exceeded Class III of China’s Environmental Quality Standards for Surface Water. The lead content in water inlet vegetation of the control region and the Anguo wetland severely exceeded limits. Pearson’s correlation, PCA, and HCA analysis results indicated that the heavy metals at the study site could be divided into two categories: Category 1 is the most prevalent in aquaculture pond B and mainly originate from aquaculture. Category 2 predominates in control region D and mainly originates from atmospheric deposition, coal mining, and leaching. In general, the degree of heavy metal contamination in the Anguo wetland, aquaculture pond, and fishery–solar hybrid project regions is lower than that in the control region. Therefore, these models should be considered during resource reutilization of subsidence ponds based on the actual conditions.

scholarly journals Heavy Metals Concentration in Contaminated Soils from Southern Part of Romania

2011 ◽  
Vol 68 (2) ◽  
Author(s):  
Diana FLORESCU ◽  
Andreea IORDACHE ◽  
Claudia SANDRU ◽  
Elena HORJ ◽  
Roxana IONETE ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Contaminated Soils ◽  
Metal Contamination ◽  
Industrial Waste ◽  
Heavy Metal Contamination ◽  
Land Application ◽  
Industrial Wastes ◽  
Treatment Processes ◽  
Contamination Of Soils

As a result of accidental spills or leaks, industrial wastes may enter in soil and in streams. Some of the contaminants may not be completely removed by treatment processes; therefore, they could become a problem for these sources. The use of synthetic products (e.g. pesticides, paints, batteries, industrial waste, and land application of industrial or domestic sludge) can result in heavy metal contamination of soils.

scholarly journals Organic Versus Conventional – a Comparative Study on Quality and Nutritive Value of Selected Vegetable Crops of Southern India

2020 ◽  
Vol 18 (1) ◽  
pp. 99-116
Author(s):  
JR Xavier ◽  
V Mythri ◽  
R Nagaraj ◽  
VCP Ramakrishna ◽  
PE Patki ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Vitamin C ◽  
Metal Contamination ◽  
Nutritive Value ◽  
Heavy Metal Contamination ◽  
Plate Count ◽  
Microbial Quality ◽  
Edible Plant ◽  
Lead And Cadmium

Vegetables are defined as edible plant parts generally consumed raw or cooked with a main dish, in a mixed dish, as an appetizer or as a salad. Food safety aspects related to microbial quality (total plate count, yeast and mold and food borne pathogens) and toxic residue (heavy metals) and mineral content were investigated for vegetables such as green leafy vegetable, salad vegetables, sprouts, brinjal, green chilies and French beans collected from organic and conventional outlets from Mysore region, Karnataka, India. Microbial analysis was carried out using standard procedures and mminerals (Ca, K, Fe, Cu, Mg, Mn and Zn) and heavy metals (Cd and Pb) were determined. Significant variations (p>0.05) were observed for microbial quality among organic and conventional vegetables. Mineral and vitamin C content were also significantly higher (p>0.01) in organic samples. Heavy metal contamination for lead and cadmium tested positive for conventional samples while organic samples tested negative. The variables that contributed most for the variability were heavy metal contamination, mineral and vitamin C content. Organically grown vegetables were free from heavy metals and safe for consumption, as well as they are rich in mineral and vitamin C content in comparison to conventional samples. SAARC J. Agri., 18(1): 99-116 (2020)

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