Abstract:The aim of this study was to assess environmental risk due to heavy metals such as cobalt (Co), chromium (Cr), cadmium (Cd), iron (Fe), nickel (Ni) and zinc (Zn) in the groundwater around integrated industrial estate (IIE) Haridwar. Index of geo-accumulation (I geo) values showed Cr contamination in groundwater of both the industrial areas. The quantification of contamination index showed that anthropogenic causes were source of contamination of all metals. Contamination factor showed that contamination levels… Show more
“…The assessment was carried out under two background scenarios viz: geometric and median mean. Authors have recommended the use of geometric mean (BGM) (Thambavani and Uma Mageswari, 2013;Bhutiani et al, 2017) and median mean (BMM) (Monakhov et al, 2015;Bhutiani et al, 2017) as background values in assessment of environmental risk. Geometric and median mean values are usually lower than the arithmetic values depending of the data distribution.…”
Section: Data Sourcementioning
confidence: 99%
“…Note: Geo-accumulation index is by Muller (1969) have been widely applied by Ghaleno et al (2015), Bhutiani et al (2017), Todorova et al (2016), Improved Nemerow Index is by Forstner et al (1990) and have been applied by Guan et al (2014); while Enrichment factor is by Sutherland (2000) and have been applied by Bhutiani et al (2017) 1.3.1 Quantification of contamination or anthropogenic metals Quantification of contamination (QoC) represents the lithogenic metal (Asaah et al 2006;Bhutiani et al, 2017) and was calculated by the formula presented by Bhutiani et al (2017).…”
Section: Data Sourcementioning
confidence: 99%
“…Enrichment factor (EF) is an index used to assess the level of contamination of heavy metals from both natural Molecular Soil Biology 2017, Vol.8, No.2, 7-20 http://msb.biopublisher.ca 10 and anthropogenic sources above uncontaminated background levels (Chen et al, 2007;Amin et al, 2009;Kowalska et al, 2016;Bhutiani et al, 2017;El-Metwally et al, 2017). Fe is the acceptable normalization element (Deely and Fergusson 1994;Elias and Gbadegesin, 2011;Elias et al, 2014;Kowalska et al, 2016;Bhutiani et al, 2017;Mazurek et al, 2017), hence it was used for the calculation of EF.…”
Section: Enrichment Factormentioning
confidence: 99%
“…Fe is the acceptable normalization element (Deely and Fergusson 1994;Elias and Gbadegesin, 2011;Elias et al, 2014;Kowalska et al, 2016;Bhutiani et al, 2017;Mazurek et al, 2017), hence it was used for the calculation of EF. Authors have variously reported that iron has the highest concentration among heavy metals in cassava mill effluents (Adejumo and Ola, 2011;Olorunfemi and Lolodi, 2011;Orhue et al, 2014;Omomowo et al, 2015).…”
Section: Enrichment Factormentioning
confidence: 99%
“…Some of these indices such as enrichment factor (EF), geo-accumulation factor (Igeo) and Quantification of contamination (QoC) have been applied by authors in assessing environmental risk assessment (Muller, 1969;Sutherland, 2000;Asaah et al, 2006;Elias et al, 2014;Tang et al, 2014;Vowotor et al, 2014;Ghaleno et al, 2015;Ghazaryan et al, 2015;Hassaan et al, 2016;Todorova et al, 2016;Wang et al, 2016;Bhutiani et al, 2017). Hence, this study aimed at assessing the Igeo, EF, QoC of heavy metals in soil receiving cassava mill effluents in a rural community of the Niger Delta region of Nigeria.…”
-accumulation index, enrichment factor and quantification of contamination of heavy metals in soil receiving cassava mill effluents in a rural community in the Niger Delta region of Nigeria, Molecular Soil Biology, 8(2): 7-20 (doi: 10.5376/msb.2017.08.0002) Abstract This study investigated enrichment factor, geo-accumulation index and quantification of contamination of heavy metals in cassava mill effluents contaminated soil by smallholder cassava processors in a rural community in the Niger Delta region of Nigeria. Data used for the environmental risk assessment is from secondary sources. The assessment was carried out under two background scenarios viz: geometric (BGM) and median mean (BMM). 50% of mean detected individual metals was used as mean data for location that the metal was not detected. Assessment was carried out following well established protocol. Results showed that enrichment factor (EF), geo-accumulation index (Igeo), improved Nemerow Index (INI), Metal enrichment index (MEI) and quantification of contamination (QoC) in soil heavy metals (viz: Fe, Cr, Zn, Cu, Co, Ni, Mn, Pb and Cd) receiving cassava mill effluents in a rural community of the Niger Delta region of Nigeria revealed un-contamination to moderately contamination for Igeo, NMI, background rank to significant enrichment for EF, no enrichment to moderate enrichment for MEI, and positive values of quantification of contamination is an indication of pollution/contamination due to anthropogenic sources. The study further showed that cassava mill effluents are contributing to soil heavy metal contamination in study area.
“…The assessment was carried out under two background scenarios viz: geometric and median mean. Authors have recommended the use of geometric mean (BGM) (Thambavani and Uma Mageswari, 2013;Bhutiani et al, 2017) and median mean (BMM) (Monakhov et al, 2015;Bhutiani et al, 2017) as background values in assessment of environmental risk. Geometric and median mean values are usually lower than the arithmetic values depending of the data distribution.…”
Section: Data Sourcementioning
confidence: 99%
“…Note: Geo-accumulation index is by Muller (1969) have been widely applied by Ghaleno et al (2015), Bhutiani et al (2017), Todorova et al (2016), Improved Nemerow Index is by Forstner et al (1990) and have been applied by Guan et al (2014); while Enrichment factor is by Sutherland (2000) and have been applied by Bhutiani et al (2017) 1.3.1 Quantification of contamination or anthropogenic metals Quantification of contamination (QoC) represents the lithogenic metal (Asaah et al 2006;Bhutiani et al, 2017) and was calculated by the formula presented by Bhutiani et al (2017).…”
Section: Data Sourcementioning
confidence: 99%
“…Enrichment factor (EF) is an index used to assess the level of contamination of heavy metals from both natural Molecular Soil Biology 2017, Vol.8, No.2, 7-20 http://msb.biopublisher.ca 10 and anthropogenic sources above uncontaminated background levels (Chen et al, 2007;Amin et al, 2009;Kowalska et al, 2016;Bhutiani et al, 2017;El-Metwally et al, 2017). Fe is the acceptable normalization element (Deely and Fergusson 1994;Elias and Gbadegesin, 2011;Elias et al, 2014;Kowalska et al, 2016;Bhutiani et al, 2017;Mazurek et al, 2017), hence it was used for the calculation of EF.…”
Section: Enrichment Factormentioning
confidence: 99%
“…Fe is the acceptable normalization element (Deely and Fergusson 1994;Elias and Gbadegesin, 2011;Elias et al, 2014;Kowalska et al, 2016;Bhutiani et al, 2017;Mazurek et al, 2017), hence it was used for the calculation of EF. Authors have variously reported that iron has the highest concentration among heavy metals in cassava mill effluents (Adejumo and Ola, 2011;Olorunfemi and Lolodi, 2011;Orhue et al, 2014;Omomowo et al, 2015).…”
Section: Enrichment Factormentioning
confidence: 99%
“…Some of these indices such as enrichment factor (EF), geo-accumulation factor (Igeo) and Quantification of contamination (QoC) have been applied by authors in assessing environmental risk assessment (Muller, 1969;Sutherland, 2000;Asaah et al, 2006;Elias et al, 2014;Tang et al, 2014;Vowotor et al, 2014;Ghaleno et al, 2015;Ghazaryan et al, 2015;Hassaan et al, 2016;Todorova et al, 2016;Wang et al, 2016;Bhutiani et al, 2017). Hence, this study aimed at assessing the Igeo, EF, QoC of heavy metals in soil receiving cassava mill effluents in a rural community of the Niger Delta region of Nigeria.…”
-accumulation index, enrichment factor and quantification of contamination of heavy metals in soil receiving cassava mill effluents in a rural community in the Niger Delta region of Nigeria, Molecular Soil Biology, 8(2): 7-20 (doi: 10.5376/msb.2017.08.0002) Abstract This study investigated enrichment factor, geo-accumulation index and quantification of contamination of heavy metals in cassava mill effluents contaminated soil by smallholder cassava processors in a rural community in the Niger Delta region of Nigeria. Data used for the environmental risk assessment is from secondary sources. The assessment was carried out under two background scenarios viz: geometric (BGM) and median mean (BMM). 50% of mean detected individual metals was used as mean data for location that the metal was not detected. Assessment was carried out following well established protocol. Results showed that enrichment factor (EF), geo-accumulation index (Igeo), improved Nemerow Index (INI), Metal enrichment index (MEI) and quantification of contamination (QoC) in soil heavy metals (viz: Fe, Cr, Zn, Cu, Co, Ni, Mn, Pb and Cd) receiving cassava mill effluents in a rural community of the Niger Delta region of Nigeria revealed un-contamination to moderately contamination for Igeo, NMI, background rank to significant enrichment for EF, no enrichment to moderate enrichment for MEI, and positive values of quantification of contamination is an indication of pollution/contamination due to anthropogenic sources. The study further showed that cassava mill effluents are contributing to soil heavy metal contamination in study area.
Non-carcinogenic health risk assessment and predicting of organic and heavy metal pollution of groundwater around Osisioma, Nigeria, using Artificial Neural Networks and Multi-Linear Modeling Principles has been done. 30 groundwater samples were collected systematically and analyzed for organic and heavy metal pollutants. The results of the analysis showed that the heavy metals and organic pollutants within the study area contributed to the pollution of groundwater resources in the locality. However, copper, ethylbenzene, xylene and toluene were within the recommended standard, whereas arsenic, iron, chromium, lead, and benzene were above the recommended standard for drinking water. Correlation matrix and principal component analysis assessment indicated weak correlation and that organic pollutants were major contributors to the loadings. The Contamination factor, Pollution load index, Metal pollution index, Geoaccumulation index, Potential ecological risk index, Elemental Contamination Index, and overall Metal Contamination Index showed no significant pollution, whereas the Heavy Metal Evaluation Index, Pollution Index of Groundwater results showed worrisome impact of the anthropogenic activities on the groundwater quality. Health risk assessment showed that children are more at risk than adults as it related to taking polluted water. MLR models performed better than the ANN. Seven (7) mathematical models were generated for the prediction of pollution indices. Based on the results, this study recommends regular monitoring of groundwater resources and the integration of ANN and MLR modeling approaches for the prediction of pollution indices.
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