Magnetic properties are used throughout the world to measure the concentration of (ferri) magnetic minerals in soil, sediment and dust. These minerals in soil come from a variety of sources, including air-borne particulate pollution, parent rock and paedogenesis. Changes in the content of magnetic minerals, as well as their spatial and vertical distribution in soil profiles are caused by human activity. Magnetic minerals are distinguished by their affinity for other elements found in soil, such as heavy metal. As a result, magnetic susceptibility has been widely used as an approximation of heavy metal contamination in soil. The current study was conducted in a tropical deciduous forest in Central Uttar Pradesh, namely the kukrail reserve forest in Lucknow to assess heavy metal contamination levels caused by various anthropogenic activities and to confirm the utility of using MS surveying in these types of studies. The current study was conducted at two sites viz. agricultural area and forest area because these sites are the most contaminated ones. Significant correlation between heavy metal concentration and magnetic susceptibility with p<0.005 is noticed for Co, Cr, Pb, Zn, Cu and Fe of agricultural area. Similarly in forest area significant correlation exists between Cr, Ni, Pb and Zn.  The χLF values show a significant correlation with the concentration of heavy metals except for Cu and Cr in forest area and Pb and Zn in agricultural area. In comparison to the methodologies of chemical analysis, the χLF measurement techniques provide us with lower cost and less time consuming method for identification of possible soil pollution.

Mathematical models for pollutant transport in semi-infinite aquifers are based on the advection-dispersion equation (ADE) and its variants. This study employs the ADE incorporating time-dependent dispersion and velocity and space-time dependent source and sink, expressed by one function. The dispersion theory allows mechanical dispersion to be directly proportional to seepage velocity. Initially the aquifer is assumed contaminant free and an additional source term is considered at the inlet boundary. A flux type boundary condition is considered in the semi-infinite part of the domain. Laplace transform technique (LTT) is then applied to obtain a closed form analytical solution. The effect of source/sink term as a function in the one-dimensional advection-dispersion equation is explained through the graphical representation for the set of input data based on similar data available in hydrological literature. Matlab software is used to obtain the graphical representation of the obtained solution. The obtained analytical solution of the proposed model may be helpful in the groundwater hydrology areas.

The term bioremediation describes biological machinery of recycling wastes to make them harmless and useful to some extent. Bioremediation is the most proficient tool to manage the polluted environment and recover contaminated river water.  Bioremediation is very much involved in the degradation, eradication, restriction, or reclamation varied chemical and physical hazardous substances from the nearby with the action of all-inclusive microorganisms. The fundamental principle of bioremediation is disintegrating and transmuting pollutants such as hydrocarbons, oil, heavy metal, pesticides and so on. Different microbes like aerobic, anaerobic, fungi and algae are incorporated in bioremediation process. At present, several methods and approaches like bio stimulation, bio augmentation, and monitoring natural recovery are common and functional in different sites around the world for treating contaminated river water. However, all bioremediation procedures it has its own pros and cons due to its own unambiguous application. Above all, utilization of bioremediation paving a minimal inconsiderably contaminated, healthy as well as safe and sound future.

Readymade garment industries are the prominent economic sector for Bangladesh as well as scoping the huge working area for workers. But health condition of workers, drinking water quality, and proper maintenance of the environmental parameters are not well monitored. This study aims to assess the physio-chemical and bacteriological quality of drinking water provided for the garment workers in Dhaka. Ten garment industries were pre-selected for the water quality analysis and three drinking water samples from each industry were taken for further analysis. Physio-chemical parameters viz pH, TDS were measured by probe method and Total harness and Chloride of the water samples were measured by titrimetric method, respectively. Biological parameters viz Total coliforms, Fecal coliforms, Total aerobic bacteria count, Fecal streptococci, Pseudomonas spp., and Vibrio Cholerae were determined through standard procedure. Results show that pH (6.7±0.05 to 7.4±0.20), TDS (126.2±8.42 to 217.9±3.60 mg/L), Total Hardness (92±7.07 to 275±21.22 mg/L), and Chloride (8.5±0.95 to 46.5±3.27 mg/L) are within the acceptable limit. Bacteriological results show that Total coliform (1.05×103±0.071×103 to 2.16×103±0.084×103 CFU/100 ml), Fecal coliforms (145±2.828 to 249±21.213 CFU/100 ml), and Total aerobic bacteria count (2152.5±399.51 to 5540.5±185.97 CFU/100 ml) are higher than the standard limits. Pseudomonas spp. was also present in all drinking water samples but Fecal streptococci and Vibrio Cholerae were absent in all water samples. Bacteriological analysis shows that sources of drinking water are contaminated and proper maintenance and screening facilities should be improved.

An important practice in environmental risk management is assessing the consequences of heavy metal concentrations resulting from a mine dam tailing failure on soil, water, and trees. To appraise the extent of pollution, an effective classification is essential. In this study, trace element contamination is handled as a two-group classification problem and examined the performance of supervised regularization algorithms as spatial classifiers using imbalanced uncertain data. In addition to conventional shrinkage algorithms such as Ridge, the Lasso and Elastic-Net, the generalized t-statistic-based U-Lasso classifiers have been introduced and tested for mitigating such imbalances and adjusting weights for class distributions. The feature interpretation studies underlined that the most important indicator of the models is Zinc (Zn). The experimental studies revealed that the Ridge classifier (l2 penalty) outperforms the other models. Statistically, the U-Lasso models exhibited notable explanation capacity and their performances recorded close to the conventional shrinkage algorithms. The use of statistical learning-based classification approach to appraise geo-environmental contamination under the conditions of natural variability and spatial uncertainty provides useful meta-data and reliable classification models.

Fluoride is one of the parameters which is non-degradable and naturally occurring inorganic anion found in many natural streams, lakes, and groundwater. Serious problems are faced in several parts of India due to the high consumption of fluoride through drinking water. These may cause dental and skeletal fluorosis to humans. This study aims to examine the level of fluoride in both Bharalu river water and groundwater within Guwahati city, Assam, India, and also to analyze the impact of fluoride reach river water on the groundwater aquifer adjacent to the river. From the investigation, it has been observed that the concentration of fluoride varies from 0.02 to 3.73 mg/l in river water and 0.04 to 4.7 mg/l in the case of groundwater. The statistical analysis shows that there is a strong correlation between the fluoride concentration of river water and groundwater. This indicates that the groundwater might have contaminated by the polluted river water.

In the present investigation, 41 soil samples were subjected to single step chemical partitioning to assess the lithogenic and non-lithogenic portions of metals in Tehran's soils. The share of various studied metals in the anthropogenic portion ranges from as low as 0.2% to as high as 85% of bulk concentration. Geo-accumulation index (Igeo) showed that Cd falls within "heavily contaminated" soils. It might be inferred that Ni, Cu, Cr, Zn, Co and Ca fall within "Deficient to minimal" class in accordance with enrichment factor (EF) classification.. Enrichment factor values (to some extents) match with the chemical partition studies results (except for Ni and Cr). The very low Ca content of soil samples could be indicative of low biological productivity in the Tehran's soil. Also the very low concentrations of Mn could be indicative of reducing environment in soils of Tehran.

This study was carried out for the purpose of investigating the issue of tailings dams as a potential source of contamination by trace elements in soils at the Sidi Bou Othmane mine in the Marrakech Region, Morocco. Soil samples taken from depths of up to 15 cm and within a radius of 50 m from the tailings dams, were analyzed for Cd, Cu, Pb and Zn using atomic absorption spectrometry. Average concentrations of Cd, Cu, Pb and Zn in soils around the abandoned tailings dams were, respectively, 157.2±8.8, 969.1±38.7, 1640.7±42.7 and 2846.8±84.6 mg/kg. Soils in the vicinity of the decommissioned tailings dams registered increased values for Cd, Cu, Pb and Zn. Contamination factors (CF) and pollution index (PI) were calculated in order to estimate the anthropogenic contribution of target pollutants which determined Cd, Cu, Pb and Zn as the main pollutants in this region. The results revealed the polluted areas in the vicinity of the mine, especially two rural communities apparently linked to the lack of appropriate measures to counteract the effects of these mine tailings, which were causing a progressive contamination of the soil with residues of heavy metal emissions in this region under study. Improved strategies for the management of tailings, among other factors, might have influenced the reduced level of contamination by trace elements at the abandoned mine tailings dam sites.

Bioremediation has become a trending and developing field in environmental restoration through the use of micro-organisms to utilize and reduced the concentration and toxicity of various chemical pollutants. This study is on bioremediation of hydrocarbon-polluted soils using some agricultural wastes. Ninety (90) plastic buckets were filled with 4kg each of the composite soil. The soil contained in the plastic buckets was spiked with 250ml crude oil, except in the unpolluted plastic buckets (0%) crude oil. The agro-wastes (plantain stem sap, bush mango peels, and fruited pumpkin husk powder) in single and combined forms were applied after 14 days soil pollution. The amendments were applied as follows: Pristine control (0% agro-wastes), crude-oil control (0% agro-wastes), 150g, 250g, and 350g of the agro-wastes. Soil samples were collected at 90 days for soil microbial counts and the total hydrocarbon content of the soil. Data collected were subjected to 2-way ANOVA. The result showed that the microbial population in the crude-oil polluted soil amended with different agricultural wastes significantly increased (p<0.05) the total heterotrophic and crude oil utilizing bacterial and fungal counts in the soils and the increase in microbial population result in a significant reduction in total hydrocarbon content (THC) of the soils. The reduction in the THC of the soil was treatment dependent. It is, therefore concluded that based on the efficiency of these agro-wastes in enhancing microbial degradation, further studies should be carried out on the enzyme activities and production of bio-surfactant from the wastes to shorten the degradation time.

With increased population, rapid industrialization and life style changes, the characteristics and the rates of solid waste generation have gone under drastic change in India. Generally, in India, management of solid waste landfill is of major concern with respect to the existing circumstances. The illegal dumping of municipal solid waste on the outskirts of cities is creating major environmental and public health problems. Improper and unscientific waste management results in potential threats from leachate leakage with subsequent impact on environment (i.e. soil, air and waterbodies) and human being. It is therefore, important to evaluate the contamination potential threat of landfill leachate. This study assesses the potential contamination from the landfill leachate by an index called leachate pollution index (LPI) and suggestions are given the landfill sites of five major cities i.e. Bangalore, Chennai, Delhi, Navi Mumbai &amp; Kolkata in India. The landfill leachate samples from these sites have been assessed using leachate pollution index for the implementation of appropriate leachate treatment techniques for reducing the adverse effects on the environment. The results show that the Pallikkaranai landfill site for Chennai city and Mavallipura landfill site for Bangalore city are highly deteriorating and may lead to increase in human health risk for nearby dwellings.