Economic and environmental impact analyses of hybrid generation system in respect to Rajasthan

Environmental Science and Pollution Research - This paper intends to show the aspects of an environment-friendly hybrid energy system (HES) for reducing the electrical power problems in remote...     

Seasonal variation and sources of carbonaceous species and elements in PM2.5 and PM10 over the eastern Himalaya

Environmental Science and Pollution Research - The study represents the seasonal characteristics (carbonaceous aerosols and elements) and the contribution of prominent sources of PM2.5 and PM10 in...     

Comparison of fuel characteristics of hydrotreated waste cooking oil with its biodiesel and fossil diesel

Environmental Science and Pollution Research - Compression ignition engines powered by diesel are the work horses of developing countries like India. However, burning fossil fuel causes a lot of...     

A study for evaluation of contaminant transport characteristics through fine-grained soil.

Transport of soluble toxic substances through porous media lead to some significant geoenvironmental problems, for example, leachate migration from municipal and industrial solid waste resulting from unregulated disposal. Advection, dispersion, diffusion, and decay are reported to be the principal mechanisms in such phenomena. Geotechnical properties of the soil also play a significant role in this deterioration. In the present study, laboratory tests were conducted to formulate an appropriate method for assessment of migration of metal ions, such as nickel, through the soil. Relevant kinetic and process parameters, such as aquifer data, surface area, dielectric constant, pH of zero point charge (pHzpc), and permeability were also studied. One-dimensional mathematical modeling was used to describe the dynamics of the process. The present investigation was carried out at an ash pond site of a thermal power plant situated in West Bengal, India.     

ARSENIC IN THE SHALLOW GROUND WATERS OF CONTERMINOUS UNITED STATES: ASSESSMENT,HEALTH RISKS,AND COSTS FOR MCL COMPLIANCE1

A methodology consisting of ordinal logistic regression (OLR) is used to predict the probability of occurrence of arsenic concentrations in different threshold limits in shallow ground waters of the conterminous United States (CONUS) subject to a set of influencing variables. The analysis considered a number of maximum contaminant level (MCL) options as threshold values to estimate the probabilities of occurrence of arsenic in ranges defined by a given MCL of 3, 5, 10, 20, and 50 μg/l and a detection limit of 1 μg/l. The fit between the observed and predicted probability of occurrence was around 83 percent for all MCL options. The estimated probabilities were used to estimate the median background concentration of arsenic in the CONUS. The shallow ground water of the western United States is more vulnerable than the eastern United States. Arizona, Utah, Nevada, and California in particular are hotspots for arsenic contamination. The risk assessment showed that counties in southern California, Arizona, Florida, and Washington and a few others scattered throughout the CONUS face a high risk from arsenic exposure through untreated ground water consumption. A simple cost effectiveness analysis was performed to understand the household costs for MCL compliance in using arsenic contaminated ground water. The results showed that the current MCL of 10 μg/l is a good compromise based on existing treatment technologies.     

Three-phase partitioning for the separation of proteins,enzymes, biopolymers,oils and pigments: a review

Environmental Chemistry Letters - Modern biomass and organic waste are becoming major, carbon-neutral sources of fine chemicals, biomolecules and fuels to replace fossil fuel products. As a...     

PREDICTIVE ASSESSMENT OF SEVERITY OF AGRICULTURAL DROUGHTS BASED ON AGRO-CLIMATIC FACTORS1

ABSTRACT: Past historical evidence indicates that droughts have had great impacts on human life. Drought (or scarcity of water) is assessed based on two key factors, namely, the estimated water demand, and the expected water supply. The formulation of these key factors for a region largely depends on the agro-climatic and economic conditions. Consideration of one such key factor is the relationship between the crop yield and water deficit in the assessment and prediction of agricultural droughts. The varying nature of this relationship from crop to crop adds to the complexity of agricultural drought analysis. To overcome this difficulty in analyzing agricultural droughts of a region, it is adequate to consider and place emphasis on a single crop (i.e., an index crop) grown homogeneously over the major area of the region. From one year to another year, the pattern of water requirement during the growing season of an index crop is rather stationary, and the water supply in arid and semi-arid area is mainly from seasonal random precipitation. In a region, grain yield of the index crop and, in turn, assessment of the severity of drought can reasonably be predicted as a function of the time of crop sowing and the distribution of rainfall, provided that temporal and spatial effects of other contributing factors (crop variety, soil fertility status, crop disease, pest control, cultivation practices etc.) on grain yield are considered to be uniformly distributed (i.e., stable). A predictive method of assessing agricultural droughts in an arid area of western India is presented. The major crop (Pearl Millet) of this region is grown from. July through September. The formulation of the proposed predictive method inherently implies that the grain yield of the main crop is a reliable indicator of agricultural drought. In the development of this predictive relationship (i.e., a regression type model) a number of potential yet simple variables affecting the grain yield in the region were investigated. The soil moisture index, although generally considered significant compared to the simple variables, has been found to account for insignificant variation in the grain yield. Results of our investigations suggest that it would be advisable to exclude the soil moisture index variable from the model. The proposed regression model can be used in the prediction of grain yield of the main crop several months ahead of crop harvesting operations and, in turn, the assessment of agricultural drought severity as mild, moderate, or severe. Such an assessment is expected to be helpful to planners for arranging appropriate measures to effectively combat agricultural drought situations.     

Artificial intelligence as a fundamental tool in management of infectious diseases and its current implementation in COVID-19 pandemic

Environmental Science and Pollution Research - The world has never been prepared for global pandemics like the COVID-19, currently posing an immense threat to the public and consistent pressure on...     

Commensal in conflict: Livestock depredation patterns by free-ranging domestic dogs in the Upper Spiti Landscape,Himachal Pradesh,India

In human-populated landscapes worldwide, domestic dogs (Canis lupus familiaris) are the most abundant terrestrial carnivore. Although dogs have been used for the protection of livestock from wild carnivores, they have also been implicated as predators of livestock. We used a combination of methods (field surveys, interview surveys, and data from secondary sources) to examine the patterns and factors driving livestock depredation by free-ranging dogs, as well as economic losses to local communities in a Trans-Himalayan agro-pastoralist landscape in India. Our results show that livestock abundance was a better predictor of depredation in the villages than local dog abundance. Dogs mainly killed small-bodied livestock and sheep were the most selected prey. Dogs were responsible for the majority of livestock losses, with losses being comparable to that by snow leopards. This high level of conflict may disrupt community benefits from conservation programs and potentially undermine the conservation efforts in the region through a range of cascading effects.     

The effects of dieldrin, dimethoate and permethrin on Tetrahymena pyriformis

The effects of three insecticides, dieldrin, dimethoate and permethrin, on the growth of a holotrichous ciliate, Tetrahymena pyriformis, were studied for 5 days. The ciliate was very sensitive to dieldrin and dimethoate. Both these insecticides produced approximately 81% and 84% inhibition of growth within two days. Dieldrin caused rounding of cells, while dimethoate induced cell lysis. Dimethoate also triggered a general mucocyst discharge. Of the three insecticides, permethrin was the least toxic and induced no morphological alterations.