Arsenic testing field kits: some considerations and recommendations

In recent years field test kits have been largely used to identify arsenic (As) levels in contaminated water sources in Bangladesh, West Bengal (India), and elsewhere in the world to establish whether or not the water is safe. Most of the kits are based on the reaction of arsine gas with some chemical agent to form a coloured complex; the intensity of the colour is compared visually with a colour-coded chart or measured electronically to calculate the concentration of As in the water sample. In this paper, a step-wise review is presented of the analytical process used in the most commonly available As field test kits and the associated shortcomings of each of these kits. We also identify the research gaps for future work to enhance the accuracy and reliability of test results produced by these kits.     

Diatoms as indicators in the Environmental Monitoring and Assessment Program-Surface Waters (EMAP-SW)

As a part of the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program-Surface Waters (EMAP-SW), sedimentary diatom assemblages were studied from 66 lakes in the northeastern U.S.A. to evaluate the applicability of diatoms for this nation-wide monitoring program. Sediment cores were collected from the study lakes and diatoms were analyzed from the top (present-day) and bottom (pre-industrial) sediment samples. Canonical correspondence analysis (CCA) was used to examine which environmental variables correlate most closely with the distributions of diatom taxa in the top (surface) samples. Forward selection and Monte Carlo permutation tests showed that diatom species distributions were significantly related to total lakewater phosphorus (TP), pH, chloride, Secchi depth, and lake size and maximum depth. We developed weighted-averaging calibration and regression models for inferring TP (r ²=0.62), chloride (r ²=0.61), pH (r ²=0.86), and Secchi depth (r ²=0.62). An index of overall lake disturbance was also developed. Our diatom data indicate that marked changes have occurred in the study lakes since pre-industrial times as a result of anthropogenic activity.     

Inhibition of nitrification in soil by metal diethyldithiocarbamates

IntroductionNitrificationisaprocessinwhichammoniumformofnitrogenisconvertedintonitrateform .Nitrogenuseefficiencyintermsofplantuptakeisgenerallylowandvariesgreatlyunderdifferentsoilandcroppingconditions.MostfertilizerNappliedtosoilsisintheformofammonium orammoniumproducingcompoundssuchasurea,andisusuallyoxidizedrapidlytonitratebynitrifyingmicroorganismsinsoils.Applicationofnitrogenfertilizersmorethanoptimumlevelsleadstolownitrogenrecoveriesandgreaternitrogenaccumulationinthesoilprofile .Theac…     

Prediction of groundwater nitrate concentration in a semiarid region using hybrid Bayesian artificial intelligence approaches

Environmental Science and Pollution Research - Nitrate is a major pollutant in groundwater whose main source is municipal wastewater and agricultural activities. In the present study, Bayesian...     

Anti-barnacle biofouling coatings for the protection of marine vessels: synthesis and progress

Environmental Science and Pollution Research - Marine biofouling has gnawed both mobile and non-mobile marine structures since time immemorial, leading to the deterioration of designed operational...     

Projections of highway vehicle population,energy demand,and CO2 emissions in India to 2040

This paper presents projections of motor vehicles, oil demand, and carbon dioxide (CO₂) emissions for India through the year 2040. The populations of highway vehicles and two‐wheelers are projected under three different scenarios on the basis of economic growth and average household size in India. The results show that by 2040, the number of highway vehicles in India would be 206‐309 million. The oil demand projections for the Indian transportation sector are based on a set of nine scenarios arising out of three vehicle‐growth and three fuel‐economy scenarios. The combined effects of vehicle‐growth and fuel‐economy scenarios, together with the change in annual vehicle usage, result in a projected demand in 2040 by the transportation sector in India of 404‐719 million metric tons (8.5‐15.1 million barrels per day). The corresponding annual CO₂ emissions are projected to be 1.2‐2.2 billion metric tons.     

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...     

Pertinence of nutriments for a stalwart body

Environmental Science and Pollution Research - Nutrition plays a significant role in the prevention and treatment of common diseases. Some superb dietary choices such as functional foods and...     

Tracking land cover change along the western edge of the U.S. Corn Belt from 1984 through 2016 using satellite sensor data: observed trends and contributing factors

The Cropland Data Layers (CDL) are high-resolution geo-referenced data products made available by the U.S. Department of Agriculture. However, the CDL lacks in its ability to be employed as a tool to identify the impact of the gradually evolving drivers of land use change, e.g., climate change, due to its limited historical depth. We implement a robust, phenology-based satellite image classification algorithm to identify historical cropland allocation in eastern South Dakota and North Dakota predating the initial CDL by 13 and 22 years, respectively. Five major land covers, i.e., corn, soybeans, wheat, alfalfa and grass (including native grass, hay and pasture) are identified using archived Landsat-5 surface reflectance data, while achieving CDL-like accuracy. The long-term rate of grassland loss during 1985–2011 is found to be significantly lower (26,781 hectares or 1.5% annually) relative to the near-term rate of grassland loss during 2006-’11 (84,545 hectares or 5.2% annually). We find similar discrepancy in regional corn expansion rates. Our value-added raster data provide opportunities for improved identification of land use drivers, whereas relying solely on the CDL’s restricted historical extent may lead to biased land use change estimates and misguide policy.