A comprehensive review of heavy metal pollution in the coastal areas of Bangladesh: abundance,bioaccumulation, health implications,and challenges

Environmental Science and Pollution Research - The coastal zone of Bangladesh, with a population density of 1278 people per square kilometer, is under serious threat due to heavy metal pollution....     

Supercritical water oxidation of phenol and process enhancement with in situ formed Fe2O3 nano catalyst

Environmental Science and Pollution Research - During the past few decades, the treatment of hazardous waste and toxic phenolic compounds has become a major issue in the pharmaceutical, gas/oil,...     

Agronomic application of olive mill wastewaters with phosphate rock in a semi-arid Mediterranean soil modifies the soil properties and decreases the extractable soil phosphorus

Olive mill wastewater (OMW), a by-product of the olive-mill industry, is produced in large amounts in Mediterranean countries. The presence of indigenous phosphate deposits in some countries like Tunisia provides an incentive for direct application or local chemical treatment at low cost to improve the solubility of low reactive phosphate rocks (PRs). The use of naturally occurring low-molecular weight organic acids (LMWOAs) that are present in OMW represents a new perspective in PR research and a possible solution for the recycling of the OMW. The present work was aimed at evaluating, under natural situations (field of olive trees), the effects of agronomic application of OMW (amounts applied: 30, 60 m(3) ha(-1)) with PR (amounts applied: 150 kg ha(-1)) on olive trees soil properties. We measured organic C, nitrogen (N), extractable phosphorus (P), exchangeable calcium (Ca), and exchangeable potassium (K), as well as other properties (pH and electrical conductivity). Our data provide evidence that agronomic application of OMW with PR has important effects on soil properties. Increases in organic C, total N, extractable P and exchangeable potassium (K) were found after the first agronomic application of OMW and PR. These increases were only temporary, following the second agronomic application of OMW and PR, significant reductions were detected in the extractable soil P (19.67 mg kg(-1) in the control soil vs. 8.99 mg kg(-1) in the amended soil). Changes in the extractable soil P could alter plant productivity and plant community structure because shifts in nutriment availability can affect the balance between limiting and non-limiting nutrients.     

Plant-based coagulants/flocculants: characteristics,mechanisms, and possible utilization in treating aquaculture effluent and benefiting from the recovered nutrients

Environmental Science and Pollution Research - The increasing intensification of the aquaculture industry requires the development of new strategies to reduce the negative impacts of wastewater on...     

Hybrid-based Bayesian algorithm and hydrologic indices for flash flood vulnerability assessment in coastal regions: machine learning,risk prediction,and environmental impact

Environmental Science and Pollution Research - Natural hazards and severe weather events are a matter of serious threat to humans, economic activities, and the environment. Flash floods are one of...     

Do anthropogenic and natural factors elevate the haze pollution in the South Asian countries? Evidence from long-term cointegration and VECM causality estimation

Environmental Science and Pollution Research - Anthropogenic and natural factors lead to substantial environmental degradation. This shift is aligned with the country's overall development,...     

Environmental geochemistry of higher radioactivity in a transboundary Himalayan river sediment (Brahmaputra,Bangladesh): potential radiation exposure and health risks

Environmental Science and Pollution Research - This study of a downstream segment (Brahmaputra, Bangladesh) of one of the longest transboundary (China-India-Bangladesh) Himalayan rivers reveals...     

Ecological treatment of El Kriymat boiler ash for recovering vanadium,nickel and zinc from sulfate leach liquor

The primary goal of this work is to develop a technology that allows for the recovery of metal values from waste products, thereby promoting the wise and efficient use of our nation's resources. To achieve this goal, an industrial waste of El Kriymat boiler fly Ash was used for recovering its content of vanadium, nickel and zinc. About 97, 95 and 99% respectively of these economic elements were first dissolved from boiler fly ash magnetic concentrate (after physical concentration). Leaching experiments using optimum conditions include: 180 g/L sulfuric acid concentration and 4% solid/solid proportion manganese dioxide acts as an oxidant at 80 °C. The recovery of vanadium (V) metal ions was carried out using 3% Alamine 336 in kerosene at an equilibrium pH value of 0.9. Subsequently, 15% sodium sulfide solution was used for co-precipitation of nickel and zinc metal ions in the raffinate solution at pH value of 3.5.

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Passive aerated in-vessel composting of food waste with the addition of Sabah ragi for campus sustainability: mass balance,dwarf crape jasmine growth and techno-economic study

Journal of Material Cycles and Waste Management - Composting is a sustainable solution on campus for waste management as it is essential for achieving the ideal circular economy. This study aims to...     

Feature selection approaches for predictive modelling of cadmium sources and pollution levels in water springs

The World Health Organization lists cadmium (Cd) as one of the top ten chemicals of public health concern. Cd is toxic at relatively low exposure levels and has acute and chronic effects on both health and the environment. In this study, we investigate a suite of data-driven methods that could assist decision-makers in estimating Cd levels in water springs, and in identifying polluting sources. Machine learning (ML) regression models were used to identify sources of contamination and predict Cd levels based on support vector machines and a variety of tree-based models, including Random Forests, M5Tree, CatBoost, and gradient boosting. Feature selection analysis revealed that heavy traffic and distance to a major power plant in the sampled area play a leading role in springs Cd contamination, together with precipitation levels and average of slopes of the closest waste dumps upstream to sampled springs. Our best performing ML model was the Adaboost regression tree using all the features (RMSE = 19.36, R^2 = 0.64). Our findings highlight the effectiveness of predictive data-driven modeling in addressing environmental challenges, particularly in high-risk areas with low resources.