Using unsupervised machine learning models to drive groundwater chemistry and associated health risks in Indo-Bangla Sundarban region.

Groundwater is an essential resource in the Sundarban regions of India and Bangladesh, but its quality is deteriorating due to anthropogenic impacts. However, the integrated factors affecting groundwater chemistry, source distribution, and health risk are poorly understood along the Indo-Bangla coastal border. The goal of this study is to assess groundwater chemistry, associated driving factors, source contributions, and potential non-carcinogenic health risks (PN-CHR) using unsupervised machine learning models such as a self-organizing map (SOM), positive matrix factorization (PMF), ion ratios, and Monte Carlo simulation.

A review of microplastic threat mitigation in Asian lentic environments.

Microplastic (MP) pollution has evolved into a significant worldwide environmental concern due to its widespread sources, enduring presence, and adverse effects on lentic ecosystems and human well-being. The growing awareness of the hidden threat posed by MPs in lentic ecosystems has emphasized the need for more in-depth research. Unlike marine environments, there remain unanswered questions about MP hotspots, ecotoxic effects, transport mechanisms, and fragmentation in lentic ecosystems.

Analysis of self-organizing maps and explainable artificial intelligence to identify hydrochemical factors that drive drinking water quality in Haor region.

Water contamination undermines human survival and economic growth. Water resource protection and management require knowledge of water hydrochemistry and drinking water quality characteristics, mechanisms, and factors. Self-organizing maps (SOM) have been developed using quantization and topographic error approaches to cluster hydrochemistry datasets.

Personal protective equipment-derived pollution during Covid-19 era: A critical review of ecotoxicology impacts, intervention strategies, and future challenges.

During the COVID-19 pandemic, people used personal protective equipment (PPE) to lessen the spread of the virus. The release of microplastics (MPs) from discarded PPE is a new threat to the long-term health of the environment and poses challenges that are not yet clear. PPE-derived MPs have been found in multi-environmental compartments, e.

Perception and legacy of soil chromium and lead contamination in an operational small-scale coal mining community.

Operational small-scale coal mining (OSCM) is one of the most significant sources of chromium (Cr) and lead (Pb) pollution in Bangladesh. Attempts to minimize or lessen the use of Cr and Pb in OSCM have shown unsatisfactory results, mainly because they need to address the sociotechnical complexity of pollution concerns in OSCM. This research adopts a multidisciplinary, sociotechnical approach to addressing Cr and Pb problems, coupling soil sampling for Cr and Pb with questionnaires of miners' and inhabitants' perceptions of pollution and its distribution.

Pollution trends and ecological risks of heavy metal(loid)s in coastal zones of Bangladesh: A chemometric review.

Heavy metal(loid)s inputs contribute to human and environmental stresses in the coastal zones of Bangladesh. Several studies have been conducted on metal(loid)s pollution in sediment, soil, and water in the coastal zones. However, they are sporadic, and no attempt has been made in coastal zones from the standpoint of chemometric review.

Identifying factors affecting irrigation metrics in the Haor basin using integrated Shannon's entropy, fuzzy logic and automatic linear model.

The sustainability of agricultural practices is seriously threatened by the quality of water used for irrigation. This paper aims to evaluate the suitability of irrigation water and identify the region suitable for agricultural use in the Haor basin of Bangladesh using conventional irrigation indices such as sodium adsorption ratio (SAR), percent sodium (Na%), magnesium hazard ratio (MHR), permeability index (PI), and Kelly's ratio (KR), as well as novel irrigation indices such as, Shannon's entropy index for irrigation water quality (EWQ) and fuzzy logic index for irrigation water quality (FIWQI). The main influences of groundwater and surface water parameters on irrigation indices were predicted using automatic linear modeling (ALM).

A critical review and prospect of NO and SO pollution over Asia: Hotspots, trends, and sources.

Nitrogen dioxide (NO) and sulfur dioxide (SO) are two major atmospheric pollutants that significantly threaten human health, the environment, and ecosystems worldwide. Despite this, only some studies have investigated the spatiotemporal hotspots of NO and SO, their trends, production, and sources in Asia. Our study presents a literature review covering the production, trends, and sources of NO and SO across Asian countries (e.