Impacts of climate change-induced natural hazards on women and their human rights implications: A study in the southwest coast of Bangladesh.

Women in coastal areas are particularly vulnerable to climate change impacts due to existing gender inequality and socio-cultural norms in Bangladesh. This research aims to explore the vulnerability of women to climate change-induced natural hazards, the challenges they face due to the chain impacts of climate change, and the resulting violation of women's rights. Quantitative and qualitative data were used in this study, where 260 structured questionnaire surveys and 15 Focus Group Discussions were performed at Mongla and Shyamnagar Upazilas in Bagerhat and Satkhira districts, respectively. The quantitative data were analyzed using SPSS 26.0 software, and qualitative data was analyzed thematically. The results disclose that most respondents in Mongla and Shyamnagar reported an increase in the occurrence rate of climate change-induced natural hazards, with cyclones, salinity, and riverbank erosion being the most devastating in Mongla and cyclones, salinity, and storm surges in Shyamnagar. It affects the lives and livelihoods of people, with women being particularly vulnerable due to limited access to education, healthcare, and economic opportunities, and women's rights are violated in these areas. Half of the study area's population has been suffering from infections or inflammation in reproductive organs, especially among fisherwomen. The findings of this study recommend that provisions for alternative livelihoods should be made for women, and all women must be brought under the umbrella of fair social safety net programs.

Removal of hazardous textile dye from simulated wastewater by municipal organic solid waste charcoal using machine learning approaches: Kinetics, isotherm, and thermodynamics.

This study focuses on the probable use of municipal organic solid waste charcoal (MOSWC) as an adsorbent for Methyl orange (MO) adsorption. The prepared MOSWC is characterized by FE-SEM and FT-IR. Batch adsorption experiments were conducted with the influencing of different operational conditions namely time of contact (1-180 min), adsorbate concentration (60-140 mg/L), adsorbent dose (1-5 g/L), pH (3-11), and temperature (25-60 °C). The high coefficient value (R2 = 0.96) of the process optimization model suggests that this model was significant, where pH and adsorbent dose expressively stimulus adsorption efficiency including 40.11 mg/g at pH (3), MO concentration (100 mg/L), and MOSWC dose (1 g/L). Furthermore, the machine learning approaches (ANN and BB-RSM) revealed a good association between the tested and projected values. The highest monolayer adsorption capacity of MO was 90.909 mg/g. Pseudo-second-order was the well-suited kinetics, where Langmuir isotherm could explain better for equilibrium adsorption data. Thermodynamic study shows MO adsorption is favourable, exothermic, and spontaneous. Finally, this study indicates that MOSWC could be a potential candidate for the adsorption of MO from wastewater.

Receptor model-based sources and risks appraisal of potentially toxic elements in the urban soils of Bangladesh.

Rapid urbanization and industrial development have prompted potentially toxic elements (PTEs) in urban soil in Bangladesh, which is a great concern for ecological and public health matters. The present study explored the receptor-based sources, probable human health and ecological risks of PTEs (As, Cd, Pb, Cr, Ni, and Cu) in the urban soil of the Jashore district, Bangladesh. The USEPA modified method 3050B and atomic absorption spectrophotometers were used to digest and evaluate the PTEs concentration in 71 soil samples collected from eleven different land use areas, respectively. The concentration ranges of As, Cd, Pb, Cr, Ni, and Cu in the studied soils were 1.8-18.09, 0.1-3.58, 0.4-113.26, 0.9-72.09, 2.1-68.23, and 3.82-212.57 mg/kg, respectively. The contamination factor (CF), pollution load index (PLI), and enrichment factor (EF) were applied to evaluate the ecological risk posed by PTEs in soils. Soil quality evaluation indices showed that Cd was a great contributor to soil pollution. The PLI values range was 0.48-2.82, indicating base levels to continuous soil degradation. The positive matrix factorization (PMF) model showed that As (50.3 %), Cd (38.8 %), Cu (64.7 %), Pb (81.8 %) and Ni (47.2 %) were derived from industrial sources and mixed anthropogenic sources, while Cr (78.1 %) from natural sources. The highest contamination was found in the metal workshop, followed by the industrial area, and brick filed site. Soil from all land use types revealed moderate to high ecological risk after evaluating probable ecological risks, and the descending order of single metal potential ecological risk was Cd > As > Pb > Cu > Ni > Cr. Ingestion was the primary route of exposure to potentially toxic elements for both adults and children from the study area soil. The overall non-cancer risk to human health is caused by PTEs for children (HI=0.65 ± 0.1) and adults (HI=0.09 ± 0.03) under USEPA safe limit (HI>1), while the cancer risks from exclusively ingesting As through soil were 2.10E-03 and 2.74E-04 for children and adults, respectively, exceeding the USEPA acceptable standard (>1E-04).

Human health risk ​and receptor model-oriented sources of heavy metal pollution in commonly consume vegetable and fish species of high Ganges river floodplain agro-ecological area, Bangladesh.

This study was intended to assess heavy metal contents and sources in commonly consumed vegetables and fish collected from the Jashore district of Bangladesh and to evaluate the probable human health risks via the ingesting of those vegetables and fish species. A total of 130 vegetable and fish samples were analyzed for As, Mn, Cu, Cr, Ni, and Pb concentration by an atomic absorption spectrophotometer. Metals and metalloids like As, Pb, and Cr in vegetable species were greater than the maximum allowable concentration (MAC), while Pb and cu in fish species exceeded the MAC. Pollution evaluation index values were ranges from 0.40-10.35 and 1.53-2.78 for vegetable and fish species, respectively, indicating light to serious pollution. Lactuca sativa followed by Cucurbita moschata, Amaranthus gangeticus for vegetables and Channa punctate, Oreochromis mossambicus, followed by Dendrobranchiata for fish are the most contaminated food items. The positive matrix factorization model showed that As (81.9%), Ni (48%), Cr (49.6%), Mn (46%), Pb (44.3%), and Cu (44.4%) for vegetable species and As (86.9%), Ni (90.5%), Mn (67.6%), Pb (65.3%), Cr (57%) and Cu (46.2%) for fish species were resulting from agrochemical, atmospheric emission, irrigation, contaminated feed, and mixed sources. The self-organizing map and principle component analysis indicates three spatial patterns e.g., As-Mn-Cu, Pb-Cr, and Ni in vegetables and As-Mn-Cr, Cu-Ni, and Pb in fish samples. The THQ values for single elements were less than 1 (except As for vegetables and Pb for fish species) for all food items but the HI values for all of the vegetables (2.18E+00 to 2.04E+01) and fish (1.07E+00 to 9.39E+00) samples were exceeded the USEPA acceptable risk level (HI > 1E+00). While the cancer risks only induced by As for all vegetables and fish species, which exceeded the USEPA safe level (TCR>1E-04). Sensitivity analysis indicates that metal concentration was the most responsible factor for carcinogenic risk.

Arsenic, iron, and manganese in groundwater and its associated human health risk assessment in the rural area of Jashore, Bangladesh.

This study investigated groundwater pollution and potential human health risks from arsenic, iron, and manganese in the rural area of Jashore, Bangladesh. Study results show that the mean value of groundwater pH is 7.25 ± 0.31, with a mean conductivity of 633.94 ± 327.41 µs/cm, while about 73, 97, and 91% of groundwater samples exceeded the Bangladesh drinking water standard limits for As, Fe, and Mn, respectively. Groundwater pollution evaluation indices, including the heavy metal pollution index, the heavy metal evaluation index, the degree of contamination, and the Nemerow pollution index, show that approximately 97, 82, 100, and 100% of samples are in the high degree of pollution category, respectively. Spatial distribution exhibited that the study area is highly exposed to As (73%), Fe (82%), and Mn (46%). In the case of non-carcinogenic health risk via oral exposure, about 94% of samples suggest a high category of risk for infants, and 97% of samples are found to be at high risk for children and adults. The carcinogenic risk of arsenic via an oral exposure pathway suggests that approximately 97% of the samples are found to be at high risk for infants, and all of the samples are at high risk for both adults and children.