Sources and types of plastic caps and properties characterization of plastic ropes produced from different types of plastic caps.

Bangladesh produces massive amounts of plastic products to meet the huge population demand. Jashore (Bangladesh) is well-known for discarding huge numbers of plastic caps (PCs). PCs are made up of hard polymer of polypropylene (PP) and high-density polyethylene (HDPE). Jashore was chosen as the study area because huge quantities of PCs are produced here and plastic rope (PR) is prepared using PCs. About 70 % of PCs came from drinking items, 20 % from toiletries items, 7 % from kitchen items, and rest 3 % from unidentified sectors. About 44.0 % of caps were blue, 35.0 % were red, 11.0 % were green, 5.0 % were yellow, 3.0 % were white, and 2.0 % were ash color. About 52 % of caps were prone to damage, 26.0 % were discolored, 15.0 % were slightly damaged, and about 7.0 % were intake. Additionally, different types of ropes (ash color; red color; yellow color, white color, blue color, rasmi, nylon, cotton, jute, and polyester rope) were collected and some mechanical characterization were performed to determine their sustainability. The internal structure of the ash, red, and yellow color PC rope, silk, jute, and cotton rope did not have any structural deformation, but the blue color rope, nylon, and polyester showed a wide range of structural deformation. Tensile strength (TS) was determined using a Universal Testing Machine (UTM), the internal structure was determined using Scanning Electron Microscopy (SEM), and chemical characterization was determined using Fourier Transform Infrared Spectroscopy (FTIR). The characteristics of PR were compared with the characteristics of other ropes. The highest strength was in silky (5315 Mpa) and nylon (2461.5) ropes. FTIR results showed that the chemical structure of C[bond, double bond]O stretching was in 1800 cm-1, and O[bond, double bond]C[bond, double bond]O stretching was in 2349 cm-1 spectrum in PC samples. It can be said that the strength could be dependent on the chemical composition of the ropes.

Hydro-chemical characteristics and groundwater quality evaluation in south-western region of Bangladesh: A GIS-based approach and multivariate analyses.

The study focuses on the chemistry of groundwater and if it is suitable for drinking and for use in agriculture using water quality indices, GIS mapping, and multivariate analyses in Sharsa Upazila, Jashore district, Bangladesh. In this study, the concentration of NH4+, K+, Ca2+, EC, Turbidity overstep BDWS drinking standards in 69 %, 14 %, 100 %, 40 % (WHO), 73 % of samples respectively. The value of Water Quality Indices (WQI) results inferred that the maximum specimen was held good quality for drinking uses, and the values distributed central eastern part to the south-eastern part were good quality water in the selected studied area. The study area's PH, EC, SAR, Na (%), TH, and NO3- values were mapped using GIS tools to show their spatial distribution. The cluster and correlation matrix analyses are used to validate for Principle Component Analysis (PCA). The five PCA results exhibited that the presence of EC, turbidity, K+, SO42- and NO3- was significant and was caused by both geogenic (rock weathering and cation exchange) and anthropogenic (agrochemicals, animal feedback) factor. According to the hydro-geochemical data, the maximum number of samples is of the Ca-Mg-HCO3-Cl type and is dominated by rocks. The irrigation water indices like MH, KR, SAR, and %Na indicate show high-quality groundwater for irrigation purposes. Most of the samples were satisfactory and compiled with WHO and Bangladeshi criteria for standard drinking water guideline values.

Exploring cigarette butts pollution in Saint Martin Island: A marine protected area.

Saint Martin Island (SMI), the only coral island in Bangladesh, is located in the Bay of Bengal and has been identified as a marine protected area (MPA). Littering cigarette butts (CBs) waste in an ecologically sensitive environment can have numerous adverse effects. The purpose of this research is to investigate the abundance and density of CBs in SMI and to assess the pollution status using the Cigarette Butt Pollution Index (CBPI). This study is conducted based on the visual survey method in the three types of land use zones of SMI. During the peak season, the investigation was carried out from 9 a.m. to 5 p.m. in December 2023. A total of 4481 CBs item were counted, and the density ranged from 0.37 to 1.76 m-2 with an average value of 0.99 m-2 across 12 sampling campaigns. The highest density was observed at service zones, and the fishing zones had the lowest density. The calculated CBPI values revealed that 75 % of the sampling stations were in the "severe pollution" while 25 % were classified as "high pollution" status, underscoring the prevalence of hazardous CBs across most areas of SMI. To tackle these issues requires regulatory measures, public awareness initiatives, and community involvement. Effective waste management and eco-friendly product promotion can help reduce CBs pollution risks in marine protected islands.

Enhancing groundwater quality assessment in coastal area: A hybrid modeling approach.

Monitoring of groundwater (GW) resources in coastal areas is vital for human needs, agriculture, ecosystems, securing water supply, biodiversity, and environmental sustainability. Although the utilization of water quality index (WQI) models has proven effective in monitoring GW resources, it has faced substantial criticism due to its inconsistent outcomes, prompting the need for more reliable assessment methods. Therefore, this study addressed this concern by employing the data-driven root mean squared (RMS) models to evaluate groundwater quality (GWQ) in the coastal Bhola district near the Bay of Bengal, Bangladesh. To enhance the reliability of the RMS-WQI model, the research incorporated the extreme gradient boosting (XGBoost) machine learning (ML) algorithm. For the assessment of GWQ, the study utilized eleven crucial indicators, including turbidity (TURB), electric conductivity (EC), pH, total dissolved solids (TDS), nitrate (NO3 -), ammonium (NH4 +), sodium (Na), potassium (K), magnesium (Mg), calcium (Ca), and iron (Fe). In terms of the GW indicators, concentration of K, Ca and Mg exceeded the guideline limit in the collected GW samples. The computed RMS-WQI scores ranged from 54.3 to 72.1, with an average of 65.2, categorizing all sampling sites' GWQ as "fair." In terms of model reliability, XGBoost demonstrated exceptional sensitivity (R2 = 0.97) in predicting GWQ accurately. Furthermore, the RMS-WQI model exhibited minimal uncertainty (<1 %) in predicting WQI scores. These findings implied the efficacy of the RMS-WQI model in accurately assessing GWQ in coastal areas, that would ultimately assist regional environmental managers and strategic planners for effective monitoring and sustainable management of coastal GW resources.