Environmental Science and Engineering

Greenhouse gas (GHG) emissions are a critical concern in the textile industry. This study assesses the carbon footprint of textile industries in the Gazipur district, using data collected through field visits in 2024. Emissions from fuel combustion and electricity consumption were quantified using the IPCC Tier 1 and Tier 2 approaches, respectively, and calculated using Life Cycle Assessment (LCA) and the GHG Protocol for scope 1 and scope 2 sources. Geographic Information System (GIS) mapping was utilized to delineate the study area. Results revealed that gas combustion is the primary emission source, while diesel combustion contributes the least. The highest emission recorded was 4,343,209 kg CO2e in 2023, and the lowest was 1,014,503 kg CO2e from electricity in study area S2. Larger industries with higher fuel consumption had greater emissions, while smaller industries emitted less due to limited operational scope. To mitigate emissions, the study recommends techniques like gas traps, economizers, effluent gas boilers, steam line insulation, alternative fabrics, and renewable energy sources. It also highlights the potential benefits of carbon trading for cost savings and sustainability. Reducing emissions in textile industries will significantly contribute to mitigating climate change and promoting environmental sustainability in Gazipur and beyond.

The textile industry in Bangladesh, particularly in Narayanganj, is a cornerstone of the nation's economy but faces significant sustainability challenges, including resource inefficiency, environmental pollution and supply chain complexities. This study employs Geographic Information Systems (GIS) to conduct a spatial analysis of sustainable supply chain practices in Narayanganj' s textile dyeing and manufacturing sector. By integrating spatial data with supply chain metrics, the research aims to identify inefficiencies, optimize resource allocation and promote circularity in the textile supply chain. The methodology involves collecting geospatial data on key supply chain nodes, including raw material sourcing, dyeing units, manufacturing facilities and distribution centers. GIS tools are used to map and analyze spatial patterns, resource flows and environmental impacts, such as carbon emissions and wastewater discharge. The study also incorporates stakeholder interviews and field surveys to validate findings and provide actionable insights. Preliminary results show spatial clustering of dyeing units in Narayanganj, creating environmental hotspots. The analysis identifies opportunities to optimize transport, reduce energy use, implement decentralized wastewater systems, integrate renewables and adopt circular economy principles for enhanced sustainability. This research demonstrates GIS's value in addressing textile supply chain challenges, offering a data-driven framework for policymakers and stakeholders to promote sustainability in Bangladesh's textile sector, aligning with global environmental and economic resilience goals.

This research evaluates changes in land use and land cover, as well as vegetation dynamics in Rupganj, using Google Earth Engine and ArcGIS. For that purpose, land cover categories were classified utilizing supervised algorithms applied to multi-temporal Landsat TM and OLI imagery from the years 1994 and 2024. The classification accuracy attained was 86.75% for the 1994 imagery and 87.20% for the 2024 imagery. The analysis of land use and land cover change between 1994 and 2024 revealed significant increases in agricultural, vegetation, and urban areas (262.51%, 60.08%, and 12.96%, respectively). On the other hand, a notable decrease in barren lands and water bodies was observed (-46.12% and -42.11%, respectively). A substantial increase in NDVI values was recorded in 2024 relative to 1994, underscoring the enhanced vegetation health. The results highlight the patterns of urban growth, increased agricultural practices, reforestation initiatives, and changes in hydrological dynamics within the region. It is imperative to implement stringent measures aimed at safeguarding water resources, directing sustainable urban development, encouraging agro-ecological practices, and establishing green infrastructure as a standard practice. In this context, the integration of cloud-enabled monitoring facilitates adaptive and sustainable land management in the face of rapid peri-urban transformation.

The Ganges River, one of the largest rivers on Earth, is a typical monsoonal and flood-controlled system but has low inter-annual peak discharge variability. The seasonal discharge can reach 70 000 m 3 s −1 during the wet season but maintains a low base flow of 500-3000 m 3 s −1 during the dry season. However, the constancy in peak discharge every year categorizes the lower Ganges River as a river with low inter-annual peak discharge variability. This paper examines the modern lower Ganges River by conducting a detailed process-oriented investigation of the main channel, channel margin and overbank deposits, supplemented by satellite image observation and comparison with other modern fluvial systems. The channel and braid bar deposits show a dominance of small-scale to medium-scale cross-sets, with a variety of accretion processes constructing braid bars. The braid bar and channel deposits are typical of facies models of rivers with low inter-annual peak discharge variance. In contrast, the channel flank deposits are dominated by planar lamination, massive sand and mud couplets, and some ripple crosslamination, with very little cross-bedding. Characteristic channel margin deposits represent sediments that accumulated by high-speed flows, multiple-surge and rapidly depositing flows, rapid or regular waning flows and hyperconcentrated flows. The overbank deposits predominantly comprise current ripples with long, thin bedforms and soft sediment deformation structures, which record flow transformation on the muddy flat topography and the processes of an unstable river bank. Our study shows that the channel margin and floodplain deposits are entirely different from those of the braid bar and channel. The bedform distribution of the fluvial deposits here (main channel, channel margin and overbank) may be an important tool in the identification of similar seasonal rivers with low inter-annual peak discharge variance and in the interpretation of fluvial processes.

Bangladesh is a developing country in South Asia that has some forest cover. An estimated 17.1% of the country's land surface is covered by forests. Using Landsat satellite pictures of the Madhupur Sal forest (Arankhola) taken in 1990, 2005, and 2023, we mapped and evaluated changes in the forest's cover over the years 1990 to 2023. We examine variation in forest cover dynamics over the period 1990-2023 using Landsat TM image of 1990, TM+ of 2005, and OLI-TIRS of 2023. This forest is a tropical deciduous stand in the Tangail Forest Division of Bangladesh. The mapping for 1990, 2005, and 2023 indicates that the forest cover accounts for 3714.6 (ha) (22.9%), 2837.4 (ha) (17.55%), and 2202.4 (ha) (13.6%) respectively. The study found that forest cover decrease rate was (-24%), and (-22%) within 1990-2005 and 2005-2023. The Rubber plantation/ Pineapple/ Lemon Cultivation increased by (+49%) within 1990-2005. The detection of land cover change resulted in a major rise in bare land/cropland/settlement (+28%) from 1990 to 2023. Based on our research findings, we have observed a significant rise in the cultivation of rubber, pineapple, and lemon crops, as well as an increase in bare land and settlements. In contrast, both robust and open forest cover declined over the study period. The factors leading to the evolution of the 'Sal Forest' were investigated using GPS-based ground verification and interviews with local residents. Hence, the study proposes the urgent implementation of restrictions on human activities and commercial logging within the forest area, along with the need for policy reforms facilitated by government initiatives.