This study employs Remote Sensing (RS) and Geographic Information Systems (GIS) to delineate groundwater potential zones. Various thematic layers, including geomorphology, land use and land cover, geology, rainfall, slope, soil composition, drainage density, and the Topographic Wetness Index (TWI), were integrated using a weighted linear combination in the GIS platform’s spatial analyst tool. The Analytic Hierarchy Process (AHP) was used to assign different ranks to these layers and their sublayers. Groundwater potential zones were categorized as poor (16.54%, 96.25 km²), moderate (67.20%, 391.13 km²), and good (16.26%, 94.62 km²). Validation involved observing water levels in various wells within the study area, with the results’ reliability assessed using a Receiver Operating Characteristic (ROC) curve, demonstrating an accuracy of 88%. The study area faces rapid urbanization and industrialization, stressing the aquifer’s groundwater availability. Identifying groundwater potential zones is thus crucial for effective groundwater development and management.

The utilization of plastic waste and dry leaves in bricks is a sustainable approach to reducing environmental pollution and managing waste. This study aims to investigate the feasibility of incorporating plastic wastes and dry leaves into the manufacturing of bricks, as well as the potential benefits of using such bricks. The study involves the collection of plastic wastes and dry leaves, sorting and cleaning them before mixing them with clay, sand, and cement in varying proportions. The mixtures are then compressed and molded into bricks, which are allowed to dry and cure before being tested for their physical and mechanical properties. To create plastic soil blocks, the soil was added to the molten plastic paste along with dry leaves in the following ratios: 1.5:1.5:0.5 (plastic, soil, and dry leaves, respectively). Results of the study showed that the inclusion of plastic wastes and dry leaves in brick production can lead to significant improvements in properties such as compressive strength, water absorption, and durability. Furthermore, the use of such bricks can help to reduce the amount of plastic waste and dry leaves in the environment, and also provide a sustainable alternative to traditional bricks that use finite natural resources. In conclusion, the utilization of plastic wastes and dry leaves in bricks is a promising approach toward sustainable construction. Further research is needed to optimize the proportions of the materials used and to investigate the long-term durability of the bricks under different environmental conditions.

The environmental impacts of mining, quarrying, and the stone processing industry are significant, affecting air quality, health, and the socioeconomic status of communities worldwide. Key contributors to air pollution include the waste of raw materials from quarrying, non-compliance with scientific protocols, and the extraction of natural mineral resources. The rapid increase in pollution sources, such as dust, water, and noise, has led to the release of various pollutants into the atmosphere, degrading local air quality. This study conducted sampling at twelve sites, adhering to the Central Pollution Control Board’s (CPCB) monitoring guidelines. Twelve metrics, including PM10, PM2.5, SO2, NOx, CO, O3, Pb, NH3, C6H6, C2OH12, As, and Ni, were measured twice a week over a three-month period (January 2024 to March 2024) by the National Ambient Air Quality Standards (NAAQS) in the research area. The results indicated that while SO2 and NOx levels were within permissible limits at all monitored locations, Suspended Particulate Matter (SPM) levels were high at every station. The average baseline levels of PM10 (37.17 μg/m³ to 70.52 μg/m³), PM2.5 (16.98 μg/m³ to 39.85 μg/m³), SO2 (5.29 μg/m³ to 13.91 μg/m³), NOx (9.8 μg/m³ to 29.71 μg/m³), CO (0.15 mg/m³ to 0.32 mg/m³), O3 (6.9 μg/m³ to 15.37 μg/m³), and NH3, Pb, Ni, As, C2OH12, and C6H6 were below the detection levels (BDL) and limits of quantification (LOQ), all within the National Ambient Air Quality Standards for commercial, industrial, and residential areas during the study period. This research highlights the urgent need for effective pollution control measures to mitigate the adverse environmental and health impacts of these industries.

The discharge of large quantities of organic dyes into the environment causes significant harm to humans and the environment. Thus, there is an urgent need to develop cost-effective adsorbents for removing these dyes. In the present study, the synthesis of activated carbon (AC) derived from mixed fish scale waste using KOH activation was investigated for Congo red (CR) dye removal. The finding shows that the obtained biocarbon has a fixed carbon of 42.9% with a crystallinity index of 15.01%. N2 adsorption-desorption isotherm was found to be type IV, signifying mesoporous structure with a surface area and total pore volume of 150.049 m2 g-1 and 0.119 cm3.g-1. Batch adsorption was carried out by various adsorbent doses, initial concentration, contact time, and pH to comprehend the effect of operating parameters on its removal efficacy. The isotherm studies fitted well for Freundlich with an R2 of 0.99%. Adsorption kinetics was best fitted by the pseudo-second-order model and thermodynamic studies revealed the adsorption process to be exothermic and spontaneous. The efficiency of AC was also studied by an amount of sorption and desorption cycles which showed its potential for reusability up to the sixth cycle. Thus, the findings suggest that activated carbon derived from mixed fish scale waste is a promising adsorbent for removing Congo red dye from aqueous solutions.

The present study is focused on the estimation of Land Surface Temperature (LST) and its relationship with three Land Use and Land Cover (LULC) indices--Normalised Difference Vegetation Index (NDVI), Normalised Difference Water Index (NDWI), and Normalised Difference Built-up Index (NDBI) in Raiganj Municipality, India. Landsat-5 TM (2001 & 2011) and Landsat-8 OLI (2021) satellite images were used, processed, and analyzed in the ArcGIS. The study observed that the values of LST and NDBI were increased by +0.9˚C and +0.71, and the values of NDVI and NDWI were decreased by -0.20 and -0.34 during 2001- 2021. The highest LST is observed over the built-up spaces and the lowest over vegetation cover and water bodies. The result indicates LST has a significant positive correlation with NDBI and a negative correlation with NDVI and NDWI. LST is increased due to dramatic changes in LULC especially in unplanned infrastructural development and losses in green and blue spaces.

The increase in the number of visitors to the tourism sector has a positive impact on the economy of the surrounding merchants. However, it also creates negative externalities through increased waste generation. The generation of unresolved waste will disrupt the function of the environment. Ecotourism Waste Management is one way to handle waste from sellers and tourists by collecting, processing, and selling processed products. The “Waste Treatment House” manages sales proceeds from and for sellers with a profit-sharing system. This effort requires the willingness to pay (WTP) sellers for waste management. This study aims to determine the amount of waste retribution and the factors that influence it. The data used in this study were primary data of 104 sellers in Telaga Ngebel Area, Ponorogo, Indonesia, and were processed using ordinary least squares (OLS) regression and descriptive analysis. WTP value is influenced by age, monthly expenses, number of dependents, operating hours, and length of business. The products produced through the program are organic waste processed into compost and fish feed, while inorganic waste is processed into handicrafts. Finally, selling processed waste products and the proceeds from these sales are used to increase merchant empowerment through revenue sharing and savings and loan products. This study has limited secondary data, namely information about the sustainability of waste management that has been carried out and the exact number of sellers in the area around Telaga Ngebel.

In tropical locations, where urban areas experience considerable temperature rises relative to rural areas, the Urban Heat Island (UHI) effect is becoming more and more evident. Reflective building façades, global warming, and hardscape areas are all contributing issues. Because they reflect solar heat, materials like glass, high-pressure laminates, and metallic sheets raise outdoor temperatures, which affects both human comfort and the environment. This study looks into ways to lessen the negative impacts of reflecting façades on urban heat islands (UHIs), with a particular emphasis on how albedo affects microclimates and urban canyons. We examine the impacts of albedo on outdoor thermal comfort by analyzing research from 2003 to 2022. Thermal comfort indices can be calculated with ENVI-met software, which is useful for specialists in urban planning and architecture. To demonstrate these consequences, a case study of a low-rise housing complex located in Greater Noida, India, is provided. With a subtropical climate, this region sees wide changes in temperature, with summer highs frequently reaching 43°C and winter lows of about 7°C. The study uses ENVI-met simulations to evaluate how reflective façades affect thermal comfort in real-world conditions. This highlights the pronounced heat island effect and the localized heat buildup in urban areas during peak daytime h. The simulation revealed significant temperature variations throughout the day, with air temperatures peaking above 43.77°C by mid-afternoon between buildings, demonstrating the pronounced heat island effect. Relative humidity levels were low, around 39% to 40%, contributing to dry air discomfort. Wind velocities exceeded 1.5 meters per second at certain junctions, intensifying discomfort by amplifying the perceived heat. These findings indicate that the use of reflective materials on building façades in Greater Noida exacerbates human thermal discomfort outdoors. The study provides an opportunity to further measure and analyze these effects to develop targeted strategies for mitigating the urban heat island phenomenon and enhancing outdoor comfort in the region.

Due to unprecedented urban growth many localities within the heart of Guwahati city witness groundwater scarcity, mainly during the dry seasons. This study aims to identify potential groundwater zones in the southwestern fringe of the city where the Guwahati Metropolitan Development Authority (GMDA) has adopted plans for future expansion. Rani and Chayani Barduar are two administrative blocks adjacent to the city, possessing a vast tract of unsettled agricultural land ideal for future township development. Multi-criteria decisionmaking technique using a Fuzzy Analytical Hierarchy Process (FAHP) in a Remote Sensing and Geographic Information System (GIS) environment is used to produce the groundwater potential map. A total of eight thematic layers important for groundwater recharge: lithology, geomorphology, slope, rainfall, lineament density, soil, drainage density, and Land Use Land Cover are prepared using satellite data, fieldwork, and other suitable techniques and used as input. The study area is classified into five groundwater potential zones – very high (42.52 %), high (28.67 %), moderate (17.23%), poor (10.21 %), and very poor (1.37%). Validation of the result using a yield map derived from the exploratory wells of the Central Ground Water Board (CGWB) shows strong agreement with the prediction accuracy (AUC = 73.36%). Field-derived water level data also show a high negative correlation (R2 = 0.71) with yield data indicating high specific yield in wells with shallow water levels. The study results will help planners and policymakers with future urban development strategies and sustainable groundwater management practices.

This study aims to demonstrate the importance of the Social Enterprise Model Canvas (SEMC) as an alternative to addressing social and ecological system challenges that describe important aspects of obtaining economic benefits from forest conservation in remote areas such as Papua. The method is carried out through Systematic Reviews and MetaAnalyses (PRISMA) and qualitative content analysis process of social services implemented in Indonesia and formulated into the required SEMC using 216 documents sourced from the Scopus Core Collection database, which consists of three types of documents: articles, reviews, and book reviews. The results are: First, content analysis of environmental service payment business models in Indonesia provides insight for the government and environmental service providers. Second, the benefits scheme as part of SEMC is an important component in determining successful outcomes. Third, in special regions such as Papua which have special autonomy status, where traditional community regulations play an important role, SEMC must cover aspects of government and regional regulations. The implications of this research can be used as recommendations in determining policies related to payment for forest environmental services.

Air pollution is a required environmental and public health issue in India, with multiple municipalities repeatedly ranking among the most polluted in the world. This study leverages large datasets to construct a predictive model for forecasting air quality trends using a novel approach that integrates the Recency Frequency Monetary (RFM) model with deep learning. The research aims to efficiently quantify pollution events frequency and assess the impact of air quality variations on public health, offering a more flexible and adaptive system for air quality monitoring. As a result, a large volume of air quality data provided by RFM (Recency, Frequency, and Monetary) will be flexible and frequently handled and analyzed. In this research, the performance of the integrated RFM technology is examined using Python and Google Colab, and the simulation results are compared to air pollution information from neural networks for structures in additional data using existing air quality monitoring systems in India. Performance examination of both regression and classification techniques in RFM. The execution of RFM can be one of the models and its potential to enhance air quality monitoring and urban sustainability