This research paper presents a comprehensive assessment of the built-up area in Mysuru City over the decade spanning from 2010 to 2020, employing advanced geospatial techniques. The study aims to analyze the spatiotemporal patterns of urban expansion, land-use dynamics, and associated factors influencing the city’s built environment. Remote sensing imagery, Geographic Information System (GIS) tools, and machine learning algorithms are leveraged to process and interpret satellite data for accurate land-cover classification. The methodology involves the acquisition and preprocessing of multi-temporal satellite imagery to delineate and map the built-up areas at different time intervals. Land-use change detection techniques are employed to identify and quantify alterations in urban morphology over the specified period. Additionally, socio-economic and environmental variables are integrated into the analysis to discern the drivers of urban growth. The outcomes of this research contribute valuable insights into urbanization dynamics and land-use planning strategies, facilitating informed decision-making for sustainable urban development.

As part of green economics, taxes are imposed on emissions of pollutants that adversely impact the environment and public health to reward more innovative, environmentally sustainable, and low-carbon resource use. There are still many nation-states testing the concept of green taxation. Many environmental performance indicators place India low on the list of countries with the worst pollution. One of the main sources of pollution is vehicle exhaust. Green taxes will be imposed on older motor vehicles under guidelines released by the Indian government in 2021. The United Nations Framework Convention on Climate Change received the Indian Nationally Determined Contribution Report in 2022. Taxonomies and low-carbon transport systems were prioritized in India, and incentives and tax breaks were offered to encourage the manufacture and use of vehicles that consume more ethanol. Academic discussions and literature on the subject are still lacking among the masses. Researchers intend to analyze the legal and economic measures taken by the Indian Government to curb vehicular pollution against this background. Due to its significant contribution to air and water pollution, as well as greenhouse gas emissions, the automobile industry has come under increasing scrutiny in recent years. India and China, for instance, have implemented green tax policies to reduce the automotive sector’s environmental footprint and promote environmental sustainability. These policies are effective, but not all of them address the disproportionate impact of environmental injustice on vulnerable populations. Specifically, this study examines the impact of Indian green tax policies on environmental justice in the automobile industry as compared to those in China. A key aim of this study is to provide insights into the strengths and weaknesses of the green taxation policies adopted by each country in the automotive sector, as well as their implications for achieving environmental justice, by analyzing the scope, enforcement, impact on vulnerable communities, industry implications, and alignment with international commitments.

This study aims to design a community-based plastic waste management model specifically for Bangun Village, Mojokerto. Using a qualitative approach through a detailed case study, we gathered rich data from observations, interviews, and document reviews. Our findings reveal that the plastic waste management situation in Bangun Village is fraught with significant social, economic, and environmental challenges. These include inadequate waste segregation, limited recycling facilities, and a general lack of community awareness and participation. The proposed model seeks to address these issues by implementing several key components: community-based plastic waste collection and processing, educational programs to raise awareness and promote sustainable practices, partnerships with external stakeholders such as local government bodies, NGOs, and private sector entities, and institutional restructuring to support and sustain these initiatives. Central to this model is the belief that community education and awareness are crucial foundations for fostering sustainable behavior. By actively involving the community in the waste management process, the model not only aims to mitigate the plastic waste problem but also seeks to provide economic and social benefits to the residents of Bangun Village. This includes creating job opportunities, improving public health, and enhancing the overall quality of life. The strength of this model lies in its ability to integrate community participation, policy support, and external partnerships, making it a robust and effective solution for sustainable plastic waste management. By fostering a collaborative and inclusive approach, the model aims to create a sustainable and resilient community that can effectively tackle the plastic waste challenge while reaping economic and social benefits. In conclusion, the community-based plastic waste management model proposed for Bangun Village has the potential to bring about significant positive changes in the way plastic waste is managed. Through this model, we hope to empower the community to contribute to solving the plastic waste problem while also benefiting economically and socially.

Traffic accidents remain a pressing public safety concern, with a substantial number of incidents resulting from drivers' lack of attentiveness to road signs. Automated road sign recognition has emerged as a promising technology for enhancing driving assistance systems. This study explores the application of Convolutional Neural Networks (CNNs) in automatically recognizing road signs. CNNs, as deep learning algorithms, possess the ability to process and classify visual data, making them well-suited for image-based tasks such as road sign recognition. The research focuses on the data collection process for training the CNN, incorporating a diverse dataset of road sign images to improve recognition accuracy across various scenarios. A mobile application was developed as the user interface, with the output of the system displayed on the app. The results show that the system is capable of recognizing signs in real time, with average accuracy for sign recognition from a distance of 10 meters: i) daytime = 89.8%, ii) nighttime = 75.6%, and iii) rainy conditions = 76.4%. In conclusion, the integration of CNNs in automated road sign recognition, as demonstrated in this study, presents a promising avenue for enhancing driving safety by addressing drivers' attentiveness to road signs in real-time scenarios.

Freshwater systems are one of the most important natural resources for life. Despite their value, these ecosystems have suffered great impacts caused by human activities, which directly affect the aquatic biota and the quality of water sources. Considering the value of aquatic macroinvertebrates as bioindicators of water quality, the richness, composition, and water quality of La Gallega-Morropón stream, Piura-Peru, were compared. Two field trips were conducted between November 2018 and May 2019 (contemplated wet and dry periods, respectively), performing 4 sampling stations. A total of 1772 individuals of macroinvertebrates were recorded, distributed in 22 families. Psychodidae had an abundance of 670 individuals, followed by morphospecies (Gasteropoda) with 379 individuals, Chironomidae with 275 individuals, and Elmidae with 136 individuals (all indicators of water quality). Finally, the water quality index method: 1) BMWP/Col, presented one station with good (HB1), acceptable (HB2), and critical (HB3 and HB4) quality, while 2) EPT exhibited two stations with good quality (HB3 and HB4), HB1 regular quality and HB2 poor (HB3 and HB4), HB1 regular quality and HB2 poor quality.

Drinking water contamination by microplastic particles is a global concern that is becoming increasingly common due to consumer abuse, and we use laser fractionation spectroscopy to examine what microplastic particles in water packaging can do. Several types of bottled water were sampled at several manufacturing facilities in Baghdad. The presence of the measured micropolymer species in water was immediately classified and detected using a laser production resolution spectrometer as well as signal and plasma scattering spectra, various MP polymers “polyethylene terephthalate, polystyrene, polypropylene, polyethylene, and polyvinyl chloride” are five polymers that were successfully detected in drinking water to validate the ability to identify health risk factors based on potential environmental risk index (RI) and potential environmental risk factors (Tin), the results are calculated to show that risk predicates have evolved over a decade depending on the risk factors. To do. The smallest particle was 20 microns and the largest particle was 63.4 microns. Microplastics were detected in 5 out of 10 samples, PET in 4 samples, PS and PP in 2 samples, and PVC in sample 1, the most common polymer in bottled water is polyethylene. The average C/H ratios of the five samples were PE (1.76), PET (1.21), PS (1.52), PP (1.23), and PVC (0.99), on average, the measured trends of C/H values were [PE greater than PS], [PP greater than PET], and [PVC greater than PET]. According to our results, the integration of LIBS technology provides a fast and efficient way to detect microplastics. It has a high resolution of fine particles, allowing the detection of very small particles associated with various adverse effects on human health. The feasibility study for water bottling was approved, and the WHO water quality criteria were confirmed. As a result, we will undertake a thorough analysis of the best water bottling quality. In this study, the initial LIBS signals of several samples were used to completely detect microplastics. Microplastics in bottled water samples have been detected and quantified using LIBS spectroscopy techniques with Ecological Potential Ecological Risk. Analytical technology is used to investigate sources, perform research, and collect relevant data, worldwide reports, and permitted statistics to deliver crucial insights and recommendations.Water samples were obtained from several locations throughout Baghdad. At the source, 2 liters of water were obtained in plastic bottles for each sample, for a total of 10 samples. Each sample is owned by the factories that supplied it.

This research investigates the migration of Bisphenol A (BPA) from packaging containers into take-out vegetable soups and premixed tomato soups through three replicate studies. The samples underwent extraction using solid-phase extraction (SPE) cartridges, followed by separation on a C18 column. BPA concentrations in the soups were assessed at 15, 30, and 45-minute intervals, consistently revealing undetectable levels (<LOQ). Plastic packaging samples, known for BPA utilization in production, remained below the Specific Migration Limit (SML) set at 0.5 mg.kg-1, irrespective of material type or contact conditions. These results, conforming to EC regulations, suggest that food-contact materials (FCMs) in the Indian market pose no apparent health hazards during initial use. The absence of detectable BPA levels is attributed to the limited time-temperature relationship during the study. However, caution is warranted as BPA migration can occur with repeated use, emphasizing the importance of considering material quality and intended use of FCMs. The study underscores the significance of understanding BPA leaching under varied conditions, necessitating further research to explore long-term implications. Overall, the findings provide valuable insights for regulators, manufacturers, and consumers, contributing to the ongoing discourse on food safety and using plastic materials in food packaging.

Biodiesel production from Pongamia pinnata, a tree-based oil using healthcare industrial waste dolomite as a catalyst, was studied. The studies aimed to establish the ideal parameters for producing biodiesel, such as temperature, the ratio of methanol to oil, and the weight percentage of the catalyst. The healthcare industrial waste was procured and characterized. With the operating conditions, temperature maintained at 75°C, methanol to oil molar ratio of about 20:1, and a catalyst weight of 5%, the optimum yield of 92.3% was obtained. The tree-based nonedible oil source for biodiesel production was suggested widely due to its ability to achieve sustainable development goals (SDGs). The Pongamia Pinnata cultivation on barren land supports the afforestation projects with economic and environmental values; further biodiesel from renewable bioresources reduces emissions, and livelihood development to eradicate unemployment are the primary objectives for achieving the SDGs. The tree-based biodiesel production and adaptation of dolomite as a heterogeneous catalyst have proven to be a recent attraction among scientists. The present study is the first report on Pongamia pinnata for biodiesel production catalyzed by dolomite.

The rapid global plastic production of 348 million tonnes in 2018 has led to widespread environmental pollution, especially in terrestrial ecosystems. This study examines microplastics in agricultural soils, coming alarmingly. Particles ≤5 mm, which are defined as microplastics, have detrimental effects on the earth’s environment. Because of its ecological importance, soil acts as an important microplastic sink, affecting soil and plant health and microbial activity. A variety of factors contribute to microplastic pollution in agricultural soils, including plastic mulching, manure, agricultural products (silage nets, twine), sewage sludge, weathering, and other indirect processes. These microplastics migrate, threatening soil integrity and biodiversity. Soil microplastics are analyzed for size, volume fraction, and polymer. Common materials include polyethylene, polypropylene, polyamide, polystyrene, polyvinyl chloride, and polyesters. Techniques, including optical microscopy and spectroscopy, extract and analyze microplastics. This comprehensive review calls for increased concern about the ecological effects of microplastics in agricultural soils. It emphasizes the importance of managing plastics to solve environmental challenges. The integrated environmental assessment highlights the complex relationship between microplastics and soil ecosystems, providing insights into potential risks and suggesting strategies to combat this looming environmental threat.

The indigenous knowledge of the Dayak Paramasan in Indonesia holds the potential for environmental sustainability. This study aims to assess an environmental education framework grounded in the local wisdom of the Paramasan Dayak tribe. A survey was conducted among 300 individuals, including traditional leaders and members of indigenous communities residing in the Paramasan Subdistrict, Indonesia. Data collection occurred from May 2023 to July 2023 and was analyzed using Structural Equation Modelling (SEM). The findings indicate a significant association between indigenous values, local expertise, and community cohesion concerning environmental education. Local wisdom includes local skills, values, and community solidarity, which are crucial for environmental education. Local skills, like farming and hunting, have a significant impact on environmental protection. Passing down knowledge to younger generations needs improvement. Limited local resources create a gap between generations, but some believe traditional leaders can safeguard nature without formal education. Further exploration of implementing environmental education models within school settings will offer valuable insights for Indigenous communities and society, fostering environmentally conscious behaviors.