A discussion to promote global sustainability techniques for motivating plastic waste to minimize carbon footprints

This paper emphasizes the significant challenges facing the sustainable environment, including managing and handling plastic waste and reducing carbon footprints. To tackle these challenges, it is essential to identify people's awareness levels of waste handling techniques and their pro-environmental behaviors. The study focuses on Guwahati, one of the most important cities in Northeast India, which generates increasing plastic waste daily. The paper aims to identify the factors contributing to the reduction of carbon footprints resulting from plastic waste management activities. The data collected from 1326 respondents was analyzed using factor analysis, and the reliability of the dataset was confirmed using Cronbach's alpha (0.84 for the awareness level of waste management techniques and 0.780 for the prevalent mode of plastic waste management techniques). KMO (0.796), Bartlett's test of sphericity (p < 0.001), and determinant score (0.019) were used to assess the data adequacy and factorability of the dataset, and the results were found to be satisfactory. Principal component analysis, exploratory factor analysis, and varimax orthogonal rotation method were used to identify high-loaded factors by reducing the number of variables. The results showed that two highly loaded components, namely awareness level of waste management techniques (AWMT) and prevalent mode of plastic waste management techniques (PWMT), explained 27.53% and 24.34% of the total variance, respectively, with eigenvalues of 3.35 and 2.88. The regression model confirmed the statistical significance of these factors (p < 0.001) and their relationship with the dependent variable, greenhouse reduction (GHGR). The study proposes that minimizing carbon footprints in the environment can be achieved by focusing on a limited number of controllable factors such as AWMT and PWMT. This study provides valuable insights to the authorities in controlling waste generation and achieving a pollution-free environment.     

A comparative assessment of the impact of different occupations on workers' static musculoskeletal fitness.

An ergonomic assessment of the involvement of static muscular forces like back strength, grip strength and pinch strength in different occupations was made. A study was conducted on 45 normal adult males (15 subjects per group) which included video display terminal (VDT) operators, industrial workers and safety inspectors. Their maximum back strength, handgrip strength and pinch strength were measured with dynamometers. The observed values of back strength were significantly lower in VDT operators while significantly higher in safety inspectors and moderate in industrial workers. The values of grip strength and pinch strength of all sample groups were more or less similar. The findings clearly indicate that static muscular strength varies significantly in different occupations. Heavy static muscular load might lead to an accumulation of metabolic waste and toxins on the back resulting in lower back strength in VDT operators and industrial workers.     

Size fraction of hazardous particulate matter governing the respiratory deposition and inhalation risk in the highly polluted city Delhi

Environmental Science and Pollution Research - Delhi has been identified as one of the highly polluted cities in the world and recently associated with the highest population weighted PM2.5...     

Assessment of noise level in Burdwan town, West Bengal

Cities and towns of the world are now facing enormous rise of noise pollution problem due to very high population rise, transport congestion and associated commercial and industrial activities. Burdwan, a district headquarter (100 km away from Kolkata) is one such town where noise pollution is very frequent. In order to assess noise level, noise data were collected from various places of the town by sound level meter with a duration of 30 minutes/location during specified time like 6.00 am, 10.00 am, 1.00 pm, 4.00 pm and 6.00 pm. Most of the monitoring places either belongs to silence category or commercial category areas. From the tabulated data, it was found that sound level lies within the range of 64-85 dB or above in different time at different places. The locations that belong to the silence zone have the noise level up to 90 dB. Statistically noise level in all these zones differ significantly at their peak hours. Noise pollution adversely affects our environment as well as human beings. Sound causes both pathological and psychological disorders in human beings. Implementation of rules and regulations under section 20, 21J, 41, 68(I), 70, 90, 111A of Environment Protection Act, 1986 and of course various technological methods and public awareness are very essential to check noise pollution in Burdwan town.     

Antennal Deformities of Chironomid Larvae and Their Use in Biomonitoring of Heavy Metal Pollutants in the River Damodar of West Bengal,India

Analyses of sediment and water indicate the presence of heavy metal pollutants like lead, zinc, copper, mercury and cadmium of the river Damodar of India. These metals are responsible for causing morphological deformities of antennae and other parts of chironomid larvae. Percentage of deformity correlated positively with the concentrations of Pb in water and sediment (r > 0.6) at the confluence point. A new severity index, SISS_(antenna) has been proposed here to assess deformity at the family or subfamily level.     

Glycerol-mediated synthesis of nanoscale zerovalent iron and its application for the simultaneous reduction of nitrate and alachlor

Environmental Science and Pollution Research - NZVI has long been used for the remediation of different groundwater contaminants but their tendency to get oxidized easily has always been a barrier...     

A critical review on plastic waste administration

The management of plastic waste through various methods such as landfilling, recycling, and incineration has several inherent shortcomings, such as a lack of resources, preparation, motivation, financial power, and expertise. Additionally, these methods are unable to handle the quantity and types of plastic waste, nor do they increase the public's interest in plastic waste management practices. According to research, environmental, economic, and social factors are the main drivers for reducing plastic waste. Experts from around the world have identified four significant areas of concern for which solutions have been proposed: methods of plastic waste reduction and management, the amount of plastic waste, the quality of waste/plastic, and awareness of plastic waste management/cost of plastic waste management. However, individual solutions proposed for these key areas of concern are facing several challenges, leading to delays in their adoption or less popularity globally. The review has identified the reasons for the less popularity of existing plastic waste management methods, which are less environmentally friendly and have a complex process, hence requiring serious reconsideration from technocrats and researchers to develop more sustainable and efficient procedures that do not produce more hazardous by-products. This study also found that financial incentives are one of the main drivers to ensure the mass participation of lower and working-class people.     

Enhancement of nutritional value of fried fish using an artificial intelligence approach

Frying affects the nutritional quality of fish detrimentally. In this study, using Catla catla and mustard oil, experiments were carried out in varying temperatures (140–240 °C), times (5–20 min), and oil amounts (25–100 ml/kg of fish) which established drastic reduction of 44.97% and 99.40% for polyunsaturated fatty acid (PUFA)/saturated fatty acids (SFA) and index of atherogenicity (IA) profile, respectively. Artificial neural network (ANN) was implemented successfully to provide an association between the independent inputs with dependent outputs (values of R² were 0.99 and 0.98; RMSE were 0.038 and 0.046; and performance were 0.038 and 0.067 for PUFA/SFA and IA, respectively) by exhaustive search of various algorithms and activation functions available in literature. ANN model–based meta-heuristic, stochastic optimization formalisms, genetic algorithm (GA) and particle swarm optimization (PSO), were applied to optimize the combination of cooking parameters for improving the nutritional quality of food which improved the nutritional value by maximizing the PUFA/SFA profile up to 63.05% and minimizing the IA profile to 99.64%. Multi-objective genetic algorithm (MOGA) was also employed to tune the inputs by maintaining a balance between the contrasting outputs and enhance the overall food value simultaneously with multi-objective (beneficial for health, economic, and environment-friendly) proposal. MOGA was able to improve the PUFA/SFA profile up to 44.76% and reduce the IA profile to 92.94% concurrently with the reduction of wastage of culinary media and energy consumption, following the optimized cooking condition (118.92 °C, 6.06 min, 40 ml oil/kg of fish).