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Varied types of particulate matter (PM) persist in the environment and exert a harmful impact on public health. The aim of this review article is to explore the key role of membrane technology in the separation of PM from ambient air. Nanofibrous, microporous, Janus, photocatalytic and hollow fiber membranes have found significant utilization in the effective separation of PM. Recent advancements in membrane technology and their key properties such as antibacterial activity, flame retardancy, wettability, thermal stability and reusability have been underscored in this review article. Moreover, the principles of PM separation have been discussed in detail to understand the working pathway of a membrane air filter via physical, chemical or biological approaches. A brief comparison between the conventional air filters and membrane air filters is provided in terms of cost, separation principle and respective merits and demerits to understand the importance of membranes in the realm of PM separation. This study also highlighted the commercial status of PM air filters with respect to their cost and scalability. By focusing on the innovations in membrane filters, this review article has highlighted the futuristic approaches such as green fabrication techniques, highly efficient material incorporation, use of AI/ML, etc., to overcome the challenges associated with conventional air filters.

The discharge from the Indian peninsular rivers is strongly controlled by the intensity of monsoonal rainfall, which is strongly influenced by atmospheric extreme events, such as El Niño, La Niña, and Indian Ocean Dipole (IOD). To examine the effect of river discharge on concentrations of nutrients, N/P ratios in the estuary and its fluxes to the coastal Bay of Bengal, time-series observations were conducted from 2008 to 2019. An increase in river discharge was observed in recent years due to an increase in monsoon rainfall, expansion of hydropower plant, and siltation of the dam reservoir. The increase in fertilizer application per hectare of agricultural land was observed in recent years. In response to an increase in both river discharge and fertilizer usage, an enhanced concentration of nutrients in the estuary was observed. Low N/P ratios were observed during the peak discharge (June to September) period due to less removal of phosphate through geochemical pathways due to low residence time of water respectively. An increase in N/P ratios, associated with phytoplankton blooms, was observed during moderate and low discharge periods, suggesting faster phosphate removal through biological or geochemical pathways. The flux of nitrogen, phosphate, and silicate increased by 675, 440, and 906% between 2008 and 2019. This study suggested that increases in river discharge and fertilizer application have both contributed to increased nutrient fluxes from the Godavari estuary to the coastal Bay of Bengal. The impacts of these increased fluxes on coastal ecosystems warrant further investigation.

Nowadays, Environmental concern towards plastic waste rises because of its low degradability and creating problems like chunking sewer lines, drainages, waterways, filling landfills, health problems, etc. The best approach is recycling and reuses plastic waste. Increase in the production of plastic day by day but, very little was recycled. On the other hand, huge demand for concrete in the construction industry. Utilization of recycled plastic waste in the production of sustainable concrete by partial replacement of fine aggregate. This study has been investigated the utilization of two types of recycled plastic waste Polyethylene Terephthalate (PET) and Polypropylene (PP) as fine aggregate in concrete. M30 grade of concrete has been used by partial replacement of fine aggregate (River Sand) with recycled plastic waste in the percentage of 5, 10, 15, 20, and 25. The workability and compressive strength results are checked to find the acceptable percentage of incorporation of PET and PP in concrete. From the results, it is observed that the workability is decreased as the percentage of recycled plastic waste is increased. The Optimum Percentage of replacement of PET is 10%. PP has shown a marginal reduction in compressive strength for 5% replacement.

A novel power generation system suitable to recover waste heat from a renewable source at medium temperature level is investigated in the present work. In a regenerative system, saturated vapour is supplied to one of the heat exchangers by a secondary solar collector, which raises the temperature of the boiler as a whole. The main advantage of this method is the reduction in irreversibility in the mixing chamber M3, which encourages a higher flow rate to the turbine. Preheating the circulating solution and completely evaporating the basic stream are used to achieve this. The performance of the system is investigated in energy aspects along with detailed exergy analysis. Environmental impact as a result of the working conditions is essential to propose the optimum decision variables. Exergy analysis in both conventional and advanced methods proposes the system components which need improvements in themselves and associated with other components more properly. Exergoenvironmental analysis using the Life cycle assessment method is examined in the system under the hot sink conditions. Exergy analysis reveals that the component with a high source will yield more losses resulting in higher irreversibility. Hence, turbine and heat exchanger 4 (HE4) need investigation in improving the system's performance. Exergoenvironmental investigation suggests that the highest impact results same components identified by the advanced exergy analysis. Exergoenvironmental analysis on the proposed Kalina power generation system is carried out under hot sink conditions. The exergy destruction and destruction cost rate of 29.23 kW and 0.478 $ h -1 at turbine inlet conditions of 185 °C and 45 bar. The exergoenvironmental factor fb and the relative difference rb reveal that the components with high environmental impact have to be minimized. Turbine and HE4 are the components resulting in higher total exergy and devise related impact on the environment.

This article investigates the merging of geopolymerization and plastic waste usage, imagining high-performance brick production that couples innovation with sustainability, in an effort to transform the environmental effect of the building sector. This idea is supported by the circular economy, which diverts resources from waste streams into a closed-loop paradigm. By creating inorganic polymers from aluminosilicate-rich sources, the chemical process of geopolymerization provides a paradigm change in the production of materials. This procedure is improved even more by the addition of plastic trash, which combats plastic pollution and improves brick qualities. In order to create a more resilient and environmentally conscientious construction industry in the future, this paper outlines the process’s complexities, advantages, and difficulties while arguing for a harmonic fusion of circular economy concepts, technical innovation, and environmental stewardship.

This study compares the ecological footprints of geopolymer and red clay brick prisms, two common building materials for long-lasting masonry structures. The study’s goal is to shed light on the environmental performance of different brick kinds by a thorough review of sustainability indices such as embodied energy, CO2 emissions, water use, and trash creation. The results suggest that geopolymer bricks have better environmental features than red clay bricks, such as lower embodied energy, decreased CO2 emissions, lower water consumption, and less waste creation. These findings underline the promise of geopolymer bricks as an eco-friendlier masonry alternative that may improve green building performance. The report, however, stresses the need to think about more than only environmental damage. The sustainability and feasibility of utilising geopolymer and red clay bricks depend heavily on factors including durability, thermal performance, and cost-effectiveness. In order to make educated selections about brick selection, it is important to evaluate these variables. The results of this study provide the groundwork for more research on sustainable masonry materials and contribute to the development of environmentally aware building practises. Architectural and engineering professionals may encourage environmentally responsible building practises and help create a more sustainable and resilient built environment by taking this study’s findings into account.

The effective use of energy in Smart Building Microgrids (SBMGs) largely depends on accurate load prediction and synchronized demand response especially with battery degradation and unreliability of renewable power. In spite of progress, problems of inaccuracies in forecasting, mismatch in demand and supply, and non-optimal optimization methods still ruin the reliability of the system and the durability of battery resources. A domain-adapted forecasting and optimization framework is proposed in this paper intending to combine Greylag Goose Optimization (GGO) with a Relational Bi-Level Aggregation Graph Convoluted Network (RBAGCN) to be used in SBMGs. In this context, the RBAGCN has been reengineered to incorporate physical and operating interrelations among the energy variables, and the GGO has been utilized to stabilize network weight convergence when the load is non-stationary, as opposed to being an independent optimizer. Before the training of a model, Fast Resampled Iterative Filtering (FRIF) is used to clean up and normalize historical sequential data and Prairie Dog Optimization (PDO) is used to remove the least salient features, i.e. three phase discharge power, battery discharge power, time of day, solar voltage, and ambient temperature. The modified RBAGCN performs load forecasting and demand-based management forecasting, and the GGO automatically adjusts the model parameters to improve convergence strength. As the simulation experiments with the MATLAB R2022b show, the proposed framework achieves an average forecasting accuracy of 98.3%, which is better than the benchmark models, including RNN (82.6%), ABMO-ANN (85.4%), RNN-LSTM (91.7%), GA-DNN (88.5%), and RNN-GRU (90.3%). In addition to this, the framework has lower error measures, such as mean absolute error of 0.0164, mean absolute percentage error of 0.0128, and mean squared error of 0.0069 as compared to benchmark values of 0.042, 0.037 and 0.031 respectively. Moreover, prediction variance and convergence iterations are decreased to 26.5% and 17.8%, respectively, which suggests a higher level of statistical stability and demand management learning efficiency of SBMG load prediction and battery-conscious demand management.

Although the mining sector is essential to technological advancement and economic growth, conventional mining methods have substantial negative social and environmental effects. Throughout the mining lifetime, sustainable mining incorporates social responsibility, environmental stewardship, and economic viability. Because of resource depletion, stakeholder conflicts, and environmental damage, achieving sustainable mining is difficult. The study emphasizes the importance of sustainable methods to mitigate negative impacts on the environment and society. Case studies on surface water, groundwater, soil, noise, and air quality are presented, highlighting the need for comprehensive sustainability evaluation methodologies in mining operations.

Fast moving consumer goods pose a major research problem as the objective is to reach the customers in an efficient manner. The delivery of goods to consumers must reach quickly without any hurdles. We assume that the FMCG companies have multiple number of warehouse hubs to reach its vast majority of consumers. Sometimes a single vehicle may not be enough to complete the tour, hence we may require another small vehicle to reach the small set of customers. The above problem has been modelled as a supply chain vehicle routing model. In our paper we have used ant colony and simulated annealing algorithm to discuss the above problem and compare their efficiencies.

Introduction. Photovoltaic (PV) systems gained immense attraction in the recent years since it produces electricity without causing environmental pollution through direct conversion of solar irradiance into electricity. Solar PV panels produce DC power. The magnitude of this DC power varies with temperature and irradiance of the sun rays. The DC supply from solar panels can be regulated using DC-DC converter and then can further be converted into the desired AC voltage by means of a voltage source inverter before being fed to an induction motor (IM). The speed and torque of an IM, fed from PV arrays, can vary due to the variation in the output power of the panels. Goal of this work is to improve the dynamic performance and reduce the torque ripple of Cuk converter-inverter fed IM drive system. The novelty of the current work proposes interleaved Cuk converter between solar PV DC source and the inverter. Purpose. To provide continuous current using an interleaved Cuk converter to the IM drive and in turn to reduce the torque ripple in IM. Methodology. Introduced an interleaved Cuk converter which is a blend of Cuk converters connected in parallel with each other between solar PV arrays and IM drive system. Originality. Simulation results are obtained for Cuk converter and interleaved Cuk converter fed IM drive by means of MATLAB. The hardware setup for the same IM systems is developed. Practical value. Simulation and hardware results are coincided with each other and it is subject from the simulation and hardware results that the interleaved Cuk converter-inverter fed IM system produced results superior than the Cuk converter inverter fed IM drive system.