Outdoor air pollution causes a lot of health problems for humans. Particulate Matter 2.5 (PM2.5), due to its small size, can enter the human respiratory system with ease and cause significant health effects on humans. This makes PM2.5 significant among the various air pollutants. Hence, it is important to measure the value of PM2.5 accurately for better management of air quality. Algorithms for deep learning and machine learning can be used to forecast air quality data. A model that minimizes the prediction error of the PM2.5 forecast is needed. In this paper, a PM2.5 concentration estimation model using Bi-LSTM (Bidirectional Long Short-Term Memory) with meteorological data as predictor variables is proposed. For a better estimation of PM2.5 values, the hyperparameters of the Bi-LSTM model used are tuned using the Osprey Optimization Algorithm (OOA), a recent meta-heuristic algorithm. The model that works with the optimal values of hyperparameters identified by OOA performed better than the other models when they are compared based on evaluation metrics like Mean-Squared Error and R2.

Bengawan Solo River water is a source of drinking water and raw materials for the government of Surakarta city, but the water has been mixed with domestic, industrial, and agricultural wastes. The waste contains estradiol-17 derived from urine and feces, both from livestock and humans as well as industries around the sub-watershed Bengawan Solo River. The content of estradiol-17 in the Bengawan Solo sub-watershed is quite high. This study is the first conducted in Bengawan Solo River to look at natural estrogens that are very rarely studied in the environment, which are likely could cause several health effects in humans and wildlife due to their relatively strong estrogenic potential and high levels in wastewater and river water. Therefore, research on the elimination of these compounds using effective, energy-efficient, and low-maintenance technologies for water treatment such as phytoremediation is highly expected. The purposes of this study were to identify estradiol, to measure the estradiol levels through HPLC tests as well as to test the effectiveness of phytoremediation with Portulaca plant as biological agents. The results show that the water of Bengawan Solo River contained estradiol substances ranging from 3.88 ppm to 5.76 ppm. The Portulaca plant species was effective at eliminating estrogenic waste up to 99.89%.

This research delves into the promising domain of CO2 capture through fine solid activated carbon adsorbent, offering a more energy-efficient alternative to traditional adsorption methods. The central challenge addressed here is the utility of cheaper CO2 adsorbent, fine powder materials whose properties can be precisely tailored via molecular-level fictionalization. Equally vital is selecting an optimal fluidizing column configuration that maximizes CO2 interaction with adsorption particles and enhances adsorption efficiency. The proposed solution is a fluidized bed column uniquely equipped with integrated acoustic vibrations to counteract interparticle forces common in fine powders. For adsorption evaluations, sound-assisted fluidized-bed experimentation on a laboratory size was set up. Adsorbent material activated carbon made up of coal underwent rigorous testing between a range of 20 Hz-200 Hz and 20 dB-135 dB. Results reveal the beneficial effects of acoustic enhancement of fluidization quality and adsorption efficiency, increased adsorption capacity, enhanced bed utilization, and accelerated adsorption rates. Extensive research has been conducted on the detailed effects of major operational variables on adsorption performance, notably frequency, sound intensity, and minimum fluidization velocity. The findings highlight the pivotal role of particle size with mean size 75 microns range as a determinant of adsorption capacity at 100 Hz and 125 dB. At the end of experimentation, the adsorbent considered for the experiment is compared to the study adsorption capacity at operating conditions. The research concludes with a discussion on the effects of influencing parameters for adsorption on employing sound vibrations using fluidization technique adsorption for CO2 capture.

The inhibitory effect of Rosemary oil on the corrosion of aluminum alloy EN AW-2011 in 1M H2SO4 solution was studied by weight loss and electrochemical methods such as open circuit potential (OCP), linear sweep voltammetry (LSV) and linear polarization resistance (LPR). The inhibition efficiency increases with increasing the concentration and shows maximum inhibition efficiency (70.7 %) at optimum concentration (0.05 g.L-1). The linear polarization resistance measurements show that the presence of Rosemary oil in 1M H2SO4 solution influences polarization resistance increasing and corrosion current decreasing. The voltammetric curve shows that Rosemary oil reduces the anodic process. Open circuit potential results confirmed that organic compounds present in Rosemary oil can form a protective layer on aluminum surfaces. The inhibitive effect was probably caused by the adsorption of organic compounds such as 1,8-cineole, α-pinene, borneol, limonene, and myrcene on aluminum surfaces which are non-toxic and environmentally friendly. This study showed that the essential oil of Rosemary could be used as an environmentally friendly inhibitor of the corrosion of alloy EN AW-2011 in an acidic medium.

Composting is an integral component of sustainable Municipal Solid Waste (MSW) management within the circular bio-economy platform. However, it faces challenges due to malodorous emissions that impact environmental and societal equilibrium. The present study aims to minimize odorous emissions and expedite compost maturation using a novel, efficient microbial consortium. Bacteria sourced from open dump sites in Sri Lanka were carefully screened based on concurrent enzyme production. Five developed consortia were tested for their performance in reducing malodors during the composting process of MSW. Consortium No. 5 (C5), comprised of Bacillus haynesii, Bacillus amyloliquefaciens, and Bacillus safensis, demonstrated outstanding performance with a significant (p < 0.05) reduction in odorous emissions. Additionally, consortium C5 exhibited impressive control over gas emissions, maintaining VOC, CH4, NH3, and H2S concentrations within ranges of 0.5-6 ppm, 0.5-0.8 ppm, 0.3-0.5 ppm, and 0.5-0.6 ppm, respectively, compared to control concentrations of 4.5-10.2 ppm, 0.5-5.5 ppm, 0.3-5.5 ppm, and 0.5-6.4 ppm, respectively. Additionally, comprehensive Electronic nose (E-nose) analysis substantiated C5’s efficiency in attenuating Methane-Aliphatic compounds, Sulfur and Aromatic compounds, along with low-polarity aromatic and alkane compounds, all with statistical significance (p < 0.05). Further, the developed consortium could reduce the composting time from 110 ± 10 days to 17 ± 3 days, offering a sustainable solution for global MSW management.

Naturally derived cyanotoxins, cylindrospermopsin (CYN), and microcystin-LR (MC-LR) have shown hepatotoxic and nephrotoxic effects in several studies. The present study aimed to determine the possible nephrotoxicity of MC-LR and CYN on mammalian kidneys using male Wistar rats as an animal model. Potential nephrotoxicity was evaluated at different doses of CYN (0.175 μg.kg-1, 0.140 μg.kg-1, 0.105 μg.kg-1) and MC-LR (0.105 μg.kg-1, 0.070 μg.kg-1, 0.035 μg.kg-1) was observed. Water samples from dug wells contaminated with CYN (0.161 μg.kg-1) and MC-LR (0.091 μg.kg-1) from the Padaviya area in Anuradhapura, Sri Lanka were used as environmental samples. The control groups were treated with distilled water. The exposure time of rats to the toxin was 90 days. Evaluation of urinary creatinine, serum creatinine, and Kidney Injury Molecule-1 (KIM-1) were estimated using standard protocols. A significant increase in serum creatinine levels was observed in all CYN and MC-LR treated groups (p<0.05) after 7 and 42 days of exposure, respectively, compared to control. It was found a decrease of urine creatinine when rats were treated with different concentrations of CYN and MC-LR (p<0.05) after 7 days compared to the control. The highest KIM-1 concentrations were recorded at 0.175 μg.kg-1 of CYN and 0.105 μg.kg-1 of MC-LR. The concentrations of KIM-1 in the control groups for CYN-treated and MC-LR-treated were not detected. Luminal protein, nuclear pyknosis, mild tubular epithelial swelling, vascular congestion, and interstitial inflammation in CYN and MC-LR treated groups were common. No predominant changes were observed in the control groups treated with CYN and MC-LR. The results of the present study confirm that the consumption of CYN and MC-LR-contaminated water may lead to kidney injury in Wistar rats.

Aquatic ecosystems that are subject to urbanization and environmental changes, such as the Kapaleeswarar and Chitrakulam tanks, depend on evaluating water quality. Their complicated data present challenges for conventional approaches. The usefulness of the Mamdani fuzzy inference system in determining the water quality in these tanks is investigated in this work. It creates a comprehensive assessment based on subject-matter expertise by handling ambiguous descriptors with linguistic variables and fuzzy sets. The system’s procedures for implementation are described in detail, with an emphasis on how well they can manage interrelated variables. The study shows how well the system measures the water quality in tanks and suggests ways to improve it. Tank evaluation that incorporates the Mamdani system encourages comprehensive resource management and cultural preservation.

In recent times, nanotechnology has experienced widespread acclaim across diverse sectors, including but not limited to tissue engineering, drug delivery systems, biosensors, and the mitigation and monitoring of environmental pollutants. The unique arrangement of carbon atoms in sp3 configurations within carbon nanomaterials endows them with exceptional physical, mechanical, and chemical characteristics, driving them to the forefront of materials research. Their appeal lies in their efficacy as superior adsorbents and their exceptional thermal resistance, making them versatile in various applications. The present review extensively explores a range of carbon-based nanomaterials, delving into their synthesis methods and examining their multifaceted applications in addressing environmental pollutants. It is crucial to emphasize that the popularity of carbon-based nanomaterials arises from their potential to serve as superior adsorbents, coupled with their outstanding thermal resistance properties. These attributes contribute to their applicability in diverse environmental contexts. Looking ahead, carbon-based nanomaterials are poised to emerge as environmentally friendly and cost-effective materials, representing promising and potential avenues for the advancement of sustainable technology.

This research aims to employ the Autoregressive Distributed Lag (ARDL) method within the insight into the Environmental Kuznets Curve (EKC) to verify whether EKC exists in the Nepalese economy. In this research, variables were used, such as carbon emissions per capita, GDP per capita, energy use per capita, trade volume, and urbanization from 1980 to 2021, and the ARDL method was used. The data has been taken in this research except trade volume from the World Bank and the Ministry of Finance, Nepal. The data sets are converted into the natural logarithmic form to minimize the problem of heteroskedasticity. The findings provide compelling evidence for the existence of the EKC in Nepal, that economic growth has an inverted U-shaped impact on carbon emissions. In the early stages of development, economic growth leads to rising carbon emissions, but in the later stages, economic growth becomes associated with declining emissions. Besides economic growth, per capita energy consumption and urbanization emerge as significant drivers of carbon emissions. However, the trade volume is not found to be the driving factor of carbon emissions. The findings of this study have significant policy implications for global climate change issues and Nepal’s transition from an underdeveloped to a developing nation. To achieve harmonious economic growth and emissions reduction, donor countries and agencies to partner with Nepal in its ambitious endeavors. This partnership can take shape through multifaceted support as fueling socio-economic progress that aligns with Nepal’s commitment to reduce carbon emissions, ensuring that development and sustainability walk together. This research recommends the government of Nepal electrify the transportation landscape by incentivizing the adoption of electric vehicles, paving the way for cleaner air and a healthier planet, empowering Nepal’s natural guardians by strengthening public and private forest programs, safeguarding invaluable ecosystems and biodiversity and curbing the tide of waste mismanagement through strict regulations and robust enforcement, transforming a potential threat into a source of innovation and resourcefulness. These measures, aligned with sustainable employment generation, can pave the way for a brighter and greener future for Nepal.

This study examines the potential use of Hybrid Renewable Energy Systems (consisting of photovoltaic, wind, bio, and diesel sources) both with and without the inclusion of battery storage in the eastern region of India. An evaluation is conducted to determine the economic viability of several system configurations, and the most efficient system is selected using HOMER software. The investigation focused on six distinct scenarios to meet the energy needs of a village community. The goal was to satisfy a daily load need of 1093.7 kWh, with a peak demand of 153.63 kW. The study examined many factors, such as system efficiency, financial viability, and ecological consequences. The primary aim of the research was to compare the power costs associated with different designs of HRES. Detailed techno-commercial assessments were carried out to examine the energy production, consumption, and financial impacts of each scenario. This research provides valuable insights for individuals and organizations seeking reliable and long-lasting energy solutions by analyzing the potential benefits and drawbacks of implementing HRES in rural areas. An evaluation is conducted to determine the energy contribution of each element within an RES, as well as the influence of HRES on energy expenses and net present value. The findings of this study reveal that the optimized hybrid system comprises 133 kW photovoltaic arrays, a 130-kW wind turbine, a 0.2 kW biogas generator, a 100-kW diesel generator, a 540-kWh battery bank with nominal capacity, and a 58-kW converter. This system has a minimum COE of 0.347$/kWh and NPC of $1.71M. The research offers useful insights for designers, scholars, and policymakers on the existing design constraints and policies of biomass-based hybrid systems.