Environmental Quality Management最新文献

The increasing generation of areca leaf waste biomass presents an opportunity for sustainable utilization in paper product manufacturing. This study aims to develop chemical-free paperboard products by converting areca leaf waste through an optimized hydrothermal-mechanical pulping process. The raw biomass was subjected to pulping under varying conditions of time, temperature, and solid-to-liquor ratio. Mechanical strength properties of the resulting paperboards were evaluated using TAPPI standard methods, while modeling and regression analysis were conducted via Minitab software to identify optimal processing parameters. Additionally, a life cycle assessment (LCA) using openLCA software was performed to evaluate the energy consumption and environmental impact of the pulping process. The optimized conditions produced greyboard, strawboard, and stencil backing sheets with tensile indexes of 18.34, 13.06, and 16.75 N/m/g; tear indexes of 7.53, 6.39, and 6.84 mN/m²/g; breaking lengths of 1867, 1332, and 1760 m; and burst indexes of 0.905, 0.56, and 1.00 kPa/m²/g, respectively. These properties conform to Indian Standard specifications (IS 2617:1967 and IS 3302:1965), demonstrating the feasibility of producing high-quality, chemical-free paperboard products without adhesives or additives. The LCA results confirmed that this process significantly reduces energy use and environmental impact compared to conventional methods. This research provides a sustainable approach to valorizing areca leaf waste, with potential applicability for blending with other non-wood pulps in the paper industry.

Perovskite microwave dielectric ceramics have been identified as a class of promising nanomaterials due to their exceptional dielectric, electronic, and optical properties, making them a potential candidate for next-generation sustainable energy applications. The dielectric constant of perovskite microwave dielectric ceramics is a crucial factor in designing supercapacitors, solar cells, and energy-harvesting systems. Hence, accurately predicting the dielectric constant is essential in designing materials for a specific purpose. However, the conventional methods, such as classical theory and density functional theory, used for the prediction of the dielectric constant are time-consuming and expensive. Prediction using machine learning algorithms allows high accuracy, fast screening, and reduced trial and error. This research work focuses on exploring and analyzing the performance of various machine learning algorithms to estimate the dielectric constant of perovskite structures by leveraging material descriptors and structural features. The predictive framework developed in this work can accelerate the design and suitable choice of features of perovskite microwave dielectric ceramics. The computational techniques presented in this study are assessed by performance metrics like root mean squared error, mean squared error, mean absolute error, and coefficient of determination. Experimental results show that both the extreme gradient boosting and random forest algorithms offer superior outcomes compared with other counterparts. The mean squared error of both algorithms is found to be 9%. This research work exhibits the potential of integrating computational material science with data-driven models for advancing nanotechnology solutions in sustainable energy systems and environmental management.

The integration of the artificial intelligence of things (AIoT) in monitoring air pollution is transforming industrial strategy for managing pollutants. It combines artificial intelligence (AI) with IoT to gather real-time data for precise and cost-effective air quality management. Traditional monitoring stations face challenges in dynamic data collection and analysis. Key benefits include real-time monitoring and alerting of air pollutants, while predictive modeling helps forecast pollution trends. AI-powered air sensors, being smaller and portable compared to fixed stations, are easier to deploy. Through AIoT integration, communities and governments can implement data-driven regulations and controls to reduce pollution exposure and identify emission hotspots. However, ensuring sensor accuracy remains challenging, requiring ongoing calibration and AI model training. Further work is needed to meet regulatory standards and integrate with existing infrastructure. The AIoT promotes sustainable development, regulatory compliance, and improved health outcomes. This chapter explores AIoT's role in real-time air pollution monitoring using AI technologies and addresses how it enhances regulatory compliance through emissions monitoring and anomaly detection, along with ethical considerations and future perspectives.

Constructed wetlands (CWs) offer a low-cost, sustainable alternative to conventional wastewater treatment technologies, particularly in developing countries. This review synthesizes current research on the application of CWs for wastewater and fecal sludge treatment in Cameroon, highlighting progress, limitations, and future research priorities. Findings indicate that most CW initiatives in Cameroon remain experimental or pilot-scale, with limited full-scale implementation. Various macrophytes have been tested for pollutant removal, among which Echinochloa pyramidalis has shown superior adaptability to wastewater environments and potential for biomass reuse. However, efforts to optimize substrate composition, hydraulic design, and configuration remain limited. Major barriers to large-scale adoption include the absence of standardized design criteria, inadequate institutional and legal frameworks, financial and infrastructural constraints, poor maintenance practices, and insufficient long-term data collection. Despite these challenges, CWs demonstrate strong potential for improving decentralized sanitation and fecal sludge management. Future research should prioritize performance optimization under local climatic conditions, the use of locally available materials, and microbial and plant–substrate interactions to guide the development of context-specific, scalable CW solutions for sustainable sanitation in Cameroon.

Globally, the ever-rising energy demand has altered the techniques for producing oil, especially in the upstream processing, such as horizontal hydraulic fracturing and targeted drilling. Drilling deep oil and gas wells necessitates specialized drilling fluid formulations to ensure safe and efficient operations, as the conventional drilling fluids, such as the water-based drilling fluids (WBDF), can cause shale swelling, and the oil-based drilling fluids (OBDF) can cause other environmental concerns because of the presence of aromatic compounds. Synthetic-based drilling fluids (SBDF) address these issues by combining superior performance with reduced environmental impact. Esters have shown the highest biodegradability and good performance as compared to other synthetic bases in drilling fluids. The present review article highlights the potential advantages of ester-based drilling fluid (EBDF) under high-pressure and high-temperature (HPHT) environments. Moreover, the review articles show the advancement in the ester synthesis by using different carboxylic acids and oil feedstocks and provide beneficial insights on the recent advances in EBDF formulations. Furthermore, the review demonstrates EBDF cost efficiency over OBDF by comparison of formulation and disposal cost. This review also comprehends the studies that examined the utilization of various nanoparticles as a Pickering emulsion stabilizer in OBDF and SBDF formulations to enhance their properties and emulsion stabilities. Lastly, the review has proposed a futuristic formulation of drilling fluids via incorporating the nanoparticles that can improve the thermal stability of EBDF.

Soil amendments and fertilizer products developed from municipal or agricultural waste streams, such as biosolids or livestock manure, are crucial to foster circular nutrient economies and reduce agricultural production costs, as well as to mitigate environmental impacts compared to traditional inorganic fertilizers. However, innovative technologies are required to develop municipal wastewater solids-based fertilizers that are safe and effective for environmental application while reducing production costs and energy consumption compared to current technologies. A greenhouse pot experiment was conducted to assess the effects of novel municipal wastewater solids-based products in the early stages of technological development at bench scale on plant growth and soil properties. Electrochemically-treated waste activated sludge (EWAS), untreated waste activated sludge (WAS), a commercially available fertilizer produced from municipal wastewater solids (Milorganite), or a commercially available inorganic fertilizer (Greenview) was applied to pots containing wheat (Triticum aestivum) grown in field-collected agricultural soil. Soil pH was higher with EWAS and Milorganite at the end of the 80-day growth period, while Greenview-treated soil had higher EC. Extractable soil P was 30% higher, while exchangeable soil Na was twice as high with EWAS as in unamended control soils. Wheat biomass was also significantly greater with EWAS compared to unamended controls and was comparable to the commercial fertilizers. This study demonstrates the potential efficacy of electrochemically-treated wastewater solids as an amendment in field-collected soil and highlights the need for further technological development of novel electrochemical processes designed to extract excess nutrients and deactivate pathogens in wastewater solids to create economically viable products while consuming less energy than conventional treatment methods.

The utilization of biomass as a value-added material has gained widespread attention due to the abundance of agricultural waste that remains underutilized. This waste is readily available at an affordable or no cost, yet when left unaddressed, it can contribute to environmental issues, such as the release of methane gas, which pollutes the air and poses risks to human health. The direct burning of agricultural waste further intensifies these problems. Along with a large amount of agricultural waste, critical land problems also arise due to the excessive use of inorganic fertilizers. This study addresses the issues by synthesizing biochar from agricultural waste (rice husks, sawdust, and bagasse) using the hydrothermal method at 180°C with NaOH as a solvent to enhance functional groups and increase adsorption capacity to be applied as a soil remediation agent. Biochar characterization was performed using Fourier Transform Infrared Spectroscopy (FTIR), Brunauer–Emmett–Teller (BET), Barrett–Joyner–Halenda (BJH) methods, and carbon, hydrogen, nitrogen, sulfur (CHNS), and total plate count (TPC) analysis. The result shows, based on the functional group of the biochar of rice husks treated at different NaOH concentrations, the best results were obtained with a 5 M concentration, that applied for the synthesis condition for sawdust and bagasse-based biochar. A large number of functional groups were exhibited by rice husk-based biochar, yet they have the smallest surface area. The large number of functional groups, however, supports the ability of biochar in soil remediation. Proven by rice husk-derived biochar demonstrated excellent performance, promoting leaf growth by 25%, root growth by 31%, and overall plant growth by 41%. Moreover, microorganisms observed in the soil after plantation increased tenfold with the addition of biochar compared to soil without biochar, highlighting the excellent potential of biochar in soil remediation.

Hydrodynamic cavitation (HC) was applied both alone and in combination with various oxidants namely, hydrogen peroxide, Fenton reagent, Advanced Fenton reagent, and sodium hypochlorite for the degradation of ofloxacin, a persistent antibiotic, which has serious environmental concerns. The study examined the effect of operational factors like solution pH and inlet pressure on HC efficiency, demonstrating that optimum conditions of pH 3 and 4 bar as inlet pressure resulted in achieving 74.93% as optimal ofloxacin degradation using only HC without any additives. Combining HC with oxidants showed synergistic effects, resulting in 92.7% degradation with hydrogen peroxide, 89.7% with sodium hypochlorite, 94.26% with Fenton, and 95.18% with advanced Fenton process under optimized conditions. Acoustic cavitation (AC) alone achieved 21.85% degradation, while coupling it with sodium hypochlorite, hydrogen peroxide, Fenton, and Advanced Fenton led to 40.22%, 46.96%, 52.49%, and 56.37% degradation respectively, at dual frequency operation and power of 240 W. Maximum kinetic rate constant as $��9.44�\times �{10}^{�-�2�}�$ $��\mathrm{mi}�n^{�-�1�}�$ was seen for $��\mathrm{HC}�+��\mathrm{Advanced}��\mathrm{Fenton}��$ coupled with superior cavitational yield and treatment costs. Two bacterial strains subjected to toxicity assessments using both treated and untreated wastewater confirmed no formation of any toxic intermediates. Combining HC and oxidants have been shown as a promising approach for efficiently treating ofloxacin-contaminated wastewater, providing potential solutions to the increasing issue of antibiotic pollution in water.

This study evaluates the heavy metal concentrations in the sediments from the Korle Lagoon dumpsite and their potential leaching into the environment. The sediments were analyzed for total heavy metal concentrations using USEPA Method 3050B, with results showing the following ranges: 19.715–44.471 mg/kg for Cu, 0.098–0.398 mg/kg for Cd, 2.891–4.385 mg/kg for As, 26.00–45.176 mg/kg for Cr, 6.656–9.072 mg/kg for Ni, 33.932–60.029 mg/kg for Pb, 0.092–0.172 mg/kg for Hg, 111.9–214.88 mg/kg for Zn, and 12,884–19,192 mg/kg for Fe. Leachates from the sediments were analyzed using the Toxicity Characteristic Leaching Procedure (TCLP) according to USEPA Method 1311. The metal concentrations in the leachate ranged from 0.002 to 0.005 mg/L for As, ND to 0.01 mg/L for Cd, 0.012 to 0.044 mg/L for Cu, 0.012 to 0.031 mg/L for Cr, 0.039 to 0.114 mg/L for Ni, 0.971 to 1.639 mg/L for Fe, ND to 0.001 mg/L for Hg, and 0.104 to 3.250 mg/L for Zn, with all leachate concentrations below the recommended guideline limits. The cumulative progressive TCLP results also showed metal concentrations below the guideline levels, suggesting that the leachate does not pose an immediate environmental risk. However, the study notes that while the current levels are within safe limits, significant leaching could occur if the pH of the medium decreases, potentially leading to environmental impacts over time. This research provides valuable insights into the current stability of the Korle Lagoon dumpsite sediments and establishes a baseline for future studies on long-term environmental risks. The findings underscore the need for continued monitoring of pH changes and metal leaching to predict future environmental impacts.