Sewage sludge management is a critical challenge requiring sustainable treatment solutions. Drying is an essential pre-treatment step for utilizing sludge in waste-to-energy systems. Although drying is an essential step in sludge management, it has often been represented in a simplified manner using general assumptions in life cycle assessment (LCA) studies aimed at evaluating environmental impacts and greenhouse gas emissions. In many assessments, sludge drying has been identified as the most environmentally burdensome stage of sludge management due to its high energy demand, with solar drying frequently proposed as a low-energy alternative. Given these findings, optimizing the environmental performance of the sludge drying process is crucial for reducing the overall life cycle impacts of sludge management. Accordingly, this study aims to compare the environmental impacts of thermal drying technologies (belt, fluidized bed, and rotary) and solar drying using a gate-to-gate LCA approach. Additionally, impact reduction scenarios were assessed, including renewable energy integration and adjusting the final solids content of sludge. The LCA was performed using the ReCiPe 2016 Endpoint (H) method. Results indicate that using photovoltaic electricity and waste-incineration steam can significantly lower the environmental impacts of belt and rotary dryers, making them comparable to solar drying. On the other hand, solar drying's high land demand remains a major limitation. These findings provide key insights for decision-makers, helping optimize sludge drying processes with lower environmental impacts. The study highlights the importance of technology-specific strategies and renewable energy integration in wastewater treatment plants.
Traditional hydrometallurgical recycling methods present challenges including complex processes, significant metal loss, and high costs. To address these issues, this work introduces a facile and efficient recycling method for spent ternary cathode materials, which combines acid leaching and oxidation as well as ammonia leaching. Firstly, careful control of the phosphoric acid concentration and sodium persulfate dosage allows for the selective leaching of Li and Ni in the process of acid leaching and oxidation, and thus their leaching efficiencies can reach as high as 99.3 % and 97.2 % respectively. Meanwhile, Co and Mn can be separated in the form of Co3O4 and MnO2 remaining in the waste residues. Secondly, based on the stability difference of complexes formed by cobalt and manganese with ammonia, Co can be selectively leached from waste residue through ammonia leaching, with the leaching efficiency reaching 93.2 %, while Mn is separated via reacting with CO32- in the solution to form MnCO3. Moreover, the mechanisms of selectively leaching Li and Ni during acid leaching and oxidation processes are revealed using characterization techniques such as XRD, ICP, SEM-EDS, and thermodynamic analysis. Finally, economic analysis shows that the benefits of this approach in terms of battery reuse are considerable, and there are clear advantages in terms of process simplification and operational safety. Compared to traditional hydrometallurgical recovery methods, which typically involve sequential separation after metal leaching, the proposed method achieves simultaneous leaching and separation of metals, thereby simplifying the recovery process and reducing metal losses.
ABSTRACT The accurate estimation of methane generation in landfills is crucial for effective greenhouse gas management and energy recovery, requiring site-specific assessments due to the inherent variability in waste composition and properties before and after disposal. This study investigates the uncertainties associated with methane generation predictions by employing a combination of stoichiometric methods, Biochemical Methane Potential (BMP) assays, and Bayesian inference. Fresh and aged (1-year-old and 5-year-old) samples collected in the tropical Saravan dump site in Gilan, Iran, were used to evaluate the waste’s methane generation potential and degradation rate in the field. The average methane generation potential (L0) for fresh samples by the stoichiometric simplified method was 83.4 m3 CH4/Mg MSW, which decreased to 44.8 m3 CH4/Mg MSW and 32.8 m3 CH4/Mg MSW for 1-year-old and 5-year-old waste samples, respectively. The BMP tests led to similar results, further validating the decreasing trend of L0 with waste age. The Bayesian approach combined with MCMC simulations revealed that uncertainty in methane estimation is highest in the early years and gradually declines as waste stabilizes, improving long-term prediction accuracy. By integrating sensitivity analysis with Bayesian inference, this study advances uncertainty quantification approaches, addressing limitations in existing landfill methane estimation models. This innovative framework identifies the most influential parameters, providing a robust foundation for refining predictive models. The decay rate constant (k) was determined to be 0.26 year−1, aligned with the guidelines for humid areas. Notably, the highest standard deviation in methane estimation was observed during the initial post-disposal years, reaching 1,384,751.5 m3 CH4/year using the BMP method and 2,266,762 m3 CH4/year with the simplified method, highlighting how early-stage variability impacts overall methane predictions, emphasizing the critical need for site-specific data. These insights contribute to improved landfill gas management strategies and support decision-making for sustainable waste management practices. Implications: This research underscores the importance of integrating methodologies like stoichiometric analysis, BMP assays, and Bayesian inference to enhance methane generation estimates from landfills. A significant outcome is the recognition of the inherent uncertainty in key parameters, particularly ultimate methane potential and decay rate constant. By employing Bayesian inference and Monte Carlo simulation, we quantified the uncertainty associated with these parameters and analyzed its influence on methane production predictions. The findings reveal that different methodologies yield varying levels of uncertainty, highlighting the necessity for a comprehensive framework that utilizes site-specific data. This approach not only improves the reliability of methane estimates but also informs greenhouse gas management strategies, fostering more effective decision-making in waste management practices.
This paper presents a numerical simulation and structural optimization study of the combustion process within the grate and boiler furnace of a 750 t/d waste incineration. The study focuses on adjusting the secondary air velocity, secondary air inclination angle, and the arrangement of secondary air nozzles. These adjustments aim to optimize parameters such as the temperature field, pollutant emission, flow field, particle residence time, and filling degree. The findings demonstrate that high-temperature zones, which lead to slagging problems, are likely to form beneath the front arch. The combustibles inside the furnace are thoroughly burnt, reflecting efficient combustion. The concentration of NOx in the flue gas at the furnace outlet generally ranges between 170 and 200 ppm. Optimal operating conditions are identified as a secondary air inclination angle of 20° with an air velocity of 55 m/s, and an angle of 30° with an air velocity of 55 m/s and 65 m/s, in conjunction with a relative arrangement of the nozzles. Under these conditions, the incineration furnace achieves its best operational state.
The environmental pressure caused by textile waste is forcing the industry to explore sustainable innovation avenues. This study focuses on the collaborative application of recyclable design and upcycling strategies, exploring the construction of a circular economy model centered on material regeneration and creative use. By adopting a unique material composition, modular component design, and simplifying the fiber blending process, the recyclable design strategy significantly improved the decomposability and recycling efficiency of textiles. The practice of simultaneous upcycling transformed post-consumer and industrial textile waste into high-value-added products. Experimental data show that the fiber recovery rate increased by 27%, and energy consumption decreased by 28% compared to traditional processes. Consumer studies show that market acceptance of creatively remade products is significantly higher than that of conventional products. The research simultaneously revealed practical bottlenecks such as material compatibility and economic feasibility, and proposed targeted solutions such as standardized identification systems and automated disassembly processes. These findings provide an operational framework for balancing ecological benefits and commercial value, and offer practical references for designers, manufacturers, and policymakers to promote the ecological transformation of the textile industry.
With the rapid development of fiber/matrix-based composites in the wind and aerospace industries, minimizing the environmental impact of composite waste has become a critical concern. This study compares pyrolysis and chemical recycling using nitric acid with the microwave assisted chemical recycling (MACR) process for carbon fiber reinforced polymer (CFRP) composite waste. The Life Cycle Assessment (LCA) tool in OpenLCA2.1® software evaluated three recycling scenarios, assuming recovered carbon fibers (RCFs) could be used for new composites. An inventory model was developed for virgin carbon fiber (VCF) production, CFRP manufacturing, and the three recycling processes, with environmental indicators identifying key variables. The results show that the MACR process has the lowest global warming potential (0.64 kg CO2 eq.) and ozone depletion potential (0.46 × 10−8 kg CFC-11 eq.) compared to other methods. VCF production is energy-intensive, but if RCFs exhibit similar mechanical properties, they could replace VCFs in new composites. The MACR process also demonstrated higher Recycling System Credits (RSC), lower environmental impacts, and reduced energy consumption. Through comprehensive analysis of the results obtained in this study, the MACR process demonstrates significant benefits by reducing VCFs production burdens and pollution emissions, making it a promising solution for managing composite waste.
Jawad Ali Hasan Shoqeir, Eman Omar Murshed Mansour
Municipal solid waste (MSW) landfills are a significant source of greenhouse gas emissions. Biogas is formed under anaerobic conditions by the decomposition of organic matter contained in the waste. Estimating biogas production, which largely depends on the type of waste deposited in the landfill, is essential for designing the gas collection system and assessing potential energy production. This study aims to demonstrate the added value of municipal waste in generating sustainable energy in Palestine, resulting from CH4 emissions from local landfills. The electricity generation of a waste-to-energy (WTE) plant was studied based on mathematical modelling. With the application of the First Order Decay (FOD) model as recommended by the Intergovernmental Panel on Climate Change (IPCC), Palestine’s MSW landfills’ methane emissions were estimated to be approximately 158.1 kg of CH4 per ton of household garbage, equivalent to approximately 251.2 million kilograms of methane annually. Applying an assumed rate of electricity generation per ton of MSW of 0.08 MWh, the estimated electricity generated from landfill gas was 127,200 MWh per year, corresponding to a reduction of approximately 69,960 tons of CO2 equivalent per year. A case study of Al-Minya landfill also highlighted the indigenous capacity for electricity generation and emission reduction, demonstrating the feasibility of WTE initiatives as a viable climate change mitigation policy for Palestine. In this article, the electricity generation and equivalent CO2 emission reduction of WTE plants using biogas from municipal landfills in both Palestine and Egypt were critically evaluated. It was found that the reduction equivalent of GHG emissions from the municipal landfills is 20.5 % in Palestine and 8.4 % in Egypt, which is a good indicator of the environmental feasibility of biogas plants to generate electricity from waste.
With the growing use of electrical and electronic devices, the volume of waste electrical and electronic equipment (WEEE) continues to increase, posing a major environmental and recycling challenge. Acrylonitrile-butadiene-styrene (ABS) is one of the most common thermoplastics found in WEEE, its recovery is complicated by contamination, heterogeneity, and degradation. While mechanical recycling of ABS is widely practiced, the impact of specific processing steps on the chemical and physical properties of the recyclate remains insufficiently explored. This study investigates the effect of shredding and extrusion, as well as the integration of virgin polybutadiene rubber (PBR), on the morphology, chemical structure, and thermal stability of ABS-rich WEEE recyclates. A multi-analytical approach, combining Fourier transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDX), inductively coupled plasma optical emission spectroscopy (ICP-OES) and thermal analysis − was employed to fully characterize the materials. Our findings show that extrusion improves sample homogeneity and removes some contaminants (e.g., Ba, Cl), leading to a significant increase in thermal stability (T10% +30 °C). The addition of virgin PBR contributes to enhanced internal cohesion and a fibrous morphology. This work provides a robust methodology for distinguishing processing-related changes from compositional variability in real-world recycled plastics. The approach can support the development of advanced processing strategies for polymer waste streams.
Despite global recognition of the climate crisis, greenhouse gas emissions are projected to rise by 8.8 % by 2030, primarily due to inadequate planning, poor implementation, and insufficient financial support. While international initiatives such as the ’Waste to Zero’ coalition launched at the 28th Conference of the Parties to the UNFCCC (COP 28) highlight the urgency of advancing decarbonization and the circularity of waste systems, this review focuses on how artificial intelligence (AI) can accelerate that transformation. It systematically explores the role of AI in advancing waste management practices, with a focus on predictive analytics, route optimization, and machine learning-based material classification. Beyond summarizing existing approaches, it proposes a multilayer framework that connects data sensing, planning, sorting, and treatment within an adaptive lifecycle perspective. The review further examines existing gaps related to policy support, infrastructure readiness, data standardization, and scalability. While numerous studies demonstrate the potential of AI to improve operational efficiency and material recovery, real-world implementation remains limited by economic, regulatory, and technological barriers. To address these limitations, a strategic roadmap is presented, integrating technical innovation with governance and investment pathways to enhance implementation potential. By consolidating these insights, the study offers a comprehensive synthesis that clarifies how AI can strengthen circularity across the waste lifecycle and guide the sector toward scalable, evidence-based sustainability transitions.
Md. Abu Musa, Abdullah-Al-Mamun, Sonia Nasrin
et al.
Rapid industrialization in southwestern Bangladesh has led to significant accumulation of heavy metals (HMs) in riverine ecosystem. However, the extent of HMs accumulation in the Bhairab River and its potential risk still remain unknown. The current study quantified HMs in water, sediment, and different fish species of Bhairab River to evaluate the ecological and human health risk. Water, sediment, and fish samples were collected during two seasons (monsoon and winter) from three locations and measured for HMs (Pb, Cd, Cr, Fe, Mn, Zn) using flame atomic absorption spectrophotometer (F-AAS, Model: Shimadzu AA-7000, Japan). HMs in water and sediment were found in the order of Cd < Pb < Cr < Zn < Mn < Fe. The Fe, Mn, and Zn exceeded the threshold limit for drinking standard as per WHO (2004) and USEPA (1999). The contamination factor and geo-accumulation index were < 1, indicating that river bank sediment is suitable for crop cultivation during winter. HMs in water, sediment, and fish were lower during the monsoon compared to winter, due to dilution effects. According to WHO (2004), FAO (1983), and MOFL (2014), HMs in fish did not exceed the tolerable limit except for Cr. According to WHO (2004) guidlines, the daily intake of HMs was less than reference dose. For non-carcinogenic risk, THQ and HI < 1, indicating no potential health risk for Khulna urban inhabitants due to consumption of the studied fish. Cr posed a potential carcinogenic risk from lifelong consumption of these fish. These findings may support national policy-making and riverine ecosystem management in achieving the Sustainable Development Goals (SDGs).
Juan Antonio Ramírez-Pérez, Felipe Jesús González Barrionuevo, Manuel Jesús Gázquez-González
et al.
The Iberian Pyrite Belt (IPB), located in the SW of Iberian Peninsula, hosts the largest massive sulfide deposit globally, and over two centuries of intensive mining activity have generated huge amounts of abandoned mining waste along this region. Due to the limited information on the volume of the mining tailings, the main objective of this study has been to develop a volumetric inventory of these wastes by using Unmanned Aerial Vehicles (UAVs). For this purpose, Digital Elevation Models (DEM) and Triangular Irregular Networks (TIN) were developed, finding that the estimated waste reserves were 23.3 Mt (1.77∙107 m3) for the selected mining areas. The concentrations of both major and trace elements, and natural radionuclides were determined. Total reserves of Fe (2.12 Mt in Almagrera, Sotiel Coronada), and other metals/metalloids were calculated; highlighting 0.05 Mt for Zn in Riotinto, 0.06 Mt for Pb in Sotiel Coronada and 989 t for Rare Earth Elements in total. Nevertheless, natural radionuclide levels are similar to those found for unperturbed soils (25 Bq kg−1 of 238U, 21 Bq kg−1 of 232Th, and 224 Bq kg−1 for 40K). As potential applications for these mining stockpiles, techniques of Fe, Zn, Pb and REE recovery and uses as building materials are proposed for their valorization and to promote the circular economy.
This short video explores the potential story of slow hope by looking into how Cainiao, a global delivery company, runs its packaging recycling programme at a pick-up station in Shenzhen, China. Online shopping and efficient delivery logistics have redefined consumption habits and urban landscapes in contemporary China. In 2024, the number of packages moving around the country reached 100 billion, according to statistics from the National Post Office. During the Double Eleven Shopping Festival in November 2024 alone, the number of packages spiked to 700 million. Seeing the mountains of packaging waste produced on a daily basis, the Chinese delivery company Cainiao started a recycling programme called Green Box in 2016. To date, the award-winning Green Box programme has covered over 100,000 pick up stations in 315 cities in China. While many celebrate the company’s environmental and social governance – potentially a story of slow hope for positive environmental change (Mauch 2019), the programme’s operation specifics remain obscure. In this video, Duan Jiaqi, Qin Xiaoyi and Lu Ziyu show more perspectives from one of the pick-up points in Shenzhen. They found that the corporate responsibility programme has continued to rely on the informal network of urban waste collection by rural migrants, and its implementation is limited by various factors.
Municipal refuse. Solid wastes, Standardization. Simplification. Waste
Marco Vizuete-Montero, Maritza Chaglla-Cango, Jenevith Cuadrado-Andrade
et al.
The emission of mercaptans during the decomposition of organic solid waste represents a significant environmental issue due to their strong odor and potential toxicity. This study aimed to explore the effectiveness of High-Density Polyethylene (HDPE) geomembrane in reducing odors produced ny mercaptans during the anaerobic decomposition of organic solid waste. The research was conducted under controlled conditions using a simulated landfill cell and employed standardrized metholologies for gas sampling and analysis. Organic waste representative of municipal solid waste composition in tropical regions was used and concentrations of methyl mercaptan and tert-butyl mercaptan were measured before and after geomembrane application using a calibrated multigas detector. Results showed a significant reduction in mercaptan levels following the implmentation of HDPE geomembrane, with concentrations decreasing from a combined 4.377 ppm to 0.696 ppm, well below established occupational exposure thresholds. Statistical analysis confirmed the reliability and significance of the results (p < 0.001). The study suggest the potential of HDPE geomembranes as an accesible and replicable solution for odor-management in solid waste treatment, particularly in resource-limited context.
Julius Nnamdi Ndive, Simeon Okechukwu Eze, Somtochukwu Godfrey Nnabuife
et al.
Textile wastewater, particularly azo dyes, poses significant environmental challenges due to its poor biodegradability and toxicity. This study explores a dual-chamber microbial fuel cell (MFC) for simultaneous wastewater treatment and electricity generation. The MFC consists of an anaerobic anode chamber and an aerobic cathode chamber, separated by a proton exchange membrane (PEM). Electroactive microorganisms in the anode chamber metabolize organic substrates, including azo dye contaminants, breaking them down into simpler by-products. Electrons released during this process flow through an external circuit to generate current, while protons migrate across the PEM to the cathode chamber for oxygen reduction. Electrochemically active microbes were isolated from azo-dye-contaminated soil, and their degradation abilities validated through assays. Optimized carbon-based electrodes and a Nafion 117 PEM were used to enhance conductivity and microbial activity. UV–Vis spectroscopy tracked dye degradation, with the absorbance peak of reactive yellow dye at 410 nm decreasing from 2.9 to 0.4, indicating effective azo-bond cleavage. The MFC achieved peak voltage and current outputs of 0.20 mV and 0.16 mA, respectively, demonstrating its dual functionality. Adding NaCl as a supporting electrolyte further improved ionic conductivity and performance. This study demonstrates MFC technology as a sustainable solution for industrial wastewater challenges, integrating microbial degradation with bioelectricity generation. Future work should address scalability, operational stability, and advanced electrode designs to enhance its practical applications.
Large quantities of used rubber material, mostly from vehicle scrap tires and tube rubbers, are discarded every year, causing environmental problems of great concern and representing a tough challenge for waste management bodies around the world. Various ways to remediate the issues have been proposed and applied from time to time. Pyrolysis offers a promising solution to convert waste tires into potential fuels and chemicals. Thermo-catalytic pyrolysis is a well-established process that aims for material, energy or chemical product recovery. The demand and need for the use of materials like scrap tubes and rubbers for producing useful products is a valuable consideration for this kind of waste that in turn may minimize the dependency on natural resources. Inner tube rubber, which is mainly made of isobutylene-isoprene, poses a hazard to the environment. However, there is also an opportunity to turn this waste product into a valuable energy source. In the current study optimization of parameters such as temperature, time and catalyst weight for catalytic pyrolysis of isobutylene-isoprene rubber into liquid fuel in the presence of Silicon Dioxide (SiO2) as catalyst is reported. A maximum rubber conversion into oils was obtained at optimized conditions of 350 °C temperature, 1.5 g of catalyst (SiO2) for an hour heating time. The obtained pyrolyzed products were subjected to several physical and chemical tests. Reported results confirm the presence of 30 % of aliphatic hydrocarbons, 25 % polar hydrocarbons and 40 % aromatic hydrocarbons. The distillation data indicates that oil obtained is a mixture of aromatic and olefinic hydrocarbons as that of diesel and may be used as an alternative fuel.
Parichat Suknark, Sompote Youwaib, Tipok Kitkobsin
et al.
Accurate prediction of shear strength parameters in Municipal Solid Waste (MSW) remains a critical challenge in geotechnical engineering due to the heterogeneous nature of waste materials and their temporal evolution through degradation processes. This paper presents a novel explainable artificial intelligence (XAI) framework for evaluating cohesion and friction angle across diverse MSW compositional profiles. The proposed model integrates a multi-layer perceptron architecture with SHAP (SHapley Additive exPlanations) analysis to provide transparent insights into how specific waste components influence strength characteristics. Training data encompassed large-scale direct shear tests across various waste compositions and degradation states. The model demonstrated superior predictive accuracy compared to traditional gradient boosting methods, achieving mean absolute percentage errors of 7.42% and 14.96% for friction angle and cohesion predictions, respectively. Through SHAP analysis, the study revealed that fibrous materials and particle size distribution were primary drivers of shear strength variation, with food waste and plastics showing significant but non-linear effects. The model's explainability component successfully quantified these relationships, enabling evidence-based recommendations for waste management practices. This research bridges the gap between advanced machine learning and geotechnical engineering practice, offering a reliable tool for rapid assessment of MSW mechanical properties while maintaining interpretability for engineering decision-making.