Comprehensive competitiveness assessment of four typical municipal sludge treatment routes in China based on environmental and techno-economic analysis

An analytic hierarchy process combined with artificial neural network model to evaluate sustainable sludge treatment scenarios

Sludge management in China faces critical environmental, economic, and technical challenges, necessitating urgent optimal management strategy selection. Given the limited number of comprehensive studies on sludge management, quantitative decision-making tools are urgently required. To address this gap, this study developed an integrated Analytic Hierarchy Process (AHP)-artificial neural network (ANN) model to evaluate sludge treatment scenarios. Four representative scenarios were evaluated based on carbon emissions, environmental impact, and economic costs. A hierarchical evaluation model based on the AHP was established for sludge treatment processes. Weight indicators were derived through expert questionnaire surveys and combined with empirical data to determine the comprehensive weights. The bootstrap method was applied to expand the sample size and ensure robust training of the ANN model. The ANN framework establishes mapping relationships between evaluation indicators and expected values. The AHP-ANN evaluation model demonstrated high predictive accuracy, achieving a maximum mean squared error (MSE) of 0.00052 in the test dataset. This model enabled the rapid assessment of parameter adjustments on evaluation outcomes and provided a quantitative basis for engineering optimization. Among the evaluated scenarios, the anaerobic digestion scenario (S1) demonstrated the best overall performance, characterized by low environmental impact and operational costs. Conversely, the incineration scenario (S3) exhibited the poorest overall performance, with high resource consumption, resulting in significant environmental impact and elevated operational costs.

Parameter-sensitive life cycle assessment of sludge incineration technologies integrating energy balance model

Incineration is vital for safe sewage sludge treatment and resource recovery in China, using methods like mono-incineration (INC), and co-incineration in coal plant (CINP), cement kiln (CINC), and municipal solid waste incineration plant (CINM). Existing studies suffer from poor inventory quality and inaccurate quantification. To overcome these challenges, this study integrates the energy balance model with life cycle assessment to evaluate key system parameters, quantify co-incineration disturbances, and assess environmental impacts. Findings indicate critical moisture content for combustion as 70 %, 60 %, 50 %, and 80 % for the four methods, respectively, with INC exhibiting the highest environmental impact, followed by CINM. CINP and CINC yield environmental benefits by replacing coal or raw materials, achieving negative carbon effects of 34.8 % and 78.8 %, and avoiding 66.4 % and 76.1 % of environmental impacts, respectively. When sludge moisture surpasses 75 %, co-incineration results in higher carbon emissions than INC, with lower dry calorific values potentially increasing emissions up to fourfold. The study positions CINP and CINC as transitional solutions, with CINM as the future trend, while INC suits cities with high sludge output and strong economies. This research offers a basis for developing inventories for solid waste co-incineration in industrial kilns and optimizing the selection of sludge incineration technologies.

Life cycle assessment of sewage sludge treatment and disposal technologies based on carbon emissions and environmental impacts

This study aimed to create a comprehensive evaluation method for sewage sludge (SS) treatment and disposal technologies, considering carbon emission and environmental impacts. Life cycle assessment (LCA) were conducted on six SS treatment and disposal technologies in China. The assessments used the IPCC emission factor approach to calculate carbon emissions and the CML2001 method to determine environmental impact factors. Additionally, a colour-coded method was implemented to quantify the evaluation results. The study found that S1 (anaerobic digestion + land application) had the lowest carbon emissions and environmental impact, making it the optimal technology. The S1 scenario had carbon emissions of 669 kg CO2(t DS)-1 and environmental impacts of 5.20E-10. A sensitivity analysis was conducted to show the impacts of each unit in the six technologies on total carbon emissions and environmental impacts. The results showed that landfilling has a high sensitivity to carbon emissions and environmental impacts. Therefore, controlling greenhouse gases and toxic substances in sludge landfills is crucial for reducing carbon emissions and environmental pollution.

Insights into the Synergistic Effect and Inhibition Mechanism of Composite Conditioner on Sulfur-Containing Gases during Sewage Sludge Pyrolysis

Sewage sludge odorous gas release is a key barrier to resource utilization, and conditioners can mitigate the release of sulfur-containing gases. The gas release characteristics and sulfur compound distribution in pyrolysis products under both single and composite conditioning strategies of CaO, Fe2O3, and FeCl3 were investigated. This study focused on the inhibition mechanisms of these conditioners on sulfur-containing gas emissions and compared the theoretical and experimental sulfur content in the products to evaluate the potential synergistic effects of the composite conditioners. The findings indicated that at 650 °C, CaO, Fe2O3, and FeCl3 inhibited H2S release by 35.8%, 23.2%, and 9.1%, respectively. Notably, the composite of CaO with FeCl3 at temperatures ranging from 350 to 450 °C and the combination of Fe2O3 with FeCl3 at 650 °C were found to exert synergistic suppression on H2S emissions. The strongly alkaline CaO inhibited the metathesis reaction between HCl, a decomposition product of FeCl3, and the sulfur-containing compounds within the sewage sludge, thereby exerting a synergistic suppression on the emission of H2S. Conversely, at temperatures exceeding 550 °C, the formation of Ca-Fe compounds, such as FeCa2O4, appeared to diminish the sulfur-fixing capacity of the conditioners, resulting in increased H2S emissions. For instance, the combination of CaO and FeCl3 at 450 °C was found to synergistically reduce H2S emissions by 56.3%, while the combination of CaO and Fe2O3 at 650 °C synergistically enhances the release of H2S by 23.6%. The insights gained from this study are instrumental in optimizing the pyrolysis of sewage sludge, aiming to minimize its environmental footprint and enhance the efficiency of resource recovery.

A Novel Sustainable and Self-Sufficient Biotechnological Strategy for Directly Transforming Sewage Sludge into High-Value Liquid Biochemicals

Sewage sludge, as a carbon-rich byproduct of wastewater treatment, holds significant untapped potential as a renewable resource. Upcycling this troublesome waste stream represents great promise in addressing global escalating energy demands through its wide practice of biochemical recovery concurrently. Here, we propose a biotechnological concept to gain value-added liquid bioproducts from sewage sludge in a self-sufficient manner by directly transforming sludge into medium-chain fatty acids (MCFAs). Our findings suggest that yeast, a cheap and readily available commercial powder, would involve ethanol-type fermentation in chain elongation to achieve abundant MCFA production from sewage sludge using electron donors (i.e., ethanol) and acceptors (i.e., short-chain fatty acids) produced in situ. The enhanced abundance and transcriptional activity of genes related to key enzymes, such as butyryl-CoA dehydrogenase and alcohol dehydrogenase, affirm the robust capacity for the self-sustained production of MCFAs. This is indicative of an effective metabolic network established between yeast and anaerobic microorganisms within this innovative sludge fermentation framework. Furthermore, life cycle assessment and techno-economic analysis evidence the sustainability and economic competitiveness of this biotechnological strategy. Overall, this work provides insights into sewage sludge upgrading independent of additional carbon input, which can be applied in existing anaerobic sludge fermentation infrastructure as well as to develop new applications in a diverse range of industries.

Enhancing biomass conversion to bioenergy with machine learning: Gains and problems

The growing concerns about environmental sustainability and energy security, such as exhaustion of traditional fossil fuels and global carbon footprint growth have led to an increasing interest in alternative energy sources, especially bioenergy. Recently, numerous scenarios have been proposed regarding the use of bioenergy from different sources in the future energy systems. In this regard, one of the biggest challenges for scientists is managing, modeling, decision-making, and future forecasting of bioenergy systems. The development of machine learning (ML) techniques can provide new opportunities for modeling, optimizing and managing the production, consumption and environmental effects of bioenergy. However, researchers in bioenergy fields have not widely utilized the ML concepts and practices. Therefore, a comparative review of the current ML techniques used for bioenergy productions is presented in this paper. This review summarizes the common issues and difficulties existing in integrating ML with bioenergy studies, and discusses and proposes the possible solutions. Additionally, a detailed discussion of the appropriate ML application scenarios is also conducted in every sector of the entire bioenergy chain. This indicates the modernized conversion processes supported by ML techniques are imperative to accurately capture process-level subtleties, and thus improving techno-economic resilience and socio-ecological integrity of bioenergy production. All the efforts are believed to help in sustainable bioenergy production with ML technologies for the future.

Comparative life cycle assessment of sewage sludge treatment in Wuhan, China: Sustainability evaluation and potential implications

Owing to the relentless growth of sewage sludge production, achieving low-carbon development in sewage sludge treatment and disposal (STD) is becoming increasingly challenging and unpredictable. However, the STD varied spatially, and city-specific analysis is deemed necessary for sustainable evaluation. Therefore, a lifecycle-based greenhouse gas (GHG), energy, and economic analysis were conducted by considering six local STD alternatives in Wuhan City, China, as a case study. The findings indicated anaerobic digestion combined with digestate utilization for urban greening (ADL) and incineration in existing power plants (INCP) exhibited the least GHG emissions at 34.073 kg CO2 eq/FU and 644.128 kg CO2 eq/FU, while INCP generated the most energy at -2594 kW.h/FU. The economic evaluation revealed that ADL and INCP were more beneficial without accounting for land acquisition. Scenario analysis showed that the energy recovery from ADL and INCP is significantly influenced by the hydrolysis yielding rate and sludge organic content. Perturbation sensitivity indicates that regional emission factor of electricity and electricity fee highly influence the overall GHG emission and cost. The results of this study could assist policymakers in identifying viable solutions to the cities experiencing the same sludge treatment burdens.

Techno-economic analysis of municipal solid waste treatment for poly-generation system

Municipal solid waste (MSW) is characterized by complex composition, low calorific value and high moisture content. Using a single treatment technology is costly and difficult to achieve optimal results. A poly-generation system that integrates classified waste pyrolysis and incineration is proposed, producing fuel, electricity, and steam. The system has been designed and optimized to find the optimal feed ratio and process model. However, the economic performance of the poly-generation system is still unclear. In this work, a techno-economic analysis (TEA) was conducted to evaluate the economic feasibility of the proposed MSW treatment poly-generation system. The annual electricity generated by the poly-generation system is 104.13 GWh. The annual steam generated is 4.91 kt, and the average annual diesel produced is 1.60 kt. The TEA results showed that the total capital investment of the system was 602.07 M¥, and the annual operating cost was 40.63 M¥. The net present value was 93.01 M¥, which is a positive value. The internal rate of return was 10.28 %, which is higher than the benchmark rate of return, indicating that the system is economically feasible. Sensitivity analysis indicated that the internal rate of return was extremely sensitive to fixed capital investment, price of electricity, product yield, and government subsidy. The TEA analysis of poly-generation system provides a fundamental theoretical basis for the feasibility of classified MSW treatment and offers valuable insights for policy makers and investors in the waste management field. Considering the complexity of the waste, future research can be carried out from the environmental aspect, combining both economic and environmental objectives for multi-objective optimization and conducting comprehensive evaluation of the industrial practicability of the poly-generation system.