Journal of Cleaner Production最新文献

Radical-induced polymerization in persulfate (PS)-based advanced oxidation process (AOP) is attracting attention in water decontamination. Herein, we revealed its new role in rapid recycling of perishable food wastes using KOH activated PS. A glucose (Glu) solution of 250 g C/L was applied to mimic the carbohydrate-rich raw material with 50–60% moisture in conventional composting, wherein boosted humification occurred after addition of solid KOH/PS. Intense heat release (from 25 to 79.4 °C), mainly generated from KOH dissolving and exothermic radical chain polymerization, was observed within 2 min. Solid KOH addition contributed to synergistic PS activation by base and self-heating, realizing complete PS decomposition and fulvic like acid (FLA, 210.8 g C/L) formation within 10 min. Extracted FLA promoted cucumber seed germination and fresh weight of chickweeds by 40.0% and 128.3%, respectively. Identified •OH and SO₄^•- played primary roles in FLA formation through aromatization, carboxylation, and polymerization, wherein several key reactive intermediates such as 5-hydroxymethylfurfural and aromatic radicals (i.e. 1,2,4-benzenetriol radical) were formed. Moreover, the humification process simultaneously produced K₂SO₄ (i.e. the end product of PS decomposition) which could be used as a typical K/S fertilizer. Scaling-up humification of waste cooked rice and fertilization results further supported the potential of solid KOH/PS in efficiently converting food wastes into FLA and K⁺-rich compound fertilizer.

Waste products destined for landfills with high calorific value are increasingly being explored for potential use in a variety of industries. One example is the potential use of these wastes in cement kilns to reduce greenhouse gas (GHG) emissions from cement production. This study develops a cradle-to-gate life cycle assessment (LCA) model to estimate the GHG emissions, criteria air contaminants (CAC), and the impact of biogenic carbon accounting methods in biomass-containing alternative fuels (AFs) on life cycle GHG emissions when replacing natural gas with AFs at a cement facility. The proposed AF mixture includes landfill wastes like construction and demolition waste, asphalt shingles, tire fluff, carpet, textiles, and plastics. While many LCAs assume the biogenic fraction's climate impact is carbon-neutral, its actual effects depend on a range of new methods being proposed to account for the climate impacts associated with biogenic carbon. The findings of this study demonstrate a reduction of approximately 7–13% in life cycle GHG emissions. The preliminary estimates suggest that the change to CACs will likely not be materially different from the current use of natural gas. It also emphasizes the importance of accounting for the biogenic fraction in biomass-based AFs, indicating a potential overall reduction of up to 7.2% in life cycle GHG emissions when the biogenic fraction is treated as carbon-neutral. While factoring in the benefits of shorter rotation and longer storage periods results in a 12.7% reduction in life cycle GHG emissions. The LCA model developed in this study holds the potential for broad application among cement facilities that are considering fossil to alternative fuels as part of their GHG emission reduction strategies.

Stakeholders' engagement in forest management decision-making is a critical tool for enhancing the business acceptability of the forest sector, and the Forest Stewardship Certification (FSC) scheme proactively involves stakeholders in its implementation. Based on the stakeholder theory, this study examined stakeholder's engagement in the FSC forest management certification in Romania over the past two decades to identify the extent and inputs of their involvement in the process. Using in-depth content analysis and text mining techniques, we explored publicly available information from 209 public reports covering 45 forest management certificates. According to data available in 178 reports, the average number of stakeholders notified per audit was 50.7. However, response evidence was found in 128 reports, with an average of 1.2 responses per audit, suggesting a limited engagement in the process. Additional stakeholders' feedback was received as part of the on-site audits, with an average of 10.2 responses per audit. Given the inconsistencies in the reporting format between certification bodies, we set a structured framework to analyse the findings on stakeholders' engagement from different report sections. The employed analytical framework sheds light on stakeholder and legitimacy theories in forest certification. Our findings highlighted stakeholders' predominantly positive feedback tone, evenly distributed across all stakeholder types and the four analysis domains. Negative feedback accounted for only 9.4% of the findings, highlighting areas for improvement for certificate holders, companies in the timber supply chain and public authorities. This study's findings may assist FSC in refining its stakeholder engagement practices, contributing to enhanced participation and better risk mitigation of non-compliance with standard requirements.

In the present world, rapid industrialization and extensive use of resources have led to an unprecedented increase in waste volumes. Industries seeking to produce more to satisfy the upsurge demand while exploiting the potential provided by advancements in technology contribute to this. This situation is leading to fast-approaching expiration date for natural resources, which calls for immediate intervention, sustainable practices, and proper waste disposal strategies. As pillars to sustainability, not only the environmental and economic aspects should be considered, the social domain is also very important to take into account. For the particular case of the waste-to-energy (WtE) technologies, the social domain entails several concerns that have never been thoroughly and representatively appraised, a clear understanding of the reasons behind this being missing. Thus, the purpose of this work is to conduct a literature review on social assessments related to the thermal conversion of wastes. Then, distinct methodologies already used for the social aspects in other areas were compared to the achieved results to better frame them and potentially suggest a workflow for this type of assessment in the WtE sector. The aim is to identify and address knowledge gaps, in order to facilitate a comprehensive evaluation of the current context surrounding this controversial topic. The main findings indicate a lack of consistent reporting practices for social life cycle assessment (S-LCA) implementation, the UNEP/SETAC approach appearing as the most commonly used. Social concerns primarily focus on employment, human health, accessibility, safety, and odor-related issues. Knowledge gaps persist, including the need for a better understanding of the interrelation between dimensions, the absence of concise and binding legislation, low sector engagement, discrimination issues, inconsistency in sensitivity analysis, and a lack of objectivity. Based on the literature review, it can be concluded that while WtE techniques have the potential to contribute to a more sustainable and resilient society, there are social concerns that must be addressed. The review highlights the importance of conducting comprehensive social assessments in the context of thermal waste conversion. By filling knowledge gaps and considering the social implications of these techniques, a more informed evaluation can be conducted, leading to better decision-making and the development of more sustainable waste management strategies. This effort should be tightly connected to the sustainability efforts and goals in place, such as the ones preconized by the European Commission and the United Nations.

The inherent uncertainty of solar energy brings great difficulties to the grid connection and short-term energy planning and dispatching. Deep learning method makes it possible to predict the short-term solar energy with its powerful learning ability, but its complex model structure and huge trainable parameters bring great difficulties to the practical deployment. Therefore, this paper proposes a lightweight framework based on knowledge distillation strategy, which greatly reduces the complexity of multi-modal solar irradiance prediction model meanwhile ensuring an acceptable accuracy, facilitating the practical deployment. Firstly, a teacher model with multi-modal structure and good accuracy is built based on ResNet18-Informer. Then, the lightweight model is obtained by the proposed lightweight framework depending on the knowledge of teacher model. The comparisons of various models and the optimal settings of knowledge distillation are analyzed. Results show that the lightweight model can reduce the trainable parameters, inference time, and GPU memory by 97.7%, 52.5%, and 36.3%, respectively. The normalized root mean square error is reduced by 24.87% compared with the same structure model but without knowledge distillation, verifying the superiority of the proposed framework. The soft loss using the light loss with the ratio of 0.3 can obtain the best training results for the lightweight model. The structure with 3 residual blocks and 3 LSTM layers is proved to be the best for the lightweight model in the solar irradiance prediction task.

In this work, excellent conductor element Ag was employed to bridge TiO₂ nanotubes (TNTs) and PbO₂ to construct an “expressway” for rapid electron transfer between the bases and active layers over the fabricated PbO₂/SnO₂-Sb/TNTs-Ag/Ti anode. Physicochemical characterizations reveal that elemental Ag can fill into the gaps between the TNTs, thus stabilizing structure and improving conductivity of the anode. Electrochemical and accelerated lifetime tests show the expanded reaction area (0.049–0.173 cm²), decreased charge transfer resistance (42.32–4.03 Ω cm⁻²), and prolonged lifetime (0.29–6.28 years). Furthermore, relatively higher average current efficiency (ACE) and less energy consumption (E_sp) can be achieved during electrochemical oxidation of acid gold G (AY36) and rhodamine B (RhB) synthetic wastewaters, as well as shortening their degradation pathways. Our research looks forward to providing a novel Ag bridging design strategy for the synthesis of highly active and stable multilayer anodes.

Agricultural innovation is pivotal for enabling cleaner production within the sector. Nonetheless, smallholder farmers in the Global South encounter functional and psychological challenges impeding innovation adoption efforts. Existing literature tends to narrowly focus on common barriers associated with individual innovations, often limiting the broader significance of psychological hindrances. This study takes a unique approach by delving primarily into the realm of psychological barriers, encompassing internal challenges that impede adoption, and explores external support strategies to overcome such hindrances. A multi-stakeholder approach was employed to gather validated insights based on data from eighteen semi-structured interviews involving rice farmers and agricultural technology companies. Research findings revealed that trust, effort, attitudinal, and normative barriers are prominent psychological hindrances to innovation adoption. To this effect, pertinent enabling factors and overcoming strategies should demonstrate clear benefits, infuse trust, reduce effort requirements, and develop human capital. This research is among the first to demystify and categorise psychological barriers and corresponding overcoming strategies into an integrated framework. The resulting framework allows for a novel and comprehensive analysis of the potential strategies to overcome the psychological barriers collectively, a complex issue involving interrelations and hidden dynamics that are challenging to explore otherwise. This study contributes to the Innovation Resistance Theory through its application within the context of smallholder farmers and leads to implications to expedite the transformation towards a more sustainable and innovative agriculture sector.

In recent years, hemp textiles have gained attention as a sustainable alternative to cotton. However, the uneven fineness and length of hemp fibers, along with their stiffness, adversely affect spinnability and exacerbate yarn evenness and hairiness, particularly due to short fibers. This study introduces a modified sustainable droplet-wet spinning technology aimed at enhancing hemp yarn quality, with a primary focus on reducing yarn hairiness. Implemented on a ring spinning machine, the technology utilizes a syringe connected to an adjustable-speed pump, delivering water onto the front top roller. This innovative approach enhances hemp yarn in two ways: firstly, the cohesive force of water promotes the consolidation of short fibers on both sides of the fiber bundle towards the center, thereby condensing the spinning triangle. Consequently, the fibers on both sides of the fiber bundle are more readily drawn into the spinning triangle and twisted to form yarn; secondly, wet hemp fibers possess a lower modulus, rendering them softer and more deformable, facilitating their embedding into the yarn, thereby enhancing yarn tenacity and reducing yarn hairiness. The study systematically investigates the relationship between droplet-wet spinning parameters (water droplet rate, hemp fiber content of the roving, and yarn twist multiplier) and hemp yarn quality. Experimental results reveals that optimal droplet-wet spinning lead to a 22% increase in yarn tenacity and about 50% reduction in hairiness. A higher hemp fiber content in the roving contributes to better performance of droplet-wet spinning technology in enhancing yarn quality. Moreover, droplet-wet spinning enables the production of high-quality hemp yarn at lower twist multipliers, thereby reducing electricity consumption during yarn production. Subsequently, the performance of knitted fabrics made from conventional ring-spun yarn and droplet-wet spun yarn was compared and analyzed. The results indicate that fabric made from droplet-wet spun yarn exhibits an approximately 8% increase in bursting strength and a one-level improvement in pilling resistance. This research highlights the potential of droplet-wet spinning technology to enhance hemp yarn quality and promote sustainable textile production.

Although various membrane and cathode electrode types have been investigated in dual chamber microbial fuel cells (DCMDCs), there is no agreement on which combination of electrodes and separator materials works best. The main objective of this study is to investigate the synergistic effects of cathode electrodes and membranes on the performance of DCMFCs during the start-up phase, to model the DCMFCs through artificial neural networks (ANN), and to determine the most cost-effective choice. Principal component analysis was used to analyze the interrelationships among various factors that influence DCMFCs. Two types of ion exchange membranes (cation exchange membrane and anion exchange membrane) and two types of cathode electrodes (carbon cloth covered with 20% Pt as catalyst and plain carbon cloth) were studied. Electrodes and membranes were analyzed using AFM, TEM, SEM, XRF, and FTIR to investigate changes in morphology and the potential of fouling. The results showed that DCMFC with cation exchange membrane (CEM) and plain carbon cloth (CC) generated the maximum power among the investigated configurations. The average voltage values and COD removal efficiency reached 748 ± 13 mV and 57.8 ± 2.5%, respectively. The maximum power density achieved was obtained when the external resistance was set at 1000 Ω and was 180 mA/m². ANN was successful in predicting the output voltage for the examined DCMFCs. The use of DCMFC with CC and CEM can be considered optimal in terms of performance and cost.

The implementation of some energy-saving and emission reduction measures can effectively offset the energy consumption and carbon emissions in the wastewater treatment process. Integrated policy-making information on carbon-energy-economy of these technologies is not clear in national wastewater treatment industry. This study investigated energy self-sufficiency, carbon neutralization potential and economic performance of wastewater treatment industry, as well as related synergy effect among the three aspects using the proposed approach. Then the approach was used to investigate energy-saving and carbon emission reduction potential of the three technologies (photovoltaic power (PV), combined heat and power (CHP) and water source heat pump (WSHP)) and technological combinations as well as related economic performance in urban wastewater treatment of Chinese different provinces in 2021. The results showed that (1) The national energy self-sufficiency is 95%; therein, 13 provinces have the potential to achieve or exceed energy self-sufficiency of 100%, and the top 3 provinces are Heilongjiang, Yunnan and Hunan. (2) The national carbon neutral potential is 87%; therein, 9 provinces have the potential to achieve or surpass carbon neutralization of 100%, and the top 3 provinces include Beijing, Hunan and Shaanxi. (3) these technologies or their combinations are potentially economically viable (net economic benefit ratio >1), and the top three provinces are Beijing, Shaanxi, and Inner Mongolia. (4) Generally, there are 13 provinces with synergy effect >1 in the country; the top three provinces are Liaoning, Heilongjiang and Hunan. Finally, targeted policy suggestions are provided for Chinese urban wastewater treatment. The proposed approach can also act as one of decision-making tools for wastewater treatment industry in other countries or areas in the world.