Journal of Material Cycles and Waste Management最新文献

Low-income coastal nations such as Mozambique grapple with providing sustainable and effective management of plastic waste (PW), which influences the increase in disease prevalence and of diverse adverse environmental impacts, primarly terrestrial and marine pollution. About 490,000 tons, from domestic generation and imports, make up the total PW in the system. In this study, a life cycle assessment (LCA) was employed to clarify the associated environmental impacts of 1 kg of PW within the waste management system in Mozambique. It was explained that over 95% of PW ended up in open dumpsites, with about 60% open burned, significantly impacting the ecotoxicity and global warming categories—5.49 kg of 1,4-dichlorobenzene (1,4-DCB) for terrestrial ecotoxicity, 4.99 kg of 1,4-DCB for human non-carcinogenic ecotoxicity, and 1.57 kg of carbon dioxide equivalent (CO₂ eq) for global warming potential. The findings provide a quantitative baseline understanding of PW management impacts in the country, thus identifying junctures and opportunities that can help inform and enable the development of policies and strategies for a sustainable PW management system.

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Studies have explored the engineering properties of Polyethylene Terephthalate (PET) fiber-reinforced concrete, including mechanical strength, crack control, and durability. However, a comprehensive analysis incorporating surface treatment is lacking. This paper provides an extensive analytical database, including previous literature on the mechanical and durability properties of PET fiber-reinforced concrete and the effects of fiber surface treatment on concrete performance. Furthermore, the microstructural and pore-structural properties of PET fiber-reinforced concrete are discussed, detailing the mechanisms behind these properties. This examines the effect of incorporating virgin and recycled PET fibers at mass percentages (wt%) of 0–2 and volume percentage (v%) of 0–12 of total mass/volume. Key findings include that the optimum PET fiber content for tensile and flexural strength is 0.5 v%, while higher contents cause fiber balling, reducing concrete’s performance. Notably, PET fiber-reinforced concrete shows a maximum compressive strength loss of 24% in 3% H₂SO₄ and 10% loss in pH 12.6 alkaline medium after 120 days. Surface treatment with 20 wt% NaOH and Silane improves compressive strength from 54 to 60 MPa. PET fiber coating with Graphene-oxide and Polydopamine increases frictional and chemical bonding in concrete by 85 and 70%, respectively. The study concludes that surface treatments enhance concrete properties by improving bonding and minimizing fiber degradation.

Waste classification is vital for addressing the current urban waste crisis. However, existing research on intelligent waste classification systems has limitations compared to traditional methods. This study, grounded in the theory of planned behavior and contextualized within Chinese policy frameworks, surveyed 614 participants from Shanghai, Suzhou, Hangzhou, and other cities. The aim was to analyze residents’ willingness to engage with intelligent waste classification systems and to construct a theoretical model. Structural equation modeling was employed to examine the influence of system usability, incentives, time costs, social impact, behavioral attitudes, and intentions on residents’ participation in intelligent waste classification. The findings reveal that perceived ease of use, perceived motivation, and time cost are significantly positively associated with behavioral attitudes. In addition, time cost, social impact, safety perception, and intelligence perception are strongly linked to residents’ behavioral intentions. The ease of use, incentives, and time costs indirectly affect waste classification behavior through behavioral attitudes, while time costs, social impact, safety perception, and intelligence perception exert indirect effects through behavioral intentions. This study offers valuable insights for enhancing urban residents’ participation in waste classification initiatives.

Recycling End-of-Use Medicines (REOUM) for reuse, which integrates circular economy principles, is a promising approach to reducing medicine wastage and improving access to medicines. This study presents an integrated theoretical model grounded in prominent theories, such as the Theory of Planned Behavior, Norm Activation Model, Value-Belief-Norm theory, and protection motivation theory, to explore the behavioral factors influencing End-of-Use Medicine (EOU-M) return intentions. The study investigates how antecedents like awareness of consequences, ascription of responsibility, social norms, and altruistic values affect EOU-M return intentions. In addition, the study examines the mediating effects of personal norms and attitudes, as well as the moderating effects of self-efficacy beliefs, response efficacy beliefs, and response cost. Perceptions concerning the behavioral intention to return EOU-M are recorded from urban residents (n = 238) using a structured questionnaire. A partial least square-structural equation modeling was used to analyze the variables’ linkages. Awareness of consequences and altruistic values were the most contributing antecedents of EOU-M return intention. Personal norms and attitudes were found to significantly mediate the effect of the antecedents on return intention. The findings suggest that policies enhancing awareness and promoting altruistic values can significantly boost REOUM efforts, contributing to sustainable medicine consumption practices.

Landfills are a primary method of waste disposal in developing nations despite their environmental impact. The decomposition of municipal organic waste in landfills generates potent greenhouse gases (GHGs) that contribute to the effects of urban climate change. In Delhi, India, which generates 11,144 tons per day (TPD) of municipal solid waste (MSW), three major landfill sites Ghazipur (GL), Bhalswa (BL), and Okhla (OL) were examined using the well-established in-situ static chamber method to measure emissions of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O). This study highlights the need to address these uncertainties by comprehensively capturing GHG emissions from the diverse dynamics within the landfill through rigorous field experiments that account for spatial and temporal variability. The average CH₄ emission fluxes from three years of extensive field studies exhibited high variability, measured at 1494 ± 893 (CV = 59.8%), 1576 ± 746 (CV = 47.3%), and 961 ± 322 (CV = 33.5%) mg m⁻² h⁻¹ for GL, BL, and OL, respectively. This resulted in CH₄ emission factors (EFs) of 5.6 ± 3.5, 4.4 ± 1.9, and 4.2 ± 1.4 g kg⁻¹ for GL, BL, and OL, respectively. The CO₂ emission fluxes were 7520 ± 3401 (CV = 45.2%), 8005 ± 3907 (CV = 48.8%), and 5066 ± 1985 (CV = 39.2%) mg m⁻² h⁻¹ with corresponding EFs of 20.0 ± 7, 23.3 ± 9, and 16.3 ± 4.7 g kg⁻¹. The N₂O emission fluxes were 1210 ± 329 (CV = 27.2%), 998 ± 298 (CV = 30%) and 944 ± 339 (CV = 36%) μg m⁻² h⁻¹ with EFs of 3.8 ± 0.1, 2.5 ± 0.2, and 3.1 ± 0.3 mg kg⁻¹ for GL, BL, and OL, respectively. Total GHG emissions from Delhi’s landfills were estimated as 328.6 ± 91.9, 231.0 ± 109.5, and 241.1 ± 112.2 Gg CO₂ equivalent for 2009–10, 2010–11, and 2011–12. Investigating waste management practices such as spreading, covering, and compaction is essential for understanding their impact on GHG emissions and advancing climate change mitigation through waste-to-energy solutions for sustainable solid waste management and energy production. While the findings offer valuable understandings into emission patterns, the limited sample size introduces some uncertainty, and the EFs should be considered as a preliminary estimation of major GHG in three consecutive years. Future research is necessary to validate these factors with more extensive datasets that capture spatial and seasonal variations in emissions.

Mechanical treatment is the predominant method in waste plastic recycling, and within this context, cleaning of raw material plays a vital role in a preprocessing step. Dry cleaning methods have emerged as alternatives to traditional processes, addressing concerns related to wastewater generation and high energy consumption. However, existing dry cleaning approaches face challenges, particularly regarding efficacy and uniformity. This study employs a pulsed gas–solid fluidized bed apparatus to assess the cleaning efficiency of waste polyethylene film. Cleaning effectiveness and uniformity are quantified using weight analysis and spectroscopy. The investigation examines the impact of cleaning time, superficial gas velocity, agitation, and pulse airflow on the cleaning process. The findings indicate that time emerges as the primary influencing factor, with superficial gas velocity exerting a substantial impact on cleaning effectiveness. In addition, the introduction of pulse airflow significantly enhances both the cleaning effectiveness and uniformity. Under optimal conditions, weight analysis and spectroscopy indicators can exceed 99%, comparable to the conventional water washing methods, and even present potential advantages in spectroscopy indicators. This research contributes valuable insights for improving the efficiency of dry cleaning processes.

The effects of high-temperature treatment and ball-mill treatment on recycled coarse aggregates (RCA) and recycled fine aggregates (RFA) were investigated in this study by comparing the physical properties such as water absorption, void ratio, density, crushing index and residual paste content of recycled aggregates before and after treatments and the flexural and compressive strengths of concrete/mortar made from 100% RCA/RFA. The results show that the combination of high temperature and ball milling significantly enhanced the physical properties of the recycled aggregates (RA), and improved the mechanical properties of the recycled aggregate concrete/mortar. The mechanism of thermal treatment to RA is that the aggregate and attached mortar show different thermal expansion at high temperature, and the connection between aggregate and residual mortar will be weakened, which makes it easier to separate during grinding. Through the ball milling, frictional collisions between different aggregate particles as well as between aggregate and grinding balls can strip and separate the attached surface mortar. In addition, ball milling improves the appearance and shape of the aggregate, resulting in smoother edges and smoother corners, and breaks up and removes light materials such as mortar adhering to the RA. Besides, the cost calculation shows that the treatment cost of RCA and RFA could be lower than the direct usage cost of natural aggregates. From the perspective of considering the actual ecological benefits and resource utilization, more low-cost treatment methods such as ball milling could be a good option to optimize the RA.

Waste segregation is an essential process in waste management. It entails identifying, classifying, separating, and arranging various kinds of waste. An efficient waste segregation process facilitates effective reuse, recycling and recovery. Various studies related to waste segregation so far lacking thorough pre-processing approaches might result in diminished classification metrics. Further, several investigations overlooked essential metrics such as F1-score, recall, and precision focusing solely on accuracy. This study proposes novel VGD6-NET architecture (referred as visual garbage detector 6-Net) for 6 categories of waste using 3-tier convolutional neural network. The main aim of this research is to enhance waste image classification by improving accuracy and detection mechanisms through the utilization of advanced technologies such as 3-tier convolutional neural networks and the development of a specialized architecture. The experimental results show the proposed model predicts the categories of waste more accurately for processes like automated waste segregation into recyclable and non-recyclable categories. Trained on 2527 waste images from 6 classes, the model achieved an accuracy score of 0.9854, with a minimal loss score of 0.0814, with a precision of 0.9772 for the cardboard class, recall value of 1.0 for plastic class, and highest F1-score of 0.9764 for the cardboard class of the 6 classes available. Ultimately, the proposed model contributes to building a more sustainable future by reducing the environmental impact of waste disposal and conserving valuable resources through improved recycling efforts.

Clinker ash (CA) is a granular waste from thermal power plants besides fly ash (FA). When used as fine aggregate e, CA’s porous nature reduces mechanical properties and durability of concrete. This study explores CA recycling in concrete by geopolymer (GP) technique, modifying CA with alkali activator solution (AS). We investigated the effects of CA substitution of partial FA and sea sand on fluidity, strength, and durability of slag/FA-based GP concrete and mortar. We also examined the changes of CA particles after immersed in AS to clarify CA’s compatibility with GP binder. The results indicated that CA particles react with AS, densifying CA and refining the interfacial transition zone (ITZ) between the GP matrix and CA particles. Although FA replacement with CA reduced strength of GP concrete, replacing sand with CA (up to 20%) minimally affected GP concrete’s flowability, while enhancing compressive and flexural strengths. A surface modifier, composed of sodium aluminate solution (AN) and ablendof silica fume and caustic soda (SN), greatly improved the carbonation resistance of GP with CA. XRD analysis identified components in CA and reaction products between CA and AS in GP materials. These results confirmed CA’s potential as fine aggregate of geopolymer concrete.

The growing demand for rare-earth elements (REEs) and their limited availability have made REEs critical with high supply risk. E-waste, particularly waste electrical and electronic equipment (WEEE), offers a valuable secondary source. This study assesses the impact of mechanical pre-treatment on the recovery of REEs and gold from discarded hard disk drives (HDDs). We compared recovery efficiencies of REEs and Au using separation techniques, particle sizing, and chemical analyses between two pre-treatment methods: shredding and manual disassembly. Shredding, common in electronic waste processing, leads to oxidation and significant loss of critical raw materials (CRMs), while manual disassembly preserves clean, and non-oxidized NdFeB magnets for magnet-to-magnet recycling. Manually disassembled HDDs were directly analyzed to determine recyclable quantities of REEs and gold. Shredded HDDs underwent sieving, density, and magnetic separation, followed by demagnetization and chemical analysis. Results indicate shredding causes a 73.9% loss of REEs and a 43.8% loss of Au compared to manual disassembly, with increased oxidation due to finer particles. These findings suggest that while shredding is adequate for recovering ferrous and aluminum fractions, manual disassembly is essential for maximizing REE recovery.