Waste Management & Research: The Journal for a Sustainable Circular Economy

The recycling processes of spent lithium iron phosphate batteries comprise thermal, wet, and biological and mechanical treatments. Limited research has been conducted on the combined mechanical process recycling technology and such works are limited to the separation of metal and non-metal materials, which belongs to mechanical recovery. In this article the combined mechanical process recycling technology of spent lithium iron phosphate batteries and the separation of metals has been investigated. The spent lithium iron phosphate batteries monomer with the completely discharged electrolyte was subjected to perforation discharge. The shell was directly recycled and the inner core was directly separated into a positive electrode piece, dissepiment, and negative electrode piece. The dissociation rate of the positive and negative materials reached 100.0% after crushing when the temperature and time reached 300 °C and 120 min. The crushed products were collected and sequentially sieved after the low-temperature thermal treatment. Then, nonferrous metals (copper and aluminium) were separated from the crushed spent lithium iron phosphate batteries by eddy current separation with particle size −4 + 0.4. The optimised operation parameters of eddy current separation were fed at speeds of 40 r min^-1, and the rotation speed of the magnetic field was 800 r min^-1. The nonferrous metals of copper and aluminium were separated by the method of pneumatic separation. The optimal air speed was 0.34 m s^-1 for the particle-size −1.6 + 0.4 mm and 12.85–14.23 m s^-1 for the particle-size −4 + 1.6 mm. The present recycling process is eco-friendly and highly efficient and produces little waste.

Accurate prediction of municipal solid waste (MSW) generation is necessary for choosing appropriate waste treatment methods and for planning the distribution of disposal facilities. In this study, a hybrid model was established to forecast MSW generation through the combination of the ridge regression and GM(1,N) models. The hybrid model is multivariate and involves total urban population, total retail sales of social consumer goods, per capita consumption expenditure of urban areas, tourism, and college graduation. Compared with the constituent models alone, the hybrid model yields higher accuracy, with a mean absolute percentage error (MAPE) of only 2.59%. Through weight allocation and optimal treatment of residuals, the hybrid model also balances the growth trends of the individual models, making the prediction curve smoother. The model coefficients and correlation analysis show that population, economics, and educational factors are influential for waste generation. MSW output in Hangzhou will gradually increase in the future, and is expected to reach 5.12 million tons in 2021. Results can help decision makers to develop the measures and policies of waste management in the future.

Smart waste collection strategies have been developed to replace conventional fixed routes with dynamic systems that respond to the actual fill-level of waste bins. The variation in waste generation patterns, which is the main driver for the profit of smart systems, is exacerbated in the United Arab Emirates (UAE) due to a high expatriate ratio. This leads to significant changes in waste generation during breaks and seasonal occasions. The present study aimed to evaluate a geographic information system (GIS)-based smart collection system (SCS) compared to conventional practices in terms of time, pollution, and cost. Different scenarios were tested on a local residential district based on variable bin filling rates. The input data were obtained from a field survey on different types of households. A knowledge-based decision-making algorithm was developed to select the bins that require collection based on historical data. The simulation included a regular SCS scenario based on actual filling rates, as well as sub-scenarios to study the impact of reducing the waste generation rates. An operation cost reduction of 19% was achieved with SCS compared to the conventional scenario. Moreover, SCS outperformed the conventional system by lowering carbon-dioxide emissions by between 5 and 22% for various scenarios. The operation costs were non-linearly reduced with the incremental drops in waste generation. Furthermore, the smart system was validated using actual waste generation data of the study area, and it lowered collection trip times by 18 to 42% compared to the conventional service. The present study proposes an integrated SCS architecture, and explores critical considerations of smart systems.

Efficiency assessment and benchmarking are crucial for managing any organization. However, especially from a regulatory perspective, such efficiency assessment and benchmarking must be unbiased from context-specific issues and should provide an absolute rating, rather than a relative one. The current work reviews the approaches used for performance assessment and benchmarking waste collection services, revealing that the majority are biased and are not absolute, and proposes two alternative context-unbiased and absolute performance indicators, the collection capacity use (CCU) and the segregated waste collection efficiency (SWE). The proposed indicators were calculated for 246 utilities operating in Portugal. The utilities were then ranked accordingly, and their position was compared with the position attained using the equivalent performance indicators in the system currently in use by the Portuguese service regulator. The results reveal ranking differences of over 50 positions and illustrate how misleading the results from context-biased and relative metrics can be.

Construction sites are plagued with numerous problems, such as improper planning and management, high amounts of waste generation and low awareness of waste reduction. Construction and demolition waste literature provides several best practises and prescriptive strategies that help minimise waste during construction. However, it lacks in the systematic identification and minimisation approach of all possibilities of waste. Therefore, studies focusing on principles and tools that help systematically analyse the inefficiencies of on-site processes leading to waste generation and philosophies addressing waste minimisation are necessary. As eliminating waste is one of the key lean principles, this article discusses the need and importance of integrating the lean construction with the construction and demolition waste management. This article aims to estimate and assess the causes of waste generation in a high-rise building construction through a case study in Chennai city (India) using value stream mapping, a key lean construction tool. Onsite monitoring and measurement were performed to quantify the amount of waste generated. A waste generation rate of 66.26 kg m⁻² was identified, of which concrete, cement mortar and brick waste represented almost 90% of the total construction waste. Direct observation and interviews of site personnel were conducted to understand the causes of waste generation. A strategic framework has been proposed to improve construction and demolition waste minimisation depicting the synergy of combining lean construction principles with construction and demolition waste management strategies. The proposed framework helps in the systematic identification, assessment and minimisation of on-site construction waste generation.

The main by-product of wine-making is grape marc. With proper treatment, grape marc may return to the vineyard as a fertiliser. This study deals with the vermicomposting of grape marc in a continuous feeding system in outdoor conditions for more than 12 months. The N-NH₄⁺, dissolved organic carbon (DOC), and N-NH₄⁺/N-NO₃^- contents were greater in the top layers. The pH value was about 8 in all the layers. The electrical conductivity was the greatest in the bottom layer. The ion-exchange capacity did not modify significantly during vermicomposting. The microbial biomass was the greatest in the upper layer, as well as the number and the biomass of the earthworms. The process of vermicomposting seems to be an ideal way of processing residues from the winemaking industry. This vermicompost has very good properties for use as a fertiliser, and for returning the nutrients and organic matter to the soil, for example, in a vineyard.

Solid waste composting has never been practised on a full scale in Jordan. However, the National Solid Waste Management Strategy recommended five major composting facilities to be put into operation starting from 2025. According to the Ministry of Environment, the waste sector is contributing to 10.6% of the total greenhouse gas emissions of the country. The main objective of this study was to assess the potential of solid waste composting in mitigating greenhouse gas emissions in Jordan. Applying the upstream-operating-downstream account framework and developing a model that estimates the greenhouse gas emissions, it was possible to estimate the emissions associated with composting of source-segregated bio-waste, which was compared with three other scenarios, including business as usual (dumping and landfilling), sanitary landfilling, and anaerobic digestion. The assessment revealed that composting and anaerobic digestion of the total generated source-segregated bio-waste (Scenarios 3 and 4) have the least net greenhouse gas emissions with 1.1 million Mg CO₂-_eq y^-1, while engineered sanitary landfilling and dumping have net emissions of 2.6 and 3.75 million Mg CO₂-_eq y^-1, respectively. The findings of this research are paving the way to make informed and responsible decisions in the Jordanian solid waste sector to adopt sustainable and integrated management options.

In the project ‘NEW-MINE’ the use of sensor-based sorting machinery in the field of ‘landfill mining’ is investigated. Defilements pose a particular challenge in the treatment and sorting of plastics contained in landfills. For this reason, the effects of various pollutants caused by the interactions in the landfill body or the mechanical treatment steps in landfill mining are examined. In the following elaboration, the focus is on the influences of surface moisture and surface roughness of plastics on sensor-based sorting by means of near-infrared technology. Near-infrared radiation (NIR) in a wavelength range of 990 nm to 1500 nm has been used for the detection and classification of plastic particles. The experiments demonstrate that increased surface roughness reduces signal noise and thereby improves the classification of both spectrally similar and transparent plastics, but reduces the yield of low-softening plastics because their sliding speed on a sensor-based chute sorter varies as a result of the heating of the chute. Surface moisture causes the absorption of radiation from 1115 nm (high density polyethylene [HDPE], linear low density polyethylene [LLDPE], polyethylen terephthalate [PET] and polyvinylchloride [PVC]) or from 1230 nm (low density polyethylene [LDPE], polypropylene [PP] and thermoplastic polyurethane [TPU]) up to at least 1680 nm, which causes amplification or attenuation of various extremes in the derivative. However, the influence of surface moisture on the yield of plastics is usually very low and depends on the spectral differences between the different plastics.

Managing waste electrical and electronic equipment is currently one of the top priority challenges of waste management in the European Union. The collection and subsequent processing of waste electrical and electronic equipment are realized by means of the so-called collective systems that employ collection boxes varying in size and materials used for their production. This study focuses on quantifying and comparing environmental impacts of often-used collection boxes on the example of mobile phone collection. The comparison was based on volume (20 l, 60 l, and 70 l) and on the material used for the construction of the box (polypropylene, corrugated cardboard, and stainless steel). Other parameters, such as lifetime, material and energy performance for production, end of life stage, and waste generation were taken in account. The evaluation was carried out using the method of life cycle assessment with the characterization model CML 2001 created in GaBi 8. The goal of the study was to identify the box with the smallest environmental impact and to identify the hotspots in the life cycles of the individual collection boxes. The results of the study show that polypropylene boxes are the most environmentally suitable for collecting small waste electrical and electronic equipment as they produce the lowest environmental impacts in all of the impact categories evaluated, while boxes made of stainless steel have been found to represent the least environmentally friendly option. The results of the study provide and suggest to the collective system basic data for choosing the type of collection box.