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Waste generation is a continuous process that needs to be managed effectively to ensure environmental safety and public health. The recent circular economy (CE) practices have brought a new shape for the waste management industry, creating value from the generated waste. The shift to a CE represents one of the most significant challenges, particularly in sorting and classifying generated waste. Addressing these challenges would facilitate the recycling industry and helps in promoting remanufacturing. But in the COVID times, most of the generated waste is getting mixed with conventional waste types, especially in the global south. The pandemic has resulted in colossal infectious waste generation. Its handling became the most significant challenge raising fears and concerns over sorting and classifying. Hence, this study proposes an Artificial Intelligence (AI) based automated solution for sorting COVID related medical waste streams from other waste types and, at the same time, ensures data-driven decisions for recycling in the context of CE. Metal, paper, glass waste categories, including the polyethylene terephthalate (PET) waste from the pandemic, are considered. The waste type classification is done based on the image-texture-dependent features, which provided an accurate sorting and classification before the recycling process starts. The features are fused using the proposed decision-level feature fusion scheme. The classification model based on the support vector machine (SVM) classifier performs best (with 96.5 % accuracy, 95.3 % sensitivity, and 95.9 % specificity) in classifying waste types in the context of circular manufacturing and exhibiting the abilities to manage the COVID related medical waste mixed.

Despite being a popular policy tool to promote household waste separation in local communities, role model strategies have been shown to achieve only mixed success so far. The reasons for their varied performance are not clearly understood. The present study aims to address this important issue by exploring how the influence of role models varies with the social, economic, and demographic features of local residential areas. Interrupted time series analyses of monthly observations of public participation in a large waste sorting program in Hangzhou, China have been conducted to test the theoretical propositions. The results show that role models increased the overall program participation level by 5.3%. This positive influence was greater in areas with stronger group cohesion, higher economic level, and a younger population. However, role models had a minimal effect among people with a low contribution predisposition. These findings demonstrate that the influence of role models on household recycling depends significantly on local contexts and personal idiosyncrasy, implying ways to improve the effectiveness of role model strategies in motivating residents’ sustainable behavior.

It is generally accepted that governments, municipalities, businesses and citizens alike have a role to play in transitioning towards a circular economy (CE). Yet most academic and policy discussions of CE revolve around technological solutions and business models. Although CE also means significant changes to ways of living, these aspects of CE are barely addressed. The citizen role is traditionally assumed to be that of a consumer or user of the newly developed solutions, while also following the guidelines for sorting and recycling. Little is known about how citizens envision being part of the CE, and what skills and competences are relevant for CE. Our study addresses this gap by exploring the perceptions of young adults in Finland on how CE reflects into their everyday lives. Our dataset consists of 249 responses from high school students in Finland to open-ended questions regarding CE. The results highlight that young adults in Finland strongly associate CE with recycling, waste sorting and re-selling/buying second-hand, which is in line with the conventional roles of efficient recyclers and consumers. Although CE harbors wider potential for more active citizen roles related to repair, maintenance and upcycling, these aspects are often overlooked in favor of more familiar lifestyles. Building on the 5R framework for CE and emerging themes from student responses, we bring forward the new roles of upcycler, thrifter, expert/learner, giver/benefactor and conservationist. Supporting these emerging roles is an opportunity for cooperation between young adults, other citizen groups, cities, policy makers and businesses, and a key for jointly advancing the transition to CE. (c) 2021 The Authors. Published by Elsevier B.V. on behalf of Institution of Chemical Engineers. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) peerReviewed

With the economy growing rapidly, as well as the increasing diversification of human material and cultural needs, waste management poses a pressing challenge for local authorities in China. The primary aim of the present study is to examine the determinants of household waste-related behaviors, especially focusing on the roles of two important social interaction-based factors, social norms and networks, and their combinations. Specifically, this paper adopted the method of principal component analysis to capture social interactions and leveraged ordered logit models to explore their influences on the behaviors involving waste sorting, bringing their own shopping bags and reusing plastic bags in other aspects. Using the data from the Chinese General Social Survey in 2013 (CGSS2013), the results reveal that both social norms and social networks exert a significant positive influence on pure altruistic waste sorting while only social norms are positively associated with bringing their own shopping bags to store and reusing bags in other aspects with the nature of impure altruism. Meanwhile, there is no convincing evidence for the interaction effect between social norms and social networks on waste sorting, yet the interaction item does work together negatively influencing bringing their own bags and reusing bags behaviors. Moreover, the results show that social norms have a much larger effect on waste-related behaviors in males than females while social networks lead to significant promotion in waste sorting only for females. For people with higher education levels, the impacts of social norms and social networks on waste sorting and bringing their own bags behaviors are insignificant, while the higher income groups are weakly affected by social networks as well, partly because of time constraints and opportunity cost. Lastly, this paper provides new insight into waste management from the perspective of social interaction.

Waste sorting is being gradually implemented as a key measure for circular and sustainable development in China, food waste will be separately collected and separated from municipal solid waste (MSW), thus the plastic content in food waste also will be reduced. In this study, supercritical water gasification (SCWG) of food waste with different contents of plastic (0–3.5 wt%) was experimentally investigated to simulate the influence of waste sorting on the food waste treatment. The results showed that lower plastic content in food waste favored higher gas yield and gasification efficiencies. The highest H2 yield and total gas yield were 3.11 mol/kg and 8.41 mol/kg in the plastic-free case, respectively. When the plastic content decreased from 3.5 wt% to 0 wt%, the cold gas efficiency (CGE), carbon conversion efficiency (CE) and hydrogen gasification efficiency (HE) increased by 125.97%, 173.48% and 94.09%, respectively. However, lower plastic content negatively affected the quality of produced syngas through decreasing H2 mole fraction and LHV. The solid residues from SCWG of food waste with lower plastic content had higher ratio of fixed carbon to volatile matter (FC/VM). Based on the analysis of pyrolysis properties and combustion behavior, decreasing the plastic content in food waste helped to improve the thermal stability of solid residues. Moreover, lower plastic content resulted in a decrease of total organic carbon (TOC) concentration in liquid effluent, which is favorable for further treatment of liquid effluent.

Considering the importance of waste sorting and treatment in the development of an ecological civilization, empirically evaluating the environmental impact of such programs is particularly important. This study uses Xiao'er Township in Gong County, Sichuan Province, China as a case study to analyze and estimate the carbon emission reduction effects of the township's pilot waste sorting program. Using the five-point sampling method, samples of waste are collected, reviewed, and measured for their major components and other key indicators. Additionally, questionnaire surveys and interviews are conducted in the township, along with investigations into existing records and other relevant information. The study adopts the solid waste management-greenhouse gas (SWM-GHG) calculator to study the township data. The case study results imply that proper waste sorting and treatment methods in villages and townships could play a major role in the reduction of carbon emission. Specifically, after implementing waste sorting in Xiao'er, annual carbon emissions were reduced by 2081 tons—equivalent to the electricity consumption of a family of three people for 1718 years, or the amount of CO2 emitted by 264 1.6L vehicles driving once around the Earth. In the optimal scenario simulation, increasing the recycling of wet waste and recyclable waste further, the level of carbon emission reduction in Xiao'er could reach up to 4482 tons per year. According to the international general carbon trade price, this is equivalent to adding 44,820 US dollars to the GDP, or to an annual saving of 5.71 million kWh. If these waste management methods are expanded to villages and townships across China, then the carbon emissions reduced in a year would be equal to the CO2 emitted from electricity generation in Beijing for over a year. Based on these findings, this paper provides three policy recommendations for effective carbon emission reduction: increasing residents' environmental protection awareness over the long term, boosting funding support and enhancing the construction of supporting facilities, and strengthening governance and institutional capacity for waste sorting and treatment.

In China, waste sorting practice is not strictly followed, plastics, especially food packaging, are commonly mixed in food waste. Supercritical water gasification (SCWG) of unsorted food waste was conducted in this study, using model unsorted food waste by mixture of pure food waste and plastic. Different operating parameters including reaction temperature, residence time, and feedstock concentration were investigated. Moreover, the effect of three representative food additives namely NaCl, NaHCO3 and Na2CO3 were tested in this work. Finally, comparative analysis about SCWG of unsorted food waste, pure food waste, and plastic was studied. It was found that higher reaction temperature, longer residence time and lower feedstock concentration were advantageous for SCWG of unsorted food waste. Within the range of operating parameters in this study, when the feedstock concentration was 5 wt%, the highest H2 yield (7.69 mol/kg), H2 selectivity (82.11%), total gas yield (17.05 mol/kg), and efficiencies of SCWG (cold gas efficiency, gasification efficiency, carbon gasification efficiency, and hydrogen gasification efficiency) were obtained at 480 °C for 75 min. Also, the addition of food additives with Na+ promoted the SCWG of unsorted food waste. The Na2CO3 showed the best catalytic performance on enhancement of H2 and syngas production. This research demonstrated the positive effect of waste sorting on the SCWG of food waste, and provided novel results and information that help to overcome the problems in the process of food waste treatment and accelerate the industrial application of SCWG technology in the future.

This study has demonstrated the use of weighted-linear-combination approach in connection with fuzzy set functions of Total Population, Total Distance, Annual income per person and Total number of opening hours of Recycling Centers (RCs), in ArcGIS environment, to generate risk maps and characterize RCs based on risk for improper sorting of waste. Analysis of data shows that there are 73 RCs, at which, risk for improper sorting of waste is highest. On average, there is one RC for every 19,402 individuals in Sweden and a single round trip made by Swedes to nearest RC, results in emission of 1340 ktons of CO2. Furthermore, it is found that strategies needed (e.g. installation of new RCs or shifting of RCs closer to densely populated areas (DPAs) or increase in number of opening hours or availability of pre-visit sorting information etc.), to reduce risk for improper sorting of waste, are different for RCs that are operated under different management forms. Variations in tariffs, limited number of waste fractions to be collected per RC, confusing terminologies, design parameters of RCs and non-implementation of EU Directive 2018/851 with respect to packaging waste, are other factors that are affecting quality of waste sorting at RCs, and are discussed in the article. Results from this research can be utilized to identify site specific needs for improving sorting of waste and to identify priority areas for installation of new RCs.

Although a plethora of research has been conducted to investigate the economic performance of construction waste (CW) management, the vast majority of studies have concentrated on the economic feasibility of CW recycling, while ignoring the economic performance of CW reduction strategies and measures. Moreover, previous studies mostly focused on one specific waste stage for waste reduction, failing to envisage dynamic interactions among various factors inherent in different waste management stages including waste generation, on-site reduction, and waste disposal, which inevitably affects the effectiveness of implementing those management strategies. To address these research gaps, this study developed a system dynamics model to investigate the economic performance of CW reduction. The model is constructed based on the interrelationships of major factors affecting the economic performance of CW reduction and comprises three subsystems covering waste generation and disposal, waste reduction, and economic performance assessment. Data from a residential building project were used for model validation and simulation. The findings reveal four strategies to effectively promote the economic performance of CW reduction, including: enhancing waste sorting, reducing illegal dumping behaviors, promoting government's financial subsidy on waste recycling, and raising waste landfilling charge. Furthermore, model simulations inform that combining different waste reduction strategies could result in better outcomes than a single measure regarding CW reduction. This study is significant in revealing the interrelationships of factors affecting the economic performance of CW reduction. Meanwhile, the results are helpful for designing policies to improve CW reduction practice.

Construction waste includes waste arising from construction works such as new build, renovation, demolition and road works. Through waste sorting and separation, inert material can be used to fill in reclamation sites; however, the non-inert portion of the construction waste still goes to landfills. However, Hong Kong is running out of landfill space. When determining reduction and management strategies for construction waste, the Government's objectives are to reduce waste generation, maximize reusing and recycling and reduce the intake of mixed construction waste at landfills. In order to develop and implement the waste reduction and management strategies at project level, proper quantification of construction waste generation is a prerequisite. Our research reveals that limited information is currently available for understanding the magnitude and composition of construction waste and for preparing an appropriate construction waste management plan for a project on new or existing facilities. To bridge the gap, the aim of this research is to present a comprehensive and practical approach for estimating the construction waste for building projects once detail design is carried out for new build or major retrofitting works. The estimation of waste quantities is based on the actual design information available from tender or contract documentation for a project at the upstream stage (a full set of bills of quantities classified under standard format). The proposed methodology of aggregating wastages accruing to quantified elements for a complete building has its advantages over a ball park figure established through indexing or other methods as proposed in existing literature, in terms of ensuring accuracy and maximizing the use of available design information whilst the workflow is uninterrupted. Three representative case studies with different formwork and facade systems are depicted to highlight the significant effects on waste generation in otherwise similar construction projects.

We study the effect of visibility of individual action on free riding using field data on household waste sorting. In our sample households pay an annual fee proportional to the number of emptyings of their bin for unsorted waste. We exploit the variation in the bin sharing policy to estimate the production of unsorted waste when bins are shared or not. We find that unsorted waste production is lower when two households share the same bin compared to households not sharing the bin. This result does not hold when more than two households share the same bin, possibly due to lack of visibility of the individual action. We interpret this evidence as suggesting that peer monitoring can promote virtuous behavior when monetary incentives cannot be used to solve social dilemmas.

There is a notable discrepancy between intention on household waste sorting and the actions taken to support this environmental initiative among residents in China. This study aims to explore the influences of personal attitudes, facilities accessibility, and government stimulus on this discrepancy. Built on an integrated framework of Theory of Planned Behaviour (TPB) and Norm Activation Model (NAM), this study examines the relationship between intention and household waste sorting behaviour considering the psychological behavioural antecedents and circumstantial constraints among Chinese residents. Results from a questionnaire survey administered in China confirm the discrepancy, and show that the link between intention and behaviour on waste sorting is weakened after adding the influencing paths from the factors of facilities accessibility and government stimulus to waste sorting behaviour: however, the presence of these two factors directly promote waste sorting behaviour, but do not moderate the intention-behaviour relationship as their interaction items with behavioural intention are not significantly related to waste sorting behaviour. Furthermore, the personal norm is found to be the major factor influencing intentions of Chinese residents towards waste sorting while both subjective norms and perceived behavioural control were unexpectedly found to have no significant influence thereon. These findings are useful for promotion and planning of waste sorting by policy-makers to ease the waste disposal problem.

Automatically waste sorting is usually resorted to robot arm to grasp solid waste. However, the solid waste is prone to being stacked up, and they are difficult to segment and consequently to be grasped. To resolve this problem, we present a novel spatial adaptive projection method based on only one RGB-D sensor to accurately segment the piled solid waste. Through the RGB-D sensor, the point cloud of waste is obtained firstly. Then it will be projected into different planes to get an optimized image which is easy to be segmented. The projection parameters are automatically computed based on a mathematical optimization framework. After segmenting stacked waste into several isolated objects, we re-project them into the point cloud. We evaluate the effectiveness and accuracy of our method in a large dataset of stacked solid waste, the results shows the performance of the proposed method is satisfactory.

Economic growth and rapid urbanization have resulted in various urban problems related to sustainable development. The continuous increase in household solid waste has become a significant concern worldwide, while waste sorting has been regarded as an effective method for waste reduction. However, the low recycling rates of household solid waste are common in many countries. Accordingly, our study used theory of planned behavior (TPB) to construct a “motivation–intention–behavior” theoretical model for the systemic illustration of the antecedents of household solid waste sorting behavior. A comparative study was performed to explore the similarities and differences between the determinants of sorting behavior in Shanghai and Singapore. A survey of 1100 urban residents from these two places was conducted to validate our model by using structural equation modeling. Findings indicated that general and specific environmental motivations substantially influenced behavioral intention. Moreover, the direct influence and moderating effect of contextual factors on waste sorting behavior are significant. Habitual factors also have a significant effect on behavior. Our study enhanced the understanding of the determinants of household solid waste sorting behavior and improved TPB by simultaneously adding motivation, contextual, and habitual factors. Moreover, our study used theory of environmental interventions as basis to provide several suggestions that will improve existing policies. These suggestions can be valuable references for waste management in megacities.

Continuously increasing municipal solid waste (MSW) generation, which has resulted in serious environmental pollution, resource consumption, and health problems, requires a disposal stream for improved recycling and reuse. In this study, a novel methodology is proposed that combines advanced “hard path” technologies and “soft path” policy to facilitate an effective and sustainable waste-to-energy approach. Multiple tech-economic MSW cascaded systems were established and combined for MSW terminal treatment, and a subsidy policy was applied to waste source management. Furthermore, an MSW reverse supply chain (MSWRSC) was proposed that integrates waste source and end treatment management, and a multi-objective mixed-integer dynamic model was established to optimize the MSW treatment process by achieving cost control, carbon emission reduction, and job creation. A practical case study was then conducted to provide the analysis paradigm including the system deployment and facilities operation. Further, some important conclusions and suggestions are summarized for reference by the local government and facilities. Therefore, the methodology that combines the cascade treatment systems with policy instruments shows important theoretical and pragmatic significance for the multi-dimensional sustainable development of MSW management.

This intervention study examined (1) the influence of household waste separation on other pro-environmental behaviors (behavioral spillover), (2) possible psychological mechanisms involved in such spillover, and (3) if the two waste separation interventions (environmental appeals vs. monetary incentives) differed in shaping spillover. Results showed that both strategies increased waste sorting behavior, which positively spilled over to other pro-environmental behaviors. However, no evidence was found for the hypothesized spillover mechanisms of pro-environmental identity, environmental concern, and relief of guilt, and the two external treatments did not significantly differ in their moderating effects on spillover. In addition to spillover, a positive pathway through changes in environmental concern was found for the environmental framing, while a negative pathway through changes in pro-environmental identity was found for monetary incentives. Overall, the findings indicate both behavioral spillover and other pathways to be responsible for the effects of two waste separation strategies on non-target environmental behaviors.

Musculoskeletal disorders are common among waste workers but preventative effort is lagging behind. This exploratory study assessed trunk posture during waste sorting tasks via statistical and experimental means. Posture exposure exceeded levels previously shown and related to elevated risk of Low Back Disorders (LBD). Results show predisposition of waste workers to LBDs.

Pyrolysis of plastic packaging waste yields a liquid product that can be processed in steam crackers producing light olefins and hence closing the loop towards new virgin plastics. However, there is a lack of knowledge on how the plastic waste composition affects the pyrolysis oil quality regarding hydrocarbon composition and contaminant concentrations. The associated uncertainty is a key reason why thermochemical recycling of contaminated plastic waste is not yet industrially established. In this study, post-consumer plastic packaging waste fractions, namely mixed polyolefins (MPO), polyethylene (PE), and polypropylene (PP) were processed in a continuous pilot-scale pyrolysis unit and the pyrolysis oils subsequently characterized using advanced analytical techniques such as two-dimensional gas chromatography. Substantial amounts of branched olefins (~63 wt%) and diolefins (~20 wt%) were detected in the pyrolysis oil of PP-rich waste, while PE-rich waste produced high amounts of linear paraffins (~34 wt%) and olefins (~26 wt%). Furthermore, significant amounts of nitrogen, oxygen, chlorine, iron, sodium and silicon were detected in the pyrolysis oils exceeding feedstock specifications for industrial steam crackers by orders of magnitude. The results show that next to improved waste sorting and separation processes, pre- and post-treatment techniques are required to produce pyrolysis products suitable for chemical processing.

Food waste produces methane in landfills, accounting for 1.5–2.0% of net global anthropogenic greenhouse gas emissions in 2010. In developing countries 40–65% of household waste can be food waste, especially from preparation, since pre-prepared food is less common. Different waste management strategies are used worldwide to get householders to separate out their food waste, including the restriction of permitted times and places for depositing household waste (e.g. 6–7pm daily at kerbside, only). Here we evaluate a Certain Time, Certain Place (CTCP) intervention used across a sample of six communities randomly allocated from a cohort in one district of Shanghai. Mixed methods are used, with directly-measured tonnages pre- and post-implementation, and site observations and open interviews of stakeholders to elicit perceived relevant factors. Quantitative results show no statistically significant impact on waste sorting performance. Relevant themes which emerged are: time period arrangements; supervision of waste stations; attitude of the assistant cleaners. These are shown to be related to known determinants of Inconvenience, Role clarification, and Positive interactions. Action Planning and Stakeholder Engagement are suggested as mitigators of Inconvenience, but Distance not found relevant. Such deconstruction of policy elements into scientific factors allows a clear scientific perspective: that this CTCP program was almost pure CT only, which increased Inconvenience without giving overall benefits from increasing supervision. Only one community had CP involved, and its performance increased significantly, suggesting CP should be studied further. In sum, this Certain Place, Certain Time recycling program was actually CT, and is not recommended for increasing food waste sorting performance. The more direct linking of policy elements to scientific factors is suggested as useful for better future design.

As an important approach for individuals to participate in environmental conservation and contribute to the public good, waste sorting is deeply embedded in and influenced by the social context. Social capital serves as less costly but effective resources dealing with social problems including waste management, but there is also evidence suggesting that different dimensions of social capital lead to divergent behavioral outcomes in waste sorting. Meanwhile, recent research highlights the mixed effects of preexisting environmental norms and argues that they can either encourage or mitigate waste separation. Drawing upon the literature on social capital and environmental norms, the current study examines the extent to which the structural and cognitive dimensions of social capital, social networks and generalized trust, impact individual participation in waste sorting and the effects of network- and contextual-level environmental norms in these processes. Multilevel analyses of nationally representative data from China suggest that both dimensions of social capital facilitate individual engagement in waste sorting, and these positive relationships function mainly through the pro-environmental norms in the networks. Additionally, contextual-level environmental norms are found to promote individual waste sorting as well as reinforce the connection between environmental norms in personal networks and waste separation, but mitigate the positive effects of social networks and generalized trust. The findings suggest that social capital does not automatically lead to waste sorting behavior and whether there is a positive effect is contingent on the preexisting environmental norms across different levels.

Despite the ubiquity of waste disposal in urban environments, there is little standardization of receptacle or signage design within and across jurisdictions. In three experiments, we explored the impact of waste disposal signage design on disposal behavior. Specifically, we were interested in two primary questions in signage design: 1) what type of waste disposal information should be presented; and 2) how the information should be presented. We found that signs containing either icons or pictures of permitted items improved sorting performance compared to signs containing only words of the items; consistent positioning of the signs improved sorting performance compared to random positions for both pictures and icons; and presenting both permitted and prohibited items can interfere with performance when the signs are icons. The current study provides experimental evidence to demonstrate that the design of waste disposal signage can impact waste sorting performance in meaningful ways and highlights the need for graphical signage and bin standardization.

This study contributes to developing a set of engagement factors to address waste mishandling and enhances waste sorting intention in households. Prior studies do not specify a set of factors to mobilize and empower households toward better waste sorting engagement. In addition, in Ecuador, waste separation rates are low, and household waste sorting reduces the separation efforts at collection facilities to increase the recycling efficiency for sustainable plastic waste management strategies. This study adopted the theory of planned behavior to understand waste sorting engagement factors, and the factors are described in qualitative information and linguistic preferences. Hence, this study applied the fuzzy Delphi method to screen out the less important attributes and fuzzy decision-making trial and evaluation laboratory to visualize the interrelationships among attributes. This study finds that waste sorting capacity is driven by environmental attitudes, perceived convenience, social norms and economic drivers. The results also indicated that households’ environmental attitudes, perceived convenience and economic drivers are causal factors that drive waste sorting engagement. For practitioners, separation knowledge, willingness to participate, pro-environmental decisions, and social responsibility arrangements are the driving criteria for improving waste sorting engagement and reducing and eliminating pollution. Theoretical and practical implications are discussed.

Effective waste administration is one of the major environmental issues of the present time. The isolation, taking care of, transportation and transfer of waste is to be appropriately overseen in order to limit the hazard to nature. The efficient estimation of waste is best acknowledged when it is isolated. The customary method for physically isolating the waste uses exertion that is more human, time and cost. This work proposes a waste tracking system with integrated waste sorting mechanism, which is an easy and economical way to segregate and track domestic waste. It is intended to sort the domestic waste into metallic, plastic and glass categories. After segregation, the tracking system informs the server how much waste each household is producing. Along these lines, a successful framework for waste management is made helpful for recycling procedures for better environmental cleaning ecosystem with proper waste management operations.

Understanding the intention and behavior of individual is crucial to the effective implementation of waste sorting. Previous scholars mainly studied it through questionnaire research. This approach has a limited sample size, and the real behavior is difficult to quantify. In this paper, 180,417 drop-off data from 13,047 college students in the backend of Internet of Things (IoT) bins are analyzed in conjunction with 320 questionnaires. Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB) and Norm Activation Model (NAM) are used together to analyze college students' waste sorting behavior. The results are as follows: (1) College students sort 0.426 kg recyclable waste per (person · week) in the investigated community, and the drop-off frequency of pre-class and mealtime is 46% higher than usual. (2) Due to the pressure of subjective norms, 75% of respondents reported a 220% higher frequency of 3–8 occasions per week than the actual situation. (3) The current incentive level (1 kg recyclables can exchange for a reward equivalent to 9 cents) cannot significantly regulate the relationship between waste sorting intention and behavior. (4) IoT and questionnaire data show that perceived ease of use could directly promote waste sorting intention and behavior. The findings provide a scientific basis for effectively improving the waste sorting behavior of the public.

Waste sorting behavior is an important factor in reducing raw material usage through recycling programs and seeking circular economy implementation. Despite huge efforts to promote sorting behavior, in Lithuania 6 percent do not sort waste at all. The main tools which can promote this behavior are informational, social, convenience and financial. However, to the best of our knowledge, no research has analyzed the impact of all these tools on sorting behavior: this analysis revealed which tools were the most effective and to which policymakers should pay the most attention. Furthermore, we analyzed whether the identified tools really contribute to waste sorting behavior, including statements about the current situation in the model. Therefore, the aim of this paper was to investigate the impact of informational, social, convenience and financial tools – and the real situation – on waste sorting behavior. Referring to a representative survey conducted in Lithuania, the results showed that, according to respondents, only informational and financial tools had significant impact on waste sorting behavior, which was insignificantly affected by social and convenience tools. Considering the real situation, the current situation of convenience and social tools significantly influenced waste sorting behavior. Meanwhile, the current level of the informational aspect negatively and insignificantly determined waste sorting behavior. Therefore, this study provided practical insights for policymakers into which tools contribute to waste sorting behavior, and how to promote it effectively.

This study aimed to compare the environmental performance of building construction waste management (CWM) systems in Hong Kong. Life cycle assessment (LCA) approach was applied to evaluate the performance of CWM systems holistically based on primary data collected from two real building construction sites and secondary data obtained from the literature. Different waste recovery rates were applied based on compositions and material flow to assess the influence on the environmental performance of CWM systems. The system boundary includes all stages of the life cycle of building construction waste (including transportation, sorting, public fill or landfill disposal, recovery and reuse, and transformation and valorization into secondary products). A substitutional LCA approach was applied for capturing the environmental gains due to the utilizations of recovered materials. The results showed that the CWM system by using off-site sorting and direct landfilling resulted in significant environmental impacts. However, a considerable net environmental benefit was observed through an on-site sorting system. For example, about 18-30kg CO2 eq. greenhouse gases (GHGs) emission were induced for managing 1 t of construction waste through off-site sorting and direct landfilling, whereas significant GHGs emission could be potentially avoided (considered as a credit -126 to -182kg CO2 eq.) for an on-site sorting system due to the higher recycling potential. Although the environmental benefits mainly depend on the waste compositions and their sortability, the analysis conducted in this study can serve as guidelines to design an effective and resource-efficient building CWM system.

Seeing that Shanghai implemented mandatory household waste sorting system (referred as Shanghai Model) in 2019 and achieved remarkable improvements, the study focuses on how to localize it in second-tier cities. Specifically, by applying system dynamics method, a qualitative Basic Model and a quantitative Shanghai Model simulating residents’ waste related behavior are built. Combined Theory of Planned Behavior and the Split-Core Model are adopted. Data of Zhengzhou is inputted and simulated to representatively deliver policy implications to second-tier cities. The result shows that improving transactional context can lift the weight of willingness and depress the weight of opportunism in behavior decision makings. Shanghai Model significantly improves the legal transaction context of waste sorting which make residents actively sort the wastes under the promotion of willingness. For second-tier cities of China, improving transactional context to reduce opportunism and conquering the short board of willingness to promote active participation are indispensable. And, waste reducing measures like the unit pricing system are recommended to make up the shortage of the Shanghai Model. The study puts forward a synthetic analyzing framework of waste related behaviors and builds a portable policy analyzing system of waste management for both China and other developing countries.

This study aims to improve the accuracy of waste sorting through deep learning and to provide a possibility for intelligent waste classification based on computer vision/mobile phone terminals. A classification model of recyclable waste images based on deep learning is proposed in this paper. In this waste classification model, the self-monitoring module is added to the residual network model, which can integrate the relevant features of all channel graphs, compress the spatial dimension features, and have a global receptive field. But the number of channels is still kept unchanged; thereby, the model can improve the representation ability of the feature map and can automatically extract the features of different types of waste images. The proposed model was tested on the TrashNet dataset to classify recyclable waste and compare its classification performance with other algorithms. Experimental results show that the image classification accuracy of this model reaches 95.87%.

Waste sorting facilities rely heavily on plentiful human labour, and the lack of adequately designed work systems leads to musculoskeletal disorders among the workers. The present research explores the ergonomic design aspects of a cost-effective intervention, a work table for waste sorting in developing countries. This study evaluates the appropriate range of work height for the sorting tasks and proper location of hoppers to drop the sorted items. The ergonomic assessment was conducted by simulating postures involved in sorting tasks in a virtual environment and performing a biomechanical evaluation of the static postures by digital human modelling. Thirty male subjects from Indian population simulated the postures of sorting tasks. The compressive force at L4/L5 intervertebral disc, shoulder flexion moment, shoulder abduction moment, and elbow flexion moment were taken as the indicative parameters of the subject's physical workload. The appropriate table height was marginally lower than the elbow height of the subject and within 4 cm. The preferred hopper position was on the floor adjacent to the worker compared with the hopper on the top of the table.

The classification of municipal household waste is a complex, adaptive system containing multiple agents, where behavior between the agents is interactive. This study focuses on the willingness of bounded, rational individuals to sort waste within complex social networks, and the evolution of group behavior. An individual cognition-behavior model was established, based on the theory of planned behavior. In this model, the intention underpinning individual waste classification is influenced by the behavioral attitude of the individual, perceived behavioral control, subjective norms, and perceived behavioral results. A multi-agent-based simulation within a social network based on the opinion propagation dynamics and a scale-free network was developed to simulate the behavior change of the agents. The results suggest that under the principle of selective connection and the hypothesis of network growth, the clustering trend of the whole network towards several central nodes becomes increasingly apparent; this means, the degree of network node centralization becomes clear. Lowering the threshold of social information interaction improved the transmission of waste classification information and increased the proportion of urban residents who carry out waste classification. Economic profits and spiritual satisfaction were considered important driving factors that impacted decision-making on waste classification, and effectively stimulated the willingness of urban residents to implement waste sorting behavior. Notably, official organizations and institutions, that is, influencers with higher connectivity were found to have a greater influence on the decisions made by residents. These findings are useful as a theoretical reference to inform the development of waste management policies.

The vast output of household waste has become a terrible environmental problem with the rapid growth of social development and population in China. Several pilot cities have introduced related policies to regulate urban residents in sorting household waste. Although existing research has concentrated on sorting waste intentions and behaviours amongst urban residents, especially in pilot cities or other large cities, waste produced in non-city areas should not be neglected. Accordingly, this study identified the determinants influencing waste sorting intentions and behaviours of residents in rural or urban–rural integration areas by incorporating the theory of planned behaviour and norm-activation model. A total of 241 residents completed valid questionnaires, and the collected data were empirically analysed through covariance-based structural equation modelling. Results implied that behavioural attitude and perceived behavioural control were the most significant predictors of sorting waste intention and behaviour. Meanwhile, personal moral norms and subjective norms also presented positive effects on behavioural intention. Awareness of consequence had a significant influence on personal moral norm rather than behavioural intention. After empirical analysis, this study proposed several managerial implications regarding waste problems in rural and urban–rural integration areas in China.

Pro-environmental activities, such as waste sorting, are considered inconveniencing; the higher the inconvenience, the more difficult it becomes to encourage active public participation. This study defines waste sorting behavior considering certain attributes and estimates the inconvenience costs associated with each attribute. The definition also considers how and when waste is disposed of as well as the hygiene of a disposal spot. We apply a conjoint analysis for data collection and latent class logit model to calculate the inconvenience costs. The model incorporates consumers' heterogeneity as a finite number of homogenous groups. The results show that the inconvenience cost for the hygiene of the disposal spot is generally higher than that of sorting itself; this tendency is strongest among young women. Moreover, older people report lower inconvenience costs than do younger ones. Further, some groups prefer manual sorting to an automated sorting service for food waste. Our findings offer policy implications considering such inconvenience costs.

Incineration of mixed municipal waste is gaining increasing importance in many European countries. This is also the case in several European Union member states such as Estonia, where waste-to-energy technology provides a relatively fast option to meet the demanding EU waste management targets regarding municipal waste recovery and landfilling. Furthermore, the biomass fraction of municipal solid waste, when used as a fuel for energy production, is recognised as a renewable energy source and is therefore eligible for government subsidy under Estonian legislation. Also CO2 emissions are accounted for according to their source, either as biogenic (resulting from the biomass fraction of the waste), and thus climate neutral, or as fossil, and thus liable for CO2 charges. Therefore, it is crucial that operators of waste incineration plants are able to determine the ratio of biogenic and fossil carbon in combustible waste. This paper summarises the results of the research conducted in the first waste incineration plant in Estonia and the Baltic States to determine the material composition (incl. biomass content) and the proportion of fossil CO2 emission from combusted mixed municipal solid waste. The results of a one year long manual waste sorting study and laboratory analysis show that the share of the biomass fraction is approximately 52 % in the combusted municipal solid waste (on a dry weight basis) and that fossil carbon accounts for about 40 % of the total carbon (on a wet weight bases). The associated annual average fossil CO2 emissions are about 429 kg per ton of combusted municipal waste.

Due to the increasing amount of global waste generated over the years, most countries have the urgency to implement effective household waste recycling to solve this problem. In order to develop the policy that regulates waste recycling behaviour, it is important to investigate on the external factors that may influence an individual's waste sorting behaviour and participation rate. In this paper, we examined how four possible external factors―namely market incentives, market facilitators such as informal recycling market, government incentive and government facilitators―influence waste separation behaviour of Hangzhou's residents in China. The survey questionnaire was designed based on the extension of an extant theoretical framework and literature review, and then disseminated to the households through systematic sampling in JB Street of Hangzhou, resulting in a sample size of 631 valid responses. The partial least squares structural equation modelling (PLS-SEM) was conducted to evaluate the effectiveness of each construct. Our results revealed a significant and positive correlation between all the constructs to waste separation intention except the path from market incentive to intention. We further discussed on the moderating effect of the social-demographic variables such as social influence, gender and income on recycling intention and waste separation behaviour. This study expands the understanding on perceived effectiveness of external factors that influence residents' waste separation behaviour. The findings can be extrapolated to other countries to implement effective household waste management policies.

Municipal solid waste (MSW) contains considerable hazardous components and the widely-distributed open MSW burning in heavily-populated urban areas can cause direct exposure of hazardous materials to citizens. By determining the best available representation of composition-varying and time-varying emission factors with fuzzy mathematics method and S-shape curves, a comprehensive atmospheric emission inventories of 9 typical toxic heavy metals (THMs, e.g. mercury (Hg), arsenic (As), lead (Pb), cadmium (Cd), chromium (Cr), selenium (Se), copper (Cu), zinc (Zn), and nickel (Ni)) from open MSW burning activities in China is established during the period of 2000–2013 for the first time. Further, the emissions in 2013 are allocated at a high spatial resolution of 0.5° × 0.5° grid by surrogate indexes. The results show that 9 typical THMs emissions from open MSW burning are estimated at 21.25 t for Hg, 131.52 t for As, 97.12 t for Pb, 10.12 t for Cd, 50.58 t for Cr, 81.95 t for Se, 382.42 t for Cu, 1790.70 t for Zn, and 43.50 t for Ni, respectively. In terms of spatial variation, the majority of emissions are concentrated in relatively developed and densely-populated regions, especially for the eastern, central and southern regions. Moreover, future emissions are also projected for the period of 2015–2030 based on different scenarios of the independent and collaborative effects of control proposals including minimizing waste, improving MSW incineration ratio, and enhancing waste sorting and recycling, etc. The collaborative effect of the above proposals is expected to bring the most effective reduction to THMs emissions from open MSW burning in China except for Hg. The results will be supplementary to all anthropogenic emissions and useful for relevant policy-making and the improvement of urban air quality as well as human health.

A crucial prerequisite for recycling forming an integral part of municipal solid waste (MSW) management is sorting of useful materials from source-separated MSW. Researchers have been exploring automated sorting techniques to improve the overall efficiency of recycling process. This paper reviews recent advances in physical processes, sensors, and actuators used as well as control and autonomy related issues in the area of automated sorting and recycling of source-separated MSW. We believe that this paper will provide a comprehensive overview of the state of the art and will help future system designers in the area. In this paper, we also present research challenges in the field of automated waste sorting and recycling.

The ability of economic incentives to promote environmentally friendly behavior has been questioned in the literature. Most studies investigating this issue are grounded in the agent-based rational choice model. The aim of this study is to expand our insights by applying an alternative theoretical framework combining elements from classical institutional economics and self-determination theory to study incentives for waste sorting. The analysis is based on data from a Norwegian municipality, Ulstein, which introduced and later terminated a differentiated waste fee. There are three main findings. First, the important role of normative motivation for sorting household waste is confirmed. Second, the economic incentive had a divisive effect on the motivation to sort household waste. Perceived autonomy linked to fundamental values about environmental concern seems to play an important role in explaining why half the sample reports no extra efforts in sorting waste as a response to the economic incentive. The other half was influenced by the external logic given to them (i.e., to save costs and hence report increased motivation to sort household waste). Finally, an increased practice of illegal waste disposal was observed as a response to the differentiated waste fee.

The problem of proper organization of waste management systems is becoming more and more significant these days. In Poland, regulations requiring municipalities to achieve by 2020, 50% recovery of weight fractions such as paper, metal, plastic and glass are the main factor contributing to the need to undertake new activities in the field of waste management. Waste processing takes place in complex technical systems. Modern waste processing systems are characterized by low efficiency. Currently, it is estimated that the efficiency of installations dealing with the sorting of waste does not exceed 35%. In 2015, the authors of the article carried out waste morphology in the city of Wroclaw (only selectively collected waste). On its basis, the authors established that fractions suitable for re-use accounted for 77% of the total weight of waste sent to processing plants. Despite the significant development of systems for automatic identification and sorting of waste in recent years, systems using mainly human labour are still very common. The main goal of this article is to analyse the impact of changes in the type of waste picked up on consecutive workstations on the value of indicators used to evaluate the process of manual waste sorting.

The management of Construction and Demolition Waste (C&DW) is complex and adds significantly to the overall life cycle cost of projects. On site waste sorting using technologies that automatically identify different materials has the potential to assist in classifying C&DW and reduce costs. The aim of this research was to design and describe a deep convolutional neural network (CNN) to identify 7 typical C&DW classifications (both single and mixed disposal) using digital images of waste deposited in a construction site bin (artefact). This approach emulated authentic construction site scenarios where on-site sorting is difficult. A novel design science methodology was used. The experiments delivered 94% accuracy, classifying both single and mixed C&DW. This accuracy is important on projects where on-site sorting is attempted, as in practice bin contamination escalates project costs and reduces C&DW diversion from landfill. To illustrate potential of the research the innovative artefact is incorporated within a hypothetical case study describing its use in a circular C&DW business model.

The smart management of radioactive waste by deep learning technology is becoming of great concern, as it could decrease the workload and errors of workers in categorizing radioactive waste, thereby reducing the waste volume. In this paper, we try to maximize the efficiency of categorization for new or temporary workers instead of skilled workers by training the categorization using deep learning technology. The waste recognition system based on the deep learning technology was trained with a total of 86,084 images for 50 epochs with a subdivision of 8 and a batch of 128, which were extracted from video data that were taken in a waste sorting site. The image recognition was applied for four typical radioactive wastes (vinyl, rubber, cotton, and paper) with no object with hands (no object) and without hands (empty). The waste recognition was tested with a total of 21,521 images to evaluate the accuracy. It was determined that the accuracy of the image recognition with a deep neural network was 99.67%.

Waste sorting is the most crucial step in the success of waste management. Recently in Beijing, a series of regulations have been introduced to promote the household’s adoption of waste sorting. While these regulations matter, it is necessary for policymakers to better understand why and why not people intend to adopt waste sorting. The purpose of this paper is to investigate the influence of residents’ awareness of benefits and difficulties on the waste sorting intention and how policy plays a role in determining residents’ intention to adopt waste sorting. Drawing upon the Theory of Reasoned Action, a conceptual framework is tested on a sample of Chinese residents in Beijing (n = 267) using hierarchical multiple regression analysis. Results reveal that there is a positive relationship between resident’s awareness of benefits and their waste sorting intention. However, there is a negative relationship between resident’s perceived difficulties and their intention to engage in waste sorting. These findings are found to be contingent upon the extent of perceived policy effectiveness. The findings of this study provide environmental policymakers with not only insights into reasons behinds residential waste sorting intention but also several recommendations in promoting waste sorting among the residents. This study also suggests policymakers to carefully design effective waste sorting policies by highlighting the benefits and lessening the difficulties.

A large, successful, residential food waste sorting (recycling) program in urban high-density housing was studied to elicit perceptions of the key elements of its success. An embedded mixed-methods approach was used with rigorous quantitative measures of weights and compositions of the waste to confirm the success of the program, combined with in-depth semi-structured interviews of stakeholders to reveal their opinions of the elements key for success. The program produced a 70% food waste capture rate slowly decreasing to 45% over 54 weeks, with

Household waste, as an inevitable result of daily activities, has attracted increasing attention, especially as it affects sustainable development. It is important to study the household waste separation behavior of individuals. Based on the theory of planned behavior, an extended theoretical model is constructed that considers perception of the outcomes in household waste separation to better illustrate individual behavior in waste separation. A comprehensive analysis is performed to explore the dynamic spread of pro-environmental and household waste separation information by conducting empirical research from 259 online questionnaires and a simulation of the evolution of household waste separation behavior in social networks. The dynamic spread of pro-environmental and household waste separation information influences the intention to sort waste, which determines waste sorting behavior. An analysis of the questionnaire data shows that considering others’ advice and perception of the behavioral outcomes has a significant influence on the intention to separate waste. Moreover, the impact of media publicity on the individual intention to sort waste is negative, indicating a need to improve the quality of propaganda. The simulation findings also advocate for enhancing the connection of people in the network, making policies that set appropriate penalties and increasing personal repayment by emphasizing three parameters: the information interaction threshold value, penalty-promoting parameter, and personal motivation parameter. Our study enhances the understanding of the evolutionary process of household solid waste separation behavior and provides several suggestions for improving existing policies, and this study can serve as a valuable reference for waste management in social networks.

This paper presents a successful application of one-dimensional convolutional neural networks (1D CNNs) for waste sorting at source based on acoustic data. Most of the existing methods use images for waste classification, which causes a high computational complexity and requires a huge amount of training data. Acoustic data have also been employed due to its high correlation to the waste material type. The traditional approaches usually use fixed and handcrafted features extracted from acoustic data. Finding efficient features is usually time consuming and could be difficult in complex situations. In this paper, the 1D CNN method is proposed to automatically extract features from acoustic data and achieve high classification accuracy. Orthogonal experiment method is applied to optimize three key hyper-parameters of the 1D CNN structure. The experiment shows that the proposed method can achieve 92.40% classification accuracy within a short time. A traditional method using handcrafted features with a shallow classifier is taken as a benchmark and the attained classification accuracy is only 81.92%. In addition, a classification accuracy rate of 68.06% is achieved when using a shallow classifier with raw acoustic data as input. Therefore, the proposed method is promising to be practically applied in the trash bins for automatic waste source separation.

The sorting and recycling of municipal household waste (MHW) as a complex adaptive system is becoming increasingly popular in current research. However, traditional simulation modeling ignores the important influence of anticipated regret and personality traits on individual choice behavior. This study introduces the degree of regret-joy in agent-based simulation modeling and designs a learning rule that takes into account the personality characteristics of individuals, their neighbors, and historical information to analyze the waste sorting behavior of municipal residents. The results suggest that the number of people participating in formal recycling approaches is significantly higher than informal recycling approaches after accounting for the economic profits of formal recycling approaches. Our results also reveal that subsidies are an important factor influencing the waste sorting behavior of municipal residents. However, simply reducing the time required for a formal recycling approach does not affect the behavioral decisions of municipal residents. Only improving the accessibility of facilities in formal recycling approaches on the premise of regulating the informal recycling market, will the number of municipal residents participating in the former increase significantly. The intensity of communication and learning among municipal residents also affects the volatility of decision-making. When intensity is high, group decision-making changes greatly, but at low intensity, group behavior tends to be stable. These findings are useful as a theoretical reference for the development of waste management policies.

Factors promoting satisfaction and engagement with waste sorting were investigated. An extended theoretical model was established by integrating the theories of consumer satisfaction and customer engagement, rather than customer loyalty. Full replies to 672 valid questionnaires were obtained from respondents in 31 Chinese provinces. This paper explored how the perceived value of waste sorting, sorting facilities, income, age, and education affect waste sorting satisfaction. This paper also analyzed the effect of satisfaction on engagement in terms of enthusiasm, social interaction, and active participation by region and gender using multiple-group structural equation modeling (SEM). The results revealed perceived value of sorting and good sorting facilities can enhance satisfaction. Satisfaction can enhance enthusiasm, social interaction, and active participation. Education level, income and age would influence satisfaction and three dimensions of engagement: enthusiasm, social interaction and active participation. Waste sorting satisfaction affected enthusiasm, social interaction, active participation to a greater extent in eastern versus middle and western regions of China. It is important to provide market-incentives, such as green points reward, deposit refund, to promote household waste sorting.

This article aims to analyze the risk of waste-fires in Sweden, using the national data of fire anomalies (13,053 fire hotspots), remotely sensed by the NASA's Visible-Infrared-Imaging-Radiometer-Suite (VIIRS). Risk of fires was studied at 1,837 waste storage sites of eight different categories: (a) waste-collection (520); (b) pre-treatment and sorting sites (194); (c) middle storage of waste (229); (d) recycling of electrical items (71); (e) other recycling activities (83); (f) combustion (348); (g) landfills (271) and (h) wood-related (121). In total, 143 waste-fires at 111 waste management sites, with fire radiative power (FRP) as high as 81 MW, were detected over a period of seven years 2012-18. Data shows that landfills and RCs are two major high-risk groups for instigation of secondary fires. It is concluded that risk of wastefires at all stages of waste management chain can be mitigated by controlling the challenges of structural over-capacities at the sites, functioning up-stream of waste management chain. Moreover, there is need to establish an increased number of property-close RCs to enhance quality of waste sorting. A novel technique for the analysis of risk of wastefires, using remote sensing and GIS modeling, is presented in this article. This technique can be extrapolated for other geographical settings for the assessment of risk of waste-fires.

Individual waste sorting is necessary for effective, efficient waste management. Despite active government interventions, waste sorting has achieved limited success in China. Previous research provides contradictory theories and mixed evidence of the relationship between perceived environmental governance and individual waste sorting behavior. Some researchers argue that perceived environmental governance enhances individual engagement by offering a supportive atmosphere, whereas the crowding out thesis suggests that it undermines intrinsic motivation and suppresses participation. This study suggests that the controversy is partially attributed to people's varying expectations for central and local governments. Multivariate analyses of nationally representative data in China show that a positive evaluation of local government motivates individuals’ sorting behavior, whereas the perceived effective environmental governance of the central government decreases individual engagement, net of demographic and socioeconomic factors. Additionally, people in danwei and affordable housing communities who perceive the central government's environmental governance to be effective are more likely to sort waste. Institutional trust and the involvement of local actors may lead to differential outcomes. These findings suggest that waste sorting results from systematic evaluations of both individual preferences and institutional settings, and effective environmental governance requires more nuanced measures to evoke intrinsic motivation, preferably at the community level.

Studies to date have shown that individual pro-environmental motivations do not always translate into pro-environmental behaviors. An important factor that modifies motivational strength is the context in which the behavior is embedded. Previous studies have largely been cross-national analyses that focus on macro-contextual factors, thus ignoring substantial variation in motivation-behavior associations at the local scale. In contrast, this study investigated the way micro-contextual mechanisms in residential areas (housing estates and communities) moderate the behavioral effects of personal values, one of the most fundamental motivations that guide individual environmental behaviors. Four contextual factors with particular attention were community environmental initiatives, social capital, local demographics, and built characteristics. The research data derived from a large-scale survey in Hangzhou, China, where community initiatives have been implemented widely to target household waste source separation. We examined our cross-level model for both waste sorting and nontarget environmental behaviors. The results showed that the associations between self-transcendent value prioritizations and waste sorting were stronger in residential areas with lower populations or community initiatives’ greater reliance on public-interest framing. Associations between value prioritizations and nontarget private behaviors were stronger in areas with lower social capital, more females, or more communal space for neighbor interactions. However, no contextual factors changed the strength of the links between value prioritizations and public behaviors. Overall, these findings highlight the significant role of micro-contextual factors in explaining the variations in motivation-behavior links. They also indicate that the characteristics of environmental behavior may moderate the dynamics between pro-environmental motivations and contextual factors further.

Anaerobic digestion (AD) is a potential biotechnology to treat food waste for both energy and resource recovery. However, a high level of contamination in food waste limits their direct use as feedstocks. Therefore, a food waste sorting system followed by anaerobic digestion and gasification is proposed in this study to evaluate the potential of food waste for hydrogen and methane co-production through the thermal-equilibrium model and experimental study. To achieve the H2-rich syngas and methane-rich biogas, the waste sorting system was used to separate the raw waste into pure food waste fraction for AD and discarded waste fraction for gasification. The thermal-equilibrium model is used to predict the content of H2 at different moisture content and air equivalence ratio (ER). The results show that gasification generated the highest hydrogen content at 28.9% with a high moisture content of 55 wt% when the value of ER is 0.35. The highest calorific value of syngas is 5.59 MJ/m3 at the conditions of 60 wt% of moisture content and 0.35 of ER. For the mesophilic AD system, the highest specific methane yield of FW is 557 mL/g VS. Thermophilic AD increased methane yield to 680 mL/g VS while AD of vegetable waste had a negligible production of methane gas. The overall energy performance of the integrated AD and gasification system was assessed in terms of the output of electricity and heat.