Municipal Solid Waste Classification Research Articles

Impacts of a municipal solid waste classification policy on carbon emissions: case study of Beijing, China

AbstractNational and local governments implement municipal solid waste classification policies to reduce waste disposal and minimize environmental pollution. Beijing started implementing its classification of municipal solid waste policy in May 2020. This study evaluates the impact of Beijing’s household waste classification policy on carbon emissions during collection, transportation, and treatment. The policy’s introduction reduced the number of trash bins, influenced transportation modes, and altered waste treatment emissions. We found a notable reduction in average net carbon emissions post-policy implementation (2403 kg CO2eq per metric ton of waste) compared with pre-policy (3584 kg CO2eq per metric ton of waste). If Beijing reaches its 2025 waste target, these emissions will decrease further to 1760 kg CO2eq per metric ton of waste. Translating these findings into monetary terms confirms this policy’s environmental and economic efficacy.

Modeling and evaluating costs and greenhouse gas emissions in solid waste management based on system dynamics in a mega-city: The case of Xi'an

With the escalating generation of municipal solid waste (MSW) and the increasing utilization of collection and transportation (C&T) vehicles within the MSW classification system, the associated costs and greenhouse gas (GHG) emissions from waste drop-off, as well as the C&T processes, have risen sharply. However, the mesoscopic view of the waste drop-off and C&T system is limited. Therefore, we divided the waste classification management (WCM) system into three subsystems: generation and drop-off, C&T, and disposal. Based on system dynamics theory, the logical relationships between relevant parameters in each subsystem were established. A WCM system dynamics model, which focused mainly on the drop-off and C&T processes, was constructed using Anylogic software. Using sensitivity, scenario, and uncertainty analyses, the economic impact and GHG emissions of the WCM system were analyzed in detail. The results showed that the waste drop-off and C&T processes accounted for 54.29–57.87% ($47.31 per ton) and 24.54–26.83% ($21.39–21.93 per ton) of the total cost in the whole waste management chain, respectively. GHG emissions were mainly generated in disposal facilities (116.84–257.86 kg CO2-eq/t), followed by C&T (19.02–20.55 kg CO2-eq/t) and drop-off processes (12.68–18.78 kg CO2-eq/t). The system cost and GHG emissions were significantly influenced by the components of the source-separated waste and operational parameters of the applied C&T vehicles. This study not only provides a basis for WCM policy formulation but also a tool for the design and optimization of waste C&T systems.

Source analysis of chlorine in municipal solid waste under waste classification: a case study of Hangzhou, China.

Inorganic chlorine is susceptible to water and soil salinization due to its non-degradability and high mobility. To clarify the environmental risks associated with the active inorganic chlorine in municipal solid waste (MSW), the specific characteristics and contributions of inorganic chlorine in different MSW categories were investigated in this study. MSW samples were collected from eight representative waste classification residential areas in Hangzhou, China. It was found that the inorganic chlorine content in different MSW categories varied significantly (0-113 mg/g). Perishable waste, paper, and plastic were found to be the main sources of inorganic chlorine in MSW. A four-category classification system was used to quantify the contribution of inorganic chlorine from each waste category. It was found that the misclassification of inorganic chlorine contributions from perishable waste and other waste accounted for 51.96% and 48.04%, respectively. However, when correctly classified into the four-category system, their contributions were reduced to 67.14% and 30.65%, respectively. Therefore, MSW classification showed a significant reduction in the overall contribution of inorganic chlorine. The misclassification reduces the contribution of inorganic chlorine to 48.04%, while correct classification increases the reduction to 69.35%.

Long-term implications of municipal solid waste (MSW) classification on emissions of PCDD/Fs and other pollutants: Five-year field study in a full-scale MSW incinerator in southern China

Understanding how municipal solid waste (MSW) classification influences the physiochemical properties and incineration emission characteristics of MSW is imperative for sustainable waste management. To investigate how long-term changes in the composition and physical properties of MSW resulting from MSW classification affect the emissions of polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs) and multiple flue gas pollutants, a five-year experiment (2018–2022) was conducted in a full-scale MSW incinerator in Shenzhen City, China. After MSW classification, the food waste in MSW was substantially reduced while the paper, textile, and wood components were notably increased. MSW classification also remarkably decreased the water and chlorine contents of MSW while concomitantly increasing the wet-based calorific value, sulfur content, and nitrogen content. Consequently, the PCDD/Fs emissions declined from 106.7 ng I-TEQ/t MSW in 2018 to 26.0 ng I-TEQ/t MSW in 2022. Moreover, a process-tracing experiment demonstrated noticeable decreases in PCDD/F synthesis in the post-combustion area, with mass-reduction efficiencies of 23.6 %–95.4 %. In a correlation analysis, the PCDD/F emissions were significantly positively correlated with food waste, water content, and chlorine and negatively correlated with the wet-based calorific value and nitrogen content. Furthermore, MSW classification reduced the emissions of conventional flue gas pollutants (SO2, CO, and HCl) and multiple heavy metals (total sum of Sb, As, Pb, Cr, Co, Cu, Mn, and Ni). In summary, the long-term study demonstrated that MSW classification can feasibly separate incombustible waste, improve combustion quality, and reduce pollutant emissions from sources. These findings offer practical guidance for promoting MSW classification.

The impact of “Internet plus” enterprises on municipal solid waste classification and social welfare: An example from China

Following rapid economic development and urbanization, the classification of municipal solid waste (MSW) has become an urgent problem. This study analyzes the multiple subjects, including government, residents, and “Internet plus” MSW classification enterprises (IPMCE), and proposes a dynamic evolutionary collaborative framework for the coproduction of public goods to address the government and market failure during the supply of MSW classification as a public good. Using China as an example, this study constructs a multi-agent equilibrium simulation model to analyze this theoretical framework and investigate how to improve the related policies. The simulation results reveal that the collaborative and coproduction of public goods facilitated by IPMCE can improve classification rates and social welfare. Moreover, government subsidies for the research and development (R&D) expenditures of IPMCE are shown to further enhance this effect. In addition, the social welfare growth rate exceeds the subsidy growth rate, indicating that the subsidy has a leverage effect. Although this study has some limitations, such as the fact that the simulation model setting cannot fully reproduce the real situation, it provides policy recommendations on how to better utilize IPMCE in MSW classification as well as strategies for solving similar problems in other regions or public goods.

Social-economic assessment of integrated waste pickers in municipal solid waste management system: A case of Tianjin in China

Currently, China's municipal solid waste (MSW) management system has been changing from mixed collection and treatment system into separated collection and treatment system. Therefore, the source separated ability of MSW, the relevant policies of MSW classification and the MSW management system are still in the stage of exploration and improvement. This study chooses to integrate waste pickers (WPs) from the informal sector into the MSW management system, so that they can conduct secondary sorting of waste as a supplement to source separation. However, the existing research does not provide a method that allows the evaluation of integrated WPs from a dynamic and long-term perspective. In this paper, the system dynamics model of MSW management is improved to provide the ability to analyze the long-term evolution of social economic benefits of integrating WPs for secondary sorting. Taking Tianjin as an example, the scenario analysis is carried out. The results show that, on the basis of the existing mixed management mode, integrating WPs for secondary sorting (80% separated rate) can reduce the waste management cost per ton by 55 yuan in 2030. Under the current situation in Tianjin where the source separation rate of food waste is 20% and the source separation rate of recyclable waste is 60%, integrating WPs can reduce the social economic cost of Tianjin's urban MSW management system by 422.45 million yuan per year from 2022 to 2030. In addition, the results show that even if the source separated rate of food and recyclable waste increases, there is still room for 20%–80% increase in wages based on giving WPs a salary higher than the national per capita disposable income in 2022. This study provides a basis for integrating WPs into Tianjin MSW management system, as well as methods and quantitative tools to integrate WPs for cities in developing countries.

Prediction of municipal solid waste treatment and disposal in high cold and high altitude area based on system dynamics: a case study of Lhasa

At present, the high cold and high altitude areas of China continue to face challenges in achieving high rates of resource utilization for the municipal solid waste (MSW). In this paper, for the first time, a prediction method based on system dynamics (SD) for the treatment and disposal of municipal solid waste in high cold and high altitude areas is proposed and applied to Lhasa City. The model simulate and predict the proportion of treatment methods (including landfill, incineration, kitchen waste disposal, recycling) and the rate of resource utilization (other disposal methods except landfill) of municipal solid waste under Natural Tendency and regulation schemes (Strengthened Municipal Solid Waste Classification Scheme and Municipal Solid Waste Classification and Treatment Scheme). The results show that strengthening municipal solid waste classification and treatment can significantly enhance the resource utilization rate of municipal solid waste in Lhasa, with an expected rate of 100% by 2026. This outcome has the potential to promote sustainable and healthy development of society, economy and environment of a city.

Research on Service Design of Garbage Classification Driven by Artificial Intelligence

This paper proposes a framework for AI-driven municipal solid waste classification service design and management, with an emphasis on advancing sustainable urban development. This study uses narrative research and case study methods to delve into the benefits of AI technology in waste classification systems. The framework includes intelligent recognition, management strategies, AI-based waste classification technologies, service reforms, and AI-powered customer involvement and education. Our research indicates that AI technology can improve accuracy, efficiency, and cost-effectiveness in waste classification, contributing to environmental sustainability and public health. However, the effectiveness of AI applications in diverse city contexts requires further verification. The framework holds theoretical and practical significance, offering insights for future service designs of waste management and promoting broader goals of sustainable urban development.

Spatio-temporal Change in City-level Greenhouse Gas Emissions from Municipal Solid Waste Sector in China During the Last Decade and Its Potential Mitigation

The waste sector is a significant source of greenhouse gas(GHG) emissions and clarifying its emission trends and characteristics is the premise for formulating GHG emission reduction strategies. Using the IPCC inventory model, the GHG emissions from the municipal solid waste(MSW) sector in China during 2010 to 2020 were estimated. The results showed that GHG emissions increased from 42.5 Mt in 2010 to 75.3 Mt in 2019, then decreased to 72.1 Mt in 2020. MSW landfills were the main source of GHG emissions. Further, with the increase in the proportion of waste incineration, the proportion of GHG incineration increased rapidly from 16.5% in 2010 to 60.1% in 2020. In terms of regional distribution, East and South China were the regions with the highest emissions, and Guangdong, Shandong, Jiangsu, and Zhejiang were the provinces with the largest GHG emissions. Implementing MSW classification, changing the MSW disposal modes from landfilling to incineration, improving the LFG collection efficiency of landfills, and using biological functional materials as the cover soil to strengthen the methane oxidation efficiency are the main measures to achieve GHG emission reduction in waste sectors.

Prediction of carbon emissions from municipal solid waste treatment in 31 provinces and cities in China under the shared socio-economic pathways

In order to reduce greenhouse gas (GHG) emissions from the municipal solid waste (MSW) sector, it is essential to describe its greenhouse gas emission patterns and propose appropriate mitigation measures. Therefore, this study predicts the greenhouse gas emissions of urban domestic waste treatment by combining the Intergovernmental Panel on Climate Change (IPCC), shared socio-economic pathways and in-depth learning model. Under the hypothetical policy scenario and the shared socio-economic pathways (SSPs), the greenhouse gas emissions from municipal solid waste treatment in 31 provinces and cities in China by 2030 are analyzed. Combined with the model comparison results, the bidirectional long and short-term memory neural network model has better prediction accuracy than the other models, with an average mean absolute percentage error of 9.68% for 31 provinces and cities, indicating good applicability. Scenario analysis shows that greenhouse gas emissions from municipal solid waste disposal can be significantly reduced only after the implementation of municipal solid waste classification. Scenario 3 (S3) of waste segregation will produce the most GHG emissions, and switching to Scenario 5 (S5) of waste segregation will produce significantly less GHG emissions. Finally, the paper makes policy recommendations on the priority areas of urban domestic waste classification, waste source classification and recycling, and the structure of urban municipal solid waste treatment.

Comparing and optimizing municipal solid waste (MSW) management focused on air pollution reduction from MSW incineration in China

China is the largest developing country in the world, and its municipal solid waste (MSW) has increased with a compound annual growth rate of 5.1 % since 1980. Incineration, which has the advantages of mass- and volume-reduction as well as energy and heat recovery, has become the mainstream environmentally sound treatment method in China. However, air pollution emissions are the primary reason for limiting MSW incineration (MSWI). Currently, the Chinese government is devoted to comprehensively implementing MSW classification. However, the classification model and the future MSW reduction rate are not yet clear. In this study, we project scenarios of air pollution emissions until 2030 based on the different MSW classification models (MSW reduction rates) and diffusion rates of ultra-low emission technology. A total of 6011 tons (t) of particulate matter, 25,881 t of SO2, 14,915 t of CO, 17,167 t of HCl, and 200,166 t of NOx will be emitted in 2030 under the business-as-usual (BAU) scenario, and air pollutants will not peak under this scenario. Air pollutants will reduce by 11 % of the BAU scenario by only implementing an MSW reduction of 20 % (JPN-model). The optimal scenario (DEU-model, increasing the efficiency of material recovery and upgrading air pollution control devices) means that air pollutants will be reduced by 83.2–96.2 % from the base amount under the BAU scenario. These results provide references for MSW management and air pollution emission reduction from the aspects of MSW classification and technology upgrades in China.

Cognitive Study on the Classification Policy of Domestic Waste among Residents in Nanning City

Nanning is one of the 46 key cities in China to establish a municipal solid waste classification system before the end of 2020, and the garbage classification work ranks in the top in many quarters. At the same time, it still faces some difficulties in the implementation of waste classification policy. Exploring people's understanding of domestic waste classification is of great significance to the improvement of waste classification policy and the implementation of waste classification work. Based on the data obtained from the field survey and questionnaire survey of Nanning residents, this paper obtains the residents' cognition of domestic waste classification policy, and obtains the influencing factors of residents' cognition of domestic waste classification policy through empirical analysis. The results show that the factors affecting residents' cognition are government regulation, publicity and education, incentive mechanism, public participation and supporting facilities, while individual wishes and behaviors, charging mechanism and community management have no significant impact on the domestic waste classification policy. According to the analysis results, this paper discusses the problems and reasons existing in the cognition of urban residents' domestic waste classification policy, and puts forward some suggestions for improvement and optimization. First, strengthen publicity and education to promote residents' cognition; The second is to strengthen government control and improve detailed policies and regulations; Third, pay attention to the supervision and implementation of reward and punishment measures, and promote the standardized implementation of classification behavior; The fourth is to build and improve the garbage classification and treatment system; Fifth, broaden the channels of public participation.

Policy reinvention in diffusion: Evidence from municipal solid waste classification policy in China

AbstractWhile research on policy diffusion has gained significant interest among scholars worldwide, little attention has been given to policy reinvention in diffusion. This study aims to investigate the influencing factors and combination paths of policy reinvention in the Municipal Solid Waste Classification Policy (MSWCP). To achieve this, a theoretical framework encompassing internal factors, intergovernmental relations, and external influence has been constructed. Empirical analysis has been conducted on the MSWCP of 31 large‐ and medium‐sized cities in China using Qualitative Comparative Analysis. Through this analysis, several combination paths that prompted local governments to reinvent policies have been identified. Furthermore, the study has clarified the various roles of six conditions—financial resources, government attention, policy experience, peer competition, organizational learning, and social demand—in achieving policy reinvention. These findings are expected to provide new theoretical and practical insights into the field of policy reinvention research.

Assessment of the Multidimensional Performances of Food Waste Utilization Technologies in China

In recent years, China has made great efforts to carry out source-separation in municipal solid waste management; in particular, the utilization of food waste has received increasing attention. Food waste-utilizing technologies, including anaerobic digestion, aerobic biological treatment, and insect feed conversion, are currently applied in China. However, in the existing cases, there were several disadvantages, such as a low rate of utilization, significant environmental impacts, poor economic benefits, etc., as well as a lack of systematic analysis and comprehensive assessment of the performances of food waste utilization technologies. In this study, a four-dimensional performance assessment method (resource efficiency, environmental impact, economic feasibility, and social effect, with 21 indicators) was established for assessing the life cycle process of food waste utilization technologies. We collected detailed information of 14 typical food waste utilization cases in China, and the results showed that the average scores of anaerobic digestion and insect feed conversion were 58.39 and 59.65, higher than those of the aerobic biological treatment (49.16). The highest scores among all subdivision technologies were centralized black soldier fly conversion and mesophilic wet anaerobic digestion, which were 67.14 and 60.82, respectively. With respect to the technologies of different treatment capacities and distribution modes, i.e., centralized and decentralized technologies, the resource efficiency and economic benefit scores of the former were 13% and 62% higher than those of the latter, whereas the environmental impacts and social effect scores of the latter were 8% and 34% greater than those of the former, respectively. In practice, the utilization technology of food waste should be chosen according to local conditions, such as the physical and chemical properties of food waste, the classification of municipal solid waste, financial affordability, collection and transportation distance, etc.

Influence of the Classification of Municipal Solid Wastes on the Reduction of Greenhouse Gas Emissions: A Case Study of Qingdao City, China

The municipal solid waste (MSW) sector is an important source of greenhouse gas (GHG) emissions. MSW classification can achieve waste reduction and improve resource utilization. However, few studies have investigated the effects of MSW classification on GHG emission reduction. Therefore, the GHG emissions under different MSW disposal modes before and after classification were studied based on the life cycle assessment method in the four districts of Qingdao City. The results showed that MSW classification could significantly reduce the GHG emissions during the whole MSW treatment process. The net carbon emissions(in CO2/MSW)during the whole process of waste treatment for mode 1 (mixed collection+landfill), mode 2 (mixed collection+incineration), mode 3 (waste classification+anaerobic digestion of food waste and other incineration), and mode 4 (waste classification+anaerobic digestion of food waste, recycling of recyclable waste, and other incineration) were 686.39, -130.12, -61.88, and -230.17 kg·t-1, respectively. Improving the classification efficiency of food waste had no significant impact on carbon emissions. The reduction in carbon emissions increased linearly with the improvement of waste recycling efficiency. For every 10% increase in the recovery efficiency of recyclable waste, the net carbon emission decreased by 26.6%(16.5 kg·t-1). Appropriate separation of food waste, improving the recycling efficiency of recyclable waste, and reducing the leakage rate of biogas from anaerobic digestion are feasible strategies to reduce carbon emissions from MSW disposal units through the classification of MSW.

Life-cycle economic and environmental impacts of municipal solid waste reverse logistics in residential areas

The economic and environmental impacts of the reverse logistics (RL) process (including drop-off, collection and transportation [C&T]) of the waste disposal chain are becoming increasingly prominent with the increasing generation of municipal solid waste (MSW) and promotion of MSW classification. Quantitative evaluation of this process from economic and environmental perspectives is of great significance for MSW management. This study focused on the financial capital, materials, and energy consumption in the RL process in Xi an City, China. Based on field investigation, the magnitude of pollutant emissions from MSW C&T vehicles over their life cycle was predicted using the GREET software and total RL life-cycle cost and life-cycle assessment were analyzed. The results showed that the finical costs of RL were $46.35–$49.03 per ton of food waste and $62.52–$88.84 per ton of residual waste; the environmental impacts caused by the RL process accounted for 79.24%–96.00% and 20.87%–68.55% of the entire food waste and residual waste management chains, respectively. Labor costs were the biggest financial expenditure and the fuel cycle of C&T vehicles caused the majority of the environmental impacts. Source-separated waste management scenarios represented more environmental benefits but poorer economic positions. In the future, improving MSW source-separation accuracy, replacing diesel C&T vehicles with electric ones, and optimizing the RL system could reduce the environmental and economic impacts of the entire waste management system.

The waste separation behaviour of primary and middle school students and its influencing factors: Evidence from Yingtan City, China

Waste separation at source has been proved to be an effective way to reduce the amount of municipal solid waste (MSW) which has become a major challenge to China’s ecological environment. However, waste source separation requires effort from each individual citizen. As the important drivers of change and potential influencers of the future world, younger Chinese’s waste separation behaviour is crucial to the long-term successful implementation of China’s MSW separation policy. To explore the waste separation behaviour of younger Chinese and identify the factors that may influence their behaviour so as to better encourage younger generation of Chinese to practice waste sorting in their daily lives, a questionnaire survey of 579 primary and middle school (PMS) students aged between 6 and18 years old (y/o) was carried out in Yingtan City, Jiangxi Province, China. Binary logistic regression was adopted to explore the factors that might influence the respondents’ waste separation behaviour. The results indicate that more than half PMS students in Yingtan have participated in waste separation, and junior year students perform better in waste separation practice than their seniors. Students are found to have basic knowledge of MSW classification, but they are more familiar with recyclable waste and hazardous waste than non-recyclable waste. The analysis also highlights positive relationships between PMS students’ attitude to waste separation, their willingness to do it, their environmental education and their waste separation behaviour. The level of convenience of waste sorting facilities and influences from friends and families are also positively related to the students’ waste separation practice, but families have the strongest influence. The perception of a mandatory waste separation policy would demotivate students in terms of waste separation practice, while giving rewards is considered to be the most effective approach to encouraging waste separation. Finally, management strategies for improving PMS students’ waste separation behaviour are discussed and several recommendations for improvement are made.

Differential game analysis between government and waste incineration plants on the management of municipal solid waste classification

PurposeThe purpose of this paper is to study how the government stimulates incineration plants to participate in waste classification management, and how to adjust the subsidy strategy for them.Design/methodology/approachConsidering that the classification behavior of residents will produce herd effect, and waste classification can reduce the disposal cost of incineration plants, the authors constructed a differential game model between the government and waste incineration plants, and analyzed the input strategy of the government and incineration plants when they cooperate in the management of municipal waste classification.FindingsIncreasing the input level of supervision or raising subsidy price, the government can promote incineration plants to increase the input level of incentive. Moreover, from a long-term perspective, increasing the input level of supervision is more effective. Compared with government supervision, the method of incineration plants incentive can more effectively increase the amount of waste disposal. Furthermore, the government supervision and the incineration plants incentive have a positive interaction effect on improving the amount of waste disposal. Increasing the input level of incineration plants incentive or the level of waste-to-energy technology can increase the amount of waste disposal, and from a long-term perspective, increasing the level of R&D investment is more beneficial to increasing the amount of waste disposal.Originality/valueThe results are helpful to improve the investment in the management of waste classification, and also provide a certain theoretical basis for the government's subsidy policy for incineration plants, so as to reduce the financial pressure of the government.

Municipal solid waste classification and real-time detection using deep learning methods

Waste management has become a significant issue in most developing countries. Municipal solid waste generation has been steadily increasing over the past decade. Recycling is gaining importance because it is the only method to maintain a healthy and sustainable environment. Furthermore, recycling is not a fully autonomous operation; a significant amount of waste must be performed manually. New and innovative procedures must be implemented to deal with the increasing volume of waste products at recycling facilities. It is suggested that effective solid waste management systems have a practical approach to detecting and classifying waste materials. This study presents CNN and Graph-LSTM, two deep-learning techniques that can recognize typical waste products when handled on a belt conveyor in waste collection systems. This convolutional neural network-based solution is trained to use six object classes: cardboard, metal, glass, plastic, paper, and organic waste. The major advantage is the ability to model long-term dependencies, Improved performance, better generalization, and easy access The experimental findings show that the suggested system can achieve 97.5% accuracy in real-world situations, outperforming existing methods identified in the literature.

Multi-agent evolutionary game analysis on the implementation of municipal solid waste classification policy

With the rapid development of economy and the improvement of people's living standard, the domestic waste is greatly increasing. Based on the multi-agent evolutionary game theory, an evolutionary game model among the recycling industry, urban management officer and government is established to address the environmental issues of rising municipal solid waste production and low recycling utilization rates in China. Through numerical example analysis, the relationship between relevant factors on the evolutionary stable state of the system is studied. The findings demonstrate that when the likelihood of severe oversight by the government and of significant enforcement by urban management officers grows, the recycling industry becomes more ready to select waste separation strategy. Additionally, the government is far more affected by the likelihood of significant enforcement by urban management officers than the recycling industries are. In addition, effective acceleration of waste sorting may be achieved by giving the recycling industries the proper government subsidies and increasing the recycling industries' profits from garbage sorting. Moreover, the government's increased fines for the urban management officers can significantly lower the incidence of bribery between the recycling industries and the urban management officers.