AI-powered municipal solid waste management: a comprehensive review from generation to utilization

The proximity principle - disposing of waste close to its origin - has been a central value in municipal solid waste (MSW) management in Japan for the last 30 years and its widespread adoption has helped resolve numerous "Not in My Backyard" issues related to MSW management. However, MSW management costs have soared, in large part because of aggressive recycling efforts and because most MSW is incinerated in a country that has scarce landfill capacity. In addition, smaller, less sophisticated incinerators have been closed because of high dioxin emissions. Rising costs combined with the closure of smaller incinerators have shifted MSW management policy toward regionalization, which is the sharing of waste management facilities across municipalities. Despite the increased use of regionalized MSW facilities, the proximity principle remains the central value in Japanese MSW management. Municipal solid waste management has become increasingly regionalized in the United States, too, but different driving forces are at work in these two countries. The transition to regionalized MSW management in Japan results from strong governmental control at all levels, with the central government providing funds and policy direction and prefectures and municipalities being the primary implementing authorities. By contrast, market forces are a much stronger force with US MSW management, where local governments - with state government oversight - have primary responsibility for MSW management. We describe recent changes in Japan's MSW programs. We examine the connections between MSW facility regionalization, on the one hand, and, on the other hand, the proximity principle, coordination among local governments, central government control, and financing mechanisms.

PurposeWith rapid industrialization and urbanization, municipal solid waste (MSW) management has become a serious challenge worldwide, especially in developing countries. The Beijing Municipality is a representative example of many local governments in China that are facing MSW management issues. Although there have been studies in the area of MSW management in the literature, less attention has been devoted to developing a structured framework that identifies and interprets the barriers to MSW management in megacities, especially in Beijing. Therefore, this study focuses on identifying a comprehensive list of barriers affecting the successful implementation of MSW management in Beijing.Design/methodology/approachThrough an extensive review of related literature, 12 barriers are identified and classified into five categories: government, waste, knowledge dissemination, MSW management process and market. Using an integrated approach including the decision-making trial and evaluation laboratory (DEMATEL), maximum mean de-entropy algorithm (MMDE) and interpretive structural modeling (ISM), a conceptual structural model of MSW implementation barriers is constructed to provide insights for industrial decision-makers and policymakers.FindingsThe results show that a lack of economic support from the government, imperfect MSW-related laws and regulations, the low education of residents and the lack of publicity of waste recycling knowledge are the main barriers to MSW management in Beijing. Combined with expert opinions, the paper provides suggestions and guidance to municipal authorities and industry practitioners to guide the successful implementation of MSW management.Practical implicationsThe findings of this study can provide a reference for MSW management in other metropolises in China and other developing countries.Originality/valueThis study proposes a hybrid DEMATEL-MMDE-ISM approach to resolve the subjectivity issues of the traditional ISM approach and it analyzes the barriers that hinder MSW management practices in Beijing.

Municipal solid waste (MSW) management and recycling has become an emerging issue in developing countries. Shanghai, the largest megacity in China, is well-known nationwide due to leading China's MSW separation and recycling. Therefore, this paper introduces the Shanghai mode for MSW management and its current situation to enrich existing MSW management studies. Results show that the total generation volume of MSW and amount of MSW generation per capita were 9.00 million tons and 372.16 kg in 2017, increased approximately eight-fold and four-fold compared with the data in 1978, respectively. The MSW treatment rate reached 100% since 2014, with incineration rate increased to 48.56% in 2017. The cost of MSW management after implementing MSW sorting regulation is increased to 985 CNY/ton, including 390 CNY/ton of MSW sorting cost. Then three key features and innovative MSW management modes, namely, mandatory MSW sorting legislation, Green Account program, and the Combined Network program are introduced. Meanwhile, two main challenges are urgent to be responded, including inadequate collecting vehicles and limited wet waste treatment capacity. Finally, policy recommendations on strengthening MSW recycling process, constructing complete terminal treatment industry, and making systematic policies were provided to respond existing challenges.

Eco-efficiency for greenhouse gas emissions mitigation of municipal solid waste management: A case study of Tianjin, China

Meeting the United Nations (UN) sustainable development goals efficiently requires designers and engineers to solve multi-objective optimization problems involving trade-offs between social, environmental, and economical impacts. This paper presents an approach for designers and engineers to quantify the social and environmental impacts of a product at a population level and then perform a trade-off analysis between those impacts. In this approach, designers and engineers define the attributes of the product as well as the materials and processes used in the product’s life cycle. Agent-based modeling (ABM) tools that have been developed to model the social impacts of products are combined with life cycle assessment (LCA) tools that have been developed to evaluate the pressures that different processes create on the environment. Designers and engineers then evaluate the trade-offs between impacts by finding non-dominated solutions that minimize environmental impacts while maximizing positive and/or minimizing negative social impacts. Product adoption models generated by ABM allow designers and engineers to approximate population level environmental impacts and avoid Simpson’s paradox, where a reversal in choices is preferred when looking at the population level impacts versus the individual product-level impacts. This analysis of impacts has the potential to help designers and engineers create more impactful products that aid in reaching the UN sustainable development goals.

The purpose of this investigation is to evaluate the current status and to identify the problems of municipal solid waste (MSW) management in China to determine appropriate remedial strategies. This is the second of two papers proposed on this topic. Major problems or difficulties identified in MSW management in China include MSW land, air, and water pollution, commingled collection, poor administration, shortage of funds, lack of facilities, and problems of training and public awareness. In order to solve these problems and to improve MSW management in China, remedial strategies in three areas are recommended: institutional reform, technology development, and legislation and administrative improvement. The primary principle involved in institutional reform is unifying legislative responsibilities into one body and developing a market mechanism for handling MSW. Composting, landfills, and incineration should be equally developed in accordance with China's needs. The feasibility of developing technology to handle MSW in China is discussed. Also recommended is the establishment of sound regulatory systems, including a service fee system, a source separation system, and a training program. China is presently undergoing economic and institutional reform at the national and local levels. Results of this study will provide useful information on MSW management in China.

Every year, religious events (REs) attended by millions of pilgrims, take place in different holy cities around the world. However, research on municipal solid waste management (MSWM) is limited despite the reputation of REs to generate large amounts of municipal solid waste (MSW), which negatively influences the environment and human health when poorly managed. The Arba’een is one of the largest REs in Iraq and worldwide that attracts more than 11 million pilgrims annually. A large quantity of MSW is produced during this event, which is poorly managed and disposed of in a dumpsite without any treatment, due to the lack of research and data about MSW generated during such events. Thus, this research aims to address part of this gap and contribute to new knowledge on MSWM at REs by studying the MSWM system applied at the Arba’een, a subject that has never been considered before. This study adopts mixed methods research approach, employing composition analysis for MSW, questionnaire surveys and interviews with the stakeholders (hoteliers, camp owners, pilgrims and MSWM authorities) and on-site observations as key methods for generation of data. The MSWM system was assessed based on the opinion of the key stakeholders and the Wasteaware benchmark indicators formwork. Numerical models were built to estimate the quantities of MSW produced by pilgrims’ accommodation (hotels and camps) based on the characteristics of the accommodation (capacity, area etc.). MSWM services users’ (hoteliers, camp owners and pilgrims) intention to participate in a recycling scheme and the variables influence this intention were studied with a view of investigating the possibility of introducing a recycling scheme at REs. The results showed that REs account for 14% of the city’s MSW and its main components were organic (57.9%), paper (14.9%) and plastic (14.6%). The MSWM system suffers from operational and governance weaknesses; the key weaknesses are lack of controlled disposal facility, absence of a formal recycling scheme, deficit of key waste-related data, poor public involvement, inadequate planning, and funding limitations. Statistical analyses showed that average municipal solid waste generation (MSWG) from hotels and camps were 112 and 413kg.day-1, respectively. Hotels’ MSWG is influenced by their capacity, staff size and expenditure while camps’ capacity, expenditure and food services affect its MSWG. MSWG from hotels and camps can be modelled with a coefficient of determination of about 0.80. In addition, more than 65% of MSWM system users are willing to participate in MSW recycling during REs and it is expected that about one third would perform recycling; this indicates that introducing MSW recycling during REs could be successful.

Municipal solid waste (MSW) management currently requires critical attention in ensuring the best principles of socio-economic attributes such as environmental protection, economic sustainability, and mitigation of human health problems. Numerous surveys on the waste management system reveal that approximately 90% of the MSW systems are improperly disposing the wastages in open dumps and landfills. Classifying the wastages into biodegradable and non-biodegradable helps converting them into usable energy and disposing properly. The advancements of effective computational approaches like artificial intelligence and image processing provide wide range of solutions for the present problem identified in MSW management. The computational approaches can be programmed to classify wastes that help to convert them into usable energy. Existing methods of waste classification in MSW remain unresolved due to poor accuracy and higher error rate. This paper presents an experimented effective computer vision–based MSW management solution with the help of the Internet of Things (IoT), and machine learning (ML) techniques namely regression, classification, clustering, and correlation rules for the perception of solid waste images. A ground-up built convolutional neural network (CNN) and CNN by the inception of ResNet V2 models trained through transfer learning for image classification. ResNet V2 supports training large datasets in deep neural networks to achieve improved accuracy and reduced error rate in identity mapping. In addition, batch normalization and mixed hybrid pooling techniques are incorporated in CNN to improve stability and yield state of art performance. The proposed model identifies the type of waste and classifies them as biodegradable or non-biodegradable to collect in respective waste bins precisely. Furthermore, observation of performance metrics, accuracy, and loss ensures the effective functions of the proposed model compared to other existing models. The proposed ResNet-based CNN performs waste classification with 19.08% higher accuracy and 34.97% lower loss than the performance metrics of other existing models.

Chapter 10 - Pollutants control strategies for modern waste incinerators: Status quo in China in the context of municipal solid waste classification

The purpose of this investigation is to evaluate the current status and identify the problems of municipal solid waste (MSW) management in China in order to determine appropriate remedial strategies. This is the first of two papers, discussing primarily the general characteristics of MSW and its management in China. The second paper focuses on specific remedial strategies. MSW generation in China has increased rapidly in the past 20 years from 31.3 million tons in 1980 to 113.0 million tons in 1998. The annual rate of increase is 3–10%. The average generation per capita is 1.0 kg/day (0.38 t/year). Nearly one-half of the waste generated is dumped in the suburbs, where the accumulated quantity has reached 6 billion tons, which has caused heavy environmental pollution. This paper provides information on MSW management in China, such as MSW generation and its physical, chemical, and biological properties. Low calorific value and high moisture content characterize China's municipal waste. Other issues related to MSW management in China are also discussed, including the factors that influence MSW generation quantity and quality, MSW collection, transfer and transport, treatment and disposal, material recovery, legislation, enforcement, and administration.

This study reports on experimentation with municipal and industrial solid waste in Brazil, on mutual inspection of municipal sanitation models in selected Spanish and Brazilian towns, and on observations of municipal solid waste (MSW) management models effective in Argentina, Great Britain, Sweden, and Germany. The diversity of management strategies inhibits technology transfer. Judging by the models inspected, Sweden and Germany appear to be best prepared for stricter European landfill diversion targets in the near future. Experimentation in Brazil has resulted in a proactive MSW management model based on divided collection, which achieves 80 percent landfill diversion. This result, surprisingly, meets and exceeds European diversion targets in a South American context. As the gap in strategy and target narrows between South America and Europe, both technology and management methods may gain intercontinental mobility and thus enhance commercial ties between the two markets in the specific branch of MSW management.

In this study, the life cycle assessment (LCA) method has been used to evaluate the environmental impacts of various municipal solid waste (MSW) management system scenarios in Banepa municipality, Nepal, in terms of global warming potential (GWP), acidification potential (AP), eutrophication potential (EP), human toxicity potential (HTP), abiotic depletion potential (ADP), and photochemical ozone creation potential (POCP). There are at least six possible scenarios of MSW management in Banepa: the current or baseline scenario (Scenario 1); composting with landfilling (Scenario 2); material recovery facility (MRF) recycling, composting, and landfilling (Scenario 3); MRF and anaerobic digestion (AD); composting, and landfilling (Scenario 4); MRF, composting, AD, and landfilling (Scenario 5); and, finally, incineration with landfilling (Scenario 6). Using both information from Ecoinvent 3.6 (2019) and published research articles, a spreadsheet tool based on the LCA approach was created. The impact of the recycling rate on each of the six abovementioned scenarios was evaluated using sensitivity analysis, which showed that the recycling rate can considerably decrease the life-cycle emissions from the MSW management system. Scenario 3 was found to have the least overall environmental impact with a GWP of 974.82 kg CO2 eq. per metric ton (t), EP of 0.04 kg PO4 eq./t, AP of 0.15 kg SO2 eq./t, HTP of 4.55 kg 1,4 DB eq./t, ADP of −0.03 kg Sb eq./t, and POCP of 0.06 kg C2H4 eq./t. By adoption of MRF and biological treatments such as composting and AD, environmental impact categories such as AP, EP, HTP, ADP, POCP, and GWP can be significantly reduced. The findings of this study can potentially serve as a reference for cities in the developing world in order to aid in both the planning and the operation of environmentally friendly MSW management systems.

Application of system dynamics model for municipal solid waste management in Khulna city of Bangladesh

Sustainable municipal solid waste (MSW) management is a critical issue that requires planning in accordance with population growth, urbanization, and living standards. An evaluation that integrates system dynamics (SD) is newly built for identifying the interactions between social activities to predict future MSW generation. In this study, SD-based greenhouse gas (GHG), energy, and economic evaluations were conducted for MSW management in the Southern Tai Lake Watershed (STWL) area in China. The considered SD factors include the gross domestic product (GDP) growth, total population, population growth, MSW generation per capita, and MSW generation charges. The results indicate that the current MSW strategy (S1) does not perform well in GHG, energy, and cost evaluation, and the current landfill capacity will be depleted in 2022. Co-processing the landfilled waste with fresh MSW in incineration plants (S7) is the most favorable strategy, which indicates the current landfill capacity will be sufficient for the ash generated from incineration over the next decade. S7 also emits 1.5–3 times less GHG, recovers 2–3.2 times more energy, and obtains 1.3–2.0 times more economic benefits than S1 during 2020–2030. This study offers valuable insights regarding the dynamics of MSW generation and an approach to determine an optimal MSW management strategy for the future.

Electricity generation and GHG emission reduction potentials through different municipal solid waste management technologies: A comparative review