How the combination of Circular Economy and Industry 4.0 can contribute towards achieving the Sustainable Development Goals

This study contributes to estimate the municipal solid waste (MSW) recycling effect on environmental quality and economic growth in the United States. Few studies have been given to macro-level aggregate analysis through national scale MSW recycling, environmental, and economic indicators. This study employs bootstrapping autoregressive distributed lag modeling for investigating the cointegration relationship among MSW recycling, economic growth, carbon emissions, and energy efficiency utilized quarterly data from 1990 to 2017. The result implies that a one percent increase in MSW recycling contributes to economic growth and reduce carbon emissions by 0.317% (0.157%) and 0.209% (0.087%) in the long-run (short-run). Similarly, a one percent improvement in energy efficiency stimulates economic growth by 0.489% (0.281%) and mitigates carbon emissions by 0.285% (0.197%) in the long-run (short-run). A higher per capita income and population growth caused higher emissions by 0.197% and 0.401% in the long-run. The overall results reveal stronger impacts in the long-run than the short-run with significant convergence towards long-run equilibrium, suggesting a prominent long-run transmission of economic and environmental fallouts. This study confirms a uni-directional causality from MSW recycling to economic growth, carbon emissions, and energy efficiency. These outcomes signify that any policy intervention related to MSW recycling produces significant changes in the level of economic growth and carbon emissions. The finding provides valuable insight for policymakers to counteract carbon emissions through recyclable waste management that simultaneously create significant economic value.

Dynamic and causality interrelationships from municipal solid waste recycling to economic growth, carbon emissions and energy efficiency using a novel bootstrapping autoregressive distributed lag

Life cycle assessment (LCA) is widely used for assessing the environmental impacts of a product or service. Collecting reliable data is a major challenge in LCA due to the complexities involved in the tracking and quantifying inputs and outputs at multiple supply chain stages. Blockchain technology offers an ideal solution to overcome the challenge in sustainable supply chain management. Its use in combination with internet-of-things (IoT) and big data analytics and visualization can help organizations achieve operational excellence in conducting LCA for improving supply chain sustainability. This research develops a framework to guide the implementation of Blockchain-based LCA. It proposes a system architecture that integrates the use of Blockchain, IoT, and big data analytics and visualization. The proposed implementation framework and system architecture were validated by practitioners who were experienced with Blockchain applications. The research also analyzes system implementation costs and discusses potential issues and solutions, as well as managerial and policy implications.

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Blockchain-based life cycle assessment: An implementation framework and system architecture

The interplay of circular economy with industry 4.0 enabled smart city drivers of healthcare waste disposal

Critical factors for enhancing the circular economy in waste management

Barriers to smart waste management for a circular economy in China

Drivers of industry 4.0 enabled smart waste management in the supply chain operations

Due to dynamics caused by factors such as random collection and transportation requirements, vehicle failures, and traffic jams, it is difficult to implement regular waste collection and transportation schemes effectively. A challenge for the stable operation of the municipal solid waste collection and transportation (MSWCT) system is how to obtain the whole process data in real time, dynamically judge the process control requirements, and effectively promote the synchronization operation between multiple systems. Based on this situation, this study proposes a cloud-edge-terminal-based synchronization decision-making and control system for MSWCT. First, smart terminals and edge computing devices are deployed at key nodes of MSWCT for real-time collection and edge computing analysis of the whole process data. Second, we propose a collaborative analysis and distributed decision-making method based on the cloud-edge-terminal multi-level computing architecture. Finally, a “three-level and two-stage” synchronization decision-making mechanism for the MSWCT system is established, which enables the synchronization operation between various subsystems. With a real-world application case, the efficiency and effectiveness of the proposed decision-making and control system are evaluated based on real data of changes in fleet capacity and transportation costs.

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Ming Wan

Papers

Barriers to smart waste management for a circular economy in China

Drivers of industry 4.0 enabled smart waste management in the supply chain operations

Cloud-Edge-Terminal-Based Synchronized Decision-Making and Control System for Municipal Solid Waste Collection and Transportation