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Eco-compensation is an important policy tool to trade off economic development and environmental protection in a watershed. This study introduced the gross ecosystem product (GEP) accounting system to identify the eco-compensation provider (ECP) and eco-compensation receiver (ECR) of a river basin. Then, a cooperative game model and a non-cooperative game model between the ECP and the ECR were established, in which system dynamics was incorporated into the game theoretical analysis to aid selection of the optimal compensation scheme. The study further demonstrated the model applications by taking the Tuojiang River Basin as a case. The results showed that the accounted GEP increased from CNY 32.2 billion in 2018 to CNY 35.5 billion in 2020, with a growth rate of 10.2%. Deyang City, as an ECP, had a cumulative difference of CNY 11.759 billion between its accounted GEP and actual GEP output over the three years. Neijiang City, Zigong City, and Luzhou City were taken as the ECR, receiving the GEP revenues as CNY 11.289 billion, 7.661 billion, and 1.497 billion, respectively. Chengdu City changed from the ECP to the ECR and ultimately to the ECP. However, Ziyang City and Meishan City changed from the ECP to the ECR. The eco-compensations increased to varying degrees during 2018–2020 in both game scenarios, with ECP payments and ECR revenues increasing by 16.5% and 4.6% in the non-cooperative game and by 5.0% and 50.8% in the cooperative game. Particularly, the eco-compensation obtained by the cooperative game had better environmental and economic performance, as there was a total of CNY 7.049 billion being saved. However, there was no savings of compensation by the non-cooperative game. It is expected that the results may provide insight into the design of the eco-compensation standard for a river basin. [ABSTRACT FROM AUTHOR]

This study employed an input-output approach to measure household CO2 emissions (HCEs) in Sichuan province, China from 2010 to 2017. A ZSG-DEA model with a factor constraint cone was built, to allocate such emission allowances to provincial subordinate cities and investigate their spatiotemporal heterogeneity. Using Tapio decoupling analysis, this study further examined the nexus between regional economic performance and HCEs. The results indicated that HCEs in Sichuan province initially increased and then decreased, peaking at 69.60 million tons in 2015. The structure of the HCEs changed from coal- to petroleum-dominated from 2010 to 2017. Indirect emissions from consumption-related sectors accounted for 60% of the total HCEs, including food, transportation, communication, and accommodation. The capital city of Chengdu, with the largest economic scale, overwhelmingly dominated the total household CO2 emissions, whereas Panzhihua, a heavy-industry-dominated city, had the highest HCEs per capita. The Tapio decoupling results suggested that seven cities, led by Chengdu, had strong decoupling statuses, indicating that these cities performed well in the trade-off between economic growth and HCEs reduction. These results indicated that HCEs had a head effect centered on cities with advanced urbanization, but there was a virtuous cycle between CO2 emissions reduction and economic development. Given the spatial and temporal heterogeneity of HCEs, differentiated policymaking on emissions reduction is the key to facilitating green transformations. [ABSTRACT FROM AUTHOR]

Surface treatment waste (HW17) contains a large amount of toxic and corrosive components, which may be harmful to the public health if improper disposal. To understand its metabolism is a prerequisite for the management optimization. In this study, the metabolic network for HW17 in Chengdu city (Sichuan Province, Southwestern China) is constructed by fusion of administrative data and web textual data to identify the associated issues through an investigation of the waste flow and direction. On such basis, a dual-objective mixed-integer linear programming model, with three scenarios (cost minimization, risk minimization, both the cost and risk minimization), is established to optimize the metabolic network for enhancing the management efficiency. The results show that the total HW17 in 2019 is 32,846.14 tons in Chengdu city. Of this, 0.4% of HW17 does not have downstream metabolic paths, and only 23.51% of it is completely disposed. About 78.08% of the generated HW17 is transported outside the metropolitan area of Chengdu city for disposal, highlighted by an open-loop feature. After optimization, the network cost reduces by 3.91% among the three scenarios, and risk decreases by 87.85%. In view of these results, this study further discusses the capacities of the recycling centers and disposal centers, as well as the limitations and uncertainty. Managerial implications are proposed, to lay a foundation for the improvement of waste management sustainability. [Display omitted] • Surface treatment waste is an environmental hazard with expensive recycling. • A metabolic network was constructed for surface treatment waste flow in Chengdu. • Dual-objective mixed-integer linear programming model for cost/risk minimization. • Delicate balance among cost/risk, spatial agglomeration & infrastructure capacity. • Potential to improve efficiency and sustainability of waste management. [ABSTRACT FROM AUTHOR]