Environmental benefits of airport waste classification and recycling strategies: An analysis of behavior in multi-agent systems

IF 5.4 Q1 ENVIRONMENTAL SCIENCES
Zixin Bian, Zhibo Zhao, Xinrui Guo, Yifan Gu, Yi Yi, Yuxian Hong, Mingxuan Tuo, Yihan Li, Yufeng Wu
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引用次数: 0

Abstract

The classification and recycling of airport waste has become a key point in developing green airports. However, airport waste classification involves a large number of stakeholders. The influence factors are complex, and the interactions between the stakeholders are not clear. Based on the agent-based model, we sort out the behaviors and driving factors of the three main stakeholders, namely passengers, collectors, and managers, and construct a multi-agent system of airport waste classification and recycling with the coupling of the waste generation subsystem, the recycling subsystem and the strategy formulation subsystem. By the complex system, we analyze the comprehensive effects of different policy strategies. Using the life cycle assessment method, an environmental benefit assessment model for airport waste classification and recycling is established to analyze the environmental benefits of different strategies and find the best strategy for the airport. The results show that implementing policy strategies can significantly change passengers’ waste disposal behavior and more than double their willingness to use green products. The combined strategy of the full-factor change scenario demonstrates a significant effect in optimizing the waste metabolism structure and recyclables disposal structure at the airport, with a 76.9 % increase in the use of green products relative to the BAU scenario. Through the implementation of the combined strategy, recyclable waste recycling can reduce 10.6 t CO2e and 15.6 % of photochemical oxidant emissions, which is a significant environmental benefit.
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来源期刊
Resources, conservation & recycling advances
Resources, conservation & recycling advances Environmental Science (General)
CiteScore
11.70
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0.00%
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0
审稿时长
76 days
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