Abstract

Municipal solid waste incineration is gradually becoming the main method of waste disposal, but waste incineration produces many organic pollutants (e.g., dioxins). In order to better implement waste management, China identified 46 key cities to implement domestic waste classification first in 2017. This study predicts dioxin emissions in 2030 based on the background of waste classification policy, and analyzes the impact of waste classification on dioxin reduction. Firstly, k-means was used to classify the 46 cities of waste classification into four categories, and the representative cities in the four categories were selected to analyze the correlation between different influencing factors and municipal solid waste in each category through grey correlation analysis. And the municipal solid waste of each city in 2030 was predicted by bidirectional long and short term memory neural network. Finally, four scenarios are set up based on the background of waste classification policy to predict dioxin emissions in each city in 2030. It is found that at least 7.49%–13.07% dioxin emission reduction can be achieved by 2030 through waste classification. Waste classification has a positive impact on dioxin emission reduction.

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