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Study on the Distribution of PM Emission Rights in Various Provinces of China Based on a New Efficiency and Equity Two-Objective DEA Model

Xianhua Wu ()
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Xianhua Wu: Shanghai Maritime University, School of Economics and Management

Chapter 18 in Environmental Disaster in China, 2026, pp 553-582 from Springer

Abstract: Abstract Under the premise that the total emissions of $$PM$$ PM (Particulate matter) of air pollution is established, the allocation of $$PM$$ PM emission rights in various provinces of China is the feasible way to governance the ash haze. In this paper, a Data Envelopment Analysis ( $$DEA$$ DEA ) model that takes into account the objectives of efficiency and equity is constructed. On the basis of evaluating the $$PM$$ PM emission performance of various provinces in China, the corresponding allocation steps are put forward. Then, the results of the $$DEA$$ DEA model and information entropy are compared. The research shows that: (1) Under the same constraint conditions, the emission right of $$PM$$ PM is allocated with $$DEA$$ DEA model, which leads to lower cost, less fluctuation of distribution amount and higher overall national performance. (2) The population $$Gini$$ Gini coefficient method is used to evaluate and it is found that the $$Gini$$ Gini coefficient value is smaller according to the distribution results of $$DEA$$ DEA model, indicating that the $$PM$$ PM emission amount is more fairly distributed among provinces. The functions of this paper are as follows: (1) A new double-objective $$DEA$$ DEA model is constructed, which is suitable for multi-agent performance evaluation with multiple objectives; (2) A scheme to allocate $$PM$$ PM among provinces is proposed, which can provide reference for the practice of haze reduction in China.

Keywords: Efficiency and equity; $$PM$$ PM Emission right; $$DEA$$ DEA Model; Entropy value method; $$Gini$$ Gini Coefficient method (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-92-0910-1_18

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DOI: 10.1007/978-981-92-0910-1_18

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