Issue |
E3S Web Conf.
Volume 143, 2020
2nd International Symposium on Architecture Research Frontiers and Ecological Environment (ARFEE 2019)
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Article Number | 02038 | |
Number of page(s) | 4 | |
Section | Environmental Science and Energy Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202014302038 | |
Published online | 24 January 2020 |
Evaluation of Atmospheric Pollutant Emission Efficiency Based on SBM-Undesirable Model —— Taking PM2.5 as an Example
1 School of Management Studies, Shanghai University of Engineering Science, Shanghai, China
2 Department of philosophy, Nanjing University, Nanjing, China
* Corresponding author: 23128757@qq.com
At present, China's haze is becoming more and more serious. How to reduce haze emission is an urgent problem in China's environmental governance. This paper uses the SBM-Undesirable model, adopting 5 inputs indexes(coal, oil, gas, labor and capital), and 2 outputs indexes(GDP and PM2.5 emissions)as expected output and unexpected output respectively, to calculate the emission efficiency of PM2.5 in China's 29 provinces. Based on the efficiency evaluation results of SBM-Undesirable model, the reasons for the inefficiency of PM2.5 emission are analyzed. The redundancy rate of investment, the insufficient rate of expected output and the redundancy rate of undesirable outputs are calculated. Results showed that: (1) Most provinces with high PM2.5 emission efficiency are concentrated in the eastern region, while the PM2.5 emission efficiency in the central and western regions is relatively low. (2) The redundancy rate of input variables and undesirable output of the eastern region is lower than that of the western and based on SBM-Undesirable model central regions. This is likely to have a great relationship with the economic development and the high level of technology in the eastern region. This study provides a reference for reducing the haze theory and providing empirical support for the government's haze reduction.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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