Inputs optimization to reduce the undesirable outputs by environmental hazards: a DEA model with data of PM2.5 in China

Wu, Xiaoqing; Chen, Yufeng; Guo, Jing; Gao, Ge

doi:10.1007/s11069-017-3105-y

Cited by 24 publications

(9 citation statements)

References 44 publications

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“…They found that the energy and environmental efficiency is highest in East China and worst in the West. Wu et al [29] calculated the output efficiency of seven input indicators in 29 provinces in China using an improved model of DEA, incorporating one undesirable output and seven inputs. They found that only Beijing, Tianjin, and Shanghai are optimal in input-output efficiency.…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic Assessment of Environmental Efficiency in Chinese Industry: A Multiple DEA Model with a Gini Criterion Approach

Xie

Chen

2019

Sustainability

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While China’s rapid industrialization has brought great pressure on environmental pollution, great variations appear in terms of environmental pollution levels among industries. The effective assessment of the environmental performance of different industries is not only conducive to identifying the major sources of pollution in China but also of great significance to the Chinese government in formulating differentiated industry environmental control policies in a targeted manner. Using data of 36 Chinese industries from 2006 to 2015 and a multiple data envelopment analysis (DEA) with a Gini criterion as well as a systematic clustering approach, this study first calculates the environmental efficiency score of Chinese industries and then identifies those pollution sources based on a ranking and clustering analysis. The main result indicates that the ranking of environmental efficiency of various industries overall varies greatly by time. In addition, using a clustering analysis, this study finds that 13 labor-intensive light industries and heavy chemical industries with high energy use and high emissions are medium- and high-pollution industries. Important policy implications are drawn to achieve green industrial development.

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Section: Literature Reviewmentioning

confidence: 99%

Dynamic Assessment of Environmental Efficiency in Chinese Industry: A Multiple DEA Model with a Gini Criterion Approach

Xie

Chen

2019

Sustainability

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“…The former one means using the inverse value of undesirable output as desirable output (Golany and Roll, 1989) or seeing the undesirable output as input (Tyteca, 1997) in standard DEA models. However, the direct approach treats the undesirable outputs more appropriately (Wu et al, 2018). Moreover, the slack-based measure (SBM) model with more desirable outputs and less undesirable outputs relative to fewer inputs should be recognized as efficient (Xie et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Evaluating Economic Growth Efficiency and Its Determinants Under Low Carbon Economy in the Chinese Context

Liu¹

2019

Appl. Ecol. Env. Res.

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This research aims to find out effective approaches to improve the low carbon economy efficiency of China and to promote its low carbon economy development. This paper utilizes two kinds of data envelopment analysis models to estimate the economic efficiency and low carbon economy efficiency of China. It takes carbon dioxide emissions as an undesirable output and compares them to find out the different performances of economic growth in various regions in China in the context of low carbon economy development, and then explores the potential determinants of low carbon economy efficiency for different regions in different periods. The results show that low carbon economy efficiency is much lower than economy efficiency in most areas in China. Additionally, both low carbon economy efficiency and economy efficiency show a slow downward trend in most provinces in China from 2000 to 2011, which was followed by a slight increase in 2012. Moreover, low carbon economy efficiency and economy efficiency show obvious geographic characters. We propose some policy implications. Several policy implications are also provided for various areas to improve low carbon economy efficiency.

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“…and moving sources (motor vehicle, off-road machines, etc.) [ 12 ]. To mitigate China’s foggy and hazy days, reduction of PM 2.5 pollution needs to be addressed.…”

Section: Introductionmentioning

confidence: 99%

“…The second assesses the environmental efficiency of industrial sectors, especially for pollution intensive industries [ 26 , 27 , 28 ]. Moreover, issues such as PM 2.5 emission allocation [ 29 ], influential factor analysis [ 30 ], input optimization for emission reduction [ 12 ], and emission abatement cost calculation [ 31 ] based on environmental efficiency have been previously proposed.…”

Section: Introductionmentioning

confidence: 99%

“…This is an effective way to measure the expected PM 2.5 concentration performance by producing more economic output while using fewer resources. To the best of the authors’ knowledge, there are limited studies regarding environmental efficiency estimation related to PM 2.5 concentration [ 12 , 29 , 32 , 33 ]. The existing studies mainly focus on environmental efficiency but not PM 2.5 concentration efficiency.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimation of PM2.5 Concentration Efficiency and Potential Public Mortality Reduction in Urban China

Jia

You

et al. 2018

IJERPH

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The particulate matter 2.5 (PM2.5) is a serious air-pollutant emission in China, which has caused serious risks to public health. To reduce the pollution and corresponding public mortality, this paper proposes a method by incorporating slacks-based data envelopment analysis (DEA) and an integrated exposure risk (IER) model. By identifying the relationship between the PM2.5 concentration and mortality, the potential PM2.5 concentration efficiency and mortality reduction were measured. The proposed method has been applied to China’s 243 cities in 2015. Some implications are achieved. (1) There are urban disparities in estimated results around China. The geographic distribution of urban mortality reduction is consistent with that of the PM2.5 concentration efficiency, but some inconsistency also exists. (2) The pollution reduction and public health improvement should be addressed among China’s cities, especially for those in northern coastal, eastern coastal, and middle Yellow River areas. The reduction experience of PM2.5 concentration in cities of the southern coastal area could be advocated in China. (3) Environmental consideration should be part of the production adjustment of urban central China. The updating of technology is suggested for specific cities and should be considered by the policymaker.

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Inputs optimization to reduce the undesirable outputs by environmental hazards: a DEA model with data of PM2.5 in China

Cited by 24 publications

References 44 publications

Dynamic Assessment of Environmental Efficiency in Chinese Industry: A Multiple DEA Model with a Gini Criterion Approach

Dynamic Assessment of Environmental Efficiency in Chinese Industry: A Multiple DEA Model with a Gini Criterion Approach

Evaluating Economic Growth Efficiency and Its Determinants Under Low Carbon Economy in the Chinese Context

Estimation of PM2.5 Concentration Efficiency and Potential Public Mortality Reduction in Urban China

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