Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach

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  • A Data envelopment analysis based materials balance approach is proposed.

  • Materials balance principle guarantees satisfaction of laws of thermodynamics.

  • Environmental efficiency of China's thermal power industry is measured.

  • Efficiency is decomposed into technical efficiency and input allocative efficiency.

  • End-of-pipe pollutant abatement activities are included in measurement.

Abstract

Appropriate measurement of environmental and emission abatement efficiency is crucial for assisting policy making in line with constructing a more sustainable society. The majority of traditional approaches for environmental efficiency measures take pollutant emissions as either undesirable outputs or environmentally determined inputs which suffer a limitation of not satisfying the physical laws that regulate the operation of economic and environmental process. In this study, we propose a DEA based approach which is combined with the materials balance principle (MBP) that accounts for laws of thermodynamics to jointly evaluate environmental and abatement efficiency. This approach is along the line of weak G-disposability based modelling but is an extension to existing models that in our approach the identification of possible adjustments on polluting mass bound in inputs and outputs, and potential adjustments on abatement of pollutants are all included. The overall environmental efficiency measured by this approach is decomposed into the measures of technical efficiency, polluting inputs allocative efficiency, and polluting and non-polluting inputs allocative efficiency with the emphasizing of incorporating pollutant abatement activities. Accordingly, new measures of abatement efficiency are proposed which help to identify the pollutant abatement potential that can be achieved from end-of-pipe abatement technology promotion associated with polluting input quality promotion and input resources reallocation. Furthermore, several global Malmquist productivity indices for identifying the changes on environmental and abatement efficiency are proposed. This approach is applied to China's thermal power industry and some empirical results verifying the necessity of introducing the MBP are obtained.

Introduction

During the latest two decades, academic researchers, industry entrepreneurs and government officials have increasingly recognized that sustainable development is one of core solutions to balance economic and social development with environment protection and climate change mitigation. Since the emissions of greenhouse (e.g., carbon dioxide, CO2) and other air pollutants (e.g., sulfur dioxide, SO2 and oxynitride, NOx) derived from fossil fuel consumption are the major contributions to global warming and regional atmospheric contamination, the appropriate measurement of environmental efficiency and emission abatement efficiency with sound theoretical base and methodical framework is crucial for making the measure of sustainability and the pursuing of sustainable development accountable and then assisting policy and decision making in line with constructing a more sustainable society. This is more obvious for China's thermal power industry since China is currently the world's largest energy consumer and greenhouse gas emitter. In addition, the thermal power industry consumes approximately 45% of the total primary energy supply and contributes more than 40% of carbon emission in China in 2014 (Wang, Lee, Zhang, & Wei, 2016). To construct a resource saving and environmentally friendly society has become one of China's primary strategies for pursuing sustainable development, and to promote environmental and abatement efficiency has also become a major policy in China's thermal power industry in which the net coal consumption rate,1 and the total amounts of SO2 and NOx emissions of electricity generation are regulated to reduce by 12%, 41% and 29%, respectively, during China's 11th and 12th Five Year Plan (FYP) periods (2006–2010 and 2011–2015) (SCC 2007, SERC 2011, Wang et al., 2016). As the government and the industry has begun to implement mechanism to reduce carbon emission and air pollutants, mathematical modelling of environmental and abatement efficiency that provide more accurate and deep insight information to national environmental policy making and thermal power industry decision making would help to promote the performances of environmental management and sustainable development.

One line of cutting-edge research on this issue has applied the widely accepted Data Envelopment Analysis (DEA) (Banker et al., 1984, Charnes et al., 1978, Cooper et al., 2011, Zhu, 2014) to develop efficiency and productivity evaluation models for decision making units (DMU), e.g., thermal power industry sector in this study, that contain both normal input and output variables (i.e., energy, labour, capital, and electricity) and variables that measure undesirable outputs, e.g., greenhouse gas and other pollutants. In the presence of including environmental regulations in efficiency evaluation of thermal power industry, both desirable output and undesirable output need to be modelled simultaneously, since the reduction of pollution might result in diverting some desirable output and input to pollution abatement activities (Adler and Volta, 2016, Dakpo et al., 2016). In the literature applying DEA method, the modelling of undesirable outputs has been formalized in several ways as (i) treating pollutions as free disposable inputs (Hailu & Veeman, 2001); (ii) treating pollutions as weak disposable outputs (Färe and Grosskopf, 2004, Färe et al., 1989); (iii) treating pollutions as multiplicative inverse outputs or as large constant added additive inverse outputs (Sahoo et al., 2011, Scheel, 2001, Seiford and Zhu, 2002, Seiford and Zhu, 2005); (iv) using two sub-technologies generating desirable output and undesirable output separately (e.g., by-production method and natural/managerial disposability method) (Murty et al., 2012, Sueyoshi and Goto, 2012); (v) using the materials balance principle (MBP) to include the laws of thermodynamics (e.g., weak G-disposability method) (Coelli et al., 2007, Hampf and Rødseth, 2015, Welch and Barnum, 2009).

The method of treating undesirable outputs as inputs has been seriously challenged as it does not reflect the real production process and does not satisfy the physical laws. The idea of undesirable output data transformation (multiplicative inverse or additive inverse) has also been challenged since the results obtained from it are inconsistent. With respect to the assumption of weak disposability of undesirable output, there are also several weaknesses in efficiency measures, for instance, it violates the monotonicity in the production of undesirable output and thus may lead to inappropriate estimation of shadow price of pollution; it may evaluate strongly dominated DMU as efficient, and which may be further used as target for benchmarking (Chen and Delmas, 2012, Leleu, 2013). Furthermore, there is another argument against weak disposability that it is not consistent with the laws of thermodynamics in the case that the end-of-pipe abatement is not available (Dakpo et al., 2016, Førsund, 2009, Hampf and Rødseth, 2015).

The violation of physical laws of the above methods may result in inaccurate estimation of environmental efficiency, especially when physical productivity is of concern, which is highlighted in the modelling of air pollutant emissions from electricity generation (Hampf, 2014, Welch and Barnum, 2009). Therefore, in this study we incorporate the materials balance principle which accounts for the laws of thermodynamics in our modelling and propose several DEA based models for environmental efficiency and abatement efficiency evaluation. The major contribution of this study is that our approach is along the same line of weak G-disposability assumption based modelling but is an extension to existing models, since our approach highlights the identification of all possible adjustments on polluting mass bound in inputs and outputs, as well as potential adjustments on abatement of pollutants. In addition, our approach decomposes the overall environmental efficiency measure into technical efficiency, polluting inputs allocative efficiency, and polluting and non-polluting inputs allocative efficiency measures with the emphasis on the modelling of pollution abatement activities in the efficiency measures. Accordingly, several new measures of abatement efficiency are developed. Furthermore, we propose several global Malmquist productivity indices to additionally identify the changes on environmental and abatement efficiency. Our approach is applied to China's thermal power industry. The regional environmental and abatement efficiency levels and the trends of efficiency movements, as well as the associated emission reduction potentials and abatement improvement potentials on air pollutants for this industry are estimated. There have been several mathematical programming based or parametric model based studies that address the energy and environmental efficiency evaluation of China's electricity industry (e.g., Bi et al., 2014, Du et al., 2013, Duan et al., 2016, Yang and Pollitt, 2009, Zhao et al., 2015), however, none of them, to our knowledge, has properly address the materials balance principle. Our paper is the first attempt to implement the DEA based MBP approach empirically in China's thermal power industry. Our empirical study verifies that there were overall environmental efficiency promotion in China's thermal power industry and identifies that this promotion was mainly derived from the quality promotion on coal utilized for electricity generation and the structure optimization on polluting and non-polluting input mix in China's thermal power industry.

The remainder of this paper is organized as follows. The next section explains the proposed materials balance approach for environmental and abatement efficiency evaluation. Section 3 presents the application to China's thermal power industry. The summary and conclusion are provided in the final section.

Section snippets

Materials balance approach for environmental and abatement efficiency measurements

In this section, we start by introducing the materials balance approach for modelling environmental and abatement technologies. Then, we introduce three generalized nonparametric optimization models for estimating the minimal amounts of pollutions for given desirable outputs and (i) fixed inputs, (ii) fixed non-polluting inputs, and (iii) variable inputs, respectively. These minimal amounts of pollutions are used for measuring environmental efficiency which can be additionally decomposed into

Application to China's thermal power industry

In this section, we present the application of the environmental and abatement efficiency measurements to China's regional thermal power industries. We use the observations of China's thermal power industry at provincial level during the period of 2006–2014 which covers China's 11th FYP period and the major years of the 12th FYP period. During these periods, the regulations for major air pollutions control such as SO2, NOx, and dust & soot emissions reduction were implemented, while there is no

Conclusion

In this study we proposed a DEA based generalized approach that is combined with the materials balance principle to jointly evaluate environmental and abatement efficiency. The proposed approach is along the line of weak G-disposability assumption based modelling but is an extension to existing models that in our approach the identification of all possible adjustments on polluting mass bound in inputs and outputs, as well as potential adjustments on abatement of pollutants are emphasized. The

Acknowledgment

We gratefully acknowledge the financial supports from the National Natural Science Foundation of China (grant numbers 71471018, 71521002 and 71642004), the Social Science Foundation of Beijing (grant number 16JDGLB013), the National Key R&D Program (grant number 2016YFA0602603), the Joint Development Program of Beijing Municipal Commission of Education, and the Research Program of State Grid Corporation of China (grant number YD71-16-014). K. Wang would like to thank Prof. F. R. Førsund of

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