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Environmental efficiency and abatement efficiency measurements of China’s thermal power industry: a data envelopment analysis based materials balance approach. (English) Zbl 1431.91285

Summary: 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.

MSC:

91B76 Environmental economics (natural resource models, harvesting, pollution, etc.)
90B50 Management decision making, including multiple objectives

Software:

DEAFrontier
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Full Text: DOI

References:

[1] Adler, N.; Volta, N., Accounting for externalities and disposability: A directional economic environmental distance function, European Journal of Operational Research, 250, 1, 314-327 (2016) · Zbl 1346.91117
[2] Ayres, R. U.; Kneese, A. V., Production, consumption, and externalities, The American Economic Review, 59, 3, 282-297 (1969)
[3] Banker, R. D.; Charnes, A.; Cooper, W. W., Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science, 30, 9, 1078-1092 (1984) · Zbl 0552.90055
[4] Bi, G. B.; Song, W.; Zhou, P.; Liang, L., Does environmental regulation affect energy efficiency in China’s thermal power generation? Empirical evidence from a slacks-based DEA model, Energy Policy, 66, 537-546 (2014)
[5] Caves, D. W.; Christensen, L. R.; Diewert, W. E., The economic theory of index numbers and the measurement of input, output, and productivity, Econometrica, 50, 6, 1393-1414 (1982) · Zbl 0524.90028
[6] Charnes, A.; Cooper, W. W.; Rhodes, E., Measuring the efficiency of decision making units, European Journal of Operational Research, 2, 6, 429-444 (1978) · Zbl 0416.90080
[7] Chen, C. M.; Delmas, M. A., Measuring eco-inefficiency: A new frontier approach, Operations Research, 60, 5, 1064-1079 (2012) · Zbl 1257.91038
[8] Chung, Y. H.; Färe, R.; Grosskopf, S., Productivity and undesirable outputs: A directional distance function approach, Journal of Environmental Management, 51, 3, 229-240 (1997)
[9] Chung, Y. H., Directional distance functions and undesirable outputs (1997), Southern Illinois University
[10] Coelli, T.; Lauwers, L.; Van Huylenbroeck, G., Environmental efficiency measurement and the materials balance condition, Journal of Productivity Analysis, 28, 1-2, 3-12 (2007)
[11] (Cooper, W. W.; Seiford, L. M.; Zhu, J., Handbook on data envelopment analysis, 164 (2011), Springer Science & Business Media) · Zbl 1050.90002
[12] Dakpo, K. H.; Jeanneaux, P.; Latruffe, L., Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric framework, European Journal of Operational Research, 250, 2, 347-359 (2016) · Zbl 1346.91176
[13] Du, L.; He, Y.; Yan, J., The effects of electricity reforms on productivity and efficiency of China’s fossil-fired power plants: An empirical analysis, Energy Economics, 40, 804-812 (2013)
[14] Duan, N.; Guo, J. P.; Xie, B. C., Is there a difference between the energy and \(CO_2\) emission performance for China’s thermal power industry? A bootstrapped directional distance function approach, Applied Energy, 162, 1552-1563 (2016)
[15] European Environment Agency. (2013). EN08 Emissions (CO2, SO2 and NOx) intensity of public conventional thermal power (electricity and heat) production. Indicator Fact Sheet IND-132-en. http://www.eea.europa.eu/data-and-maps/indicators/en08-emissions-co2-so2-and-1; European Environment Agency. (2013). EN08 Emissions (CO2, SO2 and NOx) intensity of public conventional thermal power (electricity and heat) production. Indicator Fact Sheet IND-132-en. http://www.eea.europa.eu/data-and-maps/indicators/en08-emissions-co2-so2-and-1
[16] Expert Group on Techno-Economic Issues. (2012). Guidance document on control techniques for emissions of sulphur, NOx, VOC, dust (including PM10, PM2.5 and black carbon) from stationary sources. Working Group on Strategies and Review, Fiftieth session. http://www.unece.org/fileadmin/DAM/env/documents/2012/EB/Informal_document_7_EGTEI_guidance-document_on_stationary_sources_tracked_changes_compared_with_WGSR_version.pdf; Expert Group on Techno-Economic Issues. (2012). Guidance document on control techniques for emissions of sulphur, NOx, VOC, dust (including PM10, PM2.5 and black carbon) from stationary sources. Working Group on Strategies and Review, Fiftieth session. http://www.unece.org/fileadmin/DAM/env/documents/2012/EB/Informal_document_7_EGTEI_guidance-document_on_stationary_sources_tracked_changes_compared_with_WGSR_version.pdf
[17] Fan, M.; Shao, S.; Yang, L., Combining global Malmquist-Luenberger index and generalized method of moments to investigate industrial total factor CO 2 emission performance: A case of Shanghai (China), Energy Policy, 79, 189-201 (2015)
[18] Färe, R.; Grosskopf, S., Modeling undesirable factors in efficiency evaluation: comment, European Journal of Operational Research, 157, 1, 242-245 (2004) · Zbl 1080.90527
[19] Färe, R.; Grosskopf, S., Intertemporal Production Frontiers: With Dynamic DEA (1996), Kluwer Academic Publishers
[20] Färe, R.; Grosskopf, S.; Lindgren, B.; Roos, P., Productivity changes in Swedish pharamacies 1980-1989: A non-parametric Malmquist approach, Journal of Productivity Analysis, 3, 1-2, 85-101 (1992)
[21] Färe, R.; Grosskopf, S.; Lovell, C. K.; Pasurka, C., Multilateral productivity comparisons when some outputs are undesirable: A nonparametric approach, The Review of Economics and Statistics, 90-98 (1989)
[22] Färe, R.; Grosskopf, S.; Pasurka, C. A., Environmental production functions and environmental directional distance functions, Energy, 32, 7, 1055-1066 (2007)
[23] Färe, R.; Grosskopf, S.; Pasurka, C. A., Pollution abatement activities and traditional productivity, Ecological Economics, 62, 3, 673-682 (2007)
[24] Färe, R.; Grosskopf, S.; Pasurka, C., Joint production of good and bad outputs with a network application, Encyclopedia of Energy, Natural Resources and Environmental Economics, 2, 109-118 (2013)
[25] Førsund, F. R., Good modelling of bad outputs: Pollution and multiple-output production, International Review of Environmental and Resource Economics, 3, 1, 1-38 (2009)
[26] Hailu, A.; Veeman, T. S., Non-parametric productivity analysis with undesirable outputs: An application to the Canadian pulp and paper industry, American Journal of Agricultural Economics, 83, 3, 605-616 (2001)
[27] Hampf, B., Separating environmental efficiency into production and abatement efficiency: A nonparametric model with application to US power plants, Journal of Productivity Analysis, 41, 3, 457-473 (2014)
[28] Hampf, B.; Rødseth, K. L., Carbon dioxide emission standards for US power plants: An efficiency analysis perspective, Energy Economics, 50, 140-153 (2015)
[29] Hoang, V. N.; Rao, D. P., Measuring and decomposing sustainable efficiency in agricultural production: A cumulative exergy balance approach, Ecological economics, 69, 9, 1765-1776 (2010)
[30] Hoang, V. N.; Coelli, T., Measurement of agricultural total factor productivity growth incorporating environmental factors: A nutrients balance approach, Journal of Environmental Economics and Management, 62, 3, 462-474 (2011)
[31] IPCC guidelines for national greenhouse gas inventories: Volume II energy (2006), Institute for Global Environmental Strategies: Institute for Global Environmental Strategies Japan
[32] Leleu, H., Shadow pricing of undesirable outputs in nonparametric analysis, European Journal of Operational Research, 231, 2, 474-480 (2013) · Zbl 1317.62087
[33] Murty, S.; Russell, R. R.; Levkoff, S. B., On modeling pollution-generating technologies, Journal of Environmental Economics and Management, 64, 1, 117-135 (2012)
[34] China energy statistical yearbook (2009), National Bureau of Statistics of People’s Republic of China (NBS): National Bureau of Statistics of People’s Republic of China (NBS) Beijing, China
[35] Oh, D. H., A global Malmquist-Luenberger productivity index, Journal of productivity analysis, 34, 3, 183-197 (2010)
[36] Pastor, J. T.; Lovell, C. K., A global Malmquist productivity index, Economics Letters, 88, 2, 266-271 (2005) · Zbl 1254.91615
[37] Rødseth, K. L., Environmental efficiency measurement and the materials balance condition reconsidered, European Journal of Operational Research, 250, 1, 342-346 (2016) · Zbl 1348.91225
[38] Sahoo, B. K.; Luptacik, M.; Mahlberg, B., Alternative measures of environmental technology structure in DEA: An application, European Journal of Operational Research, 215, 3, 750-762 (2011) · Zbl 1238.91116
[39] SCC. (2007). State Council of the People’s Republic of China: Comprehensive Work Plan for Energy Conservation and Emissions Reduction.; SCC. (2007). State Council of the People’s Republic of China: Comprehensive Work Plan for Energy Conservation and Emissions Reduction.
[40] SCC. (2011). State Council of the People’s Republic of China: Plan for Energy Conservation and Emissions Reduction in the 12th Five Year Plan Period.; SCC. (2011). State Council of the People’s Republic of China: Plan for Energy Conservation and Emissions Reduction in the 12th Five Year Plan Period.
[41] Scheel, H., Undesirable outputs in efficiency valuations, European Journal of Operational Research, 132, 2, 400-410 (2001) · Zbl 0985.90053
[42] Seiford, L. M.; Zhu, J., Modeling undesirable factors in efficiency evaluation, European Journal of Operational Research, 142, 1, 16-20 (2002) · Zbl 1079.90565
[43] Seiford, L. M.; Zhu, J., A response to comments on modeling undesirable factors in efficiency evaluation, European Journal of Operational Research, 161, 2, 579-581 (2005) · Zbl 1081.90570
[44] SERC. (2011). State electricity regulatory commission of the People’s Republic of China: Energy and emission reduction conditions of the power industry in 2010 and during the 11th Five Year Plan period.; SERC. (2011). State electricity regulatory commission of the People’s Republic of China: Energy and emission reduction conditions of the power industry in 2010 and during the 11th Five Year Plan period.
[45] Sueyoshi, T.; Goto, M., Data envelopment analysis for environmental assessment: Comparison between public and private ownership in petroleum industry, European Journal of Operational Research, 216, 3, 668-678 (2012) · Zbl 1237.90151
[46] Wang, K.; Lee, C. Y.; Zhang, J.; Wei, Y. M., Operational performance management of the power industry: A distinguishing analysis between effectiveness and efficiency, Annals of Operations Research (2016), in press
[47] Wang, K.; Wei, Y. M., Sources of energy productivity change in China during 1997-2012: A decomposition analysis based on the Luenberger productivity indicator, Energy Economics, 54, 50-59 (2016)
[48] Wang, K.; Wei, Y. M.; Zhang, X., A comparative analysis of China’s regional energy and emission performance: Which is the better way to deal with undesirable outputs?, Energy Policy, 46, 574-584 (2012)
[49] Wang, K.; Wei, Y. M.; Zhang, X., Energy and emissions efficiency patterns of Chinese regions: A multi-directional efficiency analysis, Applied Energy, 104, 105-116 (2013)
[50] Wang, K.; Xian, Y.; Wei, Y. M.; Huang, Z., Sources of carbon productivity change: A decomposition and disaggregation analysis based on global Luenberger productivity indicator and endogenous directional distance function, Ecological Indicators, 66, 545-555 (2016)
[51] Wang, K.; Zhang, X.; Yu, X.; Wei, Y. M.; Wang, B., Emissions trading and abatement cost savings: An estimation of China’s thermal power industry, Renewable and Sustainable Energy Reviews, 65, 1005-1017 (2016)
[52] Welch, E.; Barnum, D., Joint environmental and cost efficiency analysis of electricity generation, Ecological Economics, 68, 8, 2336-2343 (2009)
[53] Yang, H.; Pollitt, M., Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants, European Journal of Operational Research, 197, 3, 1095-1105 (2009)
[54] Zhao, X.; Yin, H.; Zhao, Y., Impact of environmental regulations on the efficiency and \(CO_2\) emissions of power plants in China, Applied Energy, 149, 238-247 (2015)
[55] Zhou, P.; Ang, B. W.; Poh, K. L., Slacks-based efficiency measures for modeling environmental performance, Ecological Economics, 60, 1, 111-118 (2006)
[56] Zhu, J., Quantitative models for performance evaluation and benchmarking: Data envelopment analysis with spreadsheets, 213 (2014), Springer · Zbl 1297.90002
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