Abstract
The objective of this paper is to conduct a comparative analysis of the real and potential CO2 emission intensity in China’s agricultural sector. In order to perform this goal, this paper combines the concept of the meta-frontier efficiency and the directional distance function to process empirical work. This methodology allows for the incorporation of technological heterogeneities into the efficiency analysis and implementation results of increment in desirable outputs and reduction in undesirable outputs. Empirical results indicate that the average total-factor CO2 emission efficiency is 0.481 and has a slight downward trend over the studied period, which is lower than that of the whole industry in China. CO2 emission efficiency and the technology gap ratios among different regions in China’s agricultural sector show different space–time characteristics. A comparative analysis is applied in this study to verify the relationship between the actual and potential CO2 intensities, whose average values are, respectively, 0.1972 and 0.0816 Mtc/billion yuan RMB. Research shows that there exists huge space for CO2 intensity reduction. Meanwhile, the major contributor to the potential CO2 intensity reduction varies across different regions, as managerial failure for most provinces in the eastern and central regions and technology gap in the western regions.
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Asafu-Adjaye J, Byrne D, Alvarez M (2016) Economic growth, fossil fuel and non-fossil consumption: a Pooled Mean Group analysis using proxies for capital. Energy Econ 60:345–356. https://doi.org/10.1016/j.eneco.2016.10.016
Azad B, Afzali SF, Francaviglia R (2019) Simulating soil CO2 emissions under present and climate change conditions in selected vegetation covers of a semiarid region. Int J Environ Sci Technol. https://doi.org/10.1007/s13762-019-02581-3
Beltran-Esteve M, Reig-Martinez E, Estruch-Guitart V (2017) Assessing eco-efficiency: a metafrontier directional distance function approach using life cycle analysis. Environ Impact Assess 63:116–127. https://doi.org/10.1016/j.eiar.2017.01.001
Bian YW, He P, Xu H (2013) Estimation of potential energy saving and carbon dioxide emission reduction in China based on an extended non-radial DEA approach. Energy Policy 63:962–971. https://doi.org/10.1016/j.enpol.2013.08.051
Bolouri S, Vafeainejad A, Alesheikh A, Aghamohammadi H (2019) Environmental sustainable development optimizing the location of urban facilities using vector assignment ordered median problem-integrated GIS. Int J Environ Sci Technol. https://doi.org/10.1007/s13762-019-02573-3
Cecchini L, Venanzi S, Pierri A, Chiorri M (2018) Environmental efficiency analysis and estimation of CO2 abatement costs in dairy cattle farms in Umbria (Italy): a SBM-DEA model with undesirable output. J Clean Prod 197:895–907. https://doi.org/10.1016/j.jclepro.2018.06.165
Chambers RG, Chung YH, Fare R (1996) Benefit and distance functions. J Econ Theory 70:407–419. https://doi.org/10.1006/jeth.1996.0096
Chang YT, Park HS, Jeong JB, Lee JW (2014) Evaluating economic and environmental efficiency of global airlines: a SBM-DEA approach. Transp Res D Transp Environ 27:46–50. https://doi.org/10.1016/j.trd.2013.12.013
Chen Y, Du J, Huo JZ (2013) Super-efficiency based on a modified directional distance function. Omega Int J Manag Sci 41:621–625. https://doi.org/10.1016/j.omega.2012.06.006
Chiu CR, Liou JL, Wu PI, Fang CL (2012) Decomposition of the environmental inefficiency of the meta-frontier with undesirable output. Energy Econ 34:1392–1399. https://doi.org/10.1016/j.eneco.2012.06.003
Cho HI, Freyre A, Burer M, Patel MK (2019) Comparative analysis of customer-funded energy efficiency programs in the United States and Switzerland Cost-effectiveness and discussion of operational practices. Energy Policy. https://doi.org/10.1016/j.enpol.2019.111010
Choi KH, Ang BW, Ro KK (1995) Decomposition of the energy-intensity index with application for the Korean manufacturing-industry. Energy 20:835–842
Chung YH, Fare R, Grosskopf S (1997) Productivity and undesirable outputs: a directional distance function approach. J Environ Manag 51:229–240. https://doi.org/10.1006/jema.1997.0146
Du KR, Huang L, Yu K (2014) Sources of the potential CO2 emission reduction in China: a nonparametric metafrontier approach. Appl Energy 115:491–501. https://doi.org/10.1016/j.apenergy.2013.10.046
Du HB, Matisoff DC, Wang YY, Liu X (2016) Understanding drivers of energy efficiency changes in China. Appl Energy 184:1196–1206. https://doi.org/10.1016/j.apenergy.2016.05.002
Fare R, Grosskopf S, Lovell CAK, Pasurka C (1989) Multilateral productivity comparisons when some outputs are undesirable—a nonparametric approach. Rev Econ Stat 71:90–98
Fare R, Grosskopf S, Noh DW, Weber W (2005) Characteristics of a polluting technology: theory and practice. J Econom 126:469–492
Fare R, Grosskopf S, Pasurka CA (2007) Environmental production functions and environmental directional distance functions. Energy 32:1055–1066. https://doi.org/10.1016/j.energy.2006.09.005
Färe Rolf, Grosskopf S, Logan J, Lovell CAK (1985) Measuring efficiency in production: with an application to electric utilities. Managerial issues in productivity analysis. Springer, The Netherlands
Fernando Y, Hor WL (2017) Impacts of energy management practices on energy efficiency and carbon emissions reduction: a survey of Malaysian manufacturing firms. Resour Conserv Recycl 126:62–73. https://doi.org/10.1016/j.resconrec.2017.07.023
Finnerty N, Sterling R, Contreras S, Coakley D, Keane MM (2018) Defining corporate energy policy and strategy to achieve carbon emissions reduction targets via energy management in non-energy intensive multi-site manufacturing organisations. Energy 151:913–929. https://doi.org/10.1016/j.energy.2018.03.070
Fossati M, Scalco VA, Linczuk VCC, Lamberts R (2016) Building energy efficiency: an overview of the Brazilian residential labeling scheme. Renew Sust Energy Rev 65:1216–1231. https://doi.org/10.1016/j.rser.2016.06.048
Haidar N, Attia M, Senouci SM, Aglzim E, Kribeche A, Asus ZB (2018) New consumer-dependent energy management system to reduce cost and carbon impact in smart buildings. Sustain Cities Soc 39:740–750. https://doi.org/10.1016/j.scs.2017.11.033
Haley B, Gaede J, Winfield M, Love P (2020) From utility demand side management to low-carbon transitions: opportunities and challenges for energy efficiency governance in a new era. Energy Res Soc Sci. https://doi.org/10.1016/j.erss.2019.101312
Hutchinson S, Langham M (1999) Productivity growth, technical progress and efficiency change in the Caribbean: key ingredients for international competitiveness? Am J Agric Econ 81:1287
Ibrahim RI (2018) Improving energy efficiency and fouling mitigation for membrane bioreactor in Al-Rustamiyah sewage treatment plant based on hydrodynamics. Int J Environ Sci Technol 15:2369–2380. https://doi.org/10.1007/s13762-017-1605-7
Li ZL, Dai HC, Song JN, Sun L, Geng Y, Lu KY, Hanaoka T (2019) Assessment of the carbon emissions reduction potential of China’s iron and steel industry based on a simulation analysis. Energy 183:279–290. https://doi.org/10.1016/j.energy.2019.06.099
Lin BQ, Du KR (2015) Energy and CO2 emissions performance in China’s regional economies: do market-oriented reforms matter? Energy Policy 78:113–124. https://doi.org/10.1016/j.enpol.2014.12.025
Liu XH, Ji X, Zhang DQ, Yang JJ, Wang YH (2019) How public environmental concern affects the sustainable development of Chinese cities: an empirical study using extended DEA models. J Environ Manag. https://doi.org/10.1016/j.jenvman.2019.109619
Ma D, Fei RL, Yu YS (2019) How government regulation impacts on energy and CO2 emissions performance in China’s mining industry. Resour Policy 62:651–663. https://doi.org/10.1016/j.resourpol.2018.11.013
Malinauskaite J, Jouhara H, Ahmad L, Milani M, Montorsi L, Venturelli M (2019) Energy efficiency in industry: EU and national policies in Italy and the UK. Energy 172:255–269. https://doi.org/10.1016/j.energy.2019.01.130
Marzi S, Farnia L, Dasgupta S, Mysiak J, Lorenzoni A (2019) Competence analysis for promoting energy efficiency projects in developing countries: the case of OPEC. Energy. https://doi.org/10.1016/j.energy.2019.115996
Monasterolo I, Raberto M (2019) The impact of phasing out fossil fuel subsidies on the low-carbon transition. Energy Policy 124:355–370. https://doi.org/10.1016/j.enpol.2018.08.051
Nicoletti G, Arcuri N, Nicoletti G, Bruno R (2015) A technical and environmental comparison between hydrogen and some fossil fuels. Energy Convers Manag 89:205–213. https://doi.org/10.1016/j.enconman.2014.09.057
Oggioni G, Riccardi R, Toninelli R (2011) Eco-efficiency of the world cement industry: a data envelopment analysis. Energy Policy 39:2842–2854. https://doi.org/10.1016/j.enpol.2011.02.057
Riccardi R, Oggioni G, Toninelli R (2012) Efficiency analysis of world cement industry in presence of undesirable output: application of data envelopment analysis and directional distance function. Energy Policy 44:140–152. https://doi.org/10.1016/j.enpol.2012.01.030
Song ML, Wang JL (2018) Environmental efficiency evaluation of thermal power generation in China based on a slack-based endogenous directional distance function model. Energy 161:325–336. https://doi.org/10.1016/j.energy.2018.07.158
Sueyoshi T, Goto M (2012) DEA radial and non-radial models for unified efficiency under natural and managerial disposability: theoretical extension by strong complementary slackness conditions. Energy Econ 34:700–713. https://doi.org/10.1016/j.eneco.2011.12.013
Sueyoshi T, Sekitani K (2007) Measurement of returns to scale using a non-radial DEA model: a range-adjusted measure approach. Eur J Oper Res 176:1918–1946. https://doi.org/10.1016/j.ejor.2005.10.043
Sueyoshi T, Yuan Y (2017) Social sustainability measured by intermediate approach for DEA environmental assessment: Chinese regional planning for economic development and pollution prevention. Energy Econ 66:154–166. https://doi.org/10.1016/j.eneco.2017.06.008
Sun HP, Edziah BK, Sun CW, Kporsu AK (2019) Institutional quality, green innovation and energy efficiency. Energy Policy. https://doi.org/10.1016/j.enpol.2019.111002
Tajbakhsh A, Hassini E (2018) Evaluating sustainability performance in fossil-fuel power plants using a two-stage data envelopment analysis. Energy Econ 74:154–178. https://doi.org/10.1016/j.eneco.2018.05.032
Tallini A, Cedola L (2016) Evaluation methodology for energy efficiency measures in industry and service sector. Energy Proced 101:542–549. https://doi.org/10.1016/j.egypro.2016.11.069
Tao XP, Wang P, Zhu BZ (2016) Provincial green economic efficiency of China: a non-separable input-output SBM approach. Appl Energy 171:58–66. https://doi.org/10.1016/j.apenergy.2016.02.133
Trianni A, Cagno E, Accordini D (2019) Energy efficiency measures in electric motors systems: a novel classification highlighting specific implications in their adoption. Appl Energy. https://doi.org/10.1016/j.apenergy.2019.113481
Wang K, Lu B, Wei YM (2013) China’s regional energy and environmental efficiency: a range-adjusted measure based analysis. Appl Energy 112:1403–1415. https://doi.org/10.1016/j.apenergy.2013.04.021
Wang QW, Hang Y, Sun LC, Zhao ZY (2016) Two-stage innovation efficiency of new energy enterprises in China: a non-radial DEA approach. Technol Forecast Soc 112:254–261. https://doi.org/10.1016/j.techfore.2016.04.019
Weng YY, Zhang XL (2017) The role of energy efficiency improvement and energy substitution in achieving China’s carbon intensity target. In: Proceedings of the 9th international conference on applied energy, vol 142, pp 2786–2790. https://doi.org/10.1016/j.egypro.2017.12.422
Wu Y (2016) China’s capital stock series by region and sector. Academic abstracts of Chinese institutions of higher learning economics 011(001):156–172 (in Chinese)
Yildiz I, Acikkalp E, Caliskan H, Mori K (2019) Environmental pollution cost analyses of biodiesel and diesel fuels for a diesel engine. J Environ Manag 243:218–226. https://doi.org/10.1016/j.jenvman.2019.05.002
Zhang N, Zhou P, Choi Y (2013) Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: a meta-frontier non-radial directional distance function analysis. Energy Policy 56:653–662. https://doi.org/10.1016/j.enpol.2013.01.033
Zhou P, Ang BW, Wang H (2012) Energy and CO2 emission performance in electricity generation: a non-radial directional distance function approach. Eur J Oper Res 221:625–635. https://doi.org/10.1016/j.ejor.2012.04.022
Zhu T, Li RR, Ma MF, Li X (2017) Influence of energy efficiency on VOCs decomposition in non-thermal plasma reactor. Int J Environ Sci Technol 14:1505–1512. https://doi.org/10.1007/s13762-017-1256-8
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The authors are indebted to the anonymous referees and the editors for their valuable and constructive suggestions. The research was supported by the financial support from the Ministry of Education of Humanities and Social Science Project of China (No. 19YJC630206), the Natural Science Foundation of Fujian Province under grant (No. 2019J01215) and Fundamental Research Funds for the Central Universities, China (2019III185).
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Fei, R.L., You, W.H. & Wang, H.L. Can China achieve its CO2 emission reduction targets in agriculture sector? Evidence from technological efficiency analysis. Int. J. Environ. Sci. Technol. 17, 4249–4264 (2020). https://doi.org/10.1007/s13762-020-02754-5
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DOI: https://doi.org/10.1007/s13762-020-02754-5