Abstract
This paper provides an assessment of energy density and energy efficiency and creates an important indicator of environmental performance. This article applied two mathematical models and econometric techniques to obtain detailed and specific results. The DEA and the non-normative account aggregation mean a collective aggregation to form a mathematical aggregation tool to create an environmental index for the BRICS countries (Brazil, Russia, India, China, and South Africa) based on available data from 2011 to 2016. The advantage of the proposed approach is to manage the irregularities of the data and follow the desired properties of the index number. The current paper is relevant for the broad scope of construction, the environmental index, and the evolution of the rankings of countries based on multiple indicators. Our results indicate that Brazil and Russia have the highest values of the Environmental Performance Index, which range between 67.44 and 60.70, respectively. India has a minimum value of 30.57 of the environmental index. The analysis shows that Brazil, Russia, and South Africa have the best scores and that these countries have the best results, while China and India also have the best results. This study can help form a valuable political tool for the development and development of the country’s politics.
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References
Aida K, Cooper WW, Pastor JT, Sueyoshi T (1998) Evaluating water supply services in Japan with RAM: a range-adjusted measure of inefficiency. Omega 26:207–232. https://doi.org/10.1016/S0305-0483(97)00072-8
Al Asbahi AAMH, Gang FZ, Iqbal W et al (2019) Novel approach of principal component analysis method to assess the national energy performance via Energy Trilemma Index. Energy Reports 5:704–713. https://doi.org/10.1016/j.egyr.2019.06.009
Augutis J, Krikstolaitis R, Martisauskas L, Peciulyte S (2012) Energy security level assessment technology. Appl Energy 97:143–149. https://doi.org/10.1016/j.apenergy.2011.11.032
Chandel SS, Shrivastva R, Sharma V, Ramasamy P (2016) Overview of the initiatives in renewable energy sector under the national action plan on climate change in India. Renew. Sustain. Energy Rev.
Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2:429–444. https://doi.org/10.1016/0377-2217(78)90138-8
Cooper WW, Park KS, Yu G (1999) IDEA and AR-IDEA: Models for dealing with imprecise data in DEA. Manage Sci 45:597–607. https://doi.org/10.1287/mnsc.45.4.597
Cook WD, Seiford LM (2009) Data envelopment analysis (DEA) - thirty years on. Eur J Oper Res. 192:1–17. https://doi.org/10.1016/j.ejor.2008.01.032
Cui L, Li R, Song M, Zhu L (2019) Can China achieve its 2030 energy development targets by fulfilling carbon intensity reduction commitments? Energy Econ 83:61–73. https://doi.org/10.1016/j.eneco.2019.06.016
Decancq K, Lugo MA (2013) Weights in multidimensional indices of wellbeing: an overview. Econom Rev 32:7–34. https://doi.org/10.1080/07474938.2012.690641
Ebert U, Welsch H (2004) Meaningful environmental indices: a social choice approach. J Environ Econ Manage 47:270–283. https://doi.org/10.1016/j.jeem.2003.09.001
Faere R, Grosskopf S, Lovell CAK, Pasurka C (1989) Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach. Rev Econ Stat 71:90. https://doi.org/10.2307/1928055
Färe R, Grosskopf S (2010) Directional distance functions and slacks-based measures of efficiency. Eur J Oper Res 200:320–322. https://doi.org/10.1016/J.EJOR.2009.01.031
Fusco E (2015) Enhancing non-compensatory composite indicators: a directional proposal. Eur J Oper Res 242:620–630. https://doi.org/10.1016/J.EJOR.2014.10.017
Huang J, Yang X, Cheng G, Wang S (2014) A comprehensive eco-efficiency model and dynamics of regional eco-efficiency in China. J Clean Prod. 67:228–238. https://doi.org/10.1016/j.jclepro.2013.12.003
IEA (2017) World Energy Outlook 2017. Int Energy Agency Paris, Fr 1:1–15. https://doi.org/10.1016/0301-4215(73)90024-4
Iqbal W, Yumei H, Abbas Q, Hafeez M, Mohsin M, Fatima A, Jamali M, Jamali M, Siyal A, Sohail N (2019) Assessment of wind energy potential for the production of renewable hydrogen in Sindh Province of Pakistan. Processes 7. https://doi.org/10.3390/pr7040196
Iram R, Zhang J, Erdogan S, Abbas Q, Mohsin M (2019) Economics of energy and environmental efficiency: evidence from OECD countries. Environ Sci Pollut Res. 27:3858–3870. https://doi.org/10.1007/s11356-019-07020-x
Johansson B (2013) A broadened typology on energy and security. Energy 53:199–205. https://doi.org/10.1016/j.energy.2013.03.012
Knox Lovell CA, Pastor JT, Turner JA (1995) Measuring macroeconomic performance in the OECD: a comparison of European and non-European countries. Eur J Oper Res. 87:507–518. https://doi.org/10.1016/0377-2217(95)00226-X
Li H, Fang K, Yang W, Wang D, Hong X (2013) Regional environmental efficiency evaluation in China: analysis based on the Super-SBM model with undesirable outputs. Math Comput Model. 58:1018–1031. https://doi.org/10.1016/j.mcm.2012.09.007
Martchamadol J, Kumar S (2014) The Aggregated Energy Security Performance Indicator (AESPI) at national and provincial level. Appl Energy 127:219–238. https://doi.org/10.1016/j.apenergy.2014.04.045
Mohsin M, Abbas Q, Zhang J, Ikram M, Iqbal N (2019a) Integrated effect of energy consumption, economic development, and population growth on CO2 based environmental degradation: a case of transport sector. Environ Sci Pollut Res. 26:32824–32835. https://doi.org/10.1007/s11356-019-06372-8
Mohsin M, Rasheed AK, Saidur R (2018a) Economic viability and production capacity of wind generated renewable hydrogen. Int. J. Hydrogen Energy 43:2621–2630
Mohsin M, Rasheed AK, Sun H, Zhang J, Iram R, Iqbal N, Abbas Q (2019b) Developing low carbon economies: an aggregated composite index based on carbon emissions. Sustain Energy Technol Assessments 35:365–374. https://doi.org/10.1016/j.seta.2019.08.003
Mohsin M, Zaidi U, Abbas Q et al (2019c) Relationship between multi-factor pricing and equity price fragility: evidence from Pakistan. Int J Sci Technol Res 8:434–442
Mohsin M, Zhang J, Saidur R, Sun H, Sait SM (2019d) Economic assessment and ranking of wind power potential using fuzzy-TOPSIS approach. Environ Sci Pollut Res. 26:22494–22511. https://doi.org/10.1007/s11356-019-05564-6
Mohsin M, Zhou P, Iqbal N, Shah SAA (2018b) Assessing oil supply security of South Asia. Energy 155:438–447. https://doi.org/10.1016/J.ENERGY.2018.04.116
Munda G, Nardo M (2009) Noncompensatory/nonlinear composite indicators for ranking countries: a defensible setting. Appl Econ 41:1513–1523. https://doi.org/10.1080/00036840601019364
Nakicenovic N, Swart R (2000) IPCC Special Report on Emissions Scenarios (SRES). Work Gr III Intergov Panel Clim Chang IPCC. doi: citeulike-article-id:9904924
O’Neill J (2002) Global Economics Paper No. 66: Building Better Global Economic BRICs
Overland JE, Wang M, Walsh JE, Stroeve JC (2014) Future arctic climate changes: adaptation and mitigation time scales. Earth’s Futur. 2:68–74. https://doi.org/10.1002/2013ef000162
Pollesch NL, Dale VH (2016) Normalization in sustainability assessment: methods and implications. Ecol Econ 130:195–208. https://doi.org/10.1016/j.ecolecon.2016.06.018
Pretis F, Roser M (2017) Carbon dioxide emission-intensity in climate projections: comparing the observational record to socio-economic scenarios. Energy 135:718–725. https://doi.org/10.1016/j.energy.2017.06.119
REN21 (2016) Renewables 2016 Global Status Report
Rogelj J, Popp A, Calvin K V., et al (2018) Scenarios towards limiting global mean temperature increase below 1.5 °C. Nat. Clim. Chang. 1–8
Rogge N (2018) On aggregating benefit of the doubt composite indicators. Eur J Oper Res 264:364–369. https://doi.org/10.1016/J.EJOR.2017.06.035
Seiford LM, Zhu J (2002) Modeling undesirable factors in efficiency evaluation. Eur J Oper Res 142:16–20. https://doi.org/10.1016/S0377-2217(01)00293-4
Shah SAA, Zhou P, Walasai GD, Mohsin M (2019) Energy security and environmental sustainability index of South Asian countries: a composite index approach. Ecol Indic 106:105507. https://doi.org/10.1016/j.ecolind.2019.105507
Sun H, Ikram M, Mohsin M, Abbas Q (2019a) Energy security and environmental efficiency: evidence from OECD countries. Singapore Econ Rev.:1–18. https://doi.org/10.1142/S0217590819430033
Sun H, Mohsin M, Alharthi M, Abbas Q (2020) Measuring environmental sustainability performance of South Asia. J Clean Prod 251:119519. https://doi.org/10.1016/j.jclepro.2019.119519
Sun HP, Tariq G, Haris M, Mohsin M (2019b) Evaluating the environmental effects of economic openness: evidence from SAARC countries. Environ Sci Pollut Res. 26:24542–24551. https://doi.org/10.1007/s11356-019-05750-6
Sueyoshi T, Goto M (2013) DEA environmental assessment in a time horizon: Malmquist index on fuel mix, electricity and CO2 of industrial nations. Energy Econ. 40:370–382. https://doi.org/10.1016/j.eneco.2013.07.013
Suranovic S (2013) Fossil fuel addiction and the implications for climate change policy. Glob Environ Chang. 23:598–608. https://doi.org/10.1016/j.gloenvcha.2013.02.006
T. Coelli D, D. Prasada Rao, CJO and GEB (2005) Additional topics on data envelopment analysis. In: An Introduction to Efficiency and Productivity Analysis. Springer-Verlag, New York, pp 183–208
Tapia JFD, Lee JY, Ooi REH, Foo DCY, Tan RR (2016) Optimal CO2 allocation and scheduling in enhanced oil recovery (EOR) operations. Appl Energy 184:337–345. https://doi.org/10.1016/j.apenergy.2016.09.093
Tyteca D (1996) On the measurement of the environmental performance of firms— a literature review and a productive efficiency perspective. J Environ Manage 46:281–308. https://doi.org/10.1006/JEMA.1996.0022
U.S. Energy Information Administration (2016) International Energy Outlook 2016-Electricity
US Office of energy efficiency & renewable energy (2017) 3.4 Fuel Cells. Fuel Cell Technol Off Multi-Year Res Dev Demonstr Plan
Wang H, Chen Z, Wu X, Nie X (2019) Can a carbon trading system promote the transformation of a low-carbon economy under the framework of the porter hypothesis? —Empirical analysis based on the PSM-DID method. Energy Policy 129:930–938. https://doi.org/10.1016/j.enpol.2019.03.007
Wang X, van’t Veld K, Marcy P et al (2018) Economic co-optimization of oil recovery and CO 2 sequestration. Appl Energy 222:132–147
World Bank (2013) CO2 emissions (metric tons per capita). World Bank Gr.
World Bank (2015) World Development Report 2015
Wu G, Liu LC, Han ZY, Wei YM (2012) Climate protection and China’s energy security: win-win or tradeoff. Appl Energy 97:157–163. https://doi.org/10.1016/j.apenergy.2011.11.061
Zeng S, Liu Y, Liu C, Nan X (2017) A review of renewable energy investment in the BRICS countries: history, models, problems and solutions. Renew. Sustain. Energy Rev.
Zhang N, Zhou P, Kung CC (2015) Total-factor carbon emission performance of the Chinese transportation industry: a bootstrapped non-radial Malmquist index analysis. Renew. Sustain. Energy Rev.
Zhou P, Ang BW, Poh KL (2008) Measuring environmental performance under different environmental DEA technologies. Energy Econ 30:1–14. https://doi.org/10.1016/j.eneco.2006.05.001
Zhou P, Ang BW, Poh KL (2006) Comparing aggregating methods for constructing the composite environmental index: an objective measure. Ecol Econ 59:305–311. https://doi.org/10.1016/J.ECOLECON.2005.10.018
Zhou P, Delmas MA, Kohli A (2017) Constructing meaningful environmental indices: a nonparametric frontier approach. J Environ Econ Manage 85:21–34. https://doi.org/10.1016/j.jeem.2017.04.003
Zhou P, Poh KL, Ang BW (2007) A non-radial DEA approach to measuring environmental performance. Eur J Oper Res 178:1–9. https://doi.org/10.1016/j.ejor.2006.04.038
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Baloch, Z.A., Tan, Q., Iqbal, N. et al. Trilemma assessment of energy intensity, efficiency, and environmental index: evidence from BRICS countries. Environ Sci Pollut Res 27, 34337–34347 (2020). https://doi.org/10.1007/s11356-020-09578-3
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DOI: https://doi.org/10.1007/s11356-020-09578-3