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Total-factor energy efficiency (TFEE) assessment has received increasing attention in both operations research and energy economics communities. Earlier TFEE studies implicitly assume that production activity lies in the economic area, which precludes the possibility that the production activity lies in the non-economic area and thus suffers from congestion. This paper contributes to develop TFEE index by taking into account congestion effect. It starts with the definition of congested production technology, based on which several data envelopment analysis models are proposed to construct TFEE index with congestion. The models for quantifying energy inefficiency caused by congestion effect are also developed. We apply the proposed index to evaluate the energy efficiency performance of Chinese industrial sectors at province level in 2010-2012. It is found that TFEE with congestion can yield useful insights about the choice of proper ways to achieve energy efficiency improvement. A comparison with the empirical results under congestion-free production technology indicates that ignoring congestion effect may lead to significantly different TFEE scores when congestion effect does exist. [ABSTRACT FROM AUTHOR]

In this paper, we review the energy efficiency in China, and the following topics are discussed. (i) Some useful empirical analyses applied on the energy efficiency based on some expanded models, (ii) the relationship among environment, energy and economic growth, (iii) some important environmental efficiency evaluation indexes, and (iv) some latest researches on the emission system. Finally, some policy recommendations are made. [ABSTRACT FROM AUTHOR]

Promoting energy efficiency in iron and steel production provides opportunities for mitigating environmental impacts from this energy-intensive industry. Energy efficiency technologies differ in investment costs, fuel-saving potentials, and environmental performance. Hence the decision-making of the adoption strategy needs to prioritize technological combinations concerning these multi-dimensional objectives. To address this problem, this study proposes a hybrid multi-criteria decision-support model for adopting energy efficiency technologies in the iron and steel industry. The modeling framework integrates a linear programming model that determines the optimal technology adoption rates based on the techno-economic, energy, and environmental performance details and an interactive multi-criteria model analysis tool for diverse modeling environments. A real case study was performed in which a total number of 56 energy efficiency technologies were investigated against various criteria concerning economics, energy, and environmental performances. The results examine the tradeoffs and synergies were examined with regard to seven criteria. A balanced solution shows that a total investment of 13.4 billion USD could save 2.51 Exajoule fuel consumption, cut 67.4 million tons (Mton) CO2 emissions, and reduce air pollution of 1.5 Mton SO2, 1.41 Mton NOx, and 0.86 Mton PM, respectively. The case study demonstrates the effectiveness and applicability of the proposed multi-criteria decision-making support framework. [ABSTRACT FROM AUTHOR]

We identify factors influencing energy efficiency and the role of price instruments such as tax and technology use in reducing energy intensity at the firm level. We use data from 2001 to 2015 for India's manufacturing sector from the Centre for Monitoring Indian Economy. Our result strongly suggests that R&D and productivity have a positive impact on achieving energy efficiency. In such a case, at least one-to-one correspondence between the tax and energy intensity may help promote renewable energy use if they are subsidized and allowed to come under the provision of tax credit or tax exemption. Since price instruments do not produce any revenue recycling effect, policymakers can trade-off between increasing corporate tax and generating employment. Therefore, environmental regulations should strictly relate to increase energy efficiency and bring the manufacturing sector out of the productivity dilemma. Also, as evidence from the empirical analysis, there is an urgent need to substitute vintage capital with new capital and better technology. In addition to the existing liberalization policies, the Government must design green domestic policies for the manufacturing sector and map them with FDI and trade. As the polluted firms are energy-intensive, "Performance, Achievement and Trade" (PAT) policies need to focus on these firms. [ABSTRACT FROM AUTHOR]