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Highlights • We estimate the energy rebound effect caused by technological progress in Shanghai. • We use the state space model with time-varying parameter based on the IPAT identity. • Shanghai has a high partial rebound effect on average at the overall-economy level. • Mitigating the energy rebound effect can significantly reduce carbon emissions. • Energy efficiency improvement should not be the only way to conserve energy. Abstract The energy rebound effect is regarded as an obstacle of achieving the expected target of energy-saving policies, especially under a rapid urbanization background in developing counties, such as China. This has become a substantial drag of sustainable development in some cities. Shanghai is the economic center of China, and it is also a typical energy import-dependent mega-city. Investigating the evolution of Shanghai's energy-saving performance and the energy rebound effect is significant for the implementation of energy-saving policies in other similar cities of China and other developing countries. Using the state space model with time-varying parameters and based on the IPAT identity and the Solow residual approach, this paper is the first study to present a specific estimation on Shanghai's energy rebound effect caused by technological progress. The results show that, during the period of 1991–2016, the average energy rebound effect of overall economy and secondary industry in Shanghai was 93.96% and 73.10%, respectively, indicating a high partial rebound effect. Most of expected energy saving caused by improved energy efficiency is offset by extra energy consumption caused by technological progress. Regarding tertiary industry, the average rebound effect was 146.61%, indicating a backfire effect. However, the average energy rebound amount of tertiary industry is less than that of secondary industry. In particular, there is an increasingly negative impact of the rebound effect of tertiary industry on energy conservation in recent years, with the sector's rapid expansion and corresponding increase in energy demand. Furthermore, we estimate the carbon rebound amount (i.e., carbon emissions caused by the energy rebound effect) and find that, on average, the energy rebound effect caused 13.1% and 0.41% increases in carbon emissions in Shanghai and China, respectively. Therefore, mitigating the energy rebound effect can significantly reduce carbon emissions. Due to the substantial impact of the rebound effect, technological progress and energy efficiency improvement should not be the only way to achieve energy-saving target, especially in energy import-dependent mega-cities like Shanghai. Some supporting policies should be implemented to ensure that the expected outcome of energy-saving effort can be realized as far as possible. [ABSTRACT FROM AUTHOR]

High energy consumption by the industry of developing countries has led to the problems of increasing emission of greenhouse gases (GHG) (primarily CO 2 ) and worsening energy shortages. To address these problems, many mitigation measures have been utilized. One major measure is to mandate fixed reductions of GHG emission and energy consumption. Therefore, it is important for each developing country to disaggregate their national reduction targets into targets for various geographical parts of the country. In this paper, we propose a DEA-based approach to allocate China’s national CO 2 emissions and energy intensity reduction targets over Chinese provincial industrial sectors. We firstly evaluate the energy and environmental efficiency of Chinese industry considering energy consumption and GHG emissions. Then, considering the necessity of mitigating GHG emission and energy consumption, we develop a context-dependent DEA technique which can better characterize the changeable production with reductions of CO 2 emission and energy intensity, to help allocate the national reduction targets over provincial industrial sectors. Our empirical study of 30 Chinese regions for the period 2005–2010 shows that the industry of China had poor energy and environmental efficiency. Considering three major geographical areas, eastern China’s industrial sector had the highest efficiency scores while in this aspect central and western China were similar to each other at a lower level. Our study shows that the most effective allocation of the national reduction target requires most of the 30 regional industrial to reduce CO 2 emission and energy intensity, while a few can increase or maintain their 2010 levels. [ABSTRACT FROM AUTHOR]

• Pyramidal approach for the analysis and decomposition of energy intensity. • Definition of structural and efficiency indicators for the whole energy system. • Impact of transformation processes and fuel types on supply side energy efficiency. • Emerging nations needed to worsen the efficiency of the supply side to thrive. • Renewable electrification simultaneously benefits energy and carbon intensities. Energy efficiency remains as the main mitigation factor to slow down the growth of energy consumption and related CO 2 emissions, undoubtedly the major responsible for climate change. Gaining insights into the driving forces that make efficiency change is a keystone to define energy policies and examine pathways to sustainable development. To this aim, this paper proposes a pyramidal approach for the analysis and decomposition of energy intensity, the main global efficiency indicator, using the LMDI method. First, the effects related to supply and demand sides of the energy system are separated in Primary Energy Factor and final energy intensity, respectively. Then, supply side is further decomposed to progressively reveal structural effects associated to transformation processes and fuel types. The approach is applied to the most emitting and consuming nations (China, United States, European Union, India, Russia, Japan) to provide a meaningful cross-country analysis over the period 1995–2017. Results show that energy intensity gains have been mainly driven by widespread demand side efficiency improvements from 25% to 61%. Regarding the supply side, unfavourable structural changes due to electrification, up to 12% in China, have only been offset by transformation efficiency gains about 6% in developed countries. Consequently, emerging economies have worsened their energy sector efficiency as they thrive. Changes in fuel mixes have generally contributed to energy intensity reductions (up to 4%) mainly due to shifts from coal and nuclear power towards gas and renewables plants. The proposed methodology could help stakeholders to effectively analyse the energy system and to develop policies to reduce its environmental impact. [ABSTRACT FROM AUTHOR]

• Natural gas subsidies of China's industrial sector are investigated. • Regional heterogeneity is investigated from regional and provincial perspectives. • Regional heterogeneity exists in the decomposition on natural gas subsidy. • Regional policies for energy subsidy reform in developing countries are needed. This paper seeks to investigate the regional heterogeneity in natural gas subsidies of China's industrial sector. Price-gap approach and logarithmic mean Divisia index method (LMDI) are combined to accomplish this goal. The results show that there exists regional heterogeneity in the decomposition on the variation of industrial natural gas subsidy in China. In other words, the factors that contribute to the changes in subsidies differ from a regional basis. During 2007–2013, consumption exerted a positive impact on the increase of industrial natural gas subsidies, contributing more than 80% both in the eastern and northeastern regions, followed by 70.66% in the western region and 69.54% in the central region. During 2013–2016, the main factor affecting the changes in industrial natural gas subsidies is the pricing mechanism. The pricing mechanism played a significant positive role in the decline of industrial natural gas subsidies, with contribution rate of 367.73% in the northeastern region, 80.64% in the eastern region, 75.68% in the central region and 74.34% in the western region. Based on the results, we suggest that the policy measures enacted by government should differ in regions when promoting subsidy reform, especially for developing countries with unbalanced regional development. [ABSTRACT FROM AUTHOR]

• A GHG emissions inventory for 305 Chinese cities is compiled for 2015. • Emissions of CO2, CH4, N2O, and fluorinated GHGs are separately accounted. • The uncertainty of city-level GHG emissions is analyzed. Accounting and understanding greenhouse gas (GHG) emissions at the city level are of great importance because cities are the focus of future mitigation and adaption activities to address climate change, especially in developing nations like China. However, existing studies have not yet provided a complete and updated emissions inventory of city-level GHGs for China in terms of city and GHG-type coverage. In this paper, we rigorously assemble a dataset that contains GHG emissions including carbon dioxide, methane, nitrous oxide, and fluorinated GHGs for 305 Chinese cities, based on a high-resolution emissions database (China High-Resolution Emission Database, CHRED 3.0) and first-hand on-site data collection and verification by 19 groups of 137 researchers using a bottom-up method, and analyze the uncertainty of the emissions. Results show that total GHG emissions are high in cities in eastern China and low in cities in west, while per capita GHG emissions are high in northern cities and low in southern cities. The emissions of four types of GHGs (CO 2 , CH 4 , N 2 O and fluoridated GHGs) share different spatial distributions, due to variant industrial structure, energy structure, industry point sources and agricultural surface sources, etc. The uncertainty of GHG emissions is highly related to the source data of cities. Finally, we propose policy recommendations, including improving data quality and strengthening competitions of city-level emission reduction, to improve city-level emissions data integrity and low-carbon development strategies. [ABSTRACT FROM AUTHOR]