• Energy Research

Abstract Understanding energy-carbon performance (ECP) and its intrinsic characteristics is important for energy saving and emissions reduction in the construction industry. However, few studies have focused on energy or carbon performance simultaneously and their pattern over time. To address this gap, this study investigated the ECP in China’s construction industry and its convergence characteristics across various provinces. We first constructed an ECP index (ECPI) using non-radical directional distance functions for the construction industry during 2003–2016. We then analyzed the convergence of ECPI using the convergence method proposed by Phillis and Sul (2007). The results showed that the overall ECPI was generally stable with some fluctuations over the sampling period, and there was no evidence to support the occurrence of convergence in the ECPI across the sample set. Furthermore, two club convergences of ECPI were recorded. Finally, we propose valuable suggestions for policymakers based on empirical results.

Abstract Ecological balance and carbon sink economies have gained increased attention for tackling global warming. Based on an improved Carnegie–Ames–Stanford Approach model, this study demonstrated regional Net Primary Productivity (NPP) and analyzed regional carbon overdraft situations in China during 2005–2015. Regional carbon allowances were allocated according to carrying capacity of carbon sequestration and China's carbon intensity reduction goals in “13th Five-year plan”. Data Envelopment Analysis (DEA) technology with panel data was further employed to estimate potential benefits resulting from carbon trading and a carbon sink economy. Regional NPP decreased from south to north and from coast to inland, while regions with severe carbon overdrafts were gathered in North and East China. In order to maintain a regional carbon balance with lower abatement costs, regional cooperation of emission reduction within either North or East China is proposed in this study. It is concluded that the majority of provinces and cities in Eastern China and some provinces in the west would be the major purchasers of carbon credits under a national carbon emissions trading (CET) market. Following the introduction of emissions offset mechanisms, Yunnan, Sichuan, and Heilongjiang would be the major providers of carbon sinks in China.

Abstract Under the framework of the Kaya identity, this paper uses the Logarithmic Mean Divisia Index (LMDI 1 ) decomposition method to explore the impacts of CO2 emission intensity of fossil energy, energy consumption structure, energy intensity, per capita Gross Domestic Product (GDP 2 ), population distribution, and population size on CO2 emissions in the Organisation for Economic Co-operation and Development (OECD 3 ) from 2001 to 2015. Additionally, the Tapio decoupling analysis is used to explore the decoupling relationships between the above influencing factors and CO2 emissions. Moreover, the LMDI decomposition formula is embedded into the decoupling analysis to analyze the influences of technical and non-technical factors on above decoupling elasticity. The results indicate that energy intensity and per capita GDP are the main factors affecting CO2 emissions. The former is the main reason for the decrease in CO2 emissions, and the latter is the main reason for the increase in CO2 emissions. The impact of population distribution on CO2 emissions is negligible. The decoupling states between the overall CO2 emission intensity of fossil energy, energy consumption structure, energy intensity, per capita GDP, and population size and CO2 emissions during 2001–2015 are recessive decoupling, recessive decoupling, weak negative decoupling, strong decoupling, and strong decoupling, respectively. Moreover, the influence of technical factors is greater than that of non-technical factors, and their influence directions are always opposite. In addition to our primary contributions, there are three marginal contributions in this paper. First, the population distribution is included in LMDI factorization. Second, LMDI decomposition is combined with Tapio decoupling analysis to explore the decoupling relationships between CO2 emissions and the above factors. Finally, the findings related to the impacts of technical and non-technical factors are novel.

Abstract Differentiated policies are key to improving the CO2 emissions reduction efficiency of cities, which are vital in mitigating climate change. The K-means cluster method and spatial logarithmic Divisia index decomposition method were used on the data of 279 cities in China to examine the impacts of local public expenditure on CO2 emissions in the context of socio-economic conditions. The results show emission differences in cities with similar socio-economic conditions. The impacts of the carbon intensity of local public expenditure and other public expenditures on the emission differences of city groups, which have different socio-economic conditions, were largest, followed by the local public expenditure scale and public environmental expenditure. The impacts of the proportions of public environmental expenditure and other expenditures were limited. Insights gained can provide feasible implications for Chinese cities, and enable policymakers to focus on the impact of different fiscal policies on CO2 emissions differences between cities.

AbstractWith the implementation of China’s top-down CO2 emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO2 emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO2 emissions in China have only focused on the national, provincial, or city levels, owing to limited methods and smaller-scale data. In this study, a particle swarm optimization-back propagation (PSO-BP) algorithm was employed to unify the scale of DMSP/OLS and NPP/VIIRS satellite imagery and estimate the CO2 emissions in 2,735 Chinese counties during 1997–2017. Moreover, as vegetation has a significant ability to sequester and reduce CO2 emissions, we calculated the county-level carbon sequestration value of terrestrial vegetation. The results presented here can contribute to existing data gaps and enable the development of strategies to reduce CO2 emissions in China.

Abstract The Chinese economy has been experiencing rapid growth since the implementation of the reform and opening-up policy. However, at the same time, it faces issues regarding resource savings and environmental protection, which are important aspects of the new industrialization. Therefore, this study conducts data envelopment analysis (DEA) to evaluate the environmental efficiency of Chinese regions. Certain existing DEA models account for undesirable outputs and do not elucidate the weak disposable relationship between undesirable and desirable outputs. Thus, polar theory is introduced among the DEA modeling in this study. First, drawing on stochastic frontier analysis, Ray stochastic frontier analysis, and DEA, we propose a Ray slack-based model (RSBM) to evaluate provincial environmental efficiencies in China from 2004 to 2012. Subsequently, an RSBM-Malmquist–Luenberger (total factor productivity) index is structured. Finally, economic growth, environmental efficiency, and energy consumption are analyzed using spatial panel econometrics. As this study treats industrial waste as undesirable outputs, the RSBM results show that the environmental efficiencies in the east are the highest, while those in the central regions are the lowest. The spatial econometric analysis reveals that the ratios of direct to total elasticity and those of direct to total effect for capital, labor, and energy input variables are fixed. Furthermore, the study provides policy implications and suggestions for future research.

AbstractAlthough the rebound effect caused by technological progress has been widely accepted, few studies have estimated and compared the rebound effects of fossil and nonfossil energy separately, because fossil and nonfossil energy consumption have different effects on sustainable development. We use the data envelopment analysis–Malmquist index, logarithmic mean Divisia index, and Jacobian matrix methods to estimate and compare the rebound effects of China's fossil and nonfossil energy during 2006–2014. Empirical results show that nonfossil energy had a higher rebound effect than fossil energy and that technological progress was helpful in decreasing the proportion of fossil energy consumption. Furthermore, we found that technological progress contributed to increases in the relative price of fossil energy, causing nonfossil energy to be more favored. Simultaneously, nonfossil energy produced a substitution effect on fossil energy over the long term. On the basis of the empirical analysis, we also present some environmental policy implications.

Water-energy nexus in a city can either prompt or undermine its development. Yet in China, the relevant research is rarely found. This study accounts the city-level water-energy nexus in Beijing-Tianjin-Hebei region in 2012 from both production and consumption perspectives, where input-output analysis based on city-level input-output tables are applied to conduct consumption-based accounts. Regarding water for energy, Beijing, Tianjin and Tangshan occupy the largest amounts of water for production in the energy sector, at 203 million tonnes (Mt), 148 Mt and 118 Mt, and they also consume most water for energy, at 6690 Mt, 1328 Mt and 1476 Mt. In terms of energy for water, Shijiazhuang and Tianjin have the largest amounts of CO2 emissions for production and consumption respectively, at 28 thousand tonnes (Kt) and 1746 Kt. Furthermore, local authorities should prioritise electricity sector as it holds 69% and 72% of the total water amounts for production and consumption in the energy sector. Besides, integrated management is crucial for cities with low water and energy efficiency (Baoding and Zhangjiakou), and for large CO2 emitters in Hebei province in order to ensure their water and energy sustainability without stunting their economic growth.