• Energy Research

Abstract Circular economy is one effective strategy to achieve a healthy environment and efficient use of resources. In this study, the trade relationship between China and Nigeria is used to establish how circular economy ameliorates climate change. On the basis of CO2 emissions, data from 1991 to 2014 are obtained and measures for energy efficiency in the mining and extractive-related sectors from energy intensity are derived using Fisher ideal index decomposition. This study utilizes panel-corrected standard error, feasible generalized least squares, autoregressive distribute lag bound, and Bayesian VAR models. These techniques suggest that energy efficiency in the mining and extractive-related sector and the circular economy have not translated into CO2 emission reduction in both countries. However, economic growth, energy use (non-renewable energy), and clean energy substitution (renewable energy) are essential factors in mitigating CO2 emissions. Given such evidence, resource melioration for energy consumption and economic growth have indispensable roles in reducing CO2 emissions.

We examine the impact of environmental diplomacy on a country's carbon emission level. Specifically, we test if the signing of environmental treaties yielded positive responses in CO2 emission. We employ common correlated effects mean group models on panel data of 76 developed and developing countries for over 35 years. Our analysis indicates that environmental diplomacy reduces CO2 emissions for developing countries in the short run. However, the results of FMOLS in the long-run estimates indicate that developed and developing countries do not adhere to treaty requirements as CO2 emissions increases with more treaties. Overall, our results imply that the signing of environmental treaties is likely to be mere international diplomacy that yields no result on climate change. We suggest that countries should fulfill their obligation under treaties rather than engage in annual rituals of signing treaties.

High energy conservation and emission reduction (ECER) requirements across industries in the Beijing–Tianjin–Hebei (BTH) region have been proposed along with the transformation of China’s economic development mode. However, the energy consumption rebound effect, as an important proxy for achieving sustainable low-carbon development, has not been adequately investigated across industrial enterprises in this area. This study adopts an alternative estimation model based on neoclassical economic theory to measure the energy rebound effect of industrial enterprises in the BTH region from 1996 to 2015. Four main results are obtained. First, the energy rebound effects in Beijing, Tianjin, and Hebei are significantly different in the temporal and spatial dimensions. Second, technological progress does not reduce energy consumption, and the local government must simultaneously consider technological progress, industrial structure, and policy formulation to achieve the ECER goals. Third, ECER policies combined with government administrative measures do not have an impact on reducing energy consumption. Fourth, in the process of implementing the integration development of the BTH region, Hebei faces greater pressure to attain ECER goals in the future than the other regions. This study provides suggestions based on these derived results from the perspectives of market-oriented measures, management factors, development mode, and regional cooperation to achieve the sustainable development of the BTH region.

Given the rapid increase of residential energy consumption in Beijing, the question of how to promote residential energy-saving behavior is an emerging topic that is increasingly engaging the attention of scholars. To address this issue, this paper provides an empirical analysis that identifies and explores the determinants of an energy-saving behavioral intention among residents from the perspective of the theory of planned behavior (TPB). A theoretical model was constructed by refining and extending the classic TPB model according to the scope and requirements of this study and the existing situation in China. Survey data collected from 276 residents in Beijing were analyzed, and hypothesized relationships in the model were then verified using a structural equation model. The results show that subjective norms, environmental attitudes, information publicity, lifestyles, and perceived behavioral control significantly influence residents' energy-saving behavior, while demographic factors, such as educational background, household income, and age, had no obvious effects on behavioral intentions. Although knowledge regarding energy did not exert a direct influence on residents' energy-saving behavioral intentions, it did exert an indirect influence via environmental attitudes. Our results indicate that the role of households in saving energy expenditure should be emphasized, and financial incentives could be adopted to help promote environmental awareness among Beijing's residents. In addition, environment-friendly and energy-saving habits should also be inculcated.

Abstract As the world’s main energy consumer, China faces an increasingly prominent conflict between its growing energy consumption and its unreasonable energy consumption structure. To optimize China's energy consumption structure, while simultaneously controlling its carbon emissions, this study proposes two models for the analysis of China’s energy configuration and energy consumption structure based on the data envelopment analysis (DEA) method. A fixed-sum input DEA model is proposed with which the energy input frontier is determined under consideration of China's energy shortage constraint. Furthermore, an energy consumption structure measurement model is developed to determine the adjustment direction and potential of the current energy consumption structure. The proposed models are further applied for the practical energy consumption structure evaluation in Chinese provinces. The obtained results show that almost all provinces suffer from an inefficient energy configuration and Eastern China experiences severe energy shortage. In addition, all provinces currently have unreasonable energy consumption structures. In particular, the proportion of gas consumption to total energy usage should be increased in all provinces. Furthermore, Chinese provinces with inefficient energy structures exhibit the geographical feature. The coal adjustment ratios in the central and western regions account for 70% of the total, which is much higher than the coal adjustment rate of the eastern region (50%). Based on these results, policies are also suggested to adjust China's energy consumption structure, such as reducing high carbon energy, implementing energy price reform, carbon tax, and clean energy subsidy.

Abstract Allocation of emission permits (AEP) is an important issue because of its significant effects on environmental governance and operations management. However, whether AEP results can constantly maintain systemic Pareto optimality still remains unclear and has not been investigated adequately in prior literature. We attempt to fill this gap by dividing the AEP process into a pre-stage observation process and a two-stage regulatory scheme as motivated by recent real-world examples. We apply the characterizations of each stage’s state variables to build a conceptual AEP model based on the classical theory of data envelopment analysis (DEA). Considering different real-world scenarios, we extend this conceptual AEP model into three different AEP models: non-limited, uniform-limited, and heterogeneous-limited AEP models. The allocation schemes derived from each of these three models are proved theoretically to be systemic Pareto optimal in the corresponding scenarios. The advantages of our models over other AEP methods are real-world tractability, enforceability, and systemic Pareto optimality. We further conduct an empirical analysis on allocating SO 2 emission permits among mainland China’s major million-KW coal-fired power plants using the proposed models. Results of our empirical study show that the heterogeneous-limited AEP model exhibits higher performance over the non-limited and uniform-limited AEP models. Thus, we suggest that the Chinese coal-fired power industry should employ the heterogeneous-limited AEP model in the practical allocation of SO 2 emission permits.

Abstract This study investigates the impact of emission regulation policies (i.e., emergency response policy versus long-term protection policy) on the investment levels of reusable environmental facilities (e.g., desulphurization pumps) used by coal-fired power plants in China to improve their sustainable operations. To set up a baseline for further analysis and compare the impact of emission regulation policies, an improved framework for performance evaluation of sustainable operations is developed in this study by integrating classical data envelopment analysis (DEA) and exponential learning curve. The proposed mathematical models are applied into an empirical study of 27 major million-kW coal-fired power plants in mainland China. Empirical analysis shows that the interactions among official emission regulation policies, reusable environmental investment (REI), and sustainable operations management of coal-fired power plants in China. Several policy suggestions are provided for power firm managers and policy makers in China. Specifically, we suggest that the Chinese government should implement long-term protection policies in less developed regions instead of emergency response policies.

Abstract Motivated by the practical application of information and communication technologies (ICT)-based innovations in environmental and social responsibility (ESR) investment, this study investigates a sustainable power supply chain that consists of a traditional energy power generation firm (TEF), a renewable energy power generation firm (REF) and a downstream power distributor (PD). Each supply chain member can invest in ESR to achieve energy conservation and emission reduction, and thereby gain economic benefits. To achieve higher power level for better ESR investment, the TEF may actively form an alliance with the REF or the PD, or not, which leads to three different alliance strategies, i.e., Strategy HA, Strategy VA, and Strategy NA, respectively. The results show that NA is the equilibrium strategy when the TEF’s investment cost is low while the PD’s investment cost is medium. However, when the TEF’s investment cost is medium while the PD’s investment cost is low, VA is the equilibrium strategy. Moreover, when the investment cost of the TEF and the REF are both low, HA is the equilibrium strategy. In the other cost intervals, the three power firms will not invest in ESR simultaneously, and consequently the alliance strategy has no effect on the revenue allocation. Therefore, the TEF forms no alliance with either the REF or the PD. By comparison with the unaligned case, we find that alliance not only benefits the TEF, but also the other firms in the power supply chain as well as the whole society resulting from the improved ESR investment, which achieves a “win-win-win” situation.