Zhaohua Wang

Driving forces of indirect carbon emissions from household consumption in China: an input–output decomposition analysis

Human activities have become a major source of Earth’s climate change, which brings the rise of surface air temperature and subsurface ocean temperature. Therefore, promoting sustainable consumption and production patterns is imperative to minimize the use of natural resources and reduce emissions of pollutants. This study uses Economic Input–Output Life-Cycle Assessment method and structural decomposition model to identify the driving forces that influence the changes in carbon emissions from China’s residential consumption in the context of sustainable consumption. The findings of the study are as follows: (1) indirect carbon emissions from Chinese household consumption increase rapidly over time; (2) the largest carbon dioxide emitting sector turns from agriculture sector in 1992 into service sector in 2007; (3) the consumption level and the emission intensity are the main drivers that influence the change in indirect carbon emissions; and (4) the factor of consumption level presents positive effect on the emissions, while the emission intensity effect plays a negative role. Besides, the factors of urbanization, production structure, population size and consumption structure also promote the rapid increase in carbon emissions.

Strategies for addressing climate change on the industrial level: affecting factors to CO 2 emissions of energy-intensive industries in China

This paper explores China’s strategies for addressing climate change on the industrial level. Focusing on six energy-intensive industries, this paper applies gray relational analysis theory to the affecting factors to CO2 emissions of each industry after calculating each industry’s CO2 emissions during 2001–2010. Further research based on GM(1, 1) model is conducted to forecast the trend of the factors, the energy consumption and each industry’s CO2 emissions during the 12th Five-Year Plan period. As a breakthrough in previous conclusions, energy consumption structure was divided into the respective proportion of coal, oil, natural gas and electricity in the primary energy consumption, with which industrial output and energy intensity are combined to analyze each of their impacts on the energy-intensive industries. It turns out that all the factors’ impacts on emissions of the six major energy-intensive industries are significant, despite their differentiated extents. It is worth noting that, contrary to previous findings, industrial output is not the leading affecting factor to CO2 emissions of the energy-intensive industries compared with the proportion of coal and electricity in the primary energy consumption. The GM(1, 1) forecast results of energy consumption and CO2 emissions by the end of 2015 show that coal and electricity will remain a large proportion in primary energy consumption. This research may shed some light on China’s adjustment of energy structure under the pressure of addressing climate change and hence provide decision support for the acceleration of renewable energy utilization in the industrial departments.

Determinants of the increased CO 2 emission and adaption strategy in Chinese energy-intensive industry

Climate change has not only brought about many natural hazards but also threaten the sustainable development of industry. This study is to investigate the adaptive implications for energy-intensive industries of China in response to climate change impacts. For this purpose, a deep and comprehensive analysis on the change of CO2 emission for 6 energy-intensive sectors is explored over the period of 2000–2007. A Log-Mean Divisia Index based on time series is also introduced in our study to identify the key factors toward the change of CO2 emission. It is shown that there were 146.1 million metric tons carbon increased in energy-intensive industries from 2000 to 2007. And the excessive growth of industrial output and increasingly fossil-intensive energy consumption structure were the main driving forces for the increased CO2 emission. Nevertheless, energy intensity change and declining emission coefficient of electricity played negative role in the growing trend of CO2 emission. On the basis of these four determinants (namely industrial output, energy intensity, fuel mix effect, and emission coefficient), it is suggested that both economic motives and technologically feasible approaches should be implemented to control the scale of excessive productions and improve energy efficiency toward the energy-intensive industries. And more importantly, strengthening energy-intensive sectors’ awareness of climate change adaptation should be given stronger emphasis as long-term work with the help of some propaganda campaigns for instance.

Determinants of energy-saving behavioral intention among residents in Beijing: Extending the theory of planned behavior

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 Beijings residents. In addition, environment-friendly and energy-saving habits should also be inculcated.

An empirical examination of energy consumption, behavioral intention, and situational factors: evidence from Beijing

With the increase in energy consumption and carbon dioxide emissions, promoting an energy-saving lifestyle among residents has become an urgent environmental and social need. Studying factors that influence household daily energy-saving behaviors may help the government draft policies for reducing the energy consumption and promoting the sustainable development of the human economic society. In this study, we investigate the features of energy-related situational factors, individual/household energy consumption behavioral norms, and energy-saving behavioral intentions by performing a questionnaire survey in Beijing. We examine the relationships among the mentioned aspects by applying factor analysis and structural equation modeling. Results show that among the three aspects assessed, situational factors most significantly and effectively influence the residents to assume energy-saving behaviors. Energy-saving behavioral norms partly mediate the relationship between situational factors and behavioral intention. We propose practice policy implications on the basis of the results. In particular, the positive influences of situational factors should be strengthened, and relevant policy measures should be emphasized to establish a situational background beneficial for accelerating the formation or transformation of energy-saving behaviors.

Energy production, economic growth and CO2 emission: evidence from Pakistan

An extensive body of knowledge is available on the relationship between energy consumption and CO2 emission incorporated by different variables. However, the role of energy production in the pollution equation is largely unknown. The present work quantifies the relationship between energy production, economic growth and CO2 emission. A family of econometric tools is used to achieve the objective of the study. Due to the sensitivity of objective of the present work, we use structural break unit root test to measure the stability of parameters within the time span of 1970–2011. Johansen cointegration test confirms the existence of cointegration among variables. Autoregressive distributive lag model reveals that energy production from the fossil fuel is the main culprit behind growing CO2 emission. Additionally, the finding of the study claims the existence of environmental Kuznets curve hypothesis in the significance of energy production in Pakistan. Moreover, bidirectional causality is detected between energy production and carbon dioxide emission in the long-run path. It is suggested that pollution can be condensed by producing energy from the renewable source (hydropower, solar power, geothermal and wind energy) and add more renewable energy to the energy mix.

Relationships between energy technology patents and CO2 emissions in China: An empirical study

This paper explores dynamic relationships between energy technology patents and CO2 emissions in China during 1985-2009. Based on vector autoregression (VAR), cointegration and vector error correction model (VECM) are adopted to uncover relationships in both long-run and short-run; also dynamic interactions are identified to establish these relationships between variables through impulse response functions and variance decomposition methods. Results show that: (1) the increase of energy technology patents does not reduce CO2 emissions in both long-run and short-run; (2) in the long-run, the increase of energy technology patents helps to reduce CO2 emissions intensity; while it does not for the short term. The present empirical study clearly indicates that Chinese government should attach more importance to investigating and improving energy technology patent system and formulating related energy technology policies for CO2 emissions reduction.

Determinants and policy implications of residents’ new energy vehicle purchases: the evidence from China

New energy vehicles (NEVs) can effectively relieve traffic energy consumption and environmental pollution problems, while their actual sales are far from those expected in recent years. Based on the improved theory of planned behaviour, this research analyses the effects of perceived usefulness, perceived ease of use, subjective norms, and perceived behavioural control on the purchase intentions behind NEVs, examines the moderating effect of perceived behavioural control on the relationship between subjective norms and purchase intentions, and establishes a discrete choice model for the purchase intentions of NEVs. In addition, the research delves further into those factors influencing NEV purchase intentions of urban residents with cars and their corresponding influence on people holding different attitudes. Results showed that, for the urban residents, perceived ease of use positively affects the NEV purchase intentions of those unwilling to buy NEVs, subjective norms have a significant positive effect on purchase intentions of residents unsure about whether or not to buy, and purchase intentions of urban residents are influenced by the relative usefulness; for urban residents with cars, subjective norms can positively influence purchase intentions of residents unsure about whether or not to buy, and their purchase intentions are also influenced by the relative usefulness. These findings can provide a reference for national policies designed for NEV industry development.

Supply Coordination Based on Bonus Policy in Assembly under Uncertain Delivery Time

The existing research of supply coordination under uncertain delivery time mainly focuses on the collaboration between the supplier and the manufacturer, which aim at minimizing the total cost of each side and finding comparative optimal solutions under decentralized decision. In the supply coordination, the collaboration between suppliers in assembly system is usually not considered. As a result, the manufacturer’s production is often delayed due to mismatching delivery of components between suppliers. Therefore, to ensure supply coordination in assembly system, collaboration between suppliers should be taken into consideration. In this paper, an assembly system with two suppliers and one manufacturer under uncertain delivery time is considered. The model is established and optimal solution is given under decentralized decision. Furthermore, the cost functions of two suppliers are both convex, and a unique Nash equilibrium exists between two suppliers. Then the optimal decision under supply coordination is analyzed, which is regarded as a benchmark for supply coordination. Additionally, the total cost of the assembly system is jointly convex in agreed delivery time. To achieve supply coordination a bonus policy is explored in the assembly system under uncertain delivery time, and the total cost under bonus policy must be lower than under decentralized decision. Finally the numerical and sensitivity analysis shows the cost of assembly system under bonus policy equals that under supply coordination, and the cost of each side in assembly system under bonus policy is lower compared to that under decentralized decision. The proposed research minimizes the total cost of each side with bonus policy in assembly system, ensures the supply coordination between suppliers and the manufacturer, and improves the competiveness of the whole supply chain.

Rebound effects for residential electricity use in urban China: an aggregation analysis based E-I-O and scenario simulation

Technological progress is considered an important means of decreasing energy consumption. However, rebound effects caused by energy efficiency improvements directly affect the realization of energy savings and emission reduction. This paper focuses on the main theory and methodology of direct and indirect rebound effects. Using 30 sets of provincial panel data and national input–output data for China from 2007, this paper builds a co-integrating equation, a panel error correction model, and an 8-sector energy-input–output model. We subsequently estimate the direct and indirect rebound effects of urban residential electricity use. The results indicate that in the long term the direct plus indirect partial rebound effect is 0.79; in the short term it is 0.78. Thus, the majority of the expected electricity reduction in Chinese urban residential energy consumption arising from efficiency improvement may be offset. These rebound effects impair the functioning of energy efficiency policies. Therefore, the Chinese government should not improve energy efficiency alone—they must also take into consideration the relevant energy-pricing reforms when formulating energy policies.