Spatial spillover effects in determining China's regional CO2 emissions growth: 2007–2010

This study proposes an alternative input–output based spatial structural decomposition analysis to elucidate the importance of domestic regional heterogeneity and inter-regional spillover effects in determining China's regional CO₂ emissions growth. Our empirical results, based on the 2007 and 2010 Chinese inter-regional input–output tables, show that changes in most regions' final demand scale, final expenditure structure, and export scale have positive spatial spillover effects on other regions' CO₂ emissions growth; changes in most regions' consumption and export preference help reduce other regions' CO₂ emissions; changes in production technology and investment preferences may exert positive or negative effects on other region's CO₂ emissions growth through domestic supply chains. For some regions, the aggregate spillover effect from other regions may be larger than the intra-regional effect in determining regional emissions growth. All these facts can significantly help provide a better, deeper understanding of the driving forces behind the growth of regional CO₂ emissions and can thus enrich the policy implications concerning a narrow definition of “carbon leakage” through domestic inter-regional “trade” as well as a relevant political consensus about responsibility sharing between developed and developing regions inside China.     

Effective ways to reduce CO2 emissions from China's heavy industry? Evidence from semiparametric regression models

Using China's province-level panel data from 2005 to 2017, this article uses a semiparametric regression model to investigate CO₂ emissions in China's heavy industry. Empirical results show that while economic growth exerted carbon reduction effects in the eastern region, it stimulated the growth of CO₂ emissions in the central and western regions. This is mainly due to regional differences in industrial structure and the high-tech industry. Energy efficiency has made a greater contribution to reducing CO₂ emissions in the central region because the R&D investment and patent rights granted in this region has grown faster. The energy consumption structure has a more complex impact. It exerts a “pulling first, then restricting” (Ո-shaped) nonlinear effect on CO₂ emissions in the eastern and western regions, but an inverted “N-shaped” effect in the central region. This is mainly due to the differences in the composition of energy consumption across regions. Environmental regulations have a positive “U-shaped” nonlinear impact on CO₂ emissions in the eastern and western regions. It means that environmental regulations help cut down CO₂ emissions in the early stage, and the facilitation effect gradually disappears at the later stage. Conversely, environmental regulations produce an inverted “U-shaped” impact in the central region.     

Identifying the driving forces of national and regional CO2 emissions in China: Based on temporal and spatial decomposition analysis models

This study explores the driving forces of the changes of national and regional CO₂ emissions using temporal decomposition analysis model, and investigates the driving forces of the differences of CO₂ emissions between China's 30 regions and the national average using spatial decomposition analysis model. The changes or the differences in national and regional CO₂ emissions during 2000–2014 are decomposed into nine underlying determinants. Temporal decomposition results show that economic scale effect is the dominant driving force leading to the increases in both national and regional CO₂ emissions, while energy intensity effect is the main contributor to the reduction of CO₂ emissions. Contribution of various variables to CO₂ emissions between eastern region and central region are roughly same. Spatial decomposition results demonstrate that the differences of CO₂ emissions among China's 30 regions are expanding increasingly. Economic scale effect is main driving force responsible for the difference in CO₂ emissions among regions, and energy intensity effect, energy structure effect and industrial structure effect are also important factors which result in the increasing differences in regional CO₂ emissions. In addition, resource-based and less developed regions have greater potential in the reduction of CO₂ emissions. Understanding CO₂ emissions and the driving forces of various regions is critical for developing regional mitigation strategies in China.     

Regional development and carbon emissions in China

China announced at the Paris Climate Change Conference in 2015 that the country would reach peak carbon emissions around 2030. Since then, widespread attention has been devoted to determining when and how this goal will be achieved. This study aims to explore the role of China's changing regional development patterns in the achievement of this goal. This study uses the logarithmic mean Divisia index (LMDI) to estimate seven socioeconomic drivers of the changes in CO₂ emissions in China since 2000. The results show that China's carbon emissions have plateaued since 2012 mainly because of energy efficiency gains and structural upgrades (i.e., industrial structure, energy mix and regional structure). Regional structure, measured by provincial economic growth shares, has drastically reduced CO₂ emissions since 2012. The effects of these drivers on emissions changes varied across regions due to their different regional development patterns. Industrial structure and energy mix resulted in emissions growth in some regions, but these two drivers led to emissions reduction at the national level. For example, industrial structure reduced China's CO₂ emissions by 1.0% from 2013 to 2016; however, it increased CO₂ emissions in the Northeast and Northwest regions by 1.7% and 0.9%, respectively. Studying China's plateauing CO₂ emissions in the new normal stage at the regional level yields a strong recommendation that China's regions cooperate to improve development patterns.     

Regional allocation of CO2 emissions allowance over provinces in China by 2020

The mitigation efforts of China are increasingly important for meeting global climate target since the rapid economic growth of China has led to an increasing share in the world's total CO₂ emissions. This paper sets out to explore the approach for realizing China's national mitigation targets submitted to the UNFCCC as part of the Copenhagen Accord; that is, to reduce the intensity of CO₂ emissions per unit of GDP by 40–45% by 2020, as well as reducing the energy intensity and increasing the share of non-fossil fuel consumption, through regional allocation of emission allowance over China's provinces. Since the realization of China's mitigation target essentially represents a total amount emission allowance allocation problem, an improved zero sum gains data envelopment analysis optimization model, which could deal with the constant total amount resources allocation, is proposed in this study. By utilizing this model and based on several scenarios of China's economic growth, CO₂ emissions, and energy consumption, a new efficient emission allowance allocation scheme on provincial level for China by 2020 is proposed. The allocation results indicate that different provinces have to shoulder different mitigation burdens in terms of emission intensity reduction, energy intensity reduction, and share of non-fossil fuels increase.     

CO2 emissions embodied in China's exports from 2002 to 2008: A structural decomposition analysis

This study examines the annual CO₂ emissions embodied in China's exports from 2002 to 2008 using environmental input–output analysis. Four driving forces, including emission intensity, economic production structure, export composition, and total export volume, are compared for their contributions to the increase of embodied CO₂ emissions using a structural decomposition analysis (SDA) technique. Although offset by the decrease in emission intensity, the increase of embodied CO₂ emissions was driven by changes of the other three factors. In particular, the change of the export composition was the largest driver, primarily due to the increasing fraction of metal products in China's total export. Relevant policy implications and future research directions are discussed at the end of the paper.     

Assessing the effects of CO2 price caps on electricity investments—A real options analysis

This paper uses real options modeling to assess the impact of different climate change policy instruments on investment, profits and cumulative emissions in the electricity sector. Even though CO₂ price caps or “safety valves” have been suggested as methods to limit uncertainty emanating from fluctuating prices of CO₂ permits that would hurt the industry's profit and thereby also energy security, our analysis shows that price caps set at a too low level are detrimental to the adoption of e.g. modern biomass-fired capacity as a replacement for existing coal-fired power plants. We therefore conduct a series of experiments with different policy scenarios to analyze under which regime emissions are most effectively reduced. With respect to CO₂ price uncertainty, it turns out that even for moderately rising CO₂ prices, fluctuations frequently lead to investment into carbon capture and storage (CCS), while investment is often not triggered in the face of deterministic CO₂ prices.     

China’s regional CO2 emissions: Characteristics,inter-regional transfer and emission reduction policies

This paper analyzes the characteristics of China’s regional CO₂ emissions and effects of economic growth and energy intensity using panel data from 1997 to 2009. The results show that there are remarkable regional disparities among eastern, central and western areas, regional elasticities of per capita GDP and energy intensity on CO₂ emissions, which reflect the regional differences in economic development, economy structure and restraining function of energy intensity decrease on the emission. Energy intensity reducing is more effective to emission abatement for provinces with higher elasticity of energy intensity, but may not be significant for provinces with lower elasticity. The inverse distribution of energy production and consumption, regional unfairness caused by institutional factors like energy price and tax system result in inter-regional CO₂ emission transfer embodied in the power transmission. The calculation indicates that the embodied emission transfer was gradually significant after 2003, from eastern area to the central and western areas, especially energy production provinces in central area, which leads to distortion on the emission and emission intensity. The regional emission reduction targets and supporting policies should be customized and consistent with the actual situations rather than setting the same target for all the provinces.     

CO2 emissions embodied in China–US trade: Input–output analysis based on the emergy/dollar ratio

To gain insight into changes in CO₂ emissions embodied in China–US trade, an input–output analysis based on the emergy/dollar ratio (EDR) is used to estimate embodied CO₂ emissions; a structural decomposition analysis (SDA) is employed to analyze the driving factors for changes in CO₂ emissions embodied in China's exports to the US during 2002–2007. The results of the input–output analysis show that net export of CO₂ emissions increased quickly from 2002 to 2005 but decreased from 2005 to 2007. These trends are due to a reduction in total CO₂ emission intensity, a decrease in the exchange rate, and small imports of embodied CO₂ emissions. The results of the SDA demonstrate that total export volume was the largest driving factor for the increase in embodied CO₂ emissions during 2002–2007, followed by intermediate input structure. Direct CO₂ emissions intensity had a negative effect on changes in embodied CO₂ emissions. The results suggest that China should establish a framework for allocating emission responsibilities, enhance energy efficiency, and improve intermediate input structure.     

Participation in GVCs and CO2 emissions

This paper attempts to explore the determinants of CO₂ emissions in the context of international trade. While there exist studies that examine the roles of horizontal specialization and inter-industry trade transactions, little previous research attention has been paid to the roles of vertical specialization and intra-industry trade transactions in affecting CO₂ emissions. To fill the knowledge gap, this study uses the panel data of 62 countries and regions for the period of 1995–2011 to estimate the effect of participation in global value chains (GVCs) on per capita CO₂ emissions. Major findings include: (1) The relationship between participation degrees in GVCs and per capita CO₂ emissions is found to be inversely U-shaped at the aggregate economy-level and for most individual industries; (2) Per capita GDP shows an N-shaped relationship with per capita CO₂ emissions; and (3) Benign drivers of CO₂ emissions include R&D, energy conservation, and population control. It can be concluded that countries with low GDP or GVC participation degrees are expected to experience worsening CO₂ emissions in the short or even medium run. This trend, however, can be moderated or even reversed with more R&D investments.     

Research and development for steam and gas turbines in low-carbon future

Abstract

Future energy requirements for the UK will need to be met with reduced CO₂ emissions. There is a requirement for 2050 CO₂ emissions to be at 20% of 1990 levels. To achieve this there will need to be considerable investment into the research and development, and construction of renewables technologies. Despite this emphasis on renewable power, fossil fuelled power generation technologies, and in particular turbines, will still have a major role to play in the future. However, the way in which the turbines will be used may change significantly. There will therefore need to be research and development investment for turbines at all levels of technology readiness. The arguments for future R&D investment for steam and gas turbines are reviewed and some directions the R&D may need to take examined.     

Driving forces of rapid CO2 emissions growth: A case of Korea

This study aims to investigate Korea's final demand structure and its impacts on CO₂ emissions in order to reduce CO₂ emissions and develop environmental policy directions. Based on the environmentally extended input–output model, this study adopts a two-step approach: (1) to estimate the embodied emissions and their intensities for 393 sectors induced by final demand; and (2) to calculate the driving factors of emission growth between 2003 and 2011 and then evaluate the result by using Structural Decomposition Analysis (SDA). The findings of this study demonstrate that the impact of composition change in export with less embodied emission intensities tends to offset the increase in CO₂ emission by the export scale growth. The relatively low residential electricity price has resulted in the rapid growth of household electricity consumption and significantly contributed to emissions growth. The result of SDA indicates that Korea's final demand behavior yielded high carbonization over the same period. The findings suggest that Korean government should promote exports in industries with less embedded CO₂ in order to protect environments. In addition, emission information of each product and service should be provided for consumers to change their purchase patterns towards contributing to low carbon emissions as active players.     

R&D intensity and carbon emissions in the G7: 1870–2014

We examine the effect of research and development (R&D) intensity on carbon dioxide (CO₂) emissions in the Group of Seven (G7) countries since the nineteenth century using a non-parametric panel data model. Our estimates suggest that the relationship between R&D and CO₂ emissions is time-varying. The estimated time-varying coefficient function of R&D was negative for three quarters of the period studied, but was positive for a 35-year period (1955–1990) during the second half of the twentieth century. Our non-parametric local linear estimates show that the common trend functions gradually increased for the first 110 years (1870–1980), but then flattened out and showed a slight decrease for the next three decades.     

Estimation,characteristics, and determinants of energy-related industrial CO2 emissions in Shanghai (China), 1994–2009

This paper estimates energy-related industrial CO₂ emissions (ICE) in Shanghai from 1994 to 2009 and summarizes ICE's characteristics. The results show that the coal-type consumption is the ICE's largest source of the entire industry and that the energy consumption structure of CO₂ emissions of the entire industry depends largely on that of six sub-sectors of high emission group, which contributes to most of ICE. Furthermore, the paper implements an econometric study on the ICE's determinants based on the ICE-STIRPAT model. The results indicate that the relationship between ICE and per capita output presents an inverted N-shaped curve with two turning points, resulting from the comprehensive influence of scale, composition, and technique effects, and that most sub-sectors remain in the second stage of the curve. Energy efficiency exerts a more efficient control over ICE than R&D intensity. ICE intensity is regulated more easily than ICE scale. In the long run, industrial growth and coal-type consumption play the most important roles in driving ICE, whereas energy efficiency exerts the most prominent effect on reducing it. The results of the robustness analysis indicate that the utilization of the ICE-STIRPAT model is valid and robust under the setting of environment impact control over ICE in Shanghai.     

Can expanding natural gas infrastructure mitigate CO2 emissions? Analysis of heterogeneous and mediation effects for China

To verify whether the expansion of natural gas infrastructure can effectively mitigate carbon dioxide (CO₂) emissions in China, this study first investigates the impact of natural gas infrastructure on China's CO₂ emissions by employing a balanced panel dataset for 30 Chinese provinces covering 2004–2017. Fully considering the potential heterogeneity and asymmetry, the two-step panel quantile regression approach is utilized. Also, to test the mediation impact mechanism between natural gas infrastructure and CO₂ emissions, this study then analyzes the three major mediation effects of natural gas infrastructure on China's CO₂ emissions (i.e., scale effect, technique effect, and structure effect). The empirical results indicate that expansion of the natural gas infrastructure can effectively mitigate China's CO₂ emissions; however, this impact is significantly heterogeneous and asymmetric across quantiles. Furthermore, through analyzing the mediation impact mechanism, the natural gas infrastructure can indirectly affect CO₂ emissions in China through the scale effect (i.e., gas population and economic effects) and structure effect (i.e., energy structure effect). Conversely, the technique effect (i.e., energy intensity effect) brought by natural gas infrastructure on CO₂ emissions in China has not been significant so far. Finally, policy implications are highlighted for the Chinese government with respect to reducing CO₂ emissions and promoting growth in the natural gas infrastructure.     

Carbon intensity of electricity in ASEAN: Drivers,performance and outlook

The Association of Southeast Asian Nations (ASEAN), with its ten member countries, has a total population exceeding 600 million. Its energy-related CO₂ emissions have been growing and in 2013 amounted to 3.6% of total global emissions. About 40% of ASEAN's energy-related CO₂ emissions are currently attributable to electricity production. In view of this high share, we study the CO₂ emissions of ASEAN's electricity production sector with a focus on the aggregate emission intensity (ACI) given by the level of CO₂ emissions for each unit of electricity produced. Drivers of ACI are analysed for individual countries and spatial analysis is conducted by comparing factors contributing to differences between the ACIs of individual countries and that of the ASEAN average. Arising from these analyses and in light of the current developments, it is concluded that drastic actions need to be taken both at the national and regional levels in order to reduce growth in the region's electricity-related CO₂ emissions. Two key policy issues, namely overcoming national circumstances to improve electricity generation mix and improving power generation efficiency, are further discussed.     

Energy and CO2 emissions performance in China's regional economies: Do market-oriented reforms matter?

This paper employs a newly developed non-radial directional distance function to evaluate China's regional energy and CO₂ emission performance for the period 1997–2009. Moreover, we analyze the impact of China's market-oriented reform on China's regional energy and carbon efficiency. The main findings are as follows. First, most of China's regions did not perform efficiently in energy use and CO₂ emissions. Provinces in the east area generally performed better than those in the central and west areas. By contrast, provinces in the west area generally evidenced the lowest efficiency. Second, Market-oriented reforms, especially the promotion of factor market, were found to have positive effect on the efficiency of energy use and CO₂ emissions. Third, the share of coal in the total energy consumption and the expansion of the industrial sector were found to be negatively correlated with China's regional energy and CO₂ emissions performance. Based on the empirical findings, we provide policy suggestions for enhancing energy and carbon efficiency in China.     

Factors influencing CO2 emissions in China's power industry: Co-integration analysis

More than 40% of China's total CO₂ emissions originate from the power industry. The realization of energy saving and emission reduction within China's power industry is therefore crucial in order to achieve CO₂ emissions reduction in this country. This paper applies the autoregressive-distributed lag (ARDL) co-integration model to study the major factors which have influenced CO₂ emissions within China's power industry from 1980 to 2010. Results have shown that CO₂ emissions from China's power industry have been increasing rapidly. From 1980 to 2010, the average annual growth rate was 8.5%, and the average growth rate since 2002 has amounted to 10.5%. Secondly, the equipment utilization hour (as an indicator of the power demand) has the greatest influence on CO₂ emissions within China's power industry. In addition, the impact of the industrial added value of the power sector on CO₂ emissions is also positive from a short-term perspective. Thirdly, the Granger causality results imply that one of the important motivators behind China's technological progress, within the power industry, originates from the pressures created by a desire for CO₂ emissions reduction. Finally, this paper provides policy recommendations for energy saving and emission reduction for China's power industry.     

Investigating the driving factors of regional CO2 emissions in China using the IDA-PDA-MMI method

In this paper, we systematically summarized existing research on the driving factors of CO₂ emissions and found that changes in technology gap may be one of the key driving factors of CO₂ emissions. Technology efficiency, technology progress, and technology gap were decomposed by using the Meta-frontier Malmquist index (MMI), which was then combined it with the Index Decomposition Analysis (IDA) and the Production-theoretical Decomposition Analysis (PDA). Our framework was applied to Chinese provincial data from 2000 to 2016. We identified nine factors to explain changes of regional CO₂ emissions. Results demonstrate that economic scale, energy technology efficiency, and output technology efficiency increased CO₂ emissions in Eastern, Central, and Western regions of China, with the economic scale being the largest contributor. Energy structure, energy intensity, energy technology progress, and output technology progress decreased regional CO₂ emissions, with the energy technology progress playing the strongest role. Energy technology gap and output technology gap led to an increase in CO₂ emissions in Central China and, to a lesser extent, in Western China. The effects of each driving factor on CO₂ emissions varied across provinces. Finally, policy implications are suggested to reduce CO₂ emissions in China.     

Biomass and CCS: The influence of technical change

The combination of bioenergy production and carbon capture and storage technologies (BECCS) provides an opportunity to create negative emissions of CO₂ in biofuel production. However, high capture costs reduce profitability. This paper investigates carbon price uncertainty and technological uncertainty through a real option approach. We compare the cases of early and delayed CCS deployments. An early technological progress may arise from aggressive R&D and pilot project programs, but the expected cost reduction remains uncertain. We show that this approach results in lower emissions and more rapid investment returns although these returns will not fully materialise until after 2030. In a second set of simulations, we apply an incentive that prioritises sequestered emissions rather than avoided emissions. In other words, this economic instrument does not account for CO₂ emissions from the CCS implementation itself, but rewards all the sequestered emissions. In contrast with technological innovations, this subsidy is certain for the investor. The resulting investment level is higher, and the project may become profitable before 2030. Negative emission in bioethanol production does not seem to be a short-term solution in our framework, whatever the carbon price drift.