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.     

Energy caps: Alternative climate policy instruments for China?

Decoupling fossil energy demand from economic growth is crucial for China's sustainable development, especially for addressing severe local air pollution and global climate change. An absolute cap on coal or fossil fuel consumption has been proposed as a means to support the country's energy and climate policy objectives. We evaluate potential energy cap designs that differ in terms of target fuel, point of control, and national versus regional allowance trading using a global numerical general equilibrium model that separately represents 30 provinces in China. First, we simulate a coal cap and find that relative to a cap on all fossil fuels, it is significantly more costly and results in high localized welfare losses. Second, we compare fossil energy cap designs and find that a national cap on downstream fossil energy use with allowance trading across provinces is the most cost effective. Third, we find that a national fossil energy cap with trading is nearly as cost effective as a national CO₂ emissions trading system that penalizes energy use based on carbon content. As a fossil energy cap builds on existing institutions in China, it offers a viable intermediate step toward a full-fledged CO₂ emissions trading system.     

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.     

Urban energy use and carbon emissions from cities in China and policy implications

Urban areas contain 40% of the population and contribute 75% of the Chinese national economy. Thus, a better understanding of urban energy uses is necessary for Chinese decision-makers at various levels to address energy security, climate change mitigation, and local pollution abatement. Therefore, this paper addresses three key questions: What is the urban contribution to China's energy usage and CO₂ emissions? What is the contribution of large cities, and what alternate energy–economy pathways are they following? How have energy uses and CO₂ emissions transformed in the last two decades in key Chinese cities? This three-tier analysis illustrates the changes in urban energy uses and CO₂ emissions in China. The results show that the urban contributions make up 84% of China's commercial energy usage. The 35 largest cities in China, which contain 18% of the population, contribute 40% of China's energy uses and CO₂ emissions. In four provincial cities, the per capita energy usage and CO₂ emissions have increased several-fold. Rapid progress was made in reducing the carbon intensity of economic activities in cities throughout the 1990s, but alarmingly, such progress has either slowed down or been reversed in the last few years. These results have important policy implications.     

China's 2020 carbon intensity target: Consistency,implementations, and policy implications

China has pledged to reduce its CO₂ emissions per unit of GDP by 40–45% by 2020 as of 2005 level. This research examines China's 2020 carbon intensity target and its interdependence with the overarching national economic and social development goals. The results show that, with annual GDP growth rate at 7% during the 12th Five-Year-Plan (FYP) period and 6% during the 13th FYP period, the 45% CO₂ intensity reduction target implies annual CO₂ emissions of 8600 million tonnes by 2020, close to 8400 million tonnes, the UNFCCC 450 ppm scenario for China. However, achieving only the 40% reduction target will lead to 9380 million tonnes CO₂ emissions in 2020 which largely surpass the UNFCCC 450 ppm scenario. We conclude that China's 45% CO₂ intensity reduction target is not only within international expectations but also self-consistent with its overall economic and social development strategy. Then primary energy and power planning for implementing the 45% carbon intensity reduction target is proposed. Related investment requirements are also estimated. To achieve the target, China needs to restructure the economic structure for significant improvements in energy conservation.     

Development of China TIMES-30P model and its application to model China's provincial low carbon transformation

To explore the provincial energy system transformation till 2050 under the carbon emission constraints from a bottom-up perspective, this research develops the China TIMES-30P model with detailed characterization of China's provincial energy system and applies it to low carbon scenarios analysis. A set of methodology is developed to project the key provincial socio-economic parameters and the provincial energy service demand, which is the major driving force of the China TIMES-30P model. Results show that compared with the value in 2015, the provincial intensity of final energy consumption will decrease by 65%–90% under different scenarios in 2050. The intensities of primary energy consumption in most of the provinces will be lower than 0.2 tce/1000 dollars under different scenarios in 2050. In the WBD2 scenario, the national CO₂ emission can reach the peak value of 9.3 billion tons in 2020 and the provincial CO₂ emission intensity in 2050 will decrease by 85%–100%, compared with the value in 2015.     

Impacts of China's emissions trading schemes on deployment of power generation with carbon capture and storage

The establishment of an emissions trading scheme (ETS) in China creates the potential for a “least cost” solution for achieving the greenhouse gas (GHG) emissions reductions required for China to meet its Paris Agreement pledges. China has pledged to reduce CO₂ intensity by 60–65% in 2030 relative to 2005 and to stop the increase in absolute CO₂ emissions around 2030. In this series of studies, we enhance the MIT Economic Projection and Policy Analysis (EPPA) model to include the latest assessments of the costs of power generation technologies in China to evaluate the impacts of different potential ETS pathways on deployment of carbon capture and storage (CCS) technology. This paper reports the results from baseline scenarios where power generation prices are assumed to be homogeneous across the country for a given mode of generation. We find that there are different pathways where CCS might play an important role in reducing the emission intensity in China's electricity sector, especially for low carbon intensity targets consistent with the ultimate goals of the Paris Agreement. Uncertainty about the exact technology mix suggests that decision makers should be wary of picking winning technologies, and should instead seek to provide incentives for emission reductions. While it will be challenging to meet the CO₂ intensity target of 550 g/kWh for the electric power sector by 2020, multiple pathways exist for achieving lower targets over a longer timeframe. Our initial analysis shows that carbon prices of 35–40$/tCO₂ make CCS technologies on coal-based generation cost-competitive against other modes of generation and that carbon prices higher than 100$/tCO₂ favor a major expansion of CCS. The next step is to confirm these initial results with more detailed modeling that takes into account granularity across China's energy sector at the provincial level.     

How industrialization and urbanization process impacts on CO2 emissions in China: Evidence from nonparametric additive regression models

This paper examines the impacts of industrialization and urbanization on CO₂ emissions in China using nonparametric additive regression models and provincial panel data from 1990 to 2011. The empirical results show that there is an inverted U-shaped nonlinear relationship between industrialization and CO₂ emissions in the three regions in China. Urbanization follows an inverted U-shaped pattern with CO₂ emissions in the eastern region, and a positive U-shaped pattern in the central region. However, the nonlinear impact of urbanization on CO₂ emissions is insignificant in the western region. As a result, the differential dynamic effects of industrialization and urbanization on CO₂ emissions in the three regions should be taken into consideration in reducing China's CO₂ emissions.     

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.     

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.     

Who shapes China's carbon intensity and how? A demand-side decomposition analysis

As national efforts to decouple carbon emissions from economic growth intensify, policymakers need more specific, sub-national information about the sources and reduction potentials of carbon intensity. This study presents a demand-side decomposition of China's carbon intensity to its regions, final demand types, and economic sectors, based on a predefined “aggregate embodied intensity (AEI)” indicator, i.e. the ratio of embodied emissions to embodied value added. We find that China's carbon intensity has been largely shaped by developed provinces, capital investment demand, and the construction sector. However, less-developed provinces, consumption demand, and the services sector have played increasingly important roles. Wealthy provinces generally experienced much lower AEIs and higher AEI reductions compared to poor provinces from 2007 to 2012, mainly owing to provincial differences in final demand structure and sectoral structure. Coastal region's emission reduction efforts at both production and demand sides were the main contributor to China's decrease in carbon intensity during the period, while interior region's structural degradation in demand partially offset the decrease. Our results suggest that allocating national carbon intensity targets based on AEI, and adjusting the final demand structure of central-western provinces, would greatly benefit for China to achieve its ambitious carbon intensity target by 2030.     

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.     

Forward-looking assessment of the GHG abatement cost: Application to China

Evaluation of abatement costs is critical in setting reduction goals and devising climate policy. However, reliable forward-looking assessment of the short-term effects of climate policy remains a major challenge. Using panel data of 30 Chinese provinces during 1997–2015, we first estimate the marginal CO₂ abatement costs using a novel data-driven approach, convex quantile regression. Based on the marginal abatement cost estimates and China's plans regarding carbon intensity reduction and economic growth, we present a forward-looking assessment of the abatement costs for Chinese provinces for 2016–2020. Our main finding is that all the Chinese provinces have a negative abatement cost, which means these provinces can benefit from an increase in the absolute level of CO₂ emissions despite the constraint on carbon intensity. The magnitudes of economic benefits exhibit a significant regional disparity because some provinces can increase more CO₂ emissions than others. However, there is still costly carbon intensity abatement relative to a counterfactual where the provinces meet their economic growth targets but in the absence of the intensity reduction constraints. Policy implications have been proposed to enhance the efficiency and fairness of climate policy in China.     

Regional differences in the CO2 emissions of China's iron and steel industry: Regional heterogeneity

Identifying the key influencing factors of CO₂ emissions in China's iron and steel industry is vital for mitigating its emissions and formulating effective environmental protection measures. Most of the existing researches utilized time series data to investigate the driving factors of the industry's CO₂ emission at the national level, but regional differences have not been given appropriate attention. This paper adopts provincial panel data from 2000 to 2013 and panel data models to examine the key driving forces of CO₂ emissions at the regional levels in China. The results show that industrialization dominates the industry's CO₂ emissions, but its effect varies across regions. The impact of energy efficiency on CO₂ emissions in the eastern region is greater than in the central and western regions because of a huge difference in R&D investment. The influence of urbanization has significant regional differences due to the heterogeneity in human capital accumulation and real estate development. Energy structure has large potential to mitigate CO₂ emissions on account of increased R&D investment in energy-saving technology and expanded clean energy use. Hence, in order to effectively achieve emission reduction, local governments should consider all these factors as well as regional heterogeneity in formulating appropriate mitigation policies.     

CO2 emissions,energy consumption and economic growth in China: A panel data analysis

This paper examines the causal relationships between carbon dioxide emissions, energy consumption and real economic output using panel cointegration and panel vector error correction modeling techniques based on the panel data for 28 provinces in China over the period 1995–2007. Our empirical results show that CO₂ emissions, energy consumption and economic growth have appeared to be cointegrated. Moreover, there exists bidirectional causality between CO₂ emissions and energy consumption, and also between energy consumption and economic growth. It has also been found that energy consumption and economic growth are the long-run causes for CO₂ emissions and CO₂ emissions and economic growth are the long-run causes for energy consumption. The results indicate that China's CO₂ emissions will not decrease in a long period of time and reducing CO₂ emissions may handicap China's economic growth to some degree. Some policy implications of the empirical results have finally been proposed.     

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.     

Can China achieve its 2030 energy development targets by fulfilling carbon intensity reduction commitments?

China has proposed carbon intensity targets and energy development targets for 2030. This study investigates the linkages between these targets and assesses if China can achieve its energy development targets by fulfilling its carbon reduction commitments. To this end, it quantitatively evaluates the impact of carbon emission controls on the Chinese economy using a dynamic computable general equilibrium model. The results show that China's carbon abatement pledge cannot guarantee achievement of all energy objectives. China is likely to reach the upper limit of its carbon intensity target in 2020 and the lower limit in 2030 if current abatement efforts are maintained. To achieve the upper limit in 2030, the carbon price will be CNY 83/tCO₂. The energy consumption target for 2020 is likely to be realized but the 2030 target is not. A more stringent price constraint on carbon emissions would be helpful to the achievement of the non-fossil energy target in 2030, but would have a limited promoting effect on natural gas development. Our results reveal the linkages between China's energy targets and carbon emission targets, which is valuable to the cost-effective dual control of energy consumption and carbon emission.     

From carbonization to decarbonization?—Past trends and future scenarios for China's CO2 emissions

Along the lines of the Kaya identity, we perform a decomposition analysis of historical and projected emissions data for China. We compare the results with reduction requirements implied by globally cost-effective mitigation scenarios and official Chinese policy targets. For the years 1971–2000 we find that the impact of high economic growth on emissions was partially compensated by a steady fall in energy intensity. However, the end – and even reversal – of this downward trend, along with a rising carbon intensity of energy, resulted in rapid emission growth during 2000–2007. By applying an innovative enhanced Kaya-decomposition method, we also show how the persistent increase in the use of coal has caused carbon intensity to rise throughout the entire time-horizon of the analysis. These insights are then compared to model scenarios for future energy system developments generated by the ReMIND-R model. The analysis reaffirms China's indispensable role in global efforts to implement any of three exemplary stabilization targets (400, 450, or 500 ppm CO₂-only), and underscore the increasing importance of carbon intensity for the more ambitious targets. Finally, we compare China's official targets for energy intensity and carbon intensity of GDP to projections for global cost-effective stabilization scenarios, finding them to be roughly compatible in the short-to-mid-term.     

Firm-level determinants of energy and carbon intensity in China

In recent years, China׳s leaders have sought to coordinate official energy intensity reduction targets with new targets for carbon dioxide (CO₂) intensity reduction. The Eleventh Five-Year Plan (2006–2010) included for the first time a binding target for energy intensity, while a binding target for CO₂ intensity was included later in the Twelfth Five-Year Plan (2011–2015). Using panel data for a sample of industrial firms in China covering 2005 to 2009, we investigate the drivers of energy intensity reduction (measured in terms of direct primary energy use and electricity use) and associated CO₂ intensity reduction. Rising electricity prices were associated with decreases in electricity intensity and increases in primary energy intensity, consistent with a substitution effect. Overall, we find that energy intensity reduction by industrial firms during the Eleventh Five-Year Plan translated into more than proportional CO₂ intensity reduction because reducing coal use—in direct industrial use as well as in the power sector—was a dominant abatement strategy. If similar dynamics characterize the Twelfth Five-Year Plan (2011–2015), the national 17 percent CO₂ intensity reduction target may not be difficult to meet—and the 16 percent energy intensity reduction target may result in significantly greater CO₂ intensity reduction.