Carbon Intensity Reduction Target Research Articles

The effect of the multi-target energy and climate policy on carbon emissions: County-level evidence from China

The use of command-and-control target policies for climate governance is crucial in achieving China's “dual carbon” goals. We investigate the impact of multi-target policy on county-level carbon emissions, using the generalized difference-in-differences model for the gradual implementation at different phases of multiple policies. We find that the Carbon Intensity Reduction Target (CIRT) and Total Energy Consumption Target (TECT) policies promote carbon reduction, while the Energy Intensity Reduction Target (EIRT) policy has less reliable outcomes. In the eastern and central regions, the initial phase of carbon reduction is primarily propelled by the EIRT policy, subsequently transitioning to the dominant influence of the CIRT policy. In the later phase, carbon reduction in the eastern region is predominantly attributed to the CIRT policy, whereas in the central region, it results from the combined effects of the EIRT, CIRT, and TECT policies. In the western region, early policies have an insignificant impact on carbon reduction, and the later-phase effects shift from being primarily influenced by the EIRT to being predominantly influenced by the CIRT. Additionally, neglecting the impact of other policies with similar targets during the same period may lead to overestimation of the effects of EIRT and TECT and underestimation of the effect of CIRT.

Forecasting China’s CO2 emissions and identifying key drivers: an application of the improved RFAGM model and LMDI decomposition methods

ABSTRACT China, the world’s largest CO2 emitter, has pledged to reduce its carbon intensity by 18% by 2025, which requires accurate forecasting of its emissions and their drivers. However, existing gray models have limitations in dealing with fluctuating data or long-time series data, and they often suffer from overfitting and poor generalization ability. Moreover, there is a lack of research and judgment on the future changes of emission drivers. To address these issues, this study proposes a fractional order gray adaptive rolling model (RFAGM(1,1)) that optimizes the background generation and incorporates the rolling mechanism. We apply RFAGM(1,1) to forecast China’s emissions, GDP, population, and consumption of raw coal, crude oil, and natural gas from 2020 to 2025. Our results show that RFAGM(1,1) achieves significantly higher accuracy than standard gray models, except for population. The projections indicate that China will meet the 18% carbon intensity reduction target by 2025. Furthermore, the LMDI decomposition reveals that economic growth and population changes have positive cumulative impacts on emission growth (245.68% and 11.95%, respectively), while energy intensity and structural changes have negative cumulative impacts (−151.60% and −6.02%, respectively). The improved forecast enables the evaluation of climate policies, while the factor analysis provides valuable insights for developing evidence-based strategies to achieve China’s carbon peaking and neutrality goals by 2030/2060.

Carbon regulation and enterprise investment: Evidence from China

Enterprises' investment response to China's carbon regulation policy is essential to the country's high-quality development. Using a difference-in-differences model, we investigate the differential impacts of China's Low-carbon Pilot (LP) program on both state-owned enterprises (SOEs) and non-SOEs, in order to reveal the differences in response to government intervention. The results show that the LP program has a negative effect on the productive investments of non-SOEs, but SOEs show unclear effect from the LP program. This conclusion remains credible after robustness tests. The negative impact of the LP program on the productive investments of non-SOEs is particularly evident in carbon-intensive sectors and large enterprises; investment diminishes in correlation with increases in the carbon intensity reduction targets. China's LP program is found to cause a decrease in the available credit resources and an increase in financing costs, in addition to a loss of technical efficiency and a reduction in investment willingness for non-SOEs, resulting in reduced productive investments.

(Invited) Design, Assessment, and Performance Evaluation of an Fully-Integrated Electrochemical Process for Direct Capture of CO2 from Flue Gas and Its Conversion to High-Purity Ethylene

Ethylene (C2H4) is a hydrocarbon of extensive societal, environmental, and industrial importance. Therefore, synthesizing C2H4 sustainably via the electrochemical CO2 reduction reaction (CO2RR) is an attractive area to explore. Even though many existing CO2RR systems have reached industrially relevant current densities (~1A/cm^2), almost all use a gas diffusion electrode (GDE)-based electrochemical system with a single-pass CO2 conversions less than 10%. Low conversion leads to a low C2H4 concentration in the gaseous product stream which mainly comprises CO2, contributing to costly post-CO2RR separation of products, rendering even processes with high CO2RR current densities unfit for scale up. In this talk, I will present an automated and fully-integrated system that combines CO2 capture and conversion into a single, sustainable, and more energy-efficient process. In particular, our technology captures CO2 from the exhaust of natural-gas combustion power plants and converts it to high-purity ethylene. The patented CO2 capture process utilizes novel migration-assisted moisture gradient (MAMG) process, with record performances of over 99% selectivity and over 0.3 mmol/m2s of capture flux. Our team has recently discovered electrocatalysts based on mixed Cu/CuOx with performance far exceeding state-of-the-art catalysts for CO2 conversion with 600 mA cm-2 and Faradaic efficiency to C2H4 over 58%. The system will be scaled up as a supplementary process to existing C2H4 production plants or for inclusion in new plants meeting carbon intensity reduction targets.

The long and winding road towards the creation of climate clubs: Transatlantic negotiations, potential regulatory models and challenges ahead

AbstractProposals for the establishment of plurilateral climate clubs have gained momentum, and both the European Union (EU) and the United States (US) will play a pivotal role in forthcoming negotiations. This article closely examines EU and US proposals to uncover distinctive features in their regulatory approaches and to critically assess different potential models for sectoral climate club arrangements. The article argues that a middle ground could be reached by combining the US policy‐neutral approach with the EU distinctive product‐based focus. A bottom‐up model involving average sectoral carbon intensity reduction targets, product standards and bans could provide an effective and practicable way forward. Recent declarations confirm that the negotiations of the Global Steel and Aluminium Arrangement are focusing on product standards. Nonetheless, several challenges lie ahead. These include the difficult coordination between plurilateral arrangements and the EU carbon border adjustment mechanism, and the US focus on non‐market economies and excess capacity.

An Evaluation on Sectoral Competitiveness of Guangdong in China: The Role of Carbon Taxation Policy

Given the spatial heterogeneity of the social-economic situations across different regions in China, the decomposition of emission reduction targets should be designed according to the actual characteristics of the industrial economy. There is concern about the loss of industrial competitiveness and leakage of CO2 emissions if just seven pilot carbon markets operate independently, so the national carbon market of the power sector was established in 2021. In this study, a China two-region CGE model including Guangdong (GD) and the rest of China (ROC) is built on an analysis of the long-term effects of CO2 prices in industrial sectors at the target 2030 peak. Based on this model, we constructed one business-as-usual scenario and six comparison carbon tax scenarios to quantify the CO2 cost impact for a wide range of manufacturing sectors and identify specific economic activities that face relatively high CO2 costs between the two regions. Based on the China two-region CGE model, the risks of leakage and competitiveness distortions in these potentially exposed sectors are qualitatively assessed. The results show that chemical, nonferrous metal, and machinery are GD’s competitive sectors, and agriculture, food, textile, paper, cement, construction, and service belong to ROC’s competitive industry. Both GD and ROC need to further unify carbon pricing policies at the same time to effectively coordinate the carbon intensity reduction target and industrial development, which is 2.6% and 3.2% of the severe GDP loss compared with BaU when implementing carbon tax policy. The results can support the setting of the carbon tax and industrial competitiveness promotion policy and with a strong reference to support the provincial emission reduction path.

Study on the extension of the dynamic benchmark system of per capita carbon emissions in China's county.

County is the center of China’s socio-economic development and the key node for urban–rural integration. Also, the county is an important carrier for promoting urban and rural green development. Improving green and low-carbon development capabilities and formulating county-level low-carbon standards will play a significant role in promoting China’s new people-oriented urbanization and rural revitalization. Although there have been extensive studies on low-carbon benchmarks, over half of the benchmarks tend to ignore the development stage of the evaluated region and its needs. When the region’s economy reaches a certain level, constraints from low-carbon targets may limit the local development process. This study firstly allocated county carbon intensity reduction targets (CIRT) by considering the differences in county carbon reduction capacity and responsibility. Secondly, a dynamic benchmark system of per capita carbon emissions (PCCE) in counties in China is constructed. Finally, we took Changxing County in Zhejiang Province as a research case to verify the dynamic benchmark of PCCE. According to the carbon intensity target reduction rate (CITRR), China’s counties can be divided into three categories: low carbon emissions reduction capability-responsible counties (L-CERCRC), medium carbon emissions reduction capability-responsible counties (M-CERCRC), and high carbon emissions reduction capability-responsible counties (H-CERCRC). The results show that (1) due to the national CO2 emission reduction target in 2030, the carbon intensity will be 60% lower than in 2005, the CITRR for China’s 1510 counties range from 8.36 to 137.83%; the average CITRR is 48.40%. (2) Changxing County’s CITRR is 57.71%, which belongs to the H-CERCRC. The PCCE of Changxing County will be much higher than the benchmark when the carbon peak is reached in the future. (3) For reaching the aiming benchmark, Changxing County is suggested to adjust its relevant influencing factors of PCCE for converting local’s PCCE reaching to the benchmark within a certain time period. The dynamic benchmark system for PCCE in China’s counties established in this study is economically sensitive, which not only takes the differences of counties into account, but also meets the needs of counties’ diverse development form stages. This system provides counties a few coordinated directions which can improve the local’s economic development and reduce greenhouse gas (GHGs) emissions through the development progress.

Efficiency of Carbon Dioxide (CO2) Emission Control Target Allocations in China

Effectively allocating emission control targets is critical for China to achieve its emission reduction goals. This study researched the efficiency of total carbon dioxide (CO2) emission control target allocations during the 13th Five-Year Plan period (2015–2020). The efficiency of carbon intensity reduction targets, allocated by the National Development and Reform Commission in 30 regions, was assessed using a Directional Distance Function (DDF) model. Then, a Zero-Sum Gains (ZSG)-DDF model was constructed to determine how to optimally allocate total CO2 emission, under the premise of maximizing economic benefits and minimizing CO2 emissions. The results showed that in the case of fixed total CO2 emissions, to improve the resource allocation efficiency, the quota should be increased in the regions with high efficiencies, and the quota should be reduced in the regions with low efficiencies. The results in this paper can help guide the future allocations of total CO2 emission in China.

Heterogeneous low-carbon targets and energy structure optimization: Does stricter carbon regulation really matter?

In this study, we use the difference-in-difference strategy to examine the effect of stricter carbon regulation on energy structure. We find that, under stricter carbon regulation, regions with above-average carbon intensity reduction targets (CIRTs) prefer to use high-carbon energy. This conclusion is found to be reliable after the robustness tests; the regions with moderate CIRTs prefer to use low-carbon energy. When low-carbon targets are increased, the effect of the policy is much greater. The reason is that above-average CIRTs lead to an improved marginal output growth rate and an increased technological bias of high-carbon energy. This increased bias further causes enterprises to increase the scale of high-carbon energy input and reduce the proportion of low-carbon energy. This study reveals that, under the constraints of the low-carbon policy, stricter carbon regulation is not conducive to optimizing the energy structure, while moderate CIRTs are conducive to increasing the consumption of low-carbon energy.

Assessing the CO2 reduction target gap and sustainability for bridges in China by 2040

In China, rapid and continuing infrastructure growth will significantly affect the feasibility of achieving CO2 emission reduction targets. It is uncertain whether the current infrastructure designs are consistent with the national emission targets of China, consequently posing a threat to the national commitment to reaching carbon neutrality. To illustrate the gap in achieving the emission targets with respect to bridges, we present carbon intensity reduction targets relevant to bridges by 2040. By exploring three policy–economic scenarios that combine with CO2 emission reduction policy scenarios of the International Energy Agency and shared socioeconomic pathways, we assess the adaptability of the bridge designs to short-, medium- and long-term carbon intensity targets. We propose a new sustainability design approach based on a bridge big data set that integrates reliability, environmental impacts, and cost. We show that, under the current policy–economic scenario, more than 50% of code-based bridges would meet the five-year CO2 emission target, whereas only one in ten thousand could meet the ten-year target under the new policy–economic scenario. Under the sustainable development policy–economic scenario, none of the bridge designs would meet the carbon reduction targets over the next 20 years. Our findings highlight that the bridges in China need to be duly considered in setting CO2 reduction targets, and in the national move toward zero carbon, careful consideration should be given to implementing our proposed bridge sustainability design.

Initial Allocation Model of CO2 Emission Allowances Based on the Equity-Efficiency Tradeoff

Reasonably and fairly allocating carbon intensity reduction targets among Chinese provinces is a key problem in effectively controlling and reducing CO2 emissions. This study establishes the ZSG-DDF model combining the Zero-Sum Gains DEA and the Directional Distance Function to study the CO2 emission allowance allocations from the perspective of maximum efficiency. This model can discriminate desirable and undesirable outputs and solve the problem of total CO2 emission amount control. Then, we add the equity principle to the constraint conditions, namely, the proportion of carbon emission allowance approaching the proportion of GDP. Finally, we establish a CO2 emission allocation scheme based on the equity-efficiency tradeoff while considering the relationship between economic development and carbon emissions as well as achieving maximum efficiency. We use this new model to allocate CO2 emission allowance during the Chinese 13th Five-Year Plan, and compare it with the other two allocation schemes, including National allocations during the 13th Five-Year Plan, allocation scheme from the perspective of efficiency maximization. The results have a certain significance for government departments to formulate the allocation scheme of CO2 emission allowance.

Unintended consequences of carbon regulation on the performance of SOEs in China: The role of technical efficiency

Abstract The change in the level of operating performance of state-owned enterprises (SOEs) under the constraint of climate policies is directly related to the success or failure of subsequent low-carbon development. In this study, taking the Low-carbon Pilot Program introduced in 2010 by the central government as an exogenous natural experiment, we investigate the impact of carbon regulation on the operating performance of SOEs by using the difference-in-differences (DID) strategy for the first time. We conduct a series of robustness tests on the estimated results, including a placebo test by changing the control group, a parallel trend test by advancing the introduction time of the policy, and an interference elimination of the self-selection bias by using the propensity score matching (PSM) method. Furthermore, we examine the heterogeneous effects with regard to carbon intensity reduction targets. Finally, we use the heterogeneous stochastic frontier analysis method to measure the technical efficiency and analyze the influential mechanism of carbon regulation on the performance of SOEs. The results show that the carbon regulation policy significantly reduces the operating performance of SOEs. Through a series of robustness tests, we find that this conclusion is reliable. The higher the carbon intensity reduction target set by the central government is, the greater the negative impact of the carbon regulation policy on the performance of SOEs will be. Under the constraints of climate policies, SOEs acquire additional credit resources and launch a great quantity of inefficient investment. These actions inhibit the improvement of firms' technical efficiency and reduce the operating performance of SOEs. Therefore, the central government should strive to promote R&D activities related to low-carbon technology and improve the technical efficiency of SOEs when introducing any low-carbon policy.

The formation and transmission of upstream and downstream sectoral carbon emission responsibilities: Evidence from China

Abstract The design of scientific and reasonable policies for emission reduction depends on an understanding of the formation and transmission of upstream and downstream carbon emission (UCE and DCE) responsibilities at the sectoral level along production chains. By extending subsystem analysis from UCEs to DCEs, this study investigates the formation mechanism of sectoral emission responsibilities in both directions. The approach is illustrated through the case of Zhejiang Province from 2002 to 2012. Moreover, multi-temporal structural path analysis is applied to identify the crucial UCE and DCE transmission paths and the perturbation factors for path regulation priorities. The results show that: (1) sectoral emission responsibilities exhibit significant disparities from the entire production chain perspective, and Mining (MS2), Electricity, Steam, Gas and Water Production and Supply (MS18), and Other Services (MS24) are the primary emission sources. (2) The spillover effect plays the dominant role in the formation of UCEs and DCEs. (3) Setting quantitative direct carbon intensity reduction targets for Electricity, Steam, Gas and Water Production and Supply (MS18) and optimizing consumption structures of emission-intensive intermediate products can significantly reduce the spillover effects of UCEs and DCEs. (4) Emission regulation priorities for crucial transmission paths depend on the path types, path emission transfers, and path economic multipliers.

The Allocation of Carbon Intensity Reduction Target by 2030 among Cities in China

The regional allocation of carbon emission quotas is of great significance to realize the carbon emission target. Basing on the combination of the multi-index method and the improved equal-proportion distribution method, and fully considering the differences in economic factors, population factors, energy factors, technological factors among cities, China’s 2030 carbon intensity reduction target was allocated. The results indicate that: (1) Under the target constraint of 60% reduction in CO2 emissions per unit of Gross Domestic Product (GDP) (carbon intensity) in 2030 compared to 2005, the carbon intensity target reduction rate (CITRR) of 285 Chinese cities is between 17.65% and 141.14%, with an average reduction rate of 51.52%; (2) the CITRR of cities presents significant spatial positive correlation, and the Global Moran I correlation index is 0.38; and (3) the distribution trend of CITRR is the same as the general trend of economic development of China, showing a basic trend of gradual decline from south to north and from coastal to inland. The allocation method takes into account fairness and efficiency, and reflects the differences between cities, so that the allocation results are likely to be accepted by all parties. Meanwhile, this method breaks the limitation of the lack of city’s data and is likely to implement in actual operation. Cities should choose distinguished low-carbon economic development paths, in combination with their characteristics of economic and social development, and carry out inter-city cooperation to promote carbon emission reduction steadily.

Structural and technological determinants of carbon intensity reduction of China's electricity generation.

Electricity generation is the largest sector with decarbonization potential for China and the world. Based on the new emission factors, this paper aims to identify the structural and technological determinants of provincial carbon intensity in the electricity generation sector (CIE) using the multiplicative LMDI-II method. Results demonstrate that (1) China's overall CIE decreases by 7.3% in 2001-2015, and the research period can be divided into four stages according to CIE changes (i.e., rapid growth, rapid decline, slow growth, and transition). The CIE in the 12th FYP estimated in this paper, 24.9% lower than that using the emission factors from IPCC, is closer to China's actual situation. (2) There exists huge heterogeneity in the determinants of provincial CIE changes in four stages. CIE growth in the Northwest and Northeast is caused by the coal-dominated energy structure. CIE growth in the Southwest is attributed to the electricity structure effect, while that of the Coast region is caused by the geographic distribution effect. The electricity efficiency effect is attributed to the CIE growth for these regions and the Southwest should also place focus on the electricity trade effect. The impact of electricity trade-related factors depends on the region being a net exporter or importer of electricity. (3) To achieve carbon intensity reduction targets, 30 provinces are categorized into four types based on various combinations of structural and technological determinants. The findings provide insights into capturing future emission-mitigating focus as well as defining the emission-mitigating responsibilities between electricity exporters and importers in China.

Does China's carbon regulatory policy improve total factor carbon efficiency? A fixed-effect panel stochastic frontier analysis

In China, climate policy has been strengthened by the mandated carbon intensity reduction target, which is a simple measurement of carbon efficiency under the single-factor framework. Is this carbon regulation during the 12th Five-Year Plan (FYP) actually effective for total factor carbon efficiency (TFCE) in China? To answer this research question, we estimate the TFCE and its policy and economic drivers using the fixed-effect stochastic frontier approach. The main results are as follows. First, the TFCE shows time and sector heterogeneity ranging from 0.235 to 0.996. Moreover, the changing pattern implies a positive relationship between TFCE and the 12th FYP. Second, the implementation of carbon regulations during the 12th FYP not only helped meet the carbon intensity reduction target, but also assisted in effectively improving TFCE. Third, carbon regulations have positively enhanced the role of energy prices in TFCE promotion and alleviated the negative role of exports. The results have significant policy implications for the carbon regulations in China's forthcoming 14th FYP. It is necessary to introduce market-oriented tools aside from the existing command-and-control policies.

Study on Feasible Carbon Reduction Paths Based on CO2 Abatement Cost Curve

Estimation of CO2 abatement costs is a critical issue in achieving the targets of carbon emission reduction of China while promoting the economic growth. This paper builds an objective programming model to estimate the China’s marginal CO2 abatement costs during 2020-2030. We designed six different mitigation strategies based on China’s 60-65 percent carbon intensity reduction target by 2030 and investigated the total economic-wide cost of these strategies. The results show that the non-equal increasing strategies will significantly increase the overall cumulative carbon dioxide emission reduction and reduce the overall cost compared to the non-equal decreasing strategies and equal amount strategies.

Quantifying the role of technical progress towards China’s 2030 carbon intensity target

This paper constructs a dynamic computable general equilibrium (DCGE) model to investigate the macroeconomic effects of endogenous technical progress in achieving China’s 2030 carbon intensity reduction target of 60–65% compared with 2005. We show that a combination of a carbon tax and technological progress can achieve the carbon intensity target in 2030, but it will exert a negative impact on economic growth. This negative effect, however, can be relieved by endogenously directed technological progress in the long term. In doing so, industrial structure and energy structure are dynamically adjusted by inhibiting the output and employment of the coal and oil sectors but promoting that of the clean energy and the service industry. We also find that with technological progress, the unit carbon abatement cost in the long term is estimated to be 200–250 yuan/ton, much lower than that in the short term (over 367 yuan/ton). Several policy implications are discussed accordingly.

How China's electricity generation sector can achieve its carbon intensity reduction targets?

As the largest sector with decarbonization potential, electricity generation is critical for achieving carbon intensity reduction targets of China by 2020 and 2030. This study combines temporal decomposition and scenario analysis to identify the key drivers and provinces with increasing carbon intensity of electricity generation (CIE) and designs four scenarios by integrating efficiency improvement and structural adjustment in 30 provinces of China, and estimates the possible reduction of CIE by 2020 and 2030. Results show that 1) CIE in China decreases by 7.25% during 2001–2015. The estimated CIE during 12th FYP in this study is 25% lower than the estimation using IPCC emission factors, which is closer to China's reality. 2) Driving forces of CIE changes in 30 provinces vary greatly across provinces. The increasing CIE in four worse-performance regions (i.e. Northeast, South Coast, Southwest, Northwest) is mainly caused by energy mix effect and geographic distribution effect. The CIE growth in South Coast is also related to thermal power share effect. 3) Both 2020/2030 targets can be achieved by regulating the drivers for CIE growth in 30 provinces (i.e., RAK scenario). CIE decline is concentrated in three types of provinces, namely provinces with large economic size, strong policy support and clean energy implementation. The findings and recommendations provide insights into achieving 2020/2030 targets for CIE reduction.

Re-examining the realization of provincial carbon dioxide emission intensity reduction targets in China from a consumption-based accounting

Abstract China’s administrative regions distribute their carbon dioxide emissions mitigation burdens differently. As a result of closer interregional economic connections, embodied carbon emissions are transferred among provinces via inter-provincial trade, resulting in carbon leakage. China usually adopts a production-based principle to evaluate the realization of carbon intensity reduction targets for disparate provinces. The carbon dioxide emission reduction targets from a consumption-based accounting were re-examined, and compared two methods that have been applied. From 2002 to 2007, the rankings of carbon dioxide emission intensity variation rates from production-based and consumption-based accounting resulted in different province rankings and, although the gaps in the rankings between both methods changed between 2007 and 2012, particularly in Guizhou and Yunnan. Because the production-based calculation ignores carbon leakage and is ineffective in accurately assessing reduction targets, these targets were re-examined from a consumption-based accounting. These findings are very significant for China’s policies on carbon dioxide emissions reduction: the provinces’ targets on reducing carbon dioxide emissions may be evaluated rationally with regard to inter-provincial carbon leakage in China; kinds of support for the reduction of carbon dioxide emissions can favor less developed regions; and encouraging economic mechanics for technological innovations assist in managing carbon dioxide emissions at the national scale.