Certified Emission Reductions Research Articles

Forest emissions reduction assessment from airborne LiDAR data using multiple machine learning approaches

Objective: This study aims to evaluate the accuracy of different modeling methods and tree structural parameters extracted from airborne LiDAR for estimating carbon emissions reduction and assess their reliability as Certified Emission Reduction (CER) assessment techniques.Methods: LiDAR data was collected from an afforestation project in Beijing, China. Various modeling methods, including statistical regression and machine learning algorithms, were used to estimate biomass and carbon emissions reduction. The models were evaluated under two schemes: tree-species-specific modeling scheme (Scheme 1) and all-sample modeling scheme (Scheme 2) using cross-validation and compared with ground-based estimations and pre-estimated emission reductions.Results: Totally, the biomass estimation models in scheme 1 showed better accuracy than scheme 2. In scheme 1, The Random Forest (RF) and Cubist models achieved the highest prediction accuracy (R2 = 0.89, RMSE = 22.87 kg, CV RMSE = 52.00 kg), followed by GDBT and Cubist, with SVR and GAM performing the weakest. In scheme 2, Cubist model had the highest accuracy (R2 = 0.75, RMSE = 33.95 kg, CV RMSE = 36.05 kg), followed by RF and GBDT, with SVR and GAM performing the weakest. LiDAR-based estimates of carbon emissions reduction were closer to ground-based estimations and higher than pre-estimated values.Conclusion: This study demonstrates that LiDAR-based models using tree structural parameters can accurately assess carbon emissions reduction. The models outperformed traditional methods in terms of cost and accuracy. Considering tree species in the modeling process improved the accuracy of the models. LiDAR technology has the potential to be a reliable assessment technique for carbon emissions reduction in forestry projects. The pre-trained models can be used for multiple predictions, reducing the cost of carbon sink surveys. Overall, LiDAR-based models provide a promising approach for assessing carbon emissions reduction and can contribute to mitigating climate change.

A carbon trading approach for heat-power-hydrogen integrated energy systems based on a Vickrey auction strategy

Exploring the way of the integrated heat-power‑hydrogen energy system (CHHP) participates in carbon trading is important for reducing carbon emissions and achieving carbon peaking and carbon neutrality goals. To fully consider the potential for renewable energy to participate in the carbon trading market through Chinese certified emission reductions (CCERs), this paper proposes a carbon trading method for CHHP based on a Vickrey auction strategy. Firstly, the model of CHHP is built by considering the waste heat of the hydrogen power generation system. The calculation of CCERs of hydrogen and other renewable energy sources is then studied based on calorific value and combined marginal emission factors. Meanwhile, given the zero carbon of renewable energy sources and the large difference in price between Chinese emission allowances (CEAs) and CCERs. For traditional energy sources, a baseline approach is used to allocate CEAs to carbon sources. A price-fixed trading model for CEAs is established considering actual carbon emissions; For the CCERs from hydrogen and other renewable energy, a trading mechanism based on a Vickrey auction has been introduced. Finally, the proposed method is analyzed in three scenarios. The approach proposed in this paper results in lower system operation costs and more favorable planning for low-carbon emission output equipment. The results show that the proposed trading method has advantages in the economy and carbon emissions.

How to promote the Chinese Certified Emission Reduction scheme in the carbon market? A study based on tripartite evolutionary game model

The Chinese Certified Emission Reduction (CCER) scheme is of great significance for China to achieve its “dual carbon” targets. However, limited effort has been made to explore the CCER scheme due to poor data availability and the short implementation time. Therefore, this study constructs a tripartite evolutionary game model involving the government, carbon emission control enterprise, and renewable energy enterprise, to analyze the evolutionary stability of each subject's strategy choice. The results indicate that: (1) Strict regulation of the government could promote carbon emission control enterprise to actively purchase CCER quotas, and motivate renewable energy enterprise to declare CCER projects. (2) When the corresponding condition is met, the system could reach the ideal evolutionary steady state of (1,1,1), and keep a stable operational status for the CCER scheme market. (3) The condition of the CCER price below the carbon price, appropriate penalties for non-compliance of carbon emissions, the dynamic balance between carbon offset rate and project declaration cost, and proper subsidies for CCER project declaration, all could promote the development of CCER projects in the carbon market. This study could enrich the knowledge hierarchy of CCER and provide important decision references for developing the CCER scheme in the carbon market.

A bi-level scheduling strategy for integrated energy systems considering integrated demand response and energy storage co-optimization

In the context of China's “double carbon” commitment to the world, the introduction of integrated demand response mechanism and compressed air energy storage system into the traditional energy system is important to improve its structure, promote the interaction of multiple heterogeneous energy sources, and improve energy conversion efficiency. As such, in this study, we constructed an upper-layer capacity configuration model aiming to optimize the operating costs of compressed air energy storage systems during the planning period and subsequently integrated a heterogeneous energy network operation and China's certified emission reduction constraints under various operating scenarios. We established a lower-level optimal scheduling model with the optimization objective of minimizing the energy purchase, operation, maintenance, integrated demand response subsidy, and carbon trading costs. Finally, the KKT condition and the Big M method were used to solve this two-tier optimization problem. The comparative analysis of the three schemes showed that, under the consideration of the integrated demand response mechanism and the equipped compressed air energy storage system, the total operating cost of the system was reduced by an average of 2.28 %, the carbon emission was reduced by an average of 7.17 %, the profit from the sale of surplus carbon emission credits increased by an average of 16.7 %, and the energy storage capacity was reduced by approximately 39 %. Thus, this method effectively reduced the capacity of the energy storage system and significantly improved its reliable, economic, and low-carbon operation.

Research Progress and Prospect of Tourism Carbon Emissions and Its Uncertainty Analysis Under the Goal of Low-Carbon Scenic Spots

Under the dual carbon goal, China Certified Emissions Reductions (CCER) and the national carbon market have become important means of emission reduction and control. The tourism industry is a strategic pillar industry of China’s national economy, and scenic spots are the main sites of tourism activities. Research on carbon emissions in scenic spots is of great significance for the construction of low-carbon scenic spots and the realization of the dual carbon goal. In this paper, the research on carbon emissions in tourism is reviewed, the current research progress is discussed, and further prospects are made. The research on tourism carbon emissions in China has a good foundation and achieved certain results. However, there are few studies on micro-scales such as scenic spots. The statistical data caliber and measurement methods of carbon emissions are not uniform, and there is a general lack of uncertainty analysis. Future research should focus on building a multi-spatial dimension research system, unifying the statistical caliber and measurement methods of carbon emission data, increasing uncertainty analysis, and ensuring the robustness of research results.

Has Chinese Certified Emission Reduction trading reduced rural poverty in China?

AbstractConsolidating and expanding poverty alleviation while simultaneously reducing carbon emissions has become one of the main issues facing China. The Chinese Certified Emission Reduction (CCER) trading programme is an important supplementary mechanism to China's carbon trading market. Based on the data of 1782 counties in China from 2006 to 2017 and a difference‐in‐differences model, this study investigates the rural poverty reduction effect of CCER trading. We find that: (1) during the sample period, CCER trading has increased the per capita net income of rural residents by at least 2.5% or 187.5 RMB (about 27.8 USD or 39.3 AUD) per year. (2) The poverty reduction effect of CCER trading in poor counties is greater than that in nonpoor counties. (3) Some relevant heterogeneous effects are also measured. We find that CCER trading of hydropower projects has played a significant poverty reduction effect; the poverty reduction effect is further enhanced when the county has additional CCER projects; we also identify regional differences with CCER trading having a greater poverty reduction effect in the western and central regions. (4) Compared with the implementation of the CCER project, trading the emission reductions generated by the CCER project has brought more significant poverty reduction effects.

China's forest carbon sinks and mitigation potential from carbon sequestration trading perspective

To achieve carbon peaking and neutrality goals, China is establishing a national unified carbon emission trading market, especially including forest carbon sequestration market. This study assesses the potential of China’s forest carbon sinks and mitigation potential. We use the Global Forest Products Model to simulate the dynamic changes in China's forest resources from 2018 to 2060, under different carbon sequestration prices scenarios. The projection results indicate that China's forest carbon sinks will be 1.26 Pg (peta-grams) in 2021–2030 and 6.78 Pg in 2021–2060, giving an offset ratio of 4.9–7.0 % and 13.2–18.2 % of China's projected carbon emission in the same period, respectively. Therefore, China's forest carbon sinks will play an important role in carbon peaking and neutrality goals. Meanwhile, forest carbon trading has the potential to increase China's forest carbon sequestration, although the impact may not be immediately apparent. The additional increase in forest carbon sinks from carbon sequestration trading scenarios will not exceed 1.6 % of China’s total carbon emissions between 2021 and 2030. At the current carbon trading price in China ($6.84/t), the increase in forest carbon sinks resulting from forest carbon trading will give an offset ratio of approximately 1 % of total carbon emissions from 2021 to 2060. When the carbon price rises, this offset ratio is 2.3 % to 3.1 % ($25/t), 4.1 % to 5.6 % ($54/t). China should therefore hasten the integration of forest carbon sinks into the national carbon emission unified market and boost the carbon trading price by policy design and market adjustment, or government directly compensate for the forest carbon sequestration function. For forest carbon sinks to play their role in reducing the carbon neutral cost of society, China should raise the amount of forest carbon sink CCERs (Chinese Certified Emission Reductions) used to offset carbon emission allowances in key emission units.

Asymmetric time-varying dependence and variable structure dependence measurement and analysis of EUA and CER

Abstract This paper analyzed the time-varying dependence and structural dependence between EU allowances (EUAs) and certified emission reductions (CERs) by using price fluctuation data from 2008 to 2021 on EU ETS. It was found that (1) there was a strong nonlinear spillover relationship between EUAs and CERs. From 14 March 2008 to 16 March 2012, the time-varying dependence values of EUAs and CERs were mostly between 0.6 and 1 and the mean coefficient of dependence was 0.86, showing a strong interdependence. From 17 March 2012 to 2 January 2017, the correlation between them was mostly below 0.6 and the mean coefficient of dependence fell to 0.25. This indicates that the dependency between EUA futures and CER futures was very low at this stage. However, in general, the mean value of dependence was above 0.55, that is, there was a dependency between them. (2) From 14 March 2008 to 2 January 2017, there were 12 structural mutation points in EUA and CER yield sequences. After four mutation points, the dependence coefficient increased and the structural dependence enhanced. Meanwhile, after eight mutation points, the dependence coefficient decreased and the structural dependence weakened. The overall level remained above 0.6, showing the existence of structural dependence. (3) Abrupt changes in EUA and CER prices were closely related to the promulgation of major policies and unpredictable emergencies. The former caused carbon prices to fluctuate slightly. When the period of change was short and the recovery was rapid, it caused sharp fluctuations in carbon prices. When the duration of change was long, and the recovery was slow, it yielded impacts that extend far beyond the publication of important information.

A split Bregman method solving optimal reactive power dispatch for a doubly-fed induction generator-based wind farm

This paper proposes an optimal reactive power control method to maximize wind farm revenue and minimize the total electrical losses of a doubly-fed induction generator (DFIG)-based wind farm. Specifically, the split Bregman method is used to solve the optimal control problem in a distributed manner. That is, the optimization problem is decomposed into sub-problems by the optimal distributed control strategy, and each sub-problem is solved independently in each local controller through the parallel method, which reduces the calculating burden and improves the information privacy. Thus, when a fault occurs, the proposed distributed control strategy can overcome the system fault and improve the reliability and security of the system. Furthermore, an economic financial model of annual revenue is contributed to examine the income impact with or without certified emission reduction (CER) by the clean development mechanism (CDM). Compared with the dual ascent (DA) method, sequential quadratic programming (SQP) method and the proportional dispatch method (PDM), the annual revenue (AR) of the wind farm using the proposed split Bregman method is the highest. Simulation results demonstrate that this method has promising performance in both optimization quality and computational efficiency.

Credit Analysis of Carbon Sink Ecological Compensation in P.R.C from the Perspective of Coase Theorem: An Empirical Analysis Based on Carbon Sink Financial Projects in X Village of Guangdong and Y Village of Zhejiang

The deterioration of the global environment and climate makes it historically important to achieve carbon peaking and carbon neutrality and plays an important role in promoting environmental protection. Among them, forestry carbon sink resources occupied an important role in China Certified Emission Reduction (CCER). While the development of carbon trading in China is still in its initial stage, the government is piloting it in some areas first, accumulating experience and gradually promoting it. This research analyzes the economic operation mechanism of the current carbon trading project such as the Green Carbon Credits, the management structure of CCER: How CCER can reduce the cost of emission reduction for enterprises and increase the flow of social wealth, how to make the development of forestry carbon sinks more widespread, and the potential directions for future development: how to make CCERs more widely available.

Paths and policy adjustments for improving carbon-market liquidity in China

Weak liquidity and low spot prices for carbon are critical problems facing China's carbon markets. This study aims to quantify the liquidity of China's carbon markets under different carbon-pricing strategies by analyzing a model which integrates linkages between the government, markets, and firms. It uses the decoupling theory to set the penalty scale, aiming to reduce the effects of carbon emissions on economic growth. The model permits the study of policy adjustments for certified emission reduction, traders' coverage, and free quotas — the benchmarks of quota allocation. The theoretical analysis indicates that the effect of policy on market liquidity is mainly reflected in the penalty scale and quota-allocation rules. Numerical simulations indicate that the issuance of new quotas accounts for 3.3% of total allocated quotas and raises carbon prices by about 45%. Further, the carbon price rises with an increase in free quotas and then rapidly drops after a peak price of 57 yuan/ton. Our findings indicate that adding free quotas in the short term and expanding trading volume in the middle and long term will improve market liquidity and raise carbon prices.

Bidding modes for renewable energy considering electricity-carbon integrated market mechanism based on multi-agent hybrid game

The proposal of carbon peak and carbon neutrality goals will inevitably promote the large-scale development of renewable energy, and the market mechanism is also being pushed forward to absorb more renewable energy in China. Considering electricity-carbon integrated market mechanism, this paper constructs a hybrid game model to study the evolutionary process of renewable energy generation companies (GENCOs) in market trading by setting up three renewable energy bidding modes. Among them, the leader-follow relationship between GENCOs and the day-ahead electricity market is reflected by the Stackelberg game model, and the bidding behavior of different GENCOs is described by cooperative and non-cooperative game models. The role of different stages for the carbon emissions trading (CET) market on the electricity market is discussed based on the sensitivity analysis. The simulation results show that the bundled sales between wind, photovoltaic and thermal power GENCOs could improve the expected profits of each GENCO and reduce the total carbon emissions. As the proportion of renewable energy in the electricity market increases, the clearing prices will decrease. Meanwhile, the peak-shaving times of thermal power units will raise, and thermal power GENCOs are more willing to participate in the auxiliary service market. Besides, the complete marketization of renewable energy GENCOs will affect the recovery of the initial investment. Moreover, it can be found that lower free carbon quota, higher CET and Chinese certified emission reduction (CCER) prices can effectively guide the electricity market to be cleaner.

How to Incorporate Blue Carbon into the China Certified Emission Reductions Scheme: Legal and Policy Perspectives

Blue carbon, the carbon sequestered in vegetated coastal ecosystems, is a potential and practical approach to combating climate change. Many countries have committed to integrating blue carbon into the climate change law and policy framework. As a significant carbon-emitting country, China has abundant blue carbon resources but suffers a significant loss of coastal habitats. Therefore, blue carbon should become a primary focus in China’s climate change law and policy. Given the successful experience in terrestrial biosequestration projects, the inclusion of blue carbon into China’s carbon trading market can be an essential move and is the primary purpose of this paper. The China Certified Emission Reductions (CCER) scheme is an effective supplementary mechanism to the national carbon trading market. To incorporate blue carbon into the CCER scheme, this article first analyzes the legislative framework underpinning the CCER scheme and indicates some critical factors, including methodology, project boundaries, legal rights, additionality, project period, and crediting period. Subsequently, the article discusses these critical factors in depth to identify legal issues that may emerge and provides several feasible solutions. (i) Dedicated methodologies need to be developed for blue carbon projects, which include a broader definition for carbon abatement activities. (ii) The new national marine functional zoning should delineate zones for the purpose of developing blue carbon projects. (iii) The current authorization system for the right to use sea areas could be used to secure a legal right to develop blue carbon projects. (iv) Additionality requirements should be appropriately adjusted. (v) Extended project periods and crediting periods would be needed. This article offers novel pathways for including blue carbon in China’s climate change law and policy framework, thus contributing to achieving its 2060 carbon neutrality goal.

Investment in CO2 capture and storage combined with enhanced oil recovery in China: A case study of China's first megaton-scale project

In recent years, China has accelerated the development of CCUS (CO2 capture, utilization and storage) technology and started construction of the first megaton-scale CCS-EOR (CO2 capture and storage combined with enhanced oil recovery) project. Taking China's first megaton-scale CCS-EOR project as an example, this study constructs a comprehensive evaluation method that integrates the decision rules of the real option approach and net present value approach to evaluate the economics and investment strategies of China's CCS-EOR projects under multiple uncertainties. The results show that the project investment in 2022 can create a profit of 2.94 million USD because of the introduction of a tax credit policy that will begin in 2030 with an initial amount of 10 USD/ton of CERs (certified emission reductions) and an annual increment of 2 USD/ton of CERs, but the optimal time to invest should be 2025. Without this incentive policy, the profit opportunity and ability of the case project will be greatly reduced. In addition, the decision-making of CCS-EOR project investment is extremely sensitive to capital cost, oil production, incentive policy start time, and incentive intensity. Therefore, China should formulate and implement tax credit incentives or similar policies with a high incentive intensity as soon as possible to improve the confidence of potential CCUS investors. Direct financial support for early CCS-EOR projects through government financial allocations should be an important addition. In addition, enterprises should strive to accurately calculate and forecast the capital cost and oil production.

Multi-objective planning and optimization of microgrid lithium iron phosphate battery energy storage system consider power supply status and CCER transactions

Lithium iron phosphate battery (LIPB) is the key equipment of battery energy storage system (BESS), which plays a major role in promoting the economic and stable operation of microgrid. Based on the advancement of LIPB technology and efficient consumption of renewable energy, two power supply planning strategies and the china certified emission reduction (CCER) model are proposed respectively. Based on it, the multi-objective planning optimization model with economic benefits, environmental benefits and power supply stability as the objective function is established for the first time, and the Newton Weighted Sum Frisch method (NWSFA) solution model is adopted. In the planning process, rain flow counting method is used to research the life of BESS, which improves the accuracy of energy storage annual cost calculation. A park in northern China is taken as a case study to demonstrate the application of this model. The simulation results show that the annual economic operating cost of BESS is decreased by 18.81%, the energy supply reliability is increased by 0.15%, and the optimal electricity price adjustment ratio of the system is 15%.

Blue carbon sequestration following mangrove restoration: evidence from a carbon neutral case in China

ABSTRACT Sequestration of blue carbon (C) in mangrove plantations depends on site characteristics and plantation management. This study evaluated the effects of plantation management on C sequestration at a C-neutral site in Xiamen, China. A field study was conducted on 10-year-old Sonneratia apetala and Kandelia obovata plantations (mono-Sa, mono-Ko) and a 15-year-old mixed plantation-. We found that mono-Ko had a significantly higher ecosystem C sequestration rate (3.32 ± 0.62 kg C m−2 yr−1) than others when planted in the indirect shade of pioneer species. As a non-native species, Sonneratia performed better (0.57 ± 0.01 kg C m−2 yr−1) when planted with Kandelia than in monotypic plantations. The temporary and long-term certified emission reduction (tCER and lCER) of the 12.98 ha mono-Ko was 4103.89 and 3693.50 net CO2-e within 10 years, respectively. A literature review was conducted to show the compatibility of this study with other natural and plantation sites of China and Bangladesh (the native habitat for Sonneratia). The C sequestration of Sonneratia plantation sites in China is comparable with those in Bangladesh. However, the soil C accumulation rate for a Sonneratia monotypic plantation in Bangladesh decreased with age, yet the same did not occur in the plantations of China.

Assessing barriers to the internationalization of China’s certified emission reductions (CCERs): a Delphi survey

ABSTRACT China’s certified emission reductions (CCERs) are generated under the China GHG Voluntary Emission Reduction Programme. In 2020, this programme was approved by the technical advisory board of the Carbon Offset and Reduction Scheme for International Aviation (CORSIA) set up under the International Civil Aviation Organisation (ICAO), making CCERs an eligible reduction unit to be used for compensating emissions stemming from the aviation sector. While such an achievement represents a cornerstone in China’s strategy on internationalizing CCERs, there remains significant practical and quality-related issues which prevent CCERs from playing a more significant role in the international carbon market. To identify these issues and understand their relative importance, we employed a Delphi approach to elicit consensus views from 17 experienced CCER practitioners on potential issues and adjustments needed for the improvement of international recognition, acceptance, and the use of CCERs. We identified defects in eight key areas: social and environmental risk management; reversal of emissions reductions; pricing mechanisms; verification systems; evaluation systems for sustainable development contributions; transaction channels for international actors; CCER methodologies; and legal and asset attributes. Based on these findings, the authors make policy recommendations for improving the China GHG Voluntary Emission Reduction Programme. Key policy insights Being selected as eligible offset credits for CORSIA does not guarantee that CCERs can contribute significantly to compensating aviation emissions. To increase the degree of internationalization of CCERs, the governing body of CCERs should address both quality-related and practical issues. Substantial efforts should be made towards managing environmental and social risks and the risk of emission reversal of CCERs.

Estimation of landfill gas production and potential utilization in a South Africa landfill

ABSTRACT Landfill gas composition comprises mainly of methane and carbon dioxide emissions and other Nonmethane Organic Carbons (NMOCs). Methane gas has a global warming potential that is estimated to be 25–36 over 100 years. Interestingly, methane generated from landfills is a renewable source of energy that has been used over the years as a source of electricity generation especially in developed and in some developing countries. However, methane from landfills has been underutilized in South Africa. Due to the recent unreliable electricity disruptions (load shedding) in South Africa, which is caused by a variety of factors. Prioritizing methane produced from landfills for use as a fuel for electricity generation is critical. This will assist to minimize the over-reliance on coal and, reduce the ongoing landfill gas generation. Therefore, the purpose of this study is to estimate the amount of methane emitted from Weltervenden landfill site using the LandGEM version 3.02 and Afvalzorg models and to evaluate the potential utilization of the gases emitted. The study was also aimed at determining the cost and benefits related to the implementation of a landfill gas utilization technology. The findings of this study show that methane emissions from the landfill will peak in the year 2023 with values of 4613 Mg/year and 3128 Mg/year for LandGem and Afvalzorg models, respectively. Also, the total methane emissions from the year 1999 to 2050, are 111,799.25 Mg/year and 27,898.93 Mg/year for both LandGEM and Afvalzorg models, respectively. The LFGcost web model simulations showed that the implementation of a LFG utilization project using Microturbine and CHP microturbine engines are economically feasible. This is considering the sales of electricity to the people. However, considering the sales of electricity generated and Certified Emission Reductions (CER) (carbon credits) to the global market all engines used in this study will be economically feasible. Implications: The methane emitted from the Polokwane landfill estimated from LandGEM and Afvalzorg models will peak in year 2023 at 4613 Mg/year and 3128 Mg/year, respectively. Also, the total methane emissions from the year 1999 to 2050, are 111,799.25 Mg/year and 27,898.93 Mg/year for both LandGEM and Afvalzorg models, respectively. The LFGcost web model simulations showed that the implementation of a LFG utilization project using Microturbine and CHP microturbine engines are economically feasible. This is considering the sales of electricity to the people. Therefore, implementation of LFG utilization is economically feasible from sales of electricity generated and Certified Emission Reductions

A Logistic Modelling Analysis for Wind Energy Potential Assessment and Forecasting its Diffusion in Pakistan

There is increased focus to harness renewable energy resources in the 21st century to contain climate change and attain energy security. In this context, wind energy is attaining a significant marketplace to meet the ever-increasing electricity demand. This study, as such, undertakes wind energy assessment and forecasts wind power market penetration in Pakistan considering three different scenarios for the period 2020–2050. The modeling approach of this study is based on the Levenberg–Marquardt algorithm (LMA) optimization method, which is used to estimate the parameters of the logistic model to improve forecasting precision. It is revealed that around 55, 64, and 73% of wind potential could be technically exploited under each of the three scenarios, respectively. The Certified Emission Reductions (CERs) for each scenario are also estimated. The anticipated annual abatement of GHG emissions and CERs earnings at 30% capacity utilization factor is found to be 158 million CERs by the year 2050. These results suggest that wind energy offers great potential to attain energy security, environmental stability, and sustainable development in Pakistan. This study would assist energy professionals, government, and stakeholders to undertake wind energy market assessment and devise appropriate energy management plans.

Market-based solution in China to finance the clean from the dirty

Financial incentives play a key role in promoting renewable energy investments that can help China achieve the ‘dual carbon’ goal. The national emissions trading scheme (ETS) and the renewable energy portfolio standard (RPS) are two existing market-based policy instruments that can generate stable expected returns for low-carbon projects. This paper studies the interactive distribution effects of these two market-based instruments. We use the micro-level thermal power plant data to investigate the abatement effects of the national ETS, in which the details show that the existing rate-based ETS will result in higher negative impacts on power units, whose installed capacities are smaller than 400 MW. The interactive distribution effects between the two markets will occur when the permit allocation standards of the national ETS become stricter than the existing ones. Provinces in Eastern China and Northern China will face high pressure on costs in both ETS and RPS markets. When the levels of the permit allocation standards are set as 70% of the existing ones and the carbon price is assumed to be 200 yuan/ton in 2030, the annual market size of the national ETS will be nearly 100 billion yuan, and the annual market size is predicted to be 250 billion yuan. In the existing rate-based national ETS, the China Certified Emission Reduction (CCER) mechanism will have an offsetting effect, which should be taken into serious consideration during the policy-making processes in the future.