Marginal Abatement Cost Research Articles

The synergetic competition of cross-regional integrated energy systems with low-carbon technology heterogeneity under carbon emission trading mechanism to achieve carbon reduction target

The integration of renewable and fossil energy in a Region Integrated Energy System (RIES) is recognized as an effective measure for carbon emission reduction. The emergence of carbon emission trading (CET) markets worldwide has raised the need to combine RIES optimal planning with CET to achieve carbon reduction targets. This study focuses on the synergetic competition of a cross-RIES system with low-carbon technology heterogeneity under the CET mechanism. A cross-RIES model is constructed, incorporating fossil Carbon Capture System (fossil-CCS), renewable Combined Cooling Heating and Power (renewable-CCHP), and cleaner production paradigms. An improved version of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is used to propose a bi-level multi-objective optimal planning framework for the cross-RIES model, employing a grandfather permit allocation method. Comparative analysis is conducted between cross-RIES optimal planning with and without considering the CET mechanism, with a focus on environmental indexes such as carbon emission, carbon intensity, and marginal abatement cost. Sensitivity studies are also performed to explore the impact of key CET design parameters on the system's environmental performance. The simulation results demonstrate that the CET mechanism effectively reduces carbon emission, primary energy consumption, and carbon intensity by promoting synergetic competition among the low-carbon technology heterogeneity of RIESs. Furthermore, the environmental performance varies among the three types of RIES. In terms of CET parameter design, lowering the cap constraint, reducing the allowance allocation ratio of fossil-CCS RIES, and increasing the trading price contribute significantly to reducing carbon emission and carbon intensity, albeit at the expense of higher marginal abatement cost.

Investigating the Future of Freight Transport Low Carbon Technologies Market Acceptance across Different Regions

Fighting climate change has become a major task worldwide. One of the key energy sectors to emit greenhouse gases is transportation. Therefore, long term strategies all over the world have been set up to reduce on-road combustion emissions. In this context, the road freight sector faces significant challenges in decarbonization, driven by its limited availability of low-emission fuels and commercialized zero-emission vehicles compared with its high energy demand. In this work, we develop the Mobility and Energy Transportation Analysis (META) Model, a python-based optimization model to quantify the impact of transportation projected policies on freight transport by projecting conventional and alternative fuel technologies market acceptance as well as greenhouse gas (GHG) emissions. Along with introducing e-fuels as an alternative refueling option for conventional vehicles, META investigates the market opportunities of Mobile Carbon Capture (MCC) until 2050. To accurately assess this technology, a techno-economic analysis is essential to compare MCC abatement cost to alternative decarbonization technologies such as electric trucks. The novelty of this work comes from the detailed cost categories taken into consideration in the analysis, including intangible costs associated with heavy-duty technologies, such as recharging/refueling time, cargo capacity limitations, and consumer acceptance towards emerging technologies across different regions. Based on the study results, the competitive total cost of ownership (TCO) and marginal abatement cost (MAC) values of MCC make it an economically promising alternative option to decarbonize the freight transport sector. Both in the KSA and EU, MCC options could reach greater than 50% market shares of all ICE vehicle sales, equivalent to a combined 35% of all new sales shares by 2035.

The cost-efficiency carbon pricing puzzle

Any global temperature target must be translated into an intertemporal carbon budget and its associated cost-efficient carbon price schedule. Under the Hotelling’s rule without uncertainty, the growth rate of this price should be equal to the interest rate. It is therefore a puzzle that many cost-efficiency IAM models yield carbon prices that increase at an average real growth rate above 7% per year, a very large return for traders of carbon assets. I explore whether uncertainties surrounding the development of green technologies could solve this puzzle. I show that future marginal abatement costs and aggregate consumption are positively correlated. This justifies doing less for climate change than in the safe case, implying a smaller initial carbon price, and an expected growth rate of carbon price that is larger than the interest rate. In the benchmark calibration of my model, I obtain an equilibrium interest rate around 1% and an expected growth rate of carbon price around 3.5%, yielding an optimal carbon price above 200 USD/tCO2 within the next few years. I also show that the rigid carbon budget approach to cost-efficiency carbon pricing implies a large uncertainty surrounding the future carbon prices that support this constraint. I show that green investors should be compensated for this risk by a large risk premium embedded in the growth rate of expected carbon prices, rather than by a collar on carbon prices as often recommended.

Techno-economic-environmental analysis based on life cycle carbon accounting and pollutants audit for cleaner production of electrolytic manganese

The electrolytic manganese metal (EMM) industry faces significant environmental challenges, including substantial resource and energy consumption, severe pollution, and high CO2 emissions. This study introduced a novel approach for developing collaborative strategies aimed at mitigating pollutants and CO2 emissions. Through the implementation of life cycle carbon accounting and critical pollutant audits, a process enhancement program incorporating 17 advanced technologies was developed. Aligned with the principles of cleaner production, this project effectively mitigates the environmental burden at the source and offers viable solutions for addressing prominent emissions, such as manganese residue and acid fog. Furthermore, the marginal abatement cost curves demonstrate the economic practicality and applicability of these measures. This study provides a strategic blueprint for achieving sustainable green development in China’s EMM industry and offers valuable guidelines for formulating relevant environmental policies.

Research on the energy transition pathways of the transportation sector in the Guangdong–Hong Kong–Macao Greater Bay Area, China

Energy transitions is an effective way to achieve sustainable development in the transportation sector. To explore the pathways to energy transitions in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) transportation sector, the article evaluated the potential of energy savings and CO2 emission reduction of different measures in a quantitative way, based on the long-range energy alternatives planning (LEAP) platform. The marginal abatement cost curves are used to visually reflect the cost–benefit of these measures, and to develop cost-effective pathways to energy transitions. The results show that the measures of transportation modes adjustment and private cars regulating should be prioritized due to the potential of significant emission reduction with good cost-effectiveness. The measures of promoting electricity and hydrogen energy have large emission reduction potential, but only those for road traffic are cost-effective, and should be treated with a lower priority. Considering the high cost, the measures of promoting biofuel should be implemented as least priority. Moreover, the measures of liquefied natural gas (LNG) application have good cost-effectiveness, as opposed to limited CO2 emission reduction potential. It can only be used as a transitional fuel for the energy transitions. The findings and research methodology will provide theoretical support for the formulation of transportation energy transition pathways in the GBA and other regions.

Carbon footprint and techno-economic analysis to decarbonize the production of linerboard via fuel switching in the lime kiln and boiler: Development of a marginal abatement cost curve

Carbon footprint and techno-economic analysis to decarbonize the production of linerboard via fuel switching in the lime kiln and boiler: Development of a marginal abatement cost curve

Progressing from first-of-a-kind to Nth-of-a-kind: Applying learning rates to carbon capture deployment in Sweden

The deployment of CO2 capture technologies presents opportunities to store fossil fuel emissions from industries and power generation (CCS) and to enable carbon utilization (CCU). However, the costs for early CCS projects are high, and this is a challenge in terms of their economic viability, requiring a strong climate policy with high carbon prices for implementation. This work details a techno-economic assessment of the cost of carbon capture based on a hybrid method and individual project approach, using first-of-a-kind contingency factors and learning rates to study the evolution of carbon capture costs as installed capacity increases over time. The work is based on a case study of 147 Swedish industrial and combined heat and power plants (total of 176 stacks). The results are presented as marginal abatement cost curves, with consideration of early mover CCS projects and learning rates. Deployment scenarios are also presented that take into account an expected increase in the CO2 price. The findings indicate that when accounting for first-of-a-kind contingencies (100 % and 200 % increases in Nth-of-a-kind costs), 90 and 17 projects, respectively, of the total 176 emission sources studied have specific CO2 costs of <300 €/t. However, high learning rates (12 %) can reduce the capture costs from first-of-a-kind to Nth-of-a-kind levels within some 30 project installations (100 % contingency). With lower learning rates (3 %), the first-of-a-kind costs are reduced by 10 %–20 %. With the expected increase in CO2 prices, a peak in carbon capture deployment is observed around Year 2035, at a carbon price of 200 €/t.

Building retrofit optimization considering future climate and decision-making under various mindsets

Building retrofit is effective in reducing building energy use and improving comfort levels for existing buildings. However, conducting multi-objective optimization for individual buildings can be challenging due to the laborious computational cost of using white box models and the difficulty in visualizing and understanding the decision-making process. Additionally, the impact of climate change has not been fully considered for the post-retrofit lifecycle. This research proposes a pragmatic automated scheme that integrates a feature selection method based on marginal abatement cost analysis and variance-based sensitivity analysis, multi-objective optimization supported by non-dominated sorting differential evolution (NSDE) algorithm, tailor-made decision-making support under different mindsets, and tree-based retrospection scheme of decision-making pathways. The simulation engine used in this study is a low-order white box modeling tool developed by the research team. The proposed scheme was applied to two educational buildings with different thermal characteristics, and the results showed that a certain number of sampling sizes were needed to achieve reliable feature selection results. The hierarchical clustering based decision-making support scheme has demonstrated robustness in visualizing and supporting decision-making for Pareto front. Two retrofit mindsets - aggressive and balanced - were assumed in the decision-making process, and the proposed method produced distinct final solutions accoridng to the two mindsets. This framework can support informed decision-making, helping stakeholders implement sustainable practices and transition to a low-carbon built environment.

OPTIMAL CLIMATE POLICY WITH NEGATIVE EMISSIONS

We can limit the future temperature impact of climate change in two ways: (i) reducing our use of CO2 emitting fuels as an energy source (abatement), and (ii) using negative emission technologies (NETs) to remove existing CO2 from the atmosphere (removal). Using a modification of the DICE model, we analyze the optimal use of these two policy responses to climate change. After calibrating the marginal costs of abatement and CO2 removal to the latest scientific information, we find that carbon removal must play a very large role in an optimal policy. If this policy is followed, we find that the Paris-Agreement 1.5–2[Formula: see text]C warming by 2100 target is not just aspirational, but optimal. When an important role is played by NETs to control global warming, the decrease in carbon emissions can be more gradual, reducing transition risk and social dislocations. We examine the impact on the economy of large-scale carbon removal programs, the potential for moral hazard and the logistical problems associated with the storage of the removed carbon.

Towards a low-carbon and beautiful world: assessing the impact of digital technology on the common benefits of pollution reduction and carbon reduction.

When ecology thrives, civilization thrives, and when ecology declines, civilization declines. Based on panel data from 30 provinces in China from 2000 to 2021, this study used marginal abatement costs to estimate the co-benefits of pollution reduction and carbon reduction. Two-way fixed effect and two-stage intermediary effect models were used to evaluate the impact of digital technology on co-benefits and its indirect channels. The results indicated that China's total carbon emissions maintained a steady growth trend, while air pollution showed a fluctuating declining trend. Reaching peak carbon neutrality calls for more innovative solutions. Under joint emission reduction efforts, the study revealed marginal abatement cost savings of 535.8 million yuan/million tons and 6216.5 million yuan/μg/m3 for carbon reduction and pollution reduction, respectively. Most importantly, the study confirmed that joint emission reduction programs can reduce environmental governance costs more than individual emission reductions can, and the co-benefits increased from 37.983 to 44.757. The co-benefits generally showed a trend of fluctuation and increases and had the characteristics of phased transformation. Intragroup differences and cross-overlapping between regions made regional differences in co-benefits obvious. The subversive, permeable, and integrated features of digital technology have resulted in the all-around transformation of the economy and society, and the new technology-economy paradigm has significantly improved co-benefits. The conclusion remains valid after robustness testing and controlling for endogeneity problems. The results of the mechanism analysis suggest that digital technology can indirectly improve synergies through the intermediary channels of fostering green technology innovation, reducing energy consumption intensity and improving the energy structure.

Granular satellite data to assess the potential for nature based solutions at a national scale: a proof of concept with data from Rwanda and Lesotho

ABSTRACT Nature-based Solutions (NbS) form a substantial part of cost-efficient climate change mitigation options. However, public financial flows towards NbS have been limited. Among the factors impeding investments in NbS are challenges in reliable remote project identification and comparison. In this article, we demonstrate a technological solution to these challenges. Using cloud-based satellite data processing and the proliferation of open geospatial data, we developed a methodology to map NbS suitability based on a set of biophysical, pedological, hydrological and climatological criteria. To provide a proof of concept, we identify potential project areas for eight types of NbS in Rwanda and Lesotho. Building on these spatially-explicit NbS suitability data layers (accessible at https://williamouellette.users.earthengine.app/view/ncs-potential), we develop marginal abatement cost curves for projects in Rwanda and Lesotho. We thus provide a proof of concept for remote identification and project comparison. These technological developments can help investors, such as multilateral donors or governments, alleviate additionality concerns that are implied by local project selection. Key Policy Insights Investment in climate change mitigation through Nature-based Solutions (NbS) is limited, in spite of the large, cost-efficient potential for achieving national and global goals. Remote project identification and comparison can help alleviate some of the impediments to international investment in NbS. Such remote identification and comparison of NbS projects is now possible because of breakthroughs in cloud-based satellite data processing technologies and increased availability of geospatial data. We present a proof of concept, establishing marginal abatement cost curves for climate change mitigation through NbS in Rwanda and Lesotho. Coupled with the institutional improvements necessary to create a reliable intergovernmental carbon credit market, these technological developments have the potential to boost international investment in NbS.

Carbon compensation cost in Jing-Jin-Ji region under the carbon neutrality goal: Considering emission responsibility and carbon abatement cost

This study investigates the carbon compensation mechanism as a tool to promote coordinated economic and environmental development in China's Jing-Jin-Ji region (Beijing, Tianjin, and Hebei). A novel approach for calculating carbon compensation cost that integrate emission responsibility as well as carbon abatement cost through a bi-level programming model is proposed. Shared producer and consumer responsibility is established for carbon emissions under the multi-regional input-output model. Marginal abatement costs of Beijing, Tianjin, and Hebei are further calculated through the input-output and linear programming method. Results highlight that the emission responsibility allocation method significantly affects the inter-regional carbon compensation amount. The production-based approach leads to a 77% reduction of carbon compensation amount from Beijing to Hebei, and a 170% overestimation from Tianjin to Hebei compared with the shared responsibility approach in 2060. The optimal carbon compensation unit cost ranges from 1539 to 6438 yuan/ton when the carbon reduction ratio ranges from 10% to 20%. Beijing would compensate Hebei 3.56 and 29.74 billion yuan for achieving 10% and 20% emission reduction, respectively. Similarly, Tianjin's compensation for Hebei would be 0.23 and 1.87 billion yuan in the two scenarios. Results further show that implementing the proposed carbon compensation mechanism can reduce total abatement cost by 43% and 84% in Jing-Jin-Ji under the two scenarios. The methods and results of this paper could help inform future carbon compensation implementation in China and other countries.

Analysis of the synergistic benefits of typical technologies for pollution reduction and carbon reduction in the iron and steel industry in the Beijing–Tianjin–Hebei region

With its high energy consumption and pollutant emissions, the iron and steel industry is a significant source of air pollution and carbon emissions in the Beijing–Tianjin–Hebei (BTH) region. To improve air quality and reduce greenhouse gas emissions, a series of policies involving ultra-low emission, synergistic reduction of pollution, and carbon application have been implemented in the region. This study has assessed air pollutant and CO2 emission patterns in the iron and steel industry of the region by employing co-control effects coordinate system, marginal abatement cost curve, and numerical modeling, along with the synergistic benefits of typical technologies. The results have demonstrated that: (1) the intensive production activities pertinent to iron and steel enterprises has contributed greatly to the emission in Tangshan and Handan, where the sintering process is the main source of SO2, NOx, PM2.5, and CO, accounting for 64.86%, 55.15%, 29.98%, and 46.43% of the total emissions, respectively. (2) Among the typical pollution control and reduction measures, industrial restructuring and adjustment of the energy-resource structure have led to the greatest effects on emission reduction. Technologies exhibiting great potential in emission reduction and high-cost efficiency such as Blast Furnace Top Gas Recovery Turbine Unit (TRT) need to be promoted. (3) In Tangshan city with the highest level of steel production, the iron and steel production activities contributed to the concentration of 30.51% of PM2.5, 50.67% of SO2, and 42.54% of NO2 during the non-heating period. During the heating period, pollutants pertinent to the combustion of fossil energy for heating have increased, while iron and steel induced emissions have decreased to 23.7%, 34.32%, and 29.13%, respectively. By 2030, it is speculated that the contribution of the iron and steel industry to air quality will be significantly decreased as result of successful implementation of ultra-low emission policies and typical synergistic reduction technologies.

Could the EU carbon border adjustment mechanism promote climate mitigation? An economy-wide analysis

Due to concerns about carbon leakage and sectoral competitiveness, the European Union (EU) proposed implementing the carbon border adjustment mechanism (CBAM). The effectiveness and potential negative consequences of CBAM have aroused extensive discussion. From the perspective of the economy-wide analysis, this study uses a global computable general equilibrium model to explore the rationality of CBAM from the aspects of socioeconomic impact and the effects of promoting climate mitigation. Furthermore, the potential alternative mechanism of CBAM is proposed. The results show that CBAM can reduce the EU's gross domestic product (GDP) loss; however, the GDP loss in all other regions increases. Moreover, CBAM raises household welfare losses in most regions, including the EU. Second, although CBAM can reduce the marginal abatement cost in eight regions, it comes at the cost of greater economic losses. Furthermore, the economic and household welfare cost of raising emissions reduction targets in regions like the USA and Japan is substantially higher than the impact of passively accepting the CBAM; therefore, CBAM's ability to drive ambitious emission reduction initiatives may be limited. Finally, for the potential alternative mechanism, from the perspective of reducing economic cost and household welfare losses, the EU could implement domestic tax cuts in the short-term and promote global unified carbon pricing in the long-term.

Life of field emission forecast development and reduction option screening for a multi-train LNG hub

The Karratha Gas Plant (KGP) is a complex integrated facility which produces liquified natural gas (LNG), domestic gas (Domgas), condensate, propane and butane products. The multi-train facility has been operating for 40 years with several phases of expansion resulting in a range of gas turbine technology and energy efficiency levels across the facility. The challenge for the next phase of KGP operation is to manage declining North West Shelf (NWS) feed gas levels, and the addition of Other Resource Owners feed gas while reducing emissions and maintaining energy efficiency. A flexible emissions forecasting tool has been developed which allows unit and whole of facility emissions reduction and energy efficiency options to be assessed. The tool builds on current quarterly timestep production forecasts and models ambient temperature, unit turndown and turn-off strategies, and potential implementation of lower emissions technology. The ability to generate and compare life of field emissions profiles for extrapolated operating modes and proposed modifications allows unit strategies and phasing of emissions reduction modifications to be investigated and screened before further economic assessment and creation of marginal abatement cost curves (MACC).

Least-cost decarbonization pathways for electricity generation in Finland: A convex quantile regression approach

This study investigates the least-cost decarbonization pathways in the Finnish electricity generation industry in order to achieve the national carbon neutrality goal by 2035. Various abatement measures, such as downscaling production, capital investment, and increasing labor and intermediate inputs, are considered. The marginal abatement costs (MACs) of greenhouse gas emissions are estimated using the convex quantile regression method and applied to unique register-based firm-level greenhouse gas emission data merged with financial statement data. We adjust the MAC estimates for the sample selection bias caused by zero-emission firms by applying the two-stage Heckman correction. Our empirical findings reveal that the median MAC ranges from 0.1 to 3.5 euros per tonne of CO2 equivalent. The projected economic cost of a 90% reduction in emissions is 62 million euros, while the estimated cost of achieving zero emissions is 83 million euros.

Climate mitigation potential and economic costs of natural climate solutions for main cropping systems across China

CONTEXTNatural climate solutions (NCS) offer immediate and cost-effective ways to tackle the climate crisis by transforming atmospheric carbon to soil carbon or avoiding greenhouse gas emissions. However, the climate mitigation potential and economic costs of NCS for cropping systems in China remain inconclusive. OBJECTIVEThe major objectives of this study are (i) to estimate the NGHG reduction potential across Chinese main cropping systems caused by NCS, (ii) to quantify the economic costs of adopting optimal management with different abatement potentials. METHODSThe Denitrification-Decomposition (DNDC) model was used to estimate the NGHG, including SOC sequestration, N2O emissions, and CH4 emissions. After calibration, we ran the DNDC model with derived data at municipality-level. We estimated the NGHG under current management, adopting optimal management individually, and integrated optimal management to project the maximum NGHG reduction potential caused by NCS. We used the marginal abatement cost method to estimate the economic cost. RESULTS AND CONCLUSIONSThe four natural climate solutions, N fertilization management (NFM), straw returning management (SRM), tillage management (TM), and rice irrigation management (RIM) can reduce national NGHG in main cropping systems by approximately 118.8 Tg CO2-eq, 116.3 Tg CO2-eq, 35.2 Tg CO2-eq, and 74.4 Tg CO2-eq, respectively. The integrated optimal management may potentially reduce NGHG by 256.9 Tg CO2-eq, equivalent to 90.2% of current NGHG, and 80% of which can be realized at the price of CN¥ 285 (Mg CO2-eq)−1. We further identify the priority NCS for different crops and regions and conclude that nitrogen fertilization management should be the priority NCS at the national level. SIGNIFICANCEOur findings highlight the great potential of NGHG reduction by adopting NCS precisely and the importance of optimizing agricultural management as a whole, and they will help policy makers to develop smart-agriculture in China.

Study on Cost-Effective Performance of Alternative Fuels and Energy Efficiency Measures for Shipping Decarbonization

Within the context of global initiatives to address climate change, the shipping industry is facing increasingly intensified pressure to decarbonize. The industry is engaging in the exploration and implementation of greenhouse gas (GHG) emission reduction measures, including energy efficiency technologies and alternative fuels, with the objective of accelerating the progression towards greenhouse gas mitigation. The application of various GHG emission reduction measures usually requires different levels of investment costs, and economic feasibility is a key factor influencing policy formulation and investment decisions. In this regard, this paper developed a cost-effective model for energy efficiency measures and alternative fuels based on the marginal abatement cost (MAC) methodology. This model can distinguish the differences between energy efficiency measures and alternative fuels in terms of Tank-to-Wake emissions and Well-to-Wake emissions in the GHG emission evaluation system. By taking typical ship types with significant emission contributions as study cases, i.e., bulk carriers (61–63K DWT), container ships (8000 TEU), product tankers (115K DWT), crude oil tankers (315–320K DWT), and Ro-Ro passenger ferries (3500 DWT), the GHG abatement cost-effective performance of major categories of measures such as operational measures, technical measures, renewable energy sources, and alternative fuels were calculated. According to the MAC results, the marginal abatement cost curves were plotted based on the ranking of energy efficiency measures and alternative fuels, respectively. The impacts of bunker fuel prices and carbon market prices on the cost-effectiveness were analyzed. The research results provided the GHG abatement potential of the integrated application of cost-effective energy efficiency measures, the cost-effectiveness ranking of alternative fuels, and the carbon emission price expected to bridge the price gap between alternative fuels and conventional bunker fuel. The presented methodology and conclusions can be used to assist shipping companies in selecting emission reduction measures, and to support maritime authorities in developing market-based measures.

Marginal abatement cost of CO2: A convex quantile non-radial directional distance function regression method considering noise and inefficiency

By purchasing emission reduction equipment or reducing production scale, it is possible to effectively decrease CO2. Therefore, understanding the marginal abatement cost (MAC) associated with these methods is crucial for making decisions. However, previous studies using the directional distance function (DDF) approach often mis-specified production functions and neglected data noise. They also assumed decision-making units (DMUs) to be on the production frontier and used proportional changes in inputs and outputs as abatement paths. This paper addresses these limitations by developing the convex quantile non-radial directional distance function (CQR-NDDF) method, which estimates the MAC of CO2 and determines optimal abatement paths for DMUs without assuming a specific production function, employing linear programming techniques. Applying this method to 30 provinces in mainland China from 2011 to 2019, the study finds that China's CO2 MAC increased from 182 to 247 yuan/ton. The lowest-cost abatement path varies by province and time. The club convergence and ordered probit model are employed to conclude that the second industry and urbanization increase the MAC of CO2, while factors such as foreign direct investment, openness level, and human capital decrease the MAC. Moreover, the CQR-NDDF method yields significantly lower MAC estimates than the NDDF method. In conclusion, this paper provides new insights into China's CO2 MAC, emphasizing the importance of considering inefficiency and data noise in MAC estimation. We anticipate that utilizing CO2 MAC as a benchmark for carbon trading market prices could lead to an increase in prices within China's carbon trading market.

Co-benefits and influencing factors exploration of air pollution and carbon reduction in China: Based on marginal abatement costs

This study addresses the pressing need for cost-effective emission reduction strategies that maximize co-benefits in terms of air pollution and carbon emissions. Our research contributes to the literature by accurately measuring these co-benefits, thereby facilitating their prompt realization in different regions. We employ an input-output framework that integrates carbon emissions and air pollution, allowing us to calculate marginal abatement costs using the shadow price of undesired output. Through this approach, we quantify the co-benefits and analyze the factors influencing them at both spatiotemporal and factor levels using spatial kernel density and geographical detectors. Our findings reveal several key insights: (1) under joint emission reduction efforts, we observe average annual reduction rates of 6.46% for marginal pollution and 6.10% for carbon reduction costs. Importantly, we document an increase in co-benefits from 0.50 to 0.86, characterized by an initial fluctuation followed by a linear increase. (2) the marginal cost difference for carbon emission and pollution reduction in western China was 179.45 and 155.08 respectively, compared to 321.51 and 124.70 in the Northeast, highlighting the crucial role of regional differences in shaping co-benefit outcomes. (3) we identify a negative spatial spillover effect between provinces, which diminishes over time, leading to heterogeneous effects when local provincial co-benefits exceed a threshold of 0.9. (4) during the adjustment period, we find that the industrial structure exerts significant single and interactive effects on co-benefits. Additionally, we highlight the critical role of environmental governance investment and government intervention as drivers of co-benefits in the current era. By offering the quantification of co-benefits under the marginal abatement costs, our study provides valuable scientific insights for planning and implementing effective synergy strategies.