Multi-Dimensional Analysis of Carbon Dioxide Sequestration Technologies in China in the Context of Carbon Neutrality: Current Status, Development Potential, and Costs

Abstract

With increasing global climate change, carbon neutrality has emerged as a common goal among the international community. In this study, we assessed the current status, development potential, and cost of carbon sequestration technology, proposing recommendations for strategic development. We adopted a comprehensive multi-method research strategy, including systematic literature analysis, case studies, and Bayesian fuzzy assessment, to analyze 13 large-scale carbon capture, utilization, and storage demonstration projects in China that include carbon sequestration segments. In addition, we conducted a comprehensive assessment of seven major carbon sequestration technologies. Hydrate-based carbon sequestration technology showed the highest overall carbon sequestration potential among the technologies. Although still in the initial research stage, this technology has significant sequestration and utilization potential, positioning it as a key focus for future development. Accordingly, we recommend increasing R&D investments to accelerate technology maturation. In terms of cost optimization, we highlight the need to focus on site costs, as well as injection and production, and to reduce related costs through technological innovation. Additionally, we explore the conceptual meaning of carbon sequestration and clarify the involved pathways. This study provides valuable insights for policymakers and investors seeking to promote the development of carbon sequestration technology in China.

1. Introduction

As the global climate continues to warm, countries around the world have endeavored to control greenhouse gas carbon dioxide (CO₂) emissions, with more than 130 countries committing to efforts toward carbon neutrality [1]. In 2016, China became a signatory to the Paris Agreement, which aims to limit the global average temperature increase from pre-industrial levels to 2 °C and strives to cap the temperature increase at 1.5 °C [2]. Subsequently, China pledged to achieve peak carbon emissions by 2030 at the 75th United Nations General Assembly. According to the China Carbon Accounting Database, domestic carbon emissions continued to increase from 1997 to 2021 [3,4,5].

According to the current status of CO₂ emissions from major industries in China (Figure 1), achieving carbon neutrality requires the construction of a three-pronged co-operative system.

The first component targets the power production sector, which involves changing the energy structure from coal-based to renewable and non-carbon energy sources. The second component targets energy consumption and the implementation of green energy solutions in high-emission areas. In the power production sector, with the development of clean energy and continuous improvements to power generation efficiency in China, there has been a consistent decrease in the carbon intensity of the annual power generation. In 2000, the carbon intensity was 864.5 g/(kW·h), which decreased to 556.8 g/(kW·h) in 2021, representing a decrease of 35.6% and an average annual decrease of 2.1%. Future adjustments to the power source structure and improvements to efficiency will promote a continuous decline in carbon intensity, thus realizing carbon peaking in the power industry. According to preliminary calculations from the National Bureau of Statistics, the total energy consumption in China reached 5.41 billion tons of standard coal in 2022, reflecting a 2.9% increase compared to the previous year. The consumption of coal accounted for 56.2% of the total energy consumption, but this figure only increased by 0.2% compared with the previous year. Regarding the proportion of non-fossil energy consumption, the consumption proportion of clean energy, such as natural gas, hydropower, nuclear power, wind power, and solar power, has increased to 25.9%, an increase of 0.4% compared with the previous year. Despite significant progress on these two fronts, carbon will continue to be the primary component in power generation and energy consumption. Therefore, the third sector targets carbon fixation, which has led to the development of carbon capture, utilization, and storage (CCUS) technologies. CCUS involves capturing CO₂, which can then be processed into industrial products or sequestered underground (Figure 2). CCUS is regarded as the cornerstone of carbon neutrality targets, with the International Energy Agency describing it as “a bridge between current and future energy systems” [6]. Thus, CCUS represents a key technological pathway for the global transition to a carbon-neutral future.

Carbon capture research has made significant breakthroughs regarding capture pathways [7,8,9], basic principles [10,11,12,13], energy consumption assessments, and cost–benefit analyses [14,15,16,17]. Furthermore, studies are actively exploring possible future capture technologies that can achieve further breakthroughs in efficiency, cost, and environmental friendliness [18,19,20]. There has been recent significant progress in CO₂ utilization technology, with a focus on geological [21], chemical [22], and biological [23], utilization, as well as the integration of CO₂ utilization and capture technologies for optimizing the efficiency of the entire CCUS system [24,25,26]. Moreover, Hepburn et al. [27] proposed a more detailed classification of CO₂ utilization pathways into ten different pathways, clarifying the scale of each pathway and predicting the cost of small- and large-scale CO₂ utilization by 2050. Researchers have also focused on source–sink matching methods using mixed integer linear programming [28,29,30,31] and CCUS full-process supply chain optimization [32,33,34]. These methods optimize the transportation costs of CO₂ utilization and storage, as well as provide important support for the economic feasibility of the entire CCUS system, which is crucial for promoting the large-scale commercialization of CCUS technology.

Despite abundant research on the principles of carbon sequestration and geological exploration methods [35,36,37,38], comprehensive assessments of CO₂ sequestration technologies are lacking. CCUS projects entail substantial expenses and have a prolonged payback period, such that most companies opt not to retrofit CCUS units and instead rely on government funding and subsidies to maintain operations. Currently, the CCUS regulatory framework in China is not comprehensive; this lack of policy support has impeded the development of CCUS projects in China. Therefore, the aim of this study was to determine the current status, development potential, and costs of different CO₂ storage technologies in China against the background of carbon neutrality. The results of this study can assist enterprises and governments in avoiding blind, uninformed investments in various candidate technologies without adequate research. As one of the most comprehensive studies to date, our research provides policymakers and investors with reliable scientific support for the commercialization and expansion of carbon sequestration technologies.

2. Materials and Methods

2.1. Data Sources and Acquisition Methods

To ensure the systematicity and reliability of data sources, this study adopted a combined strategy that integrated a systematic literature review, web crawler technology, and manual verification during the data collection stage. A rigorous data validation protocol was established to ensure the consistency, transparency, and reproducibility of the data used.

A systematic literature review was conducted to extract key parameters related to carbon sequestration technologies, including technology maturity levels, cost structures, and sequestration capacities, which served as the foundation for subsequent model development and technology classification. Literature was retrieved from multiple databases, including CNKI, Web of Science, and Elsevier, covering both Chinese and English sources within the time span from 2010 to 2024. The search strategy was built around keywords, such as “carbon sequestration”, “CCUS projects”, “sequestration scale”, and “technology maturity”.

Inclusion criteria were: (1) the study explicitly focused on carbon sequestration or CCUS technology pathways; (2) it contained quantitative information on technology readiness level (TRL), cost structures, or sequestration potential; and (3) the full text was accessible. Exclusion criteria included: (1) duplicate publications or conference abstracts; (2) review or commentary articles unrelated to the research focus; and (3) policy discussions lacking empirical data support.

Additionally, web crawler technology was employed to structurally extract data from various authoritative sources. These sources were categorized into three tiers:

Category A: Websites of scientific and governmental institutions, such as the Administrative Center for China’s Agenda 21, the Chinese Academy of Sciences, the National Energy Administration, and the Institute of Climate Change and Sustainable Development at Tsinghua University, which were crawled through three times per week.

Category B: Official websites of CCUS project-operating enterprises, such as PetroChina, CNOOC, and Qilu Petrochemical, which were crawled through once per day.

Category C: Information portals and government websites, such as Zhihu, the Ministry of Natural Resources, and provincial-level resource departments, which were crawled through every 2–3 h due to their high update frequency.

We implemented the following data validation protocol:

(1). Source classification and credibility ranking: Data sources were categorized into A (government/research institutions), B (enterprise websites), and C (social or informational platforms). Data from categories A and B were directly included while category C data were subject to manual cross-verification.

(2). Redundancy checks and cross-validation: For identical parameters or events reported by different sources, we performed multi-source comparisons and adopted values with the highest frequency of occurrence or those most consistent with the academic literature. Outliers with deviations greater than 15% were excluded, and associated uncertainties were recorded.

Furthermore, for data that were not directly reported in previous studies, estimation models were constructed based on published parameters; missing values were completed through calculated inference.

2.2. Calculation of CO₂ Sequestration Potential

This section describes the methods used to calculate the CO₂ sequestration potential of seven major CO₂ sequestration technologies applied in China.

(1). CO₂ sequestration combined with deep-saline water/brine recovery (CO₂-EWR) uses injected supercritical CO₂ to displace brine from deep-saline aquifers, which enables long-term large-scale CO₂ sequestration [39]. The sequestration potential of CO₂-EWR was calculated using the Design of Experiments (DOE) method proposed by Lu-Sheng et al. [40].

(2). CO₂-enhanced oil recovery (CO₂-EOR) technology increases well production by injecting CO₂ into the reservoir to reduce the viscosity of crude oil and improve its fluidity while simultaneously achieving long-term CO₂ sequestration [41]. The sequestration potential of CO₂-EOR was calculated by Fan et al. [42] based on crude oil resources, sequestration efficiency, and the formation volume factor.

(3). CO₂-enhanced gas recovery (CO₂-EGR) involves CO₂ injection into natural gas reservoirs, which displaces otherwise difficult-to-recover natural gas, improving the overall recovery rate of the gas field, as well as achieving long-term stable carbon sequestration by exploiting the higher density and solubility of CO₂ in a high-pressure subsurface environment [43]. The sequestration potential of CO₂-EGR was obtained from Zhang et al. [44].

(4). CO₂-enhanced coalbed methane recovery (CO₂-ECBM) technology involves sequestering CO₂ in unmineable coal seams while increasing the recovery rate of coalbed methane. This method achieves long-term, large-scale carbon sequestration, as well as improves the efficiency of coalbed methane recovery by avoiding excessive reduction of reservoir pressure during mining [45]. The sequestration potential of CO₂-ECBM was obtained from Yan-Feng et al. [46] based on the gas content method.

(5). CO₂-enhanced shale gas recovery technology (CO₂-ESGR) refers to the use of supercritical CO₂ for fracturing while simultaneously improving shale gas recovery and CO₂ geological storage [47]. The potential for CO₂ sequestration using CO₂-ESGR was calculated as follows:

(1)$K_{{CO}_2-ESGR}=S_g\times P\times R$

where $K_{{CO}_2-ESGR}$ is the CO₂-ESGR sequestration potential, $S_g$ is the shale gas reserves in China (approximately 130 billion m³ [48]), $P$ is the ratio of extracted shale gas to sequestered CO₂ (approximately 2:1), and $R$ is the shale gas recovery rate (typically 10–30% [49]). A recovery rate of 20% was used in this study.

(6). In situ leaching of uranium technology utilizes a mixture of CO₂ and oxygen as leaching agents to achieve the dual objectives of uranium resource extraction and CO₂ sequestration. This technology injects CO₂ and oxygen into uranium-bearing sandstone deposits through surface drilling, which induces a chemical reaction between CO₂ and uranium in the ore and forms soluble uranium compounds. These compounds are then pumped to the surface for processing, ultimately yielding a uranium product [50]. During uranium extraction by ground leaching, 1 mol of uranium reacts with 3 moles of CO₂ to form a soluble uranium–carbonate complex [51]. To ensure that the reaction proceeds adequately and that CO₂ sequestration is effective, an additional 10–50% of CO₂ is typically added in industrial applications (30% was used in this study). The potential for CO₂ sequestration using in situ leaching of uranium was calculated as follows:

(2)$K_U=M_U\times 3\times M_{{CO}_2}\times R_O\times S_U{,K}_{{CO}_2-ESGR}=S_g\times P\times R$

where $K_U$ is the CO₂ sequestration potential of in situ leaching of uranium in China, $M_U$ is the molar mass of uranium (238 g/mol), $M_{{CO}_2}$ is the molar mass of CO₂ (44 g/mol), $R_O$ is the proportion of excess CO₂, and $S_U$ is the total amount of uranium ore resources in China, which is approximately 2.8 million tons [52].

(7). Hydrate-based CO₂ storage technology involves the injection of CO₂ into a natural gas hydrate accumulation layer, displacing methane while achieving geological sequestration of CO₂ [53]. The methane content of combustible ice ranges from 80 to 99%. In this study, 90% was used as the representative value for calculation. Theoretically, in the process of replacing methane with CO₂, 1 mol of CO₂ can replace 1 mol of methane. The potential for CO₂ sequestration using hydrate-based technology was calculated as follows:

(3)$K_H=S_H\times {\rho }_H\times Q\times (M_{{CO}_2}/M_{{CH}_4})\times D$

where $K_H$ is the CO₂ sequestration potential of hydrate-based technology, $S_H$ is the total cumulative reserves of combustible ice (84 trillion m³ [54]), ${\rho }_H$ is the density of combustible ice (0.9 t/m³), $Q$ is the methane content of combustible ice, $M_{{CH}_4}$ is the molar mass of methane (16.04 g/mol), and $D$ is the average efficiency of methane replacement (approximately 50%, [54]).

(8). Deep-sea injection involves the direct injection of liquid CO₂ into the oceans, usually at depths below 1000 m. In this high-pressure environment, CO₂ can form stable hydrates or dissolve in seawater, leading to long-term sequestration [55]. Assessing the potential for the deep-sea injection of CO₂ faces unique challenges, stemming primarily from the dynamic nature of the marine environment. The presence of tides and currents makes it difficult for injected CO₂ to remain stationary in a given region, posing a significant obstacle to accurately quantifying localized sequestration. In view of this mobility, ocean CO₂ sequestration should be based on a global-scale approach [56]. In a special Carbon Dioxide Capture and Sequestration Report (2005), the Intergovernmental Panel on Climate Change noted that the global ocean could theoretically absorb trillions of tons of anthropogenic CO₂. However, Caldeira et al. [57] suggested that the actual feasible amount of sequestration is significantly lower than the theoretical value, limited mainly by environmental impacts and technological feasibility. Thus, despite the significant theoretical potential of deep-sea injection technology, China remains in the basic research stage.

2.3. Assessing the Current Status of Carbon Sequestration Technologies

We evaluated the technological maturity of CO₂ storage technologies based on the technology maturity level (TRL) proposed by NASA. In this study, we combined the nine levels of the TRL table according to the technology maturity level, with reference to the delineation of carbon capture technology stages [58]. As listed in Table 1, Level 1 corresponds to the conceptual design stage, levels 2 and 3 refer to the basic research stage, levels 4–6 correspond to the mid-term experimental stage, levels 7 and 8 are the engineering demonstration stage, and level 9 refers to the commercial application stage.

Conceptual stage: The technology is still at the theoretical conception stage, which mainly includes proposing innovative ideas, conducting feasibility analyses, and performing preliminary theoretical research. However, substantial experimental verification has not yet been conducted.

Basic research stage: Small-scale laboratory research is initiated to verify the feasibility of the technical principles. This phase focuses on solving basic scientific problems; thus, the technology is not yet considered for practical application.

Intermediate experimental stage: Large-scale experiments are conducted in laboratories or small-scale test sites to address key issues in the implementation of the technology. The practical application potential of this technology has recently been considered.

Industrial demonstration stage: Large-scale tests are conducted under conditions close to the actual application environment to verify the feasibility of large-scale industrialization of the technology. This stage focuses on the stability, reliability, and economy of the technology.

Commercial application: The technology is sufficiently mature for large-scale applications. This stage focuses on marketing, cost optimization, and continuous improvement of the technology.

In this study, an assessment framework that combines Bayesian fuzzy evaluation and Monte Carlo simulation was used to systematically assess the maturity stage of different carbon storage technologies. This method can effectively integrate heterogeneous information from multiple sources and provide more robust and credible assessment results in the face of data subjectivity and uncertainty. The assessment process includes the following four key steps:

Step 1 defines the prior probability. The technology maturity level in this study was divided into five stages ($D_{\alpha }, \alpha =1,2,\dots ,5$). Based on the lack of sufficient historical or empirical data to specify the prior distributions for each TRL class, this study followed the principle of maximum uncertainty and used an equal probability distribution as the initial prior setting:

(4)$P\left(D_{\alpha }\right)={\displaystyle \frac{1}{5}},\alpha =1,2,\dots ,5$

Step 2 Characteristic variable definition and fuzzy likelihood function modeling. Based on the aforementioned judgment factors, seven key features were defined: research scale ($F_1$), technological maturity ($F_2$), economic feasibility ($F_3$), number of patents and literature ($F_4$), degree of industry application ($F_5$), degree of technological standardization ($F_6$), and scale of investment ($F_7$). In terms of environmental impacts, carbon sequestration technologies have diverse pathways: different technologies have varying degrees of impact on the same environmental impact indicator. Public acceptance is subjective and dynamic, such that it was not considered in the selection of characteristics. For each feature, $F_{\beta }$, we defined the likelihood function, $P\left(F_{\beta }\right|\left(D_{\alpha }\right))$, which denotes the probability of observing the feature, $F_{\beta }$, under the conditions of a given technology stage ($D_{\alpha }$). We modelled the conditional probability of each feature at each TRL as a five-level triangular fuzzy number (see Table 2).

The calculation of the likelihood function was as follows:

(5)$\mathsf{\Gamma }\left(D_{\alpha }\right)={\prod }_{\beta =1}^{7}P\left(F_{\beta }|D_{\alpha }\right),\alpha =1,2,\dots ,5.$

Step 3 Monte Carlo Sampling with Bayesian Inference. To effectively quantify the uncertainty propagation effect of fuzzy conditional probabilities, this study introduced Monte Carlo simulation methods to numerically approximate and statistically analyze the fuzzy inputs in the Bayesian evaluation process. Through large-scale random sampling and iterative computation, the fuzzy uncertainty originally generated by expert assignment can be systematically transformed into statistical intervals of a posteriori probability distributions, which improves the stability and explanatory ability of the model. Specifically, for the conditional probability of each characteristic variable under a given technological stage, $P\left(F_{\beta }\right|\left(D_{\alpha }\right))$, we set it according to the fuzzy linguistic level it belongs to as the corresponding triangular fuzzy number. Subsequently, in each round of simulation, a set of specific conditional probability values $\{p_1,p_2,\dots ,p_7\}$ were obtained by randomly sampling from the fuzzy distributions of all the feature variables and substituting them into Bayes’ formula to compute the posterior probability of each technological stage, as follows:

(6)$P\left(D_{\alpha }|F_1,F_2,\dots ,F_7\right)\propto P\left(D_{\alpha }\right)\times \mathsf{\Gamma }\left(D_{\alpha }\right),\alpha =1,2,\dots ,5.$

We set the number of simulations to 10,000 to ensure the stability and statistical significance of the sample distribution. Each round of simulation output a complete posterior probability distribution result. After accumulating all the simulation rounds, we obtained the mean value of the posterior probability of each technology stage.

Step 4 TRL Determination. The rank with the largest a posteriori probability mean was ultimately chosen as the TRL determination for this technique:

(7)$D^{\mathrm{*}}={argmax}_{\alpha }=P\left(D_{\alpha }|F_1,F_2,\dots ,F_7\right)$

2.4. Prioritizing the Development Potential of Carbon Sequestration Technologies

In this study, we present a quantitative evaluation method for analyzing and prioritizing the development potential of various carbon sequestration technologies in China. The methodology integrates three key factors: carbon sequestration scale, technology status, and utilization.

2.4.1. Carbon Sequestration Scale (S)

Scoring was based on the sequestration potential range and the scoring criteria were as follows: 10⁹–10¹⁰ tons = 1–2 points; 10¹⁰–10¹¹ tons = 3–4 points; 10¹¹–10¹² tons = 5–6 points; 10¹²–10¹³ tons = 7–8 points; 10¹³ tons or more = 9 points; and 10¹³ tons or more plus the largest sequestration scale = 10 points. If the sequestration scale was in the lower half of the interval, a lower value was considered; otherwise, a higher value was considered. As the sequestration scale could not be predicted for deep-sea injection technology in Chinese jurisdictions, a median value of five points was assigned for this technology.

2.4.2. Technology Status (T)

Scoring was based on the stage of technology development: conceptual stage = 2 points; basic research stage = 4 points; intermediate experimental stage = 6 points; industrial demonstration stage = 8 points; and commercial application stage = 10 points.

2.4.3. Utilization (U)

Scoring was based on energy use and CO₂ emissions under the same energy release conditions. The higher the emissions, the lower the score. Technologies with no or low utilization scored 1 point, whereas clean energy with no emissions scored 10 points. After scoring according to the above rules, the weights of the indicators were calculated using the entropy weighting method using the following steps.

Step 1 Data normalization. The raw datasets were standardized to compress the values of the indicators within the [0–1] interval to facilitate subsequent calculations. We performed data normalization, where $x_{kl}$ is the raw data, $y_{kl}$ is the normalized data, and $k=1,2,\dots ,n$, $l=1,2,\dots m$, which denotes the kth sample of evaluation index l, as follows:

(8)$y_{kl}={\displaystyle \frac{x_{kl}-min{x}_{kl}}{max{x}_{kl}-min{x}_{kl}+0.0001}}$

Step 2 Calculate the specific gravity. Calculating the weight of each evaluator’s value under each indicator as a percentage of the sum of the values of all evaluators for that indicator demonstrated the relative importance of each evaluator in relation to the whole for each indicator. We calculated the proportion, $p_{kl}$, of the $l$-th eigenvalue, $y_{kl}$, of the $k$-th sample value to this eigenvalue for all sample data as follows:

(9)$p_{kl}={\displaystyle \frac{y_{kl}}{{\sum }_{k=1}^o{y}_{kl}}}(l=1,2,\dots ,m)$

Step 3 Calculate the information entropy. Quantifying the amount of information carried by each indicator. We calculated the information entropy value, $e_l$, of the $l$-th characteristic value of all samples as follows:

(10)$e_l=-\mathsf{\beta }{\displaystyle \sum _{k=1}^n}{p}_{kl}ln{p}_{kl}$

Step 4 Calculate the information entropy redundancy. The redundancy degree, $g_l$, of the information entropy value of the $l$-th characteristic value was calculated as follows:

(11)$g_l=1-e_l$

Step 5 Calculate the weight of each indicator. This indicates the relative importance of each indicator in the comprehensive evaluation system; ultimately, these weights can be used in conjunction with the raw data of each indicator to calculate the comprehensive evaluation value of each evaluation object. The weight value, $w_l$, of the $l$-th characteristic value was calculated as follows:

(12)$w_l={\displaystyle \frac{g_l}{{\sum }_{l=1}^q{g}_l}}$

Step 6 Calculate the composite score by applying the linear weighting method. The evaluation scores, $B_k$, were calculated for $n$ samples as follows:

(13)$B_k={\displaystyle \sum _{l=1}^q}{w}_l{y}_{kl}$

The entropy weighting method depends on data quality and may be potentially insensitive to subjective priorities. As the method emphasizes variability, it may downplay criteria with less data variability but substantial practical importance.

2.5. Calculating Carbon Sequestration Cost

We comprehensively evaluated the cost ranges of Chinese and international CO₂ sequestration technologies by systematically analyzing relevant literature, multiple data sources, and Internet resources. Considering the inconsistency in the disclosure time of cost data, we adopted an equivalent calculation method to convert all cost data uniformly into the 2024 baseline. We first used the relative purchasing power parity [59] to adjust the exchange rate between the Chinese RMB and the United States dollar in that year, converted the value, and then calculated the baseline value using the inflation rate (Appendix A). This method considers the price-level differences and currency purchasing power changes between countries to provide a more accurate cross-country cost comparison, as follows:

(14)$C_{2024}=C_t\times \left(1+r_t\right)\times \left(1+r_{t+1}\right)\times \dots \times \left(1+r_{2023}\right)$

where $C_{2024}$ denotes the baseline cost in 2024, $C_t$ denotes the cost in year $t$ for which the original cost data are available, $r_i$ denotes the inflation rate in China or the United States in year $i$ ($i$ from year $t$ to 2023), and $t$ denotes the year of the original cost data.

Previous studies have provided relatively few descriptions of the costs of China’s offshore CO₂-EOR and in situ leaching uranium mining technologies, as well as the international offshore CO₂-EGR technology. Therefore, we estimated the cost ranges of these three types of technologies. Bachu [60] showed that the cost of marine sequestration is approximately 2–3-fold the cost of terrestrial sequestration; a median value of 2.5-fold was used in this study to ensure the conservatism and reliability of the estimation. According to the literature [61,62,63,64,65], the injection cost accounts for a considerable proportion of the total cost, approximately 30–60%. In this study, we selected a lower percentage for the calculation to avoid potential overestimation. We also assumed that cost factors in the marine environment other than the injection costs were slightly higher than those in the terrestrial environment, with an increase of approximately 10%. Based on these assumptions and analyses, we concluded that the cost of marine geological sequestration is 1.52-fold the cost of terrestrial geological sequestration.

To calculate the cost of in situ leaching of uranium ($C_u$), we used the cost of uranium mining ($T_u$) mentioned in the Uranium Resources, Production, and Demand 2020 report, jointly published by the International Atomic Energy Agency and the Nuclear Energy Agency of the Organization for Economic Co-operation and Development (the cost of in situ leaching uranium in China is approximately USD 40 per kilogram, whereas the corresponding cost in the United States reaches USD 80 per kilogram), as well as the calculated ratio between the CO₂ sequestration potential of uranium extraction by ground leaching technology and uranium resources ($R_u$), as follows:

(15)$C_u={\displaystyle \frac{T_u}{R_u}}$

In this study, considering the different geological conditions in each region, we adjusted the cost of CCUS technology using the regional economic factor, which is calculated as follows:

(16)$f_{econ,\lambda }^j={\displaystyle \frac{C_{region,\lambda }^j}{C_{avg}^j}}$

where $f_{econ,\lambda }^j$ is the economic factor for the $\lambda \mathrm{t}\mathrm{h}$ region, $C_{region,\lambda }^j$ is the cost of the sequestration project for region $\lambda$, and $C_{avg}^j$ is the average cost of the sequestration project. If $f_{econ,\lambda }^j>1$, the region’s cost is higher than the national average; if $f_{econ,\lambda }^j<1$, the region’s cost is lower than the national average.

We constructed a cost model for carbon sequestration that considers the unique cost components of various sequestration methods, as well as incorporating additional costs arising from potential uncertainties. For ocean sequestration, owing to its specificity, we included the shipping costs for transporting materials at sea as part of the total cost of ocean carbon sequestration. This is because maritime transport is an integral part of the ocean sequestration process. In contrast, land transport costs were not included in the terrestrial sequestration cost calculations. To systematically quantify the costs of various sequestration technologies, we propose the following comprehensive cost model (relevant parameters listed in Table 3):

(17)$C{S}_j=f_{econ,\lambda }^j\times (\sum _{i\in I}\left(C_p^{ij}+C_L^{ij}+C_{man}^{ij}+C_{mon}^{ij}+C_{mar}^{ij}\right)+C_e^j+C_{inj}^j+C_{con}^j+u_j)$

2.6. Research Methodology Integration Framework

The research methodology integration framework proposed in this study systematically demonstrates the logical interconnections and information flow among the diverse methods employed, forming a cohesive and adaptive approach to address the research objectives. As outlined in Figure 3, the framework integrates six distinct yet interdependent components: literature analysis, web crawler technology, synthesized assessment, relative purchasing power parity (RPPP), Bayesian fuzzy evaluation, and TRL. Each component contributes unique analytical perspectives, while collectively creating a robust methodological foundation capable of addressing the complexities inherent in carbon sequestration projects and CCUS technologies.

Literature analysis provides the foundational theoretical basis by synthesizing insights from existing studies, identifying critical knowledge gaps, and framing the scope of subsequent methodological processes. Complementing this, web crawler technology allows for automated data extraction from online sources, ensuring the inclusion of dynamic and updated information on technological advancements. These two processes form the initial inputs for a synthesized assessment, which integrates and evaluates data from multiple sources to prioritize carbon sequestration technologies based on criteria, such as feasibility and potential environmental and economic impacts.

The integration of RPPP introduces critical macroeconomic dimensions into the analysis, incorporating regional economic coefficients and sensitivity analyses to contextualize carbon sequestration projects within broader financial frameworks. Bayesian fuzzy evaluation further enhances decision-making robustness by addressing uncertainties through the use of advanced probabilistic methods, including triangular fuzzy numbers and Monte Carlo simulations, to quantify technology maturity and viability under varying conditions. Technology Readiness Level mapping provides the final evaluative lens, categorizing technologies based on their development stages and identifying those that are ready for deployment versus those requiring further innovation.

The framework operates through interconnected iterative processes, where the output from one component feeds into the next, ensuring methodological synergy and adaptability. Multi-source data and model outputs are aggregated into the comprehensive evaluation module, which integrates various technical assessment results to achieve multi-dimensional comparison and priority ranking based on quantitative analysis. After further optimization through macroeconomic insights and probabilistic evaluation, the technology maturity assessment ultimately identifies technologies that align with strategic priorities.

3. Results and Discussion

3.1. CO₂ Storage Pathways in China

Carbon neutrality is a complex equilibrium process, the central objective of which is to maintain stable CO₂ concentrations in the atmosphere. Achieving this goal requires a balance between CO₂ emission and fixation. Carbon fixation is a key strategy for mitigating the increase in atmospheric CO₂ concentrations that includes two main pathways: natural and artificial [66]. The Earth’s natural carbon fixation processes, such as carbon sequestration in marine and terrestrial ecosystems, are crucial components of the global carbon cycle. These processes are usually not attributed to the emission reduction efforts of a particular country or entity due to their transboundary nature and difficult-to-quantify attributes. However, relying solely on natural carbon sequestration is no longer adequate to stabilize atmospheric CO₂ concentrations [67]. Therefore, we focused primarily on carbon fixation processes achieved through anthropogenic interventions. This distinction is essential for accurately assessing the contribution of human activities to carbon neutrality while also emphasizing the need to protect and enhance the capacity of natural carbon sinks.

Carbon fixation technologies can be categorized into open and closed systems. Although open systems have the potential to fix large amounts of CO₂ [27], they may be converted from carbon sinks to carbon sources in the short term in ecosystems, such as forests, grasslands, and phytoplankton [68]. Conversely, closed systems provide a stable and long-term pathway for CO₂ storage. In Figure 4, circular arrows represent open sequestration pathways, whereas straight arrows represent artificially closed sequestration pathways, such as geological and ocean sequestration. In situ uranium leaching technology uses CO₂ as a leaching agent, which is extracted from the surface together with uranium and then separated; this process entails the conversion of carbon sinks to carbon sources and is therefore categorized as an open system. Technologies, such as CO₂-EWR and deep-sea injection, although theoretically and practically feasible, lack a concomitant process of carbon utilization; therefore, their economic benefits and practical application value need further evaluation. Other technologies utilize CO₂ as a working medium, which achieves energy extraction, as well as permanently sealing CO₂ underground, reflecting the dual benefits of carbon sequestration and energy utilization.

In this study, we defined carbon sequestration technology as a technological approach to achieving the long-term, near-permanent sequestration of CO₂ through human intervention. This definition emphasizes the permanence of carbon sequestration and the importance of human intervention.

3.2. Scale of Carbon Sequestration in China

Currently, the extent of deep-saline aquifers for conducting CO₂-EWR in China is approximately 21,342 billion tons (Figure 5A) [40]. The current volume of explored CO₂ storage potential in petroleum reservoirs in China, suitable for implementing CO₂-EOR projects, is approximately 5.1 billion tons (Figure 5B), whereas the CO₂ storage potential of depleted oil reservoirs is as high as 21 billion tons [42]. Figure 5C shows the distribution of natural gas resources in China, suitable for CO₂-EGR. According to the Third National Oil and Gas Resources Assessment, under suitable conditions, the expected CO₂ storage capacity of CO₂-EGR is up to 30.4 billion tons in China [43]. Coalbed methane resources are widely distributed in China (Figure 5D); estimates from recent studies indicate a substantial potential sequestration of CO₂-ECBM in China of approximately 12 billion tons [46]. Relatively few studies have estimated the sequestration potential of CO₂-ESGR, in situ leaching, uranium extraction, or hydrate-based technologies in China (Figure 5E–G); however, according to Equations (1)–(3), the calculated CO₂ storage potentials are 11.05 billion tons, 697,200 tons, and 46.62 trillion tons, respectively.

3.3. Current CCUS Demonstration Projects in China

As of 2024, 13 large-scale CCUS demonstration projects in China involved carbon sequestration components (Table 4 and Figure 6). These projects cover various carbon sequestration technologies and reflect China’s technological diversity and innovation in the CCUS field. Two full-flow CCUS demonstration projects (marked by pentagrams) are particularly noteworthy: the Guohua Jinjie Power Plant and the Sinopec East China Oil Field Project. These projects have adopted advanced technological routes to compress captured CO₂ into liquid form, which is then transported to oil fields for oil-driven sequestration, achieving the dual benefits of carbon reduction and enhanced oil recovery.

Additionally, six independently operated carbon sequestration demonstration projects utilize CO₂-EOR methods (marked with circles). Notably, two full-chain CCUS demonstration projects employ this sequestration method. These projects use liquid or supercritical states for CO₂ sequestration to fully leverage the physical properties of CO₂ for enhanced sequestration efficiency. The technology for CO₂-EOR has matured significantly since its first use in the early 1970s in Texas, which could account for its higher level of development compared to CO₂-EGR or CO₂-EWR. In coalbed methane development, two demonstration projects utilize CO₂-ECBM methods (marked with squares). Both projects were implemented by the China United Coalbed Methane Corporation in Shanxi Province using supercritical states for CO₂ sequestration, which achieves carbon sequestration, as well as increasing the coalbed methane yield, indicating the diverse application value of CCUS technology. Furthermore, the advancement of CO₂-ECBM technology has been relatively slow, possibly attributed to the distinct nature of coal reservoirs and operational complexities. The CO₂-EWR project in the Ordos Basin (marked with a hexagon) is currently the only onshore CO₂ deep-saline aquifer storage demonstration project in China. In this project, liquid CO₂ is injected into saline aquifers 1500–2000 m underground to explore the potential for large-scale, long-term carbon sequestration. This project is of considerable importance in demonstrating the potential for future large-scale carbon sequestration endeavors in China. The in situ leaching uranium extraction project in Tongliao (marked with a diamond) achieves carbon sequestration, as well as improving uranium mining efficiency, highlighting the potential for CCUS technology to be integrated with other industries. The offshore CO₂-EWR project in the Enping Oilfield of the Pearl River Basin (marked with a triangle) is currently the only marine sequestration project in China.

3.4. Current Status of Carbon Sequestration Technology in China

We used Bayesian fuzzy evaluation to analyze the current technology levels of terrestrial and oceanic carbon sequestration in China (Figure 7). Regarding the eigenvalues, $F_1$–$F_7$, $F_1$, $F_2$, $F_6$, and $F_7$ were obtained from previous literature [41,43,53,56,69,70,71,72,73,74,75,76,77]; $F_3$ was obtained through an analysis and comparison of CO₂ sequestration costs both in China and internationally [the cost of in situ uranium leaching was calculated using Equation (15); Table 5]; $F_4$ was obtained by searching CNKI; and $F_5$ was obtained by analyzing the CCUS projects in China described in Section 3.3 (for specific feature descriptions, refer to Appendix B).

3.5. Development Potential of Carbon Sequestration Technologies in China

The differences in the time nodes when carbon technologies were proposed and policy preferences have led to the current differences in carbon sequestration technologies. According to our assessment of CO₂ sequestration technologies in China, we calculated the development potential of each technology (Table 6 and Figure 8), where the relative weights of the sequestration scale, technology status, and utilization situation scores obtained from Equations (8)–(13) were 0.25, 0.48, and 0.27, respectively. The technology with the highest overall score was in situ leaching of uranium, mainly because the level of technology has already reached the commercial application stage; however, the low CO₂ sequestration potential limits its future development potential for CO₂ sequestration. The technologies with the next highest overall scores were oceanic and terrestrial hydrate-based technologies, which perform well in terms of sequestration scale and utilization; however, the technology status is still in the basic research stage. CO₂-EWR also showed high development potential, mainly due to its larger sequestration scale and more mature technology status; however, the utilization score is low, suggesting future challenges in terms of economic benefits. CO₂-ECBM technology has an average sequestration scale, high technological maturity, and moderate utilization value, suggesting significant application potential, particularly in coal-rich regions. The conventional CO₂-EOR technology showed medium development potential, which reflects its high technological maturity, relatively low sequestration scale, and environmental benefits. Despite a large sequestration scale, deep-sea injection technology had an overall score of only 3.4 due to its low technology status and utilization scores. Thus, despite some development potential, this technology faces challenges in terms of practical application and economic benefits. Finally, the relatively low development potential for marine CO₂-EGR may be attributed to the complexity and potential environmental risks associated with implementation in marine environments.

3.6. Key Factors Influencing Cost Optimization of Carbon Sequestration Technologies in China

The implementation of CO₂ sequestration technology can be divided into several key stages. First, a detailed assessment, exploration, and development of the sequestration site; second, the installation and commissioning of CO₂ injection/production equipment; and third, transporting CO₂ in gas, supercritical, or liquid forms to designated deep underground or deep-sea sequestration locations. We categorized the costs of the sequestration process into two main types: capital and operation and maintenance (O&M) costs. Capital costs primarily include initial site costs and investment in CO₂ injection/production equipment, whereas O&M costs primarily encompass machinery operating costs, labor expenses, maintenance and repair costs, and equipment monitoring expenses (Table 7).

We conducted sensitivity analyses of CO₂-EWR, CO₂-EOR, CO₂-ECBM, and marine CO₂-EWR in China, varying the value of each cost parameter by 10% and observing the rate of change in the total cost compared with the total cost before no variation (Figure 9a). The change in total cost for these four types of sequestration was greater when the site costs and injection/production costs were changed. The site cost had the greatest impact on the total cost because the terrain of CO₂-EWR is more complicated. Marine CO₂-EWR technology requires higher injection and production costs than land-based CO₂-EWR technology because marine CO₂-EWR technology must also consider the construction costs of marine platforms and the transportation costs of ships. Therefore, changes in the cost of injection/production equipment for marine CO₂-EWR alter the total cost by up to 6.3%. Compared with the site costs and injection/production costs, the four cost parameters included in the O&M cost had a smaller impact on the total cost (≤2%). These results indicate that CCUS technology in China must still control and optimize site and injection/production costs.

The distribution of existing CCUS projects in China can be derived from Figure 6, which shows that, except for the CO₂-EOR project, the remaining types of projects are mainly concentrated in the central region of China; regional economic differences have relatively little impact on them. Therefore, this study focused on the CO₂-EOR pathway in the sensitivity analysis of regional economic differences. According to the Geological Environmental Zoning Map of China jointly compiled by the China Geological Survey and the Ministry of Natural Resources, we divided the area, where the current CO₂-EOR project is located, into four categories, A, B, C, and D, which correspond to categories I, II, IV, and VI of the geo-environmental zones of the map, respectively. Based on Equation (15) and the project cost data in Table 4, the economic factors of each region were calculated (see Table 8). On this basis, we further introduced a floating range of ±10% for the regional economic factor and carried out a regional sensitivity analysis under the CO₂-EOR path to reveal the impact of regional cost fluctuations on the overall economics. As shown in Figure 9b, the results of the analysis indicate that the regional economic factor of region D had the largest impact on the overall cost, suggesting that the region is more sensitive to changes in economic conditions; in contrast, the regional economic factor of region C had the smallest impact on the overall cost, suggesting that it is more economically stable and less sensitive to cost fluctuations.

3.7. Comparative Advantages of Marine Carbon Sequestration Technologies

According to our results, we reclassified and refined the CO₂ sequestration technologies, as shown in Figure 10. In view of the increasing depletion of terrestrial energy resources and increasing difficulty of development, marine carbon sequestration technology exhibits substantial potential. However, marine carbon sequestration technology has the following associated difficulties:

(1). Low technological maturity. The selection of injection points is complicated, the technology is still in the research stage, and large-scale application cases are lacking.

(2). High costs. Offshore construction, equipment installation, and transportation costs are high and substantially affected by environmental factors.

(3). Uncertainty in long-term environmental impacts. Difficulties in accurately predicting long-term consequences that may affect marine ecosystems.

(4). Monitoring difficulties. Seawater coverage leads to difficulties in direct observation and requires complex seabed monitoring equipment and techniques.

The advantages of marine sequestration technology are as follows:

(1). Larger capacity. The scale of oceanic CO₂ storage in deep-saline aquifers and replacement hydrates is larger than that of terrestrial sequestration, with 63% of CO₂ stored in deep-saline aquifers and 81.94% in replacement hydrates. The land sedimentary basin area in eastern China is small and sparsely distributed, with relatively low geological suitability for carbon sequestration, resulting in large carbon emissions from this region; therefore, eastern China should be considered as a development area for ocean sequestration technology.

(2). Enhanced stability. Seawater coverage can provide additional pressure, which reduces the requirement for closure of the cap layer and increases the stability of CO₂ below the seabed. In a deep-sea environment, CO₂ exists in a liquid or supercritical state; therefore, high-pressure and low-temperature conditions enhance the sequestration stability.

(3). Reduced pressure on land use. Marine sequestration technology does not require valuable land resources, which aids in reducing competition for land, especially in areas with intensive agricultural and urban development. Land sequestration requires abundant freshwater resources for CO₂ treatment and storage.

3.8. Study Limitations

Despite providing a comprehensive analysis of CO₂ storage technologies, this study has some limitations that deserve further exploration. First, we did not explore emerging technologies currently in the conceptual stage; for example, innovative approaches, such as salt-cavity CO₂ compression energy storage and CO₂ mining of dry-heat-rock geothermal energy. Second, the scale of technological sequestration, such as mineral carbonation in silicate rocks (e.g., peridotite and serpentinite), is relatively small; many technical and economic challenges require solutions before reaching the commercial application stage. Due to their low technological maturity, these technologies were not included in our analysis. Third, during the cost analysis of CO₂ storage technologies, we found significant differences among the data calculation models and evaluation scales in the existing literature. This inconsistency may have affected the accuracy and generalizability of our results. Therefore, a unified evaluation framework and standardized cost calculation methods could improve the reliability and validity of future analyses comparing CO₂ storage technologies.

4. Conclusions

This study represents the first comprehensive multi-dimensional assessment of the current status, development potential, and cost of CO₂ storage technologies in China, including a targeted strategic development path for CO₂ storage in China. Our findings provide an important reference for governments and enterprises regarding the selection and investment potential of CO₂ storage technology. Our main recommendations are as follows.

(1). Prioritize the promotion of breakthroughs in basic research on hydrate-based CO₂ storage technology. Although this technology is still in the basic research stage, it has substantial sequestration potential and potential energy utilization value, where the focus should be on supporting research in the directions of “improving the substitution efficiency of CO₂ and methane”, “strengthening the structural stability” and “feasibility and environmental impact assessment of large-scale application”. Research should focus on the “improvement of CO₂ and methane substitution efficiency”, “enhancement of structural stability”, and “feasibility of large-scale application and environmental impact assessment”. Research should be integrated into the major scientific and technological projects of “strategic mineral resources development and utilization” or “key technologies and equipment for the deep sea and polar regions”.

(2). Accelerate the promotion of CO₂-EWR demonstration and application. Despite its limited value in energy utilization, this technology has a huge sequestration scale and is particularly suitable for arid and water-scarce areas. This should be incorporated into the integrated water resources management system and carry out research on the synergistic mechanism of coupled ecological water use and carbon emission reduction to enhance its policy attractiveness.

(3). Continue to promote the commercialization of CO₂-EOR and develop the offshore oil drive path. As the most mature technology and economically rewarding sequestration path, we should focus on supporting CO₂-EOR demonstration projects in offshore oilfields, optimizing the efficiency of displacement, controlling the risk of leakage, and exploring the integration path with the “blue carbon economy”. For in situ leaching of uranium technology, although its sequestration volume is limited, it has specific application scenarios in uranium resource-rich areas, with retaining the development space as a regional complementary means.

(4). Strengthen the R&D synergy between CO₂-ECBM and deep-sea injection technology. The former should achieve the dual goals of “carbon emission reduction + energy recovery” by optimizing injection parameters and increasing the production rate of coalbed methane; the latter has potential for long-term reserves while promoting the construction of regulatory frameworks, environmental risk control, and cross-border governance mechanisms for deep-sea injection through international cooperation.

(5). Constructing a national CO₂ storage database and a refined site selection mechanism. Database construction should be incorporated into the supporting policy framework of the Carbon Emission Trading Regulations and the Greenhouse Gas Emission Accounting Guidelines. The Ministry of Ecology and Environment should take the lead with the Ministry of Natural Resources and the National Energy Administration to carry out cross-sectoral synergy. The database should integrate the operational data of sequestration projects, geological suitability distribution, sequestration capacity potential, and cost-sensitive factors, among others, to realize the entire process of supervision and verification from source transmission to sequestration.

Additionally, to promote the effective deployment of carbon sequestration technology in China, we must establish a supporting policy implementation system. The national level should accelerate the construction of a unified regulatory framework, as well as formulate safety standards, environmental assessment norms, and long-term monitoring mechanisms for all types of sequestration technologies, especially for ocean sequestration, which should strengthen cross-sectoral coordination and supervision. Moreover, a diversified financing mechanism should be constructed to encourage the provision of financial support for early demonstration projects through financial guidance, green industry funds, policy finance, and other channels, as well as to lower the threshold of social capital participation. On this basis, carbon sequestration should be incorporated into the national carbon market; endowed with the attributes of carbon assets; and an incentive structure should be established by means of tax preferences, green credits, and performance subsidies to guide enterprises to take the initiative to participate in the transformation of technology and its commercialization and application. The above measures can jointly build a synergistic system of “regulation, financing, and incentives” to provide institutional guarantees and risk mitigation support for carbon sequestration technology from demonstration to large-scale application.

Author Contributions

L.L.: Writing—original draft, Conceptualization, Methodology & Formal analysis; H.C.: Writing—original draft, Visualization; X.Q.: Validation; K.H.: Conceptualization, Formal analysis; M.Y.: Conceptualization, Formal analysis; M.W.: Conceptualization, Writing—review and editing; T.W.: Conceptualization; C.Z.: Conceptualization. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article.

Acknowledgments

We extend our gratitude to Editage (https://www.editage.cn/, accessed on 30 April 2025) for providing English language editing services.

Conflicts of Interest

Author Ming Ye is employed by Sinohrdro Bureau 6 Co., Ltd. Author Tong Wu is employed by Huaian City Development Investment and Holding Group Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:

CO2	carbon dioxide
CCUS	carbon capture, utilization, and storage
CO2-EWR	CO2 sequestration combined with deep-saline water/brine recovery
CO2-EOR	CO2-enhanced oil recovery
CO2-EGR	CO2-enhanced gas recovery
CO2-ECBM	CO2-enhanced coalbed methane recovery
CO2-ESGR	CO2-enhanced shale gas recovery technology

Footnotes

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Figures and Tables

Figure 1 Carbon emissions from major industries in China from 2019 to 2021.

Figure 2 Schematic of CCUS industrial processes and technology sectors.

Figure 3 Research framework diagram.

Figure 4 Natural and artificial carbon sequestration pathways in China. (Carbon emission pathways are shown. Artificial carbon sequestration and Marine carbon sequestration are categorized and illustrated).

Figure 5 Resource distribution map of China: (A) deep-saline aquifers, (B) oil resources, (C) natural gas resources, (D) coalbed methane resources, (E) shale gas resources, (F) uranium resources, and (G) combustible ice resources. Various types of resources provide a geologic basis for multi-path deployment of CCUS, reflecting differences in sequestration potential and technological adaptability in different regions.

Figure 6 Distribution of major CCUS projects currently involving carbon sequestration in China. The figure reflects the trend in the regional concentration of carbon sequestration projects and the types of technology applications, providing a basis for assessing regional deployment potential and policy formulation.

Figure 7 Current status and scale of carbon sequestration technologies in China. This figure shows a comparison of the maturity and storage potential of different carbon storage technologies, reflecting the diversified characteristics of carbon storage layout in China.

Figure 8 Scatter plot of CO₂ sequestration technology development potential in China. Comprehensively consider factors, such as technological maturity, scale of sequestration, and economic feasibility. The figure reflects the priority of each type of technology in the promotion and application, providing reference for technology selection and development path judgment.

Figure 9 Parameter sensitivity of the cost model for carbon sequestration technologies in China: (a) sensitivity analysis of the total cost in response to a 10% variation in each cost factor. (b) Sensitivity analysis of regional CO₂-EOR costs under ±10% fluctuations in regional economic factors.

Figure 10 Block diagram of CO₂ storage technology in China. Categorization, including carbon sequestration technologies, is summarized to facilitate the understanding of the overall architecture of China’s carbon sequestration system.

Table 1

Carbon sequestration technology maturity level classification.

Carbon Sequestration Technology Maturity	Level	General Rules for Evaluation
Conceptual stage	1	The stage of technical concepts and ideas existing only in theory or concept.
Basic research stage	2	The technology has been initially verified and may pass laboratory tests.
	3	The technology has passed laboratory tests and has preliminary functional verification.
Intermediate experimental stage	4	The technology prototype has been developed and undergoes preliminary tests.
	5	The prototype system is tested in a limited environment and has basic functions.
	6	It is tested in a simulated environment and has all functions.
Industrial demonstration stage	7	It is tested in an operational environment and has all functions.
	8	The technology has undergone system-level tests, has all functions, and is stable and reliable.
Commercial application	9	The technology is mature and ready for commercial application.

Table 2

Trigonometric fuzzy number correspondence table.

Ambiguity Level	Trigonometric Fuzzy Number Definition
Extremely low	Tri (0.0, 0.1, 0.2)
Low	Tri (0.2, 0.3, 0.4)
Middle	Tri (0.4, 0.5, 0.6)
High	Tri (0.6, 0.7, 0.8)
Extremely high	Tri (0.8, 0.9, 1.0)

Table 3

Key parameters of the total life-cycle cost of carbon sequestration.

Parameter	Description
$C{S}_j$	Total life-cycle cost of carbon sequestration using sequestration type $j$
$C_p^{ij}$	Resource consumption costs of sequestration type $j$ in year $i$
$C_L^{ij}$	Labor costs of sequestration type $j$ in year $i$
$C_{man}^{ij}$	Monitoring costs of sequestration type $j$ in year $i$
$C_{mon}^{ij}$	Maintenance and repair costs of sequestration type $j$ in year $i$
$C_e^j$	Site costs of sequestration type $j$
$C_{inj}^j$	Injection/production equipment costs of sequestration type $j$
$C_{mar}^{ij}$	Steamship transportation costs of sequestration type $j$ in year $i$
$u_j$	Uncertainty costs of sequestration type $j$

Table 4

Thirteen large-scale CCUS demonstration projects in China.

Name of the Project	Geological Type	Sequestration Depth (m)	CO2 Storage Technology	Annual CO2 Storage Capacity (t)	CO2 Storage Target (t)	Costs (USD/t)
Ordos CO2-EWR	Ordos Basin	800–2200	CO2-EWR	100,000	302,600	34.3
Jilin oilfield CO2-EOR	Daqingzijing Oilfield	1140–3360	CO2-EOR	250,000	2,000,000	22.9
Shengli oilfield CO2-EOR	Block G89 of Shengli Oilfield	2800–3200	CO2-EOR	40,000	-	62.1
Zhongyuan oilfield CO2-EOR	Zhongyuan Oilfield	2280–4300	CO2-EOR	100,000	740,000	48.3
Xinjiang CO2-EOR	Xinjiang Oilfield in the Junggar Basin	1500	CO2-EOR	50,000–100,000	1,239,000	110.4
Changqing oilfield CO2-EOR	Jiyuan Oil Region of Changqing Oilfield	1800–2700	CO2-EOR	50,000	376,000	16.8
Daqing oilfield CO2-EOR	Hailar Oilfield	4800	CO2-EOR	200,000	-	-
Guohua Jinjie power plant CCUS project	Ordos Basin	-	CO2-EOR	-	-	-
Huadong oilfield CCUS project	East China Oil and Gas Field	-	CO2-EOR	100,000	400,000	-
Tongliao in situ uranium leaching	Qianjiadian Uranium Deposit	-	In situ leaching of uranium	-	-	-
Zhonglian CO2-ECBM (Shizhuang)	Qinshui Basin	1037–1043	CO2-ECBM	1000	-	-
Zhonglian CO2-ECBM (Liulin)	Ordos Basin	-	CO2-ECBM	1000	-	-
Enping Oilfield Marine CO2-EWR	Enping Oilfield	800	Marine CO2-EWR	300,000	1,500,000	-

Table 5

Costs for various types of carbon sequestration at the current stage.

Carbon Sequestration Technology	Chinese CO2 Sequestration Costs (USD/t)	International CO2 Sequestration Costs (USD/t)
CO2-EWR	7.6–25 [78]	5.5–20 [79]
CO2-EOR	7–16 [80]	6.2–15 [81]
CO2-ECBM	3.3–34 [81,82]	4.2–11 [60]
CO2-EGR	-	11–27 [60,82]
CO2-ESGR	-	22–39 [83]
Hydrate-based	-	-
In situ uranium leaching	168,000	381,000
Marine CO2-EWR	15–35 [64,78]	9–30 [84]
Marine CO2-EOR	13–29	5–11 [85]
Marine CO2-EGR	-	20–49
Deep-sea injection	-	-

Note: The cost of in situ leaching uranium was calculated according to Equation (15).

Table 6

Assessment results of CO₂ sequestration technologies in China.

Carbon Sequestration Technology	Sequestration Scale Score	Technology Status Score	Utilization Score	Overall Score
Hydrate-based	9	4	9	6.6
CO2-EWR	7	8	1	5.9
CO2-EOR	3	8	3	5.4
CO2-EGR	3	4	5	4.0
CO2-ECBM	3	8	4	5.7
CO2-ESGR	3	4	6	4.3
In situ uranium leaching	1	10	10	7.7
Marine hydrate-based	10	4	9	6.9
Marine CO2-EWR	7	8	1	5.9
Marine CO2-EGR	2	4	5	3.8
Marine CO2-EOR	1	6	3	3.9
Deep-sea injection	5	4	1	3.4

Table 7

Capital and O&M costs of carbon sequestration.

Cost Component	Description
Capital costs
Site costs	Evaluation, exploration, and development costs of closed sites
Injection/production equipment costs	Injection equipment, including drilling, injection wells, offshore platforms/offshore transportation, and production equipment, including production wells, compression equipment, and pumping equipment
O&M costs
Resource costs	Electricity, fuel, water resources
Labor costs	Costs of skilled and unskilled personnel
Monitoring costs	Surface monitoring and subsurface monitoring
Maintenance and repair costs	Regular maintenance and repair of equipment and grounds

Table 8

CO₂-EOR regional economic factor.

	Region A	Region B	Region C	Region D
Regional economic factors	0.44	1.06	0.32	2.12

Appendix A

Appendix A.1. Exchange and Inflation Rates

Table A1

Inflation rates for China and the United States.

Year	China Inflation Rate	United States Inflation Rate
2023	+0.20%	+4.10%
2022	+1.97%	+8.00%
2021	+0.98%	+4.70%
2020	+2.42%	+1.23%
2019	+2.90%	+1.81%
2018	+2.07%	+2.44%
2017	+1.59%	+2.13%
2016	+2.00%	+1.26%
2015	+1.44%	+0.12%
2014	+1.92%	+1.62%
2013	+2.62%	+1.46%
2012	+2.62%	+2.07%
2011	+5.55%	+3.16%
2010	+3.18%	+1.64%
2009	−0.70%	−0.36%
2008	+5.90%	+3.84%
2007	+4.80%	+2.85%
2006	+1.50%	+3.23%
2005	+1.80%	+3.39%

Table A2

US–China exchange rates adjusted by the relative purchasing power parity.

Year	Exchange Rate
2019	1:7.56
2018	1:7.43
2017	1:7.46
2016	1:7.52
2015	1:7.45
2014	1:7.31
2013	1:7.29
2012	1:7.23
2011	1:7.22
2010	1:7.11
2009	1:7.14
2008	1:7.11
2007	1:6.91
2006	1:6.73
2005	1:7.12

Appendix B

Appendix B.1. Characteristics of the Seven Carbon Sequestration Technologies Analyzed in This Study

CO₂-EWR [74,75]

F1 (Research Scale): Large-scale experiments conducted in the laboratory.

F2 (Technology Maturity): The technical principles have been verified; however, further enhancement of stability is required.

F3 (Economic Feasibility): The preliminary cost analysis shows potential but has not yet reached commercial feasibility.

F4 (Number of Patents and Literature): A small number of related papers have been published, and 133 patents exist.

F5 (Degree of Industrial Application): This technology has been applied to actual industries, and one demonstration project is currently in operation.

F6 (Degree of Technology Standardization): Relevant standards have been initially formed.

F7 (Investment Scale): Certain R&D funds have been obtained; however, no large-scale industrial investment has been made.

CO₂-EOR [41,69]

F1 (Research Scale): The laboratory testing stage has currently been completed.

F2 (Technical Maturity): Technical principles have been verified and are relatively stable.

F3 (Economic Feasibility): The cost analysis indicates relatively strong economic feasibility and imminent commercial feasibility.

F4 (Number of Patents and Literature): Several related papers have been published, and 476 patents exist.

F5 (Degree of Industrial Application): This technology has been applied in actual industries, and eight projects are currently in operation.

F6 (Degree of Technology Standardization): The relevant standards are relatively mature.

F7 (Investment Scale): Large-scale industrial investments have been initially formed.

CO₂-ECBM [73,77]

F1 (Research Scale): Relatively large-scale experiments are being conducted in the laboratory.

F2 (Technical Maturity): The technical principles have been verified; however, further enhancement of stability is required.

F3 (Economic Feasibility): The preliminary cost analysis shows potential but has not yet reached commercial feasibility.

F4 (Number of Patents and Literature): Several related papers have been published, and 168 patents exist.

F5 (Degree of Industrial Application): This technology has been applied in actual industries, and two projects are currently in operation.

F6 (Degree of Technology Standardization): Relevant standards have been initially formed.

F7 (Investment Scale): No large-scale investment has been made.

CO₂-EGR [44]

F1 (Research Scale): Medium-scale experiments are being conducted in the laboratory.

F2 (Technical Maturity): The technical principles have been verified; however, further enhancement of stability is required.

F3 (Economic Feasibility): The preliminary cost analysis shows potential but has not yet reached commercial feasibility.

F4 (Number of Patents and Literature): A small number of related papers have been published, and 168 patents exist.

F5 (Degree of Industrial Application): This technology has not yet been applied in industry.

F6 (Degree of Technology Standardization): Relevant standards have not yet been established.

F7 (Investment Scale): No large-scale industrial investment have been made.

CO₂-ESGR (Li-Xin et al., 2021; Chang et al., 2024) [70,72]

F1 (Research Scale): Medium-scale experiments have been conducted in the laboratory.

F2 (Technical Maturity): The technical principles have been verified; however, further enhancement of stability is required.

F3 (Economic Feasibility): The preliminary cost analysis shows potential but has not yet reached commercial feasibility.

F4 (Number of Patents and Literature): A small number of related papers have been published, and 99 patents exist.

F5 (Degree of Industrial Application): This technology has not yet been applied in industry.

F6 (Degree of Technology Standardization): Relevant standards have not yet been established.

F7 (Investment Scale): No large-scale industrial investment has been made.

In situ leaching of uranium (Xue-bin and Zhi-ming, 2012) [76]

F1 (Research Scale): The experimental research stage has been completed.

F2 (Technical Maturity): The technology is relatively mature with good stability.

F3 (Economic Feasibility): Commercial feasibility has been reached with relatively low costs.

F4 (Number of Patents and Literature): Several related papers have been published, and 369 patents exist.

F5 (Degree of Industrial Application): This method has been applied in industry.

F6 (Degree of Technology Standardization): Relevant standards have already been formed.

F7 (Investment Scale): Large-scale investment has been made.

Hydrate-based technology (Mingxing et al., 2024) [53]

F1 (Research Scale): Small-scale experiments are being conducted in laboratories.

F2 (Technical Maturity): The technical principles are still in the verification stage, and further enhancement of stability is required.

F3 (Economic Feasibility): Preliminary cost analysis shows substantial potential but has not yet reached commercial feasibility.

F4 (Number of Patents and Literature): A small number of related papers have been published, and 56 patents exist.

F5 (Degree of Industrial Application): This technology has not yet been applied in industry.

F6 (Degree of Technology Standardization): Relevant standards have not yet been established.

F7 (Investment Scale): No large-scale industrial investment has been made.

Deep-sea injection (Bo et al., 2023) [56]

F1 (Research Scale): Small-scale experiments are being conducted both in the laboratory and on-site.

F2 (Technical Maturity): The technical principles have been verified; however, further enhancement of stability is required.

F3 (Economic Feasibility): The preliminary cost analysis shows potential but has not yet reached commercial feasibility.

F4 (Number of Patents and Literature): A small number of related papers have been published, and 10 patents have been applied for.

F5 (Degree of Industrial Application): This has not yet been applied in industry.

F6 (Degree of Technology Standardization): Relevant standards have not yet been established.

F7 (Investment Scale): No large-scale industrial investment has been made.

Marine CO₂-EWR (Jinzhou et al., 2024) [71]

F1 (Research Scale): Relatively large-scale experiments are being conducted in the laboratory.

F2 (Technical Maturity): The technical principles have been verified; however, further enhancement of stability is required.

F3 (Economic Feasibility): The preliminary cost analysis shows potential but has not yet reached commercial feasibility.

F4 (Number of Patents and Literature): Numerous related papers have been published.

F5 (Degree of Industrial Application): This technology has been applied in industry.

F6 (Degree of Technology Standardization): Relevant standards have been initially formed.

F7 (Investment Scale): Large-scale industrial investments have been made.

Marine CO₂-EOR (Hill et al., 2020) [41]

F1 (Research Scale): This technology is in the experimental stage.

F2 (Technical Maturity): The technology is relatively mature with average stability.

F3 (Economic Feasibility): The preliminary cost analysis shows potential but has not yet reached commercial feasibility.

F4 (Number of Patents and Literature): Numerous related papers have been published.

F5 (Degree of Industrial Application): This technology has not yet been applied in industry.

F6 (Degree of Technology Standardization): Relevant standards have been initially formed.

F7 (Investment Scale): No large-scale industrial investment has been made.

Marine CO₂-EGR (Liehui et al., 2023) [44]

F1 (Research Scale): Medium-scale experiments have been conducted in the laboratory.

F2 (Technical Maturity): The technical principles have been verified; however, further enhancement of stability is required.

F3 (Economic Feasibility): The preliminary cost analysis shows potential but has not yet reached commercial feasibility.

F4 (Number of Patents and Literature): A small number of related papers have been published.

F5 (Degree of Industrial Application): This technology has not yet been applied in industry.

F6 (Degree of Technology Standardization): Relevant standards have not yet been established.

F7 (Investment Scale): No large-scale industrial investment has been made.

Marine hydrate-based technology (Mingxing et al., 2024) [53]

F1 (Research Scale): Small-scale experiments are being conducted in laboratories.

F2 (Technical Maturity): The technical principles are still in the verification stage, and further enhancement of stability is required.

F3 (Economic Feasibility): Preliminary cost analysis shows great potential but has not yet reached commercial feasibility.

F4 (Number of Patents and Literature): A small number of related papers have been published, and 56 patents exist.

F5 (Degree of Industrial Application): This technology has not yet been applied in industry.

F6 (Degree of Technology Standardization): Relevant standards have not yet been established.

F7 (Investment Scale): No large-scale industrial investment has been made.

References

1. Chen, S.; Liu, J.; Zhang, Q.; Teng, F.; McLellan, B.C. A critical review on deployment planning and risk analysis of carbon capture, utilization, and storage (CCUS) toward carbon neutrality. Renew. Sustain. Energy Rev.; 2022; 167, 112537. [DOI: https://dx.doi.org/10.1016/j.rser.2022.112537]

2. Savaresi, A. The Paris Agreement: A new beginning?. J. Energy Nat. Resour. Law; 2016; 34, pp. 16-26. [DOI: https://dx.doi.org/10.1080/02646811.2016.1133983]

3. Guan, Y.; Shan, Y.; Huang, Q.; Chen, H.; Wang, D.; Hubacek, K. Assessment to China’s recent emission pattern shifts. Earths Future; 2021; 9, EF002241. [DOI: https://dx.doi.org/10.1029/2021EF002241]

4. Shan, Y.; Guan, D.; Zheng, H.; Ou, J.; Li, Y.; Meng, J.; Mi, Z.; Liu, Z.; Zhang, Q. China CO₂ emission accounts 1997–2015. Sci. Data; 2018; 5, 170201. [DOI: https://dx.doi.org/10.1038/sdata.2017.201] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29337312]

5. Shan, Y.; Huang, Q.; Guan, D.; Hubacek, K. China CO₂ emission accounts 2016–2017. Sci. Data; 2020; 7, 54. [DOI: https://dx.doi.org/10.1038/s41597-020-0393-y]

6. Liu, B.; Xu, Y.; Yang, Y.; Lu, S. How public cognition influences public acceptance of CCUS in China: Based on the ABC (affect, behavior, and cognition) model of attitudes. Energy Policy; 2021; 156, 112390. [DOI: https://dx.doi.org/10.1016/j.enpol.2021.112390]

7. Akeeb, O.; Wang, L.; Xie, W.; Davis, R.; Alkasrawi, M.; Toan, S. Post-combustion CO₂ capture via a variety of temperature ranges and material adsorption process: A review. J. Environ. Manag.; 2022; 313, 115026. [DOI: https://dx.doi.org/10.1016/j.jenvman.2022.115026] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35405546]

8. Erans, M.; Sanz-Pérez, E.S.; Hanak, D.P.; Clulow, Z.; Reiner, D.M.; Mutch, G.A. Direct air capture: Process technology, techno-economic and socio-political challenges. Energy Environ. Sci.; 2022; 15, pp. 1360-1405. [DOI: https://dx.doi.org/10.1039/D1EE03523A]

9. Garcia, J.A.; Villen-Guzman, M.; Rodriguez-Maroto, J.M.; Paz-Garcia, J.M. Technical analysis of CO₂ capture pathways and technologies. J. Environ. Chem. Eng.; 2022; 10, 108470. [DOI: https://dx.doi.org/10.1016/j.jece.2022.108470]

10. Liu, R.S.; Shi, X.D.; Wang, C.T.; Gao, Y.Z.; Xu, S.; Hao, G.P.; Chen, S.; Lu, A.H. Advances in post-combustion CO₂ capture by physical adsorption: From materials innovation to separation practice. ChemSusChem; 2021; 14, pp. 1428-1471. [DOI: https://dx.doi.org/10.1002/cssc.202002677]

11. Odunlami, O.A.; Vershima, D.A.; Oladimeji, T.E.; Nkongho, S.; Ogunlade, S.K.; Fakinle, B.S. Advanced techniques for the capturing and separation of CO₂—A review. Results Eng.; 2022; 15, 100512. [DOI: https://dx.doi.org/10.1016/j.rineng.2022.100512]

12. Shen, M.; Tong, L.; Yin, S.; Liu, C.; Wang, L.; Feng, W.; Shen, M.; Tong, L.; Yin, S.; Liu, C. . Cryogenic technology progress for CO₂ capture under carbon neutrality goals: A review. Sep. Purif. Technol.; 2022; 299, 121734. [DOI: https://dx.doi.org/10.1016/j.seppur.2022.121734]

13. Wang, M.; Lawal, A.; Stephenson, P.; Sidders, J.; Ramshaw, C. Post-combustion CO₂ capture with chemical absorption: A state-of-the-art review. Chem. Eng. Res. Des.; 2011; 89, pp. 1609-1624. [DOI: https://dx.doi.org/10.1016/j.cherd.2010.11.005]

14. Dziejarski, B.; Krzyżyńska, R.; Andersson, K. Current status of carbon capture, utilization, and storage technologies in the global economy: A survey of technical assessment. Fuel; 2023; 342, 127776. [DOI: https://dx.doi.org/10.1016/j.fuel.2023.127776]

15. Ji, Y.; Chuangting, C.; Hui, H. Cost analysis of chemical looping coal-fired power plant based on a double factors learning curve model. Clean Coal Technol.; 2024; 30, pp. 82-89.

16. Leeson, D.; Mac Dowell, N.; Shah, N.; Petit, C.; Fennell, P.S. A Techno-economic analysis and systematic review of carbon capture and storage (CCS) applied to the iron and steel, cement, oil refining and pulp and paper industries, as well as other high purity sources. Int. J. Greenh. Gas Control.; 2017; 61, pp. 71-84. [DOI: https://dx.doi.org/10.1016/j.ijggc.2017.03.020]

17. Zheng, Y.; Gao, L.; He, S. Analysis of the mechanism of energy consumption for CO₂ capture in a power system. Energy; 2023; 262, 125103. [DOI: https://dx.doi.org/10.1016/j.energy.2022.125103]

18. Dubey, A.; Arora, A. Advancements in carbon capture technologies: A review. J. Clean. Prod.; 2022; 373, 133932. [DOI: https://dx.doi.org/10.1016/j.jclepro.2022.133932]

19. Kim, S.; Lim, Y.-I.; Lee, D.; Cho, W.; Seo, M.W.; Lee, J.G.; Ok, Y.S. Perspectives of oxy-coal power plants equipped with CO₂ capture, utilization, and storage in terms of energy, economic, and environmental impacts. Energy Convers. Manag.; 2022; 273, 116361. [DOI: https://dx.doi.org/10.1016/j.enconman.2022.116361]

20. Rubin, E.S.; Davison, J.E.; Herzog, H.J. The cost of CO₂ capture and storage. Int. J. Greenh. Gas Control.; 2015; 40, pp. 378-400. [DOI: https://dx.doi.org/10.1016/j.ijggc.2015.05.018]

21. Huang, L. CO₂ geological storage and utilization. Atmosphere; 2023; 14, 1166. [DOI: https://dx.doi.org/10.3390/atmos14071166]

22. Do, T.N.; You, C.; Kim, J. A CO₂ utilization framework for liquid fuels and chemical production: Techno-economic and environmental analysis. Energy Environ. Sci.; 2022; 15, pp. 169-184. [DOI: https://dx.doi.org/10.1039/D1EE01444G]

23. Daneshvar, E.; Wicker, R.J.; Show, P.-L.; Bhatnagar, A. Biologically-mediated carbon capture and utilization by microalgae towards sustainable CO₂ biofixation and biomass valorization–A review. Chem. Eng. J.; 2022; 427, 130884. [DOI: https://dx.doi.org/10.1016/j.cej.2021.130884]

24. Fan, J.; Xu, M.; Wei, S.; Shen, S.; Diao, Y.; Zhang, X. Carbon reduction potential of China’s coal-fired power plants based on a CCUS source-sink matching model. Resour. Conserv. Recycl.; 2021; 168, 105320. [DOI: https://dx.doi.org/10.1016/j.resconrec.2020.105320]

25. Li, K.; Shen, S.; Fan, J.-L.; Xu, M.; Zhang, X. The role of carbon capture, utilization and storage in realizing China’s carbon neutrality: A source-sink matching analysis for existing coal-fired power plants. Resour. Conserv. Recycl.; 2022; 178, 106070. [DOI: https://dx.doi.org/10.1016/j.resconrec.2021.106070]

26. Sun, L.; Liu, Q.; Chen, H.; Yu, H.; Li, L.; Li, L.; Li, Y.; Adenutsi, C.D. Source-sink matching and cost analysis of offshore carbon capture, utilization, and storage in China. Energy; 2024; 291, 130137. [DOI: https://dx.doi.org/10.1016/j.energy.2023.130137]

27. Hepburn, C.; Adlen, E.; Beddington, J.; Carter, E.A.; Fuss, S.; Mac Dowell, N.; Minx, J.C.; Smith, P.; Williams, C.K. The technological and economic prospects for CO₂ utilization and removal. Nature; 2019; 575, pp. 87-97. [DOI: https://dx.doi.org/10.1038/s41586-019-1681-6]

28. Du, B.; Liu, P.; Li, Z. Optimal planning for thermal power plants with CCS under source–sink matching constraints: A case study of China. Comput. Aided Chem. Eng.; 2023; 52, pp. 425-431. [DOI: https://dx.doi.org/10.1016/B978-0-443-15274-0.50068-8]

29. Sun, L.; Chen, W. Development and application of a multi-stage CCUS source–sink matching model. Appl. Energy; 2017; 185, pp. 1424-1432. [DOI: https://dx.doi.org/10.1016/j.apenergy.2016.01.009]

30. Yi, L.; Fan, Z.; Jinsheng, W.; Peng, G.; Hao, W. Research on Source-sink matching between coal-fired power plants and CO₂ saline aquifer storage in sedimentary basins in China. Geol. China; 2024; pp. 1-22. Available online: https://link.cnki.net/urlid/11.1167.P.20240130.1035.006 (accessed on 5 March 2025).

31. Zhang, X.; Li, K.; Wei, N.; Li, Z.; Fan, J.-L. Advances, challenges, and perspectives for CCUS source-sink matching models under carbon neutrality target. Carbon Neutrality; 2022; 1, 12. [DOI: https://dx.doi.org/10.1007/s43979-022-00007-7]

32. Hasan, M.M.F.; Boukouvala, F.; First, E.L.; Floudas, C.A. Nationwide, regional, and statewide CO₂ capture, utilization, and sequestration supply chain network optimization. Ind. Eng. Chem. Res.; 2014; 53, pp. 7489-7506. [DOI: https://dx.doi.org/10.1021/ie402931c]

33. Kegl, T.; Čuček, L.; Kovač Kralj, A.K.; Kravanja, Z. Conceptual MINLP approach to the development of a CO₂ supply chain network–Simultaneous consideration of capture and utilization process flowsheets. J. Clean. Prod.; 2021; 314, 128008. [DOI: https://dx.doi.org/10.1016/j.jclepro.2021.128008]

34. Zhang, S.; Liu, L.; Zhang, L.; Zhuang, Y.; Du, J. An optimization model for carbon capture utilization and storage supply chain: A case study in northeastern China. Appl. Energy; 2018; 231, pp. 194-206. [DOI: https://dx.doi.org/10.1016/j.apenergy.2018.09.129]

35. Ali, M.; Jha, N.K.; Pal, N.; Keshavarz, A.; Hoteit, H.; Sarmadivaleh, M. Recent advances in carbon dioxide geological storage, experimental procedures, influencing parameters, and future outlook. Earth Sci. Rev.; 2022; 225, 103895. [DOI: https://dx.doi.org/10.1016/j.earscirev.2021.103895]

36. Chen, J.; Wang, L.L.; Wang, P.K. Carbon dioxide geological storage potential in saline aquifer of sedimentary basins in China Sea. Mar. Geol. Quat. Geol.; 2024; 44, pp. 98-114. [DOI: https://dx.doi.org/10.16562/j.cnki.0256-1492.2024042101]

37. He, Q.; Li, C.; Guo, C.; Wang, X.; Zhang, B.; Yang, L.; Li, X.; Zhu, Y. Geological carbon storage and compressed gas energy storage: Current status, challenges, and prospects. Hydrogeol. Eng. Geol.; 2024; 51, pp. 1-9. [DOI: https://dx.doi.org/10.16030/j.cnki.issn.1000-3665.202406013]

38. Song, Y.; Jun, S.; Na, Y.; Kim, K.; Jang, Y.; Wang, J. Geomechanical challenges during geological CO₂ storage: A review. Chem. Eng. J.; 2023; 456, 140968. [DOI: https://dx.doi.org/10.1016/j.cej.2022.140968]

39. Hunter, K.; Bielicki, J. The Production of Water from Saline Aquifers Through Carbon Dioxide Capture and Storage Operations. 2016; Available online: https://dc.engconfintl.org/co2_summit2/45/ (accessed on 20 March 2025).

40. He, L.S.; Wan, J.H.; Zhang, J.Q.; Liang, J.L.; Liu, Z.J.; Liu, W.P. CO₂ geological sequestration and evaluation of CO₂ geological sequestration potential in China. Gansu Geol.; 2024; 33, pp. 59-71.

41. Hill, L.B.; Li, X.; Wei, N. CO₂-EOR in China: A comparative review. Int. J. Greenh. Gas Control.; 2020; 103, 103173. [DOI: https://dx.doi.org/10.1016/j.ijggc.2020.103173]

42. Fan, J.; Wei, S.; Shen, S.; Xu, M.; Zhang, X. Geological storage potential of CO₂ emissions for China’s coal-fired power plants: A city-level analysis. Int. J. Greenh. Gas Control.; 2021; 106, 103278. [DOI: https://dx.doi.org/10.1016/j.ijggc.2021.103278]

43. Shi, Y.Q.; Jia, Y.; Pan, W.Y.; Huang, L.; Yan, J.; Zheng, R.C. Potential evaluation on CO₂-EGR in tight and low-permeability reservoirs. Nat. Gas Ind. B; 2017; 4, pp. 311-318. [DOI: https://dx.doi.org/10.1016/j.ngib.2017.08.013]

44. Zhang, L.H.; Cao, C.; Wen, S.M.; Zhao, Y.L.; Peng, X.; Wu, J.F. Thoughts on the developmengt of CO₂-EGR under the background of carbon peak and carbon neutrality. Nat. Gas Ind. B; 2023; 43, pp. 13-22. [DOI: https://dx.doi.org/10.1016/j.ngib.2023.07.007]

45. Godec, M.; Koperna, G.; Gale, J. CO₂-ECBM: A review of its status and global potential. Energy Procedia; 2014; 63, pp. 5858-5869. [DOI: https://dx.doi.org/10.1016/j.egypro.2014.11.619]

46. Liu, Y.F.; Li, X.C.; Bai, B. Preliminary estimation of CO₂ storage capacity of coalbeds in China. Chin. J. Rock Mech. Eng.; 2005; 24, pp. 2947-2952.

47. Liu, S.; Sun, B.; Xu, J.; Li, H.; Wang, X. Study on competitive adsorption and displacing properties of CO₂ enhanced shale gas recovery: Advances and challenges. Geofluids; 2020; 2020, pp. 1-15. [DOI: https://dx.doi.org/10.1155/2020/6657995]

48. Lu, Y.; Ping, Z.; Xian, X.; Tang, J.; Zhou, L.; Jiang, Y.D.; Xia, B.; Wang, X.; Kang, Y. Research progress and prospect of the integrated supercritical CO₂ enhanced shale gas recovery and geological sequestration. Nat. Gas Ind.; 2021; 41, pp. 60-73. [DOI: https://dx.doi.org/10.3787/j.issn.1000-0976.2021.06.007]

49. Sheng, J.J. Enhanced oil recovery in shale reservoirs by gas injection. J. Nat. Gas Sci. Eng.; 2015; 22, pp. 252-259. [DOI: https://dx.doi.org/10.1016/j.jngse.2014.12.002]

50. Xu, G.F. Analysis of the main technological parameters of CO₂+O₂ in situ leaching uranium and problems by chemical precipitation blocking. Uranium Min. Metall.; 2014; 33, pp. 197-202+222. [DOI: https://dx.doi.org/10.13426/j.cnki.yky.2014.04.006]

51. Sreenivas, T.; Rajan, K.C. Studies on the separation of dissolved uranium from alkaline carbonate leach slurries by resin-in-pulp process. Sep. Purif. Technol.; 2013; 112, pp. 54-60. [DOI: https://dx.doi.org/10.1016/j.seppur.2013.03.050]

52. Zhou, S.C.; Li, Z.Y.; Guo, J.; Cai, Y.Q.; Nie, J.T. The security of uranium resource demand under the new development. World Nucl. Geosci.; 2024; 41, 703.

53. Bai, M.X.; Zhang, Z.C.; Chen, Q.Z.; Xu, L.; Du, S.Y.; Liu, Y.X. Advances in research on CO₂ replacement for natural gas hydrate exploitation. Oil Gas Geol.; 2024; 45, pp. 553-564.

54. Wei, W.-N.; Li, B.; Gan, Q.; Li, Y.-L. Research progress of natural gas hydrate exploitation with CO₂ replacement: A review. Fuel; 2022; 312, 122873. [DOI: https://dx.doi.org/10.1016/j.fuel.2021.122873]

55. Chow, A. Ocean carbon sequestration by direct injection. CO₂ Sequestration and Valorization; Morgado, R.V.C. IntechOpen: London, UK, 2014; [DOI: https://dx.doi.org/10.5772/57386]

56. Liu, B.; Gao, S.; Xu, Z.; Fu, X.F.; Erfan, M.; Lu, H. A review of CO₂ sequestration technology by direct injection in the ocean. Geol. Rev.; 2023; 69, pp. 1449-1464. [DOI: https://dx.doi.org/10.16509/j.georeview.2023.01.021]

57. Caldeira, K.; Herzog, H.J.; Wickett, M.E. Predicting and Evaluating the Effectiveness of Ocean Carbon Sequestration by Direct Injection; Lawrence Livermore National Laboratory: Livermore, CA, USA, 2001; Available online: https://www.osti.gov/biblio/15013266 (accessed on 21 April 2025).

58. Folger, P. Carbon capture: A technology assessment. Congr. Res. Serv. Rep.; 2010; 19, Available online: https://digitalcommons.unl.edu/crsdocs/19 (accessed on 21 March 2025).

59. Luo, J.; Chen, Y. Teaching essentials and empirical test of the theory of relative purchasing power parity. Sci. Technol.; 2020; pp. 190-193.

60. Bachu, S. CO₂ storage in geological media: Role, means, status and barriers to deployment. Prog. Energy Combust. Sci.; 2008; 34, pp. 254-273. [DOI: https://dx.doi.org/10.1016/j.pecs.2007.10.001]

61. Dahowski, R.T.; Davidson, C.L.; Li, X.C.; Wei, N. A $70/t CO₂ greenhouse gas mitigation backstop for China’s industrial and electric power sectors: Insights from a comprehensive CCS cost curve. Int. J. Greenh. Gas Control.; 2012; 11, pp. 73-85. [DOI: https://dx.doi.org/10.1016/j.ijggc.2012.07.024]

62. Damen, K.; Faaij, A.; van Bergen, F.; Gale, J.; Lysen, E. Identification of early opportunities for CO₂ sequestration—Worldwide screening for CO₂-EOR and CO₂-ECBM projects. Energy; 2005; 30, pp. 1931-1952. [DOI: https://dx.doi.org/10.1016/j.energy.2004.10.002]

63. Wang, Z.; Kuang, J.; Pang, H.; Huo, Z.L. Cost analysis of CO₂ geological storage in deep saline formation. Sci. Technol. Rev.; 2014; 32, pp. 46-52.

64. Lin, Z.Q.; Zhong, D.; Xing, Q.X. Economic feasibility evaluation of CO₂-ECBM: A case study in Qinshui Basin, China. Adv. Mater. Res.; 2014; 962, 225320132257. [DOI: https://dx.doi.org/10.4028/www.scientific.net/AMR.962-965.2253]

65. Wei, N.; Li, X.; Dahowski, R.T.; Davidson, C.L.; Liu, S.; Zha, Y. Economic evaluation on CO₂-EOR of onshore oil fields in China. Int. J. Greenh. Gas Control.; 2015; 37, pp. 170-181. [DOI: https://dx.doi.org/10.1016/j.ijggc.2015.01.014]

66. Shi, T.; Wang, D.; Tang, Y.; Li, P.; Chu, Y. Research progress on calculation method and impact factors of carbon sequestration capacity in urban ecosystems. Chin. J. Appl. Ecol.; 2023; 34, pp. 555-565. [DOI: https://dx.doi.org/10.13287/j.1001-9332.202302.002]

67. Yang, G.; Peng, H.N.; Feng, W.Y. Characteristics of carbon sequestration by ecosystem and progress in its research. J. Nat. Resour.; 2013; 28, pp. 1264-1274.

68. Fatichi, S.; Pappas, C.; Zscheischler, J.; Leuzinger, S. Modelling carbon sources and sinks in terrestrial vegetation. New Phytol.; 2019; 221, pp. 652-668. [DOI: https://dx.doi.org/10.1111/nph.15451] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30339280]

69. Abuov, Y.; Serik, G.; Lee, W. Techno-economic assessment and life cycle assessment of CO₂-EOR. Environ. Sci. Technol.; 2022; 56, pp. 8571-8580. [DOI: https://dx.doi.org/10.1021/acs.est.1c06834] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35653301]

70. Chang, X.; Lin, S.; Yang, C.; Wang, K.; Liu, S.; Guo, Y. A critical review of Sc CO₂-enhanced gas recovery and geologic storage in shale reservoirs. Gas Sci. Eng.; 2024; 125, 205317. [DOI: https://dx.doi.org/10.1016/j.jgsce.2024.205317]

71. Zhao, J.Z.; Zheng, J.C.; Ren, L.; Lin, R.; Zhou, B. Research progress and development trend of marine CO₂ geological storage. Pet. Geol. Oilfield Dev. Daqing; 2024; 43, pp. 1-13. [DOI: https://dx.doi.org/10.19597/j.Issn.1000-3754.202307039]

72. Liu, L.X.; Li, Z.H.; Han, X.B.; Wang, J.; Zhao, Y.; Liao, S.B. Research progress on joint technology for underground carbon dioxide sequestration and shale gas extraction. Mod. Chem. Ind.; 2021; 41, pp. 39-43. [DOI: https://dx.doi.org/10.16606/j.cnki.issn0253-4320.2021.11.009]

73. Li, Y.; Wang, Y.; Bi, C.; Wang, Q.; Shi, Y.; Xu, Y.; Yuan, Y.; Tong, L.; Tang, Y.; Shan, Y. . Assessment of in-situ CO₂ sequestration potential and enhanced coalbed methane (ECBM) production of continental coal-bearing basins in China. Acta Geol. Sin.; 2024; 98, pp. 1602-1614. [DOI: https://dx.doi.org/10.1111/1755-6724.15188]

74. Qin, J.; Zhong, Q.; Tang, Y.; Rui, Z.; Qiu, S.; Chen, H. CO₂ storage potential assessment of offshore saline aquifers in China. Fuel; 2023; 341, 127681. [DOI: https://dx.doi.org/10.1016/j.fuel.2023.127681]

75. Ma, X.R.; Liang, J.; Li, Q. Progress and prospects of CO₂ geological storage in saline aquifer. Mar. Geol. Front.; 2024; 40, pp. 1-18. [DOI: https://dx.doi.org/10.16028/j.1009-2722.2023.266]

76. Su, X.B.; Du, Z.M. Development and prospect of China uranium in-situ leaching technology. China Min. Mag.; 2012; 21, pp. 79-83.

77. Sa, Z.Y.; Wu, J.B.; Lu, W.D.; Yang, Y.L.; Zhang, X.; Lu, S.Q.; Liu, J. Research progress of enhanced coalbed methane exploitation by carbon dioxide injection. Saf. Coal Mines; 2022; 53, pp. 32-43. [DOI: https://dx.doi.org/10.13347/j.cnki.mkaq.2022.10.005]

78. Zhao, X.; Xiao, J.; Hou, J.; Wu, J.; Lyu, X.; Zhang, J.; Liu, Y. Economic and scale prediction of CO₂ capture, utilization and storage technologies in China. Pet. Explor. Dev.; 2023; 50, pp. 751-764. [DOI: https://dx.doi.org/10.1016/S1876-3804(23)60425-2]

79. Eccles, J.K.; Pratson, L.; Newell, R.G.; Jackson, R.B. The impact of geologic variability on capacity and cost estimates for storing CO₂ in deep-saline aquifers. Energy Econ.; 2012; 34, pp. 1569-1579. [DOI: https://dx.doi.org/10.1016/j.eneco.2011.11.015]

80. Godec, M.L.; Riestenberg, D.; Cyphers, S. Potential issues and costs associated with verifying CO₂ storage during and after CO₂-EOR. Energy Procedia; 2017; 114, pp. 7399-7414. [DOI: https://dx.doi.org/10.1016/j.egypro.2017.03.1870]

81. Xu, Z.F.; Ma, L.W.; Li, Z. Cost Assessment of Carbon Dioxide Capture and Storage in China, China Society for Power Engineering (CSPE). Youth Academic Annual Meeting. 2009; Available online: https://d.wanfangdata.com.cn/conference/7013149 (accessed on 10 March 2025).

82. Reeves, S.R. Assessment of CO₂ Sequestration and ECBM Potential of US Coalbeds; Advanced Resources International, Incorporated: Arlington, VA, USA, 2003; [DOI: https://dx.doi.org/10.2172/923256]

83. Tayari, F.; Blumsack, S.; Dilmore, R.; Mohaghegh, S.D. Techno-economic assessment of industrial CO₂ storage in depleted shale gas reservoirs. J. Unconv. Oil Gas Resour.; 2015; 11, pp. 82-94. [DOI: https://dx.doi.org/10.1016/j.juogr.2015.05.001]

84. Schmelz, W.J.; Hochman, G.; Miller, K.G. Total cost of carbon capture and storage implemented at a regional scale: Northeastern and midwestern United States. Interface Focus; 2020; 10, 20190065. [DOI: https://dx.doi.org/10.1098/rsfs.2019.0065]

85. Welkenhuysen, K.; Meyvis, B.; Swennen, R.; Piessens, K. Economic threshold of CO₂-EOR and CO₂ storage in the North Sea: A case study of the Claymore, Scott and Buzzard oil fields. Int. J. Greenh. Gas Control.; 2018; 78, pp. 271-285. [DOI: https://dx.doi.org/10.1016/j.ijggc.2018.08.013]