Risk Assessment of International Seabed Mining Implementing the Analytic Hierarchy Process

Abstract

The international seabed area (“the Area”) harbors abundant metal mineral resources that are critical to address global metal supply–demand and sustainable development. However, exploitation of mineral resources in the Area faces complex risks spanning politics, economy, technology, science, environment, society, industry, and law. No commercial-scale deep-sea mining operations have been conducted to date. Systematic risk identification and prioritization can inform strategic planning for stakeholders. This study employs literature analysis and an 80-expert questionnaire to identify key risk factors affecting mineral exploitation in the Area. Using the Analytic Hierarchy Process (AHP), we quantitatively assess the relative importance and weightings of these risks. Our results indicate that Level 1 risk groups prioritize (1) policy and public opinion risk, (2) extended continental shelf (ECS) delineation risk, (3) high sea marine protected areas (HSMPAs) establishment risk, and (4) mining area economic value risk. The five most critical Level 2 risk factors are (i) policy changes in contractor states, (ii) ECS-mining area boundary conflicts, (iii) environmental provisions in exploitation regulations at the international seabed (ER), (iv) ER implementation delays, and (v) mineral resource uncertainty. These findings provide actionable insights for contractors, policymakers, and stakeholders to optimize decision making in deep-sea mining projects.

1. Introduction

The international seabed area (“the Area”), defined as the seabed and ocean floor and subsoil thereof, beyond the limits of national jurisdiction under the United Nations Convention on the Law of the Sea (UNCLOS), hosts commercially significant mineral deposits including polymetallic nodules, seafloor massive sulfides, and cobalt-rich ferromanganese crusts [1,2]. These resources, legally designated as the “common heritage of mankind”, hold strategic importance for global energy transition technologies and sustainable development initiatives [3,4,5]. However, its operation faces multilayered risks. Current challenges stem from two primary dimensions. (1) Regulatory frameworks governing resource exploitation are incomplete, and there is limited scientific understanding of deep-sea ecosystem responses to mining [6,7]. Due to these concerns, some Pacific Island nations are advocating for a pause in deep-sea mining activities [8,9,10]. (2) There are emerging governance conflicts arising from extended continental shelf (ECS) claims and the accelerated establishment of high seas marine protected areas (HSMPAs) [11,12]. Additionally, the accelerating development of seabed mining has become enmeshed in contentious geopolitical dynamics and ethical paradoxes. Recently, the United States issued an executive order to expedite mining permit approvals in both U.S. and international waters, in accordance with the 1980 Deep Seabed Hard Mineral Resources Act [13,14,15]. This situation highlights the global competition for seabed mineral resources and the complex interplay between national interests and the “common heritage of mankind” principle. To systematically analyze these challenges, this study employs literature analysis and expert consultation to identify critical risk factors. Through Analytic Hierarchy Process (AHP) modeling, we quantitatively assess risk factor weights. This study provides crucial insights for stakeholders by enhancing their understanding of the potential risks associated with international seabed mining.

Although commercial-scale operations remain unrealized, technological advancements have demonstrated technical feasibility—notably, through the successful recovery of 3000 metric tons of polymetallic nodules during pilot tests [16]. This study aims to address these complexities by the AHP to identify and quantify key risk factors, providing a structured methodology for stakeholders to navigate the uncertainties associated with international seabed mining activities [17].

In the mining industry, the AHP is widely employed because it can simplify complex problems into simple hierarchical structures and calculate the weights of each level indicator through fuzzy quantification methods [18,19,20]. This method effectively resolves issues of non-comparability among different factors and enhances the reliability of subjective judgments through consistency checks. By quantifying the experience and insights of evaluators, the AHP is particularly suitable for situations where the target structure is complex and lacks data [21]. In the context of international seabed mining, where multiple risk factors interact and data availability is limited, the AHP’s ability to handle complex hierarchical structures and subjective judgments makes it an ideal tool for risk assessment and management.

2. Methods

In this study, risk factors associated with international seabed mining are categorized into four groups based on literature review and expert interviews: (1) policy and public opinion risk, which captures the critical influence of legislative changes and societal attitudes on the feasibility of mining projects; (2) extended continental shelf (ECS) delineation risk, concerned with potential jurisdictional disputes from national continental shelf claims overlapping with mining areas; (3) high seas marine protected areas (HSMPAs) establishment risk, highlighting the impact of growing environmental concerns and new protected areas on mining operations; and (4) mining area economic value risk, which reflects uncertainties in resource valuation and market conditions that can significantly affect the economic viability of mining ventures. The selection criteria for risk factors focused on their potential impact on seabed mining operations, their frequency of mention in prior studies, and their relevance to current policies and technological advancements, and a comprehensive risk assessment index system is constructed (Figure 1). AHP is applied to quantify the relative importance relationships among the risk factors. The basic steps of the research are illustrated in Figure 2.

2.1. Importance Questionnaire of Risk Factors

An offline questionnaire was administered during the “2nd Hainan Free Trade Port International Science and Technology Innovation Cooperation Forum & Deep-Sea Science and Technology Innovation Conference: Sub-forum on the Frontiers of Science and Technology in the Development and Utilization of Deep-Sea Mineral Resources”. A total of 80 valid responses were collected from 23 research institutes and enterprises. The respondents represented diverse professional backgrounds, including industry, academia, research, and application. Specifically, 46 respondents held professional titles, 20 were early-career researchers, 7 were graduate students, and 7 were business managers (Figure 3). Furthermore, 49 respondents had over five years of work experience in the marine field, and 46 possessed direct experience in deep-sea mining research (

Table 1. The basic statistic of the respondents.

Socio-Economic Characteristics of the Respondents		Observations
Years of experience in marine research	2–5 years	31
	More than 5 years	49
Ever engaged in deep-sea mining	Yes	46
	No	34

). The affiliations of the respondents are presented in

Table 2. The affiliations of the respondents.

Work Unit	Location	Observations
Changsha Research Institute of Mining and Metallurgy Co., Ltd.	Changsha, China	11
Ocean University of China	Qingdao, China	8
China State Shipbuilding Corporation Limited (CSSC)	Shanghai, China	7
Shanghai Jiao Tong University	Shanghai, China	6
Hunan University	Changsha, China	5
CCCC Dredging (Group) Co., Ltd.	Shanghai, China	4
Guangzhou Marine Geological Survey	Guangzhou, China	4
Zhejiang University	Hangzhou, China	4
Tianjin University	Tianjin, China	4
China University of Geosciences, Beijing	Beijing, China	3
China University of Geosciences, Wuhan	Wuhan, China	3
Technical Institute of Physics and Chemistry, Chinese Academy of Sciences	Beijing, China	3
Dalian Maritime University	Dalian, China	3
Administrative Centre for China’s Agenda 21 (ACCA21)	Beijing, China	3
Development Research Center, China Geological Survey	Beijing, China	2
Second Institute of Oceanography, Ministry of Natural Resources	Hangzhou, China	2
Northeast Petroleum University	Harbin, China	2
First Institute of Oceanography, Ministry of Natural Resources	Qingdao, China	1
Third Institute of Oceanography, Ministry of Natural Resources	Xiamen, China	1
Ningbo Municipal Bureau of Ocean Economic Development	Ningbo, China	1
Qingdao Institute of Marine Geology	Qingdao, China	1
Hunan University of Science and Technology	Xiangtan, China	1
Zhejiang Hanlu Subsea Engineering Technology Co., Ltd.	Hangzhou, China	1

.

2.2. Risk Factor Weight Calculation Based on AHP

The AHP is a systematic and hierarchical analysis method that combines qualitative and quantitative methods and is highly practical in addressing complex decision-making problems [22]. The basic steps include establishing a hierarchical structure model, constructing pairwise comparison matrices, calculating weight vectors, and conducting consistency checks [23]. This article employs AHP to determine the weights of the indicators. The specific process and steps are as follows:

(1) Establish a hierarchical structure model

The AHP model is structured into three levels: the target layer, the Level 1 indicator layer, and the Level 2 indicator layer. The complete hierarchical framework is in Figure 1.

(2) Construct pairwise comparison matrices

At this stage, factors at the same level are compared pairwise using a judgment scale ranging from 1 to 9 (

Table 3. The criterion of the effect of risk.

Intensity of Importance	Definition
1	Equal importance
3	Somewhat more important
5	Much more important
7	Very much more important
9	Absolutely more important
2, 4, 6, 8	Intermediate values between the two adjacent judgments
inverse	If the ratio of index Bi over Bj is aij, the ratio of Bj over Bi is aji = 1/aij

) [22]. The scale is defined as follows:

By systematically comparing each pair of factors according to this scale, an n-order comparison judgment matrix $A$ is constructed:

$$A=\left[\begin{array}{cccccc}{a}_{11}& a_{12}& a_{13}& ·& ·& a_{1n}\\ a_{21}& a_{22}& a_{23}& ·& ·& a_{2n}\\ a_{31}& a_{32}& a_{33}& ·& ·& a_{3n}\\ ·& ·& ·& ·& ·& ·\\ ·& ·& ·& ·& ·& ·\\ a_{n1}& a_{n2}& a_{n3}& ·& ·& a_{nn}\end{array}\right]$$

(1)

(3) Merge judgment matrix using the geometric mean method

This integrated matrix $\overline{A}$ represents a consensus judgment. When evaluations are provided by k experts (k = 1, 2, … m), the individual judgment matrices are aggregated. For each element, the geometric mean is calculated as follows:

$$\overline{A}=(\prod _{k=1}^m{a}_{ij}^k{)}^{{\displaystyle \frac{1}{m}}}$$

(2)

(4) Calculate the relative weight of the judgment matrix

The weights of the integrated unique matrix are calculated using the geometric mean method, as follows:

$$W_i={\displaystyle \frac{(\prod _{j=1}^n{a}_{ij}{)}^{\frac{1}{n}}}{\sum _{i=1}^n(\prod _{j=1}^n{a}_{ij}{)}^{\frac{1}{n}}}},\hspace{1em}i=1,2,3\dots ,n$$

(3)

(5) Conducting a consistency check

Experts may reach inconsistent conclusions when comparing indicators pairwise, so it is necessary to conduct consistency checks on the judgment matrices to ensure the rationality of the indicator weights [19]. The consistency ratio ($CR$) measures the degree of consistency in the judgment matrix. A $CR$ value closer to 0 indicates higher consistency in the matrix. If $CR$ < 0.1, the judgment matrix passes the consistency check; otherwise, the matrix needs to be reconstructed. The calculation formula for $CR$ is shown in Equation (4).

$$CR={\displaystyle \frac{CI}{RI}}={\displaystyle \frac{{\lambda }_{max}-n}{(n-1)RI}}<0.1$$

(4)

$CI$ represents the consistency index, and the formula is as follows (5). $RI$ represents the random consistency index. The value of the random consistency index $RI$ depends on the order $n$ of the judgment matrix as shown in

Table 4. The value of the random consistency index RI.

Matrix order	1	2	3	4	5	6	7	8	9	10
RI	0	0	0.52	0.89	1.12	1.26	1.36	1.41	1.46	1.49

[24].

$$CI={\displaystyle \frac{{\lambda }_{max}-n}{(n-1)}}$$

(5)

${\lambda }_{max}$ is the maximum eigenvalue of the judgment matrix, calculated using Equation (6), where $\overline{A}$ is the integrated judgment matrix, $W$ is the weight vector, and ${\left[\overline{A}W\right]}_i$ is the i-th component of the matrix $\left[\overline{A}W\right]$.

$${\lambda }_{max}=\sum _{i=1}^n{\displaystyle \frac{{\left[\overline{A}W\right]}_i}{{nW}_i}}$$

(6)

Through these steps, the AHP method quantitatively determines the weights of risk factors, thereby supporting a structured and consistent decision-making process.

3. Results

Figure 4 illustrates that, at the Level 1 indicator layer, policy and public opinion risk is the most critical group, with a weight of 42.37%. ECS delineation risk follows at 27.76%, while HSMPAs establishment risk accounts for 15.58%. In contrast, mining area economic value risk is deemed the least important, with a weight of 14.30%. These findings indicate that respondents believe the development of international seabed mining is strongly influenced by both international and domestic policies, regulations, and the prevailing public opinion.

At the Level 2 indicator layer, the global weight of each risk factor is determined by multiplying the local weight of the secondary indicator by the weight of its corresponding primary indicator, thereby reflecting its overall impact on international seabed mining development [21]. As shown in Figure 5, “policy changes in contractor states” is the most influential factor, with a global weight of 16.72%. This is followed by “ECS-mining area boundary conflicts” and “environmental provisions in exploitation regulations at the international seabed (ER),” with global weights of 14.13% and 9.88%, respectively. Additionally, the risk factor “mineral resource uncertainty” ranks fifth, with a global weight of 7.36%.

4. Discussion

A new phase in international seabed development has emerged, with numerous countries actively promoting the exploration of deep-sea resources. To date, 21 government and private contractors have signed 30 exploration contracts with the International Seabed Authority (ISA), covering resources such as polymetallic nodules, polymetallic sulfides, and cobalt-rich ferromanganese crusts [25]. The ISA is anticipated to issue the “exploitation regulations at the international seabed” by 2025, marking a significant milestone toward the commercialization of deep-sea mining [26]. Notably, The Metals Company (a Canadian firm), successfully collected 3000 tons of nodules during a sea trial in 2022 and plans to commence commercial extraction by the end of 2025 [16]. This study enhances stakeholders’ understanding of the potential risks associated with international seabed mining and provides decision-support tools for mining contractors and policymakers in this emerging industry.

4.1. Policy and Public Opinion Risk

Policy and public opinion risk is the most critical risk category in deep-sea mining. Within this group, “policy changes in contractor states” is identified as a pivotal secondary indicator, with a local weight of 39.35%, thereby significantly influencing the advancement of international seabed mining. Currently, several countries—including Brazil, Canada, Denmark, France, Fiji, Germany, Mexico, and the United Kingdom—have advocated for a moratorium or a complete ban on commercial deep-sea mining [27,28]. This trend indicates a withdrawal of supportive policies and tax subsidies, thereby heightening the associated risks. Moreover, the environmental protection clauses within ER and their precise implementation schedules remain ambiguous, resulting in a lack of clear guidelines for project planning, resource exploration, mining technology development, and environmental impact monitoring [29,30]. Although “public opposition to seabed mining” has a relatively modest local weight of 8.97%, public sentiment can substantially influence policy, regulatory frameworks, legitimacy, and social acceptance and even contribute to project resistance. For instance, mobilization by the Deep Sea Conservation Coalition significantly affected certain national positions, as evidenced by the French National Assembly’s resolution advocating a pause in deep-sea mining activities [27,31]. Additionally, members of Greenpeace International have boarded mining vessels to protest The Metals Company’s trial mining activities [32].

4.2. ECS Delineation Risk

ECS delineation risk ranks as the second most important risk group. Coastal states may extend their continental shelf boundaries under UNCLOS, potentially triggering international legal disputes and political conflicts. Such actions pose direct threats to the exploitation rights of international seabed mining contractors. Among the factors, “ECS-mining area boundary conflicts” is a critical secondary indicator, accounting for 50.72%. Generally, as the geographical overlap between the external limits of delimitation cases and mining areas increases, the risk of contractors losing their development rights rises accordingly. For example, in 2018, Brazil submitted a revised delimitation case, using the “Submarine Ridges and Elevations” delimitation principle to include the Rio Grande Rise within its continental shelf, where the ISA-approved Brazilian cobalt-rich ferromanganese crust contract area is located [33]. The Commission on the Limits of the Continental Shelf (CLCS) examines submissions in the order they are received. Furthermore, the commission’s consideration of a submission is based mainly on the regional geology and geography of the claimed area, the natural prolongation of the landmasses and the rights of countries bordering the continental shelf, the determination of the foot point of slope (FOS) and the outer edge of the continental margin, the determination of the outer limit of the continental shelf, and other considerations [34]. Therefore, when assessing the ECS delineation risk, factors such as “scientific validity of ECS submissions”, “legal compliance of ECS submissions”, and “ECS submission review timelines” also need to be considered. For instance, Myanmar’s delimitation case was delayed due to objections from Bangladesh, and such cases, prone to disputes or delays, have relatively limited direct impacts on the exploitation rights of mining areas [35].

4.3. HSMPAs Establishment Risk

HSMPAs establishment risk ranks as the third most important risk group. The “Kunming-Montreal Global Biodiversity Framework” has set an ambitious target to protect 30% of the world’s oceans by 2030, commonly referred to as the “3030 goal” [36]. In parallel, the Agreement on the Conservation and Sustainable Use of Marine Biodiversity in Areas Beyond National Jurisdiction Under UNCLOS (BBNJ), has made significant progress [37]. These have facilitated the rapid establishment of HSMPAs, challenging traditional notions of high seas freedoms and introducing more stringent regulations on activities such as deep-sea mining [38,39,40]. Among the factors contributing to HSMPAs establishment risk, “HSMPAs-mining area boundary conflicts” and “HSMPAs mining activity prohibitions” hold local weights of 40.71% and 31.13%, respectively. The greater the overlap between mining areas and potential HSMPAs, and the stricter the regulations imposed by these protected areas on mining activities, the higher the environmental protection costs for mining development. In extreme cases, this could lead to the complete suspension of development activities. The Convention on Biological Diversity (CBD) has designated 321 ecologically or biologically significant areas (EBSAs) globally, some of which overlap or partially overlap with international seabed mining areas [41]. Under the impetus of the BBNJ agreement and the “3030 goal”, if these EBSAs are widely converted into HSMPAs, it could greatly restrict the development of international seabed mining. The environmental impacts of deep-sea mining activities are extensive and complex. Plumes, noise, and light pollution from mining operations may affect areas crucial for biodiversity and ecosystem services, raising direct regulatory risk [7,42,43]. However, if the establishment of potential high seas marine protected areas (HSMPAs) is anticipated to occur later, contractors may have more time to adjust their strategies and develop technologies with lower environmental impact, thereby relatively reducing development risks.

4.4. Mining Area Economic Value Risk

Mining area economic value risk is considered a smaller factor, but this risk should not be overlooked. Although technological advancements have made the exploitation of deep-sea mineral resources possible, the high investment required still makes its economic feasibility uncertain [44]. The Solwara 1 project by Nautilus Minerals in Papua New Guinea was approved in 2011 and became the only project to receive commercial-scale mining permission [45]. However, due to issues with the procurement of vessels, finances, and corporate problems, as well as opposition from the community and civil society, the project was canceled in 2019 [46,47]. The failure of the Solwara 1 project has heightened concerns about the feasibility of deep-sea mining. In assessing the economic risks associated with international seabed mining, “mineral resource uncertainty” emerges as a significant factor, with a local weight of 51.52%. During exploration, limitations in technology, equipment, and budget constraints can result in incomplete data collection, affecting the accuracy of resource assessments and potentially leading to lower-than-expected exploitable resources. Additionally, high initial investments and operational costs impose financial burdens and pressure on profit margins. The environmental impacts of deep-sea mining have a wide-ranging scope [42,43]. Mining companies may be required to implement stricter environmental protection measures, conduct extensive environmental monitoring, and possibly compensate for any environmental damage. These additional costs could increase the operational costs and impact the economic viability of deep-sea mining projects [48,49]. Fluctuations in mineral prices further complicate return-on-investment predictions. Collectively, these challenges pose significant obstacles to the economic feasibility and sustainable development of deep-sea mining projects.

Compared with terrestrial mining and offshore energy development, international seabed mining has unique risk characteristics. Terrestrial mining mainly deals with resource depletion, environmental destruction, and community conflicts [50], while offshore energy development is influenced by marine environmental conditions and energy market price fluctuations [51,52]. In contrast, international seabed mining not only faces technical challenges but also has to deal with complex international regulations, policy uncertainties, and public pressure [53]. For instance, international seabed mining raises questions about deep-sea ecosystem protection and the ethical implications of exploiting a commons resource [13,14,15]. Our study offers a comprehensive analysis of the risks linked with international seabed mining, delivering a robust foundation for devising targeted solutions. As shown in Figure 5, “Policy changes in contractor states” is the most influential factor, with a global weight of 16.72%. Therefore, policymakers need to fully consider the impact of legislation and its implementation on mining investments. The situation in Turkey serves as a cautionary example, where mining firms have experienced substantial investment losses attributable to EIA legislation and administrative practices within mining permit processes [48,49]. Additionally, the ISA grants contractors the ownership of minerals extracted from the international seabed. In return, contractors are required to pay royalties to the Authority for the mineral-bearing ore [54]. The ISA can reduce international seabed mining risks and enhance stakeholder acceptance by using mining royalties to fund eco-friendly mining technology research and support infrastructure, education, and healthcare initiatives in developing countries [55,56].

5. Conclusions

International seabed mining has been spurred by the need for critical metals to support growing populations, urbanization, high-technology applications, and the development of a green-energy economy. Risks such as policy and public opinion, ECS delimitation disputes, HSMPAs establishment, and an insufficient understanding of the economic value of mining zones all hinder the commercial development of international seabed mining currently. This study identifies the unfavorable factors in the development of international seabed mining and conducts a quantitative analysis of their importance using the AHP. The results can provide a foundation for scientific decision making in project risk management.

For policymakers, strengthening international cooperation and establishing transparent regulatory frameworks to balance stakeholders’ interests are crucial for sustainable seabed mining. Mining contractors should enhance risk management, communicate with stakeholders, and adopt eco-friendly technologies to boost economic benefits and minimize environmental impacts. Researchers need to deeply explore seabed mining’s environmental impacts and better policies, offering scientific support for the industry’s sustainable growth.

This study has some limitations. The relatively small expert sample in the questionnaire survey might restrict the results’ generalizability. The risk assessment index system and AHP model depend on expert subjective judgments, which can bring in biases. While the study focuses on international seabed mining risk assessment, it does not provide specific solutions for these risks. In future research, we plan to integrate the risk assessment process into the “GeoGPT” geoscience model [57] and use natural language processing to gather richer information to improve the risk assessment index system. Online surveys will expand the expert sample to enhance result representativeness. Additionally, detailed case studies of actual seabed mining projects will be conducted to offer comprehensive insights into international seabed mining risks and develop more effective risk management strategies.