Promoting synergies and mitigating trade-offs: governance conditions in climate action and SDG interactions

Abstract

The Sustainable Development Goals (SDGs) represent an indivisible agenda in which interactions among goals—synergies and trade-offs—must be managed. While substantial progress has been made in quantitative modeling and network analysis of SDG interactions, systematic evidence drawn from empirical policy cases remains limited, leaving a persistent knowledge gap between theoretical analysis and on-the-ground practice. This study screened 128 empirical case study papers cited in Chapter 3.4 of the IPCC Sixth Assessment Report (AR6) Synthesis Report (SYR), which addresses long-term interactions among adaptation, mitigation, and sustainable development. Papers were classified into five domains—energy and power; land use, forests, and agriculture; urban, transport, waste, and local governance; industry, supply chains, and circular economy; and governance—and systematically analyzed for synergies, trade-offs, enabling factors, and remaining challenges. Findings indicate that synergies consistently arise not from single measures but from cross-sectoral policy integration, long-term institutional frameworks, multi-criteria assessment, inclusive stakeholder engagement, and aligned incentive structures. Trade-offs, by contrast, were consistently associated with institutional fragmentation, asymmetric power and resource distribution, short-termism, and incoherent policy mixes rather than appearing as inevitable outcomes. Five key driving forces for synergy promotion and trade-off mitigation were identified: policy objective integration, inclusive governance and redistribution of agency, long-term vision and time horizon reorientation, incentive structure redesign, and institutional capacity for learning and adaptation. This study advances the literature by moving beyond descriptive mapping of SDG interactions to a mechanism-oriented analysis that explains how policy design and governance arrangements shape or mitigate these interactions in practice. These findings suggest that the most impactful leverage points reside in deep systemic properties—governance structures, decision-making rules, and dominant development paradigms—rather than in isolated technical or policy interventions, and that strategic combinations of shallow and deep interventions are required to enhance both effectiveness and political feasibility in SDG implementation.

1 Introduction

The Sustainable Development Goals (SDGs) represent a comprehensive framework adopted by the United Nations to promote integrated development across economic, social, and environmental dimensions. Achieving the SDGs requires not only pursuing each goal individually but also understanding and managing interactions among goals—namely synergies and trade-offs (Nilsson et al., 2016; Nilsson et al., 2018). The 2030 Agenda explicitly emphasizes that the SDGs are “integrated and indivisible,” balancing the three dimensions of sustainable development (United Nations General Assembly, 2015). This perspective emerged in response to policy fragmentation observed during the MDGs era (Vandemoortele, 2011), and interaction management has become a central challenge in SDG implementation.

Related discussions have also developed through concepts such as co-benefits, interlinkages, and nexus approaches (Mayrhofer and Gupta, 2016; Young, 2002; Hoff, 2011). Co-benefit research has primarily focused on the secondary positive effects generated by climate or environmental policies, such as health improvements or economic gains accompanying mitigation measures (Mayrhofer and Gupta, 2016). Interlinkage research, particularly from the late 1990s onward, emphasized coordination and interaction among multilateral environmental agreements (MEAs) and international institutional frameworks (Young, 2002; Oberthür and Gehring, 2006). Nexus approaches, meanwhile, have highlighted interdependencies among sectors and resources, particularly within water-energy-food systems (Hoff, 2011). Together, these approaches have contributed to broader recognition of the interconnected nature of sustainability challenges across environmental, social, and economic domains.

Early research was systematized through the framework of Nilsson et al. (2016), who qualitatively analyzed relationships between individual SDGs and assessed interactions using a seven-point scale model. Subsequently, Pradhan et al. (2017) constructed a global correlation matrix of inter-goal relationships using UN statistical data, quantitatively demonstrating that synergies tend to outweigh trade-offs at the global level (Pradhan et al., 2017). These findings have been incorporated into major international assessment reports, including the Global Sustainable Development Report (GSDR) and the IPCC Sixth Assessment Report, and into international policy documents as scientific evidence. Furthermore, Anderson et al. (2022) developed a systems model based on SDG indicator data to visualize second- and higher-order effects across multiple goals. Their results revealed that gender equality (SDG 5) and partnerships (SDG 17) function as levers that facilitate the achievement of other goals, while the reduction of inequalities (SDG 10) and institutional stability (SDG 16) may act as potential hurdles.

In parallel, research has focused on the linkages between climate action centered on SDG 13 (Climate Action) and other goals. Fuso Nerini et al. (2019), writing in Nature Sustainability, demonstrated that while the impacts of climate change can hinder the achievement of 16 SDGs, adaptation and mitigation actions can strengthen all 17 SDGs—while also noting that trade-off risks exist for 12 goals. These analyses position climate change action as a driving force for SDG achievement and highlight the importance of governance design that accounts for the intensity and directionality of interactions. Additionally, Pham-Truffert et al. (2020) and Weitz et al. (2018) employed network analysis to map the influence structures among goals, proposing the need to redefine policy priorities.

More recently, analysis of synergies and trade-offs has also advanced from a comprehensive perspective encompassing the relationship between ecosystems and human well-being. In particular, IPBES (Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services) (2024) has warned that while integrated policies combining biodiversity conservation, land use, and climate action are associated with synergies across multiple goals—including social inclusion, health, and poverty reduction—structural trade-offs may arise with short-term resource-intensive development approaches.

Collectively, these bodies of research have provided strategic insights into understanding SDG interactions and maximizing synergies while minimizing trade-offs within policy, institutional, and governance frameworks. However, much of the existing literature remains confined to specific sectors or national/regional scales, and studies that systematically extract and synthesize enabling factors and remaining challenges through empirical case comparisons are limited. Against this background, this study pursues the following objectives: to systematically organize existing policy measures and practical initiatives, to identify the enabling factors and remaining challenges derived from these cases, and—on this basis—to extract and conceptualize the key driving forces that foster synergies and mitigate trade-offs among the SDGs. Through this process, the study aims to present a theoretical foundation for integrated policy design and implementation mechanisms.

2 Research objectives and research questions

As discussed in the preceding section, research on interactions among the SDGs has advanced through quantitative model analysis (Pradhan et al., 2017), systems dynamics visualization (Anderson et al., 2022), and the elucidation of network structures (Weitz et al., 2018). However, efforts to systematically extract enabling factors and remaining challenges from actual policies and projects and translate them into policy implications remain limited (Fuso Nerini et al., 2019; Pham-Truffert et al., 2020). This gap has been recognized as a “knowledge gap” between theoretical analysis and on-the-ground practice (IPBES (Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services), 2024).

These questions are intended to address the case dependence frequently noted in SDG implementation research, aiming to extract mechanisms transferable across contexts while grounded in specific cases.

3 Research methodology

Research on SDG synergies and trade-offs has accumulated across countries and regions (e.g., Nilsson et al., 2016; Pradhan et al., 2017; Singh et al., 2018). However, much of this work captures inter-goal relationships at a macro level through quantitative assessments and models, and studies examining individual cases in detail remain relatively scarce. Moreover, papers that explicitly employ keywords such as SDGs, synergies, and trade-offs to systematically examine their effectiveness and implementation barriers are limited. Many studies focus on specific domains—such as climate change policy, energy policy, or land use management in particular countries or regions—and do not adopt a fully integrated SDG perspective. Consequently, relying solely on systematic review methods that search academic databases using these keywords has limitations in capturing cases that explicitly address SDG synergies and trade-offs.

Against this background, this study focuses on the Intergovernmental Panel on Climate Change (IPCC) (2023) Sixth Assessment Report (AR6) Synthesis Report, which consolidates knowledge on SDG interrelationships. In particular, Chapter 3.4 of the Synthesis Report, “Long-Term Interactions Between Adaptation, Mitigation and Sustainable Development” (pp. 88–89), discusses long-term interactions among adaptation, mitigation, and sustainable development from an SDG perspective, encompassing the related sub-chapters 3.4.1 “Synergies and Trade-offs, Costs and Benefits” and 3.4.2 “Advancing Integrated Climate Action for Sustainable Development.” These sections present a theoretical and empirical framework for integrated approaches to climate action conducive to sustainable development, and the references cited therein include a diverse range of case studies.

Furthermore, the narrative of the Synthesis Report is reinforced by references to Working Group II (WGII) and Working Group III (WGIII) reports, as well as the Special Report on Climate Change and Land (SRCCL). These reports cite numerous case studies on adaptation, mitigation, and sustainability from various regions, and provide important insights for understanding the practical challenges of the SDGs by synthesizing these cases and presenting their policy implications.

Accordingly, this study screened primary sources cited in Chapter 3.4 and related sections of the IPCC AR6 Synthesis Report to identify empirical policy and practice cases. Relevant literature was extracted from the citation lists and organized according to its study region, thematic domain (e.g., climate policy, energy transition, land use, social inclusion), and relevance to the SDGs, before identifying analytical perspectives on synergies and trade-offs. This process aimed to identify research trends, limitations, and challenges for integrated policy design. To ensure consistency in study selection, the first and third authors developed and agreed upon a screening protocol based on the objectives and selection criteria of the review. Using this protocol, references cited in the IPCC AR6 reports were divided between the two authors and screened for empirical policy and practice cases. This process resulted in an initial pool of 588 potentially relevant studies. During the primary screening (title and abstract stage), the first and third authors independently assessed all 588 studies for inclusion based on the screening protocol. This process yielded 149 and 179 studies identified by the first and third authors, respectively. Intercoder agreement for these independent inclusion/exclusion decisions was substantial (Cohen’s kappa = 0.80; observed agreement = 91.8%). Cohen’s kappa is a chance-corrected measure of agreement between reviewers, with values above 0.60 generally indicating substantial agreement (Landis and Koch, 1977). After resolving disagreements through discussion, 148 studies were retained for the secondary screening. The secondary screening (full-text reading stage) subsequently applied the selection criteria described in Section 3.1. For papers where disagreements arose, the two authors held discussions and reached consensus on inclusion or exclusion, resulting in a final sample of 128 papers. This process minimized selection bias and enhanced consistency and transparency in study selection.

3.1 Selection criteria

Papers satisfying all of these criteria were prioritized for inclusion; however, policy evaluations targeting specific policies or time periods and verifying their outcomes—including analyses of policy failures as well as successes—were also included. For studies involving cross-national comparisons, these were organized by regional groupings or policy domains with the aim of extracting cross-cutting trends. As a result, 128 papers were selected. The study screening and selection process is summarized in Figure 1.

Figure 1

The list of target papers is provided in the Supplementary Table S1. Because the review included heterogeneous qualitative, quantitative, mixed-methods, and policy evaluation studies, a formal quality appraisal was not conducted. Instead, methodological approaches were classified and reported transparently in Supplementary Table S1.

3.2 Classification of papers

The 128 selected papers cover a diverse range of domains, including energy, land use, urban development, industry, and institutional design. In this study, papers were classified into the following five categories based on the intervention domain and analytical focus of each paper (Table 1): (1) Energy and Power, (2) Land Use, Forests, and Agriculture, (3) Urban, Transport, Waste, and Local Governance, (4) Industry, Supply Chains, and Circular Economy, and (5) Policy and Governance.

In the classification process, papers whose analytical focus was placed on specific technologies, projects, land use practices, urban policies, or industrial systems were assigned to categories (1) through (4). In contrast, papers that addressed these domains but whose primary analytical focus was on institutional design, policy mixes, governance structures, policy effectiveness, governance failures, or institutional constraints—spanning national or multi-country/regional scales—were classified under (5) Policy and Governance.

That is, a defining feature of this classification is that while many papers in categories (1) through (4) carry policy and institutional implications, category (5) was established as an independent category on the basis of whether policy or governance itself constitutes the primary subject of analysis. For papers whose classification spanned multiple categories or was otherwise ambiguous, final classification was determined through discussion among the authors, based on interpretation of each paper’s analytical subject and focus. The number of papers in each category is shown in Table 1.

Regarding the identification of relevant synergies and trade-offs, the definitions follow the methodology of Anderson et al. (2022): synergies refer to cases where the outcomes of an intervention targeting one SDG goal also exert a positive influence on the achievement of other SDG goals, while trade-offs refer to cases where outcomes directed toward one goal negatively affect another. Where target papers did not explicitly reference SDG goals or indicators, cases were nonetheless included in the analysis as synergies or trade-offs if the outcomes of the intervention were judged to substantively correspond to the content of existing SDG goals and targets. The identification of synergies and trade-offs was based on an interpretive assessment of reported outcomes in relation to SDG targets. Interactions were identified by assessing whether interventions aligned with SDG targets. Furthermore, trade-offs are not treated as uniform phenomena. Based on the nature of their treatment in the original studies, they are further categorized into three types: (i) inherent trade-offs, which are identified as structurally embedded tensions without proposed mitigation mechanisms; (ii) mitigated trade-offs, where institutional, policy, or design interventions are presented as mechanisms to reduce or manage such tensions; and (iii) residual trade-offs, where tensions persist despite mitigation efforts. Furthermore, in this study, inherent trade-offs generally reflect underlying structural constraints, whereas mitigated and residual trade-offs indicate the extent to which institutional arrangements and governance processes influence the manifestation, distribution, or persistence of such tensions. This classification is reported in the Supplementary Table S1. A coding protocol specifying the unit of analysis, criteria for SDG alignment, definitions of synergies and trade-offs, and coding procedures was developed prior to the analysis and is provided in Supplementary Text S1. All coding decisions were based on the stated objectives of the intervention, its implementation characteristics, and the reported outcomes in each study. To reduce subjectivity, coding was independently conducted by two authors and subsequently cross-checked. Discrepancies were discussed and resolved through consensus. Coding was applied only when sufficient empirical, evaluative, or analytical support was identified in the original studies. This judgment was made by cross-referencing the intervention objectives, implementation content, and reported outcomes of each study against the intent and substantive content of relevant SDG goals and targets.

4 Results

4.1 Synergies and trade-offs

The literature reveals a wide range of synergies and trade-offs across sectors and SDG domains. While this review focuses on explicitly reported trade-offs for analytical consistency, some studies implicitly address potential tensions through institutional arrangements, policy design, or technological configurations without explicitly framing them as trade-offs.

4.1.1 Energy and power

The most consistent synergy in the energy and power literature is that the transition to low-carbon energy simultaneously promotes improved energy access, greenhouse gas reductions, and the modernization of industry and infrastructure. Specifically, through the introduction of renewable energy, the shift to low-carbon electricity, household energy reduction, and energy efficiency policies, a mutually reinforcing structure among SDG 7 (affordable and clean energy), SDG 13 (climate action), SDG 9 (industry, infrastructure, and innovation), and SDG 12 (responsible consumption and production) has been demonstrated across diverse contexts.

Studies demonstrating simultaneous achievement of SDG 7 and SDG 9 are concentrated in cases addressing structural transformation of power infrastructure and core industries (Cui et al., 2021; González-Mahecha et al., 2019; Rosenbloom, 2018). For example, a plant-level analysis of coal-fired power in China shows that the transition to a low-carbon electricity system can simultaneously achieve rational renewal of existing infrastructure and industrial structural transformation (Cui et al., 2021). Research focused on Latin America demonstrates that energy investments misaligned with decarbonization increase the risk of future stranded assets, thereby potentially undermining industrial and infrastructure competitiveness—suggesting that energy transition is also indispensable as industrial policy (González-Mahecha et al., 2019).

Regarding renewable energy, SDG 11 frequently co-occurs with SDG 7 and SDG 13. The deployment of renewable energy is not merely a means of electricity supply or emissions reduction, but also a process closely linked to community sustainability, urban and rural revitalization, and community cohesion and acceptance (Devine-Wright and Howes, 2010; Warren et al., 2005). Specifically, cases in which renewable energy projects promote the establishment of community funds, job creation, improvement of public infrastructure, and participatory decision-making have been reported (Aitken, 2010; Cass et al., 2010; Devine-Wright and Howes, 2010), and these are positioned as contributing to the formation of “inclusive and sustainable communities” emphasized by SDG 11. At the same time, renewable energy development is often accompanied by concerns over landscape impacts, land use competition, and effects on tourism and living environments. Potential trade-offs have also been identified with SDG 15 (life on land) through the impacts of large-scale development on terrestrial ecosystems (Bates and Firestone, 2015; Hernandez et al., 2015; Vince, 2010), with SDG 10 (reduced inequalities) regarding benefit/burden distribution and the information divide (Bradley et al., 2016; Schelly, 2014), and with SDG 16 (peace, justice, and strong institutions) in relation to CCS and BECCS (Backhouse and Lehmann, 2020; Schenuit et al., 2021).

4.1.2 Land use, forests, and agriculture

The most significant synergy across this literature is that improved management of natural resources and ecosystems simultaneously strengthens livelihoods, food security, and social well-being. Specifically, a mutually reinforcing structure among SDG 13 (climate action), SDG 15 (life on land), SDG 2 (zero hunger), and SDG 1 (no poverty)—achieved through forest conservation and regreening, soil management, water resource management, agroforestry, climate-smart agriculture, and community-led disaster prevention, fire management, and adaptation measures—has been demonstrated across regions, including the Amazon (Heilmayr et al., 2020; Nepstad et al., 2014), the Sahel (Haglund et al., 2011; Sendzimir et al., 2011; Tougiani et al., 2009), South and Southeast Asia (Jupesta et al., 2020; Khandker et al., 2014; Schoneveld et al., 2019), and rural Africa (Antwi-Agyei et al., 2018; Ighodaro et al., 2016).

Furthermore, where community participation, knowledge sharing, and institutional support are combined, synergies extend to education (SDG 4), gender equality (SDG 5), and local economies (SDG 8), with social synergies—such as enhanced women’s decision-making capacity, expansion of small-scale businesses, and income diversification—clearly observed (Ighodaro et al., 2016; Khandker et al., 2014). These studies demonstrate that protecting nature does not impede development; rather, with appropriate institutions, participation, and learning, it enables multiple SDGs simultaneously.

A recurring trade-off is the structural tension between short-term economic rationality, land use expansion, and infrastructure development on the one hand, and long-term ecosystem health and social equity on the other. Road construction, agricultural expansion, and the promotion of commodity crop production (e.g., soybeans, oil palm) are shown to contribute to SDG 8 (decent work and economic growth) and SDG 1 in the short term, while undermining SDG 13 and SDG 15 through deforestation and land degradation (Antwi-Agyei et al., 2018; Heilmayr et al., 2020; Jupesta et al., 2020; Khandker et al., 2014). Moreover, many studies identify inadequate institutional design and unequal access to power, education, basic infrastructure and information as factors that entrench trade-offs. Specifically, socio-institutional factors (Kongsager, 2017; Nasser et al., 2020; Nepstad et al., 2014) and the exclusion of smallholder farmers through market-driven policies (Montaña et al., 2016; Robalino and Pfaff, 2013) distribute the benefits and burdens of environmental conservation measures unequally, generating tension with SDG 10 (reduced inequalities). This literature suggests that trade-offs are not inevitable but are often associated with institutional and governance conditions, and can be mitigated or exacerbated depending on the design of policies.

4.1.3 Urban, transport, waste, and local governance

The urban domain repeatedly demonstrates co-benefit synergies in which a single measure simultaneously advances climate goals (SDG 13) and urban quality (SDG 11). Specifically, the following approaches recur: (1)simultaneously pursuing low-carbonization and community revitalization through citizen participation and local movements (Biddau et al., 2016); (2) targeting reductions in congestion and environmental burden alongside improvements in urban function through travel demand management (e.g., road pricing; Schuitema et al., 2010); and (3) enhancing livability and adaptive capacity while making environmental value visible through urban greening and green infrastructure (Mell et al., 2013). These reflect a design logic that bundles urban planning, transport, green space, and governance, placing SDG 11x SDG 13 at the core and generating synergies with related goals (e.g., SDG 3, SDG 8, and SDG 17).

Trade-offs related to equity, participation, and burden distribution recur. While transport pricing, urban redevelopment, and environmental regulations contribute to emissions reduction and urban improvement in aggregate, they tend to generate recurring patterns: the costs and benefits are unevenly distributed among specific groups, undermining public acceptance (Schuitema et al., 2010); the displacement of low-income residents and housing instability create tensions around just transition (Ma et al., 2018); and technology-centered environmental improvements risk widening social inequality and exclusion (Wiktorowicz et al., 2018). The common challenge in the urban domain is: that the further SDGs 13 and 11 are advanced, the more indispensable it becomes to simultaneously design for SDG 10 (reduced inequalities) and inclusive governance (SDGs 16 and 17).

4.1.4 Industry, supply chains, and circular economy

The key synergy across the four papers is that the transformation of industrial structures and production processes can simultaneously advance climate action (SDG 13) and industrial competitiveness and innovation (SDG 9). In the case of hydrogen direct reduction steelmaking (HYBRIT) in Sweden, the decarbonization of the steelmaking process was shown to contribute to national climate targets while simultaneously strengthening industrial competitiveness through the creation of a new “green steel” market (Kushnir et al., 2020). Similarly, industrial symbiosis in China’s eco-industrial parks (EIPs) and chemical industrial clusters—through the circular use of by-products, energy, and water—was shown to simultaneously achieve resource efficiency (SDG 12) and reduced environmental burden (SDG 13), while also contributing to cost reduction and stable operations for individual firms (Mathews et al., 2018). These cases consistently demonstrate that decarbonization and circularity can serve as sources of industrial system innovation rather than as environmental regulatory costs.

On the other hand, trade-offs surrounding institutions, infrastructure, and cost distribution represent the greatest constraints—more than technological feasibility. In HYBRIT, the tension between rising costs associated with hydrogen production and power infrastructure development (SDG 7) and price competitiveness and employment maintenance (SDG 8) is clearly identified (Kushnir et al., 2020). Likewise, in China’s industrial symbiosis and circular economy cases, while the system as a whole is efficient, distributional trade-offs persist in which specific firms or industries are disadvantaged in the short term due to high initial investment burdens and coordination costs (Mathews et al., 2018). Furthermore, research examining the expansion of circular economy businesses indicates that when institutional frameworks—such as waste regulations, recycling markets, and logistics infrastructure—are not sufficiently aligned, the implementation of circular business models may struggle to become economically viable. Under such conditions, tensions can arise between environmental improvements (SDGs 12 and 13) and firms’ profitability or investment recovery (Ranta et al., 2018). These findings suggest that synergies in the industrial sector depend on institutional conditions, including policy consistency, market structures, and the design of cost-sharing arrangements.

4.1.5 Governance, policy mix, and interactions

In terms of synergy patterns, multi-objective co-benefits cascading from decarbonization (SDG 13) to industrial upgrading (SDG 9), and resource efficiency and circularity (SDG 12) through combinations of institutional design, technological innovation, and financing mechanisms are frequently observed. Specifically, structural parallels are observed in the following: the way demand-side measures simultaneously enable emissions reduction and reduced dependence on negative emissions technologies (Wachsmuth and Duscha, 2019); the way city-level dedicated funds can catalyze low-carbon investment and accelerate urban transition (Peng and Bai, 2021); and the coherence of policy mixes that combine regulatory instruments, market mechanisms, and technological support can facilitate the low-carbon transition of industry (Scordato et al., 2018). Moreover, in forest, land use, and resource management contexts, some studies show that, under enabling institutional and governance conditions, ecosystem conservation (SDG 15) can be compatible with climate change measures (SDG 13; e.g., Roopsind et al., 2019).

Trade-offs converge around two tensions: (1) transition costs, infrastructure constraints, and the need for institutional coordination manifest as tensions between climate action (SDG 13) and energy systems (SDG 7) as well as industry and infrastructure (SDG 9; Wachsmuth and Duscha, 2019); and (2) governance and justice concerns, whereby conservation, decarbonization, and urban policies are repeatedly discussed as potentially generating tensions with equity and inclusiveness (SDG 10) as well as the livelihoods of vulnerable populations (SDG 1; Mehta et al., 2019; Riggs et al., 2018). Additionally, it is consistently shown that regulations, taxes, and market measures can generate short-term friction between environmental objectives (e.g., waste reduction) and the burdens placed on businesses and households (Carattini et al., 2018). Taken together, these findings converge on the conclusion that trade-offs are shaped not by policy objectives themselves but by implementation capacity (institutions, financing, and enforcement) and distributional design (who bears the costs and who receives the benefits) that determine the intensity of trade-offs.

4.2 Enabling factors

4.2.1 Energy and power

From the case studies in the energy and power domain, several common characteristics emerge as factors supporting synergies among the SDGs. Of particular importance is the explicit articulation of a long-term decarbonization vision—such as net zero by 2050—and the design of electricity mix and generation facility investment and retirement schedules in alignment with that vision. Research that evaluates existing coal-fired power plants on a plant-by-plant basis—examining which plants should be retired, and in what order, based on multiple indicators including efficiency, remaining lifespan, profitability, and environmental impact—demonstrates that plans working backward from long-term targets serve as a precondition for advancing renewable energy expansion while keeping stranded asset risks in check (Cui et al., 2021). It has also been shown that long-term planning combined with regulatory phase-out mechanisms is effective in achieving large-scale emissions reductions (Rosenbloom, 2018). Long-term vision and the institutional design aligned with it can be interpreted as enablers that anchor the overall direction of energy transition, rather than allowing it to remain a series of one-off projects.

A further common feature is the establishment of decision-making processes grounded in high-resolution data and multi-criteria assessment. Analyses that holistically evaluate power plants and transmission lines across dimensions including efficiency, utilization rates, payback periods, air pollution, and greenhouse gas emissions—incorporating social and environmental costs to determine retirement priorities and repowering candidates—enable planning that simultaneously keeps SDG 13 (climate action), SDG 7 (clean energy), SDG 3 and 11 (health and air quality), and SDG 12 (responsible consumption and production) in view. Research examining the siting of solar and wind power also employs an approach that overlays spatial data on land cover, protected areas, and biodiversity hotspots to assess both potential and environmental impact, identifying areas to avoid and low-impact priority locations (Hernandez et al., 2015). Such spatial information and multi-criteria assessment constitute an indispensable foundation for anticipating trade-offs between renewable energy expansion and ecosystem conservation.

The building of community-level organizations and trust relationships is also repeatedly emphasized as a factor underpinning renewable energy transition. In cases involving resident-led solar group-purchasing organizations and community energy companies, local organizations function as platforms for information sharing, joint procurement, and risk distribution, thereby reducing individual uncertainty and administrative burden (Noll et al., 2014; Schelly, 2014). Such frameworks support not only renewable energy deployment itself but also local networks and spaces for mutual learning, thereby generating synergies from the perspectives of SDG 7, SDG 11, and SDG 17. In addition, policy alignment—through instruments such as Energy Efficiency Resource Standards (EERS) that impose energy-saving obligations on utilities and regulators, and existing energy efficiency standards—operates as an incentive for embedding demand-side programs within corporate business models.

Furthermore, demand-side interventions that combine price incentives with visualization play a key role in supporting reductions in energy consumption and acceptance of renewable energy sources. Research on households and businesses shows that combining rate structures and monetary rewards with real-time visualization of electricity use and reduction outcomes, alongside behavioral science techniques such as social norm messaging and loss-aversion framing, facilitates the adoption of energy-saving behaviors (Allcott, 2011; Bradley et al., 2016; Ebeling and Lotz, 2015). These interventions function as enablers that simultaneously promote energy efficiency improvements (SDG 7.3) and shifts in consumption patterns (SDG 12).

What the above cases collectively reveal is that the enabling factors in the renewable energy domain cannot be reduced to specific technologies or a single policy instrument. Together, these cases suggest that SDG synergies emerge when long-term vision-based institutional design, high-resolution data and multi-criteria assessment, linkages with community organizations, and combinations of price incentives and behavioral interventions operate in a mutually reinforcing manner. In other words, the enablers surrounding renewable energy concern not merely the quantitative choice of which technologies to deploy and in what volume, but also the nature of integrated governance itself—under what rules and processes energy transition is advanced.

4.2.2 Land use, forests, and agriculture

From the case studies in the land use, forests, and agriculture domain, several common characteristics emerge as factors that realize synergies among the SDGs and mitigate trade-offs. Of particular importance is the existence of a clear institutional framework—such as forest laws and land use regulations—with a reasonably consistent enforcement record. Through continuous enforcement and sanctions linked to satellite monitoring against illegal logging and disorderly agricultural expansion, the simultaneous achievement of forest conservation (SDG 15) and climate change mitigation (SDG 13) has been made possible. Alongside this, policy designs that leverage economic incentives and market mechanisms play a role in repositioning environmental conservation from a perceived “burden” to a “benefit.” By introducing subsidies and results-based payments to support forest conservation and transitions to sustainable agriculture, compatibility between agricultural production (SDG 2) and poverty reduction (SDG 1), on the other hand, and environmental objectives, on the other, has been pursued. A further common feature across many cases is the combination of supply-chain-wide governance with co-management that draws on the agency and knowledge of local communities. Cutting across all of these is monitoring and targeting using satellite data and GIS, which enables policy targeting and evaluation.

For example, in cases of deforestation suppression targeting primarily the Brazilian Amazon, it is reported that combining forest law reform and strengthened monitoring with credit regulations that make public financing conditional on forest law compliance, and prosecuting companies involved in illegal logging, resulted in a significant reduction in deforestation rates (Nepstad et al., 2014; Azevedo et al., 2017). Here, it is not legal regulation alone, but the restructuring of incentive frameworks channeled through the financial sector that has driven changes in agro-pastoral business models. In supply chain initiatives exemplified by the Soy Moratorium, major buyers agreed not to purchase soybeans from newly deforested land, thereby advancing the decoupling of agricultural expansion and deforestation in the Amazon region (Gibbs et al., 2015). This collaboration among corporations, financial institutions, and government agencies to establish low forest-risk production as the standard across entire supply chains points to the potential synergy between forest protection and the promotion of agricultural production.

In cases from the Sahel and various parts of Africa, community-led natural regeneration and land use practices—such as Farmer Managed Natural Regeneration (FMNR) and agroforestry—have been shown to simultaneously achieve land degradation control and enhance farmer resilience. It has been reported that when farmers themselves formulate rules for tree protection and management, and share them through local organizations, this can enable compatibility between drought risk reduction (SDG 13) and livelihood improvement (SDG 1 and 2; Sendzimir et al., 2011; Tougiani et al., 2009). Such cases demonstrate that not only legal frameworks and market mechanisms, but also co-management that draws on local knowledge and social capital, constitutes an important enabling factor for synergies.

Overall, synergies in this domain emerge from the complementary interaction of regulatory frameworks, economic incentives, supply-chain-wide governance, community-based management, and monitoring systems, rather than from any single policy instrument.

4.2.3 Urban, transport, waste, and local governance

From the case studies in the urban, transport, waste, and local governance policy domain, several common enabling factors come to the fore as being associated with synergies among the SDGs while mitigating trade-offs. Of particular note is the presence of relatively clear and consistent institutional frameworks, such as urban transport policies, low-carbon urban strategies, and land use planning. Such frameworks enable experimental initiatives to be institutionalized and scaled up, rather than leaving them as isolated efforts. Also important is the establishment of cross-sectoral, multi-level governance in which diverse actors—including central government, local authorities, transport operators, private businesses, research institutions, and local communities—collaborate. In addition, making the effects of measures such as urban parks, green infrastructure, car-sharing, and congestion pricing visible through environmental, health, and economic indicators, and translating these outcomes into evidence-based policy decisions, is also positioned as a common enabling factor.

For example, Schuitema et al. (2010), analyzing Stockholm’s congestion charging scheme, note that institutionalizing it as a national-level congestion tax secured legal stability, and that a combination of pre-strengthening of public transport and a trial period—coordinated among the national government, the city, the road administration authority, and public transport operators—was key. The process in which citizens directly experienced reduced congestion and improved air quality, and subsequently voted to continue the scheme, exemplifies the mutual reinforcement of institutional frameworks, cross-sectoral collaboration, and strategic communication. Ghosh (2019), examining urban transport in India and Thailand, also shows that experiments with BRT and new mobility were enabled by national and city-level policies such as the National Urban Transport Policy and urban renewal missions, and that funding and knowledge support from international research networks and development assistance made it possible to sustain trial-and-error processes and achieve scale-up. Furthermore, Ma et al. (2018), analyzing Shanghai’s mobility transition, reveal that national strategies and urban planning related to EV uptake and shared mobility promotion were coherently designed, and that the shift away from private car dependence was advanced through incentives such as license plate restrictions and subsidies.

Similar patterns are evident in research on urban spatial governance. Kim and Coseo (2018), examining Phoenix’s urban park system, describe the process through which urban forestry was institutionalized as a policy simultaneously supporting climate action (SDG 13), health and well-being (SDG 3), and terrestrial ecosystem conservation (SDG 15)—anchored in a master plan positioning urban forests as a foundation for climate adaptation and public health improvement, and involving monetary valuation of ecosystem services through collaboration among the city, universities, federal agencies, and private firms. Wiktorowicz et al. (2018), studying an eco-district in Western Australia, show that the adoption of One Planet Living certification and co-governance involving the state government, city, research consortium, businesses, and resident organizations supported district-level low-carbonization integrating energy, water, transport, and housing. These cases—like the Ghanaian example of formally embedding urban agriculture within a food security strategy (Ayerakwa, 2017)—demonstrate that policy recognition and stakeholder alignment are indispensable for legitimizing informal initiatives as part of urban policy and unlocking synergies across multiple goals centered primarily on SDG 11 and SDG 13, with linkages to SDG 2 also observed in some cases.

Overall, the enabling factors in the urban, transport, waste, and local governance policy domain cannot be reduced to the merits of individual technologies or projects; rather, they must be understood as an integrated governance configuration in which long-term vision-based institutional frameworks, multi-actor and multi-level collaboration, and compelling communication mutually reinforce one another. When such a configuration is in place, individual measures such as congestion pricing, new mobility, green infrastructure, and urban agriculture can function not merely as one-off experiments but as components of urban transformation oriented toward the simultaneous achievement of multiple SDGs.

4.2.4 Industry, supply chains, and circular economy

From the case studies in the industry, supply chains, and circular economy domain, several common enabling factors stand out as supporting synergies among the SDGs. One is the existence of institutional frameworks—such as climate laws, circular economy promotion laws, eco-industrial park policies, and extended producer responsibility schemes—that clearly signal the direction toward low-carbonization and resource circulation, combined with aligned tax incentives, subsidies, and certification schemes. Alongside this, the involvement of multi-stakeholder networks—including national-level policy direction, local government implementation capacity, inter-firm networks, and researchers and civil society—helps create an environment in which new technologies and business models can be piloted while distributing risks and costs that no single firm could bear alone. Furthermore, the physical concentration and geographical proximity of industrial parks and clusters are also common features, as they facilitate the exchange of by-products, energy, and water, thereby improving the economic viability of industrial symbiosis.

For example, Kushnir et al. (2020), analyzing the transition to hydrogen direct reduction (H-DR) steelmaking in Sweden, identify as enabling factors: the clear decarbonization direction established by climate law and the EU ETS; the formation of a joint venture among mining companies, steel manufacturers, and electricity companies; and the establishment of a financing scheme combining government grants and private investment. Mathews et al. (2018), examining China’s circular economy transition, report that top-down policies—including five-year plans, the Circular Economy Promotion Law, and eco-industrial park certification schemes—served as a framework channeled through local governments to bundle inter-firm collaboration, technology adoption, and evaluation systems, resulting in reductions in energy intensity, water use, and waste generation across many industrial parks. Guo et al. (2016), studying a chemical industrial cluster in Xinjiang’s Wujiaqu, show that the concentration of chemical firms, inter-firm trust relationships, tax incentives and electricity tariff discounts, and triple-helix collaboration among researchers, government, and industry made the reuse of waste and by-products economically viable. Ranta et al. (2018), comparing the Nordic countries, China, the United States, and Europe, note that alongside robust legal frameworks and corporate governance, certifications and design awards for industrial symbiosis and circular products provide social legitimacy and serve as incentives for firms.

What emerges across these cases is that synergies in the industry, supply chains, and circular economy domain emerge from an institutional configuration comprising long-term policy frameworks, multi-stakeholder governance, industrial proximity, economic incentives, and social legitimacy, rather than from technologies or individual firm efforts alone.

4.2.5 Governance

From the governance case studies, several common enabling factors surface as supporting synergies among the SDGs. First, a common feature across many studies is that policy coherence and enforcement capacity determine whether synergies emerge. It has been shown that when institutions are rolled back through short-term political bargaining, not only are positive inter-goal linkages lost, but excessive burdens and high-cost responses can be transferred to other sectors; maintaining institutional credibility is therefore repeatedly identified as an enabling factor. Second, when regulations, market mechanisms, fiscal measures, and information provision are used in combination, more stable outcomes across multiple goals are observed when the respective roles and sequencing of these instruments are clear and they function in a mutually complementary manner. Third, embedding implementation conditions, including investment incentives and demand-side levers—within institutional design, and positioning the formation of social acceptance as an operational process rather than an afterthought, emerge as common enabling factors supporting implementation capacity.

For example, Rochedo et al. (2018), examining Brazil’s forest governance, show that where strong environmental governance can hold deforestation in check, not only does simultaneous progress on climate (SDG 13) and terrestrial ecosystems (SDG 15) become possible, but trade-offs that would impose excessive reductions and investments on other sectors—heightening dependence on immature technologies—can also be reduced. Here, enforcement capacity in the form of forest law implementation and command-and-control strengthening, and the maintenance of consistent long-term signals, are positioned as institutional conditions enabling synergies. Wachsmuth and Duscha (2019), focusing on demand-side measures, similarly show that centering demand-side options—sufficiency, efficiency, electrification, and fuel switching—in policy enables emissions reductions while limiting excessive dependence on negative emissions technologies, with robust sectoral standard-setting and clear demand-side levers identified as enabling factors.

From the perspective of market institutions, Grubb and Newbery (2018), examining the UK’s electricity market reform, discuss the importance of institutional design that makes investment viable. They show that rule designs—such as transmission network charging structures—can determine investment outcomes, suggesting that realizing low-carbonization requires governance design extending to the details of market rules, not only policy objectives. Regarding the tendency of policies to accumulate internal contradictions and lose substance over time, Rayner et al. (2017) note that treating policy mixes as evolving over a time horizon and repeatedly evaluating, revising, and redesigning them is itself an operational requirement, from which it can be inferred that building in continuous adjustment and learning—rather than one-off institutional introduction—constitutes an enabling factor. On the conditions for long-term transition, Bataille et al. (2020) show that the simultaneous pursuit of electrification and power sector decarbonization, access to low-carbon power sources, and a combination of multiple levers including modal shift constitute the conditions supporting a deep decarbonization transition.

Furthermore, from research on acceptance formation, process design that secures policy legitimacy and strengthens implementation capacity is confirmed as a common enabling factor. Eliasson (2014), examining congestion pricing, shows that “direct experience” through a trial reshapes attitudinal structures, with acceptance shifting before and after implementation, suggesting the importance of incorporating acceptance formation processes into institutional design. Carattini et al. (2018), examining waste taxation, also show that institutional experience can enhance acceptance, confirming that the effectiveness of regulations and taxes cannot be separated from the conditions for social acceptance.

Overall, synergies in the governance domain arise from the integration of policy coherence, enforcement capacity, complementary policy mixes, investment and demand-side levers, and social acceptance formation processes.

4.3 Remaining issues

4.3.1 Energy and power

Despite these enabling factors, several challenges remain. In the case of large-scale hydropower and transmission infrastructure, uncertainty is particularly pronounced with respect to multiple hazards and cumulative impacts. Beyond natural risks such as earthquakes, floods, and glacial lake outburst floods (GLOFs), frameworks for holistically assessing long-term ecosystem impacts—including sedimentation, turbidity changes, and habitat fragmentation—as well as the cumulative impacts of multiple overlapping projects, and for reflecting these in decision-making, remain inadequate (Vince, 2010). Even if renewable energy expansion can contribute to achieving SDG 7 and SDG 13, the risk of unforeseen burdens on SDG 14 and SDG 15 in the process has not been fully eliminated.

The positioning of fuel switching from coal to natural gas, and of gas-fired power as a bridge fuel, also carries challenges from a long-term perspective. While a shift to gas-fired power can contribute to emissions reductions in the short term, there is ongoing debate about whether investment in new gas infrastructure may create long-term lock-in and stranded asset risks. Stranded asset analyses also show that results are sensitive to underlying assumptions—plant lifespans, utilization rates, fuel prices, and carbon prices—highlighting dependence on data and models as a limitation (González-Mahecha et al., 2019).

The coherence of the policy mix and the presence of vested interests also represent major hurdles in the renewable energy transition. Emissions trading schemes (ETS), renewable energy support, fossil fuel subsidy reform, and regulations coexist, but their directions are not always aligned, and cases have been reported in which institutional inconsistencies distort investment decisions (Duan et al., 2017). Existing fossil fuel industries, electricity utilities, and business models dependent on specific technologies frequently possess the capacity to resist reform (Schenuit et al., 2021). Such institutional and political friction constrains the actual pace of deployment even where renewable technologies hold technical and economic advantages.

Regarding demand-side interventions and community-based initiatives, issues of equity and sustainability also remain. Programs such as rate structures, incentives, and PV installation support tend to skew toward relatively higher-income, environmentally conscious households due to disparities in information access and upfront costs, and it is widely noted that low-income households and those experiencing energy poverty are not adequately reached (Allcott, 2011; Bradley et al., 2016). While energy-saving effects are confirmed in experiments and short-term programs, evidence remains limited on how far these effects persist over several years and to what extent they are reproducible under different socioeconomic and cultural conditions. Even in community energy and group-purchasing cases, outcomes vary considerably depending on participant characteristics and community context, and the scalability to other regions requires careful consideration (Noll et al., 2014; Schelly, 2014).

Overall, the pace and direction of renewable energy transitions continue to be shaped by cumulative environmental risks, fossil fuel lock-in, policy incoherence, vested interests, equity concerns, and dependence on uncertain data and models.

4.3.2 Land use, forests, and agriculture

While the success cases described above exist, the land use, forests, and agriculture literature also commonly identifies several structural challenges. One is the problem of leakage. When forest conservation or land use regulations are strengthened in one area, pressures for agricultural expansion and logging can shift to neighboring areas with weaker regulations, potentially offsetting the net global reduction in deforestation and greenhouse gas emissions. Another is the insufficient inclusion of smallholder farmers and the landless poor. Supply chain initiatives, certification schemes, and results-based payment schemes such as REDD+ and PES frequently target primarily landowners and large-scale operators, carrying the risk that the most vulnerable households are left outside these systems. Furthermore, governance that relies on sanctions and monitoring is susceptible to rapid erosion through changes in government or amendments to legislation, introducing political and institutional instability. The misalignment of scales—whereby institutions at federal, state, and municipal levels operate in silos, preventing the full realization of the effects of protected area designation and land use planning—also emerges as a challenge. The lack of financial foundations and monitoring capacity to sustain REDD+ and PES over the long term is also repeatedly highlighted across many studies.

Specifically, while the Soy Moratorium achieved some success in suppressing new forest conversion in the Amazon, it has been shown that agricultural expansion pressures may have shifted to other regions with weaker regulations, such as the Cerrado (Gibbs et al., 2015). In REDD+ and PES cases, it has been reported that while land-titled households become the primary beneficiaries of payments, the exclusion of landless farmers and the poorest households from these schemes risks widening social inequality in exchange for environmental outcomes (Simonet et al., 2019). The revision of Brazil’s Forest Code and the “amnesty” granted for past illegal logging demonstrate that previously strict law enforcement can easily be hollowed out by shifts in the political environment, highlighting the vulnerability of long-term regime stability relative to short-term suppression of deforestation (Arima et al., 2014; Azevedo et al., 2017).

What remains in the land use, forests, and agriculture domain is merely insufficient implementation of individual policies, but a set of structural problems: leakage across spatial scales, asymmetries in power and bargaining capacity, and long-term deficits in financing and monitoring capacity. Moreover, the drivers of forest loss vary significantly across regions, including resource extraction, smallholder expansion, and commercial logging (Turubanova et al., 2018). This indicates that trade-offs between forest conservation and development are not governed by a single mechanism but arise from diverse structural drivers.

4.3.3 Urban, transport, waste, and local governance

The urban, transport, waste, and local governance policy literature also identifies several common threads regarding challenges that persist behind these success cases. Of particular concern is the spatial and social unevenness of the burdens and benefits generated by urban policies. Mobility policies such as congestion pricing and car-sharing bring benefits in the form of reduced congestion and environmental improvement in central areas, while tending to be perceived as financial burdens by peripheral municipalities and lower-income groups with high car dependency. There is also the fragility of institutional inclusiveness and trust. Even where community participation and community-led initiatives are formally incorporated, if decision-making authority remains limited, tensions with existing urban planning and land use policies, and a sense of distrust, can emerge. Additionally, securing long-term financial and technical foundations, and the growing risks posed by climate change, present ongoing challenges. Investment in green infrastructure and urban transport frequently depends on external funding, leaving a pattern in which the burden of maintenance and monitoring is pushed onto local authorities and residents. Meanwhile, the advance of climate change is intensifying rainfall and flood risks that exceed the design capacity of existing drainage and disaster prevention infrastructure.

Specifically, regarding Stockholm’s congestion charging scheme, Schuitema et al. (2010) note that while support for the measure is in the majority in the city center, opposition predominates in surrounding municipalities, with spatial conditions and differences in the distribution of benefits and burdens driving a divide in public support. Because the charge is uniform, depending on usage patterns, lower-income groups may face a relatively heavier burden, and concerns about equity have not been fully resolved. Biddau et al. (2016), analyzing the community-led Transition Town movement, show that while a shared local identity and mutual support are sources of strength, tensions with institutional politics, contradictions with land use planning, and distrust of public administration are also embedded within the movement. Ghosh (2019), examining urban transport experiments, also identifies as a challenge the fact that BRT and cycling infrastructure are concentrated in specific corridors and districts, while transport access and flood risk remain high in non-targeted areas and informal settlements. In cases of flood countermeasures and green infrastructure development, it is repeatedly noted that while the environmental and sanitary conditions of target areas improve, problems persist in non-project districts, and the benefits do not adequately reach low-income groups and peripheral areas.

Furthermore, the fiscal sustainability of the infrastructure and subsidies supporting EV adoption and shared mobility, the regulatory challenges arising from dependence on private platform companies, and the fact that accelerating climate change is undermining the design assumptions of existing infrastructure cannot be overlooked. The urban park case of Kim and Coseo (2018) and the eco-district case of Wiktorowicz et al. (2018) are currently recognized as advanced models but leave open questions about scalability to other cities and regions, and about who bears the long-term maintenance costs. Ayerakwa (2017) urban agriculture research also suggests that even though urban agriculture has been legitimized through policy recognition, its continued existence is not necessarily secure depending on land tenure arrangements and the pressures of urban development.

These challenges are fundamentally distributional and institutional, concerning who benefits, who bears costs, and how resilient urban systems remain under climate and fiscal pressures.

4.3.4 Industry, supply chains, and circular economy

The same body of literature also identifies common challenges that persist behind the success cases. First is uncertainty regarding the economic viability and international competitiveness of low-carbon technologies and circular business models. Hydrogen steelmaking and advanced recycling technologies frequently push up product costs under current conditions, and investment decisions are prone to instability without sufficient carbon pricing or subsidies. Second, the fragmentation of circular economy definitions, assessment indicators, and policy tools across countries, regions, and sectors leaves institutional instability and inconsistency as sources of uncertainty for businesses. Third, while large firms and capital-rich companies take the lead, the perspectives of small and medium-sized enterprises, the informal sector, and residents are insufficiently incorporated, raising challenges of inclusiveness and governance sustainability. In addition, deficiencies in high-quality by-product recycling technology and material flow data, and vulnerability to market price fluctuations, constrain the expansion of industrial symbiosis.

For example, Kushnir et al. (2020) estimate that the steel production cost under hydrogen direct reduction is approximately 20–30% higher than conventional methods, noting that adoption is difficult for firms without border adjustment measures to prevent carbon leakage and the development of a green steel market. Guo et al. (2016), while discussing a case in which the symbiotic relationship between Huatai and Xinren was severed, argue that industrial symbiosis in Xinjiang’s chemical industrial cluster easily becomes unviable due to low natural resource prices and market price volatility, with technical and economic constraints combining to generate instability in symbiotic relationships. Ranta et al. (2018), comparing China, the United States, and Europe, identify as challenges the fragmentation of circular economy concepts, indicators, and policies, and the fact that weak support for reuse and reduction—alongside recycling-heavy policies and social norms—perpetuates distrust of reused products and mixed-waste disposal practices. Mathews et al. (2018) also note that while China’s eco-industrial park policy has achieved some results, disparities in administrative capacity and access to financing and technology between coastal and inland regions persist, with cases such as the Tianjin Eco-City serving as showcase developments with low occupancy rates.

These findings suggest that remaining challenges in this domain concern the interaction of economic viability, institutional stability, inclusiveness, and technological capacity, as well as how costs and benefits are distributed and how governance structures respond to market fluctuations and political change.

4.3.5 Governance

At the same time, governance case studies consistently show that even where enabling factors are confirmed, synergies among the SDGs are not necessarily maintained in a stable or long-term manner. What many studies highlight is that even where institutional design and policy mixes have been established to a certain degree, trade-offs can re-emerge through political and institutional constraints during implementation. In particular, policy backsliding, insufficient levels of ambition, and distortions in institutional operation are repeatedly discussed as factors that destabilize initiatives premised on synergies.

For example, Rochedo et al. (2018), examining forest governance, show that when deforestation control is reversed through political bargaining or institutional weakening, not only does the overall achievability of climate action decline, but other sectors may be forced to bear excessive mitigation burdens and costly technology choices. This case is a textbook example of how governance instability damages the synergies among SDGs that were initially anticipated and amplifies trade-offs. Wachsmuth and Duscha (2019), examining demand-side measures, also note that where current standards and policy ambition levels are insufficient, necessary emissions reductions accumulate as unfinished business, potentially deferring the burden to future generations.

Research analyzing market institutions and policy mix implementation also shows that distortions in institutional design and insufficient coordination become bottlenecks at the implementation stage. Grubb and Newbery (2018) point out that where tariff structures and rule design in electricity markets impede investment, the pace of low carbonization may slow, demonstrating that institutional details can determine whether synergies materialize. Rayner et al. (2017) also identify the problem of “layering,” whereby policy mixes accumulate internal contradictions over time, showing that where continuous evaluation and adjustment do not occur, the coherence among originally intended goals risks being lost.

Furthermore, challenges around acceptance and equity are also common threads in the domain of governance. Eliasson (2014), analyzing congestion pricing, shows that while acceptance may increase after policy introduction, individual and regional differences in the perception of effects and burdens remain. Carattini et al. (2018), examining waste taxation, also confirm that while institutional experience can enhance acceptance, insufficient prior understanding and a sense of burden can contribute to resistance to the policy and remain a challenge. These studies demonstrate that even institutionally effective policies can face constraints at the implementation stage if their distributional impacts and legitimacy are not sufficiently considered.

The governance literature suggests that the key challenges lie in maintaining institutional stability, policy ambition, adjustment capacity, and equitable distribution of burdens and benefits. Without these conditions, synergies are unlikely to persist and expand over the long term.

5 Discussion

5.1 RQ1: What factors appear to support synergies among the SDGs in existing policy measures and practical initiatives?

The first finding of this review is that synergies among the SDGs appear to be associated less with single measures than with cross-sectoral policy integration and institutional design. Cases were identified in which the institutional integration of climate change policy and industrial policy simultaneously strengthens emissions reductions and industrial competitiveness, and in which connecting urban planning and climate adaptation through an equity lens was associated with both resilience and inclusiveness. This demonstrates that the integrated design of planning, budgeting, implementation, and evaluation (monitoring) is an important institutional condition associated with synergies (SDGs most commonly observed: SDG13 × SDG9 × SDG11 × SDG7 × SDG10). This finding is also consistent with existing research emphasizing the importance of institutional coherence when linking climate action to other SDGs (Fuso Nerini et al., 2018; Pradhan et al., 2017).

Second, whether sectoral success was associated with broader synergies appeared to be related to the presence of a long-term policy trajectory that anticipated interactions across sectors and objectives. In cases where uncertainty is reduced not through one-off projects but through long-term legal frameworks such as 2050 targets, climate laws, and forest laws—gradually guiding investment and behavior—long-term outcomes beyond short-term costs have been realized (SDGs most commonly observed: 13 × 9 × 8 × 17). This is also consistent with macro-level analyses showing that SDG interactions are strongly time-dependent (Singh et al., 2018).

Third, the reviewed cases suggest that synergies were more commonly associated with combinations of technologies and policy instruments than with individual measures alone. Where economic incentives such as subsidies, pricing structures, and market mechanisms are designed to align with social and environmental benefits, cases frequently reported environmental improvements alongside income growth and behavioral change, mitigating the tension between economic rationality and sustainability (SDGs most commonly observed: 8 × 13 × 15 × 12). This overlaps with prior research noting that incentive design shapes the direction of SDG interactions (Nilsson et al., 2016).

Finally, the reviewed cases suggest that coordination often extended beyond a single intervention. Cases involving local residents, farmers, women, and community organizations as implementing actors rather than merely beneficiaries frequently reported sustained behavioral change and longer-term policy impacts (SDGs most commonly observed: 1 × 2 × 5 × 13 × 15). This is also consistent with existing theoretical findings that participatory governance mediates synergies (Anderson et al., 2022).

5.2 RQ2: What structural and institutional factors give rise to trade-offs?

The second finding of this review is that trade-offs appeared less as inevitable side effects and more as phenomena associated with the design of policies, institutions, and governance arrangements. While some trade-offs reflect underlying structural constraints associated with biophysical limits, land availability, or technological conditions, the reviewed literature suggests that many observed trade-offs are also shaped by institutional factors, including fragmented governance, unequal power relations, short-term incentives, and policy incoherence. The variation observed across cases suggests that similar trade-offs may be intensified, redistributed, or mitigated depending on institutional arrangements, indicating that many observed trade-offs are not purely structural but are socially and institutionally mediated. In many cases, institutional characteristics such as short-termism, sectoral fragmentation, concentration of authority, distorted incentives, and learning failures were frequently associated with the emergence of trade-offs, rather than merely reflecting the absence of synergy conditions.

Particularly prominent is the siloed structure across sectors and the fragmentation of goals. Where policy domains such as environment, industry, agriculture, and welfare were designed and evaluated in isolation, impacts on other SDGs were often given limited consideration, and trade-offs were frequently reported in relation to the uneven distribution of costs and benefits across actors or regions. Fragmented evaluation systems and budget allocations were recurrently associated with trade-offs, a pattern also raised in existing SDG interaction research (Nilsson et al., 2016; Pradhan et al., 2017).

Moreover, while centralized, top-down governance can enhance efficiency, it tends to keep local residents and small-scale actors as objects of coordination rather than implementing agents, making the exclusion of vulnerable groups likely. Cases characterized by asymmetric distribution of authority, knowledge, and resources were more likely to report situations in which policies evaluated as successful in one domain were associated with negative impacts in other domains or for other social groups.

This point can be theoretically understood through power and justice perspectives. Lukes’ analysis of power highlights that exclusion is not limited to visible conflicts but can also be embedded in institutional arrangements that shape whose interests enter decision-making (Lukes, 1974). Similarly, Fraser’s distinction between redistribution and recognition, and Schlosberg’s extension of these dimensions to environmental justice, help explain why trade-offs often appear as distributive, procedural, and recognition-based tensions rather than as purely technical policy conflicts (Fraser, 1995; Schlosberg, 2007).

Furthermore, the reviewed cases suggest that excessive reliance on short-term outcome indicators—GDP, investment volumes, deployment quantities, and so on—may limit consideration of long-term benefits and irreversible losses. Where subsidies, prices, and market institutions were designed with limited consideration of social and environmental benefits, outcomes favoring large-scale and capital-intensive actors were recurrently observed, often alongside reported trade-offs. This structure also overlaps with existing research showing that policy frameworks that prioritize economic efficiency intensify tensions among the SDGs (Singh et al., 2018). This interpretation is also consistent with political economy perspectives, which emphasize how institutional incentives, power relations, and the distribution of resources shape development outcomes and influence the distribution of benefits and burdens across social groups. These perspectives also help explain why trade-offs often persist over time, as institutional incentives, power asymmetries, and established resource distributions can reinforce existing governance arrangements and constrain transformative change. Accordingly, not all trade-offs are considered governable. Some may arise from structural constraints, whereas others are shaped by institutional conditions and may therefore be subject to policy intervention.

5.3 RQ3: What driving forces are associated with synergy promotion and trade-off mitigation?

The third finding is that enabling factors and remaining challenges are not separate phenomena but two sides of the same institutional mechanism. These driving forces were inductively derived from cross-case patterns, while being conceptually aligned with prior understandings of systemic transformation as discussed in GSDR (2019, 2023). These driving forces can be positioned within the broader literature on sustainability transformations and transformative governance. Rather than proposing a wholly new theory, this study links SDG interaction research with transformation-governance scholarship and translates broad theoretical concerns—such as institutional reconfiguration, power redistribution, long-term orientation, incentive redesign, and learning capacity—into empirically grounded governance conditions for managing SDG synergies and trade-offs (Patterson et al., 2017). These drivers also resonate with several strands of transition and governance scholarship, including the Multi-Level Perspective, Transition Management, Adaptive Governance, and Polycentric Governance, which similarly emphasize long-term institutional change, learning, cross-scale coordination, and multi-actor participation (Figure 2).

Figure 2

The integration and coherence of policy objectives—that is, the capacity to design and operate KPIs, budgets, and evaluations across climate, industry, social, and land use policy goals rather than confining them to single sectors—emerged as a recurring governance condition associated with the feasibility and sustainability of transformation, as also highlighted in GSDR 2019 and 2023. The reviewed cases suggest a possible association between governance coordination and the emergence of synergies, whereas fragmented governance was commonly discussed in cases where trade-offs were reported. This observation is broadly consistent with Fuso Nerini et al. (2019), who argue that stronger coordination across policy domains and governance structures can help address SDG interlinkages more effectively. The reviewed cases further suggest that inclusive governance may contribute to synergy promotion when accompanied by meaningful participation and opportunities for diverse actors to influence decision-making and resource allocation. The capacity to shift time horizons from short-term outcomes to long-term resilience is also critical, as legal frameworks and long-term targets reshape decision-making criteria.

In addition, the reviewed cases suggest that incentive redesign—aligning economic interests and price signals with social and environmental benefits—was more often associated with successful synergies than technology deployment alone. Institutional capacity for learning and adaptation is likewise indispensable: systems that continuously monitor outcomes and allow correction enable early responses to leakage, counterproductive effects, and social resistance. These findings suggest that leverage points lie not in isolated instruments but in deeper systemic properties of governance structures, decision-making rules, and development paradigms. However, such interventions require long time horizons, political commitment, and coordination across scales, creating tensions with feasibility. Future research should therefore examine how combinations of shallow and deep interventions can enhance both effectiveness and feasibility.

An additional methodological consideration concerns the source of the reviewed literature. Because the reviewed studies were limited to those cited in IPCC AR6 Chapter 3.4, the sample reflects the priorities and climate-oriented perspectives of the IPCC, which may partly explain the prominence of governance-related driving forces.

6 Conclusion

This study extracted 128 papers dealing with empirical policy and practical cases from the references cited in the IPCC AR6 Synthesis Report on the long-term interactions among adaptation, mitigation, and sustainable development. These papers were classified into five domains—energy and power; land use, forests, and agriculture; urban, transport, waste, and local governance; industry, supply chains, and circular economy; and governance—and synergies and trade-offs among the SDGs, as well as enabling factors and remaining challenges, were systematically organized. A central contribution of this study lies in the identification and conceptualization of recurring driving forces associated with synergy promotion and trade-off mitigation, which are synthesized into a cross-cutting governance framework for understanding SDG interactions. While earlier interlinkage research emphasized coordination among international environmental institutions and agreements, the present findings highlight the role of interaction management within domestic governance systems and implementation processes for achieving sustainable development outcomes.

With respect to RQ1, this review suggests that synergies among the SDGs arise not as the product of single measures but as the outcome of cross-sectoral policy integration and institutional design. Initiatives centered on decarbonization (SDG 13) and resource efficiency tend to be associated with co-benefits across energy access (SDG 7), industry and infrastructure (SDG 9), urban sustainability (SDG 11), and terrestrial ecosystems (SDG 15), with structural parallels observed across domains. Factors frequently observed in cases of reporting synergies included long-term goal-based policy trajectories, high-resolution data and multi-criteria assessment, community organization involvement, and combinations of policy instruments including pricing, subsidies, and regulation. These findings suggest that synergies are more often associated with the integration and implementation of multiple measures than with the substance of individual measures.

Regarding RQ2, the trade-offs identified more often appeared as social products linked to institutional design, implementation capacity, and the distribution structure of burdens and benefits, rather than being reducible to natural conditions. Overreliance on short-term outcome indicators (GDP, investment volumes, deployment quantities, etc.), sectoral fragmentation and misalignment of budget and evaluation systems, asymmetric distribution of authority and resources through centralized decision-making, incoherence in policy mixes, and deficits in learning and adaptation were commonly observed in cases reporting trade-offs. In energy transition and industrial decarbonization, short-term cost increases and tensions with employment and price competitiveness surfaced prominently; in urban policy and environmental regulation, conflicts over equity, participation, and residential stability were associated with institutional acceptance. In the land use and forestry domain, leakage, exclusion, and unequal distribution of benefits and burdens were frequently associated with tensions related to social inequality (SDG 10) and institutional legitimacy (SDG 16). Trade-offs therefore appeared not as “inevitable outcomes” but as phenomena whose intensity and direction were associated with differences in design and implementation.

Finally, for RQ3, this study found that enabling factors and remaining challenges can be understood as closely related institutional dimensions, and identified the following five driving forces associated with synergy promotion and trade-off mitigation: (i) integration and coherence of policy objectives; (ii) inclusive governance and redistribution of agency; (iii) long-term vision and shift in time horizon; (iv) redesign of incentive structures; and (v) institutional capacity enabling learning and adaptation. These were extracted as institutional conditions repeatedly observed across domains, transcending domain-specific prescriptions, and thereby help identify recurring governance conditions that may inform the management of synergies and trade-offs, without claiming universally valid causal mechanisms.

These findings can also be interpreted as institutional design principles that provide practical guidance for policymakers seeking to promote synergies and mitigate trade-offs. In practice, integration and coherence can be operationalized through cross-sectoral planning mechanisms, shared performance indicators, integrated budgeting arrangements, and coordinated evaluation systems. Inclusive governance requires not only stakeholder participation but also meaningful influence over decision-making and resource allocation. Long-term vision can be embedded through legally anchored targets and planning frameworks that account for long-term resilience and irreversible risks. Incentive redesign involves aligning subsidies, procurement systems, pricing mechanisms, and other policy instruments with social and environmental objectives. Finally, learning and adaptation require monitoring systems, feedback mechanisms, and periodic policy review processes that enable continuous adjustment in response to emerging trade-offs and unintended consequences. Together, these elements suggest a practical governance pathway in which long-term goals, inclusive decision-making, aligned incentives, policy integration, and adaptive learning are combined to move from fragmented sectoral interventions toward more integrated management of SDG synergies and trade-offs.

These findings also carry tentative implications regarding leverage points. Specifically, the reviewed cases suggest that impactful points of intervention may reside not only in individual technologies or one-off policy instruments, but also in the deeper systemic properties of governance structures, decision-making rules, and dominant development paradigms. At the same time, interventions at this deeper level often entail long time horizons, political commitment, and cross-sectoral coordination capacity, which may create tensions with short-term feasibility. This study makes visible the tension between “depth” and “feasibility,” and suggests the need to strategically combine shallow interventions (institutional operations, incentives, data infrastructure, etc.) with deeper interventions (norms, rules, governance structures, etc.).

Finally, this study has several limitations. Firstly, because the sample was limited to studies cited in IPCC AR6 Chapter 3.4, it may reflect IPCC priorities, climate-oriented perspectives, and the predominance of English-language peer-reviewed literature. Consequently, certain forms of local, practitioner, and non-English knowledge may be underrepresented. In addition, no formal assessment of study quality or risk of bias was undertaken, nor was any formal evidence hierarchy applied. Methodological robustness may therefore vary across the included studies. The findings should be interpreted as patterns identified across the literature rather than conclusions weighted according to methodological strength. Future research should examine whether similar patterns emerge from broader and more diverse evidence bases. Secondly, while this review aimed at cross-domain generalization, limitations remain in fine-grained comparisons of the political-economic contexts and power relations of individual cases. Thirdly, although some studies did not explicitly analyze trade-offs, interactions were identified based on their substantive alignment with SDG targets. While this broadens coverage, it also entails the risk of over-interpretation and classification bias. The identification of synergies and trade-offs involves interpretive judgment, which may limit replicability across researchers. In addition, reclassifying findings into SDG categories may simplify contextual meanings and institutional conditions and may identify relationships not explicitly examined in the original studies.

Future research should validate these interactions through expert review and sensitivity analyses. Building on these findings, further work is needed to compare intervention points in terms of their depth and feasibility, to empirically examine policy design and implementation strategies that can simultaneously enhance effectiveness and political feasibility, and to investigate how structural conditions that generate trade-offs may themselves be transformed through institutional change, power redistribution, and sustainability transformations.

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