Beyond Production-Based Accounting: A Comparative SWOT Analysis of GHG Inventory Frameworks and Their Policy Implications

Abstract

The methodology used to attribute greenhouse gas (GHG) emissions to nations profoundly influences perceived climate action burdens, raising critical questions about equity in global climate governance. This study systematically evaluates current production-based accounting (PBA) by comparing it with three alternative frameworks: consumption-based accounting (CBA), historical cumulative-based accounting (HBA), and per capita-based accounting (PCBA). We conducted a comprehensive SWOT analysis using multi-stream evidence synthesis, analyzing 23 major emitting countries representing over 80% of global emissions. Data sources included UNFCCC documents, historical emission datasets, consumption-based emission data, and World Bank population estimates. Results reveal dramatic redistributions of national positioning across frameworks, with countries experiencing extreme ranking volatility—India dropped 19 places from 4th under PBA to 23rd under PCBA, while Saudi Arabia rose from 11th to 1st. Our analysis demonstrates that while accounting frameworks provide factual measurements of different emissions dimensions, their selection for policy purposes constitutes a normative choice with distributional consequences. We explicitly map each framework to the responsibility principles it operationalizes, revealing that current over-reliance on PBA creates systematic blind spots in the policy context and climate governance.

1. Introduction

Anthropogenic climate change represents one of the biggest challenges that humanity has ever faced. Global climate change has proven to have a myriad of impacts on global health, ecosystems, and populations across the board [1]. In an effort to alleviate this self-inflicted wound, great efforts have been made through international cooperation to mitigate its diverse impacts [2]. In light of this challenge, comprehensive frameworks have been developed to reduce emissions and limit global warming to 1.5 °C—most notably the Paris Agreement, which stands as the central international framework guiding global climate action. Achieving the goals set by this standard will require rapid and coordinated action on an unprecedented global scale.

This call for urgent and global action raises complex issues that climate policy must face, particularly as the largest redistributive policy in human history [3]. In order to avoid the 1.5 °C scenario, as well as the more severe 2–2.5 °C scenarios [4,5], the remaining carbon budget of 420 GtCO₂e (for a two-thirds chance of effectively limiting the 1.5 °C scenario) to be emitted needs to be allocated and contained to remain within safe limits. This, in turn, raises fundamental normative questions on who should shoulder the costs of mitigation and adaptation in such a context. The question of distributive justice sits at the heart of climate governance and has been subject to much discussion [6,7,8]. The allocation of climate responsibilities, or “shares” of the global common that this carbon budget represents [9,10], cannot be exclusively derived from empirical measurement alone, for it involves complex considerations of fairness, historical responsibility, and burden distribution across countries and generations.

Addressing such an issue requires the establishment of critical conceptual distinctions. We distinguish three interrelated but fundamentally different dimensions of the issue at hand (see Figure 1):

Figure 1. Conceptual framework for climate responsibility and emissions accounting. Justice principles (Box 1) determine policy design choices (Box 2), which in turn select appropriate accounting frameworks (Box 3) that shape political discourse and implementation (Box 4). Solid arrows indicate logical precedence: normative commitments precede measurement choices. The dashed feedback arrow represents path dependency once institutionalized.

(i)

Responsibility attribution (normative): This dimension refers to the justice principles and frameworks that guide policy design and determine who should bear which burdens in climate governance. According to the nature of these, we can distinguish between the following:

Responsibility to compensate: Based on causal contributions to the historical cumulative emissions and the harms they have caused, this aspect of responsibility focuses on the correction of loss and damage already incurred in the past [6,7,10].

Responsibility to pay the costs of mitigating: This aspect focuses on the duty to reduce the current level of emissions, allocating shares of the remaining carbon budget fairly, and is determined on the basis of causal responsibility (who emits), benefit received, or capacity to pay [6].

Responsibility to pay the costs of adaptation: Finally, this dimension of responsibility refers to the obligation to fund and support measures that allow for the preparation of vulnerable populations and nations to face unavoidable climate impacts [6,11].

Different normative frameworks allocate these responsibilities in competing ways. The Polluter Pays Principle (PPP) emphasizes causal responsibility, holding that those who caused emissions should bear mitigation and compensation costs, and is closely associated closely with “grandfathering” [7,10]. The Beneficiary Pays Principle (BPP) focuses on who gained from emission-generating activities, arguing that economic beneficiaries should contribute regardless of direct causation [12]. The Ability to Pay Principle (APP) prioritizes economic capacity, requiring wealthy nations to contribute more based on their means rather than their emissions history [6]. Lastly, Equal Per Capita Rights establishes that all individuals have equal claims to atmospheric resources, suggesting burden-sharing based on population. Other allocation principles include prioritarianism, sufficientarianism, or cosmopolitan liberal-egalitarianism.

These principles can be grounded in broader theories of distributive justice [3,6,7,8]. Libertarian approaches emphasize property rights and causal harm, supporting strict PPP or equal per capita allocation with historical adjustments. Liberal-egalitarian lens frameworks prioritize fairness to the least advantaged, combining PPP with APP to ensure wealthy nations subsidize mitigation in poor countries [6,13]. Utilitarian approaches focus on maximizing overall welfare and cost-effectiveness, supporting flexible instruments and mitigation wherever it is cheapest [14,15]. Each meta-theory generates different implications for how the three types of responsibility should be allocated [7,8].

(ii)

Policy design (normative–operational): Based on these distinct paradigms of distributive justice, different practical policies are designed on this basis, through carbon pricing, tradeable permits, emission caps, nationally determined contributions, or finance mechanisms. Critically, policy design determines which accounting framework and data collection systems are more appropriate for its own conception of justice, being able to shape both the normative and operational conceptions of responsibility.

(iii)

Measurement and political influence (factual): Essentially, measurement refers to the quantification and monitoring systems used to track and register GHG emissions. These are empirical facts and accounts of were emissions physically occur, where goods with embedded emissions are consumed, etc. [16]. These frameworks are factual instruments, but the choice of which framework to adopt for policy purposes is inherently normative, as it determines which patterns become visible and actionable [8,17]. In practice, the institutionalization of production-based accounting (PBA) in UNFCCC frameworks has normalized territorial responsibility as the default frame, creating path dependency where certain justice principles become easier to operationalize than others.

It is crucial to emphasize from the outset that this study does not aim to determine the inherent “justness” or “fairness” of accounting frameworks. Accounting frameworks serve as factual measurement tools that quantify emission patterns based on a set of criteria; where GHG are physically generated, how goods embody GHG emissions, how emissions accumulate historically or how they are distributed across populations. These measurements are empirical facts, devoid of inherent moral judgment. Which normative framework should guide policy design and implementation, however, is a question that cannot be answered from empirical analysis alone. A prior ethical and normative analysis on what constitutes fair burden-sharing in climate governance is essential. Our analysis examines how framework choice operates within the informational and policy landscape derived from these normative visions, and how framework choice interacts with this conceptual ecosystem, without prescribing which principles should be adopted, or which are fairer.

At the national level, a country’s emissions are documented in a National Emissions Inventory (NEI). The prevailing global standard, developed by the Intergovernmental Panel on Climate Change (IPCC) and implemented by the United Nations Framework Convention on Climate Change (UNFCCC) for the formulation of NEIs, is based on a territorial, or production-based accounting (PBA), approach [1], which catalogs a country’s emissions as those generated within the state’s sovereign borders as a consequence of direct or scope 1 emissions [11,18]. While PBA has proven to be a relevant milestone in the journey towards rigorous emissions reporting and transparency for most countries, growing evidence points to its limitations in capturing the full complexity of emissions responsibility and attribution, especially with regard to carbon leakage [17,19].

Among the academic literature, there is an increasing call for the revision and refinement of accounting frameworks for GHG inventories. Several alternative accounting frameworks have gained prominence in discussions over the last 15 years:

Consumption-based accounting (CBA): Tracks emissions embedded in imported-exported goods and services through international trade [17,20].

Extraction-based accounting (EBA): Assigns responsibility to the production of fossil fuels instead of their consumption [16,21,22].

Historical or cumulative-based accounting (HBA). HBA focuses on the total cumulative emissions since the industrialization (1850) [23,24].

Income-based accounting (IBA): Allocates emissions based on collective or individual acquisitive power, focusing on the means available to contribute to climate change mitigation [25,26].

Per capita-based accounting (PCBA): Normalizes emissions by population size [27].

Other alternatives, such as future (committed emissions), multi-level emissions (corporate, governmental, etc.), or tourism focused, are some of the many frameworks currently being developed [27,28].

Each framework operationalizes specific justice principles, with some providing basic emission data collection systems that are used in several justice principles simultaneously. This relationship is elaborated in Table 1.

Table 1. Mapping of justice principles to accounting frameworks and policy instruments.

Justice Principle	Policy Examples	Data Required	Primary Accounting Frameworks
Polluter Pays Principle (PPP)	Kyoto Protocol Carbon taxes Emission reduction targets (e.g., NDCs) Emission caps	Territorial/direct emission data Scope 1 sectoral data LULUCF data	PBA HBA for retrospective application
Beneficiary Pays Principle (BPP)	Import-adjusted carbon border mechanisms (CBAM) Consumption Based Carbon Pricing Carbon tariffs	Multi-regional input-output (MRIO) data International trade flows Embodied carbon in products Scope 2 and 3 emissions	CBA HBA for a cumulative benefits assessment
Ability to Pay Principle (APP)	Progressive climate finance contributions (Green Climate Fund) Differentiated NDCs differentiated by socioeconomic indicators Technology transfer	GDP per capita data National wealth indicators Wellbeing/development indicators (HDI, MPI, PHDI, etc.)	PCBA Econometric indicators
Equal per capita rights	Contraction and convergence proposals Per capita emission allowances Population-adjusted carbon budgets Tradeable emission permits with equal per capita allocation	Total population data Demographic projections Current emission inventories	PCBA HBA when adjusted per capita over time
Prioritarianism	Progressive climate finance contributions Emission reduction targets based on development indicators Carbon pricing adjusted to ability to pay	Wellbeing/development indicators (HDI, MPI, PHDI…) Vulnerability indices Capability metrics Current emissions data Development classifications and thresholds (LDCs, SIDS)	PCBA and continuous weighting
Sufficientarianism	Subsistence vs luxury emissions Poverty thresholds in emission allocation Basic needs exemptions from carbon pricing Modified equal shares model	Wellbeing/development indicators (HDI, MPI, PHDI…) Vulnerability indices Capability metrics Current emissions data Development classifications and thresholds (LDCs, SIDS)	PCBA with strict threshold adjustments

Previous research has focused predominantly on comparing PBA and CBA [16,29], with limited systematic cross-framework analysis at a national scale. Moreover, while climate justice scholarship has articulated competing normative principles [6,7,8,10], empirical studies rarely explicitly connect accounting methodologies to the justice principles they operationalize. Finally, existing work has not comprehensively evaluated practical feasibility of justice theory principles, including empirical factors such as data availability, methodological transparency, and political acceptability.

This study will address these gaps through a SWOT analysis of four accounting frameworks applied to the top 23 GHG-emitting countries under PBA, covering 80% of total annual emissions for 2022. The analysis aims to examine how accounting choices shape the information landscape within which policy decisions are made. We will explicitly map frameworks to the justice principles they operationalize, exploring the relationship between measurement choices and the normative visions they enact. We will provide a comprehensive feasibility assessment across data availability, transparency, and political acceptability, exploring the feasibility of multiframework models and the complementarity (or lack thereof) of accounting frameworks.

2. Materials and Methods

This section outlines the criteria for database selection and the methodological approach used for the comparison of accounting frameworks. Once defined, we establish a quantitative basis that will serve as the foundation for the SWOT analysis. The criteria selected in this study were based on the availability of public information and the completeness of available databases, prioritizing those including several GHG and Land Use, Land Use Change and Forestry (LULUCF) emissions.

2.1. Criteria Selection

2.1.1. Production-Based Accounting

Established by the UNFCCC, PBA is the current standard under which national inventories are compiled and serves as a central element of NDCs under the Paris Agreement. Reporting obligations vary significantly within this framework. All Annex I countries are required to submit National Inventory Documents (NID) and National Inventory Reports (NIR) biannually, with comprehensive coverage of all Kyoto gases, sectors and LULUCF emissions, using the Common Reporting Format (CRF). Non-Annex I countries provided Biannual Update Reports (BUR), a notably less stringent reporting framework, every three years, but under the new Enhanced Transparency Framework they are now required to submit Biennial Transparency Reports (BTR). BTRs are mandatory as of December 2024, except for Small Island Developing States (SIDS) and Least Developed Countries (LDC) and include comprehensive and standardized GHG data and inventories.

UNFCCC reports will serve as the primary source for PBA in this study, as they do in secondary sources that draw upon them, such as PRIMAP-hist, EDGAR and other datasets [23]. NIR, NID and BTR benefit greatly from local knowledge and expertise, with higher precision in national sector-specific emission factors and LULUCF accounting in particular [23,30].

To avoid data quality gaps, only the most recent submissions, 2022 data, will be included, with prior submissions being replaced by database estimations from the “National contributions” [23] dataset. This dataset is specifically designed for gap-filling, with its data hierarchy structure prioritizing UNFCCC submissions (thus aligning with the study’s approach) and being one of the few comprehensive datasets that accounts for LULUCF. emissions This approach preserves the integrity of existing country-reported data while providing systematic estimates for missing values using regional growth rates and sector-specific extrapolation methods, maintaining consistency with UNFCCC territorial accounting principles and avoiding the boundary inconsistencies that can cause discrepancies between datasets [31].

2.1.2. Consumption-Based Accounting

CBA emerges in the literature as the main alternative framework to PBA [20,22,32,33,34]. This methodological approach appears as especially relevant in a globalized economy, where emissions embedded in international trade often shift environmental burdens from wealthy importing nations to lower income exporters [16,35,36]. For this study, consumption emissions data were obtained from the Global Carbon Budget [37], which extends the MRIO framework established previously [38]. Consumption emissions were calculated as territorial emissions minus embodied emissions in exports plus imports of embodied carbon [38].

Consumption emissions = Territorial Emissions − Exports + Imports of Embodied Carbon

These CBA estimates use a Multi-regional input-output (MRIO) model based on the Global Trade and Analysis Project (GTAP) database [39] and extended to include CO₂ emissions across 141 countries and 57 economic sectors to quantify the emissions embodied in traded goods and services [29,38]. Detailed MRIO calculations are performed for GTAP benchmark years (1997, 2001, 2004, 2007, 2011, 2014), which provide complete bilateral trade matrices and sectoral input-output linkages. Annual time series (1990–2021) are constructed by interpolating between benchmark years using national GDP data (current USD) and bilateral trade flows.

Uncertainty in CBA estimates arises from trade data quality, sector aggregation assumptions, and price-to-volume conversions in the MRIO framework. Sensitivity analyses suggest aggregate CBA uncertainty (~±5–10%) is comparable to territorial emission inventories [29], though bilateral trade flows for individual country pairs may carry higher uncertainty due to reporting discrepancies and customs valuation methods [29].

This dataset focuses exclusively on CO₂ emissions from fossil fuel combustion and industrial processes, excluding both LULUCF emissions and other GHG emissions. This limitation is justified by CO₂’s dominance as the primary GHG exchanged in international trade flows, representing the most significant component of carbon embodied in traded goods and services [16,17,32,40].

2.1.3. Historical-Based Accounting

HBA reflects a country’s cumulative historical GHG emissions, reflecting its long-term contribution to atmospheric concentrations. Unlike annual or production-based metrics, this approach emphasizes intergenerational responsibility and the persistent legacy of emissions [23,41,42]. This is especially relevant in compensatory justice-oriented frameworks, which argue that early industrializers have reaped the economic benefits of carbon-intensive development while externalizing long-term ecological costs [11,41].

Analyzing a country’s historical emissions can be made both from a production or a consumption lens. However, most MRIO models used for CBA date back only to the mid-1990s [43,44], making the cumulative consumption adjusted footprint of a country technically unfeasible. This study quantifies HBA emissions using the “National contributions” dataset from [23], which accounts for warming contributions from historical emissions of CO₂, CH₄, and N₂O for 1851–2024 from a territorial border standpoint. This dataset was selected over alternatives (PRIMAP-hist, EDGAR, EORA) based on several key methodological advantages: It combines multiple authoritative sources (Global Carbon Project and PRIMAP-hist), provides comprehensive multi-gas coverage with proper climate weighting and converts emissions to actual temperature contributions using IPCC-consistent methodologies.

LULUCF emissions present the most significant methodological challenge in HBA due to sparse historical data and definitional inconsistencies [30]. To address these limitations, we adopt the ensemble approach from [23], which averages three independent bookkeeping models (BLUE, Houghton & Nassikas, and OSCAR) to reduce model-specific biases. The dataset provides separate fossil and LULUCF estimates, enabling transparent analysis of each component’s contribution while acknowledging higher uncertainty in pre-1950 LULUCF data.

2.1.4. Per Capita-Based Accounting

PCBA evaluates emissions by dividing a nation’s total GHG emissions by its population, providing a perspective grounded in individual action and lifestyle emission intensity. This approach is particularly relevant in equity-focused climate policy, as it accounts for demographic differences and reflects inequality in emissions consumption patterns between countries [45,46], and has been extensively developed in the climate ethics literature [47].

The recent literature tends to include it increasingly, though most of the time as a side measure or accompanying metric [22,27]. To ensure consistency with the rest of the study, per capita emissions will be calculated by dividing the current emissions under the PBA methodology operationalized with the official data from the World Bank dataset for the corresponding year [48].

PCBA can also be derived from consumption-based emissions, as well as any other framework criteria. Since the main comparative structure of this study focuses on contrasting alternative frameworks to the PBA standard, PCBA emissions will be extracted from PBA data, ensuring consistency with previous studies.

2.2. Selection of Countries for Comparative Emissions Analysis and Temporal Standarization

This section defines the country sample and addresses temporal alignment across frameworks with different data availability constraints. PBA and PCBA are extracted from the most recent UNFCCC submissions, where 2022 represents the latest available data. Where unavailable, the “National Contributions” provides gap-filling estimates that are properly flagged with asterisks (*) in Section 3. HBA data is provided using the same dataset for the 1850–2022 period. CBA data applies for 2021 as the reference year, using the Global Carbon Budget MRIO-based consumption emissions [37].

This 1-year discrepancy between CBA (2021) and all other frameworks (2022) does not compromise our comparative analysis for several reasons. Our analysis examines how different accounting methodologies present variable country rankings, with different countries appearing in different frameworks. Inter-framework differences in country rankings (on average 7 positions) far exceed intra-framework annual variability (with country positions remaining mostly stable within frameworks across years). Finally, extrapolating 2021 CBA data to 2022 would require complex trade flow processing and assumptions that would introduce unmeasured uncertainty that would hinder data provenance and replicability.

This study will focus on all countries accountable for at least 1% of the global footprint in 2022 under the PBA standard, or those accountable for at least 2% of the estimated cumulative emissions since 1850. The adoption of this dual approach seeks to capture both contemporary emission dynamics and historical trends, thereby ensuring a comprehensive and balanced basis for comparison. In doing so, the analysis encompasses not only present-day major emitters, such as China and India, but also states whose historical contributions to global emissions remain substantial. Considering that in 2022 the global emissions total ascended to 40.7 GtCO₂e [49], all countries responsible for at least 0.407 GtCO₂e will be included in this study. The historical cumulative emissions amount to a total of 477 ± 25 Gt C, or 1750 GtCO₂e, establishing the 2% benchmark at 35.03 GtCO₂e. This will allow for a detailed analysis of the actual performance of the world’s biggest emitters, in hopes of seeing how their roles and rankings differ between accounting methods.

According to the established benchmark, the set of countries to be analyzed is as follows: Australia, Brazil, Canada, China, EU27, France, Germany, India, Indonesia, Iran, Japan, Mexico, Pakistan, Russia, Saudi Arabia, South Africa, South Korea, Thailand, Turkey, the United Kingdom, the United States, and Vietnam (see full data in Supplementary Materials Table S3).

2.3. SWOT Analysis Methodology

This study employs a systematic SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis to evaluate the institutional, methodological and policy dimensions of GHG accounting frameworks, as the primary data collection tools of climate justice and policy. SWOT analysis, originally developed for strategic business planning, has been increasingly applied in environmental policy assessment because of its capacity to integrate internal characteristics with external contextual factors [50,51]. It is essential to clarify at the outset that this analysis does not attempt to determine which accounting framework is inherently “just” or “fair” in a normative sense. Rather, it systematically examines the technical capabilities, institutional constraints, and policy implications of each framework in relation to different theories of climate responsibility that have been articulated in the literature. The different elements identified in the SWOT analysis are characteristics of the measurement tools themselves in the policy context, and are under no circumstance evaluations of the justice principles they serve.

Our SWOT analysis was constructed using a systematic evidence synthesis approach that analyzed the peer-reviewed literature addressing GHG accounting methodologies, climate justice frameworks and emission responsibility allocation across 130 papers. Our review focused on articles published between 2008 and 2025 that explicitly compare accounting frameworks of discuss their policy implications. The selection process included a search protocol for each framework, with several key terms being identified as follows in Web of Science and Scopus: (“production-based accounting” OR “consumption-based accounting” OR “territorial emissions” OR “embodied carbon” OR “emission transfers” OR “per-capita”) AND (“greenhouse gas” OR “GHG” OR “climate”) AND (“responsibility” OR “justice” OR “equity” OR “comparison”).

Each source was analyzed with a structured coding framework based on the following guidelines:

Strengths: What methodological advantages, data quality features, institutional acceptance, or policy relevance does the literature attribute to this framework?

Weaknesses: What methodological limitations, data gaps, boundary problems, implementation barriers, or equity concerns are identified?

Opportunities: What emerging applications, policy integration potential, technological improvements, or political momentum are discussed?

Threats: What implementation barriers, political resistance, data degradation risks, or institutional obstacles are highlighted?

Prioritization Matrix

Each SWOT component must meet the following criteria to be included in the scoring matrix:

Evidence threshold: Identified in at least 5 independent sources. Eligible sources include: (a) peer-reviewed articles published in ISI-indexed journals between 2008 and 2025; (b) IPCC Assessment Reports (AR5, AR6) and Special Reports; (c) UNFCCC technical papers and methodological guidance documents; (d) national climate policy assessments from countries in the study sample. Sources were considered independent if they originated from different author teams and institutions.

Relevance criterion: Directly addresses at least one of the following dimensions of accounting framework performance: (a) methodological characteristics (data requirements, boundary definitions, calculation procedures); (b) data availability and quality (coverage, temporal resolution, uncertainty levels); (c) institutional adoption (integration in international reporting frameworks, policy uptake); (d) policy implications for responsibility allocation (alignment with specific principles such as Polluter Pays, Beneficiary Pays, historical responsibility, or capacity-based approaches).

Specificity requirement: Describes an observable or measurable characteristic of the accounting framework rather than general qualities. To meet this criterion, the component must be verifiable through either: (a) examination of methodological documentation (e.g., “excludes emissions embedded in trade” can be verified in UNFCCC reporting guidelines); (b) analysis of available datasets (e.g., “comprehensive LULUCF coverage” can be confirmed by examining dataset structure); or (c) documented policy adoption (e.g., “used in Paris Agreement NDC reporting” can be confirmed through official UNFCCC submissions).

Once a SWOT component meets the mentioned criteria, in order to be included in the final coding matrix, each component will be scored on three indicators (Table 2).

Table 2. SWOT selection matrix and CDR composition.

Selection Criteria	High (3 Points)	Medium (2 Points)	Low (1 Point)
Data Quality and Availability (DQA)	Framework has comprehensive, regularly updated, publicly accessible databases with transparent methodologies (e.g., UNFCCC NIR/BTR for PBA)	Framework has established databases with some limitations in coverage or update frequency (e.g., MRIO-based CBA updated to benchmark years)	Framework faces significant data gaps, inconsistencies, or relies heavily on modeling assumptions (e.g., pre-1950 LULUCF in HBA)
Institutional Integration (II)	Framework is formally embedded in international climate governance (UNFCCC reporting, Paris Agreement NDCs)	Framework is referenced in policy discussions but lacks formal adoption (academic literature, national policy assessments)	Framework remains primarily in research domain with limited policy uptake
Policy Relevance to Responsibility (PRR)	Framework directly operationalizes a widely recognized responsibility principle (e.g., Polluter Pays, Beneficiary Pays, historical responsibility)	Framework provides partial or indirect insight into responsibility allocation	Framework’s connection to responsibility principles requires extensive interpretation or assumptions

Each SWOT factor receives a Composite Relevance Score (CRS):

$$\mathrm{CRS}={\displaystyle \frac{\mathrm{DQA}+\mathrm{II}+\mathrm{PR}}{9}}\times 100$$

(1)

This yields scores from 33 to 100, where only elements with a CRS ≥ 60 were included in the study to ensure relevance for our discussion.

This rubric-based approach provides structured prioritization that is transparent and replicable. While our evidence-based scoring approach provides systematic prioritization, alternative methods such as the Delphi technique could assign relative weights through expert consensus. We opted for literature-based criteria to ensure replicability and reduce single-analyst subjectivity, but future research could triangulate findings through structured expert elicitation.

2.4. Methodological Limitations

This study faces several methodological constraints that warrant explicit acknowledgment, relating to: (i) the inherent characteristics of SWOT analysis as a qualitative-evaluative method, (ii) data heterogeneity across accounting frameworks, (iii) temporal and spatial coverage limitations, and (iv) boundary decisions in framework selection and operationalization.

(i)

While SWOT analysis provides a structured approach to evaluating multidimensional policy instruments, it carries inherent limitations related to qualitative assessment and factor prioritization, which can introduce analyst bias. In order to address this limitation, we introduced the evidence–relevance–specificity thresholds, we introduced a structured coding framework with inclusion–exclusion criteria based on DQA, II and PR, and, finally included transparent scoring rubrics that include a quantitative assessment in our analysis.

Other alternatives, such as Analytic Hierarchy Process (AHP), TOPSIS, Entropy Weight Method or Gray Correlation Analysis could provide numerical rankings. These pairwise based comparison methods would introduce additional layers of subjective judgment, limiting replicability. These tools could prove valuable in further studies, but they necessarily fall out of this study’s scope.

(ii)

Data heterogeneity in gas coverage represents an additional layer of complexity in this study. For the gas coverage asymmetry, a sensitivity assessment between PBA, HBA and PCBA in their CO₂-only coverage version and full GHG + LULUCF version revealed high stability in the rankings across countries, with an average of (±2.93 positions). Particularly, when excluding Brazil from the top 5, the median positional variation in the top 5 was of ±0.6. The biggest changes being primarily LULUCF intensive countries such as Brazil (±10.6).

(iii)

The temporal misalignment between CBA data (2021) and the rest of the frameworks (2022) is acknowledged and addressed by conducting cross year sensitivity assessments between CBA-PBA, correlating the sequential time series from 2018 to 2021, revealing high rank stability with minimal annual rank shifts, thus justifying the inclusion of 2021 data on this study.

3. Results

3.1. Emissions Profile Comparison Across Accounting Frameworks

Our comparative analysis reveals dramatic redistributions of national emission profiles across the four accounting frameworks examined. Figure 2 presents the emissions profiles for the world’s largest emitters under each methodology.

Figure 2. Graphical comparison of the net GHG emissions (CH₄, N₂O and CO₂ fossil and LULUCF emissions) of the 15 biggest emitters under each accounting framework. (a) PBA emissions were obtained from official UNFCCC documents *, namely NIRs, BURs and BTRs (see Supplementary Materials Table S2), and are expressed in GtCO₂e. (b) CBA emissions were obtained from the updated work of [38]. CBA emissions were calculated by subtracting trade flows of carbon emissions from the baseline of territorial emissions, and are expressed in GtCO₂. (c) HBA emissions were obtained from the dataset [23] and express the cumulative total from 1850 to 2022 in GtCO₂e. (d) PCBA emissions were obtained by dividing national PBA emissions * by the total population estimates of each country from the World Bank. They are expressed in tons per capita (tCO2_e/p). * Iran, Vietnam, and India have not submitted the mandatory BTR, with their latest NC or BUR being from 2010, 2016, and 2020, respectively. China, Pakistan, and Saudi Arabia have all submitted BTRs, with the coverage year being 2021. For all the aforementioned, their data is an estimation from [23] for the year 2022.

Cross-framework variations reveal substantial redistributions. Under PBA, China leads with 13.161 GtCO₂e, followed by USA (5.489 GtCO₂e), EU27 (3.133 GtCO₂e), India (2.437 GtCO₂e), and Brazil (2.617 GtCO₂e). These mostly coincide with the five biggest emitters under CBA, China (10.320 GtCO₂), USA (5.572 GtCO₂e) EU27 (3.498 GtCO₂e), India (2.448 GtCO₂e) and Russia (1.360 GtCO₂e) instead of Brazil. CBA tends to maintain a similar ranking structure to PBA, narrowing the China-USA gap or the EU27 gap, with two notable exceptions: Brazil (jumps 10 spots from 15th under PBA to 5th under CBA) and the United Kingdom (jumps 8 spots from 20th under PBA to 12 under CBA), showing the impact of exports and imports of carbon in these rankings. HBA reverses positions at the top: USA (638.639 GtCO₂e cumulative) exceeds China (479.310 GtCO₂e), with Brazil elevated to 5th due to LULUCF emissions. PCBA presents the biggest systemic shifts positioning Saudi Arabia (29.607 tCO₂e/capita), Australia (21.487 tCO₂e/capita), Canada (19.665 tCO₂e/capita), Russia (18.198 tCO₂e/capita), and USA (17.381 tCO₂e/capita) at the top of the rankings.

Ranking Volatility and Stability Across Frameworks. The choice of accounting framework generates extreme volatility in national emission rankings. Some countries experience drastic shifts in their position, while others remain remarkably stable.

India exhibits the greatest fluctuation, dropping 19 places from 4th under PBA and CBA to 23rd under PCBA. Similarly, Saudi Arabia and South Korea each shift by 18 positions, with Saudi Arabia jumping from 11th (PBA) to 1st (PCBA), and South Korea moving from 23rd (HBA) to 5th (PCBA).

At the opposite end, nations like the United States, Germany, and Brazil show high stability, varying by only two or three positions, respectively, across all frameworks and consistently remaining among the top emitters.

These redistributions correlate directly with national characteristics: resource exporters like Saudi Arabia, Canada, and Australia rank higher under PCBA; early industrializers like the United Kingdom and Germany assume greater responsibility under HBA; and current manufacturing giants like China and India lead the PBA ranking.

Concentration patterns vary by framework. The analysis reveals distinct concentration patterns across frameworks. PBA demonstrates the highest concentration, with the top-five emitters representing 68% of analyzed emissions. This concentration reflects the current dominance of large manufacturing economies. Historical-based accounting shows even higher concentration, with the top-five historical emitters accounting for 74% of cumulative emissions since 1850, revealing strong path dependencies in emission patterns.

Per capita-based accounting demonstrates the lowest concentration among frameworks, reflecting the population-normalized distribution that reduces the dominance of populous countries. This pattern highlights lifestyle and resource intensity differences between nations rather than aggregate emission volumes.

For a more detailed analysis of all country rankings and ranking differential see Table 3.

Table 3. Cross framework country rankings. Cell shading indicates ranking differential, with green indicating lower variability and red-pink indicating higher variation across frameworks.

Country Code	PBA	CBA	HBA	PCBA	Highest Rank	Lowest Rank	Ranking Differential
ARG	21	23	16	10	10	23	13
AUS	19	18	12	4	4	19	15
BRA	5	15	5	7	5	15	10
CAN	12	14	10	2	2	14	12
CHN *	1	1	2	8	1	8	7
DEU	10	7	8	9	7	10	3
EU27	3	3	3	12	3	12	9
FRA	22	17	14	17	14	22	8
GBR	20	12	9	15	9	20	11
IDN	6	9	7	18	6	18	12
IND *	4	4	6	23	4	23	19
IRN *	8	11	15	6	6	15	9
JPN	7	6	11	11	6	11	5
KOR	13	8	23	5	5	23	18
MEX	14	13	13	20	13	20	7
PAK *	15	21	20	22	15	22	7
RUS	9	5	4	14	4	14	10
SAU *	11	10	19	1	1	19	18
THA	23	20	18	21	18	23	5
TUR	16	16	22	16	16	22	6
USA	2	2	1	3	1	3	2
VNM *	17	22	21	19	17	22	5
ZAF	18	19	17	13	13	19	6

* Iran, Vietnam, and India have not submitted the mandatory BTR, with their latest NC or BUR being from 2010, 2016, and 2020, respectively. China, Pakistan, and Saudi Arabia have all submitted BTRs, with the coverage year being 2021. For all the aforementioned, their data is an estimation from [23] for the year 2022.

3.2. SWOT Analysis Results

Each SWOT component presented in Table 4 meets the evidence-specificity-relevance thresholds described in Section Prioritization Matrix, with priority scores calculated using the Composite Relevance Score (CRS) rubric. All elements included in the SWOT matrix received a CRS ≥ 60). We present the results in two tables as follows, an internal one (Strengths-Weaknesses) and a contextual/external one (Opportunities-Threats).

Table 4. Internal characteristics of GHG accounting frameworks.

Strengths and Weaknesses
Accounting Framework	Strengths	Weaknesses
PBA	Institutional integration in international climate governance (UNFCCC, Kyoto, NDCs, etc.) Standardized reporting protocols (CRF tables, IPCC Guidelines) ensuring methodological consistency across parties Comprehensive multi-decade time series data (1990-present) for Annex I countries; expanding non-Annex I coverage under ETF Alignment with territorial sovereignty principles	Excludes emissions embodied in internationally traded goods Territorial boundary definition creates discontinuity in transnational supply chain attribution Does not capture scope 3 emissions Creates economic incentives for relocating emission-intensive production to lower-regulation jurisdictions
CBA	Captures full supply chain emissions through MRIO modeling (57 sectors, 141 countries in GTAP framework) Attributes emissions to final consumption point Integrates carbon leakage and offshore production into emission allocation Provides supply chain transparency across international production networks Scope 3 coverage includes upstream production and downstream consumption phases	Requires complex MRIO calculations with multi-source data integration (national accounts, trade statistics, emission inventories) Dependent on GTAP benchmark years (1997, 2001, 2004, 2007, 2011, 2014); interpolation needed for intervening years Attribution uncertainty increases with supply chain length; sectoral aggregation (57 sectors) may obscure product-specific flows Risk of double-counting emissions in multi-stage international production processes Methodological variations across MRIO models (GTAP, EORA, EXIOBASE) produce divergence in national totals
HBA	Comprehensive temporal scope capturing cumulative emissions 1850–2024; total 1750 GtCO2e documented Integrates multiple authoritative datasets (Global Carbon Project, PRIMAP-hist) with IPCC-consistent climate forcing calculations Ensemble approach (BLUE, Houghton & Nassikas, OSCAR models) for LULUCF reduces individual model bias Multi-gas coverage (CO2, CH4, N2O) with proper radiative forcing weights	Historical data quality deteriorates pre-1950; LULUCF estimates pre-1900 carry ±40–60% uncertainty Causal attribution challenges: colonial-era emissions, infrastructure legacy effects, technology transfer impacts Limited policy uptake; no UNFCCC mechanism explicitly incorporates cumulative historical responsibility Non-identity problem in attribution
PCBA	Population normalization enables cross-country comparison independent of absolute territorial size or economic scale Provides intuitive individual-level emission metrics and high communicational value for public engagement Universal applicability: derivable from any framework (PBA, CBA, HBA) through population division	Cannot function as standalone accounting framework; requires underlying PBA/CBA/HBA data Neglects the effects of population dynamics, age gaps, migrations or geographical differences Aggregation obscures demographic structure effects (age distribution, household size, urbanization rate) Does not account for territorial size, climate, or development stage differences affecting per capita baselines
Opportunities and Threats
Accounting Framework	Opportunities	Threats
PBA	Satellite-based monitoring (GHG-SAT, Carbon Mapper) and AI verification systems enhance accuracy and reduce reporting burden Compatible with existing NDC architecture and carbon pricing mechanisms Scalable to subnational (cities, regions) and supranational (EU ETS) jurisdictions Enhanced Transparency Framework (2024) mandates comprehensive BTR submissions, standardizing non-Annex I reporting Hybrid models combining PBA with consumption adjustments under development	Alternative frameworks (CBA, HBA) gaining traction in academic literature Major net-exporting economies (China: −1.246 GtCO2, India: −0.227 GtCO2 or Russia 0.352 GtCO2 net transfers) advocate consumption-based metrics in negotiations Institutional legitimacy challenged by documented carbon leakage cases and offshore production shifts Trade policy integration (EU CBAM, US CCA proposals) creates compliance conflicts with territorial accounting, and generates pressure for revision
CBA	EU CBAM implementation (2026 full enforcement) creates regulatory demand for consumption-based data Blockchain and IoT technologies enable product-level carbon tracking through supply chains Corporate scope 3 reporting requirements (GHG Protocol, TCFD) drive methodological refinement Green finance taxonomies (EU, China) increasingly reference lifecycle and consumption-based metrics Growing consumer awareness and ESG investing ($35 trillion AUM 2020) incentivize consumption-side transparency	Sovereignty concerns from developing countries regarding external attribution of domestic production emissions Lack of international political consensus on MRIO methodology standardization; no UNFCCC-endorsed protocol Political resistance from net-importing economies facing increased attributed emissions under CBA Data reliability challenges in countries with limited trade statistics or informal economies
HBA	Complementary metric to PBA for differentiated responsibility frameworks (CBDR-RC principle) Growing support from climate justice movements and Loss and Damage negotiations (COP27 fund establishment) Climate finance allocation formulas increasingly reference historical contributions (GCF replenishment discussions) Technology transfer justification framework: early industrializers owe capacity-building support	Systematic resistance from high historical emitters Data disputes over LULUCF historical estimates, colonial-era attribution, and boundary definitions Legal liability concerns; compensation claims potentially exceeding $100 trillion based on social cost of carbon Dominant forward-focused policy paradigm (Paris Agreement NDCs) lacks historical accountability mechanism
PCBA	Supplementary indicator in NDC reporting and climate policy assessment dashboards Equity benchmark for evaluating “fair share” of remaining carbon budget lifetime per capita Urban planning integration: city-level per capita targets enable localized climate action Personal carbon budget systems and carbon cards	Overshadowed by PBA in institutional frameworks; no UNFCCC reporting requirement for per capita metrics Data privacy concerns if individualized carbon accounting implemented below household level Measurement standardization challenges for sub-national and individual-level attribution Risk of diverting attention from systemic/structural emissions drivers to individual consumer responsibility

The PBA-SWOT analysis shows the highest institutional integration of all analyzed frameworks, with deep embedding in UNFCCC reporting requirements and NDC frameworks. Temporal coverage spans from 1990 to the present for Annex I countries, with standardized methodological protocols (IPCC guidelines, CRF tables). The framework excludes scope 3 emissions, simplifying calculations, but leaving out additional emission sources and allocations in trade [19,21]. ]. This territorial boundary definition assigns emissions to jurisdictions where production physically occurs, aligning most naturally with territorial sovereignty principles and strict causal responsibility interpretations of PPP. However, causal contribution alone cannot determine remedial responsibility without prior specification of underlying entitlements and justice principles [7,47]. Emerging opportunities center on technological advances in monitoring systems (satellite observation, AI-based verification) [52], while threats include competing frameworks gaining institutional traction and trade policy integration challenges (e.g., EU CBAM).

The CBA-SWOT profile shows CBA’s scope in capturing supply chain emissions through MRIO modeling (57 sectors across 141 countries in the GTAP framework). Strengths include full lifecycle coverage and alignment with scope 3 reporting standards [53]. CBA’s supply-chain attribution creates distinct mappings to responsibility principles: it can operationalize consumer-focused interpretations of PPP, benefit-based responsibility (BPP) through consumption of emissions-intensive goods, or capacity-based obligations (APP). Methodological complexities arise from MRIO calculation requirements and dependency on benchmark year interpolation [53,54]. Policy momentum from EU CBAM implementation (2026) and corporate ESG requirements represent significant opportunities, though sovereignty concerns [55] and lack of UNFCCC standardization pose implementation barriers.

The HBA-SWOT profile provides inputs on the framework’s wide temporal sope (1850–2024) encompassing all anthropogenic cumulative emissions. The ensemble approach (BLUE, Houghton & Nassikas, OSCAR models) reduces individual model bias for LULUCF emissions, although these remain highly variable, with ±40–60% uncertainty before 1900 [23,30]. Whether current populations inherit remedial duties for past emissions depends on theories of collective responsibility, benefit transmission across generations (BPP), or cosmopolitan equal access principles—distinct justice frameworks that HBA can serve but does not itself enact [8]. The framework shows limited policy uptake despite growing support from climate justice movements and Loss and Damage fund discussions. Major barriers include systematic resistance from high historical emitters and legal liability concerns [42].

Finally, the PCBA-SWOT profile highlights several key features of this framework. Cross-country comparisons, independent of territorial size, through population normalization appear as a strength, as does the communicational value of the framework [56]. PCBA most directly operationalizes Equal Per Capita Rights principles, treating atmospheric capacity to absorb GHG emissions as a global common resource to which all individuals have a proportionate claim [3,47]. Its dependence on external data sources and accounting bases (PBA/CBA/HBA data…) means it inherits a normative base whilst including an egalitarian adjustment, presenting risks of aggregation, obscuring internal demographic and geographical dynamics within the studied countries [57,58]. No institutional integration was found in UNFCCC reporting framework.

4. Discussion

This study has analyzed four accounting frameworks, PBA, CBA, HBA, and PCBA, revealing a fundamental distinction between empirical measurement and normative responsibility attribution. While accounting frameworks provide factual descriptions of emissions patterns (territorial production, consumption flows, historical accumulation, per capita intensity), their selection and application within policy architectures necessarily reflects prior normative commitments about what constitutes fair climate burden-sharing. The empirical question of who emits cannot be separated from the normative question of who is responsible when frameworks are institutionalized in policy contexts, as framework selection itself constitutes a policy choice with distributional consequences.

A critical methodological note is necessary before proceeding. The dramatic redistributions of emission patterns documented across frameworks (Section 3.1) provide interpretative keys to analyze broader trends and political viability, but are necessarily devoid of moral or ethical considerations. This element of analysis was approached in Section 1, and is the subject of extensive climate justice and ethics studies. Each of the four measurements is factually accurate within its own methodological logic. However, what these measurements cannot determine, and what our analysis deliberately does not prescribe, is which attribution systems should serve as the basis for policy obligations. Determining this requires prior normative frameworks. Our discussion focuses on how the frameworks “enact” or “operationalize” specific justice principles, thus exploring how measurement choices align with ethical commitments. This is analytically distinct from claiming that any framework is itself morally superior or that its distributional consequences are inherently fair.

4.1. Political Redistribution of Emission Responsibilities and How Accounting Frameworks Enact Justice Principles

Our analysis demonstrates that while accounting methodologies measure empirical phenomena (territorial emissions, embodied carbon in trade, cumulative historical contributions…) their institutionalization within policy frameworks is inherently normative and, thus, consequential. The institutionalization of frameworks within policy architectures shapes how justice principles become operationally feasible or marginalized.

The empirical redistributions documented in Section 3.1 demonstrate that framework choice profoundly affects which actors are attributed emissions, but determining which attribution is morally appropriate requires prior normative specification. Should responsibility track direct causal contribution (supporting PBA), final consumption and benefit (supporting CBA), cumulative historical impact (supporting HBA), or equal per capita access to atmospheric commons (supporting PCBA)? Or should it track capacity to remedy harms (APP), which cuts across all frameworks?

Different theories of distributive justice, libertarian property rights, liberal-egalitarian fairness, utilitarian welfare maximization, generate different answers to these questions and thus support different accounting frameworks for different responsibility types. Moreover, the same accounting framework can operationalize multiple justice principles: PBA can serve causal PPP, territorial sovereignty, or producer capacity-based approaches; CBA can serve consumer PPP, BPP, or consumption-based APP; HBA can serve intergenerational PPP, BPP through inherited advantages, or cosmopolitan cumulative equality.

PBA was designed to track direct emission sources for regulatory compliance within territorial sovereignty frameworks. Its structural exclusion of scope 3 emissions and trade-embedded carbon systematically obscures dimensions of responsibility emphasized by alternative justice principles. When China emits 1.246 GtCO₂ producing goods consumed elsewhere, PBA attributes this entirely to Chinese territorial responsibility. CBA would redistribute portions to importing nations based on benefit receipt and consumption patterns. Neither measurement is inherently “correct”, for they operationalize fundamentally different conceptions of responsibility grounded in distinct justice principles.

The temporal issue is particularly relevant when considering remedial responsibility and how we deal with past emissions. PBA cannot assign responsibility to compensate or mitigate for past emissions, and while HBA can tell us that 74% of historical emissions concentrated among the top 5 emitters, it says little about what we ought to do about it. Yet, attributing obligations and responsibilities to compensate to current populations for emitters of the past raises a “non-identity” problem [6,59] of note, if it were not for past emissions, the development trends that allowed current populations to exist would have never existed, making it problematic to hold past emitters retroactively accountable, especially since they no longer exist [24].

CBA presents a different temporal mechanism for dealing with remedial responsibility, framing current benefit as the product of past emissions. Thus, consumers are assigned the remedial responsibility for the embedded emissions in the products they use, particularly long-lasting infrastructures [24] providing an alternative solution. his temporal extension distinguishes CBA’s remedial function from HBA’s comprehensive historical attribution, which establishes factual baselines for climate debt discussions without necessarily resolving who bears present obligations.

Per capita emissions showed the biggest shifts in country rankings. Emission intensities vary substantially (Saudi Arabia’s 29.6 tCO₂e/capita compared to India’s 1.8 tCO₂e/capita), showing underlying tensions of the egalitarian or per capita justice frameworks. The division of atmospheric capacity in an equal per capita distribution has been dismissed as arbitrary in several occasions [7,14], alleging it needs to be understood in the broader context of resource allocation or development needs.

The ranking volatility documented in our results—18 of 23 countries shifting more than 7 positions across frameworks—provides empirical confirmation that framework choice restructures responsibility landscapes rather than revealing pre-existing obligations. India’s 19-position drop (4th under PBA to 23rd under PCBA) reflects the difference between aggregate and per capita attribution. Saudi Arabia’s 10-position jump (11th to 1st) reflects resource extraction intensity divorced from population size. These are not measurement errors requiring reconciliation but genuine normative disagreements about whether population, cumulative history, consumption patterns, or territorial production should determine responsibility.

4.2. Methodological Diversity and Suggestions for Integrated Use

The SWOT analysis reveals that frameworks’ strengths and weaknesses are structurally linked to their design purposes rather than representing correctable deficiencies. PBA’s institutional integration and standardized protocols derive from territorial sovereignty alignment, but this same territorial focus creates blind spots for carbon leakage and supply chain emissions. CBA’s comprehensive supply chain coverage through MRIO modeling generates corresponding weaknesses—methodological complexity, cascading uncertainties across 57 sectors and 141 countries, and CO₂-only coverage limitations (our data excludes CH₄, N₂O, LULUCF, creating ±2.93 position median ranking variations). HBA’s temporal depth (1,750 GtCO₂e since 1850) confronts data quality deterioration pre-1950 (±40–60% uncertainty for LULUCF) and achieves minimal policy integration despite decades of scholarly advocacy. PCBA’s communicational clarity necessarily aggregates away demographic structure, geographic conditions, and development stage differences affecting per capita baselines.

Rather than seeking universal solutions through weighted composite indicators, which conflate measurement with justice, integrated use should deploy frameworks for distinct policy purposes based on explicit normative deliberation. Different policy instruments inherently require different empirical foundations. Carbon border adjustments tracking embodied imports cannot function using territorial accounting alone, CBA provides necessary infrastructure. The EU’s Carbon Border Adjustment Mechanism, entering definitive phase in 2026, operationalizes this logic, requiring mandatory reporting of embodied emissions despite generating sovereignty objections from major exporters viewing consumption-adjusted attribution as external interference.

Climate finance negotiations often reference common but differentiated responsibilities (CBDR), requiring simultaneous consideration of historical contributions (HBA), current emissions (PBA), economic capacity (APP), and development rights. No single framework operationalizes this multidimensional conception. Other actions such as the Loss and Damage Fund demonstrate partial progress, while carefully avoiding explicit HBA-based allocation formulas due to political resistance from countries facing concentrated historical obligations, its existence acknowledges that historical responsibility dimensions warrant distinct treatment from mitigation obligations tracked through PBA-based NDCs.

Framework complementarity operates across functional dimensions serving different responsibility phases. HBA establishes historical contribution and potential climate debt through cumulative accounting. PBA monitors current compliance and near-term targets through territorial verification, now extending beyond Annex I countries as Enhanced Transparency Framework provisions mandate Biennial Transparency Reports by 2024. CBA addresses trade-embedded emissions and assigns remedial responsibility for inherited emission-intensive infrastructure through benefit-based attribution. PCBA benchmarks emission intensity and guides lifestyle-focused policies through population normalization revealing consumption disparities.

This functional specialization suggests graduated implementation rather than comprehensive replacement. Countries could report territorial emissions (PBA) as primary metrics while including consumption-adjusted profiles (CBA) and per capita intensities (PCBA) as standardized supplementary indicators, creating transparency without disrupting existing NDC architecture. Historical contributions (HBA) could inform climate finance negotiations while remaining distinct from mitigation target-setting. Technical infrastructure development facilitates such transitions: CBAM implementation requirements create comprehensive trade-flow databases essential for consumption-based accounting; satellite monitoring advances (GHG-SAT, Carbon Mapper) improve LULUCF estimates crucial for HBA calculations; blockchain-based verification platforms could integrate multiple framework outputs while addressing transparency concerns.

The political economy of framework advocacy reveals systematic patterns. Net exporters of embodied carbon (China: −1.246 GtCO₂; Russia: −0.352 GtCO₂) selectively reference CBA to highlight wealthy importers’ responsibility while defending PBA’s territorial logic when convenient. Net importers resist CBA precisely when it would increase attributed emissions, emphasizing sovereign control over production decisions. Early industrializers acknowledge historical contributions in principle while avoiding quantified HBA-based obligations in practice. This strategic instrumentalism, countries advocating whichever framework minimizes their own responsibility, suggests accounting debates function as distributional negotiations rather than technical refinements.

4.3. Implementation Challenges and Proposed Transition Pathways

The Implementation of hybrid models faces capacity, political, and temporal challenges requiring differentiated approaches. Institutional capacity disparities create systematic disadvantages for developing countries. Nepal exemplifies climate-vulnerable nations lacking sophisticated accounting infrastructure—consistently ranked among the world’s most vulnerable yet unable to participate meaningfully in framework debates requiring advanced quantification capabilities. CBA’s MRIO complexity and HBA’s century-spanning data requirements particularly disadvantage countries with limited statistical infrastructure and resources.

Addressing capacity constraints requires targeted support mechanisms. South-South cooperation networks for technical assistance, combined with dedicated capacity-building funds, could build statistical capabilities transcending individual frameworks. The Enhanced Transparency Framework’s flexibility provisions recognizing differentiated capacities offer partial solutions, though linking capacity-building funding to framework pluralism remains underdeveloped. Technology transfers focused on emissions tracking infrastructure—satellite monitoring systems, supply chain databases, verification platforms—could simultaneously advance multiple frameworks while building national statistical capacity.

Political resistance stems from the zero-sum redistributions documented in our results. The 18 countries experiencing >7 position shifts perceive framework advocacy as strategic positioning threatening national interests. Making normative stakes explicit—debating which justice principles should guide which policies rather than which measurements are “correct”—might reduce opposition by acknowledging multiple valid perspectives. The isolationist critique suggests addressing emissions distribution separately from broader justice considerations makes negotiations tractable [14], while the integrationist position argues climate burdens cannot be separated from development needs and historical responsibility [7]. The Paris Agreement’s structure partially reflects isolationist pragmatism: NDCs function through PBA territorial accounting while the Loss and Damage Fund addresses historical dimensions separately, suggesting framework pluralism may emerge from political necessity rather than principled design.

Temporal transition pathways could leverage existing institutional momentum. The 2024 Biennial Transparency Reports create opportunities for incorporating CBA and PCBA as standardized supplementary indicators without disrupting NDC compliance infrastructure. CBAM implementation by 2026 generates mandatory embodied emissions reporting, potentially creating comprehensive databases enabling consumption-based verification. These developments suggest incremental integration through policy-specific adoption rather than comprehensive governance redesign.

Dynamic weighting systems adjusting criteria emphasis based on development status could provide politically viable pathways. Least Developed Countries might emphasize per capita metrics and historical responsibility, while emerging economies balance aggregate contributions with development trajectories, and developed nations incorporate consumption-based metrics and capacity-based obligations. Such differentiation acknowledges that static universal formulas face political resistance, while flexible frameworks reflecting diverse development contexts and justice perspectives may achieve broader acceptance.

Legal and institutional barriers remain significant. The UNFCCC’s territorial jurisdiction framework, NDCs’ legally binding character under territorial accounting, and climate litigation’s focus on causal attribution create path dependencies favoring PBA. Altering these requires legal innovations, jurisdictional frameworks recognizing consumption-based responsibility, NDC supplementary reporting requirements, and climate litigation precedents incorporating beneficiary responsibility. The EU’s CBAM represents one such innovation, testing whether consumption-based policies can coexist with territorial NDC compliance. Its success or failure will substantially influence framework integration prospects.

4.4. Limitations and Future Research

Several limitations warrant acknowledgment. Our SWOT analysis, while systematically constructed using evidence thresholds (≥5 independent sources) and Composite Relevance Scores (CRS ≥ 60), relies primarily on the existing literature and documented policy positions rather than primary stakeholder consultation. The rapidly evolving policy landscape means that some opportunities and threats may shift quickly, and thus need updating. Additional verification methods such as AHP-TOPSIS or the composition of a DELPHI panel are suggested as part of future work, for they necessarily remained outside of this study’s scope.

Substantial data limitations constrain quantitative comparison. Pre-1950 data inconsistencies (±40–60% uncertainty for LULUCF emissions) and CBA’s CO₂-only coverage (excluding CH₄, N₂O, LULUCF) mean countries must be compared primarily through rankings and positions rather than absolute values when generating inter-framework statements. Our sensitivity analysis indicates manageable median ranking variations (±2.93 positions), but LULUCF-intensive countries like Brazil experience shifts up to ±10.6 positions. Temporal misalignment (2021 CBA versus 2022 for other frameworks) reflects MRIO benchmark year constraints, though high rank stability across 2018–2021 justifies this pragmatic compromise.

Additionally, our focus on national-level accounting overlooks sub-national variations and sectoral differences that may be crucial for policy implementation. The sample restriction to 23 countries representing >80% of global emissions excludes smaller emitters and precludes regional pattern analysis. Future research should examine how multi-criteria approaches might be applied at different scales, investigate the potential for dynamic weighting systems that adjust criteria based on development status or climate vulnerability, extend temporal analysis tracking countries’ positional shifts over time.

The temporal dynamics of responsibility also deserve further attention. How should accounting frameworks evolve as countries progress through different development stages? How might climate impacts themselves alter climate justice and policy implementation patterns? These questions necessarily lie beyond the scope of the current study.

5. Conclusions

National GHG allocation rankings have been shown to vary dramatically across accounting methodologies, with profound implications for climate governance and effectiveness. This study’s systematic comparison of PBA, CBA, HBA and PCBA frameworks of the 23 biggest emitters, representing >80% of total emissions in 2022 shows great volatility across the rankings, with 18 of 23 nations shifting more than seven positions: India drops 19 places (4th under PBA → 23rd under PCBA), while Saudi Arabia jumps 10 positions (11th → 1st), and the UK shifts 11 places depending on the framework applied.

This study’s key contribution lies in demonstrating how accounting frameworks provide factual measurements and work as the internal logic mechanisms of broader normative visions. However, selecting which framework should guide specific policy constitutes a normative choice that empirical measurement alone cannot justify. Climate justice’s multifaceted normative structure is what generates framework pluralism, not the other way around. Different responsibility types (compensation, mitigation, adaptation) align with different justice principles (polluter pays, beneficiary pays, ability to pay, equal per capita rights), each requiring distinct empirical foundations.

This study’s SWOT analysis demonstrates that each framework embodies distinct but necessary trade-offs linked to design purposes rather than correctable deficiencies. PBA’s institutional integration within UNFCCC frameworks and standardized protocols derive from territorial sovereignty alignment, yet this territorial focus systematically excludes scope 3 emissions and trade-embedded carbon (China exports 1.246 GtCO₂ in goods consumed elsewhere). CBA’s comprehensive MRIO supply chain coverage generates corresponding methodological complexity and cascading uncertainties across 57 sectors and 141 countries, with CO₂-only coverage creating ±2.93 median ranking variations. HBA’s temporal depth (1,750 GtCO₂e since 1850) confronts pre-1950 data quality deterioration (±40–60% LULUCF uncertainty) and achieves minimal policy integration despite decades of scholarly advocacy. PCBA’s population normalization enables cross-country equity comparisons but necessarily aggregates away demographic structure, geographic conditions, and development stage differences affecting per capita baselines.

The study’s principal contribution demonstrates that accounting frameworks provide factual measurements of different emissions dimensions—territorial production, trade flows, historical accumulation, per capita intensity—but their selection for policy purposes constitutes a normative choice with distributional consequences. Different policy instruments inherently require different empirical foundations: carbon border adjustments demand embodied emissions data (EU CBAM implementation 2026), climate finance negotiations invoke historical contributions and capacity (Loss and Damage Fund), mitigation targets utilize territorial verification (NDCs under Paris Agreement), and lifestyle interventions employ per capita benchmarks. Framework pluralism emerges not from measurement inadequacy but from the multifaceted nature of climate policy itself. Our findings support integrated governance approaches deploying multiple frameworks for distinct purposes rather than seeking universal measurement standards.