ABSTRACT Understanding the drivers of carbon emissions from the water–food–energy (WFE) system during urbanization is essential for achieving China’s carbon peak and neutrality goals; yet, systematic quantification in this domain remains limited. This study develops a consumption-based accounting framework to estimate WFE carbon emissions for 41 cities in China’s Yangtze River Delta (YRD) from 2000 to 2023. By integrating restricted cubic splines, boosted regression trees, and piecewise structural equation modeling, we systematically uncover the nonlinear impacts and multi-path transmission mechanisms of comprehensive urbanization on WFE emissions. The key findings are as follows: (1) WFE carbon emissions (WFEC) in the YRD exhibit a fluctuating pattern with an overall upward tendency since 2000, mainly driven by industrial and residential water use. (2) A significant nonlinear relationship exists between the composite urbanization index (UI) and both WFEC and WFE carbon intensity (WFECI), with a turning point at approximately UI = 0.2. (3) The marginal effects of population, spatial, and social urbanization on WFEC intensify over time, while that of ecological urbanization weakens; effects on WFECI are predominantly negative. (4) Population, economic, and spatial urbanization exert significant direct effects on emissions, alongside indirect effects mediated by resource use intensity and behavioral consumption structure, marking them as the most pivotal and complex dimensions. The present study provides new evidence on consumption-driven WFE emissions and offers theoretical and policy insights for low-carbon transitions in resource-intensive regions.

Agricultural transboundary water pollution induced by inter-regional trade poses a complex and pressing challenge for environmental governance. This study integrates an agricultural water pollutant emission inventory, multi-regional input–output model, responsibility-sharing framework, and ecological compensation scheme to establish the collaborative control of agriculture water pollution embodied in China’s inter-provincial trade. The findings reveal, firstly, that inter-provincial agricultural trade led to significant transfers of agricultural water pollution, predominantly flowing from economically developed provinces to less developed provinces, reflecting a mismatch between economic gains and environmental costs. Specifically, Gansu and Qinghai bear the largest agricultural water pollution impact (2.15 Kt and 3.25 Kt, respectively), while it is still a loss in terms of economic net benefits (0.21 trillion and 0.06 trillion yuan, respectively). Secondly, the economic benefit responsibility-sharing shows that for most provinces, responsibility lies between production- and consumption-based accounting and provides a feasible pathway for responsibility sharing. Third, economically developed provinces like Beijing, Jiangsu, and Zhejiang bear the largest compensation liabilities to others, with 1.60 Kt, 0.73 Kt, and 0.54 Kt, respectively. Conversely, provinces including Qinghai, Gansu, and Jiangxi require the greatest compensation inflows, at 2.55 Kt, 0.62 Kt, and 0.34 Kt, respectively. Finally, the maximum acceptable payment value for compensating provinces and the minimum acceptable compensation value for recipient provinces are identified. Our study elucidates the inter-provincial disparities in agricultural water pollution burdens and economic benefits, establishing a quantitative foundation for optimizing responsibility-sharing and compensation strategies in China, which is crucial for fostering regional cooperation in water pollution control.

Abstract Background Life Cycle Assessment (LCA) of electricity consumption requires temporally resolved emission factors. Two established metrics are the Average Emission Factor (AEF), allocating total system impacts to consumed electricity, and the Marginal Emission Factor (MEF), reflecting the response of marginal generation. Previous studies in regard to Germany (e.g. Seckinger & Radgen) provided hourly AEFs but focused mainly on the Global Warming Potential (GWP) and represented storage using constant annual discharge factors, neglecting round-trip losses and construction-related (upstream) emissions. This study addresses these limitations by proposing an extended electricity impact model that treats storage as an impact storage carrying time-varying charging impacts and allocates storage construction impacts to discharge cycles. Methods The reference model by Seckinger et al. and the new approach are applied to a consistent hourly dataset for Germany covering 2020–2070. Hourly AEFs and MEFs are calculated for GWP, AP, EP $$_{fw}$$ , ODP, POCP, ADPF, and ADPE. The new model accounts for storage round-trip efficiencies and consumption-based accounting of imports, exports, and charging. It also allocates construction impacts to discharge events using a cycle-based approach linked to the state-of-charge distribution. The results are compared with those achieved by existing studies, and a sensitivity analysis evaluates key assumptions on storage construction and power plant characterization factors. Results The new model yielded higher hourly emission factors than that from Seckinger & Radgen, particularly during periods of high storage activity. Differences increased over time with rising storage deployment and are primarily driven by construction-related impacts, while hourly attribution introduces additional temporal variability. Across most impact categories, the refined storage representation leaded to higher average and marginal emission factors in storage-rich scenarios. In contrast to GWP and several other categories, ADPE increased over time, indicating a shift in environmental burdens toward non-fossil resource use as renewable generation and storage expand. Conclusions Energy storage representation strongly influences time-dependent electricity emission factors, especially in future systems with high storage penetration. Although differences between modeling approaches are small in early years, explicitly accounting for time-varying charging impacts and storage construction emissions improves accuracy and avoids systematic underestimation of future electricity footprints. Extending dynamic LCA beyond operational emissions is therefore essential to capture emerging trade-offs in highly renewable electricity systems.

ABSTRACT Consumption‐based accounting (CBA) is gaining momentum as a transformative approach that complements production‐based accounting (PBA) by capturing the emissions embedded in global trade and final demand. Although PBA accounts for emissions generated within territorial production boundaries, CBA reallocates emissions according to final consumption, offering a broader view on carbon flows and responsibilities across regions. This article moves beyond traditional reviews by integrating insights from policy frameworks of international organizations and governments, offering a systematic exploration of the methodological advancements, data innovations, and multi‐scale applications of CBA. Novel contributions include identifying the gaps between current CBA approach and practical applications, particularly in aligning research with policymaking to achieve actionable outcomes. By addressing persistent challenges such as data limitations, model inconsistencies, and policy integration, this study proposes forward‐looking strategies to enhance the robustness and policy relevance of CBA.

Implications of a consumption-based accounting of greenhouse gas emissions from global dairy cattle systems

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.

Introduction In the pursuit of carbon neutrality, cities are increasingly measuring their greenhouse gas emissions. Most cities focus on territorial emissions tied to production, excluding consumption-driven emissions outside city boundaries. This gap is critical, as Scope 3 emissions can represent as much as 80% of cities’ carbon footprint. Addressing this limitation calls for urban consumption-based carbon accounting (CBCA). Yet, despite CBCA’s relevance for climate action, it has struggled to gain political legitimacy within European cities. This raises the question: How can urban CBCA achieve political legitimacy? Methods Based on semi-structured expert interviews with municipal practitioners in 17 European cities, we explore the barriers, enablers, and strategies used to enhance CBCA legitimacy. We develop a framework that describes the process of CBCA legitimation from exploration to political legitimacy. Results Results show that urban CBCA’s legitimacy rests primarily on cognitive legitimacy. Throughout the legitimation process, data plays a crucial role. Initially, access to data and clear calculation methodologies contributes to comprehensibility by making urban CBCA seem plausible and predictable. However, once CBCA comprehensibility is achieved metrics become less important than acting in ways that align with the broader understanding of consumption-based emissions. Finally, as CBCA measures affect citizens more directly, metrics resurface as means to validate impacts of past policy decisions and thus reinforce CBCA’s legitimacy. Discussion We discuss the various pitfalls and promising strategies to build political legitimacy for urban CBCA. This research contributes to the understanding of how urban CBCA legitimacy evolves over time. The legitimation framework developed can help inform policymakers in their endeavors to advance CBCA legitimation and institutionalization.

The equitable allocation of carbon emission responsibility is fundamental to advancing China’s industrial decarbonization, achieving its dual-carbon goals, and realizing regional sustainable development. However, prevailing interprovincial carbon accounting frameworks often neglect the coupled dynamics of economic benefits, energy flows, and ecological capacity, leading to systematic misattribution of industrial carbon footprint transfers. Here, we develop an integrated analytical framework combining multi-regional input–output (MRIO) modeling and net primary productivity (NPP) assessment to comprehensively quantify industrial carbon footprints and their transfers across 30 Chinese provinces. By embedding both the benefit principle (aligning responsibility with trade-generated economic gains) and the energy flow principle (accounting for interprovincial energy trade), we construct a dual-adjustment mechanism that rectifies spatial and sectoral imbalances in traditional accounting. Our results reveal pronounced east-to-west industrial carbon footprint transfers, with resource-rich provinces (e.g., Inner Mongolia, Xinjiang) disproportionately burdened by external consumption, impacting the balance of sustainable development in these regions. Implementing benefit and energy flow adjustments redistributes responsibility more fairly: high-benefit, energy-importing provinces (e.g., Shanghai, Jiangsu, Beijing) assume greater carbon obligations, while energy-exporting, resource-dependent regions see reduced responsibilities. This approach narrows the gap between production- and consumption-based accounting, offering a scientifically robust, policy-relevant pathway to balance regional development and environmental accountability. The proposed framework provides actionable insights for designing carbon compensation mechanisms and formulating equitable decarbonization policies in China and other economies facing similar regional disparities.

This study evaluates the impact of national Emissions Trading Scheme (ETS) in China on inter-provincial and international carbon emission transfers using a multi-regional Computable General Equilibrium (CGE) model, incorporating production- and consumption-based accounting, regional trade linkages, and carbon market mechanisms. Significant regional disparities in emissions reductions and economic impacts are identified, particularly between northern and southern provinces divided by the Qinling-Huaihe Line. Northern provinces achieve greater production-side emission reductions and experience lower marginal abatement costs than southern provinces, reflecting industrial structural differences. The ETS notably eliminates production- and consumption-side emissions, with greater effects on production-side emissions due to higher supply-side responsiveness. Carbon trading significantly lowers net carbon transfers in inter-provincial and international trade, though regional heterogeneity remains. A novel carbon trading terms index highlights regional variations in carbon balances, underscoring the necessity for differentiated regional carbon targets, inter-provincial compensation, and targeted mitigation strategies addressing structural disparities.

Abstract We provide an axiomatic approach to the allocation of responsibility for GHG emissions in supply chains. Considering a set of axioms standardly used in networks and decision theory, and consistent with legal principles underlying responsibility, we show that responsibility measures shall be based on exponential discounting of upstream and downstream emissions. From a network theory perspective, the proposed responsibility measure corresponds to a convex combination of the Bonacich centralities for the upstream and downstream weighted adjacency matrices. Scope 1 emissions, consumption-based accounting and income-based accounting are obtained as particular cases of our approach, which also gives a precise meaning to scope 3 emissions while avoiding double-counting. We apply our approach to the assessment of country-level responsibility for global GHG emissions and to sector-level responsibility in the USA. We examine how the responsibility of countries/sectors varies with the discounting of indirect emissions. We identify three groups of countries/sectors: producers of emissions whose responsibility decreases with the discounting factor, consumers of emissions whose responsibility increases with the discounting factor, and an intermediary group whose responsibility mostly depends on the network position and varies non-monotonically with the discounting factor. Overall, our axiomatic approach provides strong normative foundations for the definition of reporting requirements for indirect emissions and for the allocation of responsibility in claims for climate-related loss and damage.

Abstract Purpose Life cycle impact assessment (LCIA) quantifies the potential impacts of environmental loads in the characterization step and evaluates their significance in the normalization step. This study develops consumption-based characterization factors (CFs) and normalization values (NVs) for abiotic resource use using a multi-regional input–output model. Consumption-based accounting in these steps is critical for ensuring consistency between the scope of these steps in LCIA and the overall evaluation scope of the life cycle assessment (LCA) study. Methods We calculated the consumption-based CFs and NVs for the target year 2015, covering 189 countries and regions for 29 mineral resources and three fossil fuels. These calculations were based on estimates of induced mine production and the adoption of country-level mine production-based CFs. The mining sector in the Eora multi-regional input–output database was disaggregated using country-level mine production data and trade statistics, enabling the estimation of induced mine production for each consuming country. A user cost model was adopted to calculate country-level mine production-based CFs. Results and discussion Consumption-based CFs varied significantly, with the maximum values being up to 3,300 times higher than the minimum, depending on the consuming countries. This highlights the importance of considering supply chain differences when assessing the potential impacts of abiotic resource use. The USA had the largest consumption-based NVs, followed by China and Brazil, with fossil fuels as the primary contributing resources. Some countries (e.g., Japan and Germany) exhibited notably higher consumption-based NVs compared to mine production-based NVs, reflecting their scarcity of primary resources in-country and underscoring the relevance of consumption-based NVs. Compared to previous studies with lower resolution for target resources, the consumption-based NVs developed in this study, which differentiate a greater variety of resources, offer more plausible results and enable more flexible analyses targeting specific resources. Conclusions Consumption-based accounting of the potential impacts associated with resource use can support LCA practitioners in conducting region-specific analyses without the need to identify mining countries for abiotic resources. The findings can also be utilized to analyze the responsibilities of consuming countries, sustainable supply chain management, and country-level supply risk assessments. Future work should focus on improving the disaggregation of metal-related sectors using smelter, refinery, and manufacturing data.

Greenhouse gas (GHG) emissions, and in particular CO2, are critical drivers of climate change, necessitating coordinated global efforts to mitigate their impact. This has led the Kingdom of Saudi Arabia (KSA) to launch several ambitious initiatives to curb its own emissions. However, there remain significant challenges when it comes to measuring outcomes, due to uncertainties in the existing methods and data. This current study therefore employs Production-Based (PB) and Consumption-Based (CB) emission accounting methods for KSA, emphasizing strategies to minimize the uncertainty inherent in these models. The results reveal that KSA is a net carbon exporter, with PB emissions (523 million tonnes CO2 equivalent (CO2e)) exceeding CB emissions (471 million tonnes CO2e). In addition, the validity of the applied methodology is supported by the literature. This research finds that private households form the largest contributors, along with sectors including electricity, land transport, water, and construction, as well as chemical, rubber, and plastic. The findings also confirm the potential for targeted policies to reduce emissions, i.e., the promotion of energy-efficient appliances, enhanced home insulation, public transportation, and recycling. Furthermore, this study highlights the importance of national investment in the accurate measurement of emissions and detailed energy statistics.

Unravelling food carbon footprint heterogeneity in metropolitan areas using Tokyo as a case study

Erratum to: A justice and innovative way ahead of consumption-based emission accounting approach

Allocation of carbon emission responsibility among Chinese cities guided by economic welfare gains: Case study based on multi-regional input-output analysis

While highly connected food chains provide numerous benefits, they lack traceability and transparency. As such, understanding the spatial heterogeneity in their environmental burdens is critical for targeted interventions. This is especially important for nutrient-related impacts such as nitrogen since the release of reactive nitrogen has been linked to loss of biodiversity and decrease in water quality in different parts of the world. Animal feed production is heavily dependent on synthetic fertilizers, and the consumption of beef products, in particular, is associated with high nitrogen footprints. Although there is a rich body of work on nutrient footprints of beef production, there is a gap in understanding the spatial distribution of the nutrient releases throughout the beef supply chain in the U.S. We present an optimization-based framework to trace supply chain networks of beef products at the county level. Using publicly available data, we construct a weighted network of nutrient flows based on mass balance, including synthetic fertilizers, manure production, and crop uptake and residues. The results show that beef consumption in a county can be associated with nitrogen losses in hundreds of counties. One year worth of beef consumption in the United States released approximately 1.33 teragrams (Tg) of N to the environment, and most of it as diffuse pollution during the feed production phase. Analysis also revealed the huge disparity between consumption-based and production-based impacts of beef and the need for considering consumption-based accounting in discourse around the environmental sustainability of food systems.

A justice and innovative way ahead of consumption-based emission accounting approach

The relationships of SDG 12 (responsible consumption and production) with other sustainable development goals (SDGs), both direct and indirect, necessitate a systematic analysis to understand its pivotal role in achieving other SDGs. This work focuses on a threefold investigation through a scientometric framework. Initially, the study sought to map and analyze the naturally formed linkages between SDG 12 and other SDGs by examining the literature specifically devoted to SDG 12, thereby revealing the SDGs that are strongly linked to SDG 12. The subsequent phase of the investigation identified prominent topics related to SDG 12 that require detailed exploration. Finally, the selected topics are mined through a methodical approach termed flow vergence gradient analysis, allowing for the revelation of significant contributions within each topic. Through the analysis of the SDG linkage map, SDG 13 (climate action), SDG 7 (affordable and clean energy), SDG 11 (sustainable cities and communities), and SDG 15 (life on land), among others, were recognized as closely linked to SDG 12. Following this identification, five major topics—Industrial Symbiosis, Electronic waste, Carbon emissions, Life Cycle Assessment, and Green products—were deemed suitable for comprehensive mining to extract pivotal contributions. As policy recommendations, adopting a multifaceted approach to e-waste management and sustainable practices is imperative. Implementing consumption-based accounting (CBA) to achieve SDG 12 holistically will be useful. Businesses must align with circular economy principles, minimize hazardous materials, and adhere to low-emission, green supply chain practices. The emphasis is also on the need for proactive R&D collaboration with academia to meet SDG 12 targets, alongside engaging in community awareness through corporate social responsibility initiatives.

We empirically examine the trade-related environmental impacts of the Belt and Road Initiative (BRI) using a novel technology-adjusted consumption-based accounting in addition to traditional accounting schemes and data from the Eora Global database from 1995 to 2015. We find that BRI trade accounted for 3-quarters (5.01 Gt) of global traded emissions in 2015. BRI countries account for 60%–75% of (non-BRI) developed-world consumption-based emissions. While developing (BRI) countries import 8%–42% of their consumption needs from China, they account for half of the China’s imported emissions. Our analysis reveals that technological adjustments in export sectors significantly alter the magnitude of outsourcing and emission responsibility assigned to both BRI and non-BRI countries. This leads to a notable shift in net trade balance emissions. We find that developed (BRI and non-BRI) countries have reduced emissions primarily through decoupling and outsourcing. Our findings demonstrate that BRI trade has diverse environmental effects; exports from more carbon-efficient (BRI and non-BRI) developed countries are likely to reduce (or avoid) emissions in developing (BRI) countries and vice versa. An important implication of these findings is that China’s BRI-led outsourcing and investments have the potential to yield significant environmental benefits by accelerating the transition to renewable energy in developing countries participating in the initiative.

Indonesia's contribution to global carbon flows: Which sectors are most responsible for the emissions embodied in trade?