Building capacity for sustainability transformations through transdisciplinary experimentation: Empirical evidence from a novel methodology deployed in 7 countries

The production of organic coffee (Coffea arabica L.) under shade contributes to mitigating climate change, as it generates lower greenhouse gas (GHG) emissions than conventional cultivation, thereby reducing its carbon footprint (CF). This study estimated the CF of coffee produced by the Comon Yaj Noptic SPR de RL cooperative in the municipality of La Concordia, Chiapas, Mexico, with the aim of identifying critical emission points and opportunities for environmental improvement. Information was collected from 161 plots through visits and interviews with producers, and wet milling data was integrated using emission factors from the Intergovernmental Panel on Climate Change (IPCC). The CF was estimated per kilogram of green coffee produced, considering emissions from plot management to the packaging of the final product. In the primary stage (plot management to parchment coffee), CF was 0.401 ± 0.079 kg CO2e, with variability associated with altitude, plantation age, and planting density. The main sources were pulp decomposition (0.262 kg) and wastewater (0.078 kg) due to methane and nitrous oxide emissions. During processing (roasting, grinding, and packaging), CF was 0.415 kg CO2e, with roasting being the main source (0.304 kg), followed by packaging (0.086 kg) and grinding (0.009 kg). The average CF for the entire production chain was 0.816 kg CO2e, with a range of 0.758–1.271 kg CO2e, showing consistency and low impact compared to conventional systems. The results confirm that shade-grown organic coffee has low CF and show high sustainability potential. However, opportunities for improvement were identified, such as the use of clean energy, efficient wastewater management, and the use of pulp as a by-product.

Brazil is the main coffee producer in the world. However, the impacts of climate change driven by greenhouse gas (GHG) emissions pose a major challenge for agriculture in tropical regions. This study established a GHG inventory of coffee production on farms in southern Minas Gerais, Brazil, over a two-year period, adopting a cradle-to-farm-gate approach. It considered scopes 1 and 2 emissions from on-farm activities. The emission inventories were based on Intergovernmental Panel on Climate Change (IPCC) methodologies adapted for Brazilian conditions. The emissions were categorized in direct and biogenic and by area (in hectares) and production (kg of coffee). Electricity consumption, fossil fuel use, wood burning and fertilizer application were considered. Direct total emissions ranged from 2617 to 6211 t CO2e, 2.67 to 3.81 t CO2e ha−1, and from 1.52 to 4.59 kg CO2e kg−1 of coffee. Biogenic emissions ranged from 336 to 4955 t CO2e, 0.28 to 2.95 t CO2e ha−1, and from 0.32 to 2.21 kg CO2e kg−1 of coffee. Urea-based nitrogen fertilizers were the main source of direct emission and wood burning was the main source of biogenic emission. Management practices such as applying non-urea-based fertilizers, adjusting nitrogen rates according to soil analyses and manual harvesting contributed to mitigating GHG emissions. The observed emission intensities were consistent with other reported values for Brazilian coffee production. Further reductions may be achieved by adopting agroforestry systems, increasing coffee straw retention in the soil and replacing urea with alternative nitrogen sources, including slow-release fertilizers and urease-inhibitor technologies.

We analysed national Tier 2 greenhouse gas (GHG) inventories for dairy and other cattle in ten East and Southern Africa (ESA) countries to evaluate the variation and predictors of enteric methane (CH 4 ) emission factors (eEFs), and highlight priorities for improvement. We compiled 313 eEFs for dairy cows (n = 26) and other cattle (n = 287) using the Intergovernmental Panel on Climate Change (IPCC) 2019 Tier 2 method and country-specific data, and explored relationships between inputs used in IPCC equations and gross energy intake (GEI, MJ head -1 day -1 ) to identify reliable predictors of eEFs. The eEFs for high (80.74 ± 2.19 kg CH 4 head -1 year -1 ) and low productivity dairy cows (62.26 ± 0.97 kg CH 4 head -1 year -1 ) were 6.5 and 4.5% lower than the IPCC Tier 1a default EFs, respectively. Milk yield solely predicted GEI in dairy cows (r 2 = 0.73, RMSEP = 11.8%). The eEF for low productivity other cattle (56.09 ± 1.0 kg CH 4 head -1 year -1 ) was 16% higher than the IPCC Tier 1a default EF. Our eEF for high productivity systems (56.16 ± 1.0 kg CH 4 head -1 year -1 ) was 6% lower than the IPCC eEF of 60 kg CH 4 head -1 year -1 . Bodyweight, average daily gain and energy digestibility explained 87 and 90% of variation in GEI in growing (RMSEP = 8.1%) and young cattle (RMSEP = 14.6%), respectively. These simplified equations are useful for predicting eEFs in cattle, and highlight the priority country-specific data for Tier 2 inventories in the ESA region.

Horizon scanning the climate-altered world in 2100 under the Shared Socio-Economic Pathways (SSP) is an important tool for the Inter-Governmental Panel on Climate Change (IPCC). However, because the SSP are apolitical there is an opportunity for drawing across political science insights to complement and enhance their narratives accounts of the future. I make a contribution here by drawing on 44 futures literatures juxtaposed against the Institute for State Effectiveness’ ten-part functional typology. This constructs five conceptual climate-altered states at the terminus of the SSP - (1) sustainability state, (2) middle-of-the-road, (3) security state, (4) unequal world of states, and (5) fossil-fuelled state. This analysis enhances the IPCC’s mapmaking for policymakers and civil society by highlighting the consequences on future state functions of contemporary climate policy decisions. I conclude by discussing the limitations of this approach and outlining future opportunities for political science to complement, enhance and critique the IPCC’s SSP.

South Africa’s National Climate Change Response Policy requires accurate reporting of greenhouse gas (GHG) emissions. To achieve this, the South African Department of Forestry, Fisheries and the Environment initiated a process to develop country-specific emission factors (referred to as Tier 2 factors by the Intergovernmental Panel on Climate Change (IPCC)) for fuels produced or used locally, which are more accurate than those currently used (Tier 1). In this work, we report on the development of such county-specific emission factors for the solid fuels most commonly produced and used in South Africa, based on the analysis of 107 samples. The samples received were classified into types based on the IPCC fuel classification method, which has some differences from that used in South Africa. The CO2 emission factor for sub-bituminous coal, mainly used for power generation and in the liquid fuels/chemical sectors of South Africa, was found to be 97 807 kg CO2/TJ. For ‘other bituminous coal’, the CO2 emission factor was found to be 101 171 kg CO2/TJ. These emission factors are higher than the IPCC default (also referred to as Tier 1) factors, which have been in use in South Africa to date. As solid fossil fuel use is a major contributor to South Africa’s GHG emissions, this implies higher than previously estimated CO2 emissions from this sector as well as a higher contribution to global emissions.

The Shared Socio-economic Pathways (SSPs) presented in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) indicate that increased variability and more frequent extremes in precipitation are expected to raise the risk of droughts and floods in South-Eastern Europe. According to climate projections, the potential increase in precipitation in the region is insignificant, while the rising temperatures and the associated increase in potential evapotranspiration may lead to a substantial intensification of drought severity in the future. This study reviews previous research on droughts in Bulgaria and the analytical methods applied, thereby justifying the selection of the proposed methodological approach based on the Standardized Precipitation Evapotranspiration Index (SPEI-12 and SPEI-48). The SPEI data were obtained from the Global SPEI Database and cover the period from 1950 to 2024. The spatial characteristics of the index for the territory of Bulgaria are represented by grid cells with a spatial resolution of 0.5 degrees. The study examines changes in drought conditions across Bulgaria over the period 1950–2024, using SPEI-48 data. Long-term fluctuations in average SPEI values reveal a pronounced negative trend since 1984. The index reached its lowest value during the period 2000–2003 (−1.6), which is classified as a severe drought. Average SPEI-48 values range between 0.8 and −0.8 across the decades from 1950 to 2024, and have remained predominantly negative over the last five decades. In this context, the study highlights the need to implement measures for climate change adaptation and to address the increasing risk of drought.

ABSTRACT The overexploitation of natural resources and increasing dependence on these sources have caused an increase in solid waste generation, aggravating environmental impacts and contributing significantly to climate change through enhanced greenhouse gas (GHG) emissions. This scenario highlights the urgent need for circular economy strategies focused on reducing carbon emissions and mitigating environmental impacts. Continuous monitoring is crucial to evaluate current conditions and guide effective measures in the transition toward a sustainable waste management model. This study quantifies the total potential methane (CH4) emissions and analyzes the variation in CH4 production over time within a solid waste treatment and disposal facility. Emissions were estimated using three methodologies: the standard Intergovernmental Panel on Climate Change (IPCC) approach, the LandGEM® model (V3.02) provided by the U.S. Environmental Protection Agency (EPA), and the triangular gas production model. The results indicate peak emissions of approximately 72,82 and 2,30E-3 Gg for the IPCC and triangular models, respectively, while the LandGEM® model predicted a substantially higher peak of 8,31 Gg, suggesting emissions could persist for up to 124 years post-closure. In this study, the results are not directly comparable, as the estimates are strongly dependent on the assumptions and parameters adopted, reinforcing the inherent limitations of the available models when applied to realities different from those for which they were originally developed. Therefore, they should be interpreted as extreme envelopes of behavior intended to support the planning of strategies aimed at mitigating environmental impacts. Implications: The results presented in this study contribute significantly to the improvement of environmental management strategies in urban solid waste management complexes. The estimation of greenhouse gas (GHG) emissions allows the identification of critical points of methane and carbon dioxide release, supporting the adoption of more efficient control and mitigation technologies. In addition, the data obtained can be used by public managers and policymakers to develop action plans aimed at reducing emissions in the waste sector, aligning with the climate commitments assumed by Brazil under the Paris Agreement and promoting the transition to more sustainable circular economy practices.

Abstract The Climate Change Advisory Opinion (AO) by the International Court of Justice (ICJ) demonstrates the growing prominence of general principles of law in international law. The Climate Change AO was handed down at the end of the International Law Commission's project on general principles of law with the adoption of its Draft Conclusions. In the Climate Change AO, the ICJ accords general principles of law particular importance in environmental protection. This article documents how States identified general principles of law as the bedrock of the international climate change regime, and how the ICJ employed a systematic approach to ‘thicken’ climate change law, both in terms of normative content, obligations and consequences of breach. It then examines the general principles of law affirmed by the ICJ, in particular, the principles of common but differentiated responsibilities and intergenerational equity, both extracted from the broader general principle of equity. These principles guide the interpretation of ‘how far’ or ‘how much’, operating as balancing tools in relation to other obligations. The broader significance of this development lies in the ICJ's growing recognition of general principles of law as a means of supporting and structuring its legal reasoning. The article further argues that the normative development of these principles has been reinforced by reports of the Intergovernmental Panel on Climate Change (IPCC), and that Article 38(1)(c) of the ICJ Statute provides a broader gateway for taking account of normative contributions by actors such as the IPCC. The identification of customary law and peremptory norms ( jus cogens ) is more narrowly defined than general principles of law. The article concludes by examining the IPCC's role in underpinning the normative character of certain general principles of law, building on the interaction of law and science, and suggests that strengthening these principles may facilitate their more robust incorporation into future treaty‐design mechanisms.

Fluorinated greenhouse gases (F-GHGs) from the semiconductor industry represent a rapidly growing climate driver, yet localized accounting and abatement analyses remain scarce. To improve estimation accuracy and assess mitigation potential, we developed an improved accounting model by incorporating previously neglected sources, experimentally measuring destruction and removal efficiencies (DREs) for major process gases, and establishing gas usage coefficients by wafer size and process type. Applied to Shanghai's semiconductor sector in 2022, the model estimated 3.35 Mt CO2e emissions, dominated by process gases (47.93%) and electricity consumption (43.88%). Emissions based on measured DREs were 7.4-23.0 times higher than those from the Intergovernmental Panel on Climate Change (IPCC) 2019 default DREs, revealing overestimation in defaults. The share of indirect emissions increased markedly with wafer size, from 20.68% to 55.46%, driven by higher power intensity in advanced nodes and greater abatement efficiency. Plasma-based abatement achieved the highest DREs, yet their NOx byproducts warrant further attention. Without additional controls, emissions could increase to 4.20 Mt CO2e by 2035, whereas defined mitigation scenarios could achieve 37.49-77.69% reductions, primarily through enhanced gas abatement and low-carbon electricity adoption. The study emphasizes localized methodology and scenario analysis as essential for developing effective climate strategies in emerging industries.

The study conducted a detailed carbon footprint assessment of the Gandhi Krishi Vignana Kendra (GKVK) campus, University of Agricultural Sciences, Bangalore, using internationally recognised standards such as the Intergovernmental Panel on Climate Change (IPCC) Guidelines and the greenhouse gas (GHG) Protocol. As institutions are increasingly recognised for their contribution to GHG emissions through energy use, transport, waste and food services, this research quantified emissions across scope 1 (direct), scope 2 (indirect from purchased electricity) and scope 3 (other indirect emissions). Activity data were collected from institutional records, surveys and field assessments, while emission factors were sourced from IPCC (6th assessment report) AR6, the united nations framework convention on climate change (UNFCCC) GHG calculator v2.6 and Central Electricity Authority (CEA) guidelines. The total GHG emissions from the GKVK campus were estimated at 7606.545 tonnes CO₂e/yr, with scope 1 contributing 42.08 %, scope 2 contributing 20.46 % and scope 3 contributing 37.46 %. Major sources included liquefied petroleum gas (LPG) usage (1334884 kg CO₂e), grid electricity (1556180 kg CO₂e), food waste (1622855 kg CO₂e), refrigerant leakage (982430 kg CO₂e) and student commuting (879466 kg CO₂e). While the study provides a comprehensive institutional GHG baseline, it is limited to one academic year and excludes embodied emissions from infrastructure. The findings establish a replicable framework for Indian educational institutions to measure, manage and mitigate emissions. Future research should extend this model to multi-campus assessments and long-term carbon management planning, strengthening the roadmap toward carbon-neutral academic ecosystems and supporting India’s broader net-zero commitments.

In order to analyze the characteristics of fossil source CO2 emissions in the AAO process of municipal wastewater treatment, in-situ monitoring in a typical AAO process of a municipal wastewater treatment plant in North China was conducted in this work. The CO2 emission flux of each main process unit (selection tank, anaerobic tank, anoxic tank, aerobic tank, sludge return gallery, and secondary sedimentation tank) from September 2023 to August 2024 was obtained, and the 24 h day and night continuous change pattern and the emission contribution of fossil source CO2 was analyzed. Through 12 months of continuous monitoring, the direct CO2 emission fluxes of major process units such as selection tank, anaerobic tank, anoxic tank, aerobic tank, sludge return gallery, and secondary sedimentation tank were (30.20±2.85), (43.50±5.81), (44.41±4.69), (2 736.82±213.26), (82.68±7.21), and (11.59±1.15) g·(m2·d)-1, respectively. In summer, the AAO process showed "double peaks" of direct CO2 emission flux in 24 h, with peak periods at 06:00-09:00 [average 12 443.14 μg·(m2·s)-1] and 21:00-24:00 [average 12 395.38 μg·(m2·s)-1], both of which were 20% higher than the average value of direct CO2 emission flux in summer for 24 h. In winter, the AAO process showed a "single peak" of direct CO2 emission flux in 24 h, with peak periods at 09:00-12:00 [average 16 705.90 μg·(m2·s)-1], which was 21% higher than the average value of direct CO2 emission flux in winter for 24 h. The direct CO2 emission flux in winter [24 h average 13 811.81 μg·(m2·s)-1, CV=9.0%] was higher than that in summer [24 h average 10 388.41 μg·(m2·s)-1, CV=14.4%] but with smaller fluctuations. The monthly direct CO2 emission monitoring results showed that the average direct CO2 emission flux of the AAO process for 12 months was (1 094.86±80.97) g·(m2·d)-1 with large-size monthly fluctuations (CV=35.6%); the peak occurred in March 2024 [1 737.74 g·(m2·d)-1], which was 59% higher than the average value of 12 months. The direct CO2 emission intensity of the AAO process varied significantly with the seasons. The average direct CO2 emission intensities in spring, winter, summer, and autumn were (3 546.76±616.24), (3 089.66±363.98), (2 738.55±120.38), and (2 267.45±229.33) kg·d-1, respectively. The direct CO2 emissions of different process units were obviously different, and the aerobic tank was the main source of CO2 emissions in the AAO process, with an average annual emission flux, average annual daily emission intensity, and average annual emission factor (measured in CO2/COD) of (2 736.82±213.26) g·(m2·d)-1, (2 859.14±214.32) kg·d-1, and (3.83±0.75) kg·kg-1, respectively, which were significantly (P < 0.001) higher than those of other treatment units. The direct CO2 emission flux was significantly positively correlated with oxidation-reduction potential (ORP; P < 0.000 1), DO (P < 0.05), NO3--N (P < 0.05), and NO2--N (P < 0.05) and was significantly negatively correlated with TP (P < 0.01), NH4+-N (P < 0.01), and pH (P < 0.05). The direct CO2 emissions from fossil sources in the municipal wastewater treatment process were estimated based on the measured values of direct CO2 emissions, and the overall fossil source direct CO2 emission range of the AAO process was (38.05±5.31)-(148.41±20.72) g·m-3 (converted into fossil source CO2 emissions per m3 of wastewater treated). Direct CO2 emissions from fossil sources accounted for approximately 28.7%-67.1% of the greenhouse gas emissions of the whole plant calculated by the Intergovernmental Panel on Climate Change (IPCC) method. The direct CO2 emissions from fossil sources in municipal wastewater treatment plants are underestimated by the IPCC carbon emission accounting system, and it is recommended to include direct CO2 emissions from fossil sources in the carbon emission accounting system of wastewater treatment plants.

Earth observation for land representation: implementing the Paris Agreement requirements for greenhouse gas reporting

This study presents a methodological refinement of calculating greenhouse gas emissions from agricultural land management in the Czech Republic according to IPCC requirements. The authors utilize the SoilClim model providing input data in a 500 × 500 m grid for finer division of the Czech territory into climate zones according to IPCC. The research analyses the application of nitrogen fertilizers at the district level for the period 2015–2023 instead of national data. Results show significant dynamics of climate zones, where the extent of “dry” areas fluctuated in individual years from 40% to more than 80%. Implementation of the refined model led to a reduction in reported nitrous oxide emissions by an average of more than 9% in the reported period 1990–2023, representing savings of 20 Mt CO2 equivalent. The model-based use of district-level data on fertilizer application led to an additional reduction of 1.2 Mt CO₂ equivalent for the years 2015–2023. The study demonstrates that methodological refinement and the use of region-specific activity data can significantly influence the national greenhouse gas inventory. It highlights the need for continuous updates of calculation methods and activity data to improve the quality of national reporting and provides essential insights for a more effective emission reduction strategy in the agricultural sector of the Czech Republic.

<sec><title>Objective</title> Climate change, biodiversity loss, and environmental pollution are widely recognized as the triple planetary crisis. Among them, climate change has intensified the frequency and magnitude of extreme wind events, particularly typhoons, resulting in substantial impacts on ecosystems and human societies. China is located within the active typhoon belt of the northwest Pacific, where approximately 80% of annual typhoons make landfall. Coastal regions exhibit pronounced spatial heterogeneity in wind disaster risk due to complex interactions among topography, climate conditions, and socioeconomic development. Protected areas, as critical spatial units for biodiversity conservation and ecological security, are increasingly exposed to wind hazards. However, systematic assessments of wind disaster risk at the protected-area scale remain limited. Existing studies predominantly adopt the three-dimensional “hazard−exposure−vulnerability” framework proposed by the Intergovernmental Panel on Climate Change (IPCC). In this framework, hazard represents the intensity and frequency of disasters, exposure reflects the degree to which natural and social elements are affected, and vulnerability indicates the likelihood of system damage. While this framework has been widely applied to floods, earthquakes, heatwaves, and other natural hazards, its application to wind disaster risk in protected areas is still insufficient. In particular, previous studies often fail to integrate long-term hazard dynamics with ecological and socio-economic characteristics, limiting their ability to support targeted risk management and spatial planning. </sec><sec><title>Methods</title> To address these gaps, drawing on the <italic>Sixth Assessment Report</italic> of the Intergovernmental Panel on Climate Change, we developed a three-dimensional wind disaster risk assessment framework integrating hazard, exposure, and vulnerability. The framework combined multi-source environmental and socio-economic data to quantify wind disaster risk and reveal its spatial differentiation and temporal evolution. The Fuzhou Metropolitan Area was selected as the case study because it is located along China’s southeastern coast, characterized by frequent typhoon activity, diverse protected area types, and pronounced coastal-inland gradients, making it a representative region for examining wind disaster risks under climate change. Within this framework, wind disaster risk levels of protected areas in 1980 and 2020 were quantified and compared. Multi-criteria evaluation methods were applied to construct the hazard, exposure, and vulnerability indices, while the entropy weight method was used to reduce subjectivity in indicator selection. ArcGIS spatial analysis techniques, including spatial overlay,zonal statistics, and hotspot analysis, were employed to analyze the spatial patterns and temporal dynamics of wind hazards, exposure, vulnerability, and comprehensive risk. At the indicator level, meteorological, topographic, ecological, and socio-economic data were integrated to conduct comparative risk assessments across protected areas in the Fuzhou metropolitan area. </sec><sec><title>Results</title> 1） Wind disaster risk exhibited a clear spatial pattern characterized by higher risk in the south (0.57) and lower risk in the north (0.09), with coastal protected areas generally facing higher risk levels than inland areas. Wind disaster risk showed clear spatial clustering, with high-risk protected areas (0.61−0.66) concentrated in the southern and southwestern regions, medium−high risk areas (0.500−0.550) in the central transition zone, and low-risk areas (≤0.01) mainly distributed in the northern and northeastern regions, showing a pronounced south−north decreasing gradient. 2）Exposure levels across protected areas were generally moderate to high, while vulnerability showed an overall increasing trend from 1980 to 2020, indicating growing sensitivity of protected areas to wind hazards over time. In 1980, high-exposure areas (0.59−0.62) were located in northwest mountains and central hills, and low-exposure areas (0.04) were along the eastern coast. By 2020, high-exposure zones persisted but declined (e.g., from 0.59 to 0.31), with low coastal exposure unchanged, showing stable spatial patterns and an overall decrease. 3）Comprehensive wind disaster risk differed markedly among protected area types, ranked from high to low as forest parks to scenic areas, nature reserves, wetland parks, and geological parks. High-risk protected areas, including Jiulihu Scenic Area, Dafeishan, and Biqing Forest Parks (0.54−0.57), clustered in the south and south-central region. Medium-risk areas (0.30−0.50) occupied central and coastal transitional zones. Low-risk areas, such as Dongchong Peninsula, Sandu’ao, and Baiyunshan Parks (≤0.20), were located in the north and inland mountains. </sec><sec><title>Conclusion</title> Based on these findings, we proposed three planning optimization strategies for protected areas: optimizing functional zoning to reflect spatial risk differentiation, establishing dynamic wind hazard monitoring and early-warning mechanisms, and implementing pilot-based differentiated risk mitigation measures tailored to specific risk profiles. We analyzed wind disaster risks across temporal and spatial scales and visualized their dynamics through spatial mapping. Focusing on the protected area level, fine-scale spatial heterogeneity and temporal evolution patterns can be identified, which are often obscured in conventional assessments. By revealing the spatial patterns and evolution characteristics of wind disaster risk from a protected-area perspective, we provided an assessment framework that balances universality and practicality. The framework can offer practical support for climate-resilient planning and governance of protected area systems under ongoing climate change. </sec>

<sec><title>Objective</title> Climate change has intensified global social risks and ecological crises. The increasing frequency of climate hazards such as heatwaves and extreme precipitation, combined with the persistent degradation of forests, soils, and other ecosystems, has become a critical constraint on the sustainable development of human societies. In response to climate change, the Intergovernmental Panel on Climate Change (IPCC) has proposed two overarching strategies: climate mitigation and climate adaptation. Climate adaptation refers to reducing climate-related risks by decreasing human vulnerability or safeguarding ecosystem service functions, and ecological restoration is widely regarded as one of the key approaches to climate adaptation. Ecological restoration can effectively enhance ecosystem services, such as increasing carbon sequestration, reducing surface temperature, and improving water conservation capacity—thereby demonstrating substantial potential for strengthening climate adaptability. However, although existing standards and practices of territorial ecological restoration repeatedly emphasize the integration of climate adaptation considerations, the specific types of climate adaptation within territorial ecological restoration, as well as the pathways and methods for identifying restoration areas and determining their priority with climate adaptation as a core objective, remain insufficiently defined. Therefore, clarifying climate adaptation types relevant to territorial ecological restoration and developing robust identification and priority-setting pathways and methods constitute an urgent research agenda. </sec><sec><title>Methods</title> Taking the Chengdu-Chongqing urban agglomeration as the study area, from an exposure−sensitivity−resilience perspective, three types of territorial ecological restoration zones for climate adaption are defined: climate-exposed restoration zone (CERZ), climate-sensitive restoration zone (CSRZ), and climate-resilient restoration zone (CRRZ). The research route of this study consists of three major steps. 1) Based on the concepts of CERZ, CSRZ, and CRRZ and previous research findings, sample datasets and a double-layer indicator system comprising a “core-characteristic factors” were established to construct the machine learning dataset. 2) An ensemble machine learning model integrating three algorithms—maximum entropy (Maxent), random forest (RF), and categorical boosting (CatBoost)—through logistic regression (LR) was developed. The model performance was evaluated, and the spatial extents and restoration priorities of CERZ, CSRZ, and CRRZ were identified. 3) Differentiated response strategies were proposed according to the identification results and characteristics of CERZ, CSRZ, and CRRZ. </sec><sec><title>Results</title> 1) Compared with the single-layer system, the double-layer framework improves the identification performance by approximately 5%, and the ensemble model improves it by around 3% compared with individual algorithms. 2) Both CERZ and CSRZ show more than 20% of areas at medium or higher restoration priority, indicating an urgent need for ecological restoration in the study area. Meanwhile, CRRZ with medium or higher restoration priority accounts for over 50% of the Chengdu-Chongqing urban agglomeration, suggesting that regional resilience enhancement remains a long-term and challenging task. The spatial patterns of restoration priority for the three zones exhibit the following characteristics. For CERZ, the proportions of restoration priority from high to low are 4.98%, 10.56%, 13.38%, 19.77% and 51.31%. Restoration areas above medium priority total 53,020.54 km², mainly distributed in the karst regions of southern Sichuan and the Three Gorges Reservoir Area in northeastern Chongqing. For CSRZ, the proportions from high to low are 4.63%, 9.49%, 12.74%, 36.31% and 36.83%. Restoration areas above medium priority total 49,252.83 km², exhibiting more fragmented patches and lower clustering than CERZ. Unlike CERZ, restoration priority increases within medium and large cities, especially in areas characterized by fragmented vegetation and dense river nets. For CRRZ, the proportions from high to low are 11.50%, 26.60%, 26.27%, 18.61%, 17.02%. Restoration areas above medium priority total 118,035.92 km², showing both concentrated and dispersed patterns across low-altitude plains and hilly regions in the central parts of the Chengdu-Chongqing urban agglomeration. 3) CERZ aims to integrate engineering, ecological, and economic measures to effectively reduce the direct damage caused by extreme climate events. CSRZ aims to take river basins or key ecological function areas as spatial units to promote the recovery of ecological functions and the construction of ecological networks. CRRZ aims to advance the coordinated development of a green economic system and green infrastructure networks. </sec><sec><title>Conclusion</title> By building double-layer indicator system and ensemble machine learning model, this study clearly reveals the differentiated patterns of territorial ecological restoration in the Chengdu-Chongqing urban agglomeration from an exposure−sensitivity−resilience perspective. The findings provide a replicable framework and technical reference for the scientific and rapid identification of the key areas and nodes of territorial ecological restoration, optimizing restoration layouts and resource allocation, and enhancing regional climate adaptability. In the future, our research may incorporate higher-resolution datasets of samples and indicators to further refine the identification and planning of territorial ecological restoration zones. </sec>

We used ten representative semivolatile organic compounds (SVOCs) to investigate how changes in temperature and particle concentration affect future concentrations and partitioning of SVOCs in the gas phase, particulate phase, and on surfaces in the indoor environment. Using quantum mechanical methods and quantitative structure–activity-relationship (QSAR) tools, accurate temperature-dependent octanol/air partition coefficients (KOA) and vapor pressures (PL) of the subcooled liquid were calculated. Under the pessimistic greenhouse gas emissions scenario SSP5–8.5 as projected by the Intergovernmental Panel on Climate Change (IPCC), an annual shift in the SVOC equilibrium concentration between gas phase, particle phase, and surface by up to 30% is expected until 2100. The SSP5–8.5 scenario leads to higher SVOC emission rates and changes in the organic film thickness on surfaces. However, since primarily annual averages are considered, these temperature-related changes are small. Nevertheless, a model calculation for the emission rate of DINCH, taking into account extreme daily indoor temperatures, was performed. Since many developments up to 2100 can only be estimated, simplifying assumptions were made for emission rates, film thickness, and other parameters.

Abstract Integrated assessment models produce large ensembles of socioeconomic scenarios that are used profusely in climate change research. The Intergovernmental Panel on Climate Change (IPCC), non-governmental organizations or national climate committees often rely on ensemble statistics to identify mitigation strategies and set climate targets. A limitation of such evidence is the opportunistic nature of scenario ensembles: they are an unstructured, serendipitous collection of evidence. Drawing on concepts from physical climate science and ensemble analysis, we present an approach for the flexible, multidimensional weighting of emission scenario data that accounts for relevance, quality and diversity. Our illustrative application to the latest IPCC scenario database demonstrates a reduction in dominance of highly represented models and studies, and sees net-zero emission milestones differ to those originally reported. Our framework formalizes decisions otherwise made in an ad hoc manner, providing a tool contributing to the broader challenge of assessing ensembles of opportunity.

Recently, international judicial forums have issued landmark advisory opinions on the subject of the ocean–climate nexus. The opinions are based on the recognition of the interconnection between the United Nations Framework Convention on Climate Change (UNFCCC) and the United Nations Convention on the Law of the Sea (UNCLOS). All judicial forums stated that Small Island Developing States (SIDS) are a distinct focus due to their disproportionate vulnerability to climate change, as reported by the Intergovernmental Panel on Climate Change (IPCC). According to the opinions, SIDS could become uninhabitable in the coming years, necessitating urgent global climate action. The United Nations (UN) has acknowledged the unique challenges of SIDS through various resolutions, which emphasise the need for climate justice and adherence to the 1.5 C climate target. Sustainable Development Goal 14 (SDG 14) brought attention to the direct impacts of climate change on oceans and the issues faced by SIDS. This paper reviews the historical and legal developments necessary for the sustainable development of SIDS, emphasising the nexus between climate change, ocean governance, and human rights. It highlights the potential for further advocacy and the interconnected nature of SDG 14 with judicial opinions.

Measuring the resilience of historic areas is challenging due to their heterogeneity in scale, heritage type, multi-hazard exposure, and socio-cultural context, creating the need for a flexible framework aligned with the latest Intergovernmental Panel on Climate Change (IPCC) approaches. This study introduces the SHELTER framework, which takes the historic area as its primary unit of analysis while enabling a cross-scalar assessment, from artefact/building scale to urban and transregional contexts. Developed through a co-creation strategy and an extensive literature review, the framework integrates indicators for multidimensional, cross-scale, and systemic resilience assessment and monitoring. The indicators span hazards such as heatwaves, earthquakes, floods, subsidence, and wildfires and capture exposure and vulnerability, the latter being understood as the sensitivity and coping, adaptive, and transformative capacities of communities. Refinement using the RACER methodology yielded a concise yet comprehensive shortlist of indicators, providing both general overviews and specific insights tailored to historic environments. The framework’s efficacy was tested across five case studies, demonstrating adaptability and suitability in diverse historic areas. Overall, SHELTER moves beyond a traditional focus on physical vulnerability and risk management, offering a replicable, holistic set of resilience indicators that supports consistent assessment and monitoring while respecting the singularities of historic settings.