Carbon Balance and Management最新文献

{"title":"Quantifying carbon benefits from protecting and restoring tropical forest landuse mosaics in Vanuatu","authors":"Clint Cameron,&nbsp;Olivia Bird,&nbsp;Jeffery Lava,&nbsp;Andrew Finaly","doi":"10.1186/s13021-026-00505-6","DOIUrl":"10.1186/s13021-026-00505-6","url":null,"abstract":"<div><h3>Background</h3><p>Forest loss and degradation in Vanuatu is a pertinent environmental issue, particularly for rural communities who are inherently reliant on subsistence-based agriculture derived from tropical forest landuse mosaics. Payment for Ecosystem Services (PES) projects provide a mechanism to diversify agricultural livelihoods while reducing deforestation and forest degradation and promoting ecosystem restoration. This study evaluates the <i>Life &amp; Land Project</i>, a PES initiative working with communities at Whitegrass and Middlebush on Tanna, and South River on Erromango. Few primary studies in Vanuatu have quantified forest carbon stocks or evaluated changes in carbon stocks resulting from PES interventions.</p><h3>Research objectives and methods</h3><p>These knowledge gaps are addressed by assessing: (a) forest carbon stocks and structural characteristics; (b) the drivers and rates of deforestation and forest degradation, together with pressures affecting forest health, to inform management interventions; and (c) the potential carbon benefits of implementing these interventions using a gain—loss approach.</p><h3>Results</h3><p>Results showed high variability in structural composition and carbon stocks, reflective of differences in landuse and environmental pressures. The mature, predominantly primary tropical rainforest at Whitegrass had an average carbon stock of 490.7 ± 32.6 Mg C ha⁻¹, in contrast to the invasive vine-smothered degraded forests of Imanaka Creek (Middlebush) and the Forest Enhancement Zone of South River (107.3 ± 10.7 Mg C ha⁻¹ and 128.2 ± 22.7 Mg C ha⁻¹ respectively). Forest loss at Whitegrass was driven through logging, ad-hoc garden development, and quarry operations at an estimated rate of 3.55 ha⁻¹ year⁻¹, while invasive vines were the main impediment impacting forest health at most sites. To address pressures, a conservation area at Whitegrass (<i>Forest Protection</i>) was established with community developed and enforced by-laws, while <i>Forest Restoration</i> and <i>Improved Forest Management</i> interventions involved undertaking vine clearance, maintenance, and replanting with a mix of agro-forestry and native species (all sites). Overall carbon benefits are estimated at 6,688 Mg CO₂e year⁻¹.</p><h3>Conclusions</h3><p>The study helps Vanuatu and other Small Island Developing States, particularly those of the South Pacific, strengthen the platform from which other PES projects could be developed and implemented.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"21 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13711963/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149284604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"China’s carbon emission trading and income inequality: evidence from factor substitution","authors":"Shixiong He,&nbsp;Lei Jiang,&nbsp;Mengxu Li,&nbsp;Jianghua Liu","doi":"10.1186/s13021-026-00503-8","DOIUrl":"10.1186/s13021-026-00503-8","url":null,"abstract":"<div><p>As carbon pricing mechanisms gain global prominence, understanding their distributional impacts, particularly in developing economies, becomes crucial for the design of equitable climate policies. We explore the effect of carbon emission trading (CET) policy on income inequality in China through integrated theoretical and empirical analysis. We find that the CET policy significantly reduces income inequality, and this conclusion passed the robustness tests. Theoretical analysis shows that if carbon emission allowances are treated as an input factor of production, when carbon prices are relatively low, firms tend to substitute labor for carbon emission allowances, thereby increasing the labor income share (LIS). Empirical testing also confirms that the mitigation of income inequality through CET is attributable to the increase in the LIS. In addition, the equalizing effect is more pronounced in cities with higher initial income inequality and greater marketization. Government environmental expenditure and smooth labor market mobility also have positive synergistic effects. Our research provides policy insights on balancing emissions reduction with social equity.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"21 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1186/s13021-026-00503-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149034575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drying crisis under greening: a study on the drought trigger thresholds of vegetation carbon fixation loss in karst areas","authors":"Niu Shuai,&nbsp;Yecui Hu,&nbsp;Yufan Wang","doi":"10.1186/s13021-026-00500-x","DOIUrl":"10.1186/s13021-026-00500-x","url":null,"abstract":"<div><p>Global warming has intensified the frequency of droughts. Once droughts exceed a critical threshold, they pose a severe threat to vegetation growth and limit its carbon fixation capacity. However, current research still has an insufficient understanding of the probabilistic thresholds at which drought triggers the loss of vegetation carbon fixation (VCF) capacity under sustained greening, especially lacking a systematic comparison of the differences between karst areas (KA) and non-karst areas (NKA) under complex hydrogeological conditions. For this purpose, this study uses the Copula method and conditional probability to derive the VCF loss and its trigger thresholds under different drought scenarios from 1982 to 2022, and explores the key driving factors influencing these thresholds. The results show that: (1) Compared to non-karst areas (NKA), VCF in the KA of southern China is more sensitive to drought, with a higher response intensity and a shorter lag time. (2) The probability of VCF loss in KA is significantly higher than in NKA, and the drought trigger threshold is also higher. (3) The VCF thresholds in both KA and NKA are primarily driven by the “temperature (TEM)- moisture” coupling. However, KA show higher TEM sensitivity and dependence on deep soil water storage (SWC_3-4), while in NKA, the thresholds are influenced by multiple factors, including shallow soil water storage (SWC_1-2), atmospheric vapor pressure deficit (VPD), and soil organic carbon (SOC). From the perspective of probabilistic thresholds, the results reveal the hidden drought vulnerability of VCF capacity in humid greening regions, and can provide a quantitative basis for maintaining regional carbon sink stability, implementing zonal vegetation management, and promoting proactive drought risk prevention and control.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"21 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13501861/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148811814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the coupling coordination of urban resilience and urban low-carbon in the Yellow River Basin","authors":"Jing Bai,&nbsp;Ying An,&nbsp;Xiang Wang,&nbsp;Xi Wang","doi":"10.1186/s13021-026-00489-3","DOIUrl":"10.1186/s13021-026-00489-3","url":null,"abstract":"<div><p>Against the backdrop of intensifying global climate change and increasingly prominent resource constraints, achieving synergies between resilience enhancement and low-carbon urban development has become a critical issue for advancing sustainable urban development. To address this challenge, this study constructs an evaluation framework for urban resilience (UR) and low-carbon development (LCD). It quantifies the resilience and low-carbon development levels of 60 cities in the Yellow River Basin (YRB) from 2006 to 2021. Using a coupling coordination degree model, the research reveals the interactive mechanisms between UR and LCD, further analyzing how their synergistic evolution promotes regional sustainable development. Results indicate that from 2006 to 2021, the UR in the Yellow River Basin rose from 0.13 to 0.24, with an average annual growth rate of 5.64%. Concurrently, the LCD increased from 0.06 to 0.13, with both metrics exhibiting an upward trajectory. During this period, the coupling coordination degree (CCD) between UR and LCD demonstrated a steady positive upward trend, increasing from 0.286 to 0.395. However, regional development imbalances remain prominent, solidifying into a distribution pattern of “downstream &gt; midstream &gt; upstream.”These findings indicate that synergistically enhancing UR and LCD represents a crucial pathway for the YRB to achieve its dual carbon goals and sustainable development. This study provides a theoretical framework and decision-making reference for formulating integrated governance strategies that synergistically advance climate mitigation and adaptation in the YRB and other similar regions globally.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"21 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13729307/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149316941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ride the green: How does the national carbon market affect corporate breakthrough green innovation?","authors":"Lu Zhang,&nbsp;Yan Song","doi":"10.1186/s13021-026-00493-7","DOIUrl":"10.1186/s13021-026-00493-7","url":null,"abstract":"<div><p>As a core market-based instrument for carbon management, China’s national carbon market is expected to reduce emissions and facilitate the technological transformation required for decarbonization. However, whether it primarily promotes breakthrough or incremental green innovation remains unclear. Using firm-level data and a double machine learning model, this study examines the effect of the national carbon market on firms’ breakthrough green innovation. The results show that the national carbon market significantly promotes patenting in newly entered green technological domains. This effect is more pronounced among state-owned enterprises, particularly local state-owned enterprises, firms operating in more concentrated markets, and those located in regions with stricter environmental governance. Mechanism analyses indicate that this effect is primarily driven by alleviated financing constraints and improved resource allocation. In addition, the green innovation effect is strongest when the carbon market is combined with green subsidies, followed by innovation subsidies. These findings provide new evidence on how carbon market policies shape the technological direction of green innovation and offer policy implications for improving carbon market design.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"21 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1186/s13021-026-00493-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149331975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling forest carbon stocks on the Canary Islands","authors":"Rüdiger Otto,&nbsp;Juan José García-Alvarado,&nbsp;Elena Rocafull,&nbsp;Natalia Sierra Cornejo,&nbsp;Severin D. H. Irl,&nbsp;Felipe Rodríguez Arvelo,&nbsp;Ricardo Ruíz-Peinado,&nbsp;José María Fernández-Palacios,&nbsp;Lea de Nascimento","doi":"10.1186/s13021-026-00488-4","DOIUrl":"10.1186/s13021-026-00488-4","url":null,"abstract":"<div><h3>Background</h3><p>Forest carbon mapping is crucial for sustainable forest management, climate mitigation, biodiversity conservation, ecosystem service provision and land-use planning. Carbon stocks have been studied at regional to global scales and across various biomes. However, island-wide studies of carbon stocks and carbon mapping remain limited. Here, we present the first high-resolution (50 m) spatial mapping of forest carbon for the Canary Archipelago. Combining structural field data from the Spanish National Forest Inventory plots with airborne laser scanning, Sentinel-2 multispectral satellite data and fine-scale interpolated climatic variables, we modeled total, aboveground and belowground carbon density of 18 forest types, using machine learning approaches, including Boosted Regression Tree and Random Forest models.</p><h3>Results</h3><p>Forests across the Canary Islands store an estimated 10.26 Tg of carbon. Canarian pine forests contain the largest carbon pool (57%) due to their extensive distribution area, whereas mature laurel forests exhibit exceptional carbon densities. In humid laurel forests, average carbon densities reached 413.2 ± 149.5 Mg C ha⁻¹, exceeding previous regional estimates and approaching levels of primary tropical forests. The high spatial heterogeneity of carbon densities across forest types and islands was best explained by structural stand attributes, such as tree canopy cover and volume, and climatic factors with carbon stocks being more strongly associated with moisture than with temperature. Both statistical modelling approaches performed similarly in terms of efficiency, accuracy and error statistics, and the selection of the best model depended on the specific island.</p><h3>Conclusions</h3><p>Our approach integrates field data with advanced remote sensing tools and machine learning algorithms to produce a high-resolution and accurate carbon map of topographically complex oceanic islands. We show that the Canary Islands contain exceptionally high total carbon densities, particularly within the mature, humid laurel forests of La Gomera, and identify structural attributes and water availability as the main drivers of spatial variation in carbon stocks. This assessment provides a baseline for biodiversity conservation, nature-based forest management, ecological restoration and regional climate policy towards carbon neutrality in island ecosystems.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"21 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13452119/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148683109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging meteorological legacy effects and machine learning to improve daily gap-free normalized difference vegetation index reconstruction: a critical basis for fine-scale carbon sink capacity monitoring","authors":"Huiwen Li,&nbsp;Yue Cao,&nbsp;Jingfeng Xiao,&nbsp;Fei Yu,&nbsp;Rui Wang,&nbsp;Xinyi Hao,&nbsp;Zuoqiang Yuan","doi":"10.1186/s13021-026-00487-5","DOIUrl":"10.1186/s13021-026-00487-5","url":null,"abstract":"<div><h3>Background</h3><p>The daily Normalized Difference Vegetation Index (NDVI) is a critical indicator of terrestrial carbon sequestration capacity, essential for accurately quantifying vegetation carbon sink functions and their dynamic responses to climate change. We previously developed a long-term daily NDVI dataset across China, but the over smoothed polynomial fitting method constrained reconstruction accuracy in complex scenarios, hindering precise fine-scale carbon sink monitoring. To address this limitation, we improved the reconstruction framework by integrating meteorological legacy effects and the machine learning algorithm, with a focus on validating its application value for net primary productivity (NPP) estimation.</p><h3>Results</h3><p>The reconstructed daily gap-free NDVI (1982–2023) shows strong consistency with original valid NDVI, achieving a national average <i>R</i>² of 0.9, percentage bias (<i>PB</i>) of − 0.09%, and root mean square error (RMSE) of 0.03. Over 97% of China’s reconstructed NDVI reach high-quality (<i>R</i>² &gt; 0.8, |PB|&lt;1%, RMSE &lt; 0.08), representing a 13.9% <i>R</i>² improvement over our previous dataset. The national daily average NDVI exhibits a continuous increasing trend during the study period, primarily driven by Southwest, Central, Southeast, South, and Northeast China. Attribution analysis indicates that meteorological legacy effects serve as the primary drivers for daily NDVI reconstruction across China. Temperature-related factors including average temperatures over the past 10, 30 and 60 days dominate 68.94% of China, while 60-day cumulative precipitation contributes 12.16%. NPP estimation validation indicates that our daily NDVI-derived NPP shows high agreement with in-situ measurements (<i>R</i>² = 0.82, <i>PB</i> = 5.18%, RMSE = 0.19 kg C m^–2 yr^–1), significantly outperforming coarse-temporal-resolution NDVI-based products (<i>R</i>² &lt; 0.28).</p><h3>Conclusions</h3><p>This study provides a robust long-term daily gap-free NDVI dataset for China, serving as a critical basis for fine-scale terrestrial carbon sink capacity monitoring. Integrating meteorological legacy effects into NDVI reconstruction enhances the accuracy of vegetation dynamic simulation and improves the quantification of terrestrial carbon cycle processes, particularly for fine-scale NPP estimation. Our findings highlight the superiority of high-temporal-resolution NDVI in capturing fine-scale vegetation phenological dynamics, addressing the limitations of conventional coarse-resolution products and supporting more reliable ecological and climate change research.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"21 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13715162/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149284649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved GPP modeling reveals rising precipitation influence in typical grasslands of Northern China’s Hulun Lake Basin","authors":"Tong Sun,&nbsp;Nan Shan,&nbsp;Xuehe Lu,&nbsp;Bingshuai Cao,&nbsp;Wenjing Li,&nbsp;Qian Zhang,&nbsp;Qing Huang,&nbsp;Haidong Zhang,&nbsp;Qianghao Zeng,&nbsp;Suwan Chen","doi":"10.1186/s13021-026-00491-9","DOIUrl":"10.1186/s13021-026-00491-9","url":null,"abstract":"<div><p>The Hulun Lake Basin in northern China harbors extensive temperate grasslands, whose carbon uptake and ecosystem functioning are effectively represented by gross primary productivity (GPP). However, the long-term response of grassland GPP to regional climate change remains insufficiently understood, due to the limited ability of global models to capture local ecosystem variability. This study improved GPP estimation in the Hulun Lake Basin by integrating additional grassland flux observations from China into a Random Forest model (M_CF). We subsequently examined the spatiotemporal dynamics of GPP and identified the dominant climatic drivers and their long-term trends under changing climate conditions. Results show that the M_CF model significantly outperformed the model trained solely on FLUXNET 2015 Tier 2 data in both accuracy and trend patterns of grassland GPP. A 23-year M_CF simulation in the Hulun Lake Basin showed a clear west–east GPP gradient, averaging 676.36 g C m^− 2 yr^− 1 and totaling 70.13 Tg C yr^− 1. Most of the region exhibited increasing GPP trends, with an average growth rate of 6.85 g C m^− 2 yr^− 1, resulting in an annual total increase of approximately 0.45 Tg C yr^− 1. SHAP analysis demonstrated that shifts in precipitation and temperature are reshaping the dominant factors contributing to GPP increases. Structural equation modeling further revealed that precipitation enhanced GPP through both direct and indirect pathways, with the direct effect accounting for 63.6% of the total effect, while the remaining 36.4% was mediated primarily through NIRv. In particular, over large areas of the central-eastern basin, increasing precipitation has gradually replaced shortwave radiation as the primary driver of GPP enhancement. This study provides new insights into how temperate grassland GPP responds to climate change, offering a scientific basis for region-specific ecosystem management and policy decisions.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"21 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13721663/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149293783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does the goal of food security hinder the agricultural green and low-carbon transformation? Evidence from China","authors":"Guoqun Ma,&nbsp;Zhiyu Qin,&nbsp;Lihao Yao,&nbsp;Ziqi Mou","doi":"10.1186/s13021-026-00490-w","DOIUrl":"10.1186/s13021-026-00490-w","url":null,"abstract":"<div><p>Agricultural production is crucial to food security and the realization of carbon reduction targets. Whether green and low-carbon development of agriculture can be achieved on the basis of ensuring food security is a common challenge faced by all economies. This study takes China’s 2004 designation of 13 major grain-producing areas as a quasi-natural experiment. Using provincial panel data from 2000 to 2022, a difference-in-differences model is constructed to explore if the policy can boost green transformation while ensuring yield growth. The findings reveal that the policy significantly reduces carbon emissions and agricultural non-point source pollution, with robustness confirmed by placebo tests, PSM-DID, and double machine learning. Crop structure adjustment and green technological progress have been identified as two key channels for promoting carbon reduction effects, among which labor force transfer plays a non-linear moderating role. Heterogeneity analysis indicates that excessive concentration of grain production is detrimental to the reduction and control of agricultural pollution, while the pollution reduction effect of the policy is more pronounced in regions with moderate to high levels of labor aging. It is recommended to further encourage appropriately scaled operations, promote the application and innovation of green agricultural technologies, and tailor strategies to local conditions to achieve agricultural green transformation, while continuing to uphold the major grain-producing areas policy.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"21 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13721644/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149293771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EU carbon pricing and clean energy markets: evidence from cross-quantilogram and multivariate time-varying quantile regression","authors":"Godwin Olasehinde-Williams,&nbsp;Seyi Saint Akadiri","doi":"10.1186/s13021-026-00492-8","DOIUrl":"10.1186/s13021-026-00492-8","url":null,"abstract":"<div><p>Understanding how regionally determined carbon-pricing signals are transmitted into globally traded clean energy equities is increasingly important as climate policy and financial markets become more integrated. Yet, evidence remains limited on whether these linkages are nonlinear, state-dependent, and heterogeneous across clean energy technologies. This study examines how movements in European Union Emissions Trading System (EU-ETS) futures, a regional carbon market and policy-linked price signal, are reflected in the returns of ten globally listed clean energy subsectors using daily data from 19 October 2010 to 6 July 2024. Using disaggregated NASDAQ OMX Clean Energy subsector indices, the analysis captures how carbon-pricing information originating in the EU is incorporated into globally integrated equity markets. The study combines the Cross-Quantilogram (CQ) and Multivariate Time-Varying Quantile Regression (MTVQR) frameworks to examine directional predictability and conditional impacts, while controlling for financial uncertainty (VIX) and oil-market conditions (Brent crude oil prices). The CQ results show that EU-ETS futures contain significant predictive information for clean energy returns, with nonlinear, asymmetric dependence concentrated on the tails of the distribution. The MTVQR results further show that the conditional impact of carbon-pricing signals varies across market states and technologies. More mature subsectors, such as solar, wind, and smart grid, respond more strongly in weak and normal markets, while capital-intensive and enabling technologies, including biofuels, geothermal, storage, and fuel cells, exhibit stronger upper-tail or nonlinear responses. The findings highlight EU carbon pricing as a forward-looking transition-risk signal with implications for climate policy, portfolio allocation, and transition-risk management.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"21 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13715261/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149284584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}