Enhanced urban CO2 monitoring and understanding its spatiotemporal patterns and driving factors are essential for emission management and climate change mitigation. This study developed a high-resolution framework for predicting and mapping CO2 concentrations within the road network of Shenzhen by integrating vehicle-cruising observations, street-view panoramas, and multisource remote sensing data. The proposed machine learning model demonstrated strong predictive performance (R² = 0.92). Furthermore, the effects of urban function, urban development intensity, traffic conditions, and environmental factors on CO2 concentrations were systematically examined using explainable machine learning techniques. The results indicate that in urban centres, human activities exert a substantial influence on CO2 levels. Effective non-motorway planning, accessible public transport systems, and diversified urban functions are associated with lower CO2 concentrations. Notably, areas with high vegetation cover were also found to exhibit elevated CO2 concentrations, and the influence of greenery on Shenzhen's CO2 levels was positive in November. By integrating multisource data from the perspectives of the urban landscape and street configuration, this study provides an interpretable approach for analysing the complex drivers of urban CO2 dynamics. Overall, the findings establish a cost-effective methodological framework for refined urban carbon monitoring and offer actionable insights to support low-carbon urban planning and evidence-based policy formulation.

Soil organic carbon (SOC) plays an essential role in carbon sequestration and climate change mitigation in forest ecosystems. While experimental studies have shown that plant diversity usually increases SOC, it remains unclear whether this positive relationship holds in natural ecosystems across varying climatic conditions. Using a global dataset of 15 large and long-term monitored natural forest sites spanning a wide latitudinal range, we assess the relationship between tree diversity and SOC within and across sites in temperate, subtropical, and tropical regions. We found an overall positive relationship between tree taxonomic diversity and SOC. The relationships between tree taxonomic or functional diversity and SOC became stronger under colder and more arid conditions. Additionally, tree functional composition was linked to SOC only within a subset of sites in more arid climates. These findings suggest that warmer and more humid conditions increase decomposition, offsetting diversity-driven carbon inputs, while colder and more arid conditions enhance SOC through low decomposition and increased inputs through abiotic facilitation and biotic interactions in high-diversity communities. Our findings indicate that conserving plant diversity is critical for enhancing carbon sequestration and mitigating the effects of climatic conditions, particularly in cold climates and regions facing an increase in arid conditions.

An optimization framework for integrating electric vehicles and carbon capture: Bridging cost gaps via electric vehicles deployment

Crop residues, particularly straw, are abundant sources of agricultural feedstock for energy conversion when removed from the field but also a crucial agroecological resource that should be kept in the field to improve soil quality. Reaching a trade-off is therefore necessary. How can soil fertility be reconciled with the production of renewable energy from straw and other biomass? A life-cycle approach is required in order to take a comprehensive view of the entire bioenergy system. A unique, deterministic equation was developed to calculate the optimal radius of the biomass supply area for a bioenergy plant, with the aim of maximizing greenhouse gas savings and achieving the most effective climate mitigation. This equation considers every component of the bioenergy system, from upstream field conditions to downstream energy plant operations aimed at power generation and possibly heat recovery. First, a general overview of the model and its mathematical properties was provided. Then, the equation was used to evaluate the GHG emissions associated with three different wheat cropping systems and straw management conditions in southern Italy. A sensitivity analysis of the equation parameters was also conducted. Although this work is built upon previously published studies, it significantly expands their scope of application. It was found that neglecting the GHG emission debt resulting from the long-term soil dynamic conditions caused by systematic straw removal could significantly affect the supply radius of a bioenergy plant and the climate mitigation capacity of the entire bioenergy project. A case study of an actual biomass plant designed to maximize economic profits revealed that it was oversized, in other words, not in line with the size required to deliver the greatest climate benefits, which tend to be smaller. Conversely, careful calculations and conservative estimates of soil GHG emission burdens must be made on a case-by-case basis in order to develop well-designed, fine-tuned bioenergy projects. These calculations must take into account the specific pedoclimatic conditions and cropping management practices actually being applied in the area, as well as the emission factor of the current electricity generation mix achieved by the national or European electricity sector, which should be used as a benchmark. This work demonstrates that emissions resulting from straw removal can significantly impact the GHG balance, potentially invalidating the climate mitigation objective of a bioenergy project. • Straw is an abundant energy feedstock, but also a crucial agroecological resource for soil quality. • European regulations assume that there are no emissions costs when straw is used for energy. • A deterministic equation was developed to calculate the optimal radius of the biomass supply area maximizing GHG savings. • The soil emission debt due to straw removal can invalidate the climate mitigation objective of a bioenergy project. • The soil emissions debt must be calculated taking specific pedoclimatic conditions and cropping management into account.

Conversion of unused sludge to biofuel for climate change mitigation: Unlocking resource recovery and circular economy opportunities in waste sector for low-carbon urban system

The fate of macroalgal carbon under microbial anaerobic respiration: A critical factor in macroalgae cultivation for climate change mitigation.

Effects of nutrient enrichment on microbial accumulation of RDOC: A microcosm experiment using long-term incubated inert waters.

Fair effort-sharing for climate change mitigation: A normative approach

Dynamic features and mechanisms of soil aggregate stability related to soil carbon pools and microbially mediated functions under N input: Advances, issues, and future perspectives.

ABSTRACT Fossil fuel reliant countries contribute disproportionately to climate change, yet little is known about how nations’ fossil fuel reliance relates to public support for climate change mitigation. A large cross-national study (N = 101,956) across 105 countries and six continents showed that citizens of nations with greater fossil fuel reliance were less likely to believe that climate change should be a priority for their government, more supportive of continued fossil fuel use, and less supportive of increased renewable energy use. These associations remained significant after controlling for a wide set of country-level indicators, including fossil fuel consumption, economic development, democratic governance, corruption, and climate vulnerability, as well as demographic characteristics. Overall, these findings show that fossil fuel reliance is linked to reduced support for climate change mitigation. They also point to the need for a transition that acknowledges citizens’ concerns about phasing out fossil fuels in fossil fuel reliant societies.

ABSTRACT Protected areas (PAs) provide critical ecosystem services, including global climate regulation through the retention of carbon in biomass and soil. Evaluating the impact of terrestrial PAs on carbon storage is essential for strengthening their role in mitigating climate change, especially in the face of significant Land Use and Land Cover (LULC) changes, which can influence carbon dynamics. This study focuses on Ifrane National Park (INP) in Morocco, where the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was used to simulate carbon stock changes between 2018 and 2033, with a particular emphasis on Strict PAs. The results reveal a total carbon stock decline of 14.28% within INP over the study period. Forested areas, especially Holm oak forests, showed notable resilience, with their carbon stocks increasing by 20.79% inside Strict PAs and by 46.63% outside these zones. In contrast, cedar forests experienced a decline of 5.24% within Strict PAs and 17.56% outside. This highlights the significant role of Strict PAs in mitigating carbon losses, especially in vulnerable ecosystems like cedar forests. Our study underscores the need to expand Strict PAs and adopt sustainable forest management to enhance carbon sequestration and support climate change mitigation.

Variations in land-use types and management intensity significantly alter soil physical-chemical properties and dictate carbon dioxide (CO2) emissions fluxes. This study aimed to model the control of soil physical-chemical characteristics on soil CO2 emission rates across various tropical mineral land-use types in Seginim District, South Bengkulu Regency. Utilizing an observational edaphic dataset across six dominant land-use types (corn, oil palm, natural forest, vegetables, coffee, and rubber) with three replications (N=18), advanced statistical modeling via Pearson correlation and multiple linear regression was performed. Soil CO2 emissions were measured in-situ using the modified closed-chamber method followed by alkali absorption titration, while edaphic variables (soil moisture, temperature, bulk density, and pH) were evaluated using standard laboratory procedures. Data were analyzed using Pearson correlation and multiple linear regression. The results revealed that intensive land-use types, namely corn (51.65 ± 2.31 kg/ha/day) and vegetables (43.80 ± 2.75 kg/ha/day), doubled CO2 emissions compared to natural forest (21.87 ± 1.36 kg/ha/day). Soil moisture and bulk density acted as the master variables controlling the emissions. Soil moisture alone showed a strong negative correlation, explaining 83.72% of the emission variance (r = -0.91; p < 0.01). Integrating all edaphic components into a multivariate regression model significantly increased the predictive power to 97.22% (R2 = 0.9722; p < 0.001), driven by the severe physical inhibition effect of bulk density (β = -30.83; p < 0.001). Conversely, soil temperature and pH exerted no significant partial effects due to microclimatic buffering. This study concludes that soil physical properties rigidly govern CO2 emissions across different tropical mineral land uses. Consequently, climate change mitigation strategies must prioritize protecting soil physical structures through water management and compaction prevention rather than chemical manipulation.

Forest ecosystems play an important role in climate change mitigation through carbon storage in biomass and soils. However, information on species-specific carbon sequestration in Mediterranean forests is still limited. This study evaluated biomass accumulation and carbon sequestration capacity of three native Mediterranean tree species (Quercus coccifera, Pinus halepensis, and Ceratonia siliqua) across different developmental stages, including young seedlings (1–3 years) and mature stands (20–80 years), in northern Jordan. Young seedlings were assessed using destructive biomass sampling, while mature stands were evaluated using species-specific allometric equations based on diameter measurements and soil carbon analyses. In addition, seedling and mature-tree evaluations were conducted under different environmental conditions. Carbon concentration varied significantly among plant organs, with generally higher values in leaves than in stems and roots. During early growth stages, young seedlings of C. siliqua exhibited greater annual carbon sequestration (0.55 kg tree−1year−1) than Q.coccifera and P.halepensis (0.1–0.2 kg tree−1 year−1). In mature stands, P.halepensis showed the greatest aboveground carbon storage, reaching approximately 588 kg C tree−1. Soil organic carbon stocks across the 0–60 cm soil profile varied among species, ranging from 17.9 kg m−2 under Q.coccifera to 24.1 kg m−2 under C.siliqua. Annual carbon sequestration rates derived from short-term field observations and allometric biomass estimations (including both above- and belowground components) differed markedly among species. P.halepensis showed the highest sequestration rate (>65 kg tree−1 yr−1), followed by Q.coccifera (∼23–24 kg tree−1 yr−1), whereas C.siliqua exhibited substantially lower rates (<5 kg tree−1 yr−1). These findings suggest that carbon sequestration capacity in Mediterranean forests varies with species, growth stage, and environmental conditions. This variability highlights the need to consider both species selection and site characteristics when designing restoration and afforestation programs aimed at maximizing long-term carbon storage and climate change mitigation in dryland ecosystems.

Pro-environmental behavior in climate change mitigation: The role of psychological distance.

ABSTRACT Tropical forests are central to global sustainability, underpinning biodiversity conservation, climate change mitigation, and disaster risk reduction. Yet, it remains unclear whether recent efforts have reduced tropical forest loss (TFL) and improved protection of ecologically and socially important areas. This study provides a global, spatially explicit assessment of TFL before (2011–2015) and after (2016–2022) the mid-2010s, a period coinciding with major global sustainability, climate, and biodiversity commitments. It examines how TFL relates to climate change mitigation, biodiversity conservation, and disaster (landslide) risk reduction using an integrated ecosystem co-benefit index, as well as to tropical terrestrial protected areas (PAs). Although annual TFL exhibited a statistically significant downward trend during 2016–2022, average annual TFL was 34% higher than in 2011–2015, increasing from 11.69 ± 2.13 to 15.69 ± 2.45 Mha/year, with significant increases in tropical South America and Africa. Across both periods, higher TFL consistently occurred in areas with moderate ecosystem co-benefits. Despite an 8% expansion of PAs and their greater representation in high co-benefit areas, the average annual TFL within PAs increased by 71%, from 1.12 ± 0.19 to 1.92 ± 0.41 Mha/year, while the average annual share of TFL within PAs rose from 9.6 ± 0.5% to 12.2 ± 0.9%. These findings indicate that recent slowdowns in TFL are modest and insufficient to offset persistent pressures. This underscores the need to strengthen sustainable forest management by addressing the broader socio-economic and institutional conditions that drive and perpetuate TFL.

Wetland Type Matters: Tree Community Structure and Carbon Sequestration Dynamics Along a Tropical River Basin.

ABSTRACT Urban forests are critical nature-based solutions for climate change mitigation, yet accurately quantifying their carbon sequestration potential at fine scales remains a major challenge. In this study, an integrated framework for individual-tree-level species classification and carbon stock estimation in urban forests is proposed, leveraging UAV-based LiDAR and hyperspectral data fusion. To address the challenges of high feature dimensionality and class imbalance, an enhanced feature selection strategy termed adaptive cross-validation with dynamic correlation constraints (ACV-DCC) was introduced. A total of 14,376 individual trees were automatically segmented using a seed-growing algorithm across three types of urban green spaces on the Yuzhong Campus of Lanzhou University. The ACV-DCC method significantly improved classification performance, increasing the accuracy for 18 tree species to 85.67%. Among the tested classifiers, the RF outperformed the SVM and XGBoost algorithms in terms of the accuracy (85%–86%) and robustness. Its nonlinear modeling capacity also enabled accurate prediction of tree structural attributes, supporting a carbon stock estimation of approximately 1.85 × 106 kg on campus. The results demonstrate the scalability and effectiveness of the proposed framework in small- to medium-scale heterogeneous urban green environments. This reproducible and scalable workflow provides a high-precision technical pathway that can be adapted to heterogeneous urban environments worldwide, thereby contributing to global urban carbon monitoring efforts and sustainable ecosystem planning.

In this work, we analyze storylines about forest functions alongside growing media attention regarding climate change. Using an in-depth content analysis of Austrian print media (2002–2022), we identify storylines and apply a correspondence analysis to explore interlinkages between actors and storylines. We identified six storylines reflecting three thematic divergences: (i) “Climate change is not a problem” versus (ii) “We need climate-resilient forests”; “Climate change mitigation through wood utilization” constituted by (iii) “Direct use” versus (iv) “Cascading use”; and (v) “Only a managed forest is a healthy forest” versus (vi) “Hands-off Forestry”. Actors in the forest-based sector frequently iterate storylines that communicate climate change, along with mitigation, sequestration, or adaptation strategies, to advance their own operations and strategically communicate (mostly EU-level) policies they perceive as unfavorable. Nuanced communication of complex forest management storylines is needed to highlight synergies and bridge polarized debates about forest functions.

ABSTRACT As artificial intelligence-generated (AI-generated) journalism rises, its effectiveness in engaging the public to mitigate climate change remains uncertain. This study integrates the MAIN model and expectation-confirmation theory to examine how AI-generated versus human-generated climate change news influences audience news evaluation and behavioral intentions. We conducted a 2 (human-generated news vs. AI-generated news) × 2 (authorship disclosed vs. authorship undisclosed) × 2 (narrative vs. non-narrative) between factorial experiment (N = 441) to test the effects of news source, authorship disclosure, and narrative style on readers’ perceived news credibility, readability, and behavioral intentions for climate change mitigation. The t-tests revealed that human-generated climate change news elicited positive disconfirmation, while AI-generated news resulted in negative disconfirmation. A three-way MANCOVA revealed that narrative news significantly promoted climate change mitigation intentions. Further moderation analyses indicated that while AI-generated news did not differ significantly from human-generated news in terms of persuasiveness, improving the algorithmic narrative structure of AI-generated content could enhance positive disconfirmation of readability, thereby increasing the likelihood of engagement in mitigation behaviors. These findings provide insights into optimizing AI-generated journalism to enhance climate change communication and public engagement.

Work is a social determinant of Cardiovascular (CV) and general health and can both influence and be influenced by health. The type of work, working conditions, and work environment are fundamental social determinants of CV and general health status. Climate change presents an urgent and increasing threat to workers' health, via both direct exposure to environmental risks and the indirect worsening of social and health inequalities. Occupational health, which focuses on the promotion of mental and physical health and well-being of workers, and the avoidance of occupationrelated health risks, is a crucial but less discussed concern and component of human health. Relevant research at the intersection of climate change and occupational health remains scarce. Additionally, mitigation of climate change and adaptation efforts are driving forces for rapid transformations in the workplace, including shifts towards sustainability and circular economy models. These transitions are creating new occupational hazards, including those concerning renewable energy and the circular economy sectors. Investment in occupational health research and surveillance should be increased to address the evolving influences of both climate change and the green transition, to enhance and protect workers' CV and general health. Among the work-related factors that play an important role in patients with CVD, the following seem crucial: work participation, physical and mental work capability, appropriate work, support from and flexibility of the work environment, inter-personal communication, person-centered milieu, and interdisciplinary communication. A moderate leisure-time physical activity combined with moderate occupational physical activity may be a more plausible way to combine these two activities to sustain and/or improve CV health. Such an approach may be able to ameliorate workrelated outcomes in patients with CVD. Finally, lifestyle interventions targeting multiple behaviors are also most important to prevent CVD and attain cardiometabolic health. All these issues of occupational CVD are herein reviewed, and relevant meta-analyses are tabulated and discussed.