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Background: Global climate change is one of the major challenges facing the world today, and forests play a crucial role as significant carbon sinks and providers of ecosystem services in mitigating climate change and protecting the environment. China, as one of the largest developing countries globally, owns 60% of its forest resources collectively. Evaluating the carbon sequestration cost of collective forests not only helps assess the contribution of China's forest resources to global climate change mitigation but also provides important evidence for formulating relevant policies and measures. Results: Over the past 30 years, the carbon sequestration cost of collective forests in China has shown an overall upward trend. Except for coastal provinces, southern collective forest areas, as well as some southwestern and northeastern regions, have the advantage of lower carbon sequestration costs. Furthermore, LSTM network predictions indicate that the carbon sequestration cost of collective forests in China will continue to rise. By 2030, the average carbon sequestration cost of collective forests is projected to reach 125 CNY per ton(= 16.06 Euros/t). Additionally, there is spatial correlation in the carbon sequestration cost of collective forests. Timber production, labor costs, and labor prices have negative spatial spillover effects on carbon sequestration costs, while land opportunity costs, forest accumulation, and rural resident consumption have positive spatial spillover effects. Conclusion: The results of this study indicate regional disparities in the spatial distribution of carbon sequestration costs of collective forests, with an undeniable upward trend in future cost growth. It is essential to focus on areas with lower carbon sequestration costs and formulate targeted carbon sink economic policies and management measures to maximize the carbon sequestration potential of collective forests and promote the sustainable development of forestry. [ABSTRACT FROM AUTHOR]

Mangrove ecosystems are becoming increasingly important in global climate mitigation. However, large gaps still exist in evaluating mangroves' gross primary productivity (GPP) due to reasons such as the specific influences, for example, temperature and salt stresses are poorly described in Earth System Models (ESMs). This study developed a process‐based biogeochemical model (Mango‐GPP) to improve the GPP simulation in natural and restored mangroves. The model integrates mangrove‐specific physiological processes, including the response to salt and temperature stresses, as well as the light‐use efficiency at different growing stages. Eddy covariance flux measurements at two natural sites and one restored site in China were used to calibrate and validate Mango‐GPP. The model was calibrated by inverse analysis approach based on two cases and independently validated against the other cases. The validation results showed that it was generally capable of simulating the seasonal and interannual GPP variations at different sites. The simulated daily and annual GPPs agreed well with the observations and yielded R2 of 0.67 and 0.96, with model efficiency of 0.64 and 0.93, respectively. In comparison, Mango‐GPP showed better performances than many current satellite‐based GPP products and ESMs. The model was more sensitive to solar radiation, carbon dioxide concentration, and leaf traits. Future improvements should focus on enhancing Mango‐GPP's descriptive power of key processes, and further simulating other carbon fluxes at regional scales. This work provides a model foundation for further simulating carbon exchanges between the atmosphere, mangrove, and ocean for studying the coastal wetland restoration on regional carbon neutrality. Plain Language Summary: Mangroves are becoming increasingly important for climate mitigation, but are greatly under‐represented in current ecosystem models. This study developed a new process‐based model (Mango‐GPP) to specifically estimate carbon taken up by mangrove ecosystems. The model requires few and easily accessible inputs, and showed good performance in both natural and restored mangroves. This work sets the stage for future studies on impacts of mangrove changes (e.g., restoration and reestablishment etc.) on carbon sequestration and climate mitigation. Key Points: We developed a process‐based model simulating daily gross primary productivity (GPP) for mangrovesThe model incorporates the effects of salinity and temperature, as well as light absorption and use efficiency on mangroves' GPPThe model requires only 13 easily accessible inputs and is validated well at both natural and restored mangroves in China [ABSTRACT FROM AUTHOR]

Carbon‐focused climate mitigation strategies are becoming increasingly important in forests. However, with ongoing biodiversity declines we require better knowledge of how much such strategies account for biodiversity. We particularly lack information across multiple trophic levels and on established forests, where the interplay between carbon stocks, stand age, and tree diversity might influence carbon–biodiversity relationships. Using a large dataset (>4600 heterotrophic species of 23 taxonomic groups) from secondary, subtropical forests, we tested how multitrophic diversity and diversity within trophic groups relate to aboveground, belowground, and total carbon stocks at different levels of tree species richness and stand age. Our study revealed that aboveground carbon, the key component of climate‐based management, was largely unrelated to multitrophic diversity. By contrast, total carbon stocks—that is, including belowground carbon—emerged as a significant predictor of multitrophic diversity. Relationships were nonlinear and strongest for lower trophic levels, but nonsignificant for higher trophic level diversity. Tree species richness and stand age moderated these relationships, suggesting long‐term regeneration of forests may be particularly effective in reconciling carbon and biodiversity targets. Our findings highlight that biodiversity benefits of climate‐oriented management need to be evaluated carefully, and only maximizing aboveground carbon may fail to account for biodiversity conservation requirements. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystems play a critical role in the global carbon cycle and climate change mitigation. Studying the temporal and spatial dynamics of carbon sink and the driving mechanisms at the regional scale provides an important basis for ecological restoration and ecosystem management. Taking the Dongting Lake Basin as an example, we assessed the carbon sinks of forest and shrub from 2000 to 2020 based on the maps of biomass that were obtained by remote sensing, and analyzed the dynamics of carbon sinks that were contributed by different biomass carbon density levels of constant forest and shrub and new afforestation over the past two decades. The results showed that the carbon sink of forest and shrub in the Dongting Lake Basin grew rapidly from 2000 to 2020: carbon sink increased from 64.64 TgC between 2000 and 2010, to 382.56 TgC between 2010 and 2020. The continuous improvement of biomass carbon density has made a major contribution to carbon sink, especially the carbon density increase in low carbon density forests and shrubs. Carbon-dense forests and shrubs realized their contribution to carbon sink in the second decade after displaying negative carbon sink in the first decade. Carbon sink from new afforestation increased 61.16% from the first decade to the second decade, but the contribution proportion decreased. The overall low carbon density of forest and shrub in the Dongting Lake Basin and their carbon sink dynamics indicated their huge carbon sequestration potential in the future. In addition to continuously implementing forest protection and restoration projects to promote afforestation, the improvement of ecosystem quality should be paid more attention in ecosystem management for areas like Dongting Lake Basin, where ecosystems, though severely degraded, are important and fragile, to realize their huge carbon sequestration potential. [ABSTRACT FROM AUTHOR]

Carbon neutrality strategies have a significant role in climate mitigation efforts. As global concerns regarding climate change continue to increase, achieving carbon neutrality has emerged as a paramount objective for reducing greenhouse gas emissions and limiting the adverse impacts of anthropogenic activities on the environment. This research investigates a wide range of scholarly works to conduct an in-depth analysis and synthesis of the relevant information about carbon neutrality strategies. The review introduces carbon neutrality principles and terminologies, highlighting their importance in climate mitigation. It then proceeds to explore the wide range of strategies employed across different sectors and industries, investigating their effectiveness, scalability, and potential challenges. A multidimensional analysis contrasts the United States Nationally Determined Contributions pathway 2023, China's Nationally Determined contributions 2023, and the EU Directive 2023/2413, assessing their economic, environmental, political, and social impacts. The study evaluates strategies' effectiveness, scalability, and innovation for transitioning to a sustainable, low-carbon future. It fills a gap by analyzing global approaches across the US, China, and the EU, which account for about 50% of the world's total GHG emissions. It evaluates the novel application of diverse strategies, from renewable energy transitions to innovative policy measures, highlighting their potential to mitigate climate change effectively. By providing a multidimensional analysis of these strategies' impacts, the research not only enhances understanding of effective carbon neutrality tactics but also underscores the importance of international cooperation in realizing a sustainable, low-carbon future. • Identifies and analyzes carbon neutrality strategies, emphasizing the need for diverse US, Chinese, and EU approaches. • Evaluate renewable energy, carbon capture, and policy tools for carbon reduction effectiveness, scalability, and innovation. • Highlights the study's novelty in synthesizing current knowledge on carbon neutrality, addressing a significant research gap. • Concludes with strategic ideas for international collaboration and policy development for low-carbon futures. [ABSTRACT FROM AUTHOR]

• The 57.00% of the Yangtze River Economic Belt area exhibited a significant increase in annual NPP. • The response of NPP on climate factors was nonlinear, with greater sensitivity to temperature. • The impact of topographic factors on NPP changes had a threshold effect. Net primary productivity (NPP) of terrestrial ecosystems serves as a crucial carbon sink, playing a significant role in mitigating climate change. This study, focusing on the Yangtze River Economic Belt (YREB), a key area for both economic development and ecological conservation in China, evaluates the temporal and spatial changes in regional NPP and its responses to climatic factors against the backdrop of global change. Utilizing long-term NPP and meteorological grid data from 1981 to 2017, we analyzed the annual change patterns of NPP and its linear and nonlinear responses to climatic factors using copula functions. Our findings indicate that 57.00 % of the YREB has experienced a significant increase in NPP, with the most substantial decreases observed in Shanghai and its surrounding areas (P < 0.05). Temperature emerged as the primary climatic driver, positively correlating with NPP changes in over half of the study area (P < 0.05). Moreover, the nonlinear response of NPP to temperature and precipitation underscores the complex interactions between these factors, revealing a sensitivity to temperature variations that surpasses that to precipitation. The study also highlights the influence of solar radiation and topographic factors, with a significant positive correlation between NPP and solar radiation observed in 15.85 % of the area (P < 0.05). The practical significance of these findings lies in their implications for regional ecological management and climate resilience strategies. The positive correlation between temperature and NPP underscores the potential for targeted temperature management to optimize carbon sequestration across the YREB. Furthermore, the identified nonlinear responses and the role of solar radiation and topography in influencing NPP offer valuable insights for the formulation of adaptive strategies that enhance ecosystem productivity and contribute to achieving carbon neutrality goals. By elucidating the dynamics of NPP in response to a range of environmental factors, this study provides a foundation for informed decision-making in ecological conservation and climate change mitigation efforts within the YREB and similar regions globally. [ABSTRACT FROM AUTHOR]

Despite the progress made in understanding relevant carbon dynamics under grazing exclusion, previous studies have underestimated the role of soil bulk density (BD), and its implications for potential accumulation of soil organic carbon (SOC), especially at regional scale over long term. In this study, we first constructed a database covering a vast majority of the grasslands in northwestern China based on 131 published literatures. A synthesis was then conducted by analyzing the experimental data to comprehensively investigate the mechanisms of vegetation recovery, carbon-nitrogen coupling, and the importance of changed soil BD in evaluating SOC sequestration potential. The results showed that although the recovery of vegetation height and cover were both critical for improving vegetation biomass, vegetation height required a longer recovery period. While the SOC accumulation was found to be greater in surface layers than deeper ones, it exhibited a reduced capacity for carbon sequestration and an increased risk of SOC loss. Grazing exclusion significantly reduced soil BD across different soil profiles, with the rate of change influenced by soil depth, time, geographical and climatic conditions. The potential for SOC accumulation in the top 30 cm of soil based on data of 2003–2022 was 0.78 Mg ha−1 yr−1 without considering BD effects, which was significantly underestimated compared to that of 1.16 Mg ha−1 yr−1 when BD changes were considered properly. This suggests that the efficiency of grazing exclusion in carbon sequestration and climate mitigation may have been previously underreported. Furthermore, mean annual precipitation represented the most relevant environmental factor that positively correlated to SOC accumulation, and a wetter climate may offer greater potential for carbon accumulation. Overall, this study implies grazing exclusion may play an even more critical role in carbon sequestration and climate change mitigation over long-term than previously recognized, which provides essential scientific evidence for implementing stepwise ecological restoration in grasslands. • Grazing exclusion causes significant changes in vegetation, carbon, nitrogen and bulk density. • The changes of carbon, nitrogen and bulk density depend on soil depth, time, and environment. • SOC accumulation has been underestimated by nearly 30% in previous studies. [ABSTRACT FROM AUTHOR]

Knowledge on relationship and determinants of water and carbon dioxide (CO 2) exchange is crucial to land managers and policy makers especially for the desertified land restoration. However, there remains highly uncertain in terms of water use and carbon sequestration for artificial plantation in desert. Here, continuous water and carbon fluxes were measured using eddy covariance (EC) in conjunction with hydrometeorological measurements over an artificial C4 shrub, Haloxylon ammodendron (C. A. Mey.) Bunge, from July 2020 to 2021 in Tengger Desert, China. Throughout 2021, evapotranspiration (ET) was 189.5 mm, of which 85% (150 mm) occurred during growing season, that was comparable with the summation of precipitation (132.2 mm), dew (33.5 mm) and potential other sources (e.g. deep subsoil water). This ecosystem was a strong carbon sink with net ecosystem production (NEP) up to 446.4 g C m−2 yr−1, much higher than surrounding sites. Gross primary production (GPP, 598.7 g C m−2 yr−1) in this shrubland was comparable with that of other shrublands, whereas ecosystem respiration (Re, 152.3 g C m−2 yr−1) was lower. Random Forest showed that environmental factors can explain 71.56% and 80.07% variation of GPP and ET, respectively. Interestingly, environmental factors have divergent effect on water and carbon exchange, i.e., soil hydrothermic factors (soil moisture content and soil temperature) determine the magnitude and seasonal pattern of ET and Re, while aerodynamics factors (net radiation, atmospheric temperature and wind speed) determine GPP and NEP. As such, divergent response of abiotic factors resulted in the decoupling of water and carbon exchange. Our results suggest that H. ammodendron is a suitable species for large-scale afforestation in dryland given its low water use but high carbon sequestration. Therefore, we infer that artificial planting H. ammodendron in dryland could provide an opportunity for climate change mitigation, and the long-term time series data is needed to confirm its sustainable role of carbon sequestration in the future. • Water and carbon exchange over an artificial C4 shrub in desert were determined. • Evapotranspiration (ET) was comparable with precipitation plus dew. • Positive and high net ecosystem production (NEP) suggest the strong carbon sink for it. • Gross primary production (GPP) was comparable with other shrubs but ecosystem respiration lower. • Abiotic factors have divergent effects on water (ET) and carbon fluxes (NEP and GPP). [ABSTRACT FROM AUTHOR]

Coastal salt marshes suffering from anthropogenic coastal development and sea level rise have attracted much attention because of their capacity for carbon sequestration and global climate change mitigation. Accurate mapping of coastal salt marshes is always the first step for their protection, management, and restoration. The inherent complexities of vegetation, dynamics of tides, and anthropogenic disturbances pose challenges for remote sensing-based approaches. Existing studies have utilized phenology information and various black-box algorithms to reduce misclassifications. However, the approaches with dual-temporal images containing phenology information have suffered from inefficiency; the misclassifications have been objectively post-processed rather than considered in the method design, and the tacit knowledge of the trained black-box models has not been revealed. To address the above issues, we proposed a new approach with solid improvements in dual-temporal image construction, misclassification processing, and tacit knowledge analysis, including an efficient method to synthesize dual-temporal images based on the common divisor of the green-up season or senescence season resulting from latitudinal gradients in narrow coastal areas of China, a detailed classification scheme by interpretation of iteratively collected samples, and a key decision rule approximating the trained model. We applied the approach to Sentinel-1/2 images and DEM data, thus deriving a 10-m resolution coastal salt marsh map of China with an overall accuracy of 92.5%. A qualitative comparison showed that the map produced in this study was fitted well with actual salt marsh distributions, resulting in improved accuracy when compared to recently generated maps. The most important contribution is that the overall nature of the trained model observed from the training samples was approximated by a four-feature decision rule following the principle of explainable artificial intelligence, i.e., B8 senescence /B4 senescence < 2.06 & B4 green /B8 green < 0.78 & B12 green /B11 green < 0.72 & elevation < 2.13 , and thus established a new potential classification mechanism for dual-temporal black-box algorithms, i.e., the water signal was covered up by flourishing vegetation, but the situation changed when vegetation withered. This study not only generates an accurate coastal salt marsh map at a national scale but also provides a classification mechanism for dual-temporal image-based coastal salt marsh identification and mapping. • Developed an efficient method for constructing senescence and green images. • Established a mechanism for dual-temporal image-based coastal salt marsh mapping. • Provided a coastal salt marsh map with solid improvements on the most recent one. • Explored a case of explainable artificial intelligence (XAI) in the coastal. [ABSTRACT FROM AUTHOR]

Rational allocation of carbon quotas is the fundamental premise for the orderly operation of carbon markets. To achieve the set target of carbon peak by 2030, there is an urgent need to establish China's 2030 provincial carbon quota allocation scheme. Although some proposed schemes have been formulated, there are problems with the methods used for carbon emission forecasting and evaluating the rationality of a proposed allocation scheme. This study aimed to optimize carbon emission forecast by incorporating terrestrial carbon sinks into the mechanism for building China's 2030 provincial carbon emission quota allocation schemes. Aquila Optimizer's Double Support Vector Regression (AO-based TWSVR) that has the advantages in solving problems associated with small sample size, nonlinear and high-dimensional pattern recognition with fast training speed and insensitivity to noise was adopted to predict the net carbon emission. The results show that the application of AO-based TWSVR model allows satisfactory forecast of the net carbon emission in China for the period from 2021 to 2035. This allowed terrestrial carbon sequestration being incorporated into the mechanism to formulate China's 2030 provincial carbon quota allocation schemes. Comparison of the three provincial carbon quota allocation schemes using social network analysis suggests that the equity-based carbon quota allocation scheme is more suitable for China's national conditions compared to the efficiency-based scheme and the combined principle-based scheme. The findings obtained from this study have implications for optimizing the scheme of China's 2030 provincial carbon quota allocation. [Display omitted] • AO-based TWSVR model was used to optimize carbon emission forecasting in China. • This allows satisfactory forecast of the net carbon emission from 2021 to 2035. • Three schemes were formulated for China's 2030 provincial carbon quota allocation. • Social network analysis was used to evaluate the rationality of these schemes. • The equity-based scheme is more suitable for China's national conditions. [ABSTRACT FROM AUTHOR]

Carbon capture, utilization, and storage (CCUS) is a crucial technology for global climate mitigation. To implement large-scale CCUS, decisions about where and how to build a CO 2 transportation network are urgently required. However, previous studies are limited in proposing the economical transportation network for CCUS that considered comprehensive risks from socio-economic, geographical and geological factors. Here, we develop a pipeline layout planning model to investigate the cost-effective and reliable transportation network for CCUS. Results show that to meet the annual CO 2 emission reduction target of 654 million tons for CCUS in the coal-fired power sector under China's carbon neutral goal, pipelines with a total length of 17,589 km need to be constructed. The emission sources can be transported in pipelines with an average radius of 58 km, and with diameters of 8, 12, and 16 inches. Northeast, north, and northwest China are the main areas suitable for pipeline construction. • Northeast, North, and Northwest in China are vital areas for capture, transport, and storage. • Five large-scale pipeline network groups can be constructed in China. • Pipeline construction is greatly affected by a variety of practical factors. [ABSTRACT FROM AUTHOR]

Carbon capture, utilization, and storage (CCUS) is a crucial technology for global climate mitigation. To implement large-scale CCUS, decisions about where and how to build a CO 2 transportation network are urgently required. However, previous studies are limited in proposing the economical transportation network for CCUS that considered comprehensive risks from socio-economic, geographical and geological factors. Here, we develop a pipeline layout planning model to investigate the cost-effective and reliable transportation network for CCUS. Results show that to meet the annual CO 2 emission reduction target of 654 million tons for CCUS in the coal-fired power sector under China's carbon neutral goal, pipelines with a total length of 17,589 km need to be constructed. The emission sources can be transported in pipelines with an average radius of 58 km, and with diameters of 8, 12, and 16 inches. Northeast, north, and northwest China are the main areas suitable for pipeline construction. • Northeast, North, and Northwest in China are vital areas for capture, transport, and storage. • Five large-scale pipeline network groups can be constructed in China. • Pipeline construction is greatly affected by a variety of practical factors. [ABSTRACT FROM AUTHOR]

• CO 2 sequestration and EGR are experimentally evaluated in two shale gas reservoirs. • Pore heterogeneity and connectivity are evaluated via multifractal analysis. • Shale composition controls on gas storage is evaluated from gas adsorption measurements. • Links between MICP and gas adsorption measurements were used to evaluate EGR suitability. In the global effort toward climate change mitigation, geologic storage of CO 2 in shale plays is becoming critical while it can improve production from these reservoirs. In this study, the gas storage capacity and CO 2 sequestration suitability of the Longmaxi and Niutitang shale gas reservoirs is investigated and compared via XRD analysis, programmed pyrolysis, low pressure N 2 and CO 2 adsorption, high pressure CH 4 adsorption, and MICP analysis. Results showed that clay and TOC controls on micropore heterogeneity and connectivity happens only within the Longmaxi Formation. Furthermore, both components play a role in the adsorbed quantities of gas in the formation which revealing a higher storage capacity in mesopore-macropores. This was verified by a positive correlation between adsorbed volume within the mesopore-macropore space. The Longmaxi Formation was also found to own better pore connectivity and PSD homogeneity of mesopore-macropores, indicating easier pathways for CO 2 movement channels within the pore network. Furthermore, the samples from the Longmaxi exhibited a positive relationship between adsorbed volume with the CO 2 breakthrough pressure and median pore diameter, alike between the mesopore-macropore volume and CO 2 breakthrough pressure. This means, the injected CO 2 will displace adsorbed methane within the mesopore-macropore and will be adsorbed and stored in such pores. Overall, superiority of the Longmaxi shale over the Niutitang for CO 2 storage and EGR would be significant for future operations in similar shale gas reservoirs in China and around the globe. [ABSTRACT FROM AUTHOR]

[Display omitted] • A bi-level joint-probabilistic programming approach is developed. • It can handle leader–follower issues and joint-probabilistic constraints. • The proposed approach is applied to China's multi-regional energy system model. • The optimal schemes during 2021–2050 under three mitigation scenarios are obtained. • Results are helpful to achieve low-carbon goals in multi-regional energy system. Climate change mitigation and renewable resources utilization are becoming particularly urgent for energy system management. In this study, a bi-level joint-probabilistic programming (BJPP) method is developed for planning multi-regional energy system under different mitigation policies and uncertainties. BJPP can handle leader–follower issues in decision-making process as well as examine the risk of violating joint-probabilistic constraints. Based on the BJPP method, a China's multi-regional energy system (named as BJPP_CMES) model is formulated to provide optimal scheme for energy system planning of China over a long-term horizon (2021–2050) by synergistically minimizing carbon dioxide (CO 2) emission and system cost. A series of scenarios associated with different carbon capture and storage (CCS) levels and violation risks of energy-demand constraints are examined. Results reveal that: (i) the share of non-fossil energy in China's energy supply would keep increasing in 2021–2050, and the highest growth of the renewable supply would occur in Ningxia (rising 47.7%); (ii) Sichuan, Inner Mongolia, and Gansu would be the top three suppliers of renewable electricity; (iii) the CO 2 emission of China would reach a peak of [44.3, 54.8] billion tonnes during the period of 2026–2030; Shandong, Inner Mongolia, and Shanxi would be main contributors of CO 2 emission in the future; (iv) compared with the single-level model, the CO 2 emission from the BJPP_CMES model would reduce by [2.7, 5.7]%; (v) among developed regions, the individual probability level of Jiangsu-Zhejiang-Shanghai is the most significant parameter for both CO 2 emission and system cost. The findings are helpful for decision makers to optimize multi-regional energy system (MES) with a low-carbon and cost-effective manner, as well as to provide useful information for renewable energy utilization and regional sustainable development. [ABSTRACT FROM AUTHOR]