Search Results (170)

In the context of accelerating global climate change, the accurate quantification of forest carbon sequestration at the regional scale is of critical importance to estimate carbon budgets and formulate targeted ecological policies. This study systematically investigated the spatiotemporal dynamics and driving mechanisms of arbor forest carbon stocks between 2016 and 2020 in Yunnan Province, China. Based on the “One Map” forest resource inventory, the continuous biomass expansion factor (CBEF) method, standard deviational ellipse (SDE) analysis, and multiple linear regression (MLR) modeling, the results showed the following. (1) Arbor forest carbon stocks steadily increased from 832.13 Mt to 938.84 Mt, and carbon density increased from 41.92 to 42.32 t C·hm⁻². Carbon stocks displayed a dual high pattern in the northwest and southwest, with lower values in the central and eastern regions. (2) The spatial centroid of carbon stocks shifted 4.8 km eastward, driven primarily by afforestation efforts in central and eastern Yunnan. (3) The MLR results revealed that precipitation and economic development were significant positive drivers, whereas temperature, elevation, and anthropogenic disturbances were major limiting factors. A negative correlation to afforestation area indicated a diminished need for new plantations as forest quality and quantity improved. These results provided a theoretical foundation for spatially differentiated carbon sequestration strategies in Yunnan, providing key insights for reinforcing ecological security in Southwest China and enhancing national carbon neutrality objectives. Full article

The Earth’s degassing is an important factor in evaluating global carbon budget estimates and understanding the carbon cycle. As a result, numerous studies have focused on this topic. However, current estimates predominantly focus on subaerial CO₂ emissions and CO₂ deep submarine emissions, particularly along mid-ocean ridges (MORs), whereas very few and only spatially limited estimates of shallow submarine CO₂ emissions have been reported, despite being widespread features of the seafloor. This study reports the results of measuring the dissolved CO₂ concentrations in shallow submarine environments along the coast of Vulcano Island (Aeolian Islands, Italy). For the areas exhibiting the highest concentrations, we calculated the amount of diffuse degassing by computing the sea–air CO₂ flux. The results revealed extremely high dissolved CO₂ concentrations, reaching up to 24 vol.% in areas with visible hydrothermal activity, including one location far from the island’s main crater. Notably, elevated CO₂ levels were also detected in areas with minimal or no apparent hydrothermal discharge, indicating the occurrence of diffuse degassing processes in these areas. In addition, the calculated diffuse degassing flux was comparable in magnitude to the CO₂ flux directly emitted into the atmosphere from the island’s main bubbling pools. Full article

China plays an important role in the global terrestrial carbon cycle. While China is included in global assessments of the carbon cycle, such as the global carbon budget, the performance of dynamic global vegetation models (DGVMs) over China has rarely been evaluated. This knowledge gap constrains both model applicability and region-specific parameter optimization within China. To address this gap, our study assesses the performance of terrestrial carbon stocks and sinks simulated by 12 DGVMs in China from 1970 to 2018. The results indicate that (1) there is significant variation in the numerical magnitudes of terrestrial carbon stocks as simulated by various models, with mean vegetation carbon at 38.3 PgC and mean soil carbon at 115.3 PgC. Nevertheless, their spatial distribution demonstrates a remarkable degree of congruence. Notably, the simulated carbon stocks are generally in excess of existing estimates. (2) Despite the good consistency in the spatial distribution of terrestrial carbon sinks across different models, there is considerable fluctuation in the numerical values, with a mean carbon sink of 0.02 PgC yr⁻¹, a value lower than pre-existing estimations. (3) The responses of terrestrial carbon stocks and sinks to CO₂ fertilization, climate change, and land use change exhibit pronounced heterogeneity. CO₂ fertilization has a positive effect, whereas land use change has a negative one. The impact of climate change is variable, and the carbon sink effect engendered by CO₂ fertilization is negated by the adverse influence of land use change. This comprehensive evaluation of the simulation performance of DGVMs in China is anticipated to serve as an important reference for the functional analysis and parameter optimization of DGVMs within China. Full article

Elucidating the compositions, sources and mixing processes of dissolved organic matter (DOM) is crucial for a gaining deeper understanding of the coastal carbon cycle and global carbon budget. Hangzhou Bay (HZB), a vital estuary in China, receives freshwater inputs in the upper bay, borders the Changjiang River Estuary (CRE) to the north and is adjacent to Zhoushan Islands Region (ZIR) to the east. In HZB, the DOM sources and their compositions in estuaries remain unclear due to the complexity of this dynamic environment. In this study, we aimed to explore the chemical composition and sources of the DOM in the HZB and its adjacent coastal waters based on chromophoric DOM, fluorescent DOM indices and other hydrochemical parameters in the winter. The results showed that the DOM compositions in HZB have significant differences in the upper bay, middle bay and lower bay. The highest concentration of DOC was found in the CRE, close to the northern lower HZB, with high humification index (HIX), low biological index (BIX) and high proportion of humic-like fluorescent component (C1), indicating terrestrial inputs. In contrast, the DOM in the upper bay had high BIX and low HIX, being dominated by protein-like fluorescent components (C2 and C3), indicating an autochthonous source. The DOM in the middle bay showed mixed composition characteristics indicated by the chromophoric DOM (CDOM) and fluorescent DOM (FDOM) indices. Moreover, the terrestrial DOM transported via CDW intrusion accounted for a large proportion of the DOM in Northern HZB. Our study shows that, even in coastal estuaries with very strong hydrodynamics, the DOM composition can still retain its unique source signal, which, in turn, affects its migration and transformation processes. The results of this study provide supplement insights into the global carbon cycle and carbon budget estimation. Full article

Achieving the Paris Agreement’s 1.5 °C target requires a global-scale energy transition, reaching net-zero emissions by 2050. This transition demands not only a rapid expansion of renewable energy but also significant upfront energy investment, presenting potential trade-offs between near-term energy security and long-term sustainability. Assuming we cannot rely on as yet unproven negative emissions technology, reductions must be achieved directly, requiring fossil fuel phase-out, accelerated electrification, and substantial renewable infrastructure development. This study presents a detailed, transparent methodology for the creation of a simplified global energy system model designed to rapidly evaluate trade-offs between energy and climate policy, integrating energy investment, depletion, and saturation dynamics into energy transition scenarios. The model simulates energy supply and demand across major sectors, accounting for the upfront energy costs of deploying new renewable infrastructure and the dynamics of electrification in different demand sectors. Its transparent, user-controllable framework allows for rapid scenario adjustments based on variables such as population growth, per capita energy demand, rate and extent of electrification, and strength of climate policy. The primary purpose of this paper is to present the system modelling framework. However, we also present preliminary results from scenario analysis that point to two emergent risks: (1) prioritising energy security increases the likelihood of exceeding carbon budgets, while (2) stringent emissions reductions heighten the risk of energy shortages. Even under non-existent climate policy, fossil fuel depletion makes both the renewable transition and electrification of demand inevitable, though delayed transition leads to more severe emissions overshoot. These findings underscore the urgent need for demand reduction strategies and a more nuanced understanding of the energy investment required for decarbonisation. By offering a flexible scenario tool, this study contributes to informed public discourse and policy decisions on balancing energy security, emissions reduction, and climate resilience. Full article

This study explores biochar’s impact on soil fertility, greenhouse gas (GHG) emissions, grain yield, carbon footprint (CF), and net ecosystem carbon budget (NECB) in northwest China’s arid regions. A two-year field experiment tested three biochar rates (15, 30, and 45 t ha⁻¹) against a control. The results showed that biochar significantly reduced overall soil GHG emissions, though the highest rate increased methane emissions. The 30 t ha⁻¹ rate yielded the highest average grain production (13.9 t ha⁻¹), boosted soil organic carbon storage by 76 kg ha⁻¹, and decreased global warming potential (GWP) by 87.8 kg CO₂ ha⁻¹ and GHG emission intensity by 6.74 kg t⁻¹. Biochar also lowered the CF and enhanced the NECB, primarily through increased net primary production and improved soil fertility and crop yields. CO₂ emissions and fertilizer use were major CF contributors, but biochar reduced both the biomass-scaled and yield-scaled CFs. Overall, biochar improved crop yields, NECB, and soil carbon storage while reducing GWP, GHGI, and CF. This study recommends 30 t ha⁻¹ biochar to optimize crop production, enhance carbon balance, and mitigate climate change impacts, highlighting biochar’s potential as a sustainable soil amendment in arid ecosystems. Full article

As sensitive human-environment systems, lake-intensive regions are critical governance areas for advancing global low-carbon development. Rapid economic growth has intensified the imbalance between economic carbon sources and ecological carbon sinks in these regions. However, methods for measuring territorial space carbon budgets tailored to “production–living–ecological” functions are underdeveloped, and the mechanisms driving carbon imbalance risks remain unclear. To address these issues, this study develops a spatial measurement model for “carbon sources-carbon sinks” in the Dongting Lake region. Using exploratory spatiotemporal data analysis, this study identifies grid-scale variation patterns in carbon budgets. Finally, using the logarithmic mean Divisia index (LMDI) decomposition model, this study examines the driving mechanisms of carbon budgets from a territorial space perspective. The results indicate the following: (1) The territorial space of the Dongting Lake region follows a pattern where “ecological spaces surround production spaces, with living spaces interspersed among water network spaces”. Between 2005 and 2020, functional transitions primarily occurred between agricultural production spaces and forest or water ecological spaces. (2) The study area’s territorial space carbon budgets increased annually, though the growth rate slowed. Construction land was the most significant carbon emission source in territorial space. Spatially, carbon budgets exhibit a radial pattern, with high values concentrated in plains near water bodies, gradually decreasing inland. Spatiotemporal differentiation followed a north–south development trend along the water system axis. High-High clusters were concentrated in municipal areas with dense water networks. In contrast, Low-Low clusters appeared in peripheral mountainous regions to the west, east, and south. (3) Land-use efficiency had the most potent inhibitory effect on carbon budgets, cumulatively reducing carbon emissions by 1.37 × 10⁸ tC. Economic development had the strongest positive effect, adding 1.31 × 10⁸ tC in carbon emissions. Therefore, the Dongting Lake region should promote intensive land use, adjust industrial structures, and develop a green ecological economy to achieve sustainable carbon source–sink management. Full article

This study presents a comprehensive investigation of Methane (CH₄) emissions in the wetlands of South Sudan, employing an integrated approach that combines TROPOMI satellite data, river altimetry, and hydrological model outputs. TROPOMI data show a strong increase in CH₄ concentrations over the Sudd wetlands from 2018 to 2022. We quantify CH₄ emissions using these data. We find a twofold emission increase from 2018 to 2019 (9.2 ± 2.4 Tg yr⁻¹) to 2020 to 2022 (16.3 ± 3.3 Tg yr⁻¹). River altimetry data analysis elucidates the interconnected dynamics of river systems and CH₄ emissions. We identify correlations and temporal alignments across South Sudan wetlands catchments. Our findings indicate a clear signature of ENSO driving the wetland dynamics and CH₄ emissions in the Sudd by altering precipitation patterns, hydrology, and temperature, leading to variations in anaerobic conditions conducive to CH₄ production. Significant correlations are found between CH₄ emissions and PCR-GLOBWB-simulated soil moisture dynamics, groundwater recharge, and surface water parameters within specific catchments, underscoring the importance of these parameters on the catchment scale. Lagged correlations were found between hydrological parameters and CH₄ emissions, particularly with PCR-GLOBWB-simulated capillary rise. These correlations shed light on the temporal dynamics of this poorly studied and quantified source of CH₄. Our findings contribute to the current knowledge of wetland CH₄ emissions and highlight the urgency of addressing the complex interplay between hydrology and carbon dynamics in these ecosystems that play a critical role in the global CH₄ budget. Full article

Rivers are not only a vital part of the Earth’s water cycle but also sources and sinks for greenhouse gases (GHGs), exerting a significant influence on the global carbon budget. Rapid urbanization and intense human activities lead to water pollution and river habitat degradation, thereby affecting riverine greenhouse gas (GHG) emissions indirectly. Artificial management and restoration measures taken for rivers further increase the uncertainty of GHG emissions from rivers. In the context of carbon neutrality goals, research on GHG emissions from rivers has gradually become a hot topic. However, there is a scarcity of collective and comparative studies on the spatiotemporal patterns and mechanisms of riverine GHG emissions, especially a lack of summaries exploring the impacts of pollution and restoration on GHG emissions from rivers. This work systematically reviews recent studies concerning the emissions of CO₂, CH₄, and N₂O from rivers, with a particular focus on the characteristics and driving factors. Results have shown that riverine GHG emissions exhibit significant spatiotemporal heterogeneity. Besides hydrological factors such as wind speed, flow velocity, rainfall, and water level, large amounts of pollutants entering rivers strongly affect the production and emission of GHGs, since nutrients, organic matter, heavy metals, microplastics, and antibiotics can alter the biogeochemical processes in river ecosystems. Remediation measures can reduce water pollution levels, but some measures may further increase the emission of GHGs from rivers. This work emphasizes the need for conducting in-depth research on the synergies between treating river pollution and reducing riverine GHG emissions. It also proposes to reinforce the monitoring of GHGs and construct emission databases of rivers for sustainable watershed management. Full article

Opposite to atmospheric CO₂ concentrations, which reach a minimum during the vegetation season (e.g., June–August in the Northern Hemisphere), soil CO₂ reaches a maximum in the same period due to the root respiration. In karst areas, characterized by high rock porosity, this excess CO₂ seeps inside caves, locally increasing pCO₂ values above 1%. To better understand the role of karst areas in the carbon cycle, it is essential to understand the mechanisms of CO₂ dynamics in such regions. In this study, we present and discuss the spatial and temporal variability of air temperature and CO₂ concentrations in Samograd Cave, Croatia, based on three years of monthly spot measurements. The cave consists of a single descending passage, resulting in a characteristic bimodal climate, with stable conditions during summer (i.e., stagnant air inside the cave) and a strong convective cell bringing in cold air during winter. This bimodality is reflected in both CO₂ concentrations and air temperatures. In summer, the exchange of air through the cave’s main entrance is negligible, allowing the temperature and CO₂ concentration to equilibrate with the surrounding rocks, resulting in high in-cave CO₂ concentrations, sourced from enhanced root respiration. During cold periods, CO₂ concentrations are low due to frequent intrusions of fresh external air, which effectively flush out CO₂ from the cave. Both parameters show distinct spatial variability, highlighting the role of cave morphology in their dynamics. The CO₂ concentrations and temperatures have increased over the observation period, in line with external changes. Our results highlight the role of caves in transferring large amounts of CO₂ from soil to the atmosphere via caves, a process that could have a large impact on the global atmospheric CO₂ budget, and thus, call for a more in-depth study of these mechanisms. Full article

This study investigates an intermodal routing problem for transporting wood from a storage yard of the timber harvest area to a timber mill, in which the transfer nodes in the intermodal transportation network have multiple service time windows. To improve the environmental sustainability of timber transportation, a carbon tax policy is employed in the routing to reduce the carbon emissions. Uncertain information on the capacities and carbon emission factors of the transportation activities in the intermodal transportation network is modeled using interval fuzzy numbers to enhance the feasibility of the routing optimization in the actual timber transportation. Based on the above consideration, an interval fuzzy nonlinear optimization model is established to handle the specific routing problem. Model defuzzification and linearization are then conducted to obtain an equivalent formulation that is crisp and linear to make the global optimum solution attainable. A numerical experiment is conducted to verify the feasibility of the proposed model, and it reveals the influence of the optimization level and service time windows on the routing optimization, and it confirms that intermodal transportation is suitable for timber transportation. This experiment also analyzes the feasibility of a carbon tax policy in reducing the carbon emissions of timber transportation, and it finds that the performance of this policy is determined by the optimization level given by the timber mill and is not always feasible in all cases. For the case where a carbon tax policy is infeasible, this study proposes a bi-objective optimization that can use Pareto solutions to balance the economic and environmental objectives as an alternative. The bi-objective optimization further shows the relationship between lowering the transportation costs, reducing the carbon emissions, and enhancing the reliability on capacity and budget by improving the optimization level. The conclusions provide managerial insights that can help the timber mill and intermodal transportation operator organize cost-efficient, low-carbon, and reliable intermodal transportation for timber distribution, and support sustainable forest logistics. Full article

Carbon burial patterns in lakes and their dynamic changes significantly impact terrestrial carbon sink fluxes and global carbon budgets. In this study, multi-indicator analysis of sediment core samples (P1, P2, and P3) from Pipahai Lake was conducted. Integrating the chronological sequences of ²¹⁰Pb and ¹³⁷Cs, we identified the historical changes and spatial characteristics of total organic carbon (TOC) and inorganic carbon (TIC) burial in Pipahai Lake since 1884. The results show that the TOC content was higher than that of the TIC. They exhibited an increasing trend with decreasing depth. Linear regression results indicated that the variation of TOC is less directly affected by precipitation (R = 0.39) and temperature (R = 0.58), while temperature may have a greater impact on TOC. From 1884 to 1995, nutrients were not the primary factor influencing changes in TOC. The synchronous variation in TIC and TOC contents reflects a higher contribution of external inputs to carbon burial in the Pipahai Lake basin. After 1996, nutrients may have begun to affect variations in TOC. The TOC primarily originates from distal aeolian transport or autochthonous sources, though human activity has played a role in its evolution. The TIC content is controlled by the TOC content and autochthonous sources. This study will contribute to the understanding of the carbon cycling dynamics and their influencing mechanisms in a high-altitude lake ecosystem. Full article

Cold-temperate forests (CTFs) are not only an important source of wood but also provide significant carbon storage in China. However, under the increasing pressure of human activities and climate change, CTFs are experiencing severe disturbances, such as logging, fires, and pest infestations, leading to evident degradation trends. Though these disturbances impact both regional and global carbon budgets and their assessments, the disturbance patterns in CTFs in northern China remain poorly understood. In this paper, the Genhe forest area, which is a typical CTF region located in the Inner Mongolia Autonomous Region, Northeast China (with an area of about 2.001 × 10⁴ km²), was selected as the study area. Based on Landsat historical archived data on the Google Earth Engine (GEE) platform, we used the continuous change detection and classification (CCDC) algorithm and considered seasonal features to detect forest disturbances over nearly 30 years. First, we created six inter-annual time series seasonal vegetation index datasets to map forest coverage using the maximum between-class variance algorithm (OTSU). Second, we used the CCDC algorithm to extract disturbance information. Finally, by using the ECMWF climate reanalysis dataset, MODIS C6, the snow phenology dataset, and forestry department records, we evaluated how disturbances relate to climate and human activities. The results showed that the disturbance map generated using summer (June–August) imagery and the enhanced vegetation index (EVI) had the highest overall accuracy (88%). Forests have been disturbed to the extent of 12.65% (2137.31 km²) over the last 30 years, and the disturbed area generally showed a trend toward reduction, especially after commercial logging activities were banned in 2015. However, there was an unusual increase in the number of disturbed areas in 2002 and 2003 due to large fires. The monitoring of potential widespread forest disturbance due to extreme drought and fire events in the context of climate change should be strengthened in the future, and preventive and salvage measures should be taken in a timely manner. Our results demonstrate that CTF disturbance can be robustly mapped by using the CCDC algorithm based on Landsat time series seasonal imagery in areas with complex meteorological conditions and spatial heterogeneity, which is essential for understanding forest change processes. Full article

The gross primary productivity (GPP) of vegetation stores atmospheric carbon dioxide as organic compounds through photosynthesis. Its spatial heterogeneity is primarily influenced by the carbon uptake period (CUP) and maximum photosynthetic productivity (GPP_max). Grassland, cropland, and forest are crucial components of China’s terrestrial ecosystems and are strongly influenced by the seasonal climate. However, it remains unclear whether the evolutionary characteristics of GPP are attributable to physiology or phenology. In this study, terrestrial ecosystem models and remote sensing observations of multi-source GPP data were utilized to quantitatively analyze the spatio-temporal dynamics from 1982 to 2018. We found that GPP exhibited a significant upward trend in most areas of China’s terrestrial ecosystems over the past four decades. Over 60% of Chinese grassland and over 50% of its cropland and forest exhibited a positive growth trend. The average annual GPP growth rates were 0.23 to 3.16 g C m⁻² year⁻¹ for grassland, 0.40 to 7.32 g C m⁻² year⁻¹ for cropland, and 0.67 to 7.81 g C m⁻² year⁻¹ for forest. GPP_max also indicated that the overall growth rate was above 1 g C m⁻² year⁻¹ in most regions of China. The spatial trend pattern of GPP_max closely mirrored that of GPP, although local vegetation dynamics remain uncertain. The partial correlation analysis results indicated that GPP_max controlled the interannual GPP changes in most of the terrestrial ecosystems in China. This is particularly evident in grassland, where more than 99% of the interannual variation in GPP is controlled by GPP_max. In the context of rapid global change, our study provides an accurate assessment of the long-term dynamics of GPP and the factors that regulate interannual variability across China’s terrestrial ecosystems. This is helpful for estimating and predicting the carbon budget of China’s terrestrial ecosystems. Full article

The temperature sensitivity (Q₁₀) of soil respiration (Rs) plays a crucial role in evaluating the carbon budget of terrestrial ecosystems under global warming. However, the variability in Q₁₀ along soil moisture gradients remains a subject of debate, and the associated underlying causes are poorly understood. This study aims to investigate the characteristics of Q₁₀ changes along soil moisture gradients throughout the whole growing season and to assess the factors influencing Q₁₀ variability. Changes in soil respiration (measured by the dynamic chamber method) and soil properties were analyzed in a poplar plantation located in the suburban area of Beijing, China. The results were as follows: (1) Q₁₀ increased with the increasing soil water content up to a certain threshold, and then decreased, (2) the threshold was 75% to 80% of the field capacity (i.e., the moisture content at capillary rupture) rather than the field water-holding capacity, and (3) the dominant influence shifted from soil solid-phase properties to microbes with increasing soil moisture. Our results are important for understanding the relationship between the temperature sensitivity of soil respiration and soil moisture in sandy soil, and for the refinement of the modeling of carbon cycling in terrestrial ecosystems. Full article