Carbon Balance and Management最新文献

The biogeochemical cycling of carbon in aquatic systems is profoundly regulated by extreme hydrological events, particularly through their impacts on dissolved carbon species (DCs) and total ammonia nitrogen (TAN). Despite growing recognition of these interactions, the spatial correlations and environmental linkages between DCs and TAN during meteorological extremes remain poorly constrained in large river systems. To address this critical uncertainty, we conducted a field campaign during the unprecedented summer drought (June–September 2022) in the Changjiang River Basin, collecting 24 water samples across three lateral positions along the upper Changjiang River mainstem. Our analyses revealed three key findings: First, dissolved inorganic carbon (DIC) constituted the predominant DC component (> 75%), while dissolved organic carbon (DOC) exhibited marked spatial variability (coefficient of variation > 35%). Second, bank-specific correlations emerged between carbon fractions and TAN, with DCs-TAN relationships showing strong correlations along river banks but no significant association in the river center. Third, spatial autocorrelation analyses using univariate and bivariate Moran’s I indices quantified these heterogeneities, particularly revealing a striking positive association between DOC and TAN in the right bank (Moran’s I = 0.64). This spatial variability suggests synergistic controls by drought-induced hydrological forcing, land-use derived inputs, and water quality parameters. Our findings establish a mechanistic framework linking extreme drought conditions to lateral carbon-nutrient coupling patterns, providing critical baseline data for modeling climate-driven biogeochemical shifts in monsoon-regulated river systems.

As nations pursue decarbonization targets, coupling renewable energy with electric vehicles (EVs) has emerged as a promising pathway to enhance grid flexibility, reduce greenhouse‐gas emissions, and drive sustainable mobility. This review synthesises 2013–2023 trends in clean-energy expansion, energy-use carbon intensity, and EV adoption. Regions that expanded wind and solar faster cut carbon intensity more steeply and adopted EVs more quickly. Coordinating clean power with flexibility raised renewable penetration and contained integration costs. Smart charging typically reduced peaks and curtailment by ~ 10–25%. We then map five frontiers that couple renewables with e-mobility. Intelligent bidirectional management delivered 5–8% CO₂ savings at the distribution level. Aggregator and VPP participation unlocked $3,000–$4,500 per EV per year after degradation costs. Hardware and charging-infrastructure innovations trimmed converter losses by 3–5% and stabilised voltage at high EV penetrations. Microgrid and hybrid renewable–V2G designs lifted self-consumption by up to 15% and cut diesel backup by ~ 70%. Lifecycle and circular strategies showed that second-life batteries retained > 80% capacity after ten years, could meet up to 50% of Europe’s stationary-storage needs, and reduced raw-material demand by 7.5% and lifecycle emissions by 10–12%. We then diagnose the main barriers. Standards remain fragmented (ISO 15118, CHAdeMO, GB-T). Bidirectional chargers are costly. Many markets still enforce 1 MW bid floors and 15-min settlements. Interconnection and data rules are often unclear. Finally, we propose a sequenced roadmap: high-resolution pricing, clear aggregation access, harmonised technical and market standards, and cross-sector planning. Research priorities centre on integrated modelling, hardware–software co-design, large-scale pilots, and behavioural and market studies. This roadmap aligns policy, technology, and economics to accelerate a resilient, low-carbon energy–mobility transition.

Background

To mitigate climate change, China has established extensive plantations since the 1970s, making a substantial contribution to the terrestrial carbon sink. However, after decades of growth, plantations require effective management due to potential ecological risks. While thinning can provide long-term economic and ecological benefits for planted forests, it also imposes significant short-term disturbances that may result in temporary carbon sink losses. This raises a critical question: How does thinning affect forest carbon budgets on Earth? This issue is very controversial, largely due to variations in climate conditions, methodological approaches, and study scales. Consequently, in this study, three methods were used to quantify the effects of thinning on carbon fluxes and provide a theoretical and practical basis for carbon budget estimation and forest management.

Results

The 1-tower, look-up table (LUT), and 2-tower methods were used to investigate the effects of thinning on carbon fluxes. Among them, the 2-tower method is considered the most dependable which tracked the seasonal variation pattern of the carbon fluxes best. The 1-tower method is direct and easy to conduct but may involve estimation biases introduced by climatic interannual variations. While the LUT method could theoretically diminish the effects of the varying climate, it was weak in tracking relatively extreme values. The three methods yielded consistent results, indicating that 25% thinning enhanced gross primary productivity (GPP), net ecosystem productivity (NEP), and ecosystem respiration (Re). According to the 2-tower results, in the first year after thinning, the GPP increased by 9.8%, and it increased more in the second year after thinning, reaching 14.6%. However, a much greater increase in Re was found in the second year after thinning than in the first year, with values of 23.2% and 12.6%, respectively. Consequently, the increases in NEP induced by GPP were offset by increasing Re, which was 5.4% and 0.5% in the first and second years after thinning, respectively.

Conclusions

Thinning enhanced the GPP, Re, and NEP in the subtropical forest, indicating the positive effects of thinning in a near-mature coniferous plantation, even shortly after thinning.

Consolidated airborne laser scanning (ALS) programs, satellite imagery and spaceborne structural measurements have enabled major advances in canopy height mapping that translate towards the forest carbon biomass arena. However, we must carefully evaluate the cost of using fine-grained canopy height products to predict biomass under calibration models scoped at the scale of inventory plots. In this study, we estimated biomass using field plots and ALS metrics before predicting biomass over a jurisdiction of ~ 15,500 km² in Spain using 10 m, 25 m, 44 m, and 100 m as prediction scales. We altered the scale of ALS-based biomass predictors in 10 sub-jurisdictions intensively surveyed by the Spanish National Forest Inventory (NFI) before estimating mean and total biomass using three options: (i) traditional NFI design-based (DB) estimation, (ii) a model-based (MB) approach using scale-varying canopy height metrics from ALS and NFI plots, and (iii) an small-area estimation (SAE) implemntation designed for sub-jurisdictional domains. Higher uncertainties - relative standard errors (SE) - were found for DB, particularly at sub-jurisdictional and stratum levels. We observed a consistent increase in uncertainty for MB estimation from the finest 10 m scale up to 100 m. In MB estimation, the maximum relative bias reached 11% for 10-m predictions compared to the baseline estimate at the NFI sampling native resolution. The bias associated with the prediction scale ranged from + 5% (25 m) to -8% (100 m). The mean biomass estimates for SAE generally ranged between DB and MB but at lower uncertainty to the former, especially as the NFI sampling becomes scarcer and not enough for solid inference of biomass mean. The SEA statistics helped to disentangle biomass comparisons between ALS-based inference and the traditional NFI estimation that do not incorporate remote sensing data.

Background

To understand how genetic variation among varieties and stand density affect carbon (C), we assessed C stocks, fluxes, and partitioning in Pinus taeda L. plantations in Southeast Brazil. We measured the annual C balance in two consecutive years (from 7 to 9 years after planting) in four different clonal varieties with distinct crown structures (C1-medium, C2-broad, C3-narrow, and C4-broad) and an OP (open-pollinated) family. From age 7 to 8 years, the C balance was assessed for all five varieties at a stand density of 1894 trees ha^− 1. From age 8 to 9 years, the C balance was assessed for three varieties (C2, C3, and OP) at two stand densities (low density (LD): 613 trees ha^− 1 and high density (HD): 1894 trees ha^− 1).

Results

At age 7–8, the total C stock (above- and belowground plus the litter layer) among varieties ranged from 168 Mg C ha^− 1 (C3) to 186 Mg C m^− 2 (C1), with the bole as the largest pool (68%). Aboveground net primary production (ANPP) ranged from 1.9 to 3.1 kg C m^− 2 year^− 1, and total belowground carbon flux (TBCF) from 2.0 to 2.9 kg C m^− 2 year^− 1. The partitioning of GPP (Gross Primary Production) to ANPP and TBCF reached a maximum value of 35% and 41%, respectively. At age 8–9 years, the C stock was greater in the HD stands than in the LD stands across all varieties. Overall, C stock reached between 103.5 and 184.6 Mg C ha^− 1. ANPP under HD was 1.9 kg C m⁻² year⁻¹ compared with 0.62 kg C m⁻² year⁻¹ under LD. There were no significant differences in TBCF between the HD and LD stands. The partitioning of GPP to ANPP was lower and to TBCF was higher under LD compared with HD.

Conclusion

Relationship between crown structure and the C stock, fluxes, and partitioning is not clear and should be used with caution for management prescriptions related to C sequestration. Also, no differences in the bole C stock and sequestration were found across varieties within the same planting density. Finally, the genetic variation among varieties and stand density significantly affected stand productivity, with stand density showing greater effect.

As a key indicator of terrestrial carbon cycle, carbon use efficiency (CUE) represents the efficiency of carbon fixation and carbon allocation strategy, shaping ecosystem function and services. Siberia, as a major carbon sink, is experiencing rapid and dramatic climate change, which triggers complex ecological responses and leads to uncertainties in its carbon balance evaluations. However, the spatiotemporal variations of CUE and the underlying mechanisms remain rarely studied, limiting our understanding of Siberian carbon cycle under climate change. This study investigates the spatial variations of CUE across Siberian ecosystem and employs random forest and SHapley Additive exPlanation (SHAP) to analyze the intrinsic driving mechanisms from 2001 to 2020. The results indicate that the annual mean CUE over Siberia from 2001 to 2020 is 0.60 ± 0.07, with notable ecosystem-specific variations ranging from grasslands (GRA) (0.64 ± 0.08) to closed shrublands (CSH) (0.52 ± 0.06). Vapor pressure deficit (VPD) primarily shapes the CUE spatial variations, and its interactions with mean annual temperature (MAT) and shortwave radiation (SW) synergistically distribute CUE over Siberia. Rather than non-significant trends from 2001 to 2020, CUE exhibits significant decreasing trends over Siberian regions under both SSP1-2.6 and SSP5-8.5 from 2021 to 2100, with substantial fluctuations within this period. Moreover, under SSP5-8.5, CUE experiences twice the decreasing rate of that from SSP1-2.6, indicating more vulnerable responses of Siberian ecosystems to climate change under a higher warming projection. Our results provide valuable insights into the dynamics of CUE in Siberia and offer scientific guidance for climate adaptation strategies in this region.

The water level fluctuation zone (WLFZ) of the Three Gorges Reservoir (TGR) represents a unique ecotone shaped by reversed hydrological rhythms that significantly influence plant dynamics and soil organic carbon (SOC) processes. However, the contribution of plants to SOC storage after the establishment of stable plant communities remains unclear. A field investigation and soil sampling were conducted in the WLFZ of the TGR in 2023, covering both the main stream and tributary regions in middle- (155–165 m) and high-elevation (165–175 m) zones. The plant composition, diversity, and carbon and nitrogen contents of soil and vegetation and the carbon stable isotope ratio signatures were analyzed. Results showed that plant diversity increased with elevation, while biomass allocation varied significantly between elevation zones. Cynodon dactylon (L.) Pers. had a significantly higher biomass than Xanthium strumarium L., both of which were identified as dominant species in the WLFZ based on their high importance values. The response of SOC storage to elevation differed between regions: in the main stream, SOC storage was 23% higher in the middle-elevation than in the high-elevation zone, while in the tributary, SOC storage in the high-elevation zone exceeding that in the middle-elevation zone by 38%. Soil total nitrogen and the C/N ratio were the primary factors controlling SOC storage, explaining 68.6% of the variance, while plant effects were relatively weak. Isotopic mixing model results indicated that X. strumarium contributed 34.84% to SOC storage at 165–175m, whereas C. dactylon contributed 21.06% at 155–165 m, but this difference occurred within the context of a minor overall plant contribution to SOC. These results highlight that SOC dynamics are primarily controlled by soil factors (soil nitrogen and the C/N ratio), with plants having a secondary effect.

Climate and plant diversity are the major drivers of litter return and soil organic carbon (SOC) content. However, in cold and arid regions, how plant diversity and climate are affected by other factors and their contribution rates to the regulation of litter return and SOC content remains largely unknown. This study investigated the plant diversity and SOC content in the cold and arid vegetation areas of Qilian Mountains and Qaidam Basin. Results showed that when the number of plant species was between 10 ~ 15, it promoted the litter return. The relationship between the number of plant species and the litter decomposition was mainly related to the material composition of the plant itself, and there was no obvious linear relationship. Litter return (litter-to-biomass ratio = total biomass (TB) / litter biomass (LB)) was positively correlated with SOC. Under different precipitation gradients, the correlation in shallow soil depth (0 ~ 20 cm) was higher than in deep soil depth (20 ~ 40 cm). Plant diversity (SWI: Shannon-wiener Index, SRI: Species Richness Index) further regulated SOC content by affecting litter decomposition. Plant diversity (SWI: 1.75–2.25; SRI: 10–15) maximized SOC content. Climate dominated SOC regulation below 200 mm precipitation, while diversity prevailed at 200–600 mm. Based on the above, in arid regions with annual precipitation < 200 mm, climate factors (water, temperature) are the primary drivers regulating SOC. In regions with 200–600 mm precipitation, plant diversity becomes the key factor controlling SOC. When annual precipitation > 600 mm, the sensitivity of plant diversity to climate change decreases, thereby weakening its regulatory effect on SOC and litter decomposition.These results provide a scientific basis for studying species diversity and climate effects on litter decomposition and SOC content and is importance for understanding soil carbon pool changes and its influencing factors in cold and arid grassland ecosystems rgions.

Background

Against the backdrop of deep specialization within global value chains (GVCs), it is crucial to explore how firms’ participation in global production networks affects their carbon efficiency, a key factor in achieving green growth. Using merged data from the Chinese National Tax Survey Database, the Chinese Customs Trade Statistics Database between 2008 and 2014, and the World Input-Output Database, this paper empirically examines the effect of firms’ position embedded in GVCs on carbon emission efficiency in China’s manufacturing sectors.

Results

It is found that: (1) Improving firms’ position embedded in GVCs can significantly improve their carbon emission efficiency. (2) This improvement is primarily driven by trade structures optimization and technological innovation. (3) Forward GVCs embeddedness exerts a stronger positive impact on carbon efficiency compared to backward embeddedness. And the carbon efficiency benefits of upgrading to higher positions within GVCs are more pronounced in firms with a higher degree of participation, those engaged in mixed and general trade, firms in high-pollution industries, and those located in non-resource-oriented cities. (4) Participation in GVCs contributes to energy conservation and emission reduction, supporting long-term low-carbon and intensive development of enterprises.

Conclusions

The findings shed light on the crucial role of GVCs embeddedness in enhancing carbon emission efficiency, offering a solid foundation for understanding how globalization contributes to achieving long-term sustainable development goals.

Forest carbon projects hold significant potential for mitigating greenhouse gas emissions. However, growing scrutiny has raised concerns about their climate integrity, particularly the gap between scientific knowledge and the practical implementation of carbon quantification methodologies. Southeast Asia, a rainforested tropical region, is a key focus for the development of forest carbon projects. This study critically reviewed the quantification methods and associated reporting of 69 forest carbon projects across Southeast Asia, guided by three essential and interrelated criteria: transparency, robustness, and consistency. The findings reveal limited disclosure in methodological reporting, the adoption of potentially unreliable quantification practices, and substantial variability due to the differing standards adopted by projects. These issues risk undermining the credibility of carbon credits and may hinder their alignment with national and international climate goals. By identifying key methodological gaps and proposing clear evaluation criteria, this study contributes to ongoing debates around forest carbon credit integrity and underscores the urgent need for more transparent, rigorous, and standardised carbon accounting practices within the sector.