Revealing inter-regional water-energy-carbon transfer driven by land use has great significance for realizing multiple objectives of resource collaborative optimization and carbon mitigation, yet land-use WEC accounting at the provincial scale and the efficiency of inter-regional WEC transfer driven by embodied land flow remain insufficiently explored in China. Accordingly, a theoretical framework for water-energy-carbon accounting and inter-regional transfer based on land use was established. Then the water and energy use and carbon emissions of cropland, forest land, grassland, water area, and construction land in 30 Chinese provinces were estimated and their spatial-temporal patterns were analyzed. The efficiency and spatial characteristics of inter-provincial water-energy-carbon transfer driven by embodied land flow were discussed. The results showed that the land-use water consumption was relatively stable from 2005 to 2020, while land-use energy consumption and carbon emissions exhibited an increasing trend. Embodied land mainly flowed from underdeveloped areas to developed areas, and there was regional variability in the related water-energy-carbon transfer. The energy-carbon transfer patterns driven by embodied land flow were similar. Embodied land consumption was concentrated in cropland, forest land, and grassland. Water consumption driven by embodied land flow was primarily concentrated in cropland. Energy consumption and carbon emissions driven by embodied land flow were mainly concentrated in construction land. Generally, the embodied land flow-related water-energy-carbon transfer efficiency has improved, with the proportion of efficient transfer increasing by 2.03%, 2.08%, and 2.82%, respectively. Water transfer between different land use types was more efficient than energy-carbon transfer, and water-energy-carbon transfer associated with construction land was inefficient. Water-energy-carbon transfer driven by embodied land flow could alleviate resource and environmental pressures, while its efficiency could still be enhanced. Therefore, in the future, land resource allocation should be optimized based on regional coordination and integrated water-energy-carbon management to enhance the efficiency of cross-regional water-energy-carbon transfer, thereby achieving efficient resource utilization and environmental sustainability. Overall, this study provides quantitative evidence for the resource and environmental impacts of cross-regional land resource allocation and offers new insights for synergistic resource optimization from a remote coupling perspective.
In the context of escalating global climate change and China's commitment to its dual carbon goals, this study investigates the spatiotemporal dynamics of carbon balance across 296 prefecture-level and higher cities in mainland China from 2001 to 2022, using emission data from the EDGAR database. By integrating ecosystem carbon sequestration models with economic contribution coefficients (ECC), ecological support coefficients (ESC), and China's main functional zoning framework, we systematically analyze regional carbon sources and sinks and propose a spatially explicit optimization strategy. Results reveal a distinct "higher in the north than in the south, higher in the east than in the west" emission pattern, driven by economic agglomeration and energy structure, with industrial clusters such as Beijing-Tianjin-Hebei and the Yangtze River Delta acting as high-emission hotspots; notably, the Chengdu-Chongqing region exhibited a sharp emissions surge in 2022 due to accelerated industrialization. In contrast, carbon sequestration capacity forms a "northeast-southwest high axis," enhanced by ecological restoration in regions like the Yellow River Basin but diminished along the eastern coast due to urban expansion, thereby exacerbating regional carbon imbalance. Based on ECC and ESC, we classify areas into four dynamically adjusted carbon balance zones: (1) low-carbon maintenance zones (e.g., Beijing-Tianjin-Hebei, Chengdu-Chongqing), characterized by strong economic output and carbon sink potential; (2) economic development zones (e.g., Central Plains, Shandong Peninsula), reliant on high-carbon industries yet underpinned by relatively sound ecological foundations; (3) carbon sink development zones (middle reaches of the Yangtze River), combining significant economic contributions with fragile ecosystems; and (4) comprehensive optimization zones (e.g., Hohhot-Baotou-Ordos-Yulin, Hexi Corridor), facing dual economic and ecological pressures. These are further refined into 16 sub-zones aligned with national functional zoning to enable targeted policy implementation. We recommend zone-specific strategies: consolidating low-carbon technologies and ecological advantages in maintenance zones; accelerating industrial decarbonization and energy efficiency in development zones; strengthening ecological restoration and green industry cultivation in sink zones; and fostering coordinated socio-ecological development in optimization zones through policy incentives, interregional collaboration, and market mechanisms. Ultimately, achieving nationwide carbon balance hinges on two core pathways: optimized land-use planning and the implementation of differentiated, spatially tailored policies that account for local socioeconomic and ecological contexts.
Against the backdrop of global warming, land use change critically shapes regional carbon budgets by altering both emission sources and carbon sinks. Existing studies predominantly focus on macro-scales, overlooking county-level heterogeneity and future trajectories, thus limiting precise carbon balance management. The Chengdu Plain, as a key economic agglomeration and upper Yangtze ecological barrier, faces severe carbon imbalance challenges due to rapid urbanization. This study contributes three novel insights: (i) integrating county-scale analysis with future land use simulation to project carbon budget dynamics; (ii) applying GTWR to reveal spatiotemporally heterogeneous driving mechanisms that macro-scale studies mask; and (iii) developing a county typology-based carbon management framework. (1) From 2000 to 2030, construction land expanded significantly while cropland, forest, and grassland continuously contracted; (2) The net carbon budget (net emissions) followed a trajectory of initial increase and subsequent decline, peaking at 6673.122 × 10⁴ t in 2020 before declining to a projected 6409.177 × 10⁴ t by 2030. Construction land was the dominant carbon source, while forests served as the primary carbon sink, together accounting for over 95% of the gross budget; (3) County-level net carbon budgets exhibited strong positive spatial autocorrelation, dominated by High-High and Low-Low agglomeration patterns; (4) GTWR results indicated that consumption level (mean coefficient: 0.466), urbanization level (0.392), population size (0.388), and industrial structure (0.196) positively drove net carbon emissions, while investment level (-0.048) exhibited an inhibiting effect not captured in average macro-scale models. Spatiotemporal heterogeneity was notable. Achieving a managed regional carbon balance requires differentiated county-level strategies: For urban core counties, low-carbon community transformation and optimized urban layout; for industrial counties, carbon intensity thresholds and green industrial land policies; for underdeveloped southwest counties, green consumption promotion; and cross-regional carbon compensation mechanisms to strengthen sink protection. This county-scale, mechanism-based framework provides a scientific toolkit for precise carbon balance management in ecologically and economically vital regions.
Land use carbon emissions (LUCE) is crucial for achieving carbon neutrality and sustainable development goals. How to coordinate ecological and economic benefits and formulate targeted regional carbon balance strategies based on local conditions remains to be explored. Therefore, Shaanxi Province in China was selected as the case for this study due to its rich ecological and energy resources and its significant differences. LUCE was calculated for each county in the region from 2000 to 2020. The contribution of carbon ecological capacity was quantified by calculating the carbon ecological support coefficient (ESC). The economic output per unit of carbon emission was measured using the carbon economic contribution coefficient (ECC). Based on the above, an optimized functional zoning for LUCE and carbon balance was constructed. Results showed that LUCE in Shaanxi Province increased from 2,088.18 × 104 tonnes in 2000 to 19,330.99 × 104 tonnes in 2020, with central region accounting for 64.81% of the total, northern region 22.92%, and southern region 12.27%. About 53.27% of counties maintained ecological deficits (ESC < 1) in the Northern Shaanxi Energy Zone and the Guanzhong Belt, while 56.07% exhibited an imbalance between economic output and carbon emissions (ECC < 1) in the Northern periphery and the Southern Ecological Zone. Economic growth was positively correlated with LUCE and negatively with ESC, but had a relatively small relationship with ECC and carbon absorption. Subsequently, all counties in Shaanxi Province were classified into five functional types: Carbon Sink Zones, Low-Carbon Economic Zones, Economic Development Zones, Carbon Intensity Control Zones and High-Carbon Optimization Zones, and a targeted strategy was proposed for each functional type. These results could provide a practical and transferable framework for supporting carbon neutrality planning and sustainable land use management in ecologically sensitive regions.
As a major contributor to carbon emissions among various land-use types, the expansion and spatial distribution of construction land are critical factors in regional carbon management strategies. Although considerable research has independently examined construction land growth control and regional carbon emission assessments, few studies have integrated these aspects to guide construction land expansion within the framework of carbon peaking strategies. This study proposes an innovative framework that integrates carbon emission considerations into the management of regional construction land expansion. Using Changsha City as a case study, this research analyzes the spatiotemporal dynamics of construction land expansion and associated carbon emissions from 1990 to 2020, exploring their interdependencies. To project future trends, three scenarios-natural growth, high-emission expansion, and low-emission development-were developed to simulate the impacts of construction land changes on carbon emissions by 2030. The study evaluates the carbon emission consequences of urban expansion and proposes mitigation strategies within a low-carbon development framework. The findings indicate that: (1) From 1990 to 2020, construction land in Changsha City expanded by 660.24 km², primarily encroaching upon adjacent cultivated and forested lands. During the same period, carbon emissions increased by 1.3963 × 10⁸ t, showing a strong positive correlation with construction land expansion; (2) By 2030, carbon emissions are projected to reach 2.396 × 10⁸ t, 2.582 × 10⁸ t, and 1.639 × 10⁸ t under the natural growth, high-emission, and low-emission scenarios, respectively, reflecting increases of 53.21%, 65.11%, and 4.81% relative to 2020 levels; (3) Under both the natural growth and high-emission scenarios, construction land expansion is likely to intensify its adverse impact on the regional ecosystem, thereby reducing ecological stability. In contrast, the low-emission development scenario is projected to promote significant improvements in ecosystem health and resilience. This study offers critical insights for territorial spatial planning and construction land management within the context of the dual-carbon strategy, presenting a viable pathway for reconciling land expansion with ecological sustainability.
Soil organic carbon (SOC) plays a crucial role in the ecological stability of Semi-Arid Alpine Ecosystems and in the global carbon cycle. However, its dynamic loss mechanisms, particularly the synergistic effects of snowmelt and rainfall-induced erosion, remain unclear. This study focuses on the upper Heihe River basin in the central Qilian Mountains, China. Six types of erosion units were set up along an elevation gradient, and field surveys were conducted over two years. Based on the XGBoost algorithm, digital mapping of SOC at the basin scale was carried out. Using the 2006–2020 period as the simulation timeframe, a composite hydraulic erosion calculation method was developed by coupling the SPHY hydrological model with the RUSLE model, incorporating snowmelt runoff and observed sediment data. Geographic detectors and structural equation models were used to reveal the driving mechanisms of composite hydraulic erosion on SOC loss. The results showed that the SOC density in the 0–20 cm soil layer of the basin was 10.90 × 106 kg C m− 2. The annual average soil sediment yield modulus in the basin ranged from 7.82 to 14.49 t ha− 1 yr− 1, with an SOC output rate of 0.50 ± 0.08 t C ha− 1 yr− 1. The total SOC loss in the basin was (50.16 ± 8.57)×104 t C yr− 1, with rainfall-induced erosion contributing 94% and snowmelt-induced erosion contributing 6%, highlighting the significant role of snowmelt erosion in future carbon management. High carbon loss areas were primarily concentrated in alpine cold deserts and alpine meadows, which accounted for 89.81% of the total SOC loss in the basin, making these areas key targets for future carbon management in semi-arid, high-altitude regions. The SOC loss rate during wet-cold years (0.62 ± 0.15 t C ha− 1 yr− 1) was 1.31 times and 1.51 times higher than in normal years (C2) and dry-hot years (C3), respectively, indicating the need for differentiated carbon management strategies based on climatic conditions. The coupling effects of composite hydraulic erosion processes under climate and topography regulation, along with the erosion-suppressing effect of surface vegetation, jointly determine the spatial heterogeneity of soil carbon loss. This study deepens the understanding of the water erosion–carbon loss process in semi-arid, high-altitude regions and provides theoretical support for erosion control and carbon management in alpine ecosystems.
A comprehensive understanding of land use carbon metabolism characteristics from the production-living-ecological space (PLES) perspective is crucial for formulating carbon reduction strategies. As the core economic zone of northern China, the Beijing-Tianjin-Hebei (BTH) region faces severe carbon emission pressures due to rapid urbanization and intensive land use transformation. However, focusing solely on carbon metabolism calculation without considering future changes and optimization effects may prevent achieving carbon emission reduction targets. This study assessed carbon emissions and sequestration based on different land use types in PLES, constructed a multi-objective carbon reduction scenario utilizing the Dinamica-EGO model, nondominated sorting genetic algorithm II, and entropy weight-TOPSIS model, and simulated 2035 carbon reduction characteristics by coupling PLES changes. Taking the BTH region as a case study, a methodological framework and corresponding models were established. The results show that from 2000 to 2020, the total carbon emissions in the BTH region increased significantly, presenting a spatial pattern of high emissions in the southeast and low emissions in the northwest. In contrast, the overall carbon sequestration capacity showed a decreasing trend, with stronger capacity in the northwest and weaker capacity in the southeast. The multi-variable 2035 carbon emission reduction prediction model achieved an accuracy of 82.24%. The 2035 carbon reduction plan developed based on this framework outperformed the original land use plan: economic benefits, emission reduction efficiency, spatial compactness, and accessibility are projected to increase by 15.8%, 7.9%, 2.5%, and 8.3%, respectively, while carbon emissions are expected to decrease by 19.04%. The proposed PLES-based framework for carbon metabolism measurement and emission reduction simulation exhibits good applicability in regional spatial emission reduction. These findings contribute to exploring regional carbon dynamics and provide references for governments to formulate carbon reduction policies.
Changes in global patterns can leave a lasting legacy in semiarid grasslands by reshaping microbial growth dynamics and carbon cycling during the first wet-up in the autumn-a period known for intense microbial activity and significant carbon emissions. To study the lasting impacts of decreased winter rain, we implemented two precipitation regimes (100% vs. 50% mean annual precipitation) in California Mediterranean-climate grassland field plots. After the dry season, soils were rewetted in the laboratory with H218O and sampled at 0 h, 3 h, 24 h, 48 h, 72 h, and 168 h post rewet. We quantified CO2 efflux, measured microbial growth and mortality via quantitative 18O stable isotope probing and 16S rRNA gene amplicon sequencing, and characterized the soil organic carbon chemical composition, metagenomes, and metatranscriptomes. We found that reduced winter precipitation imposed a strong legacy effect on microbial turnover; despite maintaining similar respiration rates, microbial growth declined by ~1 order of magnitude, yielding decreased community growth efficiency (CGE = new biomass growth/respiration), and microbial mortality declined by ~2 orders of magnitude. Soil organic carbon also shifted from lipid-like, amino-sugar-like, and protein-like compounds (indicative of microbial necromass) to more oxidized lignin-like and tannin-like compounds (indicative of decomposing plant-derived compounds). Meta-omics revealed distinct metabolic strategies linked to CGE. At high-CGE, microbes appeared to consume more energetically favorable N-rich necromass (released via high microbial turnover); this allowed for increased amino acids and peptidoglycan biosynthesis and greater aromatic compound degradation, fueling further energy production and growth efficiency. At low CGE, communities had elevated carbohydrate metabolism and lipid turnover, consistent with increased investment in plant detritus degradation and membrane repair and maintenance rather than growth. Together, our findings demonstrate that reduced winter rainfall decreases microbial turnover following rewetting without a concurrent reduction in CO2 emissions. This shift results in persistently lower CGE, which has the potential to increase soil carbon loss as CO2. If such conditions are maintained over multiple years, these changes could reshape soil organic carbon stocks and alter the balance of grassland ecosystems under future climate scenarios. While our data suggest that sustained reductions in CGE may drive SOC decline, the magnitude and persistence of these effects depend on long-term environmental dynamics and warrant further investigation. Video Abstract.
As the world’s largest energy consumer and CO2 emitter, China faces severe sustainable development challenges and intense international pressures. The pronounced spatial heterogeneity of CO2 emissions and sinks creates a dynamic pattern of carbon-deficient and carbon-surplus regions. Horizontal carbon eco-compensation activates the market value of carbon sinks, redistributes sink-related benefits, and internalizes both positive and negative environmental externalities, thereby facilitating the valuation of carbon-sink ecosystem services. In this research, CO2 emission space is treated as a tradable ecological product. Within a government-led, market-coordinated accounting framework, carbon-deficient regions provide ecological compensation to carbon-surplus regions, while the latter are compensated for environmental stewardship and opportunity expenses. The CO2 emission quotas of each province are first determined by the entropy method, and a horizontal carbon ecological compensation recipient and payer identification framework is constructed. Next, the compensation standard accounting models under three scenarios of active participation, passive participation and refusal to participate are constructed respectively. Finally, the empirical analysis is carried out with 30 provinces in China as the object set. The results show that: (1) Regions with high CO2 emissions are mostly economically developed, energy-intensive or densely populated areas, while the regions with high CO2 sequestration often have the characteristics of complete ecological patterns, superior hydrothermal conditions or remarkable ecological restoration results. (2) Among the 30 provinces studied, 18 provinces show the characteristics of carbon surplus, which are mainly distributed in the south, central and western regions and parts of the north; the remaining 12 are carbon-deficient regions, concentrated in the eastern coastal and northern regions of China. (3) Under the framework of the provincial horizontal carbon eco-compensation mechanism, this research identifies three behavioral scenarios: active participation, passive participation and refusal to participate. It is found that active participation compensation is the optimal strategy, which provides a basis for the formulation of differentiated horizontal eco-compensation standards and implementation plans.
Carbon stocks and stock changes in harvested wood products (HWPs) are an important part of land sector greenhouse gas (GHG) estimation and reporting. HWPs broadly categorized as products in-use (e.g., solid wood and paper products) and in solid waste disposal sites (SWDS; e.g., landfills), store carbon transferred from harvested trees. In the United States (US), estimates of carbon in HWPs have historically been reported in the US GHG Inventory and included in submissions to the United Nations Framework Convention on Climate Change. These data have been obtained from national and international statistics on production and consumption of forest products and incorporated into a compilation system to estimate carbon in products in-use and in SWDS. In contrast, estimates of carbon in forest ecosystems have been obtained from nationwide forest inventory (NFI) data collected and maintained by the US Forest Service, Forest Inventory and Analysis (FIA) program. Here we describe a case study for the northern Lake States region of the US (Michigan, Minnesota, Wisconsin) where harvest data from the FIA program were integrated into HWP compilation systems. This advance improves consistency and continuity with forest ecosystem from NFI plots with estimates of HWPs. Over the 1900-2024 time period, total estimated net accumulation (i.e., balance of additions from transfers of harvested wood from forest ecosystems and losses from decay of wood harvested in the past) of carbon stored in products in-use was 277.0 ± 17.5 Million Metric Tons (MMT) Carbon (C) and in SWDS was 155.2 ± 9.8 MMT C. We estimate that HWPs from the region represent a carbon sink of 4.9 ± 0.1 MMT C in 2024. These estimates include HWPs produced in the region and exported domestically or internationally, as well as any HWPs produced and retained in the region, but not imports. The proposed methodology enables disaggregation with coarse national and state-level FIA data, and allows for integration of more specific, entity-level data to improve precision and reduce uncertainty in HWPs estimates in the US and improves consistency and continuity with forest ecosystem estimates across spatial and temporal scales.
Amid the ongoing transition toward low-carbon urban development, subway networks, as a modern mode of transportation, have become a key focus of academic attention. However, existing research suffers from two critical gaps: first, a predominant focus on either carbon emissions or carbon absorption in isolation, rather than their equilibrium; second, a simplistic "point‑line" physical assessment of subways that overlooks network‑level accessibility and topology. This study addresses these gaps by adopting the carbon balance ratio (the ratio of terrestrial carbon absorption to anthropogenic emissions) as the outcome variable and employing Social Network Analysis to construct dynamic, station-level subway network centrality metrics in China. Empirical findings reveal that a one‑unit increase in county‑level subway network accessibility significantly improves the carbon balance ratio. This effect is strongest in economically underdeveloped regions, areas with compact spatial structures, and zones with lower residential electricity consumption. Mechanism analysis reveals a tri‑phase contribution: (1) during construction, subways preserve green space and carbon absorption capability by avoiding surface disruption; (2) during operation, they induce modal shifts that reduce transport emissions; and (3) through industrial transformation, their carbon benefits are amplified by supportive institutions, market mechanisms, and technological capabilities. By systematically integrating carbon balance measurement with network‑level subway accessibility, this study offers a comprehensive empirical framework and provides policy insights for integrating rail transit into low‑carbon spatial governance strategies.
China's low-carbon policy system is a key institutional arrangement for advancing carbon disclosure, promoting green transformation, and supporting the achievement of the "dual-carbon"goals. However, existing studies have paid limited attention to the policy system itself as an integrated and evolving object of analysis. To address this gap, this paper develops a three-dimensional analytical framework of policy instruments, policy objectives, and policy effectiveness, and applies content analysis and temporal interval analysis to 1008 coded policy documents issued between 2007 and 2024. The results show that first, policy instruments are structurally imbalanced, with environment-type instruments dominating the policy mix, while supply-side and demand-side instruments remain relatively insufficient. Second, policy objectives are primarily oriented toward the national "dual-carbon"strategy, with comparatively limited attention to corporate sustainable development and investors' low-carbon information needs. Third, policy effectiveness is unevenly distributed, as most policy texts are concentrated in provincial-level guiding documents, whereas high-authority policy documents remain limited. Fourth, China's low-carbon policy system exhibits a clear three-stage evolution, moving from initial exploration to system construction and deepening, and then to adaptation and innovation. Finally, broader trend-based evidence suggests that changes in carbon emissions, green finance, and firm-level green transformation are broadly aligned with the direction of China's low-carbon policy development. By shifting the analytical focus from isolated policy measures to the policy system itself, this study provides a more systematic basis for understanding the internal logic and evolutionary dynamics of China's low-carbon governance, while also offering policy implications for China and institutional reference for other developing countries.
Since the Industrial Revolution, the increasing emissions of greenhouse gases have posed unprecedented challenges to sustainable human development. As one of the most vital terrestrial ecosystems, farmland ecosystems play an irreplaceable role in balancing carbon emissions and absorption, attracting growing scholarly attention. Taking Jiangsu Province, one of China's major grain-producing regions, as the study area, this research integrates the Slacks-Based Measure (SBM) model, the entropy-weighted method, and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to analyze the spatiotemporal evolution of farmland carbon effects-including carbon emissions, carbon absorption, and net carbon sequestration-during 2011-2021. Furthermore, a Grey Prediction Model was employed to forecast the carbon effects of 13 cities over the next 12 years. The results show that Jiangsu's farmland carbon emission efficiency exhibited an overall upward trend with fluctuations, with an average value of 0.76. The multi-year mean fitting degrees of resource input and agricultural output were relatively low, at 0.426 and 0.358, respectively, with substantial intercity differences. The average coupling coordination degree between resource input and agricultural output was 0.66, indicating a primary coordination state. The constructed GM (1,1) model achieved a qualification rate exceeding 73.80%, demonstrating its reliability for predicting farmland carbon effects. Forecasts suggest a potential weakening of the province's agricultural carbon sink effect, with the net carbon sequestration in 2033 expected to decline by 15.55% compared with the maximum value during the observation period. This study reveals the spatiotemporal characteristics and potential evolution patterns of farmland carbon effects, providing theoretical support for region-specific agricultural emission reduction policies and promoting the sustainable development of efficient, low-carbon agriculture.
A comprehensive assessment of hydropower's climate impact requires considering both greenhouse gas (GHG) emissions and carbon burial in sediment. This study examines the Wujiang River in southwestern China, where seven cascade reservoirs were categorized into upper (Group 1), middle (Group 2), and lower (Group 3) reaches according to their geographic locations and proximity to key sediment source areas. The G-res Tool was conducted to simulate greenhouse gas (GHG) emissions from these reservoirs, which ranged from 2,231 to 19,774 t CO2e yr-1 after impoundment. The primary influencing factors include reservoir age, surface area, and water retention time. Due to the steep mountainous terrain, deep valleys, and pre-impoundment clearing, the GHG emissions from these groups of reservoirs are lower than those of other reservoirs at similar latitudes worldwide. As the cascade reservoirs were gradually constructed, sediment accumulated behind the dams, leading to the long-term storage of terrigenous carbon. Notably, the upstream Group 1 reservoirs exhibited an exceptionally high terrigenous carbon storage rate during their early impoundment phase (7,468 gC m-2 yr-1), largely due to significant sediment input from the upstream Yachihe Basin, a major sediment source. In contrast, the downstream reservoir (Group 3) exhibited relatively smaller total terrigenous carbon storage rates (319 gC m-2 yr-1), corresponding to reduced sediment retention. Despite variations in sediment retention among the groups, the total terrigenous carbon storage of all groups of reservoirs (ranging from 43,020 to 999,403 tC yr-1) exceeded their post-impoundment GHG emissions. By integrating carbon emissions and sedimentary carbon sequestration across a cascade system, this study provides a system-scale carbon balance assessment of hydropower reservoirs. Our results indicate that the cascade reservoir systems, like those on the Wujiang River, function as a net terrigenous carbon storage, mainly due to the large sediment sequestration. These findings highlight the importance of incorporating both carbon emission and storage into carbon accounting frameworks and provide new insights for carbon balance assessment and management of hydropower systems.
Synergistic water-nitrogen (N) management is vital for high maize (Zea mays L.) yields, but the integrated physiological mechanisms driving yield formation remain unclear. A 2-year field study with 3 irrigation levels and 4 N rates revealed that high maize yields were maintained under mild drought combined with medium-to-high N via distinct pathways. Water-N synergy enhanced leaf antioxidant capacity, with N increasing peroxidase (POD) activity and reducing malondialdehyde, thereby mitigating oxidative stress, delaying chlorophyll and photosynthesis (An) decline, and sustaining assimilates such as soluble sugars (SS) and free amino acids (FAA). In grains, mild drought raised SS by 3.0% but reduced sucrose synthase (SuSy) and ADP-glucose pyrophosphorylase (AGPase) activities by 13.3% and 20.7%, respectively, lowering starch (ST) by 9.7%. Severe drought drastically reduced assimilate input, enzyme activities, and ST (-37.3%). N metabolism was also impaired, with lower FAA and protein (PRO) linked to lower glutamine synthetase and glutamate synthase activities. Hormonal balance was critical: zeatin + zeatin riboside (Z + ZR) and indole-3-acetic acid (IAA) promoted grain weight and correlated positively with carbon-metabolizing enzymes, while severe drought increased gibberellin A3 (GA3). In a multivariate analysis, SuSy, AGPase, IAA, Z + ZR, and GA3 explained 82.32% of ST variation, and the interaction between N metabolism enzymes and hormonal ratios explained 92.0% of PRO variation. Carbohydrate metabolism, N metabolism, and hormone balance accounted for 44%, 19%, and 7% of the variation in 100-grain weight, respectively, while their interactions explained an additional 19%. This study establishes a physiological network of water-N synergy, highlighting antioxidant enhancement and hormone-metabolism interactions, that provides a theoretical basis for precision water-N management in maize production.
Digitalization and decarbonization are reshaping urban production, yet the relationship between factor-level digitalization and cities' carbon total factor productivity (CTFP) remains underexplored, particularly concerning its mechanisms, boundary conditions, and spatial reach. This study develops a Digitalization Index of Urban Elements (DIUE), encompassing labor, capital, and energy, to examine its association with CTFP in 213 Chinese cities from 2011 to 2023. CTFP is measured using an undesirable-output slacks-based measure, and the empirical analysis employs a two-step system GMM with Windmeijer correction, mediation analysis, spatial-lag models, and dynamic panel threshold tests. Robustness checks utilize an alternative productivity index and a difference-in-differences design based on early smart-city pilots. Three key findings emerge. First, factor-level digitalization is positively associated with urban CTFP; a one-standard-deviation increase in DIUE corresponds to a 1.5-1.7% increase in CTFP, which accumulates to approximately 4% in the long run. Second, this relationship is primarily mediated by green innovation, accounting for approximately 47% of the mediated effect, while industrial upgrading and agglomeration provide additional support, accounting for about 24% and 6%, respectively. Third, the benefits of digitalization exhibit both spatial spillovers and conditional effects: the indirect spillover effect constitutes roughly one-third of the direct effect, and positive gains are more pronounced in contexts with lower labor and capital misallocation and stronger local low-carbon commitment. By integrating a transparent and replicable measure of factor digitalization with evidence on its underlying mechanisms, spatial spillovers, and activation thresholds, this study clarifies the conditions under which digitalization can be effectively translated into enhanced carbon productivity. The policy implication is that cities should complement digital investment with measures to reduce factor misallocation, strengthen low-carbon commitment, and foster innovation.
Mangrove forests are among the most carbon-dense coastal ecosystems, yet ongoing conversion to agriculture and oil palm plantations significantly reduces landscape-scale carbon storage and climate mitigation potential. This study quantified aboveground biomass (AGB) and carbon stocks across six land-use types within Karang Gading and Langkat Timur Laut Wildlife Reserve, North Sumatra, Indonesia, covering 928.42 ha. High-resolution unmanned aerial vehicle (UAV)–derived canopy height models were integrated with field-calibrated allometric equations, using basal area–weighted Lorey’s height to improve biomass estimation in structurally heterogeneous stands. Bias correction was applied to log-transformed models to minimize systematic error. Mean AGB ranged from 0.97 Mg ha⁻¹ in oil palm plantations to 278.54 Mg ha⁻¹ in natural mangroves. Corresponding aboveground carbon (AGC) stocks ranged from 0.46 to 130.92 Mg C ha⁻¹. Natural mangroves (92.82 ha) stored 12,151.99 Mg C (44,597.11 Mg CO₂e), while community forests (98 ha) stored 10,541.86 Mg C. In contrast, mixed agriculture and oil palm systems together contributed less than 2% of total landscape-level aboveground carbon. Under a conservative avoided deforestation scenario, total CO₂-equivalent stocks correspond to an indicative economic value of approximately USD 0.63–6.35 million at voluntary carbon market prices of USD 5–50 Mg CO₂e⁻¹. Although these values represent biophysical carbon stocks rather than verified emission reductions, the integration of UAV-derived structural metrics with field validation provides a robust and scalable framework for spatially explicit carbon accounting. These findings strengthen the empirical basis for evaluating land-use impacts on coastal carbon balance and support mitigation-oriented conservation and restoration planning in tropical mangrove landscapes.
The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a critical region for coordinated low-carbon development in China, yet the structure and drivers of intercity carbon-emission spillovers remain poorly understood, especially under alternative development pathways. In addition, the carbon consequences of land-use change have received little attention. To fill these gaps, this study develops a coupled multi-scenario analytical framework to examine the spillover structure and drivers of land-use carbon emissions (LUCE), using observational data from 2000, 2010, and 2020, together with 2030 simulations under natural development (NDS), economic development (EDS), and ecological protection (EPS) scenarios. The results show that the northeastern and southwestern GBA function as relatively stable carbon sinks, whereas the central corridor exhibits persistent emission growth. Intercity LUCE disparities are largest under EDS and shrink markedly under EPS. The LUCE network is highly connected, multilevel, and transmission-efficient, indicating a robust yet centralized spillover system. Shenzhen remains the dominant hub, and the increasing number of intermediary cities further strengthens intercity carbon flows. Driver analysis reveals that historical network linkages are significantly associated with differences in per capita GDP and geographic proximity. Under the 2030 scenarios, however, industrial structure upgrading becomes increasingly influential, highlighting a scenario-dependent shift in the key drivers of intercity spillovers. Overall, this study offers a transferable multi-scenario framework for analyzing regional LUCE spillovers and provides management-relevant evidence for coordinated mitigation, cross-jurisdictional carbon governance, and policy design in the GBA.
Urbanization serves as an engine for economic development, yet the risk of "carbon lock-in" caused by infrastructure and consumption patterns threatens long-term sustainability. Studying the synergistic effects and regional differences between China's new urbanization (NU) and zero-carbon strategies (ZCS) is a crucial economic and social issue for China to participate in global climate governance and achieve urban modernization. This study systematically analyzed the evolution law and regional differences of the coupling coordination degree (CCD) between NU and TFCEE by employing the entropy-weighted TOPSIS method, coupling coordination model, Dagum-Gini coefficient, and convergence model. The findings are as follows: (1) The coupling coordination level (CCL) between NU and Total-factor carbon emission efficiency (TFCEE) has been increasing year by year, with the eastern region taking the lead in forming intermediate coordination and maintaining a leading position; (2) In terms of intra-regional differences, the CCL in the eastern, central, and northeastern regions exhibit a fluctuating decline, whereas those in the western region demonstrate a fluctuating increase. In terms of inter-regional differences, the disparity between the eastern and western regions (east-west) stands out as the most prominent. Here, inter-regional variations play a primary role in accounting for the overall inequalities; (3) In the σ-convergence and β-convergence analyses, the spatial imbalance in the western region is more pronounced, indicating that although the western region has shown a positive catch-up effect, the absolute gap with the eastern region has not yet narrowed due to differences in initial conditions. In general, the CCD between NU and TFCEE is gradually optimizing, but the spatial imbalance remains prominent, especially in the western region, which urgently needs to be improved through targeted policy guidance.
Achieving carbon peak and carbon neutrality requires not only reducing emissions but also managing the macroeconomic side effects of the energy transition. This study examines employment reallocation as a carbon transition management problem rather than as a conventional labor market performance issue. We develop an integrated multi-regional input-output (MRIO) and multi-objective optimization model to simulate how China's carbon peak constrained energy transition reshapes formal labor demand across 42 sectors and 31 provinces. The novelty of this study lies in linking a theoretical mechanism of capital biased energy transition with a detailed interregional production network, thereby identifying where the social costs of decarbonization are likely to concentrate. Our results show that although the transition increases aggregate employment, it generates a clear "winner takes all" pattern. Employment gains are captured mainly by economically developed coastal regions and high value added service and power related sectors, while less developed inland and resource dependent regions face severe losses. Shanxi, a typical coal dependent province, could lose nearly 10% of formal employment opportunities, and job growth in renewables is insufficient to fully offset losses in traditional fossil fuel and power industries. These findings provide policy relevant evidence for carbon management by showing that carbon peak pathways must be evaluated not only by emission outcomes but also by their spatial and sectoral employment risks.