Search Results (134)

The middle reaches of the Yangtze River are important bases for high-tech, advanced manufacturing, and modern service industries in China, as well as a demonstration area for the coordination of economic and ecological construction, which plays an important role in the ecosystem carbon cycle. With the steady progress of social and economic development and urbanization, the supply capacity of ecosystem services has sharply decreased, and the carbon cycle mechanism has changed, further reducing the sustainability of regional ecosystem services. In this study, carbon storage in the middle reaches of the Yangtze River was estimated from 2000 to 2020 based on the InVEST model, and the temporal and spatial evolution characteristics of carbon storage in the middle reaches of the Yangtze River were summarized using the coefficient of variation and spatial autocorrelation. The coupled InVEST-PLUS model was used to simulate the carbon storage characteristics of the middle reaches of the Yangtze River under natural development, ecological protection, cultivated land protection, and urban development scenarios in 2035. The results show the following: (1) The main land-use types in the middle reaches of the Yangtze River are cultivated and forest land, and the land-use types in the study area show the characteristics of “two increases and four decreases” in the past 20 years. (2) The carbon storage level in the middle reaches of the Yangtze River has decreased by 83.65 × 10⁶ t in the past 20 years (approximately 1.16%). The coefficient of variation showed that the carbon storage level in the middle reaches of the Yangtze River was high, with the fluctuating area accounting for 8.79% of the total area. The results of local spatial autocorrelation show that the high-value areas of carbon storage are mainly distributed in the west and southeast of the study area, and the low-value areas are mainly distributed in the middle of the study area, exhibiting characteristics of “high values surrounding low values” in space. (3) The simulation results of carbon storage in the middle reaches of the Yangtze River in 2035 showed that the ecological protection scenario was better than the other scenarios in terms of the mean level, functional performance, and patch presentation. Full article

This paper develops a model to calculate carbon emissions during the construction period of dredging projects. Carbon emission quotas for various types of dredgers and auxiliary vessels in different construction conditions and geotechnical soil types during the dredging project’s construction period are established, as well as the power consumption quota for management activities. Taking the construction of the main project of the cross-river channel from Shenzhen to Zhongshan (S09)’s foundation trench excavation and channel dredging, the Thilafushi Island reclamation project in Malé, and the second phase of the southern section of the Guangzhou Port Area channel maintenance project (2022–2023) as case studies, the validity of the quotas is verified. During the construction period, under the same dredging soil quality and the same working condition level, the carbon emissions of different types of dredgers are different. Conversely, under different dredging soil qualities and different working condition levels, the carbon emissions for the same dredger or auxiliary vessel are different. The carbon emissions of each dredger or auxiliary vessel increase with the increase in the ship’s specifications. The carbon emissions of dredging projects are huge, with direct carbon emissions accounting for 97%, and indirect carbon emissions from equipment deployment and management activities accounting for 3%, among which the carbon emissions from electricity consumption in management activities account for only 0.3%. Full article

Delineating soil management zones in cocoa cultivation areas can help optimize production and minimize ecological and environmental risks. This research assessed the spatial distribution of heavy metal concentration and soil fertility indicators in Cross River State, Nigeria, to delineate soil management zones (MZs). A total of n = 63 georeferenced, composite soil samples were collected at the 0–30 cm depth increment, air-dried, and subjected to physicochemical analysis. The soil data were subjected to principal component analysis (PCA), and the selected principal components (PCs) were used for fuzzy c-means clustering analysis to delineate the MZs. The result indicated that soil pH varied from 4.8 (strongly acidic) to 6.3 (slightly acidic), with high average organic carbon contents. The degree of contamination was low, while the ecological risk indicator (RI) of the environment under cocoa cultivation ranged from low risk (RI = 18.24) to moderate risk (RI = 287.15), with moderate risk areas mostly found in patches around the central and upper regions. Higher pH was associated with increased levels of exchangeable Ca, Mg, and K, and TN and OC. Strong spatial dependence was observed for silt, pH, OC, Mg, Zn, Cu, Pb, Cd, Cr, and DC. The result showed the first six principal components (PCs) with eigenvalues >1 accounting for 83.33% of the cumulative variance, and three MZs were derived via the selected six PCs using fuzzy c-means clustering analysis. The results of this study further indicated that MZ3 had the highest pH (6.06), TN (0.24%), OC (2.79%), exchangeable Ca (10.62 cmol/kg), Mg (4.01 cmol/kg), and K (0.12 cmol/kg). These were significantly (p < 0.05) higher than those observed in MZ2 and MZ1, and they represent the most fertile parts of the study area. Furthermore, 40.6% of the study area had marginal soil (i.e., soil under MZ2). Full article

This study, taking Anhui Province as a case study, systematically evaluated the spatiotemporal differentiation characteristics of six ecosystem services (biodiversity maintenance, water yield, carbon fixation, vegetation net primary productivity (NPP), soil retention, and crop production) from 2000 to 2020 through the integration of multi-stakeholder decision-making preferences and the Marxan model. Four conservation scenarios (ecological security priority, social benefit orientation, minimum cost constraint, and balance synergy) were established to explore the spatial optimization pathways of ecological protection zones under differentiated policy objectives. The findings indicated that: (1) The ecosystem services in Anhui Province exhibited a “low north and high south” spatial gradient, with significant synergies observed in natural ecosystem services in the southern Anhui mountainous areas, while the northern Anhui agricultural areas were subjected to significant trade-offs due to intensive development. (2) High service provision in the southern Anhui mountainous areas was maintained by topographic barriers and forest protection policies (significant NPP improvement zones accounted for 50.125%), whereas soil–water services degradation in the northern Anhui plains was caused by agricultural intensification and groundwater overexploitation (slight soil retention degradation covered 24.505%, and water yield degradation areas reached 29.766%). Urbanization demonstrated a double-edged sword effect—the expansion of the Hefei metropolitan area triggered suburban biodiversity degradation (significant degradation patches occupied 0.0758%), while ecological restoration projects promoted mountain NPP growth, highlighting the necessity of synergizing natural recovery and artificial interventions. (3) Multi-scenario planning revealed that the spatial congruence between the ecological security priority scenario and traditional ecological protection redlines reached 46.57%, whereas the social benefit scenario achieved only 12.13%, exposing the inadequate responsiveness of the current conservation framework to service demands in densely populated areas. This research validated the technical superiority of multi-objective systematic planning in reconciling ecological protection and development conflicts, providing scientific support for optimizing ecological security patterns in the Yangtze River Delta region. Full article

Vegetation carbon sequestration (CS) is critical for mitigating climate change in urban agglomerations, yet its driving mechanisms remain poorly understood in rapidly urbanizing regions. This study introduces an integrated attribution and influence analysis framework, GWR-RF-SEM, to quantitatively assess the driving forces, mechanisms, and pathways of CS using multi-source remote sensing data at the county scale within the Yangtze River Delta Urban Agglomeration (YRDUA), China, from 2001 to 2020. Our results reveal an overall increase in CS across 70.14% districts in the YRDUA, with municipal districts exhibiting significantly lower CS compared to the outside districts. Photosynthesis and human activities emerged as the dominant drivers, collectively accounting for 73.1% of CS variation, significantly surpassing the influence of climate factors. Although most factors influenced urban vegetation CS either directly or indirectly, photosynthesis, afforestation, and urban green space structure were identified as the primary direct drivers of CS enhancement in both districts. Notably, we found significant spatial heterogeneity in CS drivers between municipal districts and the outside districts, highlighting the need for targeted strategies to enhance CS efficiency. These findings advance our understanding of urban vegetation CS mechanisms, providing essential support for the enhancement of nature-based solutions depending on ecosystem services under urbanization and climate change. Full article

The Huaihe River Basin stands as a vital grain-producing base in China. Predicting the dynamic evolution of its carbon storage (CS) is of great theoretical value and practical significance for maintaining regional ecological security, guaranteeing food production capacity, and coping with climate change. This study established a multi-dimensional analysis framework of “scenario simulation–reservoir assessment–value quantification”. Using a sample of 195 cities, the PLUS-InVEST-GIS method was combined to explore the overall CS, spatial differentiation, and value changes in future scenarios. The results indicate that the following: (1) From 2000 to 2020, CS kept on declining, with cultivated land and forest land being the dominant carbon pools, accounting for over 86% of the total CS. (2) From a “city–grid–raster” perspective, the spatial pattern of high-value hot spots of CS remained stable, and the overall pattern remained unchanged under multi-scenario simulation, yet the overall carbon sink center of gravity shifted to the southwest. (3) The top five driving factors are elevation, slope, NDVI, GDP per capita, and population density, accounting for 77.2% of the total driving force. (4) The carbon sequestration capacity at the county scale continued to weaken, and the overall capacity presented the following order: 2035 Farmland protection scenario (FPS) > 2035 Natural development scenario (NDS) > 2035 Urban development scenario (UDS). The resulting carbon economic losses were USD 2.28 × 10⁸, 4.57 × 10⁸, and 6.90 × 10⁸, respectively. The research results will provide scientific land use decision-making support for the realization of the “double-carbon” goals in the Huaihe River grain-producing area. 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

Submicron soot particles (with an aerodynamic diameter of less than 1.0 μm) are found to be one of the major factors resulting in global warming and health burdens. However, research on the biomonitoring of submicron soot particles and their associated sources using tree leaves has not been comprehensively conducted. This study investigated the seasonal trends of submicron soot particles on the leaves of seven tree types collected from four individual seasons across two years in Nanjing, in the Yangtze River Delta region of China, and performed source apportionment using stable carbon isotope analysis. Significant seasonal variations in submicron soot particles were observed on tree leaves of seven tree types, with average levels of 0.3 to 0.5 mg m⁻² during summer and 0.5 to 1.3 mg m⁻² during winter. The levels of submicron soot particles varied significantly across various tree types. In contrast, the levels of δ¹³C were not found to change significantly across different types. The levels of δ¹³C ranged from −26.3‰ to −20.9‰ in winter and from −24.0‰ to −18.1‰ in summer, with fossil fuels accounting for 56% and 78% of submicron soot in winter and summer on average, respectively. These results demonstrate that tree leaves can serve as a low-cost and effective biomonitoring tool for assessing the source status of submicron soot. Full article

Land use and land cover change (LULCC) is a key driver of carbon storage changes, especially in complex coastal ecosystems such as the Yellow River Delta (YRD), which is jointly influenced by climate change and resource development. The compounded effects of sea-level rise (SLR) and land subsidence (LS) are particularly prominent. This study is the first to integrate the dual impacts of SLR and LS into a unified framework, using three climate scenarios (SSP1–26, SSP2–45, SSP5–85) provided in the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6), along with LS monitoring data, to comprehensively assess future inundation risks. Building on this, and taking into account land use and ecological protection policies in the YRD, three strategic scenarios—Ecological Protection Scenario (EPS), Natural Development Scenario (NDS), and Economic Growth Scenario (EGS)—are established. The PLUS and InVEST models are used to jointly simulate LULCC and carbon storage changes across these scenarios. Unlike previous studies focusing on single driving factors, this research innovatively develops a dynamic simulation system for LULCC and carbon storage driven by the SLR-LS compound effects, providing scientific guidance for land space development and coastal zone planning in vulnerable coastal areas, while enhancing carbon sink potential. The results of the study show the following: (1) Over the past 30 years, the land use pattern of the YRD has generally extended toward the sea, with land use transitions mainly from grasslands (the largest reduction: 1096.20 km²), wetlands, reservoirs and ponds, and paddy fields to drylands, culture areas, construction lands, salt pans, and tidal flats. (2) Carbon storage in the YRD exhibits significant spatial heterogeneity. Low-carbon storage areas are primarily concentrated in the coastal regions, while high-carbon storage areas are mainly found in grasslands, paddy fields, and woodlands. LULCC, especially the conversion of high carbon storage ecosystems to low carbon storage uses, has resulted in an overall net regional carbon loss of 2.22 × 10⁶ t since 1990. (3) The risk of seawater inundation in the YRD is closely related to LS, particularly under low sea-level scenarios, with LS playing a dominant role in exacerbating this risk. Under the EGS, the region is projected to face severe seawater inundation and carbon storage losses by 2030 and 2060. Full article

Optimizing the joint drawdown operation of mega reservoirs presents a significant opportunity to enhance the comprehensive benefits among hydropower output, water release, and carbon emission reduction. However, achieving the complementary drawdown operation of mega reservoirs while considering reservoir carbon emissions poses a notable challenge. In this context, this study introduces an innovative multi-objective optimization framework tailored for the joint drawdown operation of mega reservoirs. Firstly, a multi-objective optimization model, leveraging an intelligent evolutionary algorithm, is developed to minimize reservoir carbon emissions (Objective 1), maximize hydropower output (Objective 2), and maximize water release (Objective 3). Subsequently, a multi-criteria decision-making approach to search for the optimal scheme is employed. The proposed framework is applied to seven mega reservoirs within the Hanjiang River basin, China. The results show that the framework is effective in promoting comprehensive benefits, improving hydropower production by 8.3%, reservoir carbon emission reduction by 5.6%, and water release by 6.2% from the optimal solution under wet scenarios, compared to standard operation policies. This study not only provides a fresh perspective on the multi-objective drawdown operation of mega reservoirs but also offers valuable support to stakeholders and decision-makers in formulating viable strategic recommendations that take potential carbon emissions and advantages into account. Full article

As an important engine of China’s development, the Yangtze River Economic Belt faces the dual contradiction of economic growth and ecological protection. Addressing the insufficient analysis of the spatiotemporal evolution and driving mechanisms of city-level carbon footprints, this study delves into the concept of carbon footprint from the perspective of ecological footprint theory and carbon cycle dynamics. Using ODIAC and NPP data, it systematically evaluates carbon footprints across 130 cities and examines their spatiotemporal evolution and driving factors using kernel density estimation and the Kaya-LMDI model. The results show (1) a significant growth trend in carbon footprint, with rapid expansion from 2000 to 2012, followed by fluctuating growth from 2012 to 2022; (2) a west-to-east “low–high” spatial pattern, where disparities have narrowed but absolute gaps continue to widen, leading to polarization; and (3) economic growth and urban expansion as the primary drivers of carbon footprint growth, while ecological land use pressure and carbon sequestration capacity played a major role in mitigation, with the impact of carbon sequestration foundations remaining limited. This study conducts precise regional carbon sink accounting and offers a new perspective on the quantitative analysis of carbon footprint drivers. The findings provide insights for low-carbon governance and sustainable urban development in the Yangtze River Economic Belt. Full article

Microorganisms have a profound impact on the stability and ecological health of aquatic environments. Fungi, as important components of river ecosystems, play critical roles as decomposers and symbionts. A comprehensive understanding of the mechanisms underlying fungal community assembly is essential for the effective conservation and management of river ecosystems. However, the distribution patterns and assembly process of fungal communities along elevation gradients in river sediments remain poorly understood. In this study, ITS amplicon sequencing, a neutral community model, and a null model were employed to analyze the distribution patterns and assembly processes of fungal communities in sediments along the altitudinal gradient of the Yellow River. The results indicated that Ascomycota (47.79%) and Basidiomycota (15.68%) were identified as the dominant phyla in the sediments, collectively accounting for 63.47% of the total relative abundance of the community. In the three different altitudinal gradients, the fungal community diversity (Shannon) showed a gradually decreasing trend with increasing altitude. The co-line networks of fungal communities exhibited positive interactions and had more complex and compact networks in the sediments of the Tibetan Plateau area (YRA). Environmental factors in the sediments played an important role in shaping the structure of fungal communities, with lead (Pb), total nitrogen (TN), silt, and total organic carbon (TOC) being the main factors driving changes in community structure, contributing 15.5%, 12.3%, 10.7%, and 10.2%, respectively. In the community assembly process, deterministic processes were found to dominate, with homogenizing selection contributing the most (69.66%). These research results help us understand the distribution patterns of fungal communities along altitudinal gradients and the mechanisms of community assembly, and also provide a scientific basis for biodiversity conservation and the rational use of biological resources. Full article

Taking six provinces and one city in the middle and lower reaches of the Yangtze River as the main research object, this study investigated the carbon footprint of agricultural production in the region and promoted the development of agricultural carbon reduction. This study used the internationally mainstream IPCC emission factor method to calculate the carbon footprint of agricultural production, and selected indicators such as rural population, crop planting area, rural per capita GDP, and urbanization rate to analyze the influencing factors of agricultural carbon footprint in various provinces in the middle and lower reaches of the Yangtze River based on an extensible STIRPAT model. Due to differences in agricultural production conditions, the carbon footprint per unit area and unit yield vary among provinces and cities in the middle and lower reaches of the Yangtze River. From the 15 year average, the carbon footprint per unit area is synchronized with the carbon footprint per unit yield, with Zhejiang Province having the highest (9830.48 kg (CO₂ eq)/hm², 0.65 kg (CO₂ eq)/kg), Hubei Province in the middle (5017.90 kg (CO₂ eq)/hm², 0.54 kg (CO₂ eq)/kg), and Jiangxi Province having the lowest (3446.181 kg (CO₂ eq)/hm², 0.46 kg (CO₂ eq)/kg). From the perspective of emission structure, the carbon footprint generated by agricultural resource inputs accounts for the largest proportion, with fertilizer and fuel use being the main contributors to emissions. In the analysis of influencing factors, the indicators that mainly promote the carbon footprint of agricultural production include the following: rural population (R), ratio of agricultural value added to GDP(Z), total sown area of crops (B), level of agricultural technology (total power of agricultural machinery) (J), and degree of agricultural mechanization (N). The indicators that mainly inhibit the carbon footprint of agricultural production include the per capita disposable income of rural residents (P), rural GDP per capita (G), and urbanization rate (C). Other indicators have a relatively weak impact on carbon footprint. Overall, optimizing agricultural resource input, improving mechanized productivity, and reasonably controlling fertilizers are important ways of reducing carbon emissions from agricultural production. In the middle and lower reaches of the Yangtze River, it is still necessary to formulate emission reduction measures tailored to different ecological environment characteristics to achieve sustainable agricultural development. Full article

Identifying the driving effects and differentiated characteristics of transportation carbon emissions is crucial for developing targeted and differentiated emission reduction strategies and providing a scientific basis for the Yangtze River Economic Belt. This study adopted a “top-down” approach to account for the transportation carbon emissions of the Yangtze River Economic Belt from 2000 to 2019 and constructed LMDI models and quantile regression models to estimate the driving effects and heterogeneity of influencing factors. The research results indicate the following: (1) The level of economic development is a key driving factor for transportation carbon emissions in the Yangtze River Economic Belt, with a cumulative effect of 160%. Upon inspection, the relationship between economic and transportation carbon emissions conforms to the environmental Kuznets curve. When the per capita transportation production value reaches CNY 7500, there is a “turning point” in transportation carbon emissions. (2) The population size has a driving effect on transportation carbon emissions, but as carbon emissions continue to increase, their marginal effects gradually diminish. (3) The energy structure and transportation structure have a significant inhibitory effect on transportation carbon emissions. The driving effect of the energy structure shows an “N” shape with quantile changes, while the transportation structure gradually converges. (4) Both energy intensity and transportation intensity show inhibitory effects, indicating that innovative energy substitution, optimization of transportation structure, and improvement of organizational efficiency are key ways to achieve carbon reduction in transportation. It is suggested that the Yangtze River Economic Belt should develop differentiated emission reduction paths in different regions, effectively balance economic development and carbon emission control, and promote the green and low-carbon transformation of the transportation system. Full article

Soil organic carbon (SOC) and soil inorganic carbon (SIC) are key components of soil carbon pools in arid ecosystems, playing a crucial role in regional carbon cycling and climate change mitigation. However, the interactions between these two forms of carbon in arid alpine ecosystems remain underexplored. This study was conducted in the Heihe River Basin (HRB) in the northeastern Qinghai–Tibet Plateau, focusing on the distribution and dynamics of SOC and SIC in deep soil layers. Using data from 329 samples collected from 49 soil profiles extending to the bedrock, combined with path analysis, we explored the inter-relationships between SOC and SIC and quantified the influence of environmental factors. The results showed that (1) SOC exhibited a unimodal distribution with elevation, peaking at 3300–3600 m, while SIC continuously decreased with elevation, with reduction rates ranging from −0.39% to −31.18%; (2) SOC and SIC were significantly positively correlated (r = 0.55, p < 0.01), with SOC decreasing with depth and SIC showing an inflection point at 50 cm depth; (3) SOC was primarily driven by nutrient factors, such as total nitrogen (TN), with a path coefficient of 0.988, while SIC was influenced by abiotic factors, including potential evapotranspiration (PET), with a coefficient of −1.987; (4) SOC density accounted for 81.62% of the total soil carbon pool, playing a dominant role in carbon storage, whereas SIC density exhibited dynamic changes, particularly at depths of 110–150 cm. These findings advance our understanding of deep soil carbon dynamics in arid alpine ecosystems and provide critical data for improving carbon management strategies in similar regions. Full article