With the deepening implementation of the Global Stocktake mechanism under the Paris Agreement, independent verification and high-efficiency quantification of greenhouse gas emission inventories have emerged as critical scientific and operational requirements in international climate governance. Although the first-generation shortwave infrared hyperspectral carbon monitoring satellites represented by the GOSAT series, OCO series, and TanSat have validated the technical feasibility of high-precision space-based detection of XCO₂ and XCH₄, they are constrained by observation regimes relying on discrete point sampling or narrow-swath push-broom modes. Consequently, these missions exhibit significant limitations in spatiotemporal coverage efficiency, point source identification capabilities, and the separation of anthropogenic sources under complex background conditions. To address these bottlenecks, next-generation carbon monitoring missions exemplified by GOSAT-GW from Japan, CO2M from Europe, GeoCarb from the US, and TanSat-2 from China have comprehensively transitioned their payload architectures to wide-swath grating imaging modes. Furthermore, these missions have transcended the limitations of single polar orbits by adopting diversified orbital configurations, including Low Earth Orbit constellations, Medium Earth Orbit elliptical frozen orbits, and Geostationary Earth Orbit. By establishing systematic observation schemes integrating ultra-wide swath coverage, high-frequency revisit rates, and multi-species synergistic detection, these missions utilize aerosol synergy to enhance greenhouse gas retrieval accuracy. Additionally, they employ nitrogen dioxide as a tracer for anthropogenic emissions and Solar-Induced Chlorophyll Fluorescence to constrain natural carbon sinks, thereby effectively achieving precise separation of anthropogenic signals and detailed characterization of emission plumes. This technological leap will comprehensively enhance satellite-based capabilities for verifying anthropogenic emission inventories, providing consistent and traceable space-based observational support for the global verification of emission inventories.

As one of the most important greenhouse gases, carbon dioxide(CO₂) plays a critical role in regulating the stability of the global climate system and maintaining the balance of the terrestrial carbon cycle. Warming experiments, as a key approach to simulating climate warming scenarios, can reveal the influence mechanisms of temperature rise on key ecological processes such as soil respiration, carbon fixation and greenhouse gas emissions under controllable conditions.However, a comprehensive and systematic review and summary of the relevant research on the effects of warming experiments on CO₂ emissions is still lacking. Based on the Web of Science(WOS) database, English literatures with themes related to “Warming Experiment” and “CO₂” during the period from January 1, 2014 to December 31, 2024 were collected as the data sources. Knowledge graph analysis was carried out with the aid of Cite Space and VOS viewer software to construct the co-occurrence network of keywords, authors and research institutions, and systematically sort out the research status, hot topics and development trends in this field. The results indicate that, 1) since 2017, studies on warming experiments and CO₂ emissions have become increasingly active, with a steadily growing level of academic attention. 2) China, the United States, and Germany occupy dominant positions in this field, among which the Chinese Academy of Sciences and the University of Chinese Academy of Sciences rank highest in the number of published papers, forming a high-yield research cluster centered in China.3) Scholars such as Luo Yiqi, Josep Peñuelas, Zhu Biao and Yang Yusheng have made outstanding contributions and established several close linked internationalacademic cooperation networks.4) Research topics primarily focus on greenhouse gas emissions, temperature sensitivity, soil respiration, and carbon cycle, exhibiting a clear trend toward multi-scale, multi-gas, and multi-regional coordinated development. In the future, research should further deepen the exploration of underlying mechanisms, strengthen comparative studies across different climatic zones and ecosystem types, and elucidate the spatial heterogeneity and ecological feedback mechanisms of carbon flux changes driven by warming. At the same time, collaborative observations of multiple greenhouse gases and in-depth analysis of carbon-nitrogen coupling processes should be further promoted.

Fractional Vegetation Cover(FVC) is an important indicator reflecting the status of an ecosystem. To clarify current research progress and hot topics in FVC studies, we conducted bibliometric and visualization analysis on relevant studies. Results indicate that the number of academic works has grown significantly in recent years both in China and abroad. China has produced the highest volume of research, while studies from the United States and other western countries demonstrate greater academic influence. Key research areas include vegetation modeling, utilization of diverse remote sensing data sources, FVC status in diverse ecosystems, vegetation responses to climate change, and indicators for FVC estimation. Thematic evolution reveals that early studies primarily focused on fundamental research in ecology and meteorology, as well as mechanisms of climate-vegetation interactions. In recent years, research hotspots have shifted toward FVC model coupling and validation, climate change and ecological restoration, and improvements to FVC algorithms. Comparing themes in Chinese and foreign-language journal publications reveals that foreign journals predominantly focus on global-scale remote sensing monitoring and optimization of FVC remote sensing inversion methods. Chinese language academic works majorly emphasize temporal and spatial patterns of FVC within China and their underlying response mechanisms, frequently incorporating meteorological indicators, topographic types, and land-use changes into analyses. This study analyzes the development of FVC research, summarizes the limitations of existing research, and looks forward to future research directions, aiming to provide a reference for future ecological environment restoration, climate change response, urban planning, and sustainable development.

To elucidate the effects of chemical fertilizer reduction combined with biochar on soil particulate organic carbon(POC) and its influencing factors in Jasminum sambac gardens, a field experiment was conducted in Fuzhou.Four treatments were established: conventional fertilization, biochar application, chemical fertilizer reduction, and a combination of chemical fertilizer reduction and biochar application.Soil POC, plant characteristics, and fungal communities were analyzed.The results showed that, 1) chemical fertilizer reduction combined with biochar significantly increased soil POC content to 11.60 g·kg^-1, which was significantly higher than biochar alone(6.68 g·kg^-1), fertilizer reduction(5.66 g·kg^-1), and the control(4.16 g·kg^-1).The contribution of POC to total carbon reached 51.04%.Furthermore, the characteristic peaks of polysaccharide carbon functional groups in POC were significantly enhanced.2) Under this combined treatment, the carbon and nitrogen contents of plant roots increased significantly, and principal component analysis indicated that the chemical structure of POC was most similar to that of the roots.3) The fungal community structure was similar across treatments, but the relative abundance of Fusarium significantly decreased under the combined treatment(P<0.05).Spearman correlation analysis indicated that POC was significantly positively correlated with Aspergillus and Rhodotorula(P<0.05), but negatively correlated with Acidomyces and facultative saprotrophs(P<0.05).In conclusion, chemical fertilizer reduction combined with biochar enhances soil carbon sequestration and improves the microbial environment, making it a suitable management mode for sustainable jasmine cultivation.

The invasive species Spartina alterniflora is widely distributed in China's coastal wetlands. In recent years, large-scale control efforts have significantly influenced carbon cycling processes in these ecosystems. To investigate the effects of S. alterniflora management and post-control regrowth on the soil organic carbon(SOC) pool, this study compared two management approaches-deep tilling and rotary tilling-and evaluated their effects on soil labile organic carbon(LOC) fractions and extracellular enzyme activities. Under deep tilling, DOC and MBC contents as well as BG, CBH, and PEO activities in non-regrown bare flats significantly decreased, whereas regrown S. alterniflora significantly increased DOC and MBC contents and CBH and PEO activities. Under rotary tilling, DOC, MBC, and LOC contents and the activities of BG, CBH, PHO, and PEO in non-regrown bare flats significantly decreased, while regrowth significantly increased DOC, MBC, and LOC contents and PEO activity. Correlation analysis indicated that under deep tilling, LOC fractions and enzyme activities were mainly influenced by the Fe(Ⅲ)/Fe(Ⅱ) ratio, with SOC, DOC,and MBC jointly regulating enzyme activity. Under rotary tilling, LOC fractions and enzyme activities were influenced by both the Fe(Ⅲ)/Fe(Ⅱ) ratio and soil moisture, with enzyme activity primarily regulated by MBC. Overall, in both treatments, differences in root oxygen release and organic matter input between non-regrown bare flats and regrown stands of S. alterniflora altered LOC fractions and enzyme activities. However, differences in soil disturbance intensity between deep tilling and rotary tilling led to distinct responses in LOC fractions and enzyme activities. These findings suggest that non-regrown bare flats after control face a risk of weakened soil carbon pool function. Although post-control regrowth of S. alterniflora promotes LOC accumulation, the marked increase in extracellular enzyme activity may accelerate organic carbon mineralization, potentially reducing the long-term stability and accumulation of the soil carbon pool.

Soil microbial necromass is a major components of stable soil carbon(C) and nitrogen(N) pools, and their responses to climate warming vary across different ecosystem types. To elucidate the feedbacks of soil C and N to global warming in subtropical forests, this study was conducted in a mature Chinese fir(Cunninghamia lanceolata) forest, based on a long-term field soil warming platform with a temperature increase of 4 ℃. Two treatments—warming(W) and control(CT) were established to systematically investigate the effects of warming on soil microbial necromass carbon(MNC), microbial necromass nitrogen(MNN), and their accumulation coefficients(Nitrogen Accumulation Coefficient for Carbon, NAC; Nitrogen Accumulation Coefficient for Nitrogen, NAN). The results showed that warming significantly increased soil microbial biomass carbon(MBC) by 36.56%, while significantly decreasing soil moisture(30.25%) and free amino acid content(27.37%). The composition of microbial necromass also exhibited subtle changes: the proportions of fungal necromass C and N relative to total microbial necromass C and N decreased slightly, whereas the proportion of bacterial necromass N increased slightly. However, long-term warming did not significantly alter the total contents of soil MNC and MNN or the values of NAC and NAN, indicating that the microbial necromass maintained a dynamic equilibrium under warming conditions. Correlation analysis revealed that microbial biomass nitrogen(MBN) was significantly and positively correlated with MNC and MNN contents, and dissolved organic carbon(DOC) was also significantly positively correlated with NAC, suggesting that MBN and DOC are key regulators of microbial necromass accumulation. In conclusion, under long-term warming, soil microbial necromass pool in subtropical Chinese fir forests may maintain the dynamic equilibrium through microbial thermal adaptation or C-N coupling mechanisms. These findings provide important theoretical support for a deeper understanding of the regulatory mechanisms of carbon and nitrogen retention in subtropical forest soils and their feedback relationships with climate change.

Mineral-associated organic matter(MAOM) is a highly stable carbon pool in forest soils, and its decomposition mineralization response to soil moisture is critical for understanding the feedbacks of soil carbon sequestration under global change. To reveal the regulatory mechanisms of soil moisture conditions on MAOM mineralization under exogenous carbon input, an incubation experiment was conducted using MAOM from six typical forest ecosystems in China. Two moisture levels, 20%(W20) and 60%(W60) of the maximum water holding capacity, were applied with the addition of beech litter(Fagus sylvatica L.). Continuous measurements of respiration rate, cumulative respiration, and their effect sizes were performed, and their relationships with soil physicochemical properties and enzyme activities were analyzed. The results showed that, 1) MAOM mineralization exhibited of“rapid release in the early stage followed by a slower increase”. With the respiration peak in W20 lagging behind that in W60. 2) Low moisture significantly enhanced the respiration effect, with the cumulative respiration effect values(ER20) in W20 generally higher than those in W60(ER60). The interaction between moisture and incubation time was overall nonsignificant, indicating a relatively stable regulatory effect of moisture on MAOM mineralization over time. 3) Redundancy analysis showed that ER20 was positively correlated with soil carbon-to-nitrogen ratio and acid phosphatase activity, and ER60 was positively correlated with β-glucosidase and β-N-acetylglucosaminse activities, but was negatively limited by ammonium nitrogen and clay particle content. This study highlights the divergent mechanisms by which exogenous carbon drives MAOM mineralization under different moisture conditions, providing important insights into the stability and feedbacks of forest soil carbon pools in the context of global change.

As a key component of the detritus food chain, soil fauna can not only directly feed on and utilize nutrient elements such as nitrogen(N) in litter, but also effect N release during litter decomposition such as fragmentation or migration. However, the relevant understanding remains unclear. Therefore, we took subtropical Castanopsis carlesii plantations as the research object, used litterbags with different mesh sizes to control soil fauna access, and conducted a near-full-process in situ litter decomposition experiment to study the dynamic effects of soil fauna on N release during litter decomposition. The results showed that the mass residual rates of litters in mesh bags with 3 mm, 2 mm, and 0.025 mm pore sizes after 192 days of litter decomposition were 7.03%, 6.99%, and 42.16%. Soil fauna changed the overall upward trend of N concentration in litter, especially significantly causing a decrease in N concentration during the late decomposition stage(160~192 days). After 192 days of litter decomposition, the contribution rate of soil fauna to N release from C. carlesii litter was 64.09%. Except for the period of 80~93 days of decomposition, soil fauna significantly promoted N release from litter at other decomposition stages. Among them, macrofauna were dominant in the early(0~80 days) and late(160~192 days) decomposition stages, and promoted N release by 4.8 times and 5.6 times respectively. In the middle stage(80~160 days), the N release from litter was more dependent on the contribution of meso-microfauna, with a relative contribution rate of 238.48%. Redundancy analysis showed that the number of soil fauna groups, air temperature, and precipitation were the main factors affecting the contribution of soil fauna to N release from litter, and had a more obvious effect on the contribution of meso-microfauna. These results help to deeply understand the relationship between soil fauna and N release during the decomposition of litter in subtropical plantations, and have certain scientific value for comprehensively understanding N cycling and the functions of soil fauna.

The selection of suitable intercropping patterns of Cunninghamia lanceolata is crucial to improving soil degradation triggered by long-term monoculture of C. lanceolata.This study focused on three different intercropping patterns, namely C. lanceolata intercropped with Phoebe bournei,with Taxus wallichiana,and simultaneously intercropped with Phoebe bournei,and Taxus wallichiana.Meanwhile, the monoculture of C. lanceolata was used as the control to investigate the effects of different intercropping patterns on soil physicochemical properties and net nitrogen mineralization rates.The results showed that compared with the monoculture of C. lanceolata,C. lanceolata intercropped with P. bournei significantly decreased soil pH,while significantly increased soil total nitrogen and nitrate nitrogen content.After intercropping with T. wallichiana,soil total carbon, total nitrogen, carbon to nitrogen ratios, ammonium nitrogen, dissolved organic nitrogen, microbial biomass carbon and microbial biomass nitrogen decreased significantly, while soil nitrate nitrogen content increased significantly.After intercropping with P. bournei and T. wallichiana,soil pH and carbon to nitrogen ratios decreased significantly, and soil total nitrogen, ammonium nitrogen and dissolved organic nitrogen increased significantly.Soil net nitrogen mineralization rates varied from 0.301 to 0.581 mg·kg^-1·d^-1 under different intercropping patterns.The soil net nitrogen mineralization rate was significantly decreased by 47% in the intercropping pattern of C. lanceolata and T. wallichiana,and there was no significant difference in other intercropping patterns.Random forest analysis showed that soil microbial biomass carbon, microbial biomass nitrogen and total carbon were significant predictors of net nitrogen mineralization rates.Correlation analysis showed that soil microbial biomass carbon, microbial biomass nitrogen, ammonium nitrogen, total carbon, total nitrogen and carbon to nitrogen ratios significantly and positively affect the soil net nitrogen mineralization rate.The results showed that intercropping different tree species under C. lanceolata can affect the net nitrogen mineralization rate by altering soil properties.

Absortive root traits are critical indicators of root ecological functions and plant resource trade-off strategies, and their dynamics directly regulate soil nutrient cycling.In this study, seven broadleaved tree species in a subtropical common garden were examined to assess variations in absorptive root traits and nutrient acquisition strategies between the growing and non-growing seasons.The results demonstrated that, 1) with the exception of root diameter(RD) and root carbon concentration(RCC),traits including specific root length(SRL),specific root area(SRA),root tissue density(RTD),root exudation rate(RER),and root nitrogen concentration(RNC) were all significantly affected by season.Notably, RER and SRL exhibited the strongest seasonal sensitivity: the max: min ratio of RER was about 5.6 times higher in the non-growing season than in the growing season, while the interspecific coefficient of variation of SRL was 2.23 times higher. In contrast, the max: min ratio of RCC and the interspecific coefficient of variation of RNC were relatively low and showed little seasonal change, indicating that these traits are more conserved across species and seasons. 2) Principal component analysis showed that root nutrient economic strategies during the growing season conformed to the classical root economics spectrum, spanning a gradient from the “fast-strategy” pole(represented by SRL,RCC,and RNC) to the “slow-strategy” pole(represented by RTD). In the non-growing season, trait relationships were significantly reconfigured. Specifically, RTD shifted from non-significant to a significant positive correlation with SRL and a significant negative correlation with RER,reflecting coordinated root adaptation under stressful conditions. By examining trait plasticity and the root economics spectrum, this study clarifies how fine-root traits in subtropical trees are regulated by phenology, thereby providing a theoretical basis for understanding root dynamics and predicting their role in ecosystem carbon and nitrogen cycling.

This study investigated the responses of extracellular enzyme activities and their stoichiometric ratios to nitrogen(N) addition in rhizosphere and bulk soils of a subtropical Castanopsis carlesii natural forest.Based on a long-term simulated N deposition platform, the activities of β-glucosidase(βG),leucine aminopeptidase(LAP),β-N-acetylglucosaminidase(NAG), and acid phosphatase(AP) were measured during both growing and non-growing seasons.Enzyme stoichiometric ratios(C/NEEA,C/PEEA,N/PEEA),vector length and angle, and rhizosphere effects were calculated.Key findings include, 1) compared with the non-growing season, βG activities in rhizosphere and bulk soils increased significantly by 7.8 and 24.1 times respectively, during the growing season, whereas AP activities decreased by 41.0% and 40.1%(P<0.05).2) During the growing season, low-N addition increased rhizosphere soil βG activity by 6.2% and significantly increased C/PEEA and vector length, while enzyme vector angles decreased significantly in both rhizosphere and bulk soils(P<0.05).During the non-growing season, low-N addition decreased rhizosphere βG activity by 41.3% and significantly lowering C/PEEA,C/NEEA,and vector length. Under high-N addition, bulk soil AP activity declined by 44.9%, accompanied by significant decreases in C/PEEA and N/PEEA(P<0.05).3) During the non-growing season, high-N addition strengthened positive rhizosphere effects of βG,C/PEEA,N/PEEA,indicating enhanced carbon demand in rhizosphere microorganisms.Meanwhile, the strengthened negative rhizosphere effect on enzyme vector angle reflected aggravated phosphorus limitation in bulk soil microorganisms(P<0.05).4) Soil available phosphorus content was the most important factor explaining seasonal and nitrogen-induced variations in enzyme activities in both rhizosphere and bulk soils.Soil moisture and available nitrogen were also significant factors influencing soil enzyme activities.These results offer a scientific basis for nutrient management and sustainable protection of subtropical natural forests under the background of nitrogen deposition.

Fire disturbance has spillover effects on forest ecosystems, and the response mechanism of vegetation on the edge of burned areas is the key to assessing the resilience of ecosystems. Combining multi-source satellite remote sensing data to screen typical forest fire events in South China from 2000 to 2021, a double-layer buffer three-circle model was constructed to eliminate the impact of climate change on vegetation and quantify the spillover effect of fire interference on the forest vegetation index in South China. The results show that, the spillover effect of fire disturbance has significant spatial heterogeneity, with hotspot areas having lower elevation and sparser vegetation. The spillover effect of small-scale fires has negative effects and large-scale fires mainly contribute to vegetation recovery to a certain extent. Short-term burning can easily lead to the degradation of surrounding vegetation, while long-term burning has a positive spillover effect. Slope aspect has a more significant impact on the spillover effect of fire disturbance, but slope has an insignificant effect. This provides a theoretical reference for the study of forest vegetation restoration in South China under external disturbance, and is of great significance for the assessment of forest ecosystem resilience after fire and the optimization of restoration strategies.

Farmland ecosystem is an important ecological resource of national park. Through the monitoring of farmland nutrient background and comprehensive evaluation of fertility in Qianjiangyuan National Park, background data were accumulated for the subsequent evaluation of the impact of easement reform in Qianjiangyuan National Park. Soil bulk density, pH, organic matter, total nitrogen, total phosphorus, alkali-hydrochloric nitrogen, available phosphorus and available potassium were measured in four areas of Qianjiangyuan National Park, including Suzhuang, Hetian, Changhong and Qixi. The modified Nemero comprehensive fertility evaluation index, comprehensive soil fertility index based on principal component analysis and soil fertility health index were used to evaluate the current situation of farmland soil fertility. The results show that the soil in Qianjiangyuan National Park is generally acidic with pH value of 5.35. The soil is rich in organic matter, total nitrogen, alkali hydrolyzed nitrogen, and available phosphorus, with contents of 36.37 g·kg^-1, 1.98 g·kg^-1, 187.94 mg·kg^-1, and 74.76 mg·kg^-1, respectively. However, available potassium is relatively deficient, with a content of 64.27 mg·kg^-1. It is the main limiting factor of soil fertility. Correlation analysis shows that soil pH is significantly negatively correlated with available potassium, bulk density is significantly negatively correlated with available nitrogen, total nitrogen, and organic matter. There is a highly significant positive correlation between organic matter and total nitrogen as well as alkali-hydrolyzable nitrogen, but organic matter isn't significantly correlated with total phosphorus and available phosphorus. In the comparison of different research methods, the comprehensive soil fertility index based on principal component analysis is more applicable, the comprehensive soil fertility level in the study area is good, and the spatial heterogeneity is obvious. The fertility grades of each area are Hetian>Qixi>Changhong>Suzhuang in sequence.The comprehensive fertility level of Hetian area is one level higher than that of the other three areas. This study can provide reference for the construction of soil quality evaluation model and soil management according to local conditions in Qianjiangyuan National Park in the future, and provide scientific decision-making basis for the protection, development and utilization of soil resources in national parks.

Biochar exhibits significant potential for adsorbing and immobilizing polycyclic aromatic hydrocarbons(PAHs) in contaminated soils due to its well-developed pore structure and abundant functional groups.However, dynamic effects of biochar pyrolyzed at different temperatures on PAHs aging behavior in soils remain poorly understood.This study employed rice husk biochars produced at 300, 500, and 700 ℃(denoted as BC300, BC500, and BC700, respectively) to investigate their impacts on PAHs adsorption and aging in soil.Results indicated that biochar's specific surface area increased with pyrolysis temperature.The phenanthrene adsorption capacity(K_f) of biochar-amended soils followed: SBC700(51.56)>SBC500(41.39)>SBC300(24.31)>control(5.55).During the 90-day aging process, the contents of extractable PAHs(acenaphthene, fluorene, fluoranthene, pyrene) decreased across all treatments, and the extent of reduction followed the order: control>SBC300>SBC700≈SBC500, indicating biochar significantly delayed PAH aging.During the initial aging stage(7 days), biochar amendments substantially reduced the contents of bioavailable PAHs, with the reduction order being SBC300>SBC700≈SBC500>control.However, in the later aging stages(15~90 days), no significant differences were observed among treatments, revealing that biochar only temporarily regulates the bioavailability of PAHs in soil.These findings elucidate the mechanism by which pyrolysis temperature modulates PAH aging dynamics in soil through altering biochar's physico-chemical properties, providing theoretical support for the precise selection of biochar in the bioremediation of PAH-contaminated soils.

Through analyzing the correlation between carbon emissions and pollution source data of key emission-control enterprises in Fujian Province, differences in emission dynamics, response mechanisms, and coupling relationships between the power and cement industries were explored, to provide a scientific basis for regional environment improvement and sustainable development. Machine learning models, STL decomposition, trend significance analysis, quantitative analysis, and coupling-decoupling analysis were employed to reveal the emission characteristics of key emission-control enterprises based on data from 2016 to 2023. The results indicate that while seasonal emissions remain stable, trends vary: SO₂ and PM emissions decline steadily, validating the effectiveness of control measures, while CO₂ and NO_x emissions exhibit fluctuating increases, particularly notable in 2023, indicating a need for optimized reduction strategies. Absolute difference comparative analysis shows the power industry has achieved significant reductions in SO₂ and PM reduction(down 31.4% and 42.7%, respectively), with NO_x showing a fluctuating decline(reduction rate rising to 11.5%) but insufficient CO₂ control(up 47.8%). In the cement industry, PM emission decreased significantly(49.2%), yet SO₂ emissions rebounded(42.6%) and CO₂ rose(55.2%). Coupling analysis reveals strong coupling in power plants(correlation coefficient r>0.7), while cement plants exhibit unstable decoupling with frequent coupling points. Trend forecasts suggest a high risk of SO₂ emission increases in cement industry and limited reductions in power industry, underscoring the urgency of energy transition. These findings highlight the disparities in emission reduction technologies and policy implementation among industries, emphasizing the necessity to enhance denitrification and carbon capture technologies in the power industry while implementing stricter supervision on the cement industry to achieve synergistic emission reduction goals. This study provides data support for the formulation of differentiated environmental policies and optimization emission reduction strategies for regional key emission-control enterprises.

Recycling waste printed circuit boards(WPCBs) is vital for environmental protection and resource utilization. Yet different recycling technologies vary considerably in energy consumption, waste emissions, and carbon footprint. This study systematically evaluates the carbon footprint of three typical WPCBs recycling technologies: hydraulic shaker separation, cyclone separation, and smelting. The emission factor method is employed to calculate the carbon emissions from electricity and water consumption, fuel combustion, and waste treatment. The results show that the smelting method has the highest carbon emissions due to the high energy consumption in the high-temperature smelting process. Hydraulic shaker separation and cyclone separation mainly rely on electricity, resulting in relatively lower carbon emissions. However, the disposal of non-metallic waste still contributes to additional carbon emissions. Furthermore, an analysis of the carbon emission composition of each process stage reveals that energy consumption remains the primary source of carbon emissions. To achieve low-carbon recycling, it is recommended to optimize process flows, improve energy efficiency, enhance resource recovery rates, and promote green transformation in enterprises through policy guidance. The findings offer data support and decision guidance for the low-carbon development of the WPCBs recycling industry and for achieving national “dual-carbon” targets.

With the advancement of the construction of new power systems, the carbon emission issue of Ultra-High Voltage Direct Current(UHVDC) project has received increasing attention. Based on the theory of the entire life cycle and combined with the actual carbon emission characteristics of ultra-high voltage direct current project, a carbon footprint measurement method for the entire lifecycle of UHVDC project is proposed. The method divides the life cycle of UHVDC project into four stages: equipment production, construction, operation and maintenance, and disposal, and provides carbon emission measurement models and methods for each stage. According to the method, the impact of UHVDC project on carbon emissions and the environment can be quantified, supporting for formulating reasonable and effective carbon emission reduction measures. Additionally, the application of green construction and measurement in UHVDC project has been explored, aiming to provide more comprehensive technical support for low-carbon management of UHVDC project.

LiDAR scanning technology has emerged as a significant novel tool for forest parameter inventory. Unmanned aerial vehicle-based laser scanning(ULS) and handheld mobile laser scanning(HMLS) acquire forest structural information from complementary aerial and ground perspectives, offering distinct advantages in measuring key parameters like tree height(TH) and diameter at breast height(DBH). However, each platform has inherent limitations: ULS often exhibits larger errors in DBH estimation, while HMLS provides insufficient accuracy in TH retrieval due to restricted viewing geometry. Therefore, integrating multi-source LiDAR data to improve the accuracy of key stand parameter extraction and enhance the reliability of aboveground biomass(AGB) estimation has become a research priority. This study focused on Chinese fir plantations, utilizing ULS, HMLS, and their fused data(ULS+HMLS) for individual tree structural parameter extraction and AGB estimation, systematically evaluating the performance of different data sources at both individual tree and plot scales. The results indicate that, 1) ULS achieved the best performance in TH estimation(R²=0.98, RMSE=0.25 m), while HMLS provided the highest accuracy for DBH retrieval(R²=0.98, RMSE=1.20 cm). The fused data maintained high accuracy for both parameters. 2) Individual tree AGB estimation accuracy was dominated by DBH precision, with HMLS and the fused data performing better(both R²=0.98). 3) At the plot scale, the fused data yielded the highest AGB estimation accuracy(R²=0.92, RMSE=11.07 t·hm^-2). ULS showed relatively lower accuracy due to error accumulation stemming from incomplete individual tree segmentation. This study indicates that fusing multi-source LiDAR data effectively combines the observational strengths of different platforms can provide a robust technical approach for improving the accuracy and reliability of biomass estimation in plantations.

Stomata act as the gateways for carbon and water exchange between vegetation and the atmosphere. Stomatal conductance reflects the physiological balance between water flux protection and carbon flux capture in plants. Therefore, accurately simulating stomatal conductance is crucial for the simulation of ecosystem gross primary productivity(GPP) and evapotranspiration(ET). In this study, three stomatal conductance models, Ball-Woodrow-Berry(BWB), Ball-Berry-Leuning(BBL), and Unified Stomatal Optimization(USO), were applied to the BEPS(Boreal Ecosystem Produtivity Simulator) land surface ecological process model for simulation analysis. The differences among the models and their applicability to evergreen needleleaf forests(ENF) and deciduous broadleaf forests(DBF) were explored. The results showed that, 1) the overall accuracy of GPP and ET simulations based on the three stomatal conductance models was relatively high, with BEPS-USO performing the best. 2) The GPP simulation accuracy at ENF sites was similar, whereas substantial differences were observed at DBF sites, with an overall performance ranking of BEPS-USO > BEPS-BBL > BEPS-BWB. For ET simulation, BEPS-USO performed best at ENF sites, while BEPS-BBL slightly outperformed BEPS-USO at DBF sites, followed by BEPS-BWB. 3) The seasonal variations in simulated stomatal conductance(g_s) values by different models at ENF sites were more significant than those at DBF sites. The g_s simulated by the three models at the four flux sites all showed seasonal variations consistent with GPP, and the coupling between g_s and GPP was weaker than that between g_s and ET. This study achieved the embedding of three stomatal conductance models in the BEPS model and their simulation application at flux sites, compared and analyzed the differences and applicability of the three stomatal conductance models in different vegetation types. The findings provide practical guidance for selecting appropriate stomatal conductance models in the simulation of carbon and water cycles in terrestrial ecosystems.

To enhance the efficiency of soil and water conservation carbon sink project development, reduce development costs, and improve carbon sink measurement accuracy, remote sensing technology has become a crucial technical tool supporting carbon sink project development. Taking the Xiaonan Mountain watershed in Youyu County, Shanxi Province as a case study, this research systematically explores the application of remote sensing technology in carbon pool monitoring. Land cover classification and carbon layer delineation were conducted based on forest compartment attributes. Vegetation carbon density was calculated through systematic sampling combined with field surveys and allometric growth equations. Subsequently, a regional carbon density estimation model integrating spectral factors, vegetation indices, and carbon layer dummy variables was established(R²=0.806, MAE=9.202 t·hm^-2). This model estimated vegetation carbon density and net carbon sink capacity in the watershed from 2002 to 2024, while Kriging interpolation assessed the spatial distribution of soil carbon density. Results indicate that over 22 years, vegetation carbon density in the Xiaonan Mountain watershed increased from 14.66 t·hm^-2 to 27.02 t·hm^-2, with a net increase of 16 326.77 t in vegetation carbon stocks. High-density areas significantly expanded northward and southwestward. Soil carbon density exhibited a northeast-high, southwest-low pattern, primarily driven by carbon sequestration effects from afforestation(conversion to shrubland) in the northeast region. The study further indicates that the slight decline in carbon density observed in mixed poplar-pine forests can be mitigated through measures such as fertilization and management to mitigate tree species degradation, thereby sustaining the increase in regional net carbon sink capacity.