A carbon-neutrality-capactiy index for evaluating carbon sink contributions

Biomass allocation, carbon content change and carbon stock distribution of Scots pine (Pinus sylvestris var. mongholica) plantation forests at different stand ages and densities in the sandy area of western Liaoning Province, China

Scots pine (Pinus sylvestris var. mongholica) is one of the main afforestation species in the southeastern edge of the Horqin Sandy Land, which not only effectively prevents the expansion of the sandland, but also serves as an important carbon reservoir. Uncovering the biomass allocation, carbon content changes and carbon stock distribution among organs of Scots pine at different ages and densities can provide a theoretical basis for rational afforestation and management in the western Liaoning sandy area. In this study, the biomass and carbon content of four organs, namely, trunk, branch, leaf and root, were measured at different age classes (young stage, half-mature stage, near-mature stage, mature stage and over-mature stage forests) and densities, and the carbon stock of Scots pine plantations in the western Liaoning sandy area was estimated. The results showed that the biomass of all organs except leaves increased with the increase of stand age, but the rate of increase of each organ was not consistent. To resist wind and sand, the biomass was preferentially allocated to the trunk and roots, which was in line with the theory of allometry and optimal allocation. The carbon content of each organ of Scots pine increases and then decreases with the rise of forest age classes, and the root carbon content is the lowest in five forest ages, and the plant carbon is mainly stored in the aboveground part. The biomass of each organ in both near mature and mature forests increased with the decrease in density. Still, the root carbon content decreased with the decrease of density, and the PCA analysis showed that near mature and mature forests had better carbon sequestration capacity in low density. The carbon stock of Scots pine plantation forests in the sandy area of western Liaoning was mainly concentrated in Fuxin and Chaoyang cities, and the lowest carbon stock was found in Jinzhou. The age and density of the forest stand are important factors affecting the biomass and carbon content of Scots pine, therefore, when operating Scots pine plantation forests in the sandy areas of western Liaoning, different stand densities should be retained at different age stages, so that their biomass and carbon content can be sufficiently accumulated and distributed to improve the local environment.

Small reservoirs can enhance the terrestrial carbon sink of controlled basins in karst areas worldwide

The concentration of Greenhouse Gas (GHG) in the atmosphere has sharply increased since the Industrial Revolution, leading to climate warming and severe environmental problems. It has become a consensus that GHG emissions of large reservoirs essentially constitute inland aquatic GHG emissions. However, questions remain regarding whether small karst reservoir (SKR) is only a substantial source of GHG emissions like large reservoirs, and how much GHG emission it can offset by affecting the terrestrial carbon sink (TCS) of its controlled basin. We selected two basins in the karst area of southwestern China, with built and planned SKRs, and quantitatively analysed the impact of the SKR on basin-scale water and carbon cycles during 2000-2020 using multi-source remote sensing data and the Google Earth Engine. Results showed that the associated increase in the TCS in the SKR-controlled basin can completely offset the GHG emissions and TCS losses caused by submerged land, resulting in a 21.48 % faster increase rate of TCS and a 12.20 % greater increase in TCS caused by human activities than in non-karst reservoir basin. Meanwhile, by intercepting both surface and groundwater runoff, the SKR-controlled basin showed a 329.55 % faster increase rate of available surface water resources than the non-karst reservoir basin, alleviating the problem of engineering water shortages and enhancing the drought resistance capacity. Moreover, in the three major karst areas worldwide, and especially in southwestern China, faster vegetation restoration and TCS increase exist in most SKR-controlled basins, and this increase is enhanced with increasing proximity to the water surface. This study revealed that SKR is more than a substantial source of GHG emissions; it can also effectively enhance the TCS and available surface water resources in controlled basin, which is of great significance for achieving carbon neutrality goals while maintaining the sustainability of water and carbon cycle in karst areas.

Unexpected response of terrestrial carbon sink to rural depopulation in China

China is experiencing large-scale rural-urban migration and rapid urbanization, which have had significant impact on terrestrial carbon sink. However, the impact of rural-urban migration and its accompanying urban expansion on the carbon sink is unclear. Based on multisource remote sensing product data for 2000-2020, the soil microbial respiration equation, relative contribution rate, and threshold analysis, we explored the impact of rural depopulation on the carbon sink and its threshold. The results revealed that the proportion of the rural population in China decreased from 63.91 % in 2000 to 36.11 % in 2020. Human pressure decreased by 1.82% in rural depopulation areas, which promoted vegetation restoration in rural areas (+8.45 %) and increased the carbon sink capacity. The net primary productivity (NPP) and net ecosystem productivity (NEP) of the vegetation in the rural areas increased at rates of 2.95 g C m-2 yr-1 and 2.44 g C m-2 yr-1. Strong rural depopulation enhanced the carbon sequestration potential, and the NEP was 1.5 times higher in areas with sharp rural depopulation than in areas with mild rural depopulation. In addition, the rural depopulation was accompanied by urban expansion, and there was a positive correlation between the comprehensive urbanization level (CUL) and NEP in 75.29 % of urban areas. In the urban areas, the vegetation index increased by 88.42 %, and the urban green space partially compensated for the loss of carbon sink caused by urban expansion, with a growth rate of 4.96 g C m-2 yr-1. Changes in rural population have a nonlinear impact on the NEP. When the rural population exceeds 545.686 people/km2, an increase in the rural population will have a positive impact on the NEP. Our research shows that rural depopulation offers a potential opportunity to restore natural ecosystems and thus increase the carbon sequestration capacity.

Evaluating the impact of soil erosion on soil quality in an agricultural land, northeastern China

The impact of soil erosion on soil quality is still not systematically understood. The purpose of this study was thus to quantify the impact of soil erosion on soil quality and its change with slope morphology in an agricultural field, northeastern China based on radionuclide 137Cs, unmanned aerial vehicle derived high resolution digital elevation model, and soil sampling. 137Cs method yielded an average soil erosion rate of - 275 t km-2 yr-1 ranging from - 1870 to 1557 t km-2 yr-1. The soil quality index derived from total dataset (SQI_TDS) can be well explained by that derived from minimum data set (SQI_MDS) with a determination coefficient R2 of 0.874. SOM, sand, and cation exchange capacity in the MDS play more important roles than other soil indicators. Soil quality was significantly affected by soil erosion, with Adj. R2 of 0.29 and 0.33 for SQI_TDS and SQI_MDS, respectively. The spatial variations of soil erosion and soil quality were both affected by slope topography. Soil erosion must be controlled according to topographic and erosion characteristics in northeastern China.

Carbon peaking prediction scenarios based on different neural network models: A case study of Guizhou Province

Global warming, caused by greenhouse gas emissions, is a major challenge for all human societies. To ensure that ambitious carbon neutrality and sustainable economic development goals are met, regional human activities and their impacts on carbon emissions must be studied. Guizhou Province is a typical karst area in China that predominantly uses fossil fuels. In this study, a backpropagation (BP) neural network and extreme learning machine (ELM) model, which is advantageous due to its nonlinear processing, were used to predict carbon emissions from 2020 to 2040 in Guizhou Province. The carbon emissions were calculated using conversion and inventory compilation methods with energy consumption data and the results showed an "S" growth trend. Twelve influencing factors were selected, however, five with larger correlations were screened out using a grey correlation analysis method. A prediction model for carbon emissions from Guizhou Province was established. The prediction performance of a whale optimization algorithm (WOA)-ELM model was found to be higher than the BP neural network and ELM models. Baseline, high-speed, and low-carbon scenarios were analyzed and the size and time of peak carbon emissions in Liaoning Province from 2020 to 2040 were predicted using the WOA-ELM model.

Temporal and spatial evolution simulation and attribution analysis of vegetation photosynthesis over the past 21 years based on satellite SIF data: a case study from Asia

Photosynthesis in vegetation is one of the key processes in maintaining regional ecological balance and climate stability, and it is of significant importance for understanding the health of regional ecosystems and addressing climate change. Based on 2001-2021 Global OCO-2 Solar-Induced Fluorescence (GOSIF) dataset, this study analyzed spatiotemporal variations in Asian vegetation photosynthesis and its response to climate and human activities. Results show the following: (1) From 2001 to 2021, the overall photosynthetic activity of vegetation in the Asian region has shown an upward trend, exhibiting a stable distribution pattern with higher values in the eastern and southern regions and lower values in the central, western, and northern regions. In specific regions such as the Turgen Plateau in northwestern Kazakhstan, Cambodia, Laos, and northeastern Syria, photosynthesis significantly declined. (2) Meteorological factors influencing photosynthesis exhibit differences based on latitude and vertical zones. In low-latitude regions, temperature is the primary driver, while in mid-latitude areas, solar radiation and precipitation are crucial. High-latitude regions are primarily influenced by temperature, and high-altitude areas depend on precipitation and solar radiation. (3) Human activities (56.44%) have a slightly greater impact on the dynamics of Asian vegetation photosynthesis compared to climate change (43.56%). This research deepens our comprehension of the mechanisms behind the fluctuations in Asian vegetation photosynthesis, offering valuable perspectives for initiatives in environmental conservation, sustainability, and climate research.

Terrestrial vegetation carbon sink analysis and driving mechanism identification in the Qinghai-Tibet Plateau

The estimation of terrestrial carbon sinks in the Qinghai-Tibet Plateau (QTP) still faces significant uncertainties, and the spatiotemporal dynamics of terrestrial carbon sinks along altitudinal gradients remain unexplored. Moreover, the driving mechanisms of terrestrial carbon sinks at the watershed scale in the QTP continue to be lacking. To address these research gaps, based on multi-source remote sensing data and meteorological data, this study calculated the Net Ecosystem Productivity (NEP) in the QTP from 2000 to 2020 using the Modis NPP-soil respiration model. Through the coefficient of variation (CV), the Mann-Kendall test (MK), and the spatial autocorrelation methods, the spatial distribution pattern and spatiotemporal trends of NEP were investigated. Employing a pixel accumulation method, the variation of NEP along altitudinal gradients was explored. Grey relation analysis, Pearson correlation analysis, and Geographical detector (GD) were used to investigate the driving mechanisms of NEP at the watershed scale. Results showed that: (1) the terrestrial ecosystem in the QTP served as a carbon sink, which produced a total of 2.04 Pg C from 2000 to 2020, and the multi-year average of total carbon sinks was 96.92 Tg C; (2) the spatial distribution of NEP shows a decreasing change from southeast to northwest, and the clustering characteristic of NEP is significant at the watershed scale; (3) the elevation of 4507 m we proposed is likely to be a key threshold for biophysical processes of the terrestrial ecosystems in the QTP; (4) the fluctuation and change trend of carbon sources and carbon sinks show significant differences between the East and West; (5) at the watershed scale, precipitation and temperature play a dominant role in the variation of NEP, while the impact of human activities on NEP variation is weak. Our study aims to address the existing knowledge gaps and provide valuable insights into the management of terrestrial carbon sinks in QTP.

A daily gap-free normalized difference vegetation index dataset from 1981 to 2023 in China

Long-term, daily, and gap-free Normalized Difference Vegetation Index (NDVI) is of great significance for a better Earth system observation. However, gaps and contamination are quite severe in current daily NDVI datasets. This study developed a daily 0.05° gap-free NDVI dataset from 1981-2023 in China by combining valid data identification and spatiotemporal sequence gap-filling techniques based on the National Oceanic and Atmospheric Administration daily NDVI dataset. The generated NDVI in more than 99.91% of the study area showed an absolute percent bias (|PB|) smaller than 1% compared with the original valid data, with an overall R2 and root mean square error (RMSE) of 0.79 and 0.05, respectively. PB and RMSE between our dataset and the MODIS daily gap-filled NDVI dataset (MCD19A3CMG) during 2000 to 2023 are 7.54% and 0.1, respectively. PB between our dataset and three monthly NDVI datasets (i.e., GIMMS3g, MODIS MOD13C2, and SPOT/PROBA) are only -5.79%, 4.82%, and 2.66%, respectively. To the best of our knowledge, this is the first long-term daily gap-free NDVI in China by far.

Energy-saving targets and carbon neutrality: A perspective on carbon emissions and carbon substitution in 288 Chinese cities

Environmental protection is a shared task among nations. In pursuit of its commitment to achieve carbon neutrality by 2060, China has implemented more robust energy-saving targets. This study utilizes panel data from 288 Chinese cities spanning from 2006 to 2020 to examine the policy effects of energy-saving targets on carbon neutrality. The findings reveal that (1) energy-saving targets positively impact carbon substitution, resulting in reduced carbon emissions and facilitating the progress towards carbon neutrality through three primary channels: energy governance, energy production, and energy consumption. (2) The influence of energy-saving targets on carbon neutrality exhibits a significant spatial spillover effect, driven primarily by the reduction in carbon emissions, although the spatial spillover effect of carbon substitution is relatively limited. The collaboration between the government and enterprises plays a crucial role in achieving carbon neutrality, while the engagement of the general public is yet to be fully realized. (3) However, the inadequacy of enhancing carbon neutrality through energy-saving targets lies in the compulsory emissions reduction behavior at the expense of sacrificing some economic benefits in cities that overachieve energy-saving targets. This undermines the coordinated development of ecology and economy. Therefore, it is recommended to establish a policy implementation monitoring system to ensure the scientific basis of policy objectives, enhance the level of green technology innovation, accelerate the digital transformation of enterprises, and establish a synergistic mechanism that involves multiple stakeholders.

Analysis of change process of NPP dominated by human activities in Northwest Hubei, China, from 2000 to 2020

Clarifying the spatial distribution of the impact of different human disturbance activities on the net primary productivity (NPP) in regions with single climatic conditions is of considerable importance to ecological protection. Time-series NPP from 2000 to 2020 was simulated in Northwest Hubei, China, and the effects of the climate and human activities on the NPP changes were separated. Research results showed that from 2000 to 2020, the NPP change with an area of 10,166.63 km2 in Northwest Hubei is influenced by climate and human activities. Among them, human activities account for as high as 84.53%. From 2000 to 2020, the NPP in Northwest Hubei showed a slight upward trend at a rate of 1.61 g C m-2 year-1. The significantly increased NPP accounted for 21.4% of the total, which was mainly distributed in north of Northwest Hubei. And the farming of cultivated land led to the increase of NPP in west as well as the reduced human distribution in cultivated land, which was scattered in forests. Only 6.67% of the total area demonstrated a significantly decreased NPP, which was distributed mainly in the central affected by the expansion of rural-urban land and change of broad-leaved forests to shrubs and in southeast regions of Northwest Hubei caused by the increase in potential evapotranspiration. This study refined the driving factors of spatial heterogeneity of NPP changes in Northwest Hubei, which is conducive to rational planning of terrestrial ecosystem protection measures.

Modelling the effects of climate and management on the distribution of deadwood in European forests

Deadwood is a key old-growth element in European forests and a cornerstone of biodiversity conservation practices in the region, recognized as an important indicator of sustainable forest management. Despite its importance as a legacy element for biodiversity, uncertainties remain on the drivers of deadwood potentials, its spatial distribution in European forests and how it may change in the future due to management and climate change. To fill this gap, we combined a comprehensive deadwood dataset to fit a machine learning and a Bayesian hurdle-lognormal model against multiple environmental and socio-economic predictors. We deployed the models on the gridded predictors to forecast changes in deadwood volumes in Europe under alternative climate (RCP4.5 and RCP8.5) and management scenarios (biodiversity-oriented and production-oriented strategies). Our results show deadwood hotspots in montane forests of central Europe and unmanaged forests in Scandinavia. Future climate conditions may reduce deadwood potentials up to 13% under a mid-century climate, with regional losses amounting to up to 22% in Southern Europe. Nevertheless, changes in management towards more biodiversity-oriented strategies, including an increase in the share of mixed forests and extended rotation lengths, may mitigate this loss to a 4% reduction in deadwood potentials. We conclude that adaptive management can promote deadwood under changing environmental conditions and thereby support habitat maintenance and forest multifunctionality.

Study on the relationship between regional soil desertification and salinization and groundwater based on remote sensing inversion: A case study of the windy beach area in Northern Shaanxi

Soil desertification and salinization are important environmental concerns in arid regions, and their relationship with groundwater change must be further clarified. However, the relationships among soil desertification, salinization, and groundwater are difficult to investigate on a large spatiotemporal scale using traditional ground surveys. In the windy beach area in Northern Shaanxi (WBANS), desertification and salinization problems coexist; therefore, this area was selected as the study area. The feasibility of implementing large-scale remote sensing inversions to identify the degree of desertification and salinization was verified based on measured data, and the degree of influence of groundwater burial depth (GBD) on desertification and salinization was quantified using the geodetector and residual trend analysis methods. The results showed that the GBD in the WBANS presented an increasing trend and the degree of salinization showed a decreasing trend. Moreover, the joint influence of the unique natural environment and anthropogenic activities has led to increases in fractional vegetation cover and considerable improvements in the ecological environment. The intensity of desertification explained by GBD in the WBANS increased significantly (p < 0.01) at a rate of change of 0.0190/year, with high q-values above 0.66 for both Yuyang and Shenmu. The contribution rate of potential evapotranspiration and precipitation to salinization in Yuyang and Shenmu was >97 %, and the contribution rate of GBD to salinization in Dingbian, Jingbian, and Hengshan was 34.78 %, 31.15 %, and 29.41 %, respectively. Overall, the suitable GBD in the WBANS is 2-4 m. The study results provide a reference for research on the inversion, monitoring, and prevention of desertification and salinization dynamics on a large spatiotemporal scale and offer a scientific basis for rationally determining GBD.

Spatial effect of carbon neutrality target on high-quality economic development-Channel analysis based on total factor productivity

This study utilizes panel data from 30 provinces in mainland China from 2011 to 2020 to investigate the impact of carbon-neutral development on economic high-quality development by constructing an economic high-quality development index and a carbon-neutral development index. Firstly, the study examines the effects of carbon-neutral development on economic high-quality development using baseline regression and spatial Durbin regression. The results indicate that carbon-neutral development has a positive direct effect on economic high-quality growth, but there are negative spatial spillover effects. Secondly, this study employs total factor productivity (TFP) as an intermediate variable in the mediation model regression. The findings demonstrate that carbon-neutral development significantly improves TFP, and the significant improvement in TFP promotes high-quality economic growth. Lastly, the study conducts regional heterogeneity analysis and finds a significant promoting effect of carbon-neutral development on economic high-quality development in the eastern and central regions of China, while it is not significant in the western region. Therefore, it is recommended that China, in the process of achieving carbon-neutral growth, consider the geographical connections between different regions to prevent negative spillover effects. Additionally, regional heterogeneity should be taken into account when formulating relevant policies to promote economic high-quality development.

Global predictions of topsoil organic carbon stocks under changing climate in the 21st century

The organic carbon (OC) stored in global topsoil (0-30 cm) will be the most active participant in the carbon cycle under future climate change. Due to differences in focus regions or research methods, the spatio-temporal changes of future global topsoil OC stocks and how they will be affected by climate change are not systematically understood, which needs to be further explored. In this study, we developed data-driven models to predict the spatio-temporal dynamics of global topsoil OC stocks by combining 32,579 soil profiles with environmental variables and comprehensively explored the impact of future climate change on topsoil OC. It was found that the topsoil OC stocks were 1249.29 Pg in the baseline period (1971-1990). By 2100, under the normal and high representative concentration paths, it is predicted that the global topsoil OC stocks will decrease by 113.67 ± 25.93 Pg and 193.71 ± 39.76 Pg, respectively. In the future, the largest global topsoil carbon loss will occur in boreal forest areas, which are expected to lose 17.03-27.90 % (66.01-108.13Pg) of their carbon stocks. The influence of climate on topsoil OC stocks is mainly manifested in temperature, which has a negative influence on the global topsoil OC stock, and the contribution rate of temperature to the effect on the global topsoil OC stock is about 26.96 %. Overall, our results provide a high spatio-temporal resolution assessment of global topsoil OC stocks and their relationship to environmental factors, and highlight the spatial heterogeneity, which has been generally ignored in many experimental frameworks and prediction models. These results will help governments to make appropriate management decisions to mitigate climate change.

Artificial Soil-Like Material Enhances CO2 Bio-Valorization into Chemicals in Gas Fermentation

Gas fermentation offers a carbon-neutral route for producing industrial feedstocks using autotrophic microbes to convert carbon dioxide (CO2) in waste gases, such as industrial emissions and biogas, into valuable chemicals or biofuels. However, slow microbial metabolism owing to low gaseous solubility causes significant challenges in gas fermentation. Although chemical or genetic manipulations have been explored to improve gas fermentation, they are either nonsustainable or complex. Herein, an artificial soil-like material (SLM) inspired by natural soil was fabricated to improve the growth and metabolism ofCupriavidus necatorfor enhanced poly-β-hydroxybutyrate (PHB) biosynthesis from CO2 and hydrogen (H2). Porous SLM comprises low-cost nanoclay, boehmite, and starch and serves as a biocarrier to facilitate the colonization of bacteria and delivery of CO2 to bacteria. With 3.0 g/L SLM addition, the solubility of CO2 in water increased by ∼4 times and biomass and PHB production boosted by 29 and 102%, respectively, in the 24 h culture. In addition, a positive modulation was observed in the metabolism of PHB biosynthesis. PHB biosynthesis-associated gene expression was found to be enhanced in response to the SLM addition. The concentrations of intermediates in the metabolic pathway of PHB biosynthesis, such as pyruvate and acetyl-CoA, as well as reducing energy (ATP and NADPH) significantly increased with SLM addition. SLM also demonstrated the merits of easy fabrication, high stability, recyclability, and plasticity, thereby indicating its considerable potential for large-scale application in gas fermentation.

How does corporate organizational identity, environmental project complexity and environmental project effort matter for project success?

The challenge of achieving success in environmental projects persists for many organizations, and the reasons behind it are unclear. This study is aimed at investigating such reasons by testing the impact of corporate environmental identity, project complexity, and environmental intensity on environmental project success. The study seeks to provide practical recommendations to organizations to enhance their efforts to reduce environmental pollution. The study obtained data from sixteen experts of environmental project managers and applied the fuzzy AHP, fuzzy hierarchical models, and fuzzy TOPSIS techniques for empirical findings. The findings show that organizational identity for the environment and environment project complexity are the key triggers for the success of the environment in the Chinese context. Moreover, it is discovered that team functional diversity is critical to team absorptive capability. This research identified links that offer managers information on prospective selection and project improvement models, with enhanced capacity in leadership dimensions leading to increased project management success. The study also suggested several implications for environmental project success and developing pro-environmental behavior among project managers.

Spatialization and driving factors of carbon budget at county level in the Yangtze River Delta of China

The county is the basic administrative unit of China, and the spatialization of carbon budget at the county scale plays an irreplaceable role in deepening the understanding of the carbon emission mechanism and spatial pattern. Yueqing County, an economically developed county in the Yangtze River Delta of China, was selected as the study area, the spatial pattern of the carbon budget and the optimal resolution of the spatialization at the county level were dissected on the basis of accurate accounting, and driving factors of carbon emissions were further identified using the geographically weighted regression model. The results indicated that (1) the carbon emissions were mainly generated from fossil fuel combustion related to energy, accounting for 98.8% of the total carbon budget in the study area; (2) the optimal resolution of spatialization was 200 m and carbon emissions were concentrated in the southeast of the study area; (3) energy intensity, energy structure, per capita GDP, and urbanization rate were positively correlated with carbon emissions, while population played a bidirectional role in carbon emissions. This study not only strengthens the understanding of the patterns and drivers of the carbon budget but also establishes a theoretical framework and operational tools for policymakers to formulate solutions to mitigate the carbon crisis.