Carbon Density Research Articles

Spatial distribution and driving factors of soil organic carbon in the Northeast China Plain: Insights from latest monitoring data

Soil organic carbon (SOC) is a critical component of soil fertility and plays a crucial role in the global carbon cycle. Despite the widespread reports of a decrease in SOC content and stock in the Northeast China Plain in recent decades, the current status and driving factors of its content and distribution are unclear. In this study, the surface soil (0–20 cm) SOC content data of 1920 sampling points within the Northeast China Plain covering an area of 2.6 × 105 km2 were obtained based on the Land Quality Geochemical Monitoring Network established in 2018. Random forest model and correlation analysis were used to identify the main driving factors of SOC distribution. The results showed that the SOC content, soil organic carbon density (SOCD), and soil organic carbon storage (SOCS) in the Northeast China Plain were 13.48 g·kg−1, 3.45 kg·C·m−2, and 898.95 Tg, respectively. SOC content in paddy land was the highest among different land use types, which reached 18.77 g·kg−1. SOC content showed strong spatial dependence and gradually increased from southwest to northeast in the monitoring area. The results of the random forest analysis showed that the SiO2, mean annual temperature, and Fe2O3 explained 39.4 %, 18.9 %, and 12.8 % of the spatial variation of SOC, respectively. Although the SOCS (0–20 cm) in the Northeast China Plain has decreased by 8.68 % in the last 40 years compared to the Second National Soil Survey (1980), it's important to note that the SOCS has transitioned from a decreasing trend between 1980 and 2006 to an increasing trend from 2006 to 2018.This study provides important information for decision-makers on the spatiotemporal changes of SOC and its driving factors in the Northeast China Plain, which has a great significance for soil carbon sequestration and the development of management strategies to maintain soil fertility.

Controlling carbon nanostructure synthesis in thermal plasma jet: Correlation of process parameters, plasma characteristics, and product morphology

Thermal plasma has emerged as an effective approach for producing carbon nanostructures without the need for specific catalysts nor substrates. While efforts have focused on the effect of process parameters such as reaction pressure, input power or carbon source, the intricate role and relationship with plasma characteristics like density and temperature are often overlooked due to the complexity of the environment. This study addresses this gap by establishing a correlation between process parameters, plasma characteristics, and product morphology, essential for controlling the growth of carbon nanostructures. We explored the impact of carbon precursor type (CH4 and C2H2), hydrogen, pressure, and flow rate on nanostructure formation. Using in situ optical emission spectroscopy (OES), we mapped the distribution of both temperature and dicarbon molecule (C2) density within the plasma jet. We demonstrate that the growth of low-density nanostructures, such as carbon nanohorns (CNHs), is favoured at dilute C2 local densities and high temperatures, while denser nanostructures, such as onion-like polyhedral graphitic nanocapsules (GNCs), are favoured at higher C2 densities and lower temperatures. The carbon density can be controlled by the flow rate and the pressure, which in turn significantly influence the nanostructure morphology, evolving from graphene nanoflakes (GNFs) to GNCs as either parameter increases. Increasing the H/C ratio from 1 to 8 resulted in a morphological transition from CNHs to GNFs. During the synthesis, the plasma jet temperature surpassed 3000 K, with crystalline growth occurring 50–100 mm below the nozzle.

Determining Allometry and Carbon Sequestration Potential of Breadfruit (Artocarpus altilis) as a Climate-Smart Staple in Hawai‘i

Breadfruit (Artocarpus altilis) is an underutilized Pacific tree crop that has been highlighted as having substantial potential to contribute to global food security and climate-smart agriculture, including adaptation to and mitigation of climate change. To explore the carbon sequestration potential of breadfruit production, we characterize tree volume, wood density, carbon density, foliar biomass, and growth rates of breadfruit in Hawai‘i. Strong relationships to trunk or branch diameter were displayed for wood density (r2 0.81), carbon density (r2 0.87), and foliar biomass (r2 0.91), which were combined to generate an allometric prediction of tree volume (r2 0.98) based on tree diameter at breast height. Growth rates, as measured by diameter at breast height, were well predicted over time when trees were classified by habitat suitability. We extrapolate potential breadfruit growth and carbon sequestration in above-ground biomass to the landscape scale over time. This study shows that breadfruit is on the low end of broadleaf tropical trees in moist and wet environments, but in an orchard can be expected to sequester ~69.1 tons of carbon per hectare in its above-ground biomass over a 20-year period.

Computational tools for assessing forest recovery with GEDI shots and forest change maps

Tropical secondary forests are ecosystems of critical importance for protecting biodiversity, buffering primary forest loss, and sequestering atmospheric carbon. Monitoring growth and carbon sequestration in secondary forests is difficult, with inventory plots sampling <0.001% of secondary forests. The Global Ecosystem Dynamics Investigation (GEDI), a space-borne LiDAR sampler, provides billions of aboveground carbon density (ACD) estimates across the tropics. We fuse these carbon density estimates with a time series of forest change maps to identify their age since last deforestation and thus estimate the average rate of carbon sequestration in secondary forests across the Amazon biome. To our knowledge, this is the first estimate of these rates made using the new GEDI dataset. Moreover, this paper addresses key statistical and computational challenges of GEDI data fusion and analysis. We propagate both GEDI ACD and geolocation uncertainty to the regrowth rate estimate through a Monte Carlo approach, and we handle heteroskedasticity, outliers, and spatial autocorrelation using robust statistical methods. The large size of the GEDI dataset combined with the proposed Monte Carlo bootstrap can be highly computationally intensive, with a naive implementation taking over a month to complete. Nevertheless, we demonstrate the feasibility of our method by developing optimized open-source code that performs this computation on the 151 million quality-filtered GEDI shots available for the Amazon biome from April 2019–August 2021 in under 25 min in benchmark tests. By resolving these statistical and computational challenges with an efficient open-source pipeline, we create a standard approach that can be used more broadly in any work seeking to combine the GEDI dataset with high-resolution classification maps. Using this approach, we identify approximately 23, 000 GEDI samples of regrowing forest at least 60 m × 60 m wide across the Amazon biome and estimate a carbon sequestration rate of 1.86 MgC/ha/yr with a 95% empirical confidence interval of 1.75–1.97 MgC/ha/yr, with rates varying from 1.27 to 1.99 MgC/ha/yr across smaller subregions.

Distribution of Soil Organic Carbon Density Fractions in Aggregates as Influenced by Salts and Microbial Community

Understanding soil organic carbon (SOC) at the aggregate level is crucial for soil health in secondary-salinized greenhouse development. Nevertheless, the specific patterns and contributions of ion content and microbial communities on SOC density fractions at the aggregate level remain unclear in secondary-salinized soil. We investigated variations in salts [electrical conductivity (EC) and ions] and microbial communities across various aggregate classes in both a 16-year-use greenhouse and open-field soils. We also examined SOC density fractions, including the light fraction (LF), the heavy fraction of particulate organic matter (POM), and mineral-associated organic matter (MOM) across different aggregates. The findings revealed that a lower Ca2+/K+ along with elevated EC levels (average 2.49 mS cm−1) reduced the macroaggregate percentage in greenhouse compared to open-field conditions, with a lower EC of 0.58 mS cm−1. Bacterial diversity and community composition exhibited no variation across different aggregate sizes at both sites. Conversely, fungal diversity and relative abundance (primarily dominated by Ascomycota of 78.50%) substantially increased in microaggregates (&lt;0.25 mm) compared to macroaggregates (&gt;0.25 mm). Macroaggregates exhibited a higher proportion of LF and MOM (3.3–18.2%, 24.9–34.5%, and 2.9–4.0% for LF, MOM, and POM, respectively) than microaggregates. Correlation and redundancy analyses revealed that fungal diversity, particularly the relative abundance of Ascomycota in aggregates &lt; 0.25 mm, significantly and positively influenced (p &lt; 0.05) the proportion of MOM carbon in terms of the overall SOC (J-type). This study provides valuable insights into the distribution patterns of SOC within the secondary salt-affected soils.

Mapping surface soil organic carbon density by combining different soil sampling data sources and prediction models in Yangtze River Delta, China

Soil organic carbon (SOC) is a crucial soil property governing various agricultural, ecological, and environmental processes in the terrestrial ecosystem. However, acquiring accurate and high resolution SOC density (SOCD) map remained a challenge in the current researches. Based on soil samples collected from soil survey and published literatures (952 samples), this study tested different approaches for generating high accuracy dataset of 0–20 cm SOCD with the spatial resolution of 90-m in the Yangtze River Delta. Two spatial prediction methods, including artificial neural network (ANN, represented non-linear), multiscale geographically weighted regression (MGWR, represented linear) were applied to generated the SOCD maps. Then three fusion models, including multiple linear regression fusion (MLR_F), ANN fusion (ANN_F) and a self-developed model (multiscale geographically normalize weighted fusion, MGNW_F), were applied to fuse the prediction results of spatial interpolation methods. Among spatial interpolation methods, the ANN performed better in capturing the SOCD spatial pattern, while the MGWR performed better in accuracy measures of mean square error, mean absolute error and coefficient of determination. After data fusing by the three models, improved accuracy measures than the ANN and MGWR were achieved. The predictions of fusion models also showed better reliability than the soil dataset of high resolution National Soil Information Grids of China, mainly due to that more soil samples were included in the prediction. Among these fusion models, the MGNW_F performed slightly better than the other two and had the strongest adaptability to the overall environment of the study area. Findings of this study highlighted the potentials of acquiring additional soil samples from existing literatures and fusing different methods for enhancing the accuracy in mapping SOCD.

Distribution of biomass and carbon content in estimation of carbon density for typical forests

Accurate measurements of parameters related to carbon stock are crucial for evaluating the potential of regional forest ecosystems to sequester carbon and implement enhanced carbon sequestration. This study analysed the differences in biomass and carbon content (CC) among fourteen forest types and assessed the capacity of forest ecosystems to sequester carbon, using karst typical forest ecosystems in central Guizhou Province as an example. The results showed that: 1) the arbor layer was the dominant component of the forest biomass, accounting for more than 66 % of the total forest biomass; 2) the CC of branches was slightly higher than that of leaves and stems, and the CC of the carbon layer ranged from 37.79 % to 48.90 %, with the arbor layer having the highest average CC; 3) the vegetation CC of each forest type differed significantly from the default value in common research, and the adoption of the fixed values may result in errors in carbon stock estimation; 4) the forest ecosystem had an average carbon density of 187.78 t/hm2, and the forest vegetation maintained a higher level of carbon pooling than the soil. Moreover, the topsoil had a higher carbon density than the deep soil. This study makes important contributions to improving the accuracy of carbon stock estimates and maximizing the potential for carbon stock in karst regions.

Southern Alaska's Forest Landscape Integrity, Habitat, and Carbon Are Critical for Meeting Climate and Conservation Goals

AbstractThe interdependent crises of climate change and biodiversity losses require strategic policies to protect, manage, and restore essential ecosystems. Here, we evaluate the relative importance of US national forests (NFs) for protection and conservation as natural climate and biodiversity solutions. We compared landscape integrity (degree of modification by humans), habitat for three keystone species, forest carbon density, accumulation, and total biomass carbon stocks across 154 NFs in the United States. Southern Alaska's Tongass and Chugach NFs hold disproportionally large amounts of high landscape integrity area among all NFs with 25.3% and 5.6% (total 30.9%) of all high (≥9.6) landscape integrity found on NF lands. The Tongass and Chugach store approximately 33% and 3% of all biomass carbon stocks that occur in NFs with high landscape integrity. These two NFs together account for about 49%, 37%, and 18% of all bald eagle, brown bear, and gray wolf habitat found on NF lands. Gray wolf habitat extent was 4% of the total or less on remaining NFs. The Tongass and Chugach were historically wetter and cooler among NFs, and are projected to experience much larger increases in precipitation and much lower increases in maximum temperatures over the coming century. Combined with relatively low recent occurrence of wildfire, this makes permanence more likely. The Tongass and Chugach forests, along with the Pacific Northwest's high carbon density forests should be a high priority for protection and conservation to meet climate and biodiversity goals given their landscape‐scale scarcity and high value.

The Changes in Cropland Pattern Enhanced Carbon Storage in Northwest China

Northwest China has experienced dramatic changes in agricultural land area in recent years. The effects of these changes on carbon storage are unknown, and this ambiguity hinders land development policies related to carbon emissions. In this study, we evaluated the effects of annual cropland changes (expansion and abandonment) during 2000 to 2020 on carbon storage in Northwest China by using land use data, carbon density data, and statistical yearbooks using the Intergovernmental Panel on Climate Change (IPCC) method. The results indicated that the area of cropland increased by 1.47 × 106 ha from 2000 to 2020, in that the area of cropland expansion and abandonment are 3.58 × 106 and −2.11 × 106 ha, respectively. Cropland expansion was mainly from other land and grassland, and the conversion of cropland to grassland made up the largest proportion of cropland abandonment, followed by built-up land. The cropland changes resulted in a total carbon sequestration of 4.05 Tg (0.20 Tg C year−1), including a 17.66 Tg decrease and 21.71 Tg increase in carbon storage due to, respectively, cropland expansion and cropland abandonment, in which the conversion of forest to cropland (−8.60 Tg) and cropland to forest (11.16 Tg) were the main causes of the increase and decrease in carbon storage. Specifically, regional carbon storage due to cropland changes exhibited an increasing variation characteristic during 2000 to 2007, a gradually decreasing variation characteristics during 2007 to 2014, and fluctuated stabilization since then (during 2014 to 2020). In addition, the highest carbon emission was found in Xinjiang (−3.68 Tg), followed by Ningxia (−0.21 Tg) province, while Shanxi (3.44 Tg), Gansu (3.17 Tg) and Qinhai (1.33 Tg) had carbon accumulation. Overall, cropland changes acted as a carbon sink in Northwest China from 2000 to 2020. We suggest that the development of high-carbon-density lands or the conversion of low-carbon-density lands are critical to increasing future carbon sequestration due to cropland change.

Organic carbon storage and accumulation characteristics of peatlands in the Changbai Mountains, China

AbstractPeatlands are important carbon pools and stable carbon sinks in terrestrial ecosystems. Studying carbon storage and accumulation characteristics can provide a scientific basis for the conservation and restoration of peatlands. Based on the 2014–2015 survey of the Jilin Provincial Forestry Department on the carbon storage of peatlands in the Changbai Mountains, the surveyed 865 peatlands have a total area of 22,900 hm2 and carbon storage of 18,753,300 tons. There are 275 medium‐sized organic carbon (OC) stocks of peatlands (10000–100,000 tons) in this area, and their carbon storage accounts for 41.3% of the total reserves. The peatland carbon in this area is mainly distributed in the Yanbian Korean Autonomous Prefecture, valleys and the lava platform are the most important geomorphological basis for peatland deposits. The Mudanjiang River Basin has the largest carbon storage and it is dominated by a nutrient‐rich peatland. Peatlands in the Changbai Mountains formed and developed since the Holocene, and the carbon accumulation intensity is different in each stage. The average carbon density of peatlands in this area was 69.74 kg/m3 with an average value of 81.77 kg/m2 for OC accumulation per unit area. The average value of the carbon cumulative intensity of peatlands was 164.43 ton/km2 and the carbon accumulation rate of peatlands was 38.96 g/(a m2).

Coupling of Forest Carbon Densities with Landscape Patterns and Climate Change in the Lesser Khingan Mountains, Northeast China

This research investigated the effects of the forest landscape composition and spatial distribution and local climate change’s lag effects on the carbon density of stands and provides a reference for optimizing the stand structure and sustainable management of forest resources in Xinqing District, Yichun City, Heilongjiang Province, China. Using second-class forest resource survey data of the Xinqing Forestry Bureau for 2007 and 2017, the forest carbon density, landscape pattern index and local forest climate were quantified by ArcGIS10.7, Fragstats4.2 and SPSS25, and a coupling coordination degree model was constructed to reflect their correlations. The overall broadleaved mixed forest area was larger in the new green area, and the overall forest productivity had improved in the past ten years. Forest management gradually improved from nonforest to forest land, resulting in a high degree of fragmentation in the surrounding landscape. The coupling research on the forest carbon density and the forest landscape pattern index and local climate index showed that, overall, the landscape pattern and the impact of climate change on the forest carbon density had a positive interaction; adjustments and improvements can be made to the forest carbon density in the poor-condition area by combining specific situations of the landscape pattern and climate change.

Forest Carbon Storage and Carbon Sequestration Potential in Shaanxi Province, China

The carbon storage of forest vegetation plays a crucial role in the terrestrial carbon budget. The objective of this study is to elucidate the current biomass carbon storage and sequestration capacity, as well as the future carbon sequestration potential of forest ecosystems in Shaanxi Province of China, thus providing data support and policy references for sustainable forest management and the response of carbon sequestration to climate change. Based on the data obtained from the seventh and ninth forest resource inventories, the regional biomass conversion factors, and carbon measurement parameters, the biomass conversion factor method is employed to estimate the biomass storage and carbon sequestration capacity of forest ecosystems. (1) The total carbon storage of forest lands in Shaanxi Province was 285.20 Tg. The carbon storage of arbor forests, sparse woodlands, scattered forests, four-side trees, shrub woodland, and bamboo forests were 237.09 Tg, 2.93 Tg, 12.30 Tg, 5.98 Tg, 26.35 Tg, and 0.56 Tg, respectively. (2) Over the 10 years from the seventh (2005) to the ninth (2015) forest resource inventories, the carbon storage of forests increased from 207 Tg to 285 Tg, with a total increase of 78.01 Tg (37.65%), demonstrating a significant carbon sink function. (3) From 2015 to 2060, the carbon density of arbor forests will increase from 33.53 Mg/ha to 46.90 Mg/ha, and the carbon storage will increase from 237 Tg to 432 Tg. These results indicate that forests have significant net carbon sequestration capacity and can play an important role in achieving China’s carbon peak and carbon neutrality goals. Aiming for carbon neutrality, improving forest management, along with protecting and utilizing forest resources through technological innovation, will become the driving force for increasing carbon storage in Shaanxi Province in the future.

Preparation of low residual silicon content Si-SiC ceramics by binder jetting additive manufacturing and liquid silicon infiltration

Complex silicon carbide (SiC) ceramic components are difficult to fabricate due to their strong covalent bonds. Binder jetting (BJ) additive manufacturing has the outstanding advantages of high forming efficiency and no thermal deformation, especially suitable for printing complex structure SiC components. This study tried to obtain low silicon content silicon carbide ceramics by binder jetting followed by phenolic resin impregnation and pyrolysis (PRIP) and liquid silicon infiltration (LSI). BJ was used for the SiC green parts fabrication, and the highest compressive strength (7.7 ± 0.3 MPa) and lowest dimensional deviations (1.2–1.6 mm) were obtained with the printing layer thickness of 0.15 mm. Subsequently, PRIP treatments were introduced to increase the carbon content for the following LSI process. As the number of PRIP cycles increased, the carbon density of SiC/C preform increased and the porosity decreased. After the LSI treatment, the final Si-SiC composites processed with 2 PIRP cycles reached the highest flexural strength (257 ± 14.26 MPa) and the best wear resistance. This was attributed to the low residual silicon content (10.2 vol%) and almost no residual carbon. Furthermore, several complex structural components were fabricated using these methods. The preparation of complex components verifies the feasibility of BJ and LSI for manufacturing high-strength and high-precision SiC ceramics. Besides, this work hopes to provide technical guidance for the preparation of complex SiC composites in the future.

Toward quantification of active site density and size-dependent ORR activity of ZIF-derived carbons in alkaline electrolyte

ZIF-derived carbons (ZDCs) represent a novel category of non-precious metal catalysts (NPMCs) for the oxygen reduction reaction (ORR). Nevertheless, establishing the correlation between their structure and performance is challenging due to their diverse structural properties and ill-defined active site moieties. Here we investigate the effect of ZIF-67 derived carbon’s particle size and corresponding distribution of assorted nitrogen functionalities on the ORR. Our findings reveal a substantial increase in ORR activity with decreasing ZDC particle size, while the exact influence of nitrogen functionalities remains uncertain. Most importantly, the present work unveils a correlation between the ORR activity and the site density (SD) of Co-Nx within the ZDC materials, which can be attributed to the concurrently increasing SD and accessibility of Co-Nx on the ZDC particles with small sizes. The present work provides novel insights into the optimization of ZDCs as high-performance NPMCs for ORR in alkaline electrolytes.

Diffuse reflectance mid-infrared spectroscopy is viable without fine milling

While diffuse reflectance Fourier transform mid-infrared spectroscopy (mid-DRIFTS) has been established as a viable low-cost surrogate for traditional soil analyses, the assumed need for fine milling of soil samples prior to analysis is constraining the commercial appeal of this technology. Here, we reevaluate this assumption using a set of 2380 soil samples collected across North American agricultural soils. Cross-validation indicated that the best preprocessing (standard normal variate) and model form (memory-based learning) resulted in very good and nearly identical predictions for the <2 mm preparation and fine-milled preparation of these soils for total organic carbon (TOC), clay, sand, pH and bulk density (BD). Application of larger models built from the USDA NRCS mid-DRIFTS library also resulted in minimal performance differences between the two sample preps. Lower predictive performance of the existing library was attributed to less-than-perfect spectral representativeness of the library. Regardless of model form, there was very little variability between replicates of the <2 mm prep, suggesting that the lack of fine milling did not lead to more heterogeneous subsamples. Additionally, there was no relationship between residual error and soil texture, implying these results should be robust across most soil types. Overall, in agreement with other recent findings, these results suggest that routine scanning of standard <2 mm preparation does not degrade predictive performance of mid-DRIFTS-based inference systems. With good standard operating procedures including quality control and traditional analysis on a small percent of samples, mid-DRIFTS can become a routine tool in commercial soil laboratories.

Soil carbon sequestration potential of cultivated lands and its controlling factors in China

Understanding soil organic carbon (SOC) stocks and carbon sequestration potential in cultivated lands can have significant benefit for mitigating climate change and emission reduction. However, there is currently a lack of spatially explicit information on this topic in China, and our understanding of the factors that influence both saturated SOC level (SOCS) and soil organic carbon density (SOCD) remains limited. This study predicted SOCS and SOCD of cultivated lands across mainland China based on point SOC measurements, and mapped its spatial distribution using environmental variables as predictors. Based on the differentiation between SOCS and SOCD, the soil organic carbon sequestration potentials (SOCP) of cultivated land were calculated. Boosted regression trees (BRT), random forest (RF), and support vector machine (SVM) were evaluated as prediction models, and the RF model presented the best performance in predicting SOCS and SOCD based on 10-fold cross-validation. A total of 991 topsoil (0–20 cm) SOC measurements and 12 environmental variables explaining topography, climate, organism, soil properties, and human activity were used as predictors in the model. Both SOCS and SOCD suggested higher SOC levels in northeast China and lower levels in central China. The cultivated lands in China had the potential to sequester about 2.13 ± 0.96 kg m−2 (3.25 Pg) SOC in the top 20 cm soil depth. Northeastern China had the largest SOCP followed by Northern China, and Southwestern China had the lowest SOCP. The primary environmental variables that affected the spatial variation of SOCS were mean annual temperature, followed by clay content and normalized difference vegetation index (NDVI). The assessment and mapping of SOCP in China's cultivated lands holds significance importance as it can provide valuable insights to policymakers and researchers about SOCP, and aid in formulating climate change mitigation strategies.

Research on soil organic carbon pool and distribution characteristics in farmland

In this paper, the researches on the estimation of cultivgated soil organic carbon storage and its variation trend were conducted in Shayang County, a typical agricultural county in Jianghan Plain in China. The results showed that the order of soil organic carbon density (SOCD) was paddy soil &gt; moisture soil &gt; yellow brown soil, and the mean values were 4.46, 3.12 and 2.55 kg/m2, respectively. No matter which soil type, the organic carbon content of soil decreased gradually from the surface to the deep soil in the form of exponential function. By analyzing and processing the organic carbon data from 2001 to 2018, the average SOCD in the topsoil increased from 3.69 to 4.25 kg/m2, with an increase of 15.18%.

Increasing forest carbon sinks in cold and arid northeastern Tibetan Plateau

Arid forest lands account for 6 % of the world's forest area, but their carbon density and carbon storage capacity have rarely been assessed. Forest inventories provide estimates of forest stock and biomass carbon density, improve our understanding of the carbon cycle, and help us develop sustainable forest management policies in the face of climate change. Here, we carried out three forest inventories at five-year intervals from 2006 to 2016 in 104 permanent sample plots covering the Qinghai spruce (Picea crassifolia) distribution in the north slope of Qilian Mountains, northeastern Tibetan Plateau. Results shows that mean biomasses for Qinghai spruce were 133.80, 144.89, and 157.01 Mg ha−1 while biomass carbon densities were 65.52, 70.92, and 76.88 Mg C ha−1, in 2006, 2011, and 2016, respectively. This shows an increase in the Qinghai spruce carbon density of 17.34 % from 2006 to 2016. Both the precipitation and temperature play crucial roles on the increase of aboveground carbon density. The average carbon densities were different among forests with different ages and were higher for older forests. Our results show that the carbon sequestration rate for Qinghai spruce in the Qilian Mountains is significantly higher than the average rates of national forest parks in China, suggesting that this spruce forest has the potential to sequester a significant amount of carbon despite the general harsh growing conditions of cold and arid ecoregions. Our findings provide important insights that are helpful for the assessment of forest carbon for cold and arid lands.

Coal Tar Pitch-Based Porous Carbon Loaded MoS2 and Its Application in Supercapacitors.

In this paper, with coal tar pitch as the carbon source, porous carbon (PC) was prepared by one-step carbonization. To improve the energy density of coal tar pitch-based porous carbon, MoS2@PC was prepared by a hydrothermal method on a PC substrate. The effect of MoS2 loading on the structure and electrochemical properties of the sample was studied. The results show that the specific surface area of the MoS2@PC-0.3 synthesized is 3053 m2 g-1, and the large specific surface area provides sufficient attachment sites for the storage of electrolyte ions. In the three-electrode system, the specific capacitance of MoS2@PC-0.3 at 0.5 A g-1 is 422.5 F g-1, and the magnification performance is 57.3% at 20 A g-1. After 10,000 charge/discharge cycles, the capacitance retention rate of the sample is 76.73%, with the Coulombic efficiency being 100%. In the two-electrode test system, the specific capacitance of MoS2@PC-0.3 at 0.5 A g-1 is 321.4 F g-1, with the power density and energy density being 500 W kg-1 and 44.6 Wh kg-1, respectively. At a current density of 20 A g-1, the capacitance retention rate is 87.69% after 10,000 cycles. This study greatly improves the energy density of PC as the electrode material of supercapacitors.

Biodiversity and carbon conservation under the ecosystem stability of tropical forests

Although efforts to protect high levels of biodiversity and carbon storage can greatly increase the effectiveness of species loss and climate change mitigation, there is evidence indicating a trade-off scenario for their conservation at regional scale. Decisions making in trade-off scenarios can be supported by including information on the ecosystem stability of tropical forests (i.e., the ability of the ecosystem to maintain its function over time). Forest stability may affect biodiversity integrity and the residence time of carbon stored in tree biomass. Here, we assess the stability of old-growth forests' productivity by analyzing a 19-year time series of the Normalized Difference Vegetation Index (NDVI). We also used geoprocessing tools to analyze the overlap among forest-specialist vertebrate species richness, carbon density, and stability of old-growth forest throughout the Brazilian Atlantic Forest. We used model selection to find environmental predictors of the stability of primary productivity and build a predictive map of potential stability. Then, we overlapped maps of potential stability, species richness of forest-specialist vertebrates, and carbon density to identify hotspot areas of biodiversity and carbon density occurring at highest and lowest potential stability. We found that forest stability increases from north to south along the Atlantic Forest. High biodiversity occurs mainly at low stability while high carbon stock at high stability. Spatial overlap of the hotspots, where conservation co-benefits high biodiversity and carbon stock, occurs mostly at high stability in a large area along part of the coast and in smaller inland areas of the southern region. Most of the hotspots with low stability for biodiversity, carbon stock and combination of both are found in unprotected areas. Hence, the strategic mitigation of species loss and carbon emissions lies in three approaches: prioritizing forest protection in unprotected hotspots; implementing forest management practices in protected hotspots with low stability; and enforcing a comprehensive regime of protection and management in hotspots that exhibit low stability. Focused on forest stability, these approaches involve ecosystem-based planning offering Brazil's government effective strategies to fulfill its commitments in biodiversity conservation and carbon emission reduction.