Iron (Fe) minerals possess a huge specific surface area and high adsorption affinity, usually considered as rust tanks of organic carbon (OC), playing an important role in global carbon storage. Microorganisms can change the chemical form of Fe by producing Fe-chelating agents such as side chains and form a stable complex with Fe(III), which makes it easier for microorganisms to use. However, in seasonal frozen soil thawing, the succession of soil Fe-cycling microbial communities and their coupling relationship with Fe oxides and Fe-bound organic carbon (Fe-OC) remains unclear. We characterized changes in the Fe phase, Fe-OC, Fe-oxidizing bacteria (FeOB), and Fe-reducing bacteria (FeRB) in the subsoil and analyzed the microbial mechanism underlying Fe-OC changes in alpine grassland by constructing a composite structural equation model (SEM). We found that the Fe(III) content consistently exceeded that of Fe(II). Among the three types of Fe oxides, organically complex Fe (Fe-p) decreased from 2.54 to 2.30 gkg(-1), whereas the opposite trend was observed for poorly crystalline Fe (Fe-o). The Fe-OC content also decreased (from 10.31 to 9.47 gkg(-1); p < 0.05). Fe-cycling microorganisms were markedly affected by the thawing of frozen soil (except FeRB). Fe-p and Feo directly affected changes in Fe-OC. Soil moisture (SM) and FeOB were significant indirect factors affecting Fe-OC changes. Freeze-thaw changes in the subsoil of alpine grassland in Central Asia significantly affected FeOB and Fe oxides, thus affecting the Fe-OC content. To the best of our knowledge, this was the first study to examine the influence of Fe-cycling microorganisms on the Fe phase and Fe-OC in the soil of alpine grassland in Central Asia. Overall, our findings provide scientific clues for exploring the biogeochemical cycle process in future climate change.

Alpine grassland ecosystems play a crucial role in the global carbon (C) balance by contributing to the soil organic carbon (SOC) pool; thus, quantifying SOC stocks in these ecosystems is essential for understanding potential gains or losses in soil C under the threat of climate change and anthropogenic activities. Remote sensing plays a vital role in estimating SOC stocks; however, identifying reliable remote sensing proxies to enhance SOC prediction remains a challenge. Information on soil C cycling proxies can reveal how the balance between C inputs and outputs affects SOC. Therefore, these proxies could be effective indicators of SOC variations. In this study, we explored the potential of satellite-derived attributes related to soil C cycling proxies for predicting SOC stocks. We derived remote sensing indices such as gross primary production, soil respiration, soil moisture, land surface temperature, radiation, and soil disturbance and assessed the relationships between these indices and SOC stocks via partial least squares structural equation modeling (PLS-SEM). We evaluated the effectiveness of these indices in predicting SOC stocks, we compared PLS-SEM and quantile regression forest (QRF) models across different variable combinations, including static, intra-annual, and inter-annual information. The PLS-SEM results demonstrated the suitability of the derived remote sensing indices and their interactions in reflecting processes related to soil C balance. The QRF models, using these indices, achieved promising prediction accuracies, with a coefficient of determination (R2) of 0.54 and a root mean square error (RMSE) of 0.79 kg m-2 at the topmost 10 cm of soil. However, the prediction performance generally decreased with increasing soil depth, up to 30 cm. The results also revealed that adding intra- and inter-annual information to remotely sensed proxies did not increase the prediction accuracy. Our study revealed that gross primary production, soil respiration, soil moisture, land surface temperature, radiation, and soil disturbance are effective proxies for representing factors influencing soil C balance and mapping SOC stocks in alpine grasslands.

Elemental carbon (EC), also known as black carbon, plays an important role in climate change. Accurately assessing EC concentration in aerosols remains challenging due to the overestimations caused by carbonates and organic carbon (OC) during thermal-optical measurement in the Tibetan Plateau (TP). This study evaluates the extent of EC overestimated by carbonates and OC at four remote sites (Nyalamu, Lulang, Everest and Ngari) in southern and western of the TP using different treatments. The average overestimation of EC concentration due to acid treatment was consistent across all sites (25.5 f 2.4 %). After correction, the proportion of EC overestimated by carbonates were approximately 8.5 f 7.3 %, 12.3 f 6.9 %, 18.1 f 11.8 % and 22.7 f 13.3 %, respectively, revealing an increasing trend from humid to arid regions. Methanol-soluble OC (MSOC) concentrations were significantly correlated with the reduction of EC concentrations, indicating that the methanol extraction effectively mitigates EC overestimation. Seasonal variation of carbonaceous aerosol concentrations was significantly affected by sources from South Asia. Despite the variations in climate and aerosol sources, the average overestimations of measured EC concentration by carbonates and OC were similar at Nyalamu (49.4 f 14.0 %), Lulang (47.8 f 8.4 %), Everest (48.7 f 15.9 %) and Ngari (49.3 f 13.7 %) sites. Therefore, the actual EC concentrations were only about 51.2 f 13.1 % of the original values. This estimation will significantly enhance the contribution of brown carbon (BrC) to radiative forcing relative to EC, highlighting a critical area for future research. Investigating the actual concentrations of EC in the TP provides critical data to support model simulation and validate model accuracy, further enhancing our understanding of EC's impacts on climate warming and glacier melting.

The abrupt warming events punctuating the Termination 1 (about 11.7-18 ka Before Present, BP) were marked by sharp rises in the concentration of atmospheric methane (CH4). The role of permafrost organic carbon (OC) in these rises is still debated, with studies based on top-down measurements of radiocarbon (14C) content of CH(4 )trapped in ice cores suggesting minimum contributions from old and strongly C-14-depleted permafrost OC. However, organic matter from permafrost can exhibit a continuum of C-14 ages (contemporaneous to >50 ky). Here, we investigate the large-scale permafrost remobilization at the Younger Dryas-Preboreal transition (ca. 11.6 ka BP) using the sedimentary record deposited at the Lena River paleo-outlet (Arctic Ocean) to reflect permafrost destabilization in this vast drainage basin. Terrestrial OC was isolated from sediments and characterized geochemically measuring delta C-13, Delta C-14, and lignin phenol molecular fossils. Results indicate massive remobilization of relatively young (about 2,600 years) permafrost OC from inland Siberia after abrupt warming triggered severe active layer deepening. Methane emissions from this young fraction of permafrost OC contributed to the deglacial CH4 rise. This study stresses that underestimating permafrost complexities may affect our comprehension of the deglacial permafrost OC-climate feedback and helps understand how modern permafrost systems may react to rapid warming events, including enhanced CH4 emissions that would amplify anthropogenic climate change.

High uncertainty in optical properties of black carbon (BC) involving heterogeneous chemistry has recently attracted increasing attention in the field of atmospheric climatology. To fill the gap in BC optical knowledge so as to estimate more accurate climate effects and serve the response to global warming, it is beneficial to conduct site-level studies on BC light absorption enhancement (E-abs) characteristics. Real-time surface gas and particulate pollutant observations during the summer and winter over Wuhan were utilized for the analysis of E-abs simulated by minimum R squared (MRS), considering two distinct atmospheric conditions (2015 and 2017). In general, differences in aerosol emissions led to E-abs differential behaviors. The summer average of E-abs (1.92 +/- 0.55) in 2015 was higher than the winter average (1.27 +/- 0.42), while the average (1.11 +/- 0.20) in 2017 summer was lower than that (1.67 +/- 0.69) in winter. E-abs and R-BC (representing the mass ratio of non-refractory constituents to elemental carbon) constraints suggest that E-abs increased with the increase in R-BC under the ambient condition enriched by secondary inorganic aerosol (SIA), with a maximum growth rate of 70.6% in 2015 summer. However, E-abs demonstrated a negative trend against R-BC in 2017 winter due to the more complicated mixing state. The result arose from the opposite impact of hygroscopic SIA and absorbing OC/irregular distributed coatings on amplifying the light absorbency of BC. Furthermore, sensitivity analysis revealed a robust positive correlation (R > 0.9) between aerosol chemical compositions (including sulfate, nitrate, ammonium and secondary organic carbon), which could be significantly perturbed by only a small fraction of absorbing materials or restructuring BC through gaps filling. The above findings not only deepen the understanding of BC, but also provide useful information for the scientific decision-making in government to mitigate particulate pollution and obtain more precise BC radiative forcing.

Wildfire strongly influences permafrost environment and soil organic carbon (SOC) pool. In this study, we reviewed the effects of fire severity, time after a fire, and frequency on SOC in boreal permafrost regions. This review highlighted several key points: the effect of wildfires on SOC increased with an increase of fire severity, and the amount of vegetation returned and surface organic matter replenished was less in a short term, which resulted in a significantly lower SOC content compared to that of before the fire. Within a short period after fire, the SOC in near-surface permafrost and the active layer decreased significantly due to the loss of above ground biomass, permafrost thaw, and increased microbial decomposition; as the years pass after a fire, the SOC gradually accumulates due to the contributions of litter layer accumulation and rooting systems from different stages of succession. The increase in fire frequency accelerated permafrost thawing and the formation of thermokarst, resulting in the rapid release of a large amount of soil carbon and reduced SOC storage. Therefore, the study on the effects of wildfires on SOC in the boreal permafrost region is of great significance to understanding and quantifying the carbon balance of the ecosystem.

Soil organic carbon (SOC) plays a vital role in the global carbon cycle and soil quality assessment. The Qinghai-Tibet Plateau is one of the largest plateaus in the world. Therefore, in this region, SOC density and the spatial distribution of SOC are highly sensitive to climate change and human intervention. Given the insufficient understanding of the spatial distribution of SOC density in the Qinghai-Tibet Plateau, this study utilized machine learning (ML) algorithms to estimate the density and distribution pattern of SOC density in the region. In this study, we first collected multisource data, such as optical remote sensing data, synthetic aperture radar) (SAR) data, and other environmental variables, including socioeconomic factors, topographic factors, climate factors, and soil properties. Then, we used ML algorithms, namely random forest (RF), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM), to estimate the topsoil SOC density and spatial distribution patterns of SOC density. We also aimed to investigate any driving factors. The results are as follows: (1) The average SOC density is 5.30 kg/m(2). (2) Among the three ML algorithms used, LightGBM showed the highest validation accuracy (R-2 = 0.7537, RMSE = 2.4928 kgC/m(2), MAE = 1.7195). (3) The normalized difference vegetation index (NDVI), valley depth (VD), and temperature are crucial in predicting the spatial distribution of topsoil SOC density. Feature importance analyses conducted using the three ML models all showed these factors to be among the top three in importance, with contribution rates of 14.08%, 12.29%, and 14.06%; 17.32%, 20.73%, and 24.62%; and 16.72%, 11.96%, and 20.03%. (4) Spatially, the southeastern part of the Qinghai-Tibet Plateau has the highest topsoil SOC density, with recorded values ranging from 8.41 kg/m(2) to 13.2 kg/m(2), while the northwestern part has the lowest density, with recorded values ranging from 0.85 kg/m(2) to 2.88 kg/m(2). Different land cover types showed varying SOC density values, with forests and grasslands having higher SOC densities compared to urban and bare land areas. The findings of this study provide a scientific basis for future soil resource management and improved carbon sequestration accounting in the Qinghai-Tibet Plateau.

Carbonaceous particles have been confirmed as major components of ambient aerosols in urban environments and are related to climate impacts and environmental and health effects. In this study, we collected different-size particulate matter (PM) samples (PM1, PM2.5, and PM10) at an urban site in Lanzhou, northwest China, during three discontinuous one-month periods (January, April, and July) of 2019. We measured the concentrations and potential transport pathways of carbonaceous aerosols in PM1, PM2.5, and PM10 size fractions. The average concentrations of OC (organic carbon) and EC (elemental carbon) in PM1, PM2.5, and PM10 were 6.98 +/- 3.71 and 2.11 +/- 1.34 mu g/m(3), 8.6 +/- 5.09 and 2.55 +/- 1.44 mu g/m(3), and 11.6 +/- 5.72 and 4.01 +/- 1.72 mu g/m(3). The OC and EC concentrations in PM1, PM2.5, and PM10 had similar seasonal trends, with higher values in winter due to the favorable meteorology for accumulating pollutants and urban-increased emissions from heating. Precipitation played a key role in scavenge pollutants, resulting in lower OC and EC concentrations in summer. The OC/EC ratios and principal component analysis (PCA) showed that the dominant pollution sources of carbon components in the PMs in Lanzhou were biomass burning, coal combustion, and diesel and gasoline vehicle emissions; and the backward trajectory and concentration weight trajectory (CWT) analysis further suggested that the primary pollution source of EC in Lanzhou was local fossil fuel combustion.

In order to foresee the impact of permafrost thaw on CO2 emissions by high-latitude rivers, in-situ measurements across a permafrost and climate/vegetation gradient, coupled with assessment of possible physico-chemical and landscape controlling factors are necessary. Here we chose 34 catchments of variable stream order (1 to 9) and watershed size (1 to >10(5) km(2)) located across a permafrost and biome gradient in the Western Siberian Lowland (WSL), from the permafrost-free southern taiga to the continuous permafrost zone of tundra. Across the southnorth transect, maximal CO2 emissions (2.2 +/- 1.1 g C-CO2 m(-2) d(-1)) occurred from rivers of the discontinuous/sporadic permafrost zone, i.e., geographical permafrost thawing boundary. In this transitional zone, fluvial C emission to downstream export ratio was as high as 8.0, which greatly (x 10) exceeded the ratio in the permafrost free and continuous permafrost zones. Such a high evasion at the permafrost thawing front can stem from an optimal combination of multiple environmental factors: maximal active layer thickness, sizable C stock in soils, and mobilization of labile organic nutrients from dispersed peat ice that enhanced DOC and POC processing in the water column, likely due to priming effect. Via a substituting space for time approach, we foresee an increase in CO2 and CH4 fluvial evasion in the continuous and discontinuous permafrost zone, which is notably linked to the greening of tundra increases in biomass of the riparian vegetation, river water warming and thermokarst lake formation on the watershed.

Carbonaceous particles play a crucial role in atmospheric radiative forcing. However, our understanding of the behavior and sources of carbonaceous particles in remote regions remains limited. The Tibetan Plateau (TP) is a typical remote region that receives long-range transport of carbonaceous particles from severely polluted areas such as South Asia. Based on carbon isotopic compositions ( Delta 14 C/ delta 13 C) of water -insoluble particulate carbon (IPC) in total suspended particle (TSP), PM 2.5 , and precipitation samples collected during 2020 - 22 at the Nam Co Station, a remote site in the inner TP, the following results were achieved: First, fossil fuel contributions ( f fossil ) to IPC in TSP samples (28.60 +/- 9.52 %) were higher than that of precipitation samples (23.11 +/- 8.60 %), and it is estimated that the scavenging ratio of IPC from non -fossil fuel sources was around 2 times that from fossil fuel combustion during the monsoon season. The f fossil of IPC in both TSP and PM 2.5 samples peaked during the monsoon season. Because heavy precipitation during the monsoon season scavenges large amounts of long-range transported carbonaceous particles, the contribution of local emissions from the TP largely outweighs that from South Asia during this season. The results of the IPC source apportionment based on Delta 14 C and delta 13 C in PM 2.5 samples showed that the highest contribution of liquid fossil fuel combustion also occurred in the monsoon season, reflecting increased human activities (e.g., tourism) on the TP during this period. The results of this study highlight the longer lifetime of fossil fuel -sourced IPC in the atmosphere than that of non -fossil fuel sources in the inner TP and the importance of local emissions from the TP during the monsoon season. The findings provide new knowledge for model improvement and mitigation of carbonaceous particles.