The global climate is becoming warmer and wetter, and the physical properties of saline soil are easily affected by the external climate changes, which can lead to complex water-heat-salt-mechanics (WHSM) coupling effect within the soil. However, in the context of climate change, the current research on the surface energy balance process and laws of water and salt migration in saline soil are not well understood. Moreover, testing systems for studying the impact of external meteorological factors on the properties of saline soil are lacking. Therefore, this study developed a testing system that can simulate the environmental coupling effect of the WHSM in saline soil against a background of climate change. Based on meteorological data from the Hexi District in the seasonal permafrost region of China, the testing system was used to clarify the characteristics of surface energy and WHSM coupling changes in sulfate saline soil in Hexi District during the transition of the four seasons throughout the year. In addition, the reliability of the testing system was also verified using testing data. The results showed that the surface albedo of sulfate saline soil in the Hexi region was the highest in winter, with the highest exceeding 0.4. Owing to changes in the external environment, the heat flux in the sulfate saline soil in spring, summer, and early autumn was positive, while the heat flux in late autumn and winter was mainly negative. During the transition of the four seasons throughout the year in the Hexi region, the trends of soil temperature, volumetric water content, and conductivity were similar, first increasing and then decreasing. As the soil depth increased, the influence of external environmental factors on soil temperature, volumetric water content, and conductivity gradually weakened, and the hysteresis effect became more pronounced. Moreover, owing to the influence of external environmental temperature, salt expansion in the positive temperature stage accounts for approximately five times the salt-frost heave deformation in the negative temperature stage, indicating that the deformation of sulfate saline soil in the Hexi region is mainly caused by salt expansion. Therefore, to reduce the impact of external climate change on engineering buildings and agriculture in salted seasonal permafrost regions, appropriate measures and management methods should be adopted to minimize salt expansion and soil salinization.

Glacial responses to climate change exhibit considerable heterogeneity. Although global glaciers are generally thinning and retreat, glaciers in the Karakoram region are distinct in their surging or advancing, exhibiting nearly zero or positive mass balance-a phenomenon known as the Karakoram Anomaly. This anomaly has sparked significant scientific interest, prompting extensive research into glacier anomalies. However, the dynamics of the Karakoram anomaly, particularly its evolution and persistence, remain insufficiently explored. In this study, we employed Landsat reflectance data and Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A3 albedo products to developed high-resolution albedo retrieval models using two machine learning (ML) regressions--random forest regression (RFR) and back-propagation neural network regression (BPNNR). The optimal BPNNR model (Pearson correlation coefficient [r] = 0.77-0.97, unbiased root mean squared error [ubRMSE] = 0.056-0.077, RMSE = 0.055-0.168, Bias = -0.149 similar to -0.001) was implemented on the Google Earth Engine cloud-based platform to estimate summer albedo at a 30-m resolution for the Karakoram region from 1990 to 2021. Validation against in-situ albedo measurements on three glaciers (Batura, Mulungutti and Yala Glacier) demonstrated that the model achieved an average ubRMSE of 0.069 (p < 0.001), with RMSE and ubRMSE improvements of 0.027 compared to MODIS albedo products. The high-resolution data was then used to identify firn/snow extents using a 0.37 threshold, facilitating the extraction of long-term firn-line altitudes (FLA) to indicate the glacier dynamics. Our findings revealed that a consistent decline in summer albedo across the Karakoram over the past three decades, signifying a darkening of glacier surfaces that increased solar radiation absorption and intensified melting. The reduction in albedo showed spatial heterogeneity, with slower reductions in the western and central Karakoram (-0.0005-0.0005 yr(-1)) compared to the eastern Karakoram (-0.006 similar to -0.01 yr(-1)). Notably, surge- or advance-type glaciers, avalanche-fed glaciers and debris-covered glaciers exhibited slower albedo reduction rates, which decreased further with increasing glacier size. Additionally, albedo reduction accelerated with altitude, peaking near the equilibrium-line altitude. Fluctuations in the albedo-derived FLAs suggest a transition in the dynamics of Karakoram glaciers from anomalous behavior to retreat. Most glaciers exhibited anomalous behavior from 1995 to 2010, peaking in 2003, but they have shown signs of retreat since the 2010s, marking the end of the Karakoram anomaly. These insights deepen our understanding of the Karakoram anomaly and provide a theoretical basis for assessing the effect of glacier anomaly to retreat dynamics on the water resources and adaptation strategies for the Indus and Tarim Rivers.

Aviation emissions contribute to climate change and local air pollution, with important contributions from non-CO2 emissions. These exhibit diverse impacts on atmospheric chemistry and radiative forcing (RF), varying with location, altitude, and time. Assessments of local mitigation strategies with global emission metrics may overlook this variability, but detailed studies of aviation emissions in areas smaller than continents are scarce. Integrating the AviTeam emission model and OsloCTM3, we quantify CO2, NOx, BC, OC, and SOx emissions, tropospheric concentration changes, RF, region-specific metrics, and assess alternative fuels for Norwegian domestic aviation. Mitigation potentials fora fuel switch to LH2 differ by up to 3.1 x 108 kgCO2-equivalents (GWP20) when using region-specific compared to global metrics. These differences result from a lower, region- specific contribution of non-CO2 emissions, particularly related to NOx. This study underscores the importance of accounting for non-CO2 variability in regional assessments, whether through region-specific metrics or advanced atmospheric modelling techniques.

Snow distribution has been altered over the past decades under global warming, with a significant reduction in duration and extent of snow cover and an increase in unprecedented snowstorms across large areas in cold regions. The altered snow conditions are likely to have immediate (in winter) and carry-over or legacy (which an extended effect might continue in the following spring, summer and autumn) impacts on soil processes and functioning, but a quantification of the legacy effect of snow coverage alternation is still lacking. Furthermore, studies investigating the effect of snow cover changes on soil respiration, soil carbon pools and microbial activity are increasing, but contrasting results of different studies makes it difficult to assess the overall effect of snow cover changes and the underlying mechanisms, thus a systematic and comprehensive meta-analysis is required. In this study, we synthesized the results from 60 papers based on field snow manipulation experiments and conducted a meta-analysis to evaluate immediate and prolonged effects on eight variables related to soil carbon dynamics and microbial activity to snow coverage alternation. Results showed that snow removal had no significant effect on soil respiration, but increased dissolved organic carbon (DOC) (11.5%) and fungal abundance (32.0%). By contrast, snow addition significantly increased soil respiration (16.3%) and microbial biomass carbon (MBC) (6.6%). Snow addition had immediate and prolonged impacts on soil carbon dynamics and microbial activity lasting from winter to the following autumn, whereas an effect of snow removal on total organic carbon (TOC) and DOC was detectable only in the following spring. Snow depth, ecosystem and soil types determined the extent of the impact of snow treatments on soil respiration, DOC, MBC and microbial biomass nitrogen (MBN). Our findings provide critical insights into understanding how changes in snow coverage affect soil respiration and microbial activity. We suggest future field-based experiments to enhance our understanding the effect of climate change on soil processes and functioning in the winter and the following seasons.

Microplastics in drinking water captured widespread attention following reports of widespread detection around the world. Concerns have been raised about the potential adverse effects of microplastics in drinking water on human health. Given the widespread interest in this research topic, there is an urgent need to compile existing data and assess current knowledge. This paper provides a systematic review of studies on microplastics in drinking water, their evidence, key findings, knowledge gaps, and research needs. The data collected show that microplastics are widespread in drinking water, with large variations in reported concentrations. Standardized methodologies of sampling and analysis are urgently needed. There were more fibrous and fragmented microplastics, with the majority being <10 mu m in size and composed of polyester, polyethylene, polypropylene, and polystyrene. Little attention has been paid to the color of microplastics. More research is needed to understand the occurrence and transfer of microplastics throughout the water supply chain and the treatment efficiency of drinking water treatment plants (DWTPs). Methods capable of analyzing microplastics <10 mu m and nanoplastics are urgently needed. Potential ecological assessment models for microplastics currently in use need to be improved to take into account the complexity and specificity of microplastics.

Alpine areas play a substantial role in supplying the world's water resources. The hydrological cycle in these areas has been experiencing notable alterations owing to climate change. However, the present comprehension of how water yield capacity (WYC) responds to climate change at varying elevations within alpine basins is impeded due to the complex terrain and simplified representation of coupled water-energy processes in traditional hydrological models. Through integrating the Weather Research and Forecasting hydrological modeling system (WRF-Hydro) and Budyko framework, this study quantitatively assessed the influence of climate change on WYC across different elevations in a Tibetan Plateau alpine basin, named Xiying River Basin (XRB). The results indicated the WRF-Hydro adeptly reproduced the streamflow and evapotranspiration (ET) within the XRB. The combination of the WRF-Hydro model allows the Budyko framework, traditionally limited to the watershed scale, to be applicable at the grid scale. We found that the XRB underwent substantial climate change from 1980 to 2015, and there existed an abrupt change in 1997. Climate change caused the WYC reduced by -17.06% during the post-1997 period (1998-2015), compared to the pre-1997 period (1980-1997). Additionally, all elevation bands displayed the WYC reductions, ranging from -3.69% to -24.31%, with diminishing magnitude at higher elevations. This WYC reduction is primarily attributed to an increase of 11.38% in ET. Although ET and precipitation increased with elevation, the former consistently exceeded the latter, resulting in decreasing water deficits and an altitudinal gradient of the WYC reduction. Besides the increasing vapor pressure deficit and decreasing albedo, our findings emphasized the significance of precipitation event timing in influencing WYC. The longer time intervals between precipitation events in the XRB led to more soil moisture loss through ET. These findings shed valuable implications for policymakers, offering guidance for the formulation of sustainable policies for water resource management and ecological conservation.

Background Stable carbon isotope composition (delta C-13(p)) can be used to estimate the changes in intrinsic water use efficiency (iWUE) in plants, which helps us to better understand plants' response strategies to climate change. This study focused on the variations in delta C-13(p) and iWUE for the different life-form plants (i.e., herbs, shrubs, and trees) along an altitudinal gradient (3300, 3600, 3900, 4100, 4300, and 4500 m) on the eastern slope of Yulong Snow Mountain, southeastern margin of the Qinghai-Tibet Plateau. The response mechanisms of delta C-13(p) and iWUE for different life-form plants to altitude were thoroughly analyzed in this mountain ecosystem. Results The delta C-13(p) values of plants on the eastern slopes of Yulong Snow Mountain ranged from - 30.4 parts per thousand to - 26.55 parts per thousand, with a mean of - 28.02 parts per thousand, indicating a dominance of C-3 plants. The delta C-13(p) and iWUE values varied among different life-form plants in the order of herbs > shrubs > trees, particularly in 3600, 3900, and 4300 m. The delta C-13(p) and iWUE values for herbs and shrubs increased with altitude and were mainly controlled by air temperature. The two parameters for trees exhibited a trend of initial decrease followed by an increase with altitude. Below 3900 m, the delta C-13(p) and iWUE values decreased with altitude, influenced by soil moisture. However, above 3900 m, the two parameters increased with altitude, mainly regulated by air temperature. In addition, iWUE was positively correlated with leaf P content but negatively correlated with leaf N:P ratio, especially for herbs and trees, suggesting that P plays a key role in modulating iWUE in this region. Conclusions The differentiated responses of water availability for different life-form plants to a higher altitudinal gradient are regulated by air temperature, soil moisture, and leaf P content in the Yulong Snow Mountain. These results provide valuable insights into understanding the water-carbon relationships in high-altitude ecosystems.

The deposition of light absorbing impurities (LAIs) (e.g., black carbon (BC), organic carbon (OC), mineral dust (MD)) on snow is an important attribution to accelerate snowmelt across the northern Xinjiang, China. At present, there is still a lack of understanding of the LAIs concentration, elution and enrichment process in snow cover over Xinjiang. Based on these, continuously sampling during two years carried out to investigate the concentrations, impacts and potential sources of LAIs in snow at Kuwei Station in the southern Altai Mountains. The average concentrations of BC, OC and MD in the surface snow were 2787 +/- 2334 ng g(-1), 6130 +/- 6127 ng g(-1), and 70.03 +/- 62.59 mu g g(-1), respectively, which dramatically increased along with snowmelt intensified, reflecting a significant enrichment process of LAIs at the snow surface. Besides, high LAIs concentrations also found in the subsurface and melting layers of the snowpit, reflecting the elution and redistribution of LAIs. With the simulation of the SNow ICe Aerosol Radiative model, BC was the main dominant factor in reducing snow albedo and radiative forcing (RF), its impact was more remarkable in the snowmelt period. The average contribution rates of BC, MD and BC + MD to snow albedo reduction increased by 20.0 +/- 1.9%, 13.0 +/- 0.2%, and 20.5 +/- 2.3% in spring compared with that in winter; meanwhile, the corresponding average RFs increased by 15.8 +/- 3.4 W m(-2), 4.7 +/- 0.3 W m(-2) and 16.4 +/- 3.2 W m(-2), respectively. Changes in the number of snowmelt days caused by BC and MD decreased by 3.0 +/- 0.4 d to 8.3 +/- 1.3 d. It indicated that surface enrichment of LAIs during snow melting might accelerate snowmelt further. Weather Research and Forecasting Chemistry model showed that the resident emission was the main potential source of BC and OC in snow. This implied that the mitigation of intensive snowmelt needs to mainly reduce resident emission of LAIs in the future. (C) 2020 Elsevier Ltd. All rights reserved.

The southeastern Tibetan Plateau (SETP), which hosts the most extensive marine glaciers on the Tibetan Plateau (TP), exhibits enhanced sensitivity to climatic fluctuations. Under global warming, persistent glacier mass depletion within the SETP poses a risk to water resource security and sustainability in adjacent nations and regions. This study deployed a high-precision ICESat-2 satellite altimetry technique to evaluate SETP glacier thickness changes from 2018 to 2022. Our results show that the average change rate in glacier thickness in the SETP is -0.91 +/- 0.18 m/yr, and the corresponding glacier mass change is -7.61 +/- 1.52 Gt/yr. In the SETP, the glacier mass loss obtained via ICESat-2 data is larger than the mass change in total land water storage observed by the Gravity Recovery and Climate Experiment follow-on satellite (GRACE-FO), -5.13 +/- 2.55 Gt/yr, which underscores the changes occurring in other land water components, including snow (-0.44 +/- 0.09 Gt/yr), lakes (-0.06 +/- 0.02 Gt/yr), soil moisture (1.88 +/- 1.83 Gt/yr), and groundwater (1.45 +/- 0.70 Gt/yr), with a closure error of -0.35 Gt/yr. This demonstrates that this dramatic glacier mass loss is the main reason for the decrease in total land water storage in the SETP. Generally, there are decreasing trends in solid water storage (glacier and snow) against stable or increasing trends in liquid water storage (lakes, soil moisture, and groundwater) in the SETP. This persistent decrease in solid water is linked to the enhanced melting induced by rising temperatures. Given the decreasing trend in summer precipitation, the surge in liquid water in the SETP should be principally ascribed to the increased melting of solid water.

Extensive, detailed information on the spatial distribution of active layer thickness (ALT) in northern Alaska and how it evolves over time could greatly aid efforts to assess the effects of climate change on the region and also help to quantify greenhouse gas emissions generated due to permafrost thaw. For this reason, we have been developing high-resolution maps of ALT throughout northern Alaska. The maps are produced by upscaling from high-resolution swaths of estimated ALT retrieved from airborne P-band synthetic aperture radar (SAR) images collected for three different years. The upscaling was accomplished by using hundreds of thousands of randomly selected samples from the SAR-derived swaths of ALT to train a machine learning regression algorithm supported by numerous spatial data layers. In order to validate the maps, thousands of randomly selected samples of SAR-derived ALT were excluded from the training in order to serve as validation pixels; error performance calculations relative to these samples yielded root-mean-square errors (RMSEs) of 7.5-9.1 cm, with bias errors of magnitude under 0.1 cm. The maps were also compared to ALT measurements collected at a number of in situ test sites; error performance relative to the site measurements yielded RMSEs of approximately 11-12 cm and bias of 2.7-6.5 cm. These data are being used to investigate regional patterns and underlying physical controls affecting permafrost degradation in the tundra biome.