Air pollution is a global health issue, and events like forest fires, agricultural burning, dust storms, and fireworks can significantly worsen it. Festivals involving fireworks and wood-log fires, such as Diwali and Holi, are key examples of events that impact local air quality. During Holi, the ritual of Holika involves burning of biomass that releases large amounts of aerosols and other pollutants. To assess the impact of Holika burning, observations were conducted from March 5th to March 18th, 2017. On March 12th, 2017, around 1.8 million kg of wood and biomass were openly burned in about 2250 units of Holika, located in and around the Varanasi city (25.23 N, 82.97 E, similar to 82.20 m amsl). As the Holika burning event began the impact on the Black Carbon (BC), particulate matter 10 & 2.5 (PM10 and PM2.5), sulphur dioxide (SO2), oxides of nitrogen (NOx), ozone (O-3) and carbon monoxide (CO) concentration were observed. Thorough optical investigations have been conducted to better comprehend the radiative effects of aerosols produced due to Holika burning on the environment. The measured AOD at 500 nm values were 0.315 +/- 0.072, 0.392, and 0.329 +/- 0.037, while the BC mass was 7.09 +/- 1.78, 9.95, and 7.18 +/- 0.27 mu g/m(3) for the pre-Holika, Holika, and post-Holika periods. Aerosol radiative forcing at the top of the atmosphere (ARF-TOA), at the surface (ARF-SUR), and in the atmosphere (ARF-ATM) are 2.46 +/- 4.15, -40.22 +/- 2.35, and 42.68 +/- 4.12 W/m(2) for pre-Holika, 6.34, -53.45, and 59.80 W/m(2) for Holika, and 5.50 +/- 0.97, -47.11 +/- 5.20, and 52.61 +/- 6.17 W/m(2) for post-Holika burning. These intense observation and analysis revealed that Holika burning adversely impacts AQI, BC concentration and effects climate in terms of ARF and heating rate.

Glaciers playa vital role in providing water resources for drinking, agriculture, and hydro-electricity in many mountainous regions. As global warming progresses, accurately reconstructing long-term glacier mass changes and comprehending their intricate dynamic relationships with environmental variables are imperative for sustaining livelihoods in these regions. This paper presents the use of eXplainable Machine Learning (XML) models with GRACE and GRACE-FO data to reconstruct long-term monthly glacier mass changes in the Upper Yukon Watershed (UYW), Canada. We utilized the H2O-AutoML regression tools to identify the best performing Machine Learning (ML) model for filling missing data and predicting glacier mass changes from hydroclimatic data. The most accurate predictive model in this study, the Gradient Boosting Machine, coupled with explanatory methods based on SHapley Additive eXplanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) analyses, led to automated XML models. The XML unveiled and ranked key predictors of glacier mass changes in the UYW, indicating a decrease since 2014. Analysis showed decreases in snow water equivalent, soil moisture storage, and albedo, along with increases in rainfall flux and air temperature were the main drivers of glacier mass loss. A probabilistic analysis hinging on these drivers suggested that the influence of the key hydrological features is more critical than the key meteorological features. Examination of climatic oscillations showed that high positive anomalies in sea surface temperature are correlated with rapid depletion in glacier mass and soil moisture, as identified by XML. Integrating H2OAutoML with SHAP and LIME not only achieved high prediction accuracy but also enhanced the explainability of the underlying hydroclimatic processes of glacier mass change reconstruction from GRACE and GRACE-FO data in the UYW. This automated XML framework is applicable globally, contingent upon sufficient high-quality data for model training and validation.

Northeastern China (NEC) is the largest grain base in China. Improving understanding of the effect of climate change on grain production over NEC is conducive to providing immediate response strategies for grain production. In this study, the relationships of the maize production with the dry state during the different maize growth stage have been investigated using the year-to-year increment method. Results showed that the severe drought that occurred from the jointing to maturity period have exerted severe effects on the maize growth. Further analysis indicated that the sea surface temperature (SST) anomalies over North Atlantic and Maritime Continent in later spring are the important factors affecting the summer droughts over NEC. The late spring SST anomaly over North Atlantic can excite the Rossby waves from the western North Atlantic and propagate eastward to NEC. The snow anomaly over western Siberia in late spring and the soil moisture anomaly over NEC in summer are key factors linking the SST anomaly to drought over the NEC. On the other hand, the Maritime Continent SST anomaly in late spring can modulate the activity of the East Asian jet stream via the East AsiaPacific (EAP) teleconnection, which can provide the favorable conditions for the soil moisture reduction over NEC. Eventually, a predictive model for maize yield over NEC is successfully developed by using the predictive indices of the North Atlantic and the Maritime Continental SST during late spring. Both the cross-validation and independent sample tests show that the calibrated prediction model is robust and exhibits high skill in predicting maize yield over NEC.

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.

Precipitation comes in various phases, including rainfall, snowfall, sleet, and hail. Shifts of precipitation phases, as well as changes in precipitation amount, intensity, and frequency, have significant impacts on regional climate, hydrology, ecology, and the energy balance of the land-atmosphere system. Over the past century, certain progress has been achieved in aspects such as the observation, discrimination, transformation, and impact of precipitation phases. Mainly including: since the 1980s, studies on the observation, formation mechanism, and prediction of precipitation phases have gradually received greater attention and reached a certain scale. The estimation of different precipitation phases using new detection theories and methods has become a research focus. A variety of discrimination methods or schemes, such as the potential thickness threshold method of the air layer, the temperature threshold method of the characteristic layer, and the near-surface air temperature threshold method, have emerged one after another. Meanwhile, comparative studies on the discrimination accuracy and applicability assessment of multiple methods or schemes have also been carried out simultaneously. In recent years, the shift of precipitation from solid to liquid (SPSL) in the mid-to-high latitudes of the Northern Hemisphere has become more pronounced due to global warming and human activities. It leads to an increase in rain-on-snow (ROS) events and avalanche disasters, affecting the speed, intensity, and duration of spring snow-melting, accelerating sea ice and glacier melting, releasing carbon from permafrost, altering soil moisture, productivity, and phenological characteristics of ecosystems, and thereby affecting their structures, processes, qualities, and service functions. Although some progress has been made in the study of precipitation phases, there remains considerable research potential in terms of completeness of basic data, reliability of discrimination schemes, and the mechanistic understanding of the interaction between SPSL and other elements or systems. The study on shifts of precipitation phases and their impacts will play an increasingly important role in assessing the impacts of global climate change, water cycle processes, water resources management, snow and ice processes, snow and ice-related disasters, carbon emissions from permafrost, and ecosystem safety.

Glaciers provide multiple ecosystem services (ES) to human society. Due to the continued global warming, the valuation of glacier ES is of urgent importance because this knowledge can support the protection of glaciers. However, a systematic valuation of glacier ES is still lacking, particularly from the perspective of ES contributors. In this study, we introduce the concept of emergy to establish a methodological framework for accounting glacier ES values, and take the Tibetan Plateau (TP) as a case study to comprehensively evaluate the spatiotemporal characteristics of glacier ES during the early 21st century. The results show that the total glacier ES values on the TP increased from 2.36E+24 sej/yr in the 2000s to 2.40E+24 sej/yr in the 2010s, with an overall growth rate of 1.6%. The values of the various services in the 2010s are ranked in descending order: climate regulation (1.59E+24 sej/yr, 66.1%), runoff regulation (4.40E+23 sej/yr, 18.4%), hydropower generation (1.88E+23 sej/ yr, 7.8%). Significantly higher glacier ES values were recorded in the marginal TP than in the endorheic area. With the exception of climate regulation and carbon sequestration, all other service values increased during the study period, partially cultural services, which have experienced rapid growth in tandem with social development. The results of this study will help establish the methodological basis for the assessment of regional and global glacier ES, as well as a scientific basis for the regional protection of glacier resources.

Environmental changes, such as climate warming and higher herbivory pressure, are altering the carbon balance of Arctic ecosystems; yet, how these drivers modify the carbon balance among different habitats remains uncertain. This hampers our ability to predict changes in the carbon sink strength of tundra ecosystems. We investigated how spring goose grubbing and summer warming-two key environmental-change drivers in the Arctic-alter CO2 fluxes in three tundra habitats varying in soil moisture and plant-community composition. In a full-factorial experiment in high-Arctic Svalbard, we simulated grubbing and warming over two years and determined summer net ecosystem exchange (NEE) alongside its components: gross ecosystem productivity (GEP) and ecosystem respiration (ER). After two years, we found net CO2 uptake to be suppressed by both drivers depending on habitat. CO2 uptake was reduced by warming in mesic habitats, by warming and grubbing in moist habitats, and by grubbing in wet habitats. In mesic habitats, warming stimulated ER (+75%) more than GEP (+30%), leading to a 7.5-fold increase in their CO2 source strength. In moist habitats, grubbing decreased GEP and ER by similar to 55%, while warming increased them by similar to 35%, with no changes in summer-long NEE. Nevertheless, grubbing offset peak summer CO2 uptake and warming led to a twofold increase in late summer CO2 source strength. In wet habitats, grubbing reduced GEP (-40%) more than ER (-30%), weakening their CO2 sink strength by 70%. One-year CO2-flux responses were similar to two-year responses, and the effect of simulated grubbing was consistent with that of natural grubbing. CO2-flux rates were positively related to aboveground net primary productivity and temperature. Net ecosystem CO2 uptake started occurring above similar to 70% soil moisture content, primarily due to a decline in ER. Herein, we reveal that key environmental-change drivers-goose grubbing by decreasing GEP more than ER and warming by enhancing ER more than GEP-consistently suppress net tundra CO2 uptake, although their relative strength differs among habitats. By identifying how and where grubbing and higher temperatures alter CO2 fluxes across the heterogeneous Arctic landscape, our results have implications for predicting the tundra carbon balance under increasing numbers of geese in a warmer Arctic.

Monitoring and modelling surface deformation are crucial components of understanding the freeze-thaw process and preventing disasters in permafrost regions. However, previous methods had limitations that inhibited the interpretation of freeze-thaw deformation, such as a lack of physical meaning, an inability to reflect the physical freeze-thaw process and consideration of only a single external factor's impact on permafrost deformation. This study proposes an improved degree-day model (IDM) for quantitatively isolating surface deformation using interferometric synthetic aperture radar (InSAR) technology over permafrost. We considered the effect of soil moisture variation on permafrost deformation and incorporated interannual variation in the freeze-thaw process due to climate change. By applying small baseline subset (SBAS) technology to Sentinel-1 InSAR measurements over the Wudaoliang permafrost region on the Qinghai-Tibet Plateau from 2018 to 2019, we estimated long-term and seasonal permafrost deformation. The reliability of InSAR results was validated using in situ measurements, with root mean square errors (RMSEs) less than 10 mm. The results showed that the average linear deformation rates in 2018 and 2019 were -3.8 mm a-1 and -11.0 mm a-1, respectively, and the maximum seasonal deformations were 15.7 mm and 13.2 mm, respectively. Compared with the original degree-day model (ODM), the method used in this study produced smaller residual deformations of 6.9 mm and 6.4 mm, highlighting its ability to improve a quantitative description of permafrost deformation.

Siberia occupies vast areas underlain by permafrost, and understanding its land cover changes is important for ecological environmental protection in a warming climate. Based on the land cover and climate datasets, we analyzed the land cover changes and their drivers in Siberia from 1992 to 2020. The results show that (1) From 1992 to 2020, the areas of evergreen needleleaf trees and deciduous needleleaf trees in Siberia decreased by 9% and 2.5%, and the areas of grassland, shrub, cropland, and construction land increased by 1.5%, 14.2%, 2.8%, and 39.2%, respectively. Cropland expansion had the fastest rate of 1.85% in the continuous permafrost zone, and construction land expansion had the fastest rate of 3.07% in the non-permafrost zone. (2) The center of gravity of agricultural land continues to migrate to the northeast, and the center of gravity of construction land continues to migrate to the southwest. (3) The primary drivers for the land cover changes were temperature and precipitation, and active layer thickness also affected grassland, cropland, and deciduous needleleaf trees. The correlation coefficient between active layer thickness and cropland area is 0.74 in the continuous permafrost zone. The interaction between factors is mostly manifested as a two-factor enhancement, with the highest q-value of the interaction of temperature and precipitation for explanatory power. Our results suggest that climate change and permafrost degradation significantly changed land cover in Siberia. This finding deepens our understanding of the mechanisms of land cover change under the influence of permafrost degradation and provides a new perspective on the land cover changes in permafrost regions.

Freeze-thaw cycles (FTC) alter soil function through changes to physical organization of the soil matrix and biogeochemical processes. Understanding how dynamic climate and soil properties influence FTC may enable better prediction of ecosystem response to changing climate patterns. In this study, we quantified FTC occurrence and frequency across 40 National Ecological Observatory Network (NEON) sites. We used site mean annual precipitation (MAP) and mean annual temperature (MAT) to define warm and wet, warm and dry, and cold and dry climate groupings. Site and soil properties, including MAT, MAP, maximum-minimum temperature difference, aridity index, precipitation as snow (PAS), and organic mat thickness, were used to characterize climate groups and investigate relationships between site properties and FTC occurrence and frequency. Ecosystem-specific drivers of FTC provided insight into potential changes to FTC dynamics with climate warming. Warm and dry sites had the most FTC, driven by rapid diurnal FTC close to the soil surface in winter. Cold and dry sites were characterized by fewer, but longer-duration FTC, which mainly occurred in spring and increased in number with higher organic mat thickness (Spearman's rho = 0.97, p < 0.01). The influence of PAS and MAT on the occurrence of FTC depended on climate group (binomial model interaction p (chi(2)) < 0.05), highlighting the role of a persistent snowpack in buffering soil temperature fluctuations. Integrating ecosystem type and season-specific FTC patterns identified here into predictive models may increase predictive accuracy for dynamic system response to climate change.