Brown carbon (BrC) is the ubiquitous part of the atmospheric organic carbon. It absorbs solar lights and greatly impacts the Earth's radiative balance. This study examines the spectral characteristics of BrC and its radiative effect in the Dhaka South (DS) site and Dhaka North (DN) site from July 2023 to January 2024 with a high-volume particulate matter sampler on quartz filters. Spectral characteristics such as absorption coefficient (babe,), mass absorption efficiency (MAE), absorption angstrom exponent (AAE), and refractive index (Kabs-x) were determined by using a UV -visible spectrophotometer, and fluorescence emission spectra were analyzed in different pH by the fluorescent spectrophotometer. The concentrations of BrC and black carbon (BC) were determined by an aethalometer. The mean concentrations of BrC and BC in Dhaka city were 18.63 +/- 3.84 mu g 111-3 and 17.93 +/- 3.82 pg M-3, respectively. The AAE values lie in the range of 3.20-4.01 (DN) and 3.27-4.53 (DS), and the radiative forcing efficiency of BrC was obtained at 4.43 +/- 1.02 W g-1 in DN and 3.93 +/- 0.74 W g-1 in DS, indicating the presence of highly light-absorbing BrC in these locations. Average MAE and Kabs_k values were 1.55 +/- 0.45 m2g1 and 0.044 + 0.013, respectively, in DS, alternatively 1.84 +/- 0.59 m2g1 and 0.052 +/- 0.016 in DN. The fluorescence excitation-emission spectra confirmed the presence of a polyconjugate cyclic ring with multifunctional groups in the structure of BrC. Light absorption properties and fluorescence emission spectra were varied with the change of pH. As the pH increased (2-8), the AAE value decreased and MAEB,c_365 increased due to protonation or deprotonation. This study highlights that the BrC has a significant impact on the air quality as well as the Earth's radiative balance, emphasizing its strong light-absorbing properties and variability with environmental factors.

Subarctic palsa mires are natural indicators of the status of permafrost in its sporadic distribution zone. Estimation of the rate of their thawing can become an auxiliary indicator to predict climate shifts. The formation, growth, and degradation of palsas are dynamic processes that depend on seasonal weather fluctuations and local environmental factors. Therefore, accurate forecasts of palsas conditions and related ecosystem shifts must be based on a broad set of attributes of palsas from different regions of the Northern Hemisphere. With this in mind, we studied two palsa mires sites on the Kola Peninsula, for which no thorough descriptions were previously available. The first site, Chavanga, is at the southern limit of the permafrost zone under unfavorable climatic conditions and is a collapsing relic. The second site, Ponoy, in contrast, is within the sporadic permafrost zone with relatively cold and dry conditions. Our dataset was created by combining several methods to produce detailed spatial models of permafrost for the studied palsa mires. We used 3D ground-penetrating radar (GPR) survey, UAV-based orthophoto maps, peat thermometry, time-domain reflectometry, and manual sampling. We developed two integrated geospatial models that describe the active layer, the configuration of the palsa frozen core, and its thermal state and identify the zones of the most intense thawing. These observations revealed a significant thermal effect of the groundwater flow and its critical role in the palsas segmentation and rapid collapse. We have investigated a regulating effect of micromorphological features of palsa mounds such as heights, slope, depressions, and mire mineral bed through groundwater drainage. As a result, two new scenarios for the palsa degradation process have been developed, emphasizing the influence of environmental factors on the permafrost condition.

Estimating Top-of-Atmosphere (TOA) flux and radiance is essential for understanding Earth's radiation budget and climate dynamics. This study utilized polar nephelometer measurements of aerosol scattering coefficients at 17 angles (9-170 degrees), enabling the experimental determination of aerosol phase functions and the calculation of Legendre moments. These moments were then used to estimate TOA flux and radiance. Conducted at a tropical coastal site in India, the study observed significant seasonal and diurnal variations in angular scattering patterns, with the highest scattering during winter and the lowest during the monsoon. Notably, a prominent secondary scattering mode, with varying magnitude across different seasons, was observed in the 20-30 degrees angular range, highlighting the influence of different air masses and aerosol sources. Chemical analysis of size-segregated aerosols revealed that fine-mode aerosols were dominated by anthropogenic species, such as sulfate, nitrate, and ammonium, throughout all seasons. In contrast, coarse-mode aerosols showed a clear presence of sea-salt aerosols during the monsoon and mineral dust during the pre-monsoon periods. The presence of very large coarse-mode non-spherical aerosols caused increased oscillations in the phase function beyond 60 degrees during the pre-monsoon and monsoon seasons. This also led to a weak association between the phase function derived from angular scattering measurements and those predicted by the Henyey-Greenstein approximation. As a result, TOA fluxes and radiances derived using the Henyey-Greenstein approximation (with the asymmetry parameter as input in the radiative transfer model) showed a significant difference- up to 24% in seasons with substantial coarse-mode aerosol presence- compared to those derived using the Legendre moments of the phase function. Therefore, TOA flux and radiance estimates using Legendre moments are generally more accurate in the presence of complex aerosol scattering characteristics, particularly for non-spherical or coarse-mode aerosols, while the Henyey-Greenstein phase function may yield less accurate results due to its simplified representation of scattering behavior.

The extent of wildfires in tundra ecosystems has dramatically increased since the turn of the 21st century due to climate change and the resulting amplified Arctic warming. We simultaneously studied the recovery of vegetation, subsurface soil moisture, and active layer thickness (ALT) post-fire in the permafrost-underlain uplands of the Yukon-Kuskokwim Delta in southwestern Alaska to understand the interaction between these factors and their potential implications. We used a space-for-time substitution methodology with 2017 Landsat 8 imagery and synthetic aperture radar products, along with 2016 field data, to analyze tundra recovery trajectories in areas burned from 1953 to 2017. We found that spectral indices describing vegetation greenness and surface albedo in burned areas approached the unburned baseline within a decade post-fire, but ecological succession takes decades. ALT was higher in burned areas compared to unburned areas initially after the fire but negatively correlated with soil moisture. Soil moisture was significantly higher in burned areas than in unburned areas. Water table depth (WTD) was 10 cm shallower in burned areas, consistent with 10 cm of the surface organic layer burned off during fire. Soil moisture and WTD did not recover in the 46 years covered by this study and appear linked to the long recovery time of the organic layer.

The Sanjiangyuan region, known as the Chinese Water Tower, serves as a crucial ecological zone that is highly sensitive to climate change. In recent years, rising temperatures and increased precipitation have led to permafrost melt and frequent occurrences of thermokarst landslides, exacerbating soil erosion issues. Although studies have explored the impact of freeze-thaw action (FTA) on soil properties, research on this phenomenon within the unique geomorphological unit of thermokarst landslides, formed from degrading permafrost, remains sparse. This study, set against the backdrop of temperature-induced soil landslides, combines field investigations and controlled laboratory experiments on typical thermokarst landslide bodies within the permafrost region of Sanjiangyuan to systematically investigate the effects of FTA on the properties of soils within thermokarst landslides. Furthermore, this study employs the EPIC model to establish an empirical formula for the soil erodibility (SE) factor before and after freeze-thaw cycles (FTCs). The results indicate that: (1) FTCs significantly alter soil particle composition, reducing the content of clay particles in the surface soil while increasing the content of sand particles and the median particle size, thus compromising soil structure and enhancing erodibility. (2) FTA initially significantly increases soil organic matter content (OMC); however, as the number of FTCs increases, the magnitude of these changes diminishes. The initial moisture content of the soil significantly influences the effects of FTA, with more pronounced changes in particle composition and OMC in soils with higher moisture content. (3) With an increasing number of FTCs, the SE K-value first significantly increases and then tends to stabilize, showing significant differences across the cycles (1 to 15) (p < 0.05). This study reveals that FTCs, by altering the physicochemical properties of the soil, significantly increase SE, providing a scientific basis for soil erosion control and ecological environmental protection in the Sanjiangyuan area.

Arctic permafrost soils contain a vast reservoir of soil organic carbon (SOC) vulnerable to increasing mobilization and decomposition from polar warming and permafrost thaw. How these SOC stocks are responding to global warming is uncertain, partly due to a lack of information on the distribution and status of SOC over vast Arctic landscapes. Soil moisture and organic matter vary substantially over the short vertical distance of the permafrost active layer. The hydrological properties of this seasonally thawed soil layer provide insights for understanding the dielectric behavior of water inside the soil matrix, which is key for developing more effective physics-based radar remote sensing retrieval algorithms for large-scale mapping of SOC. This study provides a coupled hydrologic-electromagnetic framework to model the frequency-dependent dielectric behavior of active layer organic soil. For the first time, we present joint measurement and modeling of the water matric potential, dielectric permittivity, and basic physical properties of 66 soil samples collected across the Alaskan Arctic tundra. The matric potential measurement allows for estimating the soil water retention curve, which helps determine the relaxation time through the Eyring equation. The estimated relaxation time of water molecules in soil is then used in the Debye model to predict the water dielectric behavior in soil. A multi-phase dielectric mixing model is applied to incorporate the contribution of various soil components. The resulting organic soil dielectric model accepts saturation water fraction, organic matter content, mineral texture, temperature, and microwave frequency as inputs to calculate the effective soil dielectric characteristic. The developed dielectric model was validated against lab-measured dielectric data for all soil samples and exhibited robust accuracy. We further validated the dielectric model against field-measured dielectric profiles acquired from five sites on the Alaskan North Slope. Model behavior was also compared against other existing dielectric models, and an indepth discussion on their validity and limitations in permafrost soils is given. The resulting organic soil dielectric model was then integrated with a multi-layer electromagnetic scattering forward model to simulate radar backscatter under a range of soil profile conditions and model parameters. The results indicate that low frequency (P-,L-band) polarimetric synthetic aperture radars (SARs) have the potential to map water and carbon characteristics in permafrost active layer soils using physics-based radar retrieval algorithms.

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.

Evapotranspiration (ET) is a critical component of the soil-plant-atmosphere continuum, significantly influencing the water and energy balance of ecosystems. However, existing studies on ET have primarily focused on the growing season or specific years, with limited long-term analyses spanning decades. This study aims to analyse the components of ET within the alpine ecosystem of the Heihe River Basin, specifically investigating the dynamics of vegetation transpiration (T) and soil evaporation (Ev). Utilizing the SPAC model and integrating meteorological observations and eddy covariance data from 2013 to 2022, we investigate the impact of solar radiation and vegetation dynamics on ET and its partitioning (T/ET). The agreement between measured and simulated energy fluxes (net radiation and latent energy flux) and soil temperature underscores the validity of the model's performance. Additionally, a comparison employing the underlying water use efficiency method reveals consistent T/ET values during the growing season, further confirming the model's accuracy. Results indicate that the annual average T/ET during the 10-year study period is 0.41 +/- 0.03, close to the global average but lower than in warmer, humid regions. Seasonal analysis reveals a significant increase in T/ET during the growing season (April to October), particularly in May and June, coinciding with the thawing of permafrost and increased soil moisture. In addition, the study finds that the leaf area index and canopy stomatal conductance exhibit a logarithmic relationship with T/ET, whereas soil temperature and downward longwave radiation show an exponential relationship with T/ET. This study highlights the importance of understanding the stomatal conductance dynamics and their controls of transpiration process within alpine ecosystems. By providing key insights into the hydrological processes of these environments, it offers guidance for adapting to climate change impacts.

Frozen soil resistivity exhibits high sensitivity to temperature variations and ice-water distribution. The conversion of soil water content (SWC) and resistivity based on petrophysical relationships enables the characterization of spatial distribution and changes in freezing and thawing states. Monitoring ground resistivity is essential for understanding frozen soil structure and evaluating climate change and ecosystems. The previous studies demonstrate that estimating soil resistivity below zero degrees based on the empirical model has significant errors. This work proposes a capillary bundle fractal model for frozen soil resistivity estimation based on SWC hydrologic parameters. The fractal theory describes the geoelectrical features of frozen porous media through the variable pore geometry and representative elementary volume. The sensitivity analysis discusses the potential relationships between pore parameters, conductance components, and fractal geometric parameters within frozen soil resistivity and reconstructs the hysteresis separation of freeze-thaw processes. The field test application in the seasonal freeze-thaw monitoring site demonstrates that the estimated resistivity and experimental samples are consistent with the field monitoring resistivity data. By combining unified conceptual assumptions, we established the connection between electrical permeability and thermal conductivity, offering a basis for exploring coupled hydro-thermal mechanisms in frozen soil. The proposed model accurately estimates the variations in seasonal frozen resistivity, providing a reliable reference for quantitatively analyzing the mechanisms of freeze-thaw processes.

Particulate matter (PM) is a vital pollutant that severely impacts human health, ecosystem well-being, and climate systems. In this review, the importance of vertical profiling is considered for understanding PM behavior between different layers of the atmosphere, and it includes modern techniques used such as meteorological towers and building methods, unmanned aerial vehicles (UAVs), aircraft, and satellite-based aerosol optical depth measurements. A systematic review was conducted, sourcing 150 articles published between 2000 and 2023, using relevant keywords such as Particulate Matter, Vertical Profiling, Environmental Impacts, and Climate Change from databases like Web of Science, Scopus, and Google Scholar. Key findings illustrate the vertical variations in PM levels associated with interactions among urban environments, meteorology, and specific atmospheric processes such as cloud formation, radiative forcing, and long-distance transport of pollutants. PM's effects on biodiversity, nutrient cycles, and ecosystem stability are also discussed. The environmental impacts of PM deposition, including biodiversity loss, nutrient cycling disruption, and ecosystem destabilization, elucidate widespread chronic anthropogenic particulate causes of long-term ecological damage around the globe. The study also examines relevant regulatory frameworks, specifically air quality standards, and policies, underpinning mitigation strategies. This review discusses how PM pollution is an increasingly alarming health risk. It reiterates the importance of demanding effective regulations on the local and global levels to counteract detrimental environmental and climatic consequences. This review clearly shows the immediate threats of PM. It should form a wake-up call to develop more effective monitoring tools and stringent regulatory measures against this omnipresent pollutant.