Atmospheric particulate matter (PM) as light-absorbing particles (LAPs) deposited to snow cover can result in early onset and rapid snow melting, challenging management of downstream water resources. We identified LAPs in 38 snow samples (water years 2013-2016) from the mountainous Upper Colorado River basin by comparing among laboratory-measured spectral reflectance, chemical, physical, and magnetic properties. Dust sample reflectance, averaged over the wavelength range of 0.35-2.50 mu m, varied by a factor of 1.9 (range, 0.2300-0.4444) and was suppressed mainly by three components: (a) carbonaceous matter measured as total organic carbon (1.6-22.5 wt. %) including inferred black carbon, natural organic matter, and carbon-based synthetic, black road-tire-wear particles, (b) dark rock and mineral particles, indicated by amounts of magnetite (0.11-0.37 wt. %) as their proxy, and (c) ferric oxide minerals identified by reflectance spectroscopy and magnetic properties. Fundamental compositional differences were associated with different iron oxide groups defined by dominant hematite, goethite, or magnetite. These differences in iron oxide mineralogy are attributed to temporally varying source-area contributions implying strong interannual changes in regional source behavior, dust-storm frequency, and (or) transport tracks. Observations of dust-storm activity in the western U.S. and particle-size averages for all samples (median, 25 mu m) indicated that regional dust from deserts dominated mineral-dust masses. Fugitive contaminants, nevertheless, contributed important amounts of LAPs from many types of anthropogenic sources.

We present an innovative approach to understanding permafrost degradation processes through the application of new environment-based particle image velocimetry (E-PIV) to time-lapse imagery and correlation with synchronous temperature and rainfall measurements. Our new approach to extracting quantitative vector movement from dynamic environmental conditions that can change both the position and the color balance of each image has optimized the trade-off between noise reduction and preserving the authenticity of movement data. Despite the dynamic polar environments and continuous landscape movements, the E-PIV provides the first quantitative real-time associations between environmental drivers and the responses of permafrost degradation mechanism. We analyze four event-based datasets from an island southwest of Tuktoyaktuk, named locally as Imnaqpaaluk or Peninsula Point near Tuktoyaktuk, NWT, Canada, spanning a 5-year period from 2017 to 2022. The 2017 dataset focuses on the interaction during a hot dry summer between slope movement and temperature changes, laying the foundation for subsequent analyses. In 2018, two datasets significantly expand our understanding of typical failure mechanisms in permafrost slopes: one investigates the relationship between slope movement and rainfall, while the other captures an overhang collapse, providing a rare quantitative observation of an acute landscape change event. The 2022 dataset revisits the combination of potential rain and air temperature-related forcing to explore the environment-slope response relationship around an ice wedge, a common feature of ice-rich permafrost coasts. These analyses reveal both a direct but muted association with air temperatures and a detectable delayed slope response to the occurrence of rainfall, potentially reflective of the time taken for the warm rainwater to infiltrate through the active layer and affect the frozen ground. Whilst these findings also indicate that other factors are likely to influence permafrost degradation processes, the associations have significant implications given the projections for a warmer, wetter Arctic. The ability to directly measure permafrost slope responses offers exciting new potential to quantitatively assess the sensitivity of different processes of degradation for the first time, improving the vulnerability components of hazard risk assessments, guiding mitigation efforts, and better constraining future projections of erosion rates and the mobilization of carbon-rich material.

Deposition of ambient black carbon (BC) aerosols over snow-covered areas reduces surface albedo and accelerates snowmelt. Based on in-situ atmospheric BC data and the WRF-Chem model, we estimated the dry and wet deposition of BC over the Yala glacier of the central Himalayan region in Nepal during 2016-2018. The maximum and minimum BC dry deposition was reported in pre- and post-monsoon respectively. Approximately 50% of annual dry deposition occurred in the pre-monsoon season (March to May) and 27% of the annual dry deposition occurred in April. The total dry BC deposition rate was estimated as -4.6 mu g m- 2 day- 1 providing a total deposition of 531 mu g m- 2 during the pre-monsoon season. The contribution of biomass burning and fossil fuel sources to BC deposition on an annual basis was 28% and 72% respectively. The annual accumulated wet deposition of BC was 196 times higher than the annual dry deposition. The ten months of observed dry deposition of BC (October 1, 2016 to August 31, 2017 - except December 2016) was -39% lower than that of WRFChem's estimated annual dry deposition from September 1, 2016 to August 31, 2017 partially due to model bias. The deposited content of BC over the snow surface has an important role in albedo reduction, therefore snow samples were collected from the surface of the Yala Glacier and the surrounding region in April 2016, 2017, and 2018. Samples were analyzed for BC mass concentration through the thermal optical analysis and single particle soot photometer method. The BC calculated via the thermal optical method was in the range of 352-854 ng g- 1, higher than the BC calculated through the particle soot photometer method and estimated BC in 2 cm surface snow (imperial equation). The maximum surface snow albedo reduction due to BC was 8.8%, estimated by a widely used snow radiative transfer model and a linear regression equation.

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.

The seasonal mountain snowpack of the Western US (WUS) is a key water resource to millions of people and an important component of the regional climate system. Impurities at the snow surface can affect snowmelt timing and rate through snow radiative forcing (RF), resulting in earlier streamflow, snow disappearance, and less water availability in dry months. Predicting the locations, timing, and intensity of impurities is challenging, and little is known concerning whether snow RF has changed over recent decades. Here we analyzed the relative magnitude and spatio-temporal variability of snow RF across the WUS at three spatial scales (pixel, watershed, regional) using remotely sensed RF from spatially and temporally complete (STC) MODIS data sets (STC-MODIS Snow Covered Area and Grain Size/MODIS Dust Radiative Forcing on Snow) from 2001 to 2022. To quantify snow RF impacts, we calculated a pixel-integrated metric over each snowmelt season (1st March-30th June) in all 22 years. We tested for long-term trend significance with the Mann-Kendall test and trend magnitude with Theil-Sen's slope. Mean snow RF was highest in the Upper Colorado region, but notable in less-studied regions, including the Great Basin and Pacific Northwest. Watersheds with high snow RF also tended to have high spatial and temporal variability in RF, and these tended to be near arid regions. Snow RF trends were largely absent; only a small percent of mountain ecoregions (0.03%-8%) had significant trends, and these were typically decreasing trends. All mountain ecoregions exhibited a net decline in snow RF. While the spatial extent of significant RF trends was minimal, we found declining trends most frequently in the Sierra Nevada, North Cascades, and Canadian Rockies, and increasing trends in the Idaho Batholith. This study establishes a two-decade chronology of snow impurities in the WUS, helping inform where and when RF impacts on snowmelt may need to be considered in hydrologic models and regional hydroclimate studies.

Black carbon (BC) aerosol is one of the most important factor in global warming. BC radiative forcing remains unconstrained, mainly because of the uncertain parameterizations of its absorption and scattering properties in the atmosphere. The single sphere model is widely used in current climate assessment of BC aerosols due to its computational convenience, however, their complex morphologies in particle level are excessively simplified which leads to computed inaccuracy. In this study, we present a dynamic model for optical calculations of BC aerosol ensembles considering their complex fractal aggregate morphologies with the constraint of max monomer numbers (N s, max) and radius (a max). We show that the simulation accuracy of the dynamic model with suitable values of N s, max and a max may achieve similar to 95% while the computation time may reduce to similar to 6%. We find that optical properties of BC aerosol ensembles can be simulated for higher accuracy or faster calculation by performing different selections of monomer numbers and radius in their size distributions. This method enables extensive and accurate optical calculations of BC particles with complex morphologies, which would be useful for the remote sensing inversion and the assessment of climate.

Charge distribution measurements are required to understand the spatiotemporal distribution of the number concentrations of submicron atmospheric particles that affect radiative forcing and particle deposition in human airways. The number concentrations of non -charged and charged particles within the 0.3-0.5 pm diameter (D) range were measured at Keio University in Yokohama, Japan, from June 2022 to January 2023 by combining a parallel -pate particle separator and optical particle counters to investigate critical parameters controlling the charging state of submicron atmospheric particles. The measurement uncertainties in the average charge number per particle (pave) and the standard deviation (1 sigma), derived from the charge distribution of the submicron particles, were within 15%. The monthly median values of 1 sigma increased in summer and decreased in winter and correlated with the water vapor amount and wind speed. The 1 sigma values in summer and winter, derived from the seasonally averaged charge distributions of particles, were close to those from the theoretically calculated charge distribution of particles within 0.387-0.5 pm D range and with D = 0.3 pm, respectively, suggesting that the observed particle charge distributions approached the stationary charge distribution for the effective D. In summer, the frequent transport of water molecules and ions from the Pacific Ocean causes efficient collisions between multiple ions and submicron particles with a larger effective D, which may expand the charge distribution of particles. The polarity ratio, the concentration of positively charged particles relative to that of negatively charged particles, was almost unity, indicating the well-balanced charge polarity of the submicron atmospheric particles. The polarity ratio and pave changed significantly during lightning events, indicating that the atmospheric particle charge balance broke. Our findings show that the charge distribution of submicron atmospheric particles can be partly controlled by meteorological parameters (e.g., absolute humidity) and the microphysical properties of the particles.

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.

Lumbini isa world heritage site located in the southern plains region of Nepal, and is regarded as a potential site for evaluating transboundary air pollution due to its proximity to the border with India. In this study, 82 aerosol samples were collected between April 2013 and July 2014 to investigate the levels of particulate-bound mercury (PBM) and the corresponding seasonality, sources, and influencing factors. The PBM concentration in total suspended particulate (TSP) matter ranged from 6.8 pg m-3 to 351.7 pg m-3 (mean of 99.7 +/- 92.6 pg m-3), which exceeded the ranges reported for remote and rural sites worldwide. The Hg content (PBM/TSP) ranged from 68.2 ng g-1 to 1744.8 ng g-1 (mean of 446.9 +/- 312.7 ng g-1), indicating anthropogenic enrichment. The PBM levels were higher in the dry season (i.e., winter and the pre-monsoon period) than in the wet season (i.e., the monsoon period). In addition, the d202Hg signature indicated that waste/coal burning and traffic were the major sources of Hg in Lumbini during the pre-monsoon period. Meanwhile, precipitation occurring during photochemical processes in the atmosphere may have been responsible for the observed D199Hg values in the aerosol samples obtained during the monsoon period. The PBM concentration was influenced mostly by the resuspension of polluted dust during dry periods and crop residue burning during the post-monsoon period. The estimated PBM deposition flux at Lumbini was 15.7 lg m-2 yr-1. This study provides a reference dataset of atmospheric PBM over a year, which can be useful for understanding the geochemical cycling of Hg in this region of limited data. (c) 2021 China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).

According to the monitoring data of the optical and microphysical characteristics of smoke aerosol at AERONET stations during forest fires in the summer of 2019 in Alaska, the anomalous selective absorption of smoke aerosol has been detected in the visible and near-infrared spectral range from 440 to 1020 nm. With anomalous selective absorption, the imaginary part of the refractive index of smoke aerosol reached 0.315 at a wavelength of 1020 nm. A power-law approximation of the spectral dependence of the imaginary part of the refractive index with an exponent from 0.26 to 2.35 is proposed. It is shown that, for anomalous selective absorption, power-law approximations of the spectral dependences of the aerosol optical extinction and absorption depths are applicable with an angstrom ngstrom exponent from 0.96 to 1.65 for the aerosol optical extinction depth and from 0.97 to -0.89 for the aerosol optical absorption depth, which reached 0.72. Single scattering albedo varied from 0.62 to 0.96. In the size distribution of smoke aerosol particles with anomalous selective absorption, the fine fraction of particles of condensation origin dominated. The similarity of the fraction of particles distinguished by anomalous selective absorption with the fraction of tar balls (TBs) detected by electron microscopy in smoke aerosol, which, apparently, arise during the condensation of terpenes and their oxygen-containing derivatives, is noted.