A snow survey was carried out to collect 13 surface snow samples (10 for fresh snow, and 3 for aged snow) and 79 subsurface snow samples in seasonal snow at 13 sites across northeastern China in January 2014. A spectrophotometer combined with chemical analysis was used to quantify snow particulate absorption by insoluble light-absorbing particles (ILAPs, e.g., black carbon, BC; mineral dust, MD; and organic carbon, OC) in snow. Snow albedo was measured using a field spectroradiometer. A new radiative transfer model (Spectral Albedo Model for Dirty Snow, or SAMDS) was then developed to simulate the spectral albedo of snow based on the asymptotic radiative transfer theory. A comparison between SAMDS and an existing model – the Snow, Ice, and Aerosol Radiation (SNICAR) – indicates good agreements in the model-simulated spectral albedos of pure snow. However, the SNICAR model values tended to be slightly lower than those of SAMDS when BC and MD were considered. Given the measured BC, MD, and OC mixing ratios of 100–5000, 2000–6000, and 1000–30 000 ng g⁻¹, respectively, in surface snow across northeastern China, the SAMDS model produced a snow albedo in the range of 0.95–0.75 for fresh snow at 550 nm, with a snow grain optical effective radius (R_eff) of 100 µm. The snow albedo reduction due to spherical snow grains assumed to be aged snow is larger than fresh snow such as fractal snow grains and hexagonal plate or column snow grains associated with the increased BC in snow. For typical BC mixing ratios of 100 ng g⁻¹ in remote areas and 3000 ng g⁻¹ in heavy industrial areas across northern China, the snow albedo for internal mixing of BC and snow is lower by 0.005 and 0.036 than that of external mixing for hexagonal plate or column snow grains with R_eff of 100 µm. These results also show that the simulated snow albedos by both SAMDS and SNICAR agree well with the observed values at low ILAP mixing ratios but tend to be higher than surface observations at high ILAP mixing ratios.

The optical properties and chemical composition of PM_1.0 particles in a suburban environment (Huairou) near the megacity of Beijing were measured during the HOPE-J³A (Haze Observation Project Especially for Jing–Jin–Ji Area) field campaign. The campaign covered the period November 2014 to January 2015 during the winter coal heating season. The average values and standard deviations of the extinction, scattering, absorption coefficients, and the aerosol single scattering albedo (SSA) at λ = 470 nm during the measurement period were 201 ± 240, 164 ± 202, 37 ± 43 Mm⁻¹, and 0.80 ± 0.08, respectively. The average values for the real and imaginary components of the effective complex refractive index (CRI) over the campaign were 1.40 ± 0.06 and 0.03 ± 0.02, while the average mass scattering and absorption efficiencies (MSEs and MAEs) of PM_1.0 were 3.6 and 0.7 m² g⁻¹, respectively. Highly time-resolved air pollution episodes clearly show the dramatic evolution of the PM_1.0 size distribution, extensive optical properties (extinction, scattering, and absorption coefficients), and intensive optical properties (SSA and CRI) during haze formation, development, and decline. Time periods were classified into three different pollution levels (clear, slightly polluted, and polluted) for further analysis. It was found that (1) the relative contributions of organic and inorganic species to observed aerosol composition changed significantly from clear to polluted days: the organic mass fraction decreased from 50 to 43 % while the proportion of sulfates, nitrates, and ammonium increased strongly from 34 to 44 %. (2) Chemical apportionment of extinction, calculated using the IMPROVE algorithm, tended to underestimate the extinction compared to measurements. Agreement with measurements was improved by modifying the parameters to account for enhanced absorption by elemental carbon (EC). Organic mass was the largest contributor (52 %) to the total extinction of PM_1.0, while EC, despite its low mass concentration of ∼ 4 %, contributed about 17 % to extinction. When the air quality deteriorated, the contribution of nitrate aerosol increased significantly (from 15 % on clear days to 22 % on polluted days). (3) Under polluted conditions, the average MAEs of EC were up to 4 times as large as the reference MAE value for freshly generated black carbon (BC). The temporal pattern of MAE values was similar to that of the OC / EC ratio, suggesting that non-BC absorption from secondary organic aerosol also contributes to particle absorption.

Mineral dust is a major light-absorbing aerosol, which can significantly reduce snow albedo and accelerate snow/glacier melting via wet and dry deposition on snow. In this study, three scenarios of internal mixing of dust in ice grains were analyzed theoretically by combining asymptotic radiative transfer theory and (core–shell) Mie theory to evaluate the effects on absorption coefficient and albedo of the semi-infinite snowpack consisting of spherical snow grains. In general, snow albedo was substantially reduced at wavelengths of <1.0 µm by internal dust–snow mixing, with stronger reductions at higher dust concentrations and larger snow grain sizes. Moreover, calculations showed that a nonuniform distribution of dust in snow grains can lead to significant differences in the values of the absorption coefficient and albedo of dust-contaminated snowpack at visible wavelengths relative to a uniform dust distribution in snow grains. Finally, using comprehensive in situ measurements across the Northern Hemisphere, we found that broadband snow albedo was further reduced by 5.2 % and 9.1 % due to the effects of internal dust–snow mixing on the Tibetan Plateau and North American mountains. This was higher than the reduction in snow albedo caused by black carbon in snow over most North American and Arctic regions. Our results suggest that significant dust–snow internal mixing is important for the melting and retreat of Tibetan glaciers and North American mountain snowpack.

A large field campaign was conducted and 284 snow samples were collected at 38 sites in Xinjiang Province and 6 sites in Qinghai Province across northwestern China from January to February 2012. A spectrophotometer combined with chemical analysis was used to measure the insoluble light-absorbing particles (ILAPs) and chemical components in seasonal snow. The results indicate that the cleanest snow was found in northeastern Xinjiang along the border of China, and it presented an estimated black carbon (C_BC^est) of approximately 5 ng g⁻¹. The dirtiest snow presented a C_BC^est of approximately 450 ng g⁻¹ near industrial cities in Xinjiang. Overall, the C_BC^est of most of the snow samples collected in this campaign was in the range of 10–150 ng g⁻¹. Vertical variations in the snowpack ILAPs indicated a probable shift in emission sources with the progression of winter. An analysis of the fractional contributions to absorption implied that organic carbon (OC) dominated the 450 nm absorption in Qinghai, while the contributions from BC and OC were comparable in Xinjiang. Finally, a positive matrix factorization (PMF) model was run to explore the sources of particulate light absorption, and the results indicated an optimal three-factor/source solution that included industrial pollution, biomass burning, and soil dust.

Water-soluble organic carbon (WSOC) in the cryosphere has an important impact on the biogeochemistry cycling and snow–ice surface energy balance through changes in the surface albedo. This work reports on the chemical characterization of WSOC in 28 representative snowpack samples collected across a regional area of northern Xinjiang, northwestern China. We employed multimodal analytical chemistry techniques to investigate both bulk and molecular-level composition of WSOC and its optical properties, informing the follow-up radiative forcing (RF) modeling estimates. Based on the geographic differences and proximity of emission sources, the snowpack collection sites were grouped as urban/industrial (U), rural/remote (R), and soil-influenced (S) sites, for which average WSOC total mass loadings were measured as 1968 ± 953 ng g⁻¹ (U), 885 ± 328 ng g⁻¹ (R), and 2082 ± 1438 ng g⁻¹ (S), respectively. The S sites showed the higher mass absorption coefficients at 365 nm (MAC₃₆₅) of 0.94 ± 0.31 m² g⁻¹ compared to those of U and R sites (0.39 ± 0.11 m² g⁻¹ and 0.38 ± 0.12 m² g⁻¹, respectively). Bulk composition of WSOC in the snowpack samples and its basic source apportionment was inferred from the excitation–emission matrices and the parallel factor analysis featuring relative contributions of one protein-like (PRLIS) and two humic-like (HULIS-1 and HULIS-2) components with ratios specific to each of the S, U, and R sites. Additionally, a sample from site 120 showed unique pollutant concentrations and spectroscopic features remarkably different from all other U, R, and S samples. Molecular-level characterization of WSOC using high-resolution mass spectrometry (HRMS) provided further insights into chemical differences among four types of samples (U, R, S, and 120). Specifically, many reduced-sulfur-containing species with high degrees of unsaturation and aromaticity were uniquely identified in U samples, suggesting an anthropogenic source. Aliphatic/protein-like species showed the highest contribution in R samples, indicating their biogenic origin. The WSOC components from S samples showed high oxygenation and saturation levels. A few unique CHON and CHONS compounds with high unsaturation degree and molecular weight were detected in the 120 sample, which might be anthraquinone derivatives from plant debris. Modeling of the WSOC-induced RF values showed warming effects of 0.04 to 0.59 W m⁻² among different groups of sites, which contribute up to 16 % of that caused by black carbon (BC), demonstrating the important influences of WSOC on the snow energy budget.

Snow is the most reflective natural surface on Earth and consequently plays an important role in Earth's climate. Light-absorbing particles (LAPs) deposited on the snow surface can effectively decrease snow albedo, resulting in positive radiative forcing. In this study, we used remote-sensing data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and the Snow, Ice, and Aerosol Radiative (SNICAR) model to quantify the reduction in snow albedo due to LAPs before validating and correcting the data against in situ observations. We then incorporated these corrected albedo-reduction data in the Santa Barbara DISORT (Discrete Ordinate Radiative Transfer) Atmospheric Radiative Transfer (SBDART) model to estimate Northern Hemisphere radiative forcing except for midlatitude mountains in December–May for the period 2003–2018. Our analysis reveals an average corrected reduction in snow albedo ($\mathrm{\Delta }{\mathit{\alpha }}_{\text{MODIS,corrected}}^{\mathrm{LAPs}}$ ) of ∼ 0.021 under all-sky conditions, with daily radiative forcing (${\mathrm{RF}}_{\text{MODIS,daily}}^{\mathrm{LAPs}}$ ) values of ∼ 2.9 W m⁻², over land areas with complete or near-complete snow cover and with little or no vegetation above the snow in the Northern Hemisphere. We also observed significant spatial variations in $\mathrm{\Delta }{\mathit{\alpha }}_{\text{MODIS,corrected}}^{\mathrm{LAPs}}$ and ${\mathrm{RF}}_{\text{MODIS,daily}}^{\mathrm{LAPs}}$ , with the lowest respective values (∼ 0.016 and ∼ 2.6 W m⁻²) occurring in the Arctic and the highest (∼ 0.11 and ∼ 12 W m⁻²) in northeastern China. From MODIS retrievals, we determined that the LAP content of snow accounts for 84 % and 70 % of the spatial variability in albedo reduction and radiative forcing, respectively. We also compared retrieved radiative forcing values with those of earlier studies, including local-scale observations, remote-sensing retrievals, and model-based estimates. Ultimately, estimates of radiative forcing based on satellite-retrieved data are shown to represent true conditions on both regional and global scales.