Review and uncertainty assessment of size-resolved scavenging coefficient formulations for below-cloud snow scavenging of atmospheric aerosols

Abstract

Abstract. Theoretical parameterizations for the sizeresolved scavenging coefficient for atmospheric aerosol particles scavenged by snow ( snow ) need assumptions regarding (i) snow particle-aerosol particle collection efficiency E, (ii) snow-particle size distribution N(D p ), (iii) snow-particle terminal velocity V D , and (iv) snow-particle cross-sectional area A. Existing formulas for these parameters are reviewed in the present study, and uncertainties in snow caused by various combinations of these parameters are assessed. Different formulations of E can cause uncertainties in snow of more than one order of magnitude for all aerosol sizes for typical snowfall intensities. E is the largest source of uncertainty among all the input parameters, similar to rain scavenging of atmospheric aerosols ( rain ) as was found in a previous study by Wang et al. (2010). However, other parameters can also cause significant uncertainties in snow , and the uncertainties from these parameters are much larger than for rain . Specifically, different N(D p ) formulations can cause one-order-of-magnitude uncertainties in snow for all aerosol sizes, as is also the case for a combination of uncertainties from both V D and A. Assumptions about dominant snowparticle shape (and thus different V D and A) will cause an uncertainty of up to one order of magnitude in the calculated scavenging coefficient. In comparison, uncertainties in rain from N (D p ) are smaller than a factor of 5, and those from V D are smaller than a factor of 2. As expected, snow estimated from empirical formulas generated from field measurements falls in the upper range of, or is higher than, the theoretically estimated values, which can be explained by additional processes/mechanisms that influence field-derived snow but that are not considered in the theoretical snow formulas. Predicted aerosol concentrations obtained by using upper range vs. lower range of snow values (a difference of around two orders of magnitude in snow ) can differ by a factor of 2 for just a one-centimetre snowfall (liquid water equivalent of approximately 1 mm). Based on the median and upper range of theoretically generated snow and snow values, it is likely that, for typical rain and snow events, the removal of atmospheric aerosol particles by snow is more effective than removal by rain for equivalent precipitation amounts, although a firm conclusion requires much more evidence.

Snow scavenging and phase partitioning of nitrated and oxygenated aromatic hydrocarbons in polluted and remote environments in central Europe and the European Arctic

“…Our data suggests that the phase distribution of polar particulate phase substances, such as NMAHs in snow is determined by an interplay between GPP in the aerosol, mass size distribution in the atmosphere, and dissolution in cloud or rain droplets, or the liquid water phase on the surface of ice hydrometeors during in-or below-cloud scavenging. This behaviour is in line with what was previously shown for the effect of aerosol mass size distribution on snow scavenging (Zhang et al, 2013), and what was found 5 for in-cloud scavenging of other polar mono-and difunctional organics, such as aliphatic alcohols, and aliphatic and monoaromatic aldehydes and carboxylic acids (Limbeck and Puxbaum, 2000), namely the polarity of these substances is a significant parameter for their scavenging when solubility is > 1 g L -1 . The experimental data on GPP of NMAHs is scarce in the literature, which was also not addressed here.…”

“…Nitrocatechols on the other hand were exclusively associated with the fine fraction (PM1; ~80%), similar to observations reported by . This mass size distribution could potentially enhance snow scavenging of nitrophenols following the interception of coarse particles by snowflakes -this mechanism was suggested to be important for PM in the size range of 1 µm to a few microns (Zhang et al, 2013), and its contribution 20 is expected to increase with the particle size. It was further suggested that a combination of Brownian diffusion, interception, and inertial impaction leads to a low snow particle-aerosol particle collection efficiency (suggested to be the most important source of uncertainty in snow scavenging of PM) in the particle size range of 0.01-1.0 µm (Zhang et al, 2013), which could further explain the relatively low WT values found for nitrocatechols in the present study.…”

Assessing the Risk of Engineered Nanomaterials in the Environment: Development and Application of the nanoFate Model

“…86 Wet deposition of aerosols considers the scavenging ratio developed by Mackay 66 and an additional factor of 0.01 for raindrop scavenging of nanoparticles (SIUG, Section 2.1.2), since 10 nm and smaller particles can have a scavenging ratio of up to 2 orders of magnitude smaller than those in the 1−5 μm range. 87 Free and aerosol-associated ENMs can be transported in or out of the air compartment via wind (SIUG, Section 2.1.3). Since heteroaggregation of ENMs with aerosols has not been studied for specific ENMs, the rate of heteroaggregation in air is reduced by a factor of 1000 because the collision frequency is assumed to be lower in air resulting in fewer particle interactions that result in heteroaggregation (SIUG, Section 2.1.4).…”

Development of a new semi-empirical parameterization for below-cloud scavenging of size-resolved aerosol particles by both rain and snow

“…This choice matters because CTMs with different formulations produce significantly different predictions of particulate matter concentrations and atmospheric deposition budgets (e.g., Rasch et al, 2000;Solazzo et al, 2012). To quantify the differences in the existing size-resolved formulations for and to identify the dominant product terms causing these differences, we recently conducted detailed reviews of available parameterizations of below-cloud scavenging of size-resolved aerosol particles by rain ( rain ) and by snow ( snow ) (Wang et al, 2010(Wang et al, , 2011Zhang et al, 2013). The major conclusions from these review studies can be summarized as follows:…”