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Wang X.,Kellys Environmental Services | Zhang L.,Environment Canada | Moran M.D.,Environment Canada
Geoscientific Model Development | Year: 2014

A parameter called the scavenging coefficient λ is widely used in aerosol chemical transport models (CTMs) to describe below-cloud scavenging of aerosol particles by rain and snow. However, uncertainties associated with available size-resolved theoretical formulations for λ span one to two orders of magnitude for rain scavenging and nearly three orders of magnitude for snow scavenging. Two recent reviews of below-cloud scavenging of size-resolved particles recommended that the upper range of the available theoretical formulations for λ should be used in CTMs based on uncertainty analyses and comparison with limited field experiments. Following this recommended approach, a new semiempirical parameterization for size-resolved λ has been developed for below-cloud scavenging of atmospheric aerosol particles by both rain (λrain) and snow (λsnow). The new parameterization is based on the 90th percentile of λ values from an ensemble data set calculated using all possible "realizations" of available theoreticalλformulas and covering a large range of aerosol particle sizes and precipitation intensities (R). For any aerosol particle size of diameter d, a strong linear relationship between the 90th-percentile log10(λ) and log10(R), which is equivalent to a power-law relationship between λ and R, is identified. The log-linear relationship, which is characterized by two parameters (slope and y intercept), is then further parameterized by fitting these two parameters as polynomial functions of aerosol size d. A comparison of the new parameterization with limited measurements in the literature in terms of the magnitude of λ and the relative magnitudes of λrain and λsnow suggests that it is a reasonable approximation. Advantages of this new semiempirical parameterization compared to traditional theoretical formulations for λ include its applicability to belowcloud scavenging by both rain and snow over a wide range of particle sizes and precipitation intensities, ease of implementation in any CTM with a representation of size-distributed particulate matter, and a known representativeness, based on the consideration in its development, of all available theoretical formulations and field-derived estimates for λ(d) and their associated uncertainties. © 2014 Author(s). Source


Wang X.,Kellys Environmental Services | Zhang L.,Environment Canada | Moran M.D.,Environment Canada
Atmospheric Chemistry and Physics | Year: 2010

Current theoretical and empirical size-resolved parameterizations of the scavenging coefficient (Î?), a parameter commonly used in aerosol transport models to describe below-cloud particle scavenging by rain, have been reviewed in detail and compared with available field and laboratory measurements. Use of different formulations for raindrop-particle collection efficiency can cause uncertainties in size-resolved values of one to two orders of magnitude for particles in the 0.01-3 1/4m diameter range. Use of different formulations of raindrop number size distribution can cause values to vary by a factor of 3 to 5 for all particle sizes. The uncertainty in caused by the use of different droplet terminal velocity formulations is generally small than a factor of 2. The combined uncertainty due to the use of different formulations of raindrop-particle collection efficiency, raindrop size spectrum, and raindrop terminal velocity in the current theoretical framework is not sufficient to explain the one to two order of magnitude under-prediction of Î? for the theoretical calculations relative to the majority of field measurements. These large discrepancies are likely caused by additional known physical processes (i.e, turbulent transport and mixing, cloud and aerosol microphysics) that influence field data but that are not considered in current theoretical Î? parameterizations. The predicted size-resolved particle concentrations using different theoretical parameterization can differ by up to a factor of 2 for particles smaller than 0.01 1/4m and by a factor of >10 for particles larger than 3 1/4m after 2-5 mm of rain. The predicted bulk mass and number concentrations (integrated over the particle size distribution) can differ by a factor of 2 between theoretical and empirical parameterizations after 2-5 mm of moderate intensity rainfall. © 2010 Author(s). Source


Wang X.,Kellys Environmental Services | Zhang L.,Environment Canada | Moran M.D.,Environment Canada
Atmospheric Chemistry and Physics | Year: 2011

Existing theoretical formulations for the size-resolved scavenging coefficient Λ(d) for atmospheric aerosol particles scavenged by rain predict values lower by one to two orders of magnitude than those estimated from field measurements of particle-concentration changes for particles smaller than 3 μm in diameter. Vertical turbulence is not accounted for in the theoretical formulations of Λ(d) but does contribute to the field-derived estimates of Λ(d) due to its influence on the overall concentration changes of aerosol particles in the layers undergoing impaction scavenging. A detailed one-dimensional cloud microphysics model has been used to simulate rain production and below-cloud particle scavenging, and to quantify the contribution of turbulent diffusion to the overall Λ(d) values calculated from particle concentration changes. The relative contribution of vertical diffusion to below-cloud scavenging is found to be largest for submicron particles under weak precipitation conditions. The discrepancies between theoretical and field-derived Λ(d) values can largely be explained by the contribution of vertical diffusion to below-cloud particle scavenging for all particles larger than 0.01 μm in diameter for which field data are available. The results presented here suggest that the current theoretical framework for Λ(d) can provide a reasonable approximation of below-cloud aerosol particle scavenging by rain in size-resolved aerosol transport models if vertical diffusion is also considered by the models. © 2011 Author(s). Source


Wang X.,Kellys Environmental Services | Zhang L.,Environment Canada | Moran M.D.,Environment Canada
Journal of Advances in Modeling Earth Systems | Year: 2014

Bulk or modal parameterizations for below-cloud mass and number scavenging coefficients Îm (s-1) and În (s-1) of three aerosol modesâfine (PM2.5), coarse (PM2.5-10), and giant (PM10+)âfor both rain and snow scavenging are developed for use in modal-approach aerosol transport models. The new bulk parameterizations are based on the size-resolved Î(d) parameterization of Wang et al. (2014), using assumed lognormal mass and number size distributions for PM2.5, PM2.5-10, and PM10+. The resulting modal-mean formulas for Îm and În follow power law relationships with precipitation intensity R, consistent with most existing studies. The empirical parameters in the power law relationships obtained in this study are also within the range of parameter values obtained in previous field and theoretical studies. Uncertainties in Îm due to the size distribution or size range assumed for each aerosol mode are generally smaller than 30% for PM2.5-10 and PM10+ but could be on the order of factor of 2 for PM2.5. These uncertainties, however, are much smaller than other known uncertainties in existing Î formulations, which are typically larger than 1 order of magnitude. Moreover, the new bulk parameterizations are believed to be more representative than most existing schemes because the size-resolved parameterization of Wang et al. (2014), which they are based on, was developed with consideration of all available theoretical formulations and field-derived estimates for size-resolved Î and their associated uncertainties. © 2014. The Authors. Source


Zhang L.,Environment Canada | Wang X.,Kellys Environmental Services | Moran M.D.,Environment Canada | Feng J.,Environment Canada
Atmospheric Chemistry and Physics | Year: 2013

Theoretical parameterizations for the size-resolved scavenging coefficient for atmospheric aerosol particles scavenged by snow (Λsnow) need assumptions regarding (i) snow particle-aerosol particle collection efficiency E, (ii) snow-particle size distribution N(Dp), (iii) snow-particle terminal velocity VD, and (iv) snow-particle cross-sectional area A. Existing formulas for these parameters are reviewed in the present study, and uncertainties in Λsnow caused by various combinations of these parameters are assessed. Different formulations of E can cause uncertainties in Λsnow 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 (Λrain) as was found in a previous study by Wang et al. (2010). However, other parameters can also cause significant uncertainties in Λsnow, and the uncertainties from these parameters are much larger than for Λrain. Specifically, different N(Dp) formulations can cause one-order-of-magnitude uncertainties in Λsnow for all aerosol sizes, as is also the case for a combination of uncertainties from both VD and A. Assumptions about dominant snow-particle shape (and thus different VD and A) will cause an uncertainty of up to one order of magnitude in the calculated scavenging coefficient. In comparison, uncertainties in Λrain from N(Dp) are smaller than a factor of 5, and those from VD are smaller than a factor of 2. As expected, Λsnow 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 Λsnow but that are not considered in the theoretical Λsnow formulas. Predicted aerosol concentrations obtained by using upper range vs. lower range of Λsnow values (a difference of around two orders of magnitude in Λsnow) 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 Λsnow and Λsnow 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. © Author(s) 2013. Source

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