Evaluation and Improvement of Dry Deposition Algorithms

The first study quantifies differences between dry deposition algorithms commonly used in North America. Five models were selected to calculate dry deposition velocity (V_d) for O₃ and SO₂ over a temperate mixed forest in southern Ontario, Canada where a five-year flux database had previously been developed. Differences in mean V_d values between models were on the order of a factor of 2 in both summer and winter. Several models produced magnitudes of the diel variation of V_d(O₃) comparable to the measurements, while all models produced slightly smaller diel variations than the measurements of V_d(SO₂) in summer. A few models produced larger diel variations than the measurements of V_d for O₃ and SO₂ in winter. Model differences were mainly due to different surface resistance parameterizations for stomatal and non-stomatal uptake pathways, while differences in aerodynamic and quasi-laminar resistances played only a minor role. Modeled V_d in summer was sensitive to the minimum stomatal resistance and, in winter, to the canopy snow cover fraction. It is recommended that users of inferential dry deposition models consider an uncertainty factor of 2 or use ensemble modeling results for ecosystem assessment analysis.

The second study extends the gaseous dry deposition algorithm of Zhang et al. (2003) to include additional 14 oxidized volatile organic compounds (oVOC). Model parameters were selected mainly based on oVOC’s physical and chemical properties, and to some extent also based on limited flux measurements over a mixed forest. The model captured well the diel cycles of the observed V_d for most chemical species. Modeled V_d were comparable to the measurements for most of the oVOCs during the nighttime, but were lower during the daytime, e.g., with the maximum daytime V_d typically at 1 cm/s from the model versus 2-5 cm/s from the measurement. The very high V_d from measurements could be partially due to fast chemical reactions within the canopy, and the model is designed to provide relatively conservative estimates of V_d for most oVOC species, considering the flux data are still very limited. Based on the knowledge obtained from the model evaluations, model parameters for the 22 previously model oVOC species were also adjusted to slightly increase their V_d.

The third study revises a widely used size-resolved particle dry deposition algorithm of Zhang et al. (2001). The original model is able to reasonably predict V_d for bulk PM_2.5 and PM₁₀, but tends to overpredict V_d for particles smaller than 0.1 µm, especially over smooth surfaces. A revision is proposed to reduce the collection efficiencies by Brownion diffusion for most LUCs and increasing interception collection efficiencies for forest canopies so the modelled V_d can better fit field data over most of the land types. Such a modification may not have significant impact on the predicted bulk aerosol mass concentration, but has important implications to aerosol number concentration, which is of concern in studying climate-related issues.