An experimental and theoretical investigation of the dry deposition of particles to snow, pine trees and artificial collectors

Ibrahim, Mohammed; Barrie, Leonard A.; Fanaki, F.

doi:10.1016/0004-6981(83)90427-4

Cited by 108 publications

(53 citation statements)

References 17 publications

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“…Over ice/snow surface, the results suggest that the ZH14 is the most accurate parameterization, and PZ10 is the least accurate. Qualitatively, this finding is consistent with Petroff and Zhang (2010), who reported that their model significantly underestimated the measured deposition velocities over ice/snow surface for the following studies: Ibrahim et al (1983), Duan et al (1988), Nilsson and Rannik (2001), and Contini et al (2010), which were also investigated in the present study. We also note that the Z01 parameterization overestimated the measured V d from the aforementioned studies.…”

Section: Discussionsupporting

confidence: 93%

“…We note that the studies by Möller and Schumann (1970) and Sehmel et al (1974) were conducted in the wind tunnels, and thus the observed deposition does not necessarily reflect deposition under natural conditions. Particle deposition measurements on ice/snow pack were collected from eight studies: Ibrahim et al (1983), Duan et al (1988), Nilsson and Rannik (2001), Gronlund et al (2002), Contini et al (2010), Held et al (2011a, b), and Donateo and Contini (2014). The parameterizations were fed using reported values of particle properties (diameter and density), meteorological conditions (stability parameter, temperature, wind speed, etc.…”

Section: An Evaluation Of the Dry Deposition Parameterizationsmentioning

confidence: 99%

“…Two studies over snow (Ibrahim et al, 1983;and Duan et al, 1988) and six studies over ice surfaces (Nilsson and Rannik, 2001;Gronlund et al, 2002;Contini et al, 2010;Held et al, 2011a, b;and Donateo and Contini, 2014) were used to evaluate the accuracy of the four parameterizations (Z01, PZ10, KS12, and ZH14) for smooth surfaces. The ZS14 parameterization was not included here because it does not allow prediction of deposition over ice/snow surfaces.…”

Section: Evaluation Of Dry Deposition To Snow and Ice Surfacesmentioning

confidence: 99%

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Evaluation of five dry particle deposition parameterizations for incorporation into atmospheric transport models

Khan

Perlinger

2017

Geosci. Model Dev.

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Abstract. Despite considerable effort to develop mechanistic dry particle deposition parameterizations for atmospheric transport models, current knowledge has been inadequate to propose quantitative measures of the relative performance of available parameterizations. In this study, we evaluated the performance of five dry particle deposition parameterizations developed by Zhang et al. (2001) ("Z01"), Petroff and Zhang (2010) ("PZ10"), Kouznetsov and Sofiev (2012) ("KS12"), Zhang and He (2014) ("ZH14"), and Zhang and Shao (2014) ("ZS14"), respectively. The evaluation was performed in three dimensions: model ability to reproduce observed deposition velocities, V d (accuracy); the influence of imprecision in input parameter values on the modeled V d (uncertainty); and identification of the most influential parameter(s) (sensitivity). The accuracy of the modeled V d was evaluated using observations obtained from five land use categories (LUCs): grass, coniferous and deciduous forests, natural water, and ice/snow. To ascertain the uncertainty in modeled V d , and quantify the influence of imprecision in key model input parameters, a Monte Carlo uncertainty analysis was performed. The Sobol' sensitivity analysis was conducted with the objective to determine the parameter ranking from the most to the least influential. Comparing the normalized mean bias factors (indicators of accuracy), we find that the ZH14 parameterization is the most accurate for all LUCs except for coniferous forest, for which it is second most accurate. From Monte Carlo simulations, the estimated mean normalized uncertainties in the modeled V d obtained for seven particle sizes (ranging from 0.005 to 2.5 µm) for the five LUCs are 17, 12, 13, 16, and 27 % for the Z01, PZ10, KS12, ZH14, and ZS14 parameterizations, respectively. From the Sobol' sensitivity results, we suggest that the parameter rankings vary by particle size and LUC for a given parameterization. Overall, for d p = 0.001 to 1.0 µm, friction velocity was one of the three most influential parameters in all parameterizations. For giant particles (d p = 10 µm), relative humidity was the most influential parameter. Because it is the least complex of the five parameterizations, and it has the greatest accuracy and least uncertainty, we propose that the ZH14 parameterization is currently superior for incorporation into atmospheric transport models.

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Section: Discussionsupporting

confidence: 93%

Section: An Evaluation Of the Dry Deposition Parameterizationsmentioning

confidence: 99%

Section: Evaluation Of Dry Deposition To Snow and Ice Surfacesmentioning

confidence: 99%

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Evaluation of five dry particle deposition parameterizations for incorporation into atmospheric transport models

Khan

Perlinger

2017

Geosci. Model Dev.

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“…Again, it should be noted that our aerosol number fluxes are dominated by sub-50 nm particles. Ibrahim et al (1983) report aerosol deposition velocities of v t = 0.39 mm s −1 under stable stratification, and v t = 0.96 mm s −1 under unstable conditions using 35 S tagged ammonium sulfate particles 0.7 µm in diameter. Bergin et al (1995) derived aerosol sulfate deposition velocities ranging from 0.23 mm s −1 to 0.62 mm s −1 at Summit, Greenland, based on particle mass using surrogate surfaces (particle diameter <15 µm) and impactor data (particle diameter <10 µm).…”

Section: Aerosol Flux Observations -Division Into Sectorsmentioning

confidence: 98%

On the potential contribution of open lead particle emissions to the central Arctic aerosol concentration

et al. 2011

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Abstract. We present direct eddy covariance measurements of aerosol number fluxes, dominated by sub-50 nm particles, at the edge of an ice floe drifting in the central Arctic Ocean. The measurements were made during the ice-breaker borne ASCOS (Arctic Summer Cloud Ocean Study) expedition in August 2008 between 2 • -10 • W longitude and 87 • -87.5 • N latitude. The median aerosol transfer velocities over different surface types (open water leads, ice ridges, snow and ice surfaces) ranged from 0.27 to 0.68 mm s −1 during depositiondominated episodes. Emission periods were observed more frequently over the open lead, while the snow behaved primarily as a deposition surface. Directly measured aerosol fluxes were compared with particle deposition parameterizations in order to estimate the emission flux from the observed net aerosol flux. Finally, the contribution of the open lead particle source to atmospheric variations in particle number concentration was evaluated and compared with the observed temporal evolution of particle number. The direct emission of aerosol particles from the open lead can explain only 5-10% of the observed particle number variation in the mixing layer close to the surface.

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“…Reported measured and modelled values indicate that p-NO 3 has a somewhat more limited range in v d to snow, from close to zero (Ibrahim et al, 1983;Bergin et al, 1995;Nilsson and Rannik, 2001) to around 4 cm s (1 (Cress et al, 1995;Rattray and Sievering, 2001), where the v d of p-NO 3 is strongly dependent on the size of the particle the nitrate is associated with (Seinfeld and Pandis, 2006). Deposition velocity to snow is also known to be temperature dependent for HNO 3 among other species, where a low v d is estimated at colder temperatures (Granat and Johansson, 1983;Johansson and Granat, 1986 (Beine et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Nitrate dry deposition in Svalbard

Björkman

Kühnel

Partridge

et al. 2013

Tellus B: Chemical and Physical Meteorology

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A B S T R A C T Arctic regions are generally nutrient limited, receiving an extensive part of their bio-available nitrogen from the deposition of atmospheric reactive nitrogen. Reactive nitrogen oxides, as nitric acid (HNO 3 ) and nitrate aerosols (p-NO 3 ), can either be washed out from the atmosphere by precipitation or dry deposited, dissolving to nitrate (NO À 3 ). During winter, NO À 3 is accumulated in the snowpack and released as a pulse during spring melt. Quantification of NO À 3 deposition is essential to assess impacts on Arctic terrestrial ecology and for ice core interpretations. However, the individual importance of wet and dry deposition is poorly quantified in the high Arctic regions where in-situ measurements are demanding. In this study, three different methods are employed to quantify NO and p-NO 3 using atmospheric concentrations and stability observations, resulting in a total combined nitrate dry deposition of Á10.7691.26 mg m (2 . The model indicates that deposition primarily occurs via HNO 3 with only a minor contribution by p-NO 3 . Modelled median deposition velocities largely explain this difference: 0.63 cm s (1 for HNO 3 while p-NO 3 was 0.0025 and 0.16 cm s (1 for particle sizes 0.7 and 7 mm, respectively.Overall, the three methods are within two standard errors agreement, attributing an average 14% (total range of 2Á44%) of the total nitrate deposition to dry deposition. Dry deposition events were identified in association with elevated atmospheric concentrations, corroborating recent studies that identified episodes of rapid pollution transport and deposition to the Arctic.

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An experimental and theoretical investigation of the dry deposition of particles to snow, pine trees and artificial collectors

Cited by 108 publications

References 17 publications

Evaluation of five dry particle deposition parameterizations for incorporation into atmospheric transport models

Evaluation of five dry particle deposition parameterizations for incorporation into atmospheric transport models

On the potential contribution of open lead particle emissions to the central Arctic aerosol concentration

Nitrate dry deposition in Svalbard

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