Eddy correlation measurements of aerosol deposition to grass

Vong, Richard J.; Vickers, Dean; Covert, David S.

doi:10.3402/tellusb.v56i2.16414

Cited by 32 publications

(39 citation statements)

References 28 publications

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“…Two approaches to correcting this problem, which differ in their choice of particle growth formula, are outlined in Kowalski (2001) and Vong et al (2004). We use here the model of Vong et al, which assumes a particle growth with humidity of…”

Section: Corrections and Filteringmentioning

confidence: 99%

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Aerosol flux measurements above a mixed forest at Borden, Ontario

et al. 2011

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Abstract. Aerosol fluxes were measured above a mixed forest by Eddy Covariance (EC) with a Fast Mobility Particle Sizer (FMPS) at the Borden Forest Research Station in Ontario, Canada between 13 July and 12 August 2009. Chemically speciated flux measurements were made at a height of 29 m at the same location between 19 July and 2 August, 2006 using a Quadrupole Aerosol Mass Spectrometer (Q-AMS). The Q-AMS measured an average sulphate deposition velocity of 0.3 mm s −1 and an average nitrate deposition velocity of 4.8 mm s −1 . The FMPS, mounted at a height of 33 m (approximately 10 m above the canopy top) and housed in a temperature controlled enclosure, measured sizeresolved particle concentrations from 3 to 410 nm diameter at a rate of 1 Hz. For the size range 18 < D < 452 nm, 60 % of fluxes were upward. The exchange velocity was between −0.5 and 2.0 mm s −1 , with median values near 0.5 mm s −1 for all sizes between 22 and 310 nm. The size distribution of the apparent production rate of particles at 33 m peaked at a diameter of 75 nm. Results indicate a decoupling of the above and below canopy spaces, whereby particles are stored in the canopy space at night, and are then diluted with cleaner air above during the day.

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Section: Corrections and Filteringmentioning

confidence: 99%

“…The hygroscopic growth parameter is assumed to be γ = 0.214, which Swietlicki et al (2000) suggest for "aged European air". As shown in Vong et al (2004), the deposition velocity correction is…”

Section: Corrections and Filteringmentioning

confidence: 99%

Aerosol flux measurements above a mixed forest at Borden, Ontario

et al. 2011

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“…In daytime, when the average atmospheric relative humidity was 70-80% in this study, the hygroscopic growth of the most hygroscopic particles will be only 1-2%. The error due to hygroscopic growth (Fairall, 1984;Kowalski, 2001;Vong et al, 2004) can be estimated by calculating the saturation ratio flux (Fairall, 1984) and by assuming a particle size distribution in the Junge form (Junge, 1963). This error can be large when the slope of the number distribution is steep.…”

Section: Flux Measurementsmentioning

confidence: 99%

Emission and dry deposition of accumulation mode particles in the Amazon Basin

et al. 2010

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Abstract. Size-resolved vertical aerosol number fluxes of particles in the diameter range 0.25-2.5 µm were measured with the eddy covariance method from a 53 m high tower over the Amazon rain forest, 60 km NNW of Manaus, Brazil. This study focuses on data measured during the relatively clean wet season, but a shorter measurement period from the more polluted dry season is used as a comparison. Size-resolved net particle fluxes of the five lowest size bins, representing 0.25-0.45 µm in diameter, were in general dominated by deposition in more or less all wind sectors in the wet season. This is an indication that the source of primary biogenic aerosol particles may be small in this particle size range. Transfer velocities within this particle size range were observed to increase linearly with increasing friction velocity and increasing particle diameter.In the diameter range 0.5-2.5 µm, vertical particle fluxes were highly dependent on wind direction. In wind sectors where anthropogenic influence was low, net upward fluxes were observed. However, in wind sectors associated with higher anthropogenic influence, deposition fluxes dominated. The net upward fluxes were interpreted as a result of primary biogenic aerosol emission, but deposition of anthropogenic particles seems to have masked this emission in wind sectors with higher anthropogenic influence. The net emission fluxes were at maximum in the afternoon when the mixed layer is well developed, and were best correlated with horizontal wind speed according to the equationwhere F is the net emission number flux of 0.5-2.5 µm particles [m −2 s −1 ] and U is the horizontal wind speed [ms −1 ] at the top of the tower.

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“…Five measurement studies conducted on grass (Wesely et al, 1977;Allen et al, 1991;Neumann and den Hartog, 1985;Nemitz et al, 2002;and Vong et al, 2004) were used to evaluate the accuracy of the parameterizations. In those studies, reported values of meteorological parameters, canopy properties, and particle size vary widely.…”

Section: Evaluation Of Dry Deposition To Grassmentioning

confidence: 99%

“…1 according to the five LUCs. Measurements conducted over grass by Wesely et al (1977), Neumann and den Hartog (1985), Allen et al (1991), Nemitz et al (2002), and Vong et al (2004) were used to evaluate the performance of the five parameterizations. For coniferous forest, modeled deposition velocities were compared with measurements from Lamaud et al (1994), Wyzers and Duyzer (1996), Gallagher et al (1997), Ruijgrok et al (1997), Buzorius et al (2000), Rannik et al (2000), Gaman et al (2004), Pryor et al (2007), and Grönholm et al (2009).…”

Section: An Evaluation Of the Dry Deposition Parameterizationsmentioning

confidence: 99%

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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Eddy correlation measurements of aerosol deposition to grass

Cited by 32 publications

References 28 publications

Aerosol flux measurements above a mixed forest at Borden, Ontario

Aerosol flux measurements above a mixed forest at Borden, Ontario

Emission and dry deposition of accumulation mode particles in the Amazon Basin

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

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