Aerosol particle dry deposition velocity above natural surfaces: Quantification according to the particles diameter

Aerosol particle dry deposition velocity above natural surfaces: Quantification according to the particles diameter

Journal of Aerosol Science 114 (2017) 107–117 Contents lists available at ScienceDirect Journal of Aerosol Science journal homepage: www.elsevier.co...

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Journal of Aerosol Science 114 (2017) 107–117

Contents lists available at ScienceDirect

Journal of Aerosol Science journal homepage: www.elsevier.com/locate/jaerosci

Aerosol particle dry deposition velocity above natural surfaces: Quantification according to the particles diameter

MARK



G. Pellerina,b, , D. Maroa, P. Damaya, E. Gehinb, O. Connana, P. Laguioniea, D. Héberta, L. Soliera, D. Boulaudc, E. Lamaudd, X. Charriere a

Institut de Radioprotection et de Sûreté Nucléaire, PSE-ENV/SRTE/LRC, BP 10 Rue Max-Pol Fouchet, 50130 Cherbourg Octeville, France Université Paris-Est (UPE), Centre d’Etudes et de Recherches en Thermique Environnement et Systèmes (CERTES), EA 3481, Université Paris-Est Créteil Val de Marne (UPEC), Créteil, France c Institut de Radioprotection et de Sûreté Nucléaire, PSE-ENV, Le Vésinet, France d Institut National de Recherche en Agronomie, Unité Interaction Sol Plante Atmosphère, Villenave d’Ornon, France e Institut National de Recherche en Agronomie, Unité Fourrages Environnement Ruminants Lusignan, France b

AR TI CLE I NF O

AB S T R A CT

Keywords: Index: Atmospheric aerosol Eddy correlation Cospectral analysis Dry deposition velocities Ultrafine particles Emission

To assess the impact of an accidental or chronic radionuclide release in form of aerosol particles in the atmosphere, it is important to study their dry deposition in a rural environment. For particles of less than 1 µm, there is a lack of experimental data in this regard, leading to uncertainty in terms of the results of models, which can reach up to two orders of magnitude (Petroff Mailliat, Amielh, & Anselmet, 2008). Moreover, there is no in situ deposition velocity measurement data available for particles that are smaller than 10 nm. The objective of this study is to measure and analyse the dry deposition velocity for aerosol particles with a particle size of between 2.5 nm and 1.2 µm, with particular focus on the particle size range of 2.5–14 nm. To this end, an in situ experimental method based on eddy correlation was used. This method uses an Electrical Low Pressure Impactor (ELPI, DEKATI) for particles of between 7 nm and 1.2 µm and an original method that entails coupling two condensation particle counters (CPC 3788 and 3786, TSI). Seven experimental campaigns were conducted between 2007 and 2015, during which the dry deposition velocities (Vd in m.s−1) were obtained for atmospheric aerosol particles of size between 2.5 nm and 1.2 µm in size, above different natural surfaces (maize, grassland, bare soil and forest). The findings highlight the influence of the following parameters: friction velocity of the wind, surface sensible heat flux and atmospheric stability (quantified by the length of Monin-Obukhov). Comparing the findings for each natural surface revealed it can reasonably be assumed that the influence of each natural surface on deposition is mainly explained in the data provided by friction velocity (u* m.s−1). The other parameters related to the natural surface, such as the Leaf Area Index (LAI) or vegetation cover properties (adherence, micro roughness), have a second order impact on all the findings.

1. Introduction The particles, present in the atmosphere, may undergo different processes, such as atmospheric dispersion, deposition in dry



Corresponding author at: Institut de Radioprotection et de Sûreté Nucléaire, PSE-ENV/SRTE/LRC, BP 10 Rue Max-Pol Fouchet, 50130 Cherbourg Octeville, France. E-mail addresses: geoff[email protected] (G. Pellerin), [email protected] (D. Maro), [email protected] (E. Gehin), [email protected] (O. Connan), [email protected] (P. Laguionie), [email protected] (D. Hébert), [email protected] (L. Solier), [email protected] (D. Boulaud), [email protected] (E. Lamaud), [email protected] (X. Charrier). http://dx.doi.org/10.1016/j.jaerosci.2017.09.004 Received 3 February 2017; Received in revised form 4 May 2017; Accepted 2 September 2017 Available online 08 September 2017 0021-8502/ © 2017 Elsevier Ltd. All rights reserved.

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weather or deposition in wet weather. Dry deposition is the removal process through which aerosol particles are taken up by the Earth's surface while in the process of wet deposition, particles first have to be incorporated into hydrometeors and then delivered to the surface via precipitation (Zhang & Vet, 2006). Studying dry deposition, through dry deposition velocity, is an important challenge to be overcome in order to quantify the impact of radionuclides on populations and the environment. Furthermore, the large uncertainties of the dry deposition velocity are for submicron particles (Pryor, Larsen, Sørensen, & Barthelmie, 2008; Rannik, Peltola, & Mammarella, 2016) and are several orders of magnitude, following the models applied (Gallagher et al., 1997; Petroff et al., 2008; Ruijgrok, Tieben, & Eisinga, 1997; Slinn, 1982; Zhang, Gong, Padro, & Barrie, 2001). Estimates from some of these models (Hicks, Saylor, & Baker, 2016) revealed that they differ from each other greatly and the largest uncertainty is for the 0.2–1.0 µm particle size range, for which the deposition velocities can vary by 2–3 orders of magnitude. In fact, the deposition velocities predicted by different models for particles less than about 0.2 µm diameters are in fair agreement with observations, but this is not the case for particles in the range 0.3 to about 5 µm (Hicks et al., 2016). To explain this, experimentalists noted the inability of models to take all of the known processes fully into account, while at the same time representing known processes in ways that appeared limited by the small scales of the formative wind tunnel studies. The outstanding problem is to consolidate this understanding in a way that accurately portrays the behaviour of a natural landscape. In fact for this difference between model and field measurement of deposition velocities may be explain by micrometeorological parameters influence: for example, the dry deposition velocity is very poorly quantified as a function of surface roughness (Gallagher et al., 2002), wind friction velocity and sensible heat flux (Damay, 2010; Fowler et al., 2009; Pryor et al., 2007). Moreover, there is no in situ data available for particles smaller than 10 nm. A few studies have been conducted in wind tunnels, focusing on the free fraction of radon deposition (particles of 1 nm in size) (Chamberlain, 1966; Porstendörfer, 1994; Porstendorfer, Robig, & Ahmed, 1980). In this context, the objective of this study was to quantify the dry deposition velocity of the particles as a function of their size (from 2.5 nm to 1.2 µm), of micrometeorological parameters and of the surface characteristics. A eddy correlation (EC) method, in accordance with the method used by Damay et al. (2009), was used to measure dry deposition fluxes and then generate dry deposition velocities. The method was based on analysing fluctuations, over a 30-minute period, of the vertical component of the wind velocity and of the atmospheric aerosol particles concentration measured for different particle sizes. This flux measurement technique has been implemented at three sites in France. At the Mano site (south-west France), as part of the Landes 1–4 campaigns, the research focused on grassland (October 2007), bare soil (March 2008) and maize (June 2007 and 2008) (Damay, 2010). Measurements above forest were then performed at the Bilos site (south-west France; July 2014) as part of the REMORA project campaign. Finally, as part of DEPECHMOD 1 and 2 campaigns, measurements were implemented above a grassland at the Lusignan site (south-west France) in April and September 2015. The first part of this document describes the methodology and the equipment used. A second part is devoted to analysing and discussing the results, with specific focus on any results highlighting the process that contributes to aerosol particles emission. To finish, the influence that the surface characteristics, micrometeorological parameters and particle size have on dry deposition velocity will be showed. 2. Methodology 2.1. Experimental sites Seven experimental campaigns have been conducted above different natural surfaces between 2007 and 2015. Table 1 lists the date of the seven experimental campaigns, as well as the natural surfaces studied and their homogeneity and also the devices used. In the rest of the study, arbitrary z0/h = 0.1 et d/h = 0.75 (Hicks, Hyson, & Moore, 1975; Raupach, 1994; Stanhill, 1969) with z0 the roughness length, d the displacement height and h the cover height. For the bare soil, z0 was calculated with the Eq. (1) because the vegetation started to regrowth at different places on the cover and so could modify the cover roughness.

u (z ) =

u* ⎛ z − d ⎞ ln κ ⎝ z0 ⎠ ⎜



(1)

Where u(z) is the horizontal wind speed at altitude z, κ the Von Karman constant and u* the wind friction velocity Different devices for aerosol particles concentration have been used during these campaigns. For the particle size range of between 2.5 nm and 14 nm, the aerosol concentration was measured simultaneously by coupling two condensational particle counters (CPC 3788 or 3786, TSI, Inc.) (Twin CPC Method, (Buzorius, Rannik, Nilsson, & Kulmala, 2001; Held & Klemm, 2006)). For the particle size range of between 7 nm to 10 µm, an electrical low pressure impactor (ELPI, Dekati Inc.) is used. The three wind velocity components and the temperature were measured using an ultrasonic anemometer (Young 81000, Inc.). 2.1.1. Mano site: Landes 1, 2, 3 and 4 campaigns Four measurement campaigns between 2007 and 2008 were completed on a farm site, as part of research conducted by Damay (2010). During these four campaigns, an ELPI was used to obtain flux measurements of aerosol particles. The measurement site was set up a few kilometres apart a farm in the Mano commune (Latitude: 44, 24030; Longitude: −0, 38382), located in the Landes at approximately 70 km south of Bordeaux in France. The seasonal changes of a maize field, surrounded by forest (chiefly composed of Landes pine trees), provided the various substratum studied. The natural surface studied during the Landes 1 campaign was maize. A change of soil type was the main reason 108

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Table 1 General description of the different campaigns. Campaign (Date)

Type of cover (height)

Devices used (particle size range)

Measurement height

Surface homogeneity

Roughness length (z0)

Displacement height (d)

Landes 1 (13th to 17th June 2007) Landes 2 (16th to 23rd October 2007) Landes 3 (4th to 10th March 2008) Landes 4 (24th June to 2nd July 2008) REMORA NEEDS (30th June to 11th July 2014) DEPECHEMOD 1 (22nd to 30th April 2015)

Maize (1.3 m)

ELPI (7 nm to 1.2 µm)

6m

> 700 m

0.13 m

1m

Grassland (0.2 m)

ELPI (7 nm to 1.2 µm)

6m

> 700 m

0.02 m

0.15 m

Bare soil (0.05 m)

ELPI (7 nm to 1.2 µm)

6m

> 700 m

0.02 m

0.04 m

Maize (1.3 m)

ELPI (7 nm to 1.2 µm)

6m

> 700 m

0.13 m

1m

Landes pine trees (8 m)

ELPI (7 nm to 1.2 µm)

12 m

> 600 m

0.8 m

6m

Grassland (0.5 m)

ELPI (7 nm to 1.2 µm) Twin CPC (2.5–14 nm) ELPI (7 nm to 1.2 µm) Twin CPC (2.5–14 nm)

5m

> 700 m

0.05 m

0.4 m

> 700 m

0.04 m

0.3 m

Grassland (0.4 m)

DEPECHEMOD 2 (22nd September to 1st October 2015)

2m 5m 2m

behind performing the Landes 2 campaign in October 2007. The measurements were performed above grass, rather than above a cover composed of maize plants. In March 2008, the Landes 3 measurement campaigns were performed on the same field but this time it is plowed and so the cover could be assimilated to a bare soil. The Landes 4 campaign took place one year after the Landes 1 campaign (June 2008). This campaign confirmed the findings from the previous campaigns and provided additional measurements from above a maize field. 2.1.2. Bilos site: REMORA campaign In June 2014, within the framework of the NEEDS REMORA project, a measurement campaign was conducted above the INRA ICOS site located in Bilos made up of Landes forest, at 50 km from Bordeaux (Latitude: 44,4939; Longitude: −0,9559). The natural surface in this case was a Landes pine forest, approximately 8 m high. This campaign was used to perform research into natural surfaces different to those studied by Damay (2010) and to obtain dry deposition velocity measurements, thanks to the ELPI, on a low studied cover. 2.1.3. Lusignan site: DEPECHEMOD 1 and 2 campaigns The DEPECHEMOD campaigns were conducted in the middle of a grassland (46°25, 02’N; 0°7, 08’E) in the INRA site in Lusignan (France), located 30 km from Poitiers. The new results from the DEPECHEMOD campaign lay in the dry deposition velocity measurements of ultrafine particles. So, during DEPECHEMOD 1, in addition to the measurement of dry deposition by an ELPI, measurements using the twin CPC method were completed with two different devices (TSI 3786 and 3788.) During DEPECHEMOD 2 campaign, the two CPCs were similar (TSI 3788). For the wind directions between [0°; 20°] and [330°; 360°], the buildings could modify the atmospheric turbulence, and, therefore, the dry deposition velocity. As such, any data where the wind came from this direction was not taken into account in this study. 2.2. Eddy correlation method (EC method) 2.2.1. Brief description of the theory In stationary situation, and if the horizontal homogeneity is confirmed, the vertical flux of particles could be determined by covariance analysis between the vertical wind velocity w and the particle concentration (turbulent correlation method). If the cospectral analysis of the vertical wind velocity and the particle concentration is applied, the flux can be expressed as follows (Kaimal & Finnigan, 1994):

F = w′C ′ =

∫n

nf

0

Co wc (n) dn

(2)

Where n0 is the lowest frequency that can be measured on a sample over time t. In this example, the time spent to process the samples is half an hour, n0 is therefore approximately 10−3 Hz. nf corresponds with the spectral response threshold of the measurement 109

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devices. This technique requires rapid aerosol sampling, i.e. at a frequency greater than 10 Hz (Businger, 1986) to ensure compatibility with the atmospheric turbulence scale. A response time of more than 0.1 s entails underestimating the flux, since there is a signal attenuation in the high frequency range. However, few systems measuring the concentration in submicron particles in the environment can perform sampling at such a high frequency. As such, to assess this under-estimation of particle flux, an original correction method was created based on the similarities between the cospectra of aerosol particles flux w′C ′’ and the cospectra of sensible heat flux (H = ρCpw′T ′) noted w′T ′ normalized by the flux and weighted by the natural frequency in the surface layer (Damay et al., 2009; Lamaud, Chapuis, Fontan & Serie, 1994). In fact, this method allowed the reconstruction of the cospectra of aerosol particles flux by the cospectra of sensible heat flux to remove the cospectral loss at high frequency. In addition, this methodology also corrects low frequency oscillations sometimes observed. Tests on the quality of turbulent data were performed (Foken & Wichura, 1996), and made it possible to check well-developed turbulence layer (surface layer) and signal stationary. Corrections of the density fluctuations are not taken in account because we used closed-path sensors and the sampling tubes length was important. The phenomenon of deliquescence are also not taken in account but the ELPI, the two CPCs and a part of the sampling tubes were in an air-conditioned enclosure at 17 °C and for the most cases the relative humidity was below 80%. Moreover, we do not data detailed information on aerosol composition, so it is not possible to calculate an appropriate growth factor (Kowalski, 2001). 2.2.2. Concentrations measurements for aerosol particles size range between 2 nm and 14 nm: Twin CPC and between 7 nm and 1.2 µm: ELPI The twin CPC method was used during both 2015 campaigns (DEPECHEMOD 1 and 2), to measure the flux through the EC of ultrafine particles: from 2.5 to 14 nm. For DEPECHEMOD 1, CPC 3786, with a response time lower than 2 s (TSI, Inc, 2005), was coupled with CPC 3788, with a response time lower than 100 ms, (TSI, Inc, 2012). For DEPECHEMOD 2, two CPC 3788 were coupled. The minimum detectable particle size of the counter is usually defined as the smallest diameter of particles detected with an efficiency of 50% (Held & Klemm, 2006). The 50% detection limit of CPC 3788 is 2.5 nm. To obtain a concentration for a particle size range between 2.5–14 nm, a diffusion screen is positioned at the inlet of one CPC 3788, operating with a flow rate of 1.5 L min−1. Thanks to this screen, the 50% detection limit is raised to 14 nm. Then, the required concentration range is obtained by calculating the difference between the concentration measurements of the two CPCs. For the particle size range between 7 nm and 1.2 µm, an Electrical Low Pressure Impactor was used. In the atmospheric aerosol concentration ranges (sensitivity of ELPI electrometers of 100000 fA), the ELPI has a response time of 1.6 s (Damay et al., 2009). The different characteristics of the impaction aspects, operating at 30 L min−1, used during the different measurement campaigns have been summarized in Table 2. Because of the detection limit for the three last stages (10, 11 and 12) of the ELPI and the concentration of aerosol particles in the environment for these sizes, the quantification of dry deposition velocity for these three stages, in our case, is not possible. 3. Results and discussion 3.1. Deposition and emission of submicron particles The different campaigns were done to obtain deposition velocities for submicron particles. The first finding is that dry deposition velocity measurements show daily changes related to changes in the micrometeorological parameters (peaks in the middle of the day), especially the wind friction velocity (Donateo & Contini, 2014; Gallagher et al., 2002) and the sensible heat flux (Nemitz, Gallagher, Duyzer, & Fowler, 2002) (Fig. 1). The dry deposition velocity values for particles of 74 nm stand at between 8 × 10−3 m.s−1 (mid-day peak) and 5 × 10−4 m.s−1 (at night) for the two campaigns. This increase in deposition velocity is related to the growth of friction velocity and sensible heat flux. The various changes in the dry deposition velocity of aerosol particles as a function of the weather (presented previously), reveal Table 2 Sizes of aerosol particles measured by ELPI. Stage

Aerodynamic diameter, geometric average (µm), bare soil (Landes, March 2008) and grassland (Landes 2, DEPECHEMOD 1 and 2, October 2007, April and September 2015)

Aerodynamic diameter, geometric average (µm), maize (Landes 1 and 4, June 2007 and 2008) and forest (REMORA, June 2014)

1 2 3 4 5 6 7 8 9 10 11 12

0.014 0.041 0.074 0.122 0.202 0.316 0.484 0.762 1.23 1.96 3.09 6.31

0.014 0.033 0.054 0.092 0.171 0.287 0.456 0.742 1.20 1.90 3.01 6.13

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Fig. 1. Evolution of vertical transfer velocity for the 3rd stage of the ELPI (circles) and of the different micrometeorological parameters: heat sensible flux H (line) and friction velocity u* (broken line), both normalized by their respective maximum: 220 W m−2 and 0.65 m s−1, during the DEPECHEMOD 1 campaign (A) and 137 W m−2 and 0.62 m s−1, during the DEPECHEMOD 2 campaign (B).

a difference of one order of magnitude between the maximum daily values and minimum night values. The micrometeorological parameters, which are the translation of the daily changes in atmospheric turbulence (Lamaud & Chapuis, 1994) must be taken into account. During DEPECHEMOD 2 campaign we can note that on the day of 24 September, there is an emission period during all the day. The second finding that we can confirm, further to the results of all the campaigns, is that there are emission velocities for specific particle sizes. Evolution of emission velocity is similar to the evolution of deposition velocity. The peak in the middle of the day is again observed and is related to the micrometeorological parameters (Fig. 2). The emission velocity values are between −8 × 10−3 m.s−1 for the highest peak in the middle of the day on 28 April 2015 for DEPECHEMOD 1 and 27 September for DEPECHEMOD 2 and fall to almost zero (around −5 × 10−4 m.s−1), with sometimes a few deposition episodes. Fig. 3 shows two comparisons of normalized cospectra of heat sensible flux with cospectra of vertical aerosol particles flux. The first case (A) corresponds to an aerosol particles deposition flux obtained with the Twin CPC method, whereas the second (B) corresponds to an aerosol emission flux obtained with the stage 6 of the ELPI. The cospectra similarities allowed to guarantee the physical character of the phenomena observed (Damay et al., 2009). In this way, the emission phenomenon represented on Fig. 3 is physically real. In addition, this predominance of emission phenomena is related to the diameter of the particles. Fig. 4 shows a predominance, during the different campaigns, of emission phenomena for aerosol particles above 0.1 µm in size, whereas the deposition flux are in a clear majority for smaller aerosol particles (< 0.1 µm). Moreover, this trend is also observed with regard to ultrafine particles corresponding to the CPC method (predominance of deposition). Lamaud and Chapuis (1994) characterized wind erosion as a source of emission flux during the experimental campaign in an arid environment. The wind speeds identified during these measurements were greater than 7 m.s−1. However, this process did not succeed in explaining emission phenomena, given wind velocity values observed during the different campaigns. Furthermore, the range of particle sizes affected by such a process is in the order of 10 µm, while our study is limited to particles with diameters below 1.2 µm. In actual fact, the smaller the particle, the less important wind erosion becomes. This size corresponds to the cut-off diameter between stages 8 and 9 of ELPI. The sizes measured are therefore too small to undergo wind erosion processes that correspond to the measured wind velocities, i.e. lower than 7 m s−1 (Marticorena & Bergametti, 1995). Held, Niessner, Bosveld, Wrzesinsky, and Klemm (2007) describe the conversion of gas particles owing to terpenes as emission flux sources, but their measurements are performed in a forest environment and therefore the emission episodes in other natural surfaces studied in this case cannot be explained by this phenomenon alone. However, the hypothesis of converting gases, emitted by plant cover, into particles is covered in the references for natural surfaces other than forests. Nemitz et al. (2004) observed a similar 111

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Fig. 2. Evolution of vertical transfer velocity for the 5th stage of the ELPI (circles) and of the different micrometeorological parameters: heat sensible flux H (line) and friction velocity u* (broken line), both normalized by their respective maximum: 220 W m−2 and 0.65 m s−1, during the DEPECHEMOD 1 campaign (A) and 137 W m−2 and 0.62 m s−1, during the DEPECHEMOD 2 campaign (B).

Fig. 3. An example of the cospectra corresponding to aerosol deposition (A) and emission (B) fluxes compared with the sensible heat flux cospectra.

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Fig. 4. Proportion of emissive events as a function of geometric diameter of particles for all data from the seven experimental campaigns, from the Twin CPC method (no filled) and ELPI.

distribution between deposition and emission above heathland and explained that the phenomenon is linked to agricultural practices. We thus remark a predominance of emission phenomena that is even more pronounced for natural surfaces that have undergone a recent enrichment (maize during Landes 1 and 4 and grassland for DEPECHEMOD 1 and 2). In addition, we can note that the increase in the number of emission phenomenon occurs when the atmospheric aerosol mode changes: transition from Aitken mode to accumulation mode. Fertilization using nitrogen derivatives, which is applied in our experimental zones (Landes 1–4, DEPECHEMOD 1 and 2), encourages the phenomena of gas conversion (NH3, HNO3). Two phenomenon could happen at this time (Nemitz et al., 2009; Pryor & Binkowski, 2004): (1) Particles of a few nanometers are formed by condensation and because they are highly reactive, they can react among one another to form Aitken mode clusters; these clusters will then coagulate on the atmospheric aerosol accumulation mode; (2) Condense directly on particles in accumulation mode. New particles will therefore appear in accumulation mode, which could be a translation of the vertical emission of these particles. The vertical flux of the aerosol particles emitted were measured and analysed in the references (Deventer, Held, ElMadany, & Klemm, 2015; Nemitz et al., 2004), and the strategy with regard to the positive flux measurements can differ depending on the approach. Some authors (Nemitz et al., 2002) include the emission flux in their total means for calculating normalized flux according to concentration, while keeping the ‘deposition velocity’ designation. The other approach consists of studying the deposition flux and the emission flux separately (Deventer et al., 2015; Lamaud & Chapuis, 1994). In this case, the data should be considered as being the minimum aerosol transfer velocities between the natural surface and the air. We have adopted the second approach, since the quality criteria enable us to consider that the resulting phenomena observed occurred in a stationary manner during each 30 min of measurement time. 3.2. Influence of particle size on dry deposition velocity In this study, we have decided to devote our attention chiefly to dry deposition velocities obtained in neutral and stable conditions because we have not a lot of valid dry deposition velocities measurements in unstable condition for certain campaigns. To interpreted the data in function of turbulence conditions, we decided to use the approach given by Zhang and He (2014). The particle dry deposition velocity can be calculated according to (Gallagher et al., 2002; Slinn, 1982; Zhang et al., 2001):

Vd = Vg +

1 R a + Rs

(3)

where Vg is the gravitational settling velocity, Ra is the aerodynamic resistance above the canopy, and Rs is the surface resistance. Note that the inverse of Rs is also referred to as surface deposition velocity (Vds). Simple analytical formulas are available in the literature for calculating Ra (Zhang et al., 2001) and Vg can be omitted for the particle size that are studied here. According to Zhang et al. (2001), Vds was calculated as: (4)

Vds = ε 0 u* (EB + EM + EIN)R1

where ε0 is an empirical constant (taken as 3.0), u∗ is friction velocity, EB, EIM, EIN are collection efficiency from Brownian diffusion, impaction and interception, respectively, and R1 is the correction factor representing the fraction of particles that stick to the surface. It is usually shown (Gallagher et al., 2002; Lamaud & Chapuis, 1994; Zhang & He, 2014) that the surface deposition velocities Vds in neutral and stable conditions can be parameterized as a simple linear function of u∗: (5)

Vds = a1u*

The Table 3 regroup the different values of parameterization of the surface deposition velocities normalized by the friction 113

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Table 3 Values of parameterization found in the literature. Particles diameter (µm)

Studied cover

Reference

Parametrization

0.4

Beswick et al. [1994];

vds/u* = 0.003–0.004

0.1–0.2

Forest, Netherlands; Douglas Fir Lush grass Landes forest Pinus Pinaster all surfaces

(Wesely, Cook, Hart, & Speer, 1985) (Lamaud & Chapuis, 1994; Lamaud, Brunet et al., 1994) (Gallagher et al., 2002)

< 2.5

all surfaces

(Zhang & He, 2014)

vds/u* =0.002 vds/u* = k1 k1 = 0.004 vds/u* = k1 k1 = 0.001222*log(zo) + 0.003906 vds/u* = a1 where a1 is the LUC-dependent empirical constant and is ranged from 0.0034 to 0.0069

0.4 0.05–1

velocity that we can found in the literature. Fig. 5 shows all the results of surface deposition velocities normalized by wind friction velocity according the size of the aerosol particles and for the different natural surfaces studied during the seven experimental campaigns in neutral and stable conditions. The error bars represent the standard deviation for this data. The surface deposition velocities normalized by wind friction velocity values for the ultrafine particles obtained using the twin CPC method are almost the same for both campaigns and are equal to roughly 10−2. Surface deposition velocity values for aerosol particles with a diameter of between 14 and 60 nm are similar: between 2 × 10−3 and 5 × 10−3, for grass, maize and bare soil. The values for forests are slightly higher, between 7 × 10−3 and 1 × 10−2. The curves show a minimum value in the accumulation range (at 0.2–0.3 µm) that can reach 7 × 10−4 for maize and grassland in 2010 and 2 × 10−3 for bare soil. For the DEPECHEMOD 1 and 2 campaigns, this minimum is 10−3 and 2 × 10−3 respectively. The minimum is less clear with regards to changes in the deposition velocity above bare soil, however, it is within this size range that the lowest flux were measured. The last campaigns in 2015 did not produce any deposition velocity results for particles larger than 0.7 µm in size and, more specifically, DEPECHEMOD 1 produced no deposition results for particles over 0.4 µm. Above 0.3 µm, the Vds/u* ratio values increase slightly with particle size. This increase is then more pronounced from 0.7 µm. If we compare our values to the literature they are very close. In fact, for particles of 0.48 µm we have of 2 × 10−3 above a forest and 1 × 10−3 above a grass. We decide to concentrate us on 2 parameterizations: (Gallagher et al., 2002) and (Zhang & He, 2014) because this study treated all surfaces. The Table 4 compare the calculated values for the surfaces studies here (Gallagher et al., 2002) and the empirical constant a1 corresponding to our substrates (Zhang & He, 2014), with our values of the 7 campaigns. For the parameterization of Gallagher et al. (2002) the corresponding diameter values are given by the stage 4 of the ELPI. The values of parameterization by Zhang and He (2014) are given for a log-normal particles distribution with a geometric mass median diameter and geometric standard deviation of 0.4 µm and 2.2 respectively. The same log-normal distribution is applied at our values for particles between 14 nm and 1.2 µm for three campaigns where there is no missing data: Landes 2, Landes 3 and REMORA. A global surface dry deposition velocity normalized by the friction velocity is then calculated to compare with the values of Zhang and He (2014). We can note immediately that values calculated by the parameterization of Gallagher et al. (2002) are very close to our values of deposition velocities and moreover for grassland et forest. However the values for maize are overestimated compared to the parameterization. That could be due that the maize grew up during the campaign and so the roughness length raise also. Our surface dry deposition velocities normalized by the friction velocities are very close and has the same variations than the purposed parameterization by L. Zhang and He (2014): in fact the value are more important for forest. For these different curves, we can finding the

Fig. 5. Surface dry deposition velocities normalized by u* for neutral and stable conditions according the geometric diameter of the particles during the seven experimental campaigns, obtained with the Twin CPC method (no filled) and the ELPI.

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Table 4 Comparison of two parameterization models and our experimental values. Parametrization reference (Gallagher et al., 2002)

(Zhang & He, 2014)

Campaign

Calculated values −3

Landes 1 (Maize)

k1 = 2.78 × 10

Landes 2 (Grassland)

k1 = 1.83 × 10−3

Landes 3 (Bare soil)

k1 = 1.83 × 10−3

Landes 4 (Maize)

k1 = 2.78 × 10−3

REMORA (Forest)

k1 = 3.79 × 10−3

DEPECHEMOD 1 (Grassland)

k1 = 2.32 × 10−3

DEPECHEMOD 2 (Grassland)

k1 = 2.20×10−3

Landes 2 (Grassland) Landes 3 (bare soil) REMORA (Forest)

a1 = 5.4 × 10−3 a1 = 5.4 × 10−3 a1 = 4.3 × 10−3

Our corresponding values Vds/u* = 1.65 × 10−3 ± 7.79 × 10−4 Vds/u* = 1.88 × 10−3 ± 3.06 × 10−4 Vds/u* = 2.43 × 10−3 ± 1.62 × 10−3 Vds/u* = 1.52 × 10−3 ± 1.31 × 10−3 Vds/u* = 5.16 × 10−3 ± 4.03 × 10−3 Vds/u* =2.43×10−3 ± 1.46×10−3 Vds/u* = 2.65 × 10−3 ± 1.60 × 10−3 Vds/u* = 6.50 × 10−3 Vds/u* = 6.03 × 10−3 Vds/u* = 3.03 × 10−3

theoretical curve form of dry deposition velocity with the effects of the three dry deposition mechanisms: Brownian diffusion, interception and impaction (Sehmel, 1980). Thus, the dry deposition velocity of ultrafine particles (nucleation mode) is essentially caused by Brownian diffusion. With regard to particles with a diameter of less than 0.2 µm (Aitken mode), as and when the diameters increase, the impact of the Brownian diffusion is increasingly low, but at the same time, the deposition caused by interception and impaction phenomena increase. Beyond 0.5 µm and up to 1.2 µm (accumulation mode), the influence of Brownian diffusion is negligible, the increase is caused by the sharp escalation in the influence of interception and impaction. A comparison of this values is made (Fig. 6) with the model purpose by Zhang et al. (2001) and Slinn (1982). The deposition rate values are modelled for neutral and stable atmospheric conditions. A wind friction speed of 0.26 m s−1 was set. It corresponds to the mean of the episodes in neutral atmospheric conditions. The input parameters of the models are grouped in Table 5. Zhang's model of impaction is close to that of Slinn, but the modelling values for interceptions are much lower. The model of Zhang et al. is mainly governed by the phenomena of sedimentation and Brownian diffusion. Moreover the minimum of experimental values is in adequation with the Slinn model (around 0.2 µm). Given the discrepancy between models and measured values, models seem to underestimate the phenomena of interception and impaction. 4. Conclusion To determine that the dry deposition velocity of submicron particles is dependent of their diameter and of micrometeorological parameters, measurements were taken using the EC method, with a cospectral analysis, during seven different measurement campaigns between 2007 and 2015. Analysis into the proportion of emission flux as a function of the diameter was performed. It appears a trend to obtain a majority of deposition flux for fine particles (< 0.1 µm) while there is a majority of emission flux for the largest particles (> 0.1 µm). In addition, we note that the DEPECHEMOD 1 and 2 campaigns are relatively similar to the curve obtained for maize by Damay (2010). These substrates were enriched shortly before the experimental campaigns. Because of this, the hypothesis is that the nitrogen

Fig. 6. Comparison of models purpose by Slinn (1982) and Zhang et al. (2001) with the seven experimental campaigns measurements.

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Table 5 Input values of the deposition models of Slinn (1982) and Zhang et al. (2001). Used data for modelization −3

ρparticle (kg.m ) ηair (kg.m−1.s−1) l (m) g (m.s−2) RH (%) ρair (kg.m−3) kB (J.K−1) U* (m.s−1) 1/L (m−1) z, zr, z0, h (m) K T (K)

2650 1.80 × 10−5 6 × 58 × 10−8 9.81 30% 1.2 1.38 × 10−23 0.26 0 Depending on the cover 0.41 282

Parameters (Zhang et al., 2001)

Parameters (Slinn, 1982)

C1 C2 C3 C4 α γ ψH (m) ε0 β A (m)

CD cv/cd c  (m) Á (m) b F Ko γslinn

0.279 3.12 5.42×10–11 −1.399 1.2 0.54 0 3 2 0.002

3.79 × 10−3 0.33 1 1 10−3 1 10−5 2 1% 0.00266 3.34

derivatives used for soil fertilization are behind the measured emission flux. A dry deposition velocity study for neutral and stable conditions was then performed. This study made it possible to emphasize that particle size has an influence on the ratio between the dry deposition velocity and the wind friction velocity. The results obtained are similar for all these campaigns and the dry deposition velocities of ultrafine particles are consistent with the rest of the curve obtained. The experimental values was compared with the literature and it appears that for neutral and stable conditions the surface dry deposition velocities are a linear correlation with the friction velocities. Moreover the obtained values are in the same order of magnitude with the literature. It would be beneficial to obtain dry deposition velocity measurements for ultrafine particles for other natural surfaces. In fact the roughness lengths of the substrates studied are not very different and so, other surfaces need to be studied. For example, experimental campaigns on snow or ice would also be interesting to acquire new data and limit the uncertainties (Contini et al., 2010; Nilsson, Rannik, & Håkansson, 2001). But also, it will be interesting to study the urban area. To conclude, other research, such as the measurements of nitrogen-composed flux produced by gas-particle conversion, which would make it possible to clearly identify the emissions of particles over 0.2 µm, would pave the way for progress in the understanding of all phenomena related to aerosol transfers in the surface layer and also to the evolution of radioactive particles in post-accident situations. Acknowledgements We would like to thank the INRA team in Lusignan for giving us permission to perform the DEPECHEMOD 1 and 2 campaigns on their site. 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