Characterization of size-segregated particles turbulent flux and deposition velocity by eddy correlation method at an Arctic site
Abstract. Estimating aerosol depositions on snow and ice surfaces and assessing the aerosol lifecycle in the Arctic region is challenged by the scarce available measurement data for particle surface fluxes. This work aims at assessing the deposition velocity of atmospheric particles at an Arctic site (Ny-Ålesund, Svalbard Islands) over snow, during the melting season and over dry tundra. The measurements were performed using the eddy‐covariance method from March to August 2021. The measurement system was based on a condensation particle counter (CPC) for ultrafine particle (UFP, < 0.25 μm) fluxes and an Optical Particle Counter (OPC) for evaluating particle size fluxes in the accumulation mode (ACC, 0.25 < dp < 0.7 μm) and quasi-coarse mode (CRS, 0.8 < dp < 3 μm). Turbulent fluxes in the ultrafine particle size range resulted prevalently downward especially in summertime. By contrast, particles fluxes in the accumulation and quasi-coarse mode were more frequently positive especially during the colder months, pointing to surface sources of particles from e.g., sea spray, snow sublimation or local pollution. The overall median deposition velocity (Vd+) values were 0.90, 0.62 and 4.42 mm s-1, for UFP, ACC and CRS, respectively. Deposition velocities were smaller, on average, over the snowpack with median values of 0.73, 0.42 and 3.50 mm s-1. The observed velocities differ of less than 50% respect to previous literature in analogous environments (i.e. ice/snow) in the particles in the size range 0.01–1 μm. At the same time, an agreement with the results of predictive models was found for only a few parameterizations, especially with Slinn (1982), while large biases were found with other models especially in the range 0.3 – 10 µm of particle diameters. Our observations show better fit with the models predicting a minimum deposition velocities for small accumulation mode particle sizes (0.1 – 0.3 μm) rather than for larger ones (~ 1 µm), which could result from an efficient interception of particles over snow surfaces which are rougher than the idealized ones. Finally, a polynomial fit parameterization was proposed in this study to describe the deposition velocity observations which properly represents their size-dependence and magnitude.
Antonio Donateo et al.
Status: open (until 31 Mar 2023)
- RC1: 'Comment on acp-2022-768', Anonymous Referee #2, 28 Feb 2023 reply
- RC2: 'Comment on acp-2022-768', Anonymous Referee #3, 11 Mar 2023 reply
Antonio Donateo et al.
Antonio Donateo et al.
Viewed (geographical distribution)
This paper presents 5 months of particles fluxes measured by eddy covariance at Ny Alesund, Svalbard. Deposition velocities as a function of particle size are derived for snow-covered, melting and snow-free conditions. In addition to the ultra-fine particle numbers obtained by a condensation particle counter, the 16 size channels of a optical particle counter are summed into 2 broader size classes in order to obtain workable statistics. An analysis is performed first on all fluxes regardless of direction, and downward fluxes are then analyzed separately to construct deposition velocity parameterizations for the three periods. Results are compared to previously published numbers and models and agree reasonably well.
There are some issues with this analysis that cannot be improved upon after the fact, such as the measurement site on top of a building that is likely to cause flow conditions less than ideal for eddy covariance, or the limited spectral response of the particle instrumentation. These should be discussed and justified in more detail than is currently the case. There are also a few issues that may warrant some additional thought and perhaps some further analysis. Simply concentrating on only positive (deposition) fluxes without accounting for natural scatter across the zero line is somewhat arbitrary and is likely to introduce artificial biases towards larger numbers; therefore, this should be justified in more detail. Some additional information, such as an ogive of particle fluxes and some statistics on the upward (emission) particle fluxes, either in the manuscript or a supplement, would also be helpful to convince the reader of the validity of the results.
Given the paucity of published direct measurements of particle fluxes, and especially in the Arctic, this paper can represent a useful addition to the field if these issues are addressed.
Line 104: Please include a photo of the building and mast, and state the dimensions of the building (height, footprint) and the mast. Doing flux measurements on a rooftop can cause all kinds of problems due to flow distortion, and for some directions more than others, but a bit more on that later.
L150: If T comes from the sonic (Ts), it’s not the actual temperature, but rather a virtual temperature (or close to virtual, for all intents and purposes) which also depends on moisture. Therefore, what you are calculating is not strictly the sensible heat flux H, but a virtual sensible heat flux that is probably close enough to H for all practical purposes. But it’s best to be exact at the definition phase.
L155 and after: make the “i” a subscript
L157: here you define Vdi, but later you only use Vex. Make this consistent throughout. Vex is more transparent and therefore a better choice.
Eq. (2): should include Ts rather than T
Section 2.4 could use some rereading and grammatical clean-up
L192: rephrase/clarify. There was no correction for large angles, but the small ones were corrected?
L194: please clarify.
L202: dependent on (not according to)
L288: “below 0C” would be more accurate than “about -10C”.
Fig. 3: wind directions look better when plotted using dots rather than lines
Fig. 5: averaging together the whole measurement period, consisting of vastly varying climatic and heat flux regimes, may not be the best way to do this. I would suggest splitting into at least 2 panels, one for snow-covered and one for snow-free, plus perhaps one for the transition period.
L357: according to the flux footprint estimate in Fig. 1, and the stated maximum footprint in L356, the ocean is well outside the footprint, and therefore it seems very unlikely that swell would be the cause of these upwards momentum fluxes. Could it be katabatic winds coming down Zeppelin Mountain? Or a very shallow sea breeze? Would need to look at wind directions carefully.
L349: these are very large roughness lengths for snow or tundra surfaces, an order of magnitude higher than expected, suggesting that the building is introducing a significant roughness element to the flow observed at the sonic.
L403: rephrase. The average value of FACC for the whole period was ….
L405: Finally, the mean of FCRS …
L420: overlap with
L421: the village and shipping are all well outside the flux footprint (see comment to L357)
L439: simply throwing out all negative Vd’s and continuing the analysis with the rest will bias the readings (unless the histogram is strongly bimodal and there are hardly any numbers around zero), and including these would bring the averages down. This is an important enough point that it should be discussed in some detail, and the potential biases evaluated. They may be part of the reason for your numbers being higher than measurements by others and the Zhang and Pleim & Ran models for much of the range (Fig. 8).
Table 4: did you also try doing the statistics for Vd– ? Could be interesting, and lend some support to the validity of separating out all the positives into Vd + and simply ignoring negative values.
Fig. 8d) snow free
L490: Seems unlikely that water surfaces have anything to do with this since a snow surface, with all its fractal roughness elements, would be a good surface for deposition. Seems more likely that the increasing z0 as the snow melts has an effect, as you reasonably state in the conclusions [L 574].
L534 and conclusions: state clearly that the polynomial only applies to the size range 0.25 – 3 µm and does not cover UFP.