Aerosol deposition to the boreal forest in the vicinity of the Alberta Oil Sands
Abstract. Measurements of size-resolved aerosol concentration and fluxes were made in a forest in the Athabasca Oil Sands Region (AOSR) of Alberta, Canada in August 2021 with the aim of investigating a) particle size distributions from different sources, b) size-resolved particle deposition velocities, and c) the rate of vertical mixing in the canopy. Particle size distributions were attributed to different sources determined by wind direction. Background air from undeveloped forested areas air showed a peak number concentration for diameters near 70 nm while air mixed with upgrader smokestack plumes had higher number concentrations with peak number between diameters of 70 and 80 nm. Aerosols from the direction of open-pit mine faces showed number concentration peaks near 150 nm and volume distribution peaks near 250 nm (with secondary peaks near 600 nm). Size-resolved deposition fluxes were calculated which show good agreement with previous measurements and a recent parameterization. There is a minimum deposition velocity of vd = 0.02 cm s-1 for particles of 80 nm diameter; however, there is a large amount of variation in the measurements and this value is not significantly different from zero in the 68 % confidence interval. Finally, gradient measurements of PM1 demonstrated nighttime decoupling of air within and above the forest canopy, with median lag times at night of up to 40 min, and lag times between 2 and 5 min during the day. PM1 fluxes determined using flux/gradient methods (with different diffusion parameterizations) underestimate the flux magnitude relative to eddy covariance flux measurements when averaged over the nearly 1-month measurement period. However, there is significant uncertainty in the averages determined using the flux/gradient method.
Timothy Jiang et al.
Timothy Jiang et al.
Timothy Jiang et al.
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The authors present a study of size-segregated particle size-distribution (SDP) and flux measurements at a forest site in the Athabasca Oil Sands Region of Alberta, Canada. The measurements enabled to correlate the SDPs to different particle sources in the Alberta Oil Sands. The particle flux measurement system enabled to determine the particle deposition rates in the size range from 60 nm to 1 mm. The particle flux measurements, in particular the size-segregated measurements, always impose a challenge due to high variability of flux sources and sinks and resulting high uncertainty in fluxes. The observed size-dependence of deposition velocities was in a good correspondence with latest parameterization and therefore the manuscript is a great contribution to experimental research on particle dry deposition.
Whereas there are no major concerns, a few topics would benefit from additional clarifications and potentially improvements. First, the particle number concentrations and SDPs exhibit systematic variation with wind direction. This is attributed to the downwind sources of pollutants or background concentrations in extensive forested areas. However, within the identified sectors (i to vii) there is significant variation and the authors have not attempted to find explanation of this variation in terms of atmospheric mixing (determined by stability) conditions. Simplest would be to differentiate the measurements into day-time and night-time, or into a few stability classes and test the hypothesis that the variation within segments is related to hour of day (perhaps also the source activity is dependent on time) or atmospheric conditions. A more sophisticated tool could be the source concentration footprint modelling, but presumable the assumptions of such models would be strongly violated (such as the assumption of surface sources) and as such not worth of considering. It is possible that the authors have made such analysis and neglected from the manuscript because of not finding strong evidence of the dependence on stability or time of day. In that case it deserves short explanation in the manuscript.
The deposition velocities are analysed as aggregates over all measurements (section 3.3). There is considerable scatter (and this is natural) and probably hard to differentiate more the measurements. However, attempt to separate day-night and/or some wind directions according to sectors i-vii (grouped to few subsets) might give additional insights and separate the conditions with different deposition/emission patterns, perhaps even to reduce the scatter when differently behaving samples are separated. Did you try this? If yes and this did not produce improvements, please mention in the manuscript.
A topic of a concern is the EC system frequency performance. It was explained that the size distributions were sampled at 1 Hz frequency (L. 102) and that the attenuation of signal at frequencies >1 Hz was corrected. It is not evident how the particle EC system frequency response was determined. Sampling rate is not equivalent to the frequency response of the system. In addition, in case of EC flux measurements it is important to determine what are the frequency response characteristics of the complete system consisting of the spectrometer and the rather long (32 m) sampling line. Please provide additional explanations to this experimental detail.
The last part of the result, the particle mass flux inference from measured PM1 gradients raises the question on the applicability of the K-theory inside canopy. In general, the K-theory is poorly applicable inside the canopy and in case of more closed canopies might not be applicable at all (counter-gradient fluxes within canopy contradict the K-theory). This needs to be acknowledged in the manuscript. However, the forest at the study site was not closed and the reasons for large discrepancy are probably elsewhere. Within canopy deposition mostly occurs at the upper part of the canopy (in most canopies majority of leaf area is in the upper part of the canopy and deposition is more efficient at higher levels where more turbulence exists). Therefore, the average K evaluated for the height interval of the observations might be biased (the "resistance" equivalent to those K-parameterizations over estimated). Could this be partly responsible for discrepancy?