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1. How does in-cloud scavenging depend on cloud water phase?

2. How is below-cloud scavenging calculated in FLEXPART?

3. What is the methodology used to quantify individual scavenging contributions in the FLEXPART simulations?

4. What is the purpose of the scaling scheme in generating new physical air concentrations?

Accepted Answer

In-cloud scavenging in FLEXPART 10.4 depends on the cloud water phase, which can be liquid, ice, or mixed. The nucleation efficiency of aerosols plays a crucial role in serving as ice crystal or liquid droplet nuclei. The process is activated inside precipitating grid cells where cloud water is present. The precipitating cloud water (PCW) is defined using a specific equation, and the fraction of cloud water in the precipitating part of the cloud is calculated. Aerosol particles are activated as cloud droplet or cloud ice nuclei, leading to in-cloud scavenging. The nucleation efficiency (F nuc) is further split into contributions from the liquid and ice water fractions (a L and a I respectively), with a L + a I = 1. The efficiencies depend on aerosol particle size, concentration, and cloud properties such as updraft velocities. Larger particles generally have larger nucleation efficiencies compared to smaller particles. The Bergeron-Findeisen process, where ice crystals grow at the expense of liquid droplets, is assumed to result in CCN eff > IN eff for most aerosol particles (Grythe et al., 2017).

Accepted Answer

Below-cloud scavenging in FLEXPART is calculated separately for rain and snow. The scavenging coefficient is parameterized using an equation with factors a and b, which are fitting parameters based on observations. The equation considers the mean particle diameter (d p), the scavenging rate (d 0), and the scavenging coefficient (L 0). The factors a and b differ between rain and snow, with values ranging from 0.1 to 10 to cover the range of below-cloud scavenging rates seen in other ATMs. Despite the size-dependent nature of below-cloud scavenging, FLEXPART only calculates it for the mean particle diameter, unlike dry deposition which is size-dependent and calculated by sampling the log-normal size distribution.

Accepted Answer

The methodology used to quantify individual scavenging contributions in the FLEXPART simulations involves directly writing the c i 's into the simulation output by altering the source code. This method provides more accurate insight into the different contributions compared to previous studies that set L i = 0. The first step in the methodology is to quantify the individual scavenging contributions of the reference simulation (Sect.2.4). The values are daily averaged concentrations as calculated by the parabolic kernel-method in FLEXPART. The relative sum of all scavenging-contributions and remaining air concentration is equal to 1, in accordance with Eq. (10). Figure 5 shows quantitatively which part of the concentration has been removed due to the different scavenging processes for the part of the plume that reaches the detector during a given time period. The air concentration left over after scavenging (c, black coloured area) is relative to c 0, which is determined only by the winds and not deposition, much like what would be the case with a noble gas such as Xenon. Therefore, unlike the temporal variations in c, the variations in the ratio c/c 0 are not mediated by the windfields, but instead solely by spatiotemporal variations of the different removal processes. In other words, an overview of the scavenging processes across all stations is shown in Fig. 6 (left panel), covering the whole simulation period (11 March -5 April 2011). In total, 84% of the concentration is scavenged and deposited in the reference simulation, with 66% of the wet scavenging occurring below-cloud and 34% occurring in-cloud. This partitioning of below-and in-cloud scavenging found here is in contrast with those of some previous studies, which may be due to erroneous methodology for calculating the partitioning or underestimation of the scavenging coefficients in those studies. The methodology used in this study avoids compensation effects by directly extracting the c i 's from the simulation, through alterations of the FLEXPART source code.

Accepted Answer

The scaling scheme aims to change scavenging contributions in a post-process step to generate new physical air concentrations. Simply scaling contributions with a factor can lead to non-physical negative concentrations. A more elaborate scaling scheme is proposed, where a scaling factor A i is associated with each scavenging process. This factor acts on the concentration field, ensuring that the remaining concentration c remains positive. The scaling scheme also reproduces the physical compensation effect when increasing the strength of a scavenging process.

Accepted Answer

The default value for mean particle diameter d p is not specified in the given information. However, it is mentioned that the value is chosen to be in better agreement with measurements from the aftermath of the FDNPP accident. The specific value mentioned in the text is 0.65 um. This value is used in the FLEXPART v10.4 input-parameters for the deposition scheme, as used in the reference simulation of 137 Cs. The concentration and deposition values are output over a 3-hour interval on a 0.5 * grid. The parameter values used in the simulation include C rain 1, C snow 1, CCN eff 0.9, IN eff 0.9, and r p 1900 kg m^-3. These values are crucial for accurately representing the deposition of particles and their impact on the environment.

Accepted Answer

In FLEXPART simulations, 137 Cs and 133 Xe measurements are used as receptors to provide more accurate values compared to grid outputs. The IMS stations, with the highest measured concentrations of these radionuclides, are implemented in FLEXPART. The measurements are daily averaged concentrations for 137 Cs and daily or twice-daily for 133 Xe. To compare the simulations to the IMS observations, the simulation output is averaged over the integration time of the measurements, which is 24 hours for 137 Cs and 24 hours or 12 hours for 133 Xe. Additionally, wet deposition measurements of 137 Cs from the National Atmospheric Deposition Program (NADP) in the United States are used, obtained through collectors that open only when it rains, minimizing contamination by dry deposition. This data consists of measured radioactive samples from 35 NADP sites across the contiguous United States and Alaska.

Accepted Answer

The potential sources of error in the reference simulation for 137 Cs include the windfields, the source term, the precipitation data, and the deposition scheme. The windfields were evaluated and found not to be the main cause of discrepancy. The source term of Terada et al. (2020) is considered on the lower end of available estimated source terms, reducing the total emitted 137 Cs by 29%. The precipitation data comparison between ECMWF and GPCP showed a good correspondence. Therefore, the discrepancy in the reference simulation is likely due to the deposition scheme in FLEXPART. Further improvements can be made by finding better input parameters for the wet deposition scheme compared to those in Table 1.

Accepted Answer

Optimised scavenging contributes significantly to total wet deposition, with below-cloud scavenging being the largest contributor at 63% compared to 37% for in-cloud scavenging. The optimisation method reduces bias and improves statistical scores, indicating increased efficiency in all four scavenging processes. The greatest increase is found for below-cloud scavenging by rain (x3.6), while in-cloud scavenging by cloud condensation nucleation (CCN) and ice nucleation (IN) are increased by slightly greater amounts (x2.0 and 1.8 respectively). The optimised scavenging contributions for station RN71 are shown in Fig. 5 (right panel), and the new removal contributions over all stations are displayed in Fig. 6 (right panel). Overall, the optimised scavenging process reduces the total concentration reaching the detectors from 16% of the concentration c0 to 6%.

Accepted Answer

To use optimisation results in FLEXPART simulations, translate optimisation parameters to physical scavenging coefficients. This involves altering FLEXPART input parameters {C rain, C rain, CCN eff, IN eff} (Table 1). The methodology is post-process, aiming for close simulation matches. An ansatz is proposed, relating x i to L i t, and scaling factors A i (Eq. 14) to scavenging nature (Eq. 2). Optimised scavenging over initial scavenging gives Eq. (16), with new FLEXPART input parameters in Table 6. Efficiencies of in-cloud nucleation may exceed 1, requiring interpretation adjustments. Using optimised values in FLEXPART yields 137 Cs concentrations in Fig. 8, close to post-process optimised concentrations in Fig. 7. Table 7 shows improved statistical scores compared to Table 4.

Accepted Answer

Wet deposition plays a crucial role in various atmospheric aspects, such as the transport and diffusion of airborne radionuclides. It helps in removing pollutants and particles from the atmosphere, thereby influencing air quality and climate. Simulating wet deposition in atmospheric transport models, however, remains a challenge due to the complexity of the processes involved. Understanding wet deposition is essential for accurately predicting the behavior of pollutants and their impact on the environment.

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Most frequently asked questions

1. How does in-cloud scavenging depend on cloud water phase?

2. How is below-cloud scavenging calculated in FLEXPART?

3. What is the methodology used to quantify individual scavenging contributions in the FLEXPART simulations?

4. What is the purpose of the scaling scheme in generating new physical air concentrations?

5. What is the default value for mean particle diameter d p?

6. How are 137 Cs and 133 Xe measurements utilized in FLEXPART simulations?

7. What are the potential sources of error in the reference simulation for 137 Cs?

8. How does optimised scavenging contribute to total wet deposition?

9. Translate optimisation parameters to scavenging coefficients?

10. How does wet deposition impact atmospheric aspects?

References

A review of parameterizations for modelling dry deposition and scavenging of radionuclides

World Meteorological Organization's model simulations of the radionuclide dispersion and deposition from the Fukushima Daiichi nuclear power plant accident.

Refinement of source term and atmospheric dispersion simulations of radionuclides during the Fukushima Daiichi Nuclear Power Station accident

Snow scavenging of ultrafine particles: field measurements and parameterization

Size distribution of radioactive particles collected at Tokai, Japan 6 days after the nuclear accident

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