Chapter III: A Note on Flow Behavior in Axially-Dispersed Plug Flow Reac-
5.5 Supporting Information
5.5.8 Droplet Simulation
In this section, we show how to calculate the partition of PA among the gas phase, air-water interface, and the aqueous phase as functions of the droplet size, given the surface-gas (Ksg =9.62×104m) and surface-bulk (Ksb =2.01×10−4m) equilibrium constants. The Langmuir adsorption model is assumed to keep consistent with the model framework, so the expression is different from EQ. (2) in the manuscript, although this does not affect the conclusion that surface reaction is the largest sink of surface-active species at the air-water interface.
The overall PA concentration in the air parcel iscP = 0.5 nmol m−3air and the liquid water mixing ratio iswL =3×10−7m3water m−3air. The droplet radius (R) is in the range of 2.5−50×10−6m. We useg,s, andbto represent the concentration in the gas phase, surface, and the bulk aqueous phase in units of molec m−3air, molec m−2area, and molec m−3water, respectively.
Based on a mass balance, there are two equations:
N4
3πR3 =wL (5.17)
g+s·N4πR2+b·N4
3πR3=10−9cPNA (5.18) whereN is the number concentration of the droplets andNAis Avogadro’s number.
From the equilibrium constant we have:
s
g(1−sσ) =Ksg (5.19)
s
b(1−sσ) =Ksb (5.20)
where σ = 30× 10−20 Å2 is the effective cross section area of PA. Combining EQs.(5.17) - (5.20), we can solve forN,g,s, andb.
Figure 5.17a shows the ratios of the fractions in the gas phase and in the bulk aqueous phase to that on the surface, as well as the number concentration of the droplet as functions of the droplet diameter. Because of the high surface activity of PA and high surface area concentration when the droplet radius is small, over 99% remains on the surface asR < 10µm. Figure 5.17b shows the simulated temporal profiles of OH uptake coefficients on the surface of droplets of 5µm and 100µm, respectively.
Figure 5.17: a) Ratios of the fractions of PA in the gas phase and in the bulk aqueous phase to that on the surface, as well as the number concentration of the droplet as functions of the droplet diameter. b) Simulated temporal profiles of OH uptake coefficients on the surface of droplets of 5 µm and 100 µm.
C h a p t e r 6
CONCLUSIONS AND FUTURE WORK
This thesis has focused on characterizing and applying atmospheric reactors to study secondary organic aerosol (SOA) in the laboratory. The design and characterization of the Caltech PhotoOxidation flow Tube reactor (CPOT) led to the development of the advective-diffusive model (AD-PFR model). We proposed a unified theory to model the vapor-wall interaction and parameterized the processes. We also developed a multi-phase mass transport and reaction model to simulate the OH- initiated reactions occurring at the air-water interface of a droplet. Through Chapter 2 to Chapter 5, we stress that a proper interpretation of laboratory atmospheric chemistry study requires a well-characterized reactor and a well-defined model framework.
In addition to the work that has been carried out in this thesis, the methods we have developed can be applied to other aspects of SOA formation.
For example, Eq. 3.4 describing the cumulative residence time distribution in Chapter 3 can be combined with the parameterized vapor-wall interaction model in Chapter 4 to describe the signal delay in a sampling tube, which can be significant for instruments to detect those compounds with low volatilities. The Jimenez group in CU Boulder has made efforts on this topic. For example, Pagonis et al. (2017) proposed a vapor-wall interaction mechanism within a PFR model framework, simi- lar to the absorption/desorption processes in chromatography, to describe the signal delay in Teflon sampling tube. This numerical model can reproduce the experi- mental data quite well, but is possible to be simplified into a single equation. One can follow the derivation of Deemter et al. (1956) for chromatography and use one or two key parameters in a key equation to represent the signal delay by sampling tubes.
Another on-going project is based on the multi-phase mass transport and reaction model in Chapter 5, which can be extended to a new comprehensive model to simulate single particle growth/evaporation by considering especially gas-particle interfacial interactions. Different from the model in Chapter 5 that assumes no water evaporation during the reaction, the single particle growth/evaporation model has a moving boundary, i.e., a typical Stefan problem. The concept of this model
is similar to that of the Kinetic Multi-layer model of GAs-Particle interactions in aerosols and clouds (KM-GAP, by M. Shiraiwa et al., 2012), however, instead of dividing the particle into multi-layer and treating each layer as a box model, the new model is based on the diffusion-reaction partial differential equation to represent the processes within the particle. This new model can help to evaluate the equilibration time between the gas- and particle- phases. Different from the traditional definition of equilibration time of gas- and particle- phases (Mai et al., 2015), the newly defined equilibrium time will consider only the equilibrium between the gas phase and the surface, which is more intuitive and can better reflect the interaction between the vapor and the particle.
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