Experimental determination of the thermal accommodation and condensation coefficients of water

Abstract

The condensation coefficient of water vapor on liquid water and the thermal accommodation coefficient of air on liquid water are poorly known despite their importance in many applications, such as cloud physics. We have developed a new technique for determining the condensation and thermal accommodation coefficients experimentally. The technique consists of simultaneously measuring the homogeneous nucleation rate of ice and the evaporation rate of liquid water droplets as a function of pressure (droplet Knudsen number). As the Knudsen number increases, surface kinetic processes limit mass and energy fluxes and, as a result, the equilibrium temperature of an evaporating droplet is a function of the condensation and thermal accommodation coefficients. The homogeneous freezing nucleation rate is used as a sensitive measure of the droplet temperature. The nucleation and evaporation rates are determined by observing the scattered light from evaporating water droplets suspended in an electrodynamic levitation system housed within a controlled environment. The observed rates are consistent with a condensation coefficient between 0.04 and 0.1, with 0.06 being most probable, and a thermal accommodation coefficient between 0.1 and 1, with 0.7 being most probable.

Nanofluidic transport governed by the liquid/vapour interface

“…The difficulty in accurately measuring σ arises from uncertainties in estimating heat and mass transfer resistances and the interfacial temperature in the presence of latent heat transfer [41][42][43] , since vapour pressure is a strong function of temperature. As a result, experimental estimates even in relatively recent studies (since 1989) are scattered over almost two orders of magnitude (0.01 to 1) 31,34,[44][45][46][47] . Molecular dynamics simulations have also yielded varying values depending on the models used 48,49 .…”

Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

“…To test the effects of the mass accommodation coefficient and spectrum discretization on the CDSD, two more sensitivity studies are conducted. One case is to set the mass accommodation coefficient (α m ) to 0.06 based on Shaw and Lamb (1999). It is expected that a smaller value of α m might suppress the growth of cloud droplets.…”

“…Turbulence can result in not only upward and downward oscillations but also in entrainment and mixing (Shaw, 2003;Devenish et al, 2012). The latter can cause cloud droplet evaporation, deactivation and reactivation (Korolev et al, 2013;Yang et al, 2016).…”

“…Turbulence is ubiquitous in the clouds and can cause CDSD broadening in both condensation and collision processes (e.g., Shaw, 2003;Devenish et al, 2012). Turbulence induces vertical oscillations of air parcels and causes fluctuations in temperature, water vapor concentration and supersaturation (e.g., Ditas et al, 2012;Hammer et al, 2015).…”

The influence of radiation on ice crystal spectrum in the upper troposphere

“…Based on experimental measurements (e.g. Fukuta and Walter, 1970;Shaw and Lamb, 1999), the thermal accommodation coefficient α = 0.7, and the deposition coefficient β = 0.04 exp{−(T − T 0 )/85} that fits the data of Fukuta and Walter (1970) when T > −85°C. (6) F s -the solar flux absorbed by an ice crystal.…”