CO Depletion in Infrared Dark Clouds (2509.04864v1)
Abstract: Infrared Dark Clouds (IRDCs) are cold, dense structures representative of the initial conditions of star formation. Many studies of IRDCs employ CO to investigate cloud dynamics. However, CO can be highly depleted from the gas phase in IRDCs, impacting its fidelity as tracer. CO depletion is also of great interest in astrochemistry, since CO ice in dust grain mantles provides the raw material for forming complex organic molecules. We study CO depletion toward four IRDCs to investigate how it correlates with volume density and dust temperature, calculated from Herschel images. We use 13CO(1-0) and (2-1) maps to measure CO depletion factor, $f_D$, across IRDCs G23.46-00.53, G24.49-00.70, G24.94-00.15, and G25.16-00.28. We also consider a normalized CO depletion factor, f_D', which takes a value of unity, i.e., no depletion, in the outer, lower density, warmer regions. We then investigate the dependence of f_D and f_D' on gas density, $n_H$ and dust temperature, $T_{dust}$. We find CO depletion rises as density increases, reaching maximum values of f_D'$\sim$10 in regions with $n_H>3\times105:{cm}{-3}$, although with significant scatter at a given density. We find a tighter, less scattered relation of f_D' with temperature, rising rapidly for temperatures <18 K. We propose a functional form $f_D\prime = :{exp}(T_0/[T_{dust}-T_1])$ with $T_0\simeq4:$K and $T_1\simeq12:$K to reproduce this behaviour. We conclude that CO is heavily depleted from the gas phase in cold, dense regions of IRDCs. Thus CO depletion can lead to underestimation of total cloud masses based on CO line fluxes by factors up to 5. These results indicate a dominant role for thermal desorption in setting near equilibrium abundances of gas phase CO in IRDCs, providing important constraints for both astrochemical models and the chemodynamical history of gas during the early stages of star formation.
Collections
Sign up for free to add this paper to one or more collections.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.