Abstract
We explore the chemistry of the most abundant C-, O-, S-, and N-bearing species in molecular clouds, in the context of the IRAM 30 m Large Programme Gas phase Elemental abundances in Molecular Clouds (GEMS). Thus far, we have studied the impact of the variations in the temperature, density, cosmic-ray ionisation rate, and incident UV field in a set of abundant molecular species. In addition, the observed molecular abundances might be affected by turbulence which needs to be accounted for in order to have a more accurate description of the chemistry of interstellar filaments. In this work, we aim to assess the limitations introduced in the observational works when a uniform density is assumed along the line of sight for fitting the observations, developing a very simple numerical model of a turbulent box. We searched for any observational imprints that might provide useful information on the turbulent state of the cloud based on kinematical or chemical tracers. We performed a magnetohydrodynamical (MHD) simulation in order to reproduce the turbulent steady state of a turbulent box with properties typical of a molecular filament before collapse. We post-processed the results of the MHD simulation with a chemical code to predict molecular abundances, and then post-processed this cube with a radiative transfer code to create synthetic emission maps for a series of rotational transitions observed during the GEMS project. From the kinematical point of view, we find that the relative alignment between the observer and the mean magnetic field direction affect the observed line profiles, obtaining larger line widths for the case when the line of sight is perpendicular to the magnetic field. These differences might be detectable even after convolution with the IRAM 30 m efficiency for a nearby molecular cloud. From the chemical point of view, we find that turbulence produces variations for the predicted abundances, but they are more or less critical depending on the chosen transition and the chemical age. When compared to real observations, the results from the turbulent simulation provides a better fit than when assuming a uniform gas distribution along the line of sight. In the view of our results, we conclude that taking into account turbulence when fitting observations might significantly improve the agreement with model predictions. This is especially important for sulfur bearing species which are very sensitive to the variations of density produced by turbulence at early times (0.1 Myr). The abundance of CO is also quite sensitive to turbulence when considering the evolution beyond a few 0.1 Myr.
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