\section{Introduction} 
Stars go through many periods of mass loss throughout their lives. Young embedded protostars drive powerful collimated outflows, and as they evolve, the mass loss rate decreases and the outflows become less collimated \citep{Bontemps_1996,Arce_2006}. Wide-angle winds, sometimes coexistent with a more collimated, jet-like component, are observed around evolved pre-main sequence stars (T-Tauri and Herbig Ae/Be stars). It was realized early on in the study of winds that both the outflows driven by protostars and winds from T-Tauri stars have the potential to significantly affect the dynamics and structure of the parent cloud \citep{Norman_1980}, and the impact has been observed and analysed by Arce et al (2007) and \citet{Arce_2010}. However, the original bubble model proposed by \citet{Norman_1980} lost its appeal when T-Tauri stars were more often observed to have an effect on their surroundings through what are now well-known bipolar outflows.

However, parsec-scale circular cavities (typically referred to as ``shells'' or ``bubbles'') are regularly found in regions of high-mass star formation, and are likely created by spherical winds from high-mass stars \citep{Churchwell_2006,Churchwell_2007,Beaumont_2010}. High-mass stars evolve faster than low-mass stars, and they reach the main sequence while they are still accreting material and embedded in their parent cloud. Mass loss rates of $\sim 10^{-6}$ M$_{\odot}$ yr$^{-1}$ that can create these bubbles have been observed around high-mass stars during their main sequence phase. Previously, people thought that the same process did not happen in regions of intermediate- and/or low-mass star formation. However, \citet{Arce_2011} find that in the Perseus cloud it is possible, and frequent, for B or later types of main sequence stars and evolved pre-main sequence stars to drive spherical winds that can have a significant impact on the natal cloud. In their estimates of the impact, comparisons between the energy entrained in these shells and the turbulent energy in the cloud show that the embedded stellar winds have enough energy to disturb the cloud and contribute to the turbulence therein.

Reliable estimates of density and  dynamics are critical to measuring the significance of wind-cloud interactions. \citet{Goodman_2009} find that mass estimates can vary significantly due to biases inherent to various techniques for measuring column density in molecular clouds, including near-infrared extinction, mid/far-infrared thermal emission and molecular line emission.  These uncertainties and biases in mass determination can lead to similarly uncertain and/or biased estimates of momentum and energy.  \citet{Goodman_2009} find that not only do different types of observations trace different components (e.g. warm/cold gas/dust) in molecular clouds, but they also have sensitivity limits that are different from one another. These limits are dependent on the physical environment, and extreme care should be taken extreme when using (any of) these tracers to estimate the density and other physical properties.

The recent release of data taken by the Herschel Space Observatory has inspired many works examining the validity and caveats of using far-infrared thermal emission in estimates of column density. One of the most discussed issues is the artificial anti-correlation between the temperature and the emissivity spectral index that can be caused by (even small amounts of) noise in real data, when certain fitting procedures are used. The boost of computational power and new algorithms in the past decade has allowed researchers to use parameter-estimation techniques that are less likely to cause false correlations amongst fitted parameters.  \citet{Kelly_2012} have proposed a hierarchical Bayesian-fitting method and tested it on  Herschel data, and they claim that the Bayesian procedure (as opposed to least-squares fitting) reduces (false) temperature-opacity anti-correlation when fitting models for thermal dust emission at multiple wavelenghts.

In this paper we focus on an embedded stellar wind in one of the most near-by molecular clouds: Ophiuchus. A shell structure is found around a group of B-stars ($\rho$ Oph; \S2). Multi-wavelength observations are used in the analysis of the shell. These include near-infrared data from the Two-Micron All-Sky Survey (2MASS), mid/far-infrared maps released by the Improved Reprocessing of the IRAS Survey (IRIS), the Herschel Space Observatory and $^{12}$CO (1-0) and $^{13}$CO (1-0) line data taken at Five College Radio Astronomy Observatory (FCRAO) from the COoridnated Molecular Probe Line Emission Thermal Emission \citep[COMPLETE;]{Ridge_2006} project (\S3). These data sets allow us to reproduce a similar analysis of the limits on using them to trace the column density in molecular clouds as in \citet{Goodman_2009} (\S4.1). In this paper, we also experiment with the hierarchical Bayesian-fitting method \citep{Kelly_2012} on the Herschel maps at PACS 70/100 $\mu$m and SPIRE 250/350/500 $\mu$m (\S4.2). This is the first time the algorithm has been applied on an extended source. Then we conclude with an estimate of the impact caused by the embedded stellar wind (\S5). The result reconfirms the idea proposed by \citet{Arce_2011} that stellar winds driven by B or even later types of stars can contribute to the turbulence in molecular clouds.
