Near-infrared scattering as a dust diagnostic
  We examine the possibility of using near-infrared scattering to constrain the
local radiation field and the dust properties, for example, the size
distribution of the grains, and maximum grain size. We use radiative transfer
modelling to examine the constraints provided by J, H, and K bands in
combination with mid-infrared surface brightness at 3.6 $\mu$m. We use a
spherical one-dimensional and elliptical three-dimensional cloud models to
study the observable effects of different grain size distributions with varying
absorption and scattering properties. As an example, we analyse observations of
a molecular cloud in Taurus, TMC-1N. The observed surface brightness ratios
between the bands change when the dust properties are changed. However, even a
small change of 10% in the surface brightness of one channel changes the
estimated powerlaw exponent of the size distribution $\gamma$ by up to ~30% and
the estimated strength of the radiation field K_ISRF by up to ~60%. The maximum
grain size A_max and $\gamma$ are always strongly anti-correlated. For example,
overestimating the surface brightness by 10% changes the estimated radiation
field strength by ~20% and the exponent of the size distribution by ~15%. The
analysis of our synthetic observations indicates that the relative uncertainty
of the parameter distributions are on average A_max, $\gamma$ ~25%, and the
deviation between the estimated and correct values $\Delta$ Q <15%. We show
that scattered infrared light can be used to derive meaningful limits for the
dust parameters. However, errors in the surface brightness data can result in
considerable uncertainties in the derived parameters.
