  We prove a Poisson limit theorem in the total variation distance of
functionals of a general Poisson point process using the Malliavin-Stein
method. Our estimates only involve first and second order difference operators
and are closely related to the corresponding bounds for the normal
approximation in the Wasserstein distance by Last, Peccati and Schulte (2016).
As an application of this Poisson limit theorem, we consider a stationary
Poisson point process in $\mathbb{R}^d$ and connect any two points whenever
their distance is less than or equal to a prescribed distance parameter. This
construction gives rise to the well known random geometric graph. The number of
edges of this graph is counted that have a midpoint in the $d$-dimensional unit
ball. A quantitative Poisson limit theorem for this counting statistic is
derived, as the space dimension $d$ and the intensity of the Poisson point
process tend to infinity simultaneously, showing that the phase transition
phenomenon holds also in the high-dimensional set-up.
