For multiscale embedding calculations of spectroscopic properties, it is crucial to have a physically accurate treatment of the interactions between the quantum subsystem and its classical environment. Different levels of sophistication are employed to describe the interactions: mechanical, electrostatic, and polarizable embedding. Mechanical embedding treats the interactions fully classically, electrostatic embedding includes polarization of the electronic density of the quantum subsystem, and polarizable embedding includes mutual polarization between the quantum and classical subsystems. The most common is electrostatic embedding with point charges from a standard MM force field. However, polarizable embedding is becoming more popular, particularly for spectroscopic applications. Different variants exist, including Drude oscillators and fluctuating charges, but the most used is induced dipoles. This work is based on the fragment-based fully self-consistent polarizable embedding (PE) model. Here the environment effects are modeled by atom-centered multipoles and polarizabilities derived from ab initio calculations performed on each fragment in the environment. For solvents, the fragments consist of individual solvent molecules. In environments with large molecules, such as proteins, a more elaborate fragmentation procedure is employed. The resulting embedding potential has been shown to be highly accurate for a wide range of systems and properties. However, it is more costly than approaches based on standard force fields. The computational cost can be substantially reduced by using transferable parameters for a subset of the classical sites. Moreover, recently developed linear-scaling techniques and approximate couplings can drastically reduce the cost associated with polarizable embedding. For applications, it is usually necessary to include a statistical sampling of nuclear configurations, e.g., using molecular dynamics (MD) simulations. Calculations are then performed on a suitable number of structures extracted from the MD trajectory. These molecular structures are defined within an appropriate simulation box (i.e., cubic, triclinic, etc.). Applications using embedding methods often apply a cutoff where a part of the entire simulation box is cut out and used in the embedding calculations. This is sometimes referred to as a droplet model. In principle, it is necessary to determine the cutoff distance for every system and property. Cutoff distances routinely used in embedding calculations for molecular properties are 10-16 Å from the quantum subsystem in homogenous environments, such as solvents, and around 20 Å or more for inhomogenous biomolecular environments. Droplet models can be a useful approximation for electrostatic embedding, assuming that the cutoff distance is large enough. However, for polarizable embedding approaches, this inevitably introduces unphysical polarization at the outer boundary that may affect the properties of the quantum subsystem. Of course, this also holds when using the full simulation box without periodic boundary conditions (PBC).