State-of-the-art ground-based surveying with the transient electromagnetic (TEM) method uses the innovative towed TEM system, which is capable of mapping large areas with high lateral resolution, but is limited by the off-road mobility of the pulling all-terrain vehicle. Near surface TEM applications in steep slopes or difficult terrain still require the usage of stationary ground-based TEM systems, which commonly employ heavy equipment and require separated transmitter and receiver loops in the so-called central-loop configuration. Furthermore, adequate modeling procedures are required to model the dispersion of the electrical resistivity. The dispersion causes the induced polarization (IP) effect, which leads to a deformation of the TEM decay curves. While most studies consider the central-loop configuration, the IP effects on single-loop measurements have not been investigated in detail. We present here an application of the light-weight TEM-FAST 48 system in a single-loop configuration to investigate IP effects in TEM data. In particular, we investigate near surface targets in glaciers and graphite ores, which represent varying electrical resistivity. Our open-source forward modeling and inversion routine is based upon two existing open-source python libraries. We use empymod to obtain the forward response of the single-loop system and model the IP effect. For the inversion, we include our forward solver into pyGIMLi. We investigate the responses from our forward solver associated to 1) conductive media without IP effects in a soda lake, 2) conductive media with IP effects in a former graphite quarry, and 3) resistive media with IP effects in an alpine ice glacier. We evaluate our forward modeling approach by comparison to existing commercial and open-source software. To evaluate the TEM inversion results from field data, we compare them to results from complementary geophysical methods. We demonstrate the possibility to obtain reliable TEM data with the single-loop configuration, which simplifies field procedures and allows to obtain extensive data sets in rough terrains. Our results show the importance of including the IP effect in the inversion of TEM data to fit voltage readings that otherwise could not be resolved.