The origins of particles and trace gases involved in the rapidly changing polar climates remain unclear, limiting the reliability of climate models. This is especially true for particles involved in aerosol-cloud interactions with polar clouds. As detailed chemical fingerprinting measurements are difficult and expensive in polar regions, backward modeling is often used to identify the sources of observed atmospheric compounds. However, the accuracy of these methods is not well quantified. This study provides an evaluation of these analysis protocols by combining backward trajectories from the FLEXible PARTicle dispersion model (FLEXPART) with simulations of tracers from the Weather Research and Forecast model including Chemistry (WRF-Chem). Knowing the exact modeled tracer emission sources in WRF-Chem enables a precise quantification of the source detection accuracy. The results show that direct interpretation of backward model outputs or more advanced analyses like potential source contribution functions (PSCFs) are often unreliable in identifying emission sources. After exploring parameter sensitivities thanks to our simulation framework, we present an updated and rigorously evaluated backward-modeling analysis protocol for tracing the origins of atmospheric species from measurement data. Two tests of the improved protocol on actual aerosol data from Arctic campaigns demonstrate its ability to correctly identify known sources of methane sulfonic acid and black carbon. Our results reveal that traditional back-trajectory methods often misidentify emission source regions. Therefore, we recommend using the method described in this study for future efforts to trace the origins of measured atmospheric species.