Application of a Signal Technique to the Source–Receptor Relationship in Three-Dimensional Tracer Simulations

Abstract

Identifying pollutant sources that contribute to downstream locations is important for policy making and air-quality control. In this study, a computationally economic signal technique was implemented into a three-dimensional nonhydrostatic atmospheric model to help to identify source?receptor relationships. An idealized supercell case and a semireal air-pollution case in Turkey were used to investigate the potential of the technique. For each pollutant, signals with various frequencies were emitted from different source locations and added into that particular type of emitted pollutants. The time series of pollutant concentration collected at receptors were then projected onto frequency space using the Fourier transform and short-time Fourier transform methods to identify the source locations. During the model integration, a particular tracer was also emitted from each pollutant source location (i.e., a conventional method to study the source?receptor relationship) to validate and evaluate the signal technique. Results show that frequencies could be slightly shifted after signals were transported for some distance and that evident secondary frequencies (i.e., beat frequencies) could be generated as a result of nonlinear effects. Although these could potentially confuse the identification of signals released from source points, signals were still distinguishable in this study. Results from a sensitivity test of the diffusion effect on different frequencies suggest that the effect of diffusion on amplitude damping is stronger for higher frequencies than for lower frequencies.