The potential source contribution function (PSCF) is a receptor modeling technique for identifying emission sources and transport pathways. This technique has been widely used in the determination of potential emission sources and preferred transport pathways of a variety of air pollutants for more than a decade. However, the model has not been objectively evaluated against well-documented real-world data and the performance of the model is virtually untested. In this study we verified the PSCF model and tested the model performance by taking the opportunity of the 1998 Central America smoke events that produced elevated levels of aerosols detected at the Southern Great Plains site operated by the U.S. Department of Energy's Atmospheric Radiation Measurement. Our results show that the PSCF model could correctly identify the emission source locations and transport pathways of the smoke particles. However, one cannot take the PSCF results for granted without further examination of back trajectories that are responsible for the transport. False positives could result from the tailing of the back trajectories that travel over the true source locations. Model performance analysis suggests that using the mean or median as the criterion value yielded satisfactory PSCF results. Use of a high criterion value (e.g., the 90th percentile) and a larger database could improve the resolution of PSCF source identification. Trajectory arrival height above the surface sampling station should be carefully chosen to be within the column mixing height to ensure an effective coupling of transport and surface measurement. ¿ 2001 American Geophysical Union