<p>A model that requires only minimal input parameters while accurately estimating pollution sources is crucial for air quality management, the formulation of pollution reduction strategies, and effective environmental enforcement. The current study proposes a novel approach based on expected values theory to identify the concentration of pollutants contributed by various sources to 10 monitoring stations in Central Taiwan Science and Industrial Park in Taichung, Taiwan. Wind speed and wind direction are the only two required input variables in the present model for source tracing. Data from 2005 to 2006 were used to test the viability of the proposed model. The rigorous data analysis of the year-long monitoring program revealed that approximately 50% of the reported pollutants originated from Central Taiwan Science and Industrial Park, 30% originated from mobile pollution sources in the surrounding area, such as traffic, and the rest originated from unrelated industries in the surrounding area. It is noted that the accuracy and the resolution of predictions by the present model are limited by the quantity of ground-level sampling. In the future, integrating the present model and monitoring data by calibrated low-cost sensors could further enhance the accuracy and spatial resolution of the air pollution source tracing.</p>