Much attention has been found to the long-range transport (LRT) of air pollutants and their adverse effects on downwind air qualities resulting from the Chinese haze, which frequently occurs in association with winter monsoon. This study integrates ground-based measurements, unmanned aerial vehicles (UAVs), and model simulations to characterize the meteorological, chemical, and particulate matter (PM) properties comprehensively for the events that were LRT or local pollution (LP) dominated in northern Taiwan during the wintertime of 2017. During the two types of episodes, various approaches were made to investigate the vertical mixing conditions and PM properties with UAV flights. A confined and PM accumulated feature near ground level with a temperature inversion was found during the LP event. In contrast, a vertically homogeneous atmospheric structure with strong winds was suggested during the LRT event. Independent measurements of criteria air pollutants, meteorological variables, volatile organic compounds (VOCs), and micropulse lidar (MPL) made at the ground level were closely supported by the vertical measurements. When synchronizing all these observational and numerical tools in a three-dimensional manner, the characterization of air masses and possible origins of pollution, such as LP vs. LRT, has now become more versatile and capable of gaining a complete picture of atmospheric conditions that define air quality.