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Mineral dust particles play an important role in the Earth system, imposing a variety of effects on air quality, climate, human health, and economy. Accurate forecasts of dust events are highly desirable to provide an early warning and inform the decision-making process. East Asia is one of the largest dust sources in the world. This study applies and evaluates four widely used regional air quality models to simulate dust storms in northeastern China. Three dust schemes in the Weather Research and Forecasting model with Chemistry (WRF-Chem) (version 3.9.1), two schemes in both CHIMERE (version 2017r4) and CMAQ (version 5.2.1), and one scheme in CAMx (version 6.50) were applied to a dust event during 4-6 May 2015 in northeastern China. Most of these models were able to capture this dust event with the exception of CAMx, which has no dust source map covering the study area; hence, another dust source mask map was introduced to replace the default one for the subsequent simulation. Although these models reproduced the spatial pattern of the dust plume, there were large discrepancies between predicted and observed PM10 concentrations in each model. In general, CHIMERE had relatively better performance among all simulations with default configurations. After parameter tuning, WRF-Chem with the Air Force Weather Agency (AFWA) scheme using a seasonal dust source map from Ginoux et al. (2012) showed the best performance, followed by WRF-Chem with the UOC_Shao2004 scheme, CHIMERE, and CMAQ. The performance of CAMx had significantly improved by substituting the default dust map and removing the friction velocity limitation. This study suggested that the dust source maps should be carefully selected on a regional scale or replaced with a new one constructed with local data. Moreover, further study and measurement of sandblasting efficiency of different soil types and locations should be conducted to improve the accuracy of estimated vertical dust fluxes in air quality models.