The Arctic is influenced by long-range transport of air masses from mid-latitudes, during winter and spring. There are also local sources within the Arctic region, such as combustion for heating and power production, leading to enhance aerosol concentrations in remote sites. However, the formation of secondary aerosol particles in the dark wintertime Arctic conditions is poorly understood. In this study, which contributes to the Air Pollution in the Arctic: Climate, Environment and Societies - Alaskan Layered Pollution and Chemical Analysis (PACES-ALPACA) initiative, the Weather Research Forecasting Model with chemistry (WRF-Chem) is used to investigate wintertime pollution over central Alaska, focusing on the Fairbanks region, during the pre-ALPACA campaign in winter 2019. Fairbanks is the most polluted city in the United States during winter due to high local emissions and the occurrence of strong surface temperature inversions trapping pollutants near the surface. During the pre-ALPACA campaign aerosols, oxidants and aerosol precursors, were measured in key locations in Fairbanks, including vertical profile data collected in the lowest 20m, with the aim to identify the origins of aerosols during pollution episodes. A quasi-hemispheric WRF-Chem simulation, using an improved WRF set-up with increased vertical resolution below 2km, is used to assess large-scale synoptic conditions and to evaluate Arctic Haze, influencing central Alaska. The model was run with Copernicus Atmosphere Monitoring System v4.2 anthropogenic emissions, with an initial horizontal resolution of 10x10km. Discrepancies in modelled aerosols compared to available data are investigated (missing dark formation mechanisms, treatment of removal processes). Fine-resolution WRF-Chem simulations, including local point sources, over the Fairbanks region are used to explore chemical and dynamical processes influencing aerosol formation under different meteorological conditions observed during the campaign, including a cold stable episode and a period with possible mixing of air masses from aloft. Model results are evaluated against data from surface monitoring sites and collected during the campaign. The sensitivity of modelled aerosols to meteorological factors (relative humidity, vertical mixing) are examined.