# Data Assimilation of AOD and Estimation of Surface Particulate Matters over the Arctic
## 2 Experiments  
### Description of WRF/CMAQ Model Simulations  
A year-long Chemistry Transport Model (CTM) simulation was carried out to understand the levels of particulate matter over the Arctic. WRF v3.4.1 modeling [52] was also carried out to generate meteorological fields, acting as drivers and/or driving atmospheric chemical and physical processes of the regional CTM model, such as (i) the transports of species; (ii) chemical losses through chemical reactions and photolysis; (iii) physical removal through dry and wet depositions. For the WRF model simulation, the initial and lateral boundary conditions were taken from the National Center for EnvironmentalAs a 3D-CTM, Community Multi-scale Air Quality (CMAQ) v5.1 model was employed to simulate the levels of air pollutants over the Arctic for the year 2008 [61]. We decided on 2008 as the target year because many modeling and observation studies were conducted as part of POLARCAT-IPY, aiming at improving understanding of Arctic pollution and its impact on climate during International Polar Year (IPY) in 2007 and 2008 [62]. From a meteorological perspective, it is unusual for the Arctic weather in 2008, which showed an abnormally cold winter in Greenland, especially with an intense melt season [63]. The modeling domain centered on Svalbard was configured with 18 km \(\times\) 18 km horizontal grid spacing and vertical resolution of 17 layers from surface to 80 hPa, covering the Arctic Ocean, Greenland Sea, Barents Sea, Norwegian Sea, Greenland, Queen Elizabeth Island, and some parts of Norway, Sweden, Finland, and Russia (Figure 1a). We employed the SAPRC-07 mechanism and AERO6 module for the gas-phase chemistry and aerosol (thermo) dynamics, respectively (Table 1). Information on boundary conditions for atmospheric gases and aerosols were taken from the output simulated by the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4) model ([[http://www.acom.ucaredu/wrf-chem/mozart.shtml](http://www.acom.ucaredu/wrf-chem/mozart.shtml)]([http://www.acom.ucaredu/wrf-chem/mozart.shtml](http://www.acom.ucaredu/wrf-chem/mozart.shtml))) [64]. The anthropogenic emissions of gaseous and particulate species were obtained from the Monitoring Atmospheric Composition and Climate and megacity Zoom for the Environment projects (MACCity), which has a 0.5\({}^{\circ}\) resolved database compiled for the year 2008 [65]. For PM\({}_{10}\) and PM\({}_{2.5}\), the anthropogenic emissions were taken into account from the Evaluating the Climate and Air Quality Impacts of Short-lived Pollutants (ECLIPSE) v4a emission inventories based on the CLE scenario [66]. Furthermore, to consider biogenic and biomass burning emissions, we used the 0.5\({}^{\circ}\) resolved Model of Emissions of Gases and Aerosols from Nature-Monitoring Atmospheric Composition and Climate (MEGAN-MACC) and Global Fire Emissions Database v3 (GFED3) emission inventories, respectively [67; 68]. All emissions were downloaded from the ECCAD archive ([[https://eccad3.sedoo.fr/](https://eccad3.sedoo.fr/)]([https://eccad3.sedoo.fr/](https://eccad3.sedoo.fr/))). Figure 1 presented the annual emission fluxes of SO\({}_{2}\), NOx, EC, OC, PM\({}_{10}\), and PM\({}_{2.5}\) used in the CMAQ model simulations. High emission fluxes were found over Finland and Russia in the study domain. Despite relatively fewer amounts of emissions, the ship-emitted pollutants were considered in the emission inventory. The emissions can be seen along the coastal lines of Norway and Iceland.