## 2 Data Description  
For the estimation of PM\({}_{2.5}\) using AODs in this study, we used the multiple remote sensing instruments onboard low-orbit satellites: Moderate Resolution Imaging Spectro-radiometer (MODIS) on Terra and Aqua satellites, Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-NPP satellite, Multi-angle Imaging Spectroradiometer (MISR) on the Terra satellite, and Ozone Monitoring Instrument (OMI) on the Aura satellite [10; 11]. Each satellite mission has its own retrieval algorithm based on the different wavelength view-angle and spatiotemporal properties. For the MODIS measurement, AOD can be retrieved from both the Dark Target (DT) and Deep Blue (DB) algorithm with a 10 \(\times\) 10 km\({}^{2}\) resolution at nadir [12], and the DT AOD retrieval with a 3 km resolution [13]. Here we used these three different AODs, named MODIS-DT, MODIS-DB, and MODIS-3 km AODs, respectively. The differences in the specifications of all satellite AODs considered in this study are summarized in Table 1. Although the satellite sensors have multiple channels, AODs in the visible channel around 500-550 nm converted from other channels have been much qualified [11], and are usually considered to be the representative satellite AOD product. Thus, this study only used the satellite AODs at 500 or 550 nm wavelengths. This enabled a better diagnosis of the effect of the retrieval algorithm and spatiotemporal resolution on the PM\({}_{2.5}\) estimation. In addition to the satellite AOD measurements, we also utilized AODs from multiple ground-based measurements. Due to the participation of the KOREA-US air quality (KORUS-AQ) campaign [14], several ground-based remote sensing instruments were installed concurrently in May 2016 at the top of the Science Hall in Yonsei University, South Korea (37.564\({}^{\circ}\) N, 126.935\({}^{\circ}\) E), and maintained observations until April 2017: a sun-photometer registered in the Aerosol Robotic Network (AERONET), a skyradiometer registered in the SKYNET, a Brewer spectrophotometer, and two Multi-Filter Rotating Shadowband Radiometers (MFRSR), as summarized in Table 2[15; 16; 17; 18; 19; 20]. Because these are remote sensing instruments, AOD measurement is only available in daytime, from sunrise to sunset. AERONET and SKYNET AODs are generally produced each 20 min, the MFRSR AOD is per 5 min, and AOD of the Brewer spectrophotometer is per 1 h. To ensure consistency, we used the daily mean AOD for all instruments. In contrast to the satellite AOD, we used ground-based AOD observations at multiple channels (wavelengths) because this approach has been more intensively validated [21; 22; 23]. Because the ground-based instruments better reflect the local air properties and have better accuracy than the satellite measurements, the usage of these ground-based AOD observations enable inspection of the performance of PM\({}_{2.5}\) estimation according to the channel of the AODs. In order to prepare an effective MLR model for the PM estimation using various AODs, as described in the next section, a number of meteorological and physical variables are necessary. Planetary boundary layer height (PBLH) is one of the essential pieces of information in the conversion process between column-integrated and surface-level data [24]. In this study, we used the PBLH data retrieved from the ecolometer measurement at the top of the Science Hall in Yonsei University. The process of PBLH calculation was well described in [25]. For comparison purposes, we also used the PBLH from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data, ERA-Interim. Additionally, we used several meteorological parameters, such as air temperature, relative humidity, wind speed, and visibility. These meteorological parameters in the Korean peninsula are routinely monitored at the Automatic Weather Station (AWS) operated by the Korea Meteorological Administration (KMA). For this study, we used meteorological data