Abstract
Abstract. The performance of various empirical linear models to estimate the concentrations of surface-level particulate matter with a diameter less than 10 μm (PM10) was evaluated using Aerosol Robotic Network (AERONET) sun photometer and Moderate-Resolution Imaging Spectroradiometer (MODIS) data collected in Seoul during the Distributed Regional Aerosol Gridded Observation Network (DRAGON)-Asia campaign from March to May 2012. An observed relationship between the PM10 concentration and the aerosol optical depth (AOD) was accounted for by several parameters in the empirical models, including boundary layer height (BLH), relative humidity (RH), and effective radius of the aerosol size distribution (Reff), which was used here for the first time in empirical modeling. Among various empirical models, the model which incorporates both BLH and Reff showed the highest correlation, which indicates the strong influence of BLH and Reff on the PM10 estimations. Meanwhile, the effect of RH on the relationship between AOD and PM10 appeared to be negligible during the campaign period (spring), when RH is generally low in northeast Asia. A large spatial dependency of the empirical model performance was found by categorizing the locations of the collected data into three different site types, which varied in terms of the distances between instruments and source locations. When both AERONET and MODIS data sets were used in the PM10 estimation, the highest correlations between measured and estimated values (R = 0.76 and 0.76 using AERONET and MODIS data, respectively) were found for the residential area (RA) site type, while the poorest correlations (R = 0.61 and 0.68 using AERONET and MODIS data, respectively) were found for the near-source (NS) site type. Significant seasonal variations of empirical model performances for PM10 estimation were found using the data collected at Yonsei University (one of the DRAGON campaign sites) over a period of 17 months including the DRAGON campaign period. The best correlation between measured and estimated PM10 concentrations (R = 0.81) was found in winter, due to the presence of a stagnant air mass and low BLH conditions, which may have resulted in relatively homogeneous aerosol properties within the BLH. On the other hand, the poorest correlation between measured and estimated PM10 concentrations (R = 0.54) was found in spring, due to the influence of the long-range transport of dust to both within and above the BLH.
Highlights
Atmospheric aerosols are known to play an important role in air quality and climate change (Kaufman et al, 2002; WHO, 2005; IPCC, 2013)
Concentrations of PM10 were estimated in Seoul, Korea, during the Distributed Regional Aerosol Gridded Observation Network (DRAGON)-Asia campaign period by considering the effective radius of the aerosol size distribution, together with boundary layer height (BLH), relative humidity (RH), and aerosol optical depth (AOD), within empirical models that used Aerosol Robotic Network (AERONET) data obtained at multiple sites for the first time
The performances of various empirical models were evaluated for hourly PM10 estimations using AERONET and Moderate-Resolution Imaging Spectroradiometer (MODIS) data sets
Summary
Atmospheric aerosols are known to play an important role in air quality and climate change (Kaufman et al, 2002; WHO, 2005; IPCC, 2013). Spatial distributions of PM2.5 can be estimated by applying the ratio of AOD to PM2.5, as calculated from chemical transport models (CTMs), such as the Goddard Earth Observing System-Chemistry (GEOS-CHEM) transport model and the Community Multiscale Air Quality (CMAQ) model (Liu et al, 2004; Choi et al, 2009; van Donkelaar et al, 2010). These previous studies have demonstrated the strong possibility of deriving surface PM concentrations from AOD data
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