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Estimation of HCHO Column Using a Multiple Regression Method with OMI and MODIS Data

  • Hong, Hyunkee (Environmental Satellite Center, National Institute of Environmental Research: Department of Spatial Information Engineering, Pukyong National University) ;
  • Yang, Jiwon (Department of Spatial Information Engineering, Pukyong National University) ;
  • Kang, Hyeongwoo (Department of Spatial Information Engineering, Pukyong National University) ;
  • Kim, Daewon (Department of Spatial Information Engineering, Pukyong National University) ;
  • Lee, Hanlim (Department of Spatial Information Engineering, Pukyong National University)
  • Received : 2019.07.04
  • Accepted : 2019.07.31
  • Published : 2019.08.31

Abstract

We have estimated the vertical column density (VCD) of formaldehyde (HCHO) on a global scale using a multiple linear regression method (MRM) with Ozone Monitoring Instrument (OMI) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data. HCHO VCDs were estimated in regions of biogenic, pyrogenic, and anthropogenic emissions using independent variables, including $NO_2$ VCD, land surface temperature (LST), an enhanced vegetation index (EVI), and the mean fire radiative power (MFRP), which are strongly correlated with HCHO. To evaluate the HCHO estimates obtained using the MRM, we compared estimates of HCHO VCD data measured by OMI ($HCHO_{OMI}$) with those estimated by multiple linear regression equations (MRE) ($HCHO_{MRE}$). Good MRM performances were found, having the average statistical values (R = 0.91, slope = 1.03, mean bias = $-0.12{\times}10^{15}molecules\;cm^{-2}$, percent difference = 11.27%) between $HCHO_{MRE}$ and $HCHO_{OMI}$ in our study regions where high HCHO levels are present. Our results demonstrate that the MRM can be a useful tool for estimating atmospheric HCHO levels.

Acknowledgement

Supported by : Pukyong National University

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