A GIS-based assessment of the suitability of SCIAMACHY satellite sensor measurements for estimating reliable CO concentrations in a low-latitude climate

Environ Monit Assess. 2015 Feb;187(2):25. doi: 10.1007/s10661-014-4227-2. Epub 2015 Jan 28.

Abstract

An assessment of the reliability of the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) satellite sensor measurements to interpolate tropospheric concentrations of carbon monoxide considering the low-latitude climate of the Niger Delta region in Nigeria was conducted. Monthly SCIAMACHY carbon monoxide (CO) column measurements from January 2,003 to December 2005 were interpolated using ordinary kriging technique. The spatio-temporal variations observed in the reliability were based on proximity to the Atlantic Ocean, seasonal variations in the intensities of rainfall and relative humidity, the presence of dust particles from the Sahara desert, industrialization in Southwest Nigeria and biomass burning during the dry season in Northern Nigeria. Spatial reliabilities of 74 and 42 % are observed for the inland and coastal areas, respectively. Temporally, average reliability of 61 and 55 % occur during the dry and wet seasons, respectively. Reliability in the inland and coastal areas was 72 and 38 % during the wet season, and 75 and 46 % during the dry season, respectively. Based on the results, the WFM-DOAS SCIAMACHY CO data product used for this study is therefore relevant in the assessment of CO concentrations in developing countries within the low latitudes that could not afford monitoring infrastructure due to the required high costs. Although the SCIAMACHY sensor is no longer available, it provided cost-effective, reliable and accessible data that could support air quality assessment in developing countries.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Air Pollutants / analysis*
  • Altitude
  • Atlantic Ocean
  • Biomass
  • Carbon Monoxide / analysis*
  • Dust / analysis
  • Environmental Monitoring / methods*
  • Geographic Information Systems*
  • Reproducibility of Results
  • Satellite Imagery*
  • Seasons

Substances

  • Air Pollutants
  • Dust
  • Carbon Monoxide