SO2 trajectories in a complex terrain environment using CALPUFF dispersion model, OMI and MODIS data
2018
Sagan, Vasit | Pasken, Robert | Zarauz, Jorge | Krotkov, Nickolay
Latest improvements in the resolution of atmospheric satellite sensors that measure chemical constituents from space have led to enhanced detection of trace gases. This paper explores the use of sulfur dioxide (SO₂) level 2 dataset from OMI instrument, in conjunction with aerosol optical depth and Ångström exponent data from MODIS spectroradiometer, to estimate SO₂ loads under clear and turbid atmospheres. The spatial patterns of SO₂ loads in polluted atmospheric conditions are compared with a regional pollutant dispersion model (CALPUFF) and field observations near the Andes Peruvian city La Oroya, which is one of the most polluted places in the world. The efficacy of this methodology is further examined incorporating synchronous wind vectors. Results show that the spatial-temporal dynamics of OMI SO₂ is in agreement with field measurements and CALPUFF. The SO₂ satellite data obtained under optimal viewing conditions and clear skies are also compared with field observations. A correlation is found between in-situ measurements and OMI estimations. The correlation increases for days with predominantly fine aerosols when Ångström exponents are between 0.7 and 1. Moreover, pixel averaging techniques and low and high spatial frequency filtration, applied to OMI SO₂ data, results in a more reliable representation of the mean SO₂ plume. The paper concludes that anthropogenic SO₂ can be monitored from space, even for turbid sky conditions. This demonstrates the potential for the use of satellite products to improve the air quality prediction models.
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