| Full text | |
| Author(s): |
Schumacher, Vanucia
;
Setzer, Alberto
Total Authors: 2
|
| Document type: | Journal article |
| Source: | Atmospheric Environment; v. 323, p. 14-pg., 2024-02-14. |
| Abstract | |
The present study carries out the systematic performance evaluation of aerosol optical depth (AOD) products retrieved using Visible Infrared Imaging Radiometer Suite (VIIRS) Deep Blue (DB) and Dark Target (DT) onboard Suomi National Polar-orbiting Partnership (S-NPP) satellite over the Amazon Basin. Characteristics and uncertainty were evaluated under distinct air pollution scenarios such as a clean background in the wet season, polluted conditions in the dry season with biomass burning emissions and peak burning season with higher fire activity. VIIRS retrievals were also analyzed under aerosol loading, particle size and surface vegetation coverage against the Aerosol Robotic Network (AERONET) measurements at 9 sites in 2012-2022. VIIRS DB showed good accuracy, with 78% of AOD matchups falling within the expected error, 84% in the wet season, and 71% in the dry and burning seasons. In contrast, VIIRS DT indicated poor accuracy (64%) and trends overestimate the AOD in all air pollution scenarios. Both algorithms were sensitive to AERONET sites with high elevation and dark vegetated coverage characteristics. VIIRS DB and DT systematically overestimated AERONET AOD as increased aerosol loading. DB trends underestimate aerosol under background conditions and overestimate with coarse and fine particle predominance. Additionally, both algorithms indicated poor accuracy under forest type with a large positive bias. VIIRS DB demonstrated the highest accuracy in the presence of aerosol loading in sites characterized by mixed land cover type. This was observed in both coarse and fine mode scenarios for grassland. VIIRS DT demonstrated satisfactory accuracy under background conditions and dominance of coarse particles within grassland land cover type. For mixed land cover, satisfactory accuracy was found under intermediate aerosol loading conditions. DB algorithm showed greater uncertainty associated with the coarse particle aerosol for the full period and all polluted scenarios. Overall, VIIRS DT accuracy was more sensitive to varying air pollution scenarios. (AU) | |
| FAPESP's process: | 22/01829-8 - Validation and calibration of satellite measurements of aerosols and trace gases with surface monitoring stations |
| Grantee: | Vanúcia Schumacher Pogorzelski |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 20/15230-5 - Research Centre for Greenhouse Gas Innovation - RCG2I |
| Grantee: | Julio Romano Meneghini |
| Support Opportunities: | Research Grants - Research Centers in Engineering Program |