Understanding haze: modeling size-resolved mineral aerosol from satellite remote sensing
Mineral dust aerosols are composed of a complex mixture of silicates, carbonates, oxides, and sulfates. The minerals’ chemical composition and size distribution are vital parameters to evaluate dust environmental impacts. However, the quantification of minerals remains a challenge due to the sparse...
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sg-ntu-dr.10356-1605992022-07-30T20:11:24Z Understanding haze: modeling size-resolved mineral aerosol from satellite remote sensing Sanwlani, Nivedita Das, Reshmi Earth Observatory of Singapore Satellite Remote Sensing Centre Science::Geology Mineral Dust Aerosol Aerosol Size Distribution Mineral dust aerosols are composed of a complex mixture of silicates, carbonates, oxides, and sulfates. The minerals’ chemical composition and size distribution are vital parameters to evaluate dust environmental impacts. However, the quantification of minerals remains a challenge due to the sparse in situ measurements of dust samples. Here we derive the size-resolved mineralogical composition of airborne dust aerosols from MODIS (Terra and Aqua) satellite-acquired optical measurements and compare it with chemically analyzed elemental (Al, Fe, Ca, Mg) concentrations of aerosols for PM2.5 and PM10 from Chonburi, Chiang Rai, and Bangkok in Thailand, and from Singapore. MODIS-derived mineral retrievals exhibited high correlations with elemental concentrations with R2 ≥ 0.84 for PM2.5 and ≥0.96 for PM10 . High mineral dust activity was detected in the vicinity of biomass-burning areas with gypsum and calcite exhibiting tracer characteristics of combustion. The spatiotemporal pattern of the MODIS-derived minerals matched with Ozone Monitoring Instrument (OMI)-derived dust, sulfates, and carbonaceous aerosols, indicating the model’s consistency. Variation in aerosol loading by ±90% led to deviation in the mineral concentration by <10%. An uncertainty of 6.4% between AERONET-measured and MODIS-derived AOD corresponds to a < ± 2% uncertainty in MODIS-derived mineral concentration, demonstrating the robustness of the model. Ministry of Education (MOE) Published version The in situ chemical analyses of aerosols were supported by a Singapore Ministry of Education (MOE) Tier 1 grant (MOE-NTU_RG125/16-(S)). 2022-07-27T06:18:05Z 2022-07-27T06:18:05Z 2022 Journal Article Sanwlani, N. & Das, R. (2022). Understanding haze: modeling size-resolved mineral aerosol from satellite remote sensing. Remote Sensing, 14(3), 761-. https://dx.doi.org/10.3390/rs14030761 2072-4292 https://hdl.handle.net/10356/160599 10.3390/rs14030761 2-s2.0-85124518363 3 14 761 en MOE-NTU_RG125/16-(S) Remote Sensing © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf |
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Science::Geology Mineral Dust Aerosol Aerosol Size Distribution Sanwlani, Nivedita Das, Reshmi Understanding haze: modeling size-resolved mineral aerosol from satellite remote sensing |
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Mineral dust aerosols are composed of a complex mixture of silicates, carbonates, oxides, and sulfates. The minerals’ chemical composition and size distribution are vital parameters to evaluate dust environmental impacts. However, the quantification of minerals remains a challenge due to the sparse in situ measurements of dust samples. Here we derive the size-resolved mineralogical composition of airborne dust aerosols from MODIS (Terra and Aqua) satellite-acquired optical measurements and compare it with chemically analyzed elemental (Al, Fe, Ca, Mg) concentrations of aerosols for PM2.5 and PM10 from Chonburi, Chiang Rai, and Bangkok in Thailand, and from Singapore. MODIS-derived mineral retrievals exhibited high correlations with elemental concentrations with R2 ≥ 0.84 for PM2.5 and ≥0.96 for PM10 . High mineral dust activity was detected in the vicinity of biomass-burning areas with gypsum and calcite exhibiting tracer characteristics of combustion. The spatiotemporal pattern of the MODIS-derived minerals matched with Ozone Monitoring Instrument (OMI)-derived dust, sulfates, and carbonaceous aerosols, indicating the model’s consistency. Variation in aerosol loading by ±90% led to deviation in the mineral concentration by <10%. An uncertainty of 6.4% between AERONET-measured and MODIS-derived AOD corresponds to a < ± 2% uncertainty in MODIS-derived mineral concentration, demonstrating the robustness of the model. |
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Earth Observatory of Singapore |
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Earth Observatory of Singapore Sanwlani, Nivedita Das, Reshmi |
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Article |
author |
Sanwlani, Nivedita Das, Reshmi |
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Sanwlani, Nivedita |
title |
Understanding haze: modeling size-resolved mineral aerosol from satellite remote sensing |
title_short |
Understanding haze: modeling size-resolved mineral aerosol from satellite remote sensing |
title_full |
Understanding haze: modeling size-resolved mineral aerosol from satellite remote sensing |
title_fullStr |
Understanding haze: modeling size-resolved mineral aerosol from satellite remote sensing |
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Understanding haze: modeling size-resolved mineral aerosol from satellite remote sensing |
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understanding haze: modeling size-resolved mineral aerosol from satellite remote sensing |
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2022 |
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https://hdl.handle.net/10356/160599 |
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