Improvement of Surface PM 2.5 Diurnal Variation Simulations in East Africa for the MAIA Satellite Mission

Chengzhe Li; Jun Wang; Huanxin Zhang; David J. Diner; Sina Hasheminassab; Nathan Janechek

doi:10.1021/acsestair.3c00008

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Improvement of Surface PM 2.5 Diurnal Variation Simulations in East Africa for the MAIA Satellite Mission

Journal article

Open access

Peer reviewed

Improvement of Surface PM 2.5 Diurnal Variation Simulations in East Africa for the MAIA Satellite Mission

Chengzhe Li, Jun Wang, Huanxin Zhang, David J. Diner, Sina Hasheminassab and Nathan Janechek

ACS ES&T Air, Vol.1(4), pp.223-233

04/12/2024

DOI: 10.1021/acsestair.3c00008

Appears in UI Libraries Support Open Access

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Abstract

The Multi-Angle Imager for Aerosols (MAIA), supported by NASA and the Italian Space Agency, is planned for launch into space in 2025. As part of its mission goal, outputs from a chemical transport model, the Unified Inputs for Weather Research and Forecasting Model coupled with Chemistry (UI-WRF-Chem), will be used together with satellite data and surface observations for estimating surface PM2.5. Here, we develop a method to improve UI-WRF-Chem with surface observations at the U.S. embassy in Ethiopia, one of MAIA’s primary target areas in east Africa. The method inversely models the diurnal profile and amount of anthropogenic aerosol and trace gas emissions. Low-cost PurpleAir sensor data are used for validation after applying calibration functions obtained from the collocated data at the embassy. With the emission updates in UI-WRF-Chem, independent validation for February 2022 at several different PurpleAir sites shows an increase in the linear correlation coefficients from 0.1–0.7 to 0.6–0.9 between observations and simulations of the diurnal variation of surface PM2.5. Furthermore, even by using the emissions optimized for February 2021, the UI-WRF-Chem forecast for March 2022 is also improved. Annual update of monthly emissions via inverse modeling has the potential and is needed to improve MAIA’s estimate of surface PM2.5.

PM2.5

Diurnal Variation

Inverse Modeling

UI-WRF-Chem

Addis Ababa

Ethiopia

Anthropogenic Emission

UIOWA OA Agreement

Details

Title: Subtitle: Improvement of Surface PM 2.5 Diurnal Variation Simulations in East Africa for the MAIA Satellite Mission
Creators: Chengzhe Li - University of Iowa
Jun Wang - University of Iowa
Huanxin Zhang - University of Iowa
David J. Diner - Jet Propulsion Laboratory
Sina Hasheminassab - Jet Propulsion Laboratory
Nathan Janechek - University of Iowa
Resource Type: Journal article
Publication Details: ACS ES&T Air, Vol.1(4), pp.223-233
DOI: 10.1021/acsestair.3c00008
ISSN: 2837-1402
eISSN: 2837-1402
Publisher: American Chemical Society
Grant note: DOI: 10.13039/100006196, name: Jet Propulsion Laboratory, award: 1583456
Language: English
Electronic publication date: 01/29/2024
Date published: 04/12/2024
Academic Unit: Electrical and Computer Engineering; Civil and Environmental Engineering; Iowa Technology Institute; Physics and Astronomy; Chemical and Biochemical Engineering
Record Identifier: 9984554855102771

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