Retrieval of nighttime aerosol optical depth by simultaneous consideration of artificial and natural light sources.

Aerosol optical depth Atmospheric radiative transfer simulation Extinction method Nighttime VIIRS/DNB

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
20 Oct 2023
Historique:
received: 05 04 2023
revised: 13 08 2023
accepted: 15 08 2023
medline: 19 8 2023
pubmed: 19 8 2023
entrez: 18 8 2023
Statut: ppublish

Résumé

Aerosol Optical Depth (AOD) is a critical optical parameter that quantifies the degree of light attenuation by aerosols and serves as a fundamental indicator of atmospheric quality. Therefore, accurate quantification and retrieval of AOD is crucial for relevant studies. However, current satellite-based AOD retrieval algorithms suffer from inapplicability under low-light conditions, limiting the development of nighttime AOD retrieval. Under this context, we proposed a novel algorithm, namely Simultaneous Consideration of Artificial and Natural light Sources (SCANS), to obtain nighttime AOD. The core of the SCANS algorithm is considering the synergy of both the natural and artificial light sources to obtain nighttime AOD by integrating atmospheric radiative transfer simulation into an extinction method and performing multiple iterations. SCANS was applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) and the retrieved nighttime AOD was validated with in-situ measurements from five AERONET sites. Results indicate that the Mean Bias Errors (MBEs) of the retrieved nighttime AOD range from 0.0 to 0.08 and the corresponding Root Mean Square Errors (RMSEs) range from 0.11 to 0.17, which exhibit better accuracy than that of the nighttime MERRA-2 AOD. We further compared the retrieved nighttime AOD with the corresponding Air Quality Index (AQI) measurements at six environment monitoring stations and obtained high correlation coefficients (i.e., ranging from 0.733 to 0.940), indicating SCANS's reliability and high accuracy. The proposed SCANS algorithm can effectively obtain nighttime AOD with high quality, thereby advancing research on the diurnal variation of crucial Earth's key elements.

Identifiants

pubmed: 37595924
pii: S0048-9697(23)04979-3
doi: 10.1016/j.scitotenv.2023.166354
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

166354

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Yizhen Meng (Y)

School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China. Electronic address: yz.meng@std.uestc.edu.cn.

Ji Zhou (J)

School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China. Electronic address: jzhou233@uestc.edu.cn.

Ziwei Wang (Z)

School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China. Electronic address: wangzw@std.uestc.edu.cn.

Wenbin Tang (W)

School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China. Electronic address: wenbint@std.uestc.edu.cn.

Jin Ma (J)

School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China. Electronic address: jin.ma@uestc.edu.cn.

Tao Zhang (T)

School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China. Electronic address: zhangtao_sre@uestc.edu.cn.

Zhiyong Long (Z)

College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China. Electronic address: longzhiyong17@nudt.edu.cn.

Classifications MeSH