干旱区生态环境知识资源中心(Arid): Classification of aerosols over Saudi Arabia from 2004-2016

Arid

DOI	10.1016/j.atmosenv.2020.117785
	Classification of aerosols over Saudi Arabia from 2004-2016
	Ali, Arfan; Nichol, Janet E.; Bilal, Muhammad; Qiu, Zhongfeng; Mazhar, Usman; Wahiduzzaman, Md; Almazroui, Mansour; Islam, M. Nazrul
通讯作者	Bilal, M
来源期刊	ATMOSPHERIC ENVIRONMENT
ISSN	1352-2310
EISSN	1873-2844
出版年	2020
卷号	241
英文摘要	Knowledge of aerosol size and composition is very important for investigating the radiative forcing impacts of aerosols, distinguishing aerosol sources, and identifying harmful particulate types in air quality monitoring. The ability to identify aerosol type synoptically would greatly contribute to the knowledge of aerosol type distribution at both regional and global scales, especially where there are no data on chemical composition. In this study, aerosol classification techniques were based on aerosol optical properties from remotely-observed data from the Ozone Monitoring Instrument (OMI) and Aerosol Robotic Network (AERONET) over Saudi Arabia for the period 2004-2016 and validated using data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). For this purpose, the OMI-based Aerosol Absorption Optical Depth (AAOD) and UltraViolet Aerosol Index (UVAI), and AERONET-based AAOD, Angstrom Exponent (AE), Absorption Angstrom Exponent (AAE), Fine Mode Fraction (FMF), and Single Scattering Albedo (SSA) were obtained. Spatial analysis of the satellite-based OMI-AAOD showed the dominance of absorbing aerosols over the study area, but with high seasonal variability. The study found significant underestimation by OMI AAOD suggesting that the OMAERUV product may need improvement over bright desert surfaces such as the study area. Aerosols were classified into (i) Dust, (ii) Black Carbon (BC), and (iii) Mixed (BC and Dust) based on the relationships technique, between the aerosol absorption properties (AAE, SSA, and UVAI) and size parameters (AE and FMF). Additionally, the AE vs. UVAI and FMF vs. UVAI relationships misclassified the aerosol types over the study area, and the FMF vs. AE, FMF vs. AAE and FMF vs. SSA relationships were found to be robust. As expected, the dust aerosol type was dominant both annually and seasonally due to frequent dust storm events. Also, fine particulates such as BC and Mixed (BC and Dust) were observed, likely due to industrial activities (cement, petrochemical, fertilizer), water desalination plants, and electric energy generation. This is the first study to classify aerosol types over Saudi Arabia using several different aerosol property relationships, as well as over more than one site, and using data over a much longer time-period than previous studies. This enables classification and recognition of specific aerosol types over the Arabian Peninsula and similar desert regions.
英文关键词	Aerosols AERONET Single scattering albedo Absorption angstrom exponent Ozone monitoring instrument Aerosol absorption optical depth
类型	Article
语种	英语
开放获取类型	Green Accepted
收录类别	SCI-E
WOS记录号	WOS:000576812500004
WOS关键词	MULTIPLE CLUSTERING-TECHNIQUES ; INDO-GANGETIC PLAIN ; OPTICAL-PROPERTIES ; BLACK CARBON ; WAVELENGTH DEPENDENCE ; AOD VARIABILITY ; AERONET ; DEPTH ; DUST ; ABSORPTION
WOS类目	Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
来源机构	南京信息工程大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/326725
作者单位	[Ali, Arfan; Bilal, Muhammad; Qiu, Zhongfeng] Nanjing Univ Informat Sci & Technol, Sch Marine Sci, Nanjing 210044, Peoples R China; [Nichol, Janet E.] Univ Sussex, Sch Global Studies, Dept Geog, Brighton, E Sussex, England; [Mazhar, Usman] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing 210044, Peoples R China; [Wahiduzzaman, Md] Nanjing Univ Informat Sci & Technol, Joint Int Res Lab Climate & Environm Change ILCEC, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Key Lab Meteorol Disaster,Minist Educ KLME,Inst C, Nanjing 210044, Peoples R China; [Almazroui, Mansour; Islam, M. Nazrul] King Abdulaziz Univ, Ctr Excellence Climate Change Res, Dept Meteorol, Jeddah 21589, Saudi Arabia
推荐引用方式 GB/T 7714	Ali, Arfan,Nichol, Janet E.,Bilal, Muhammad,et al. Classification of aerosols over Saudi Arabia from 2004-2016[J]. 南京信息工程大学,2020,241.
APA	Ali, Arfan.,Nichol, Janet E..,Bilal, Muhammad.,Qiu, Zhongfeng.,Mazhar, Usman.,...&Islam, M. Nazrul.(2020).Classification of aerosols over Saudi Arabia from 2004-2016.ATMOSPHERIC ENVIRONMENT,241.
MLA	Ali, Arfan,et al."Classification of aerosols over Saudi Arabia from 2004-2016".ATMOSPHERIC ENVIRONMENT 241(2020).