气候变化领域集成服务门户(CCPortal): Classification of aerosols over Saudi Arabia from 2004

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DOI	10.1016/j.atmosenv.2020.117785
	Classification of aerosols over Saudi Arabia from 2004–2016
	Ali M.A.; Nichol J.E.; Bilal M.; Qiu Z.; Mazhar U.; Wahiduzzaman M.; Almazroui M.; Islam M.N.
发表日期	2020
ISSN	1352-2310
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 Ultra-Violet Aerosol Index (UVAI), and AERONET-based AAOD, Ångström Exponent (AE), Absorption Ångström 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. © 2020 Elsevier Ltd
关键词	Absorption ångström exponent AERONET Aerosol absorption optical depth Aerosols Ozone monitoring instrument Single scattering albedo
语种	英语
scopus关键词	Air quality; Atmospheric radiation; Desalination; Dust; Optical properties; Optical radar; Storms; Ultraviolet spectrometers; Water filtration; Aerosol optical property; Aerosol robotic networks; Classification and recognition; Classification technique; Cloud-aerosol lidar and infrared pathfinder satellite observations; Electric energy generation; Ozone monitoring instruments; Single scattering albedo; Aerosols; black carbon; ozone; AERONET; aerosol; aerosol composition; aerosol property; air quality; albedo; CALIPSO; instrumentation; model validation; optical property; particle size; pollution monitoring; radiative forcing; absorption; aerosol; air pollution; air quality; Article; cloud; comparative study; desalination; dust; dust storm; electricity; environmental monitoring; industrialization; nonhuman; optical depth; ozone layer; plant; priority journal; Saudi Arabia; ultraviolet radiation; Arabian Peninsula; Saudi Arabia
来源期刊	ATMOSPHERIC ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/248939
作者单位	School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Department of Geography, School of Global Studies, University of Sussex, United Kingdom; School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Institute for Climate and Application Research (ICAR), Nanjing University of Information Science & Technology, Nanjing, 210044, China; Center of Excellence for Climate Change Research/Department of Meteorology, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
推荐引用方式 GB/T 7714	Ali M.A.,Nichol J.E.,Bilal M.,等. Classification of aerosols over Saudi Arabia from 2004–2016[J],2020,241.
APA	Ali M.A..,Nichol J.E..,Bilal M..,Qiu Z..,Mazhar U..,...&Islam M.N..(2020).Classification of aerosols over Saudi Arabia from 2004–2016.ATMOSPHERIC ENVIRONMENT,241.
MLA	Ali M.A.,et al."Classification of aerosols over Saudi Arabia from 2004–2016".ATMOSPHERIC ENVIRONMENT 241(2020).