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Wang D, Zhang F, Yang S, Xia N, Ariken M. Exploring the spatial-temporal characteristics of the aerosol optical depth (AOD) in Central Asia based on the moderate resolution imaging spectroradiometer (MODIS). ENVIRONMENTAL MONITORING AND ASSESSMENT 2020; 192:383. [PMID: 32436044 DOI: 10.1007/s10661-020-08299-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 04/14/2020] [Indexed: 06/11/2023]
Abstract
Central Asia has become a key node of the belt and road corridor. It is located in arid and semi-arid climate regions, and it is a region where the contribution of global aerosols of sand and dust is continuous. However, few studies have been conducted on the Central Asian aerosol optical depth. Therefore, this paper relied on the belt and road sustainable development dataset to analyze the spatial-temporal variations in the AOD in Central Asia and provide spatial-temporal characteristics of the AOD for environmental services. We analyzed the spatial and temporal variation in the aerosol optical depth (AOD) in Central Asia by using MODIS/AQUA C6 MYD08_M3 images from 2008 to 2017. The results showed that (1) the annual average AOD in Central Asia in the past decade varied from 0.183 to 0.232, which indicated a slow decline starting in 2014. The percentage of average annual decline was approximately 0.18%, and the regular distinct revealed the distribution characteristics of AOD. In different years, the Central Asian region exhibited the similar monthly change characteristics: from July to December, the AOD decreased, and from December to February, it increased. In different seasons, the Central Asian region exhibited the different seasonal change characteristics: the AOD value was higher in the spring and summer. The mean values in the spring, summer, autumn, and winter were 0.273, 0.240, 0.155, and 0.183, respectively, and the standard deviations were 0.036, 0.038, 0.025, and 0.048, respectively. (3) Based on spatial distribution characteristics, the Tarim Basin, Aral Sea region, and Ebinur Lake area were high value areas, and Kazakhstan was a low value area. The AOD of the surrounding area of the Aral Sea had increased in the last 5 years, while that of Kazakhstan, Uzbekistan, and Turkmenistan had decreased. The AOD of the Taklamakan area exhibited an inter-annual change. Sand dust aerosols were the largest contributors to the AOD in the Taklamakan area. The rising trend of the AOD in the Aral Sea area was clear, with an average annual increase of 0.234%, and the contribution of salt dust aerosols to the AOD increased. The average annual AOD in the Ebinur Lake area remained stable.
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Affiliation(s)
- Di Wang
- Key Laboratory of Smart City and Environmental Modeling of Higher Education Institute, College of Resources and Environment Sciences, Xinjiang University, Urumqi, 830046, People's Republic of China
- Key Laboratory of Oasis Ecology, Urumqi, 830046, China
| | - Fei Zhang
- Key Laboratory of Smart City and Environmental Modeling of Higher Education Institute, College of Resources and Environment Sciences, Xinjiang University, Urumqi, 830046, People's Republic of China.
- Key Laboratory of Oasis Ecology, Urumqi, 830046, China.
- Engineering research center of Central Asia Geoinformation development and utilization, National administration of surveying, Mapping and Geoinformation, Urumqi, 8300464, China.
| | - Shengtian Yang
- State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing, China
| | - Nan Xia
- Key Laboratory of Smart City and Environmental Modeling of Higher Education Institute, College of Resources and Environment Sciences, Xinjiang University, Urumqi, 830046, People's Republic of China
- Key Laboratory of Oasis Ecology, Urumqi, 830046, China
| | - Muhadaisi Ariken
- Key Laboratory of Smart City and Environmental Modeling of Higher Education Institute, College of Resources and Environment Sciences, Xinjiang University, Urumqi, 830046, People's Republic of China
- Key Laboratory of Oasis Ecology, Urumqi, 830046, China
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Lin M, Fiore AM, Horowitz LW, Cooper OR, Naik V, Holloway J, Johnson BJ, Middlebrook AM, Oltmans SJ, Pollack IB, Ryerson TB, Warner JX, Wiedinmyer C, Wilson J, Wyman B. Transport of Asian ozone pollution into surface air over the western United States in spring. ACTA ACUST UNITED AC 2012. [DOI: 10.1029/2011jd016961] [Citation(s) in RCA: 201] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Yang ES, Christopher SA, Kondragunta S, Zhang X. Use of hourly Geostationary Operational Environmental Satellite (GOES) fire emissions in a Community Multiscale Air Quality (CMAQ) model for improving surface particulate matter predictions. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2010jd014482] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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McMillan WW, Pierce RB, Sparling LC, Osterman G, McCann K, Fischer ML, Rappenglück B, Newsom R, Turner D, Kittaka C, Evans K, Biraud S, Lefer B, Andrews A, Oltmans S. An observational and modeling strategy to investigate the impact of remote sources on local air quality: A Houston, Texas, case study from the Second Texas Air Quality Study (TexAQS II). ACTA ACUST UNITED AC 2010. [DOI: 10.1029/2009jd011973] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Pisso I, Real E, Law KS, Legras B, Bousserez N, Attié JL, Schlager H. Estimation of mixing in the troposphere from Lagrangian trace gas reconstructions during long-range pollution plume transport. ACTA ACUST UNITED AC 2009. [DOI: 10.1029/2008jd011289] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Hoff RM, Christopher SA. Remote sensing of particulate pollution from space: have we reached the promised land? JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2009. [PMID: 19603734 DOI: 10.3155/1047-3289.59.6.645] [Citation(s) in RCA: 144] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The recent literature on satellite remote sensing of air quality is reviewed. 2009 is the 50th anniversary of the first satellite atmospheric observations. For the first 40 of those years, atmospheric composition measurements, meteorology, and atmospheric structure and dynamics dominated the missions launched. Since 1995, 42 instruments relevant to air quality measurements have been put into orbit. Trace gases such as ozone, nitric oxide, nitrogen dioxide, water, oxygen/tetraoxygen, bromine oxide, sulfur dioxide, formaldehyde, glyoxal, chlorine dioxide, chlorine monoxide, and nitrate radical have been measured in the stratosphere and troposphere in column measurements. Aerosol optical depth (AOD) is a focus of this review and a significant body of literature exists that shows that ground-level fine particulate matter (PM2.5) can be estimated from columnar AOD. Precision of the measurement of AOD is +/-20% and the prediction of PM2.5 from AOD is order +/-30% in the most careful studies. The air quality needs that can use such predictions are examined. Satellite measurements are important to event detection, transport and model prediction, and emission estimation. It is suggested that ground-based measurements, models, and satellite measurements should be viewed as a system, each component of which is necessary to better understand air quality.
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Affiliation(s)
- Raymond M Hoff
- Department of Physics and the Joint Center for Earth Systems Technology/Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, MD 21250, USA.
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