scholarly journals Multi-Time Scale Analysis of Regional Aerosol Optical Depth Changes in National-Level Urban Agglomerations in China Using Modis Collection 6.1 Datasets from 2001 to 2017

2019 ◽  
Vol 11 (2) ◽  
pp. 201 ◽  
Author(s):  
Lei Zhang ◽  
Ming Zhang ◽  
Yibin Yao
Keyword(s):  
Time Series ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Time Scale ◽  
Yangtze River ◽  
National Level ◽  
River Delta ◽  
Urban Agglomerations ◽  
Spatial And Temporal Changes

With the rapid development of China’s economy and industry, characterizing the spatial and temporal changes of aerosols in China has attracted widespread attention from researchers. The national-level urban agglomerations are the most concentrated areas of China’s economic, population and resource. Studying the spatial and temporal changes of aerosol optical depth (AOD) in these regions has practical guiding significance for effective monitoring of atmospheric particulate pollution. This paper analyzed the spatial and temporal variations of AOD in China’s urban agglomerations during 2001–2017 by using Terra Moderate resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1) Level 2 aerosol products (MOD04_L2). Five national-level urban agglomerations were chosen: Yangtze River Delta (YRD), Pearl River Delta (PRD), Beijing-Tianjin-Hebei (BTH), Yangtze River Middle-Reach (YRMR) and Cheng-Yu (CY). We analyzed the change patterns of AOD in different urban agglomerations at multi-time scales and built a time series decomposition model to mine the long-term trend, seasonal variation and abnormal change information of AOD time series. The result indicated that averaged AOD values in the five urban agglomerations were basically increased first and then decreased at the annual time scale during 2001–2017. The averaged AOD showed strong seasonal differences and AOD values in spring and summer were typically higher than those in autumn and winter. At the monthly time scale, the AOD typically varied from low in cold months to high in warm months and then decreased during the rainy periods. Time series decompositions revealed that a notable transition around 2007–2008 dominated the long-term overall trend over the five selected urban agglomerations and an initial upward tendency followed by a downward tendency was observed during 2001–2017. This study can be utilized to provide decision-making basis for atmospheric environmental governance and future development of urban agglomerations.

scholarly journals Retrieval of Aerosol Optical Depth Based on MODIS

2020 ◽  
Vol 206 ◽  
pp. 02018
Author(s):  
Jie Lv ◽  
Xianglai Mao
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Yangtze River ◽  
Global Climate ◽  
National Level ◽  
Atmospheric Correction ◽  
The Yangtze River ◽  
Rapid Urbanization ◽  
Climate Effect ◽  
Urban Agglomerations

Aerosol plays an important role in global climate effect, and Aerosol Optical Depth (AOD), as one of its important parameters, can not only monitor the turbidity of the atmosphere, but also is an important index of atmospheric correction quality in remote sensing. Urban agglomeration in the middle reaches of the Yangtze River is a key national-level urban agglomerations in China, and its rapid urbanization leads to the aggravation of urban diseases such as disorderly development of cities, waste of resources and environmental pollution, and the research on ecological environment problems of urban agglomerations is also the current key project.In view of the above problems, this paper studies the AOD inversion and its spatial and temporal distribution in the middle reaches of the Yangtze River, in order to provide important scientific materials for environmental monitoring and satellite atmospheric correction quality inspection.

scholarly journals Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks

2016 ◽  
Vol 9 (1) ◽  
pp. 53-62 ◽  
Author(s):  
R. D. García ◽  
O. E. García ◽  
E. Cuevas ◽  
V. E. Cachorro ◽  
A. Barreto ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Artificial Neural Networks ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Mineral Dust ◽  
Dust Particles ◽  
Filter Radiometer ◽  
Artificial Neural

Abstract. This paper presents the reconstruction of a 73-year time series of the aerosol optical depth (AOD) at 500 nm at the subtropical high-mountain Izaña Atmospheric Observatory (IZO) located in Tenerife (Canary Islands, Spain). For this purpose, we have combined AOD estimates from artificial neural networks (ANNs) from 1941 to 2001 and AOD measurements directly obtained with a Precision Filter Radiometer (PFR) between 2003 and 2013. The analysis is limited to summer months (July–August–September), when the largest aerosol load is observed at IZO (Saharan mineral dust particles). The ANN AOD time series has been comprehensively validated against coincident AOD measurements performed with a solar spectrometer Mark-I (1984–2009) and AERONET (AErosol RObotic NETwork) CIMEL photometers (2004–2009) at IZO, obtaining a rather good agreement on a daily basis: Pearson coefficient, R, of 0.97 between AERONET and ANN AOD, and 0.93 between Mark-I and ANN AOD estimates. In addition, we have analysed the long-term consistency between ANN AOD time series and long-term meteorological records identifying Saharan mineral dust events at IZO (synoptical observations and local wind records). Both analyses provide consistent results, with correlations  >  85 %. Therefore, we can conclude that the reconstructed AOD time series captures well the AOD variations and dust-laden Saharan air mass outbreaks on short-term and long-term timescales and, thus, it is suitable to be used in climate analysis.

scholarly journals Columnar Aerosol Optical Property Characterization and Aerosol Typing Based on Ground-Based Observations in a Rural Site in the Central Yangtze River Delta Region

2022 ◽  
Vol 14 (2) ◽  
pp. 406
Author(s):  
Yong Xie ◽  
Yi Su ◽  
Xingfa Gu ◽  
Tiexi Chen ◽  
Wen Shao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
Central China ◽  
Rural Site ◽  
Classification Methods ◽  
Aerosol Classification

Accurate and updated aerosol optical properties (AOPs) are of vital importance to climatology and environment-related studies for assessing the radiative impact of natural and anthropogenic aerosols. We comprehensively studied the columnar AOP observations between January 2019 and July 2020 from a ground-based remote sensing instrument located at a rural site operated by Central China Comprehensive Experimental Sites in the center of the Yangtze River Delta (YRD) region. In order to further study the aerosol type, two threshold-based aerosol classification methods were used to investigate the potential categories of aerosol particles under different aerosol loadings. Based on AOP observation and classification results, the potential relationships between the above-mentioned results and meteorological factors (i.e., humidity) and long-range transportation processes were analyzed. According to the results, obvious variation in aerosol optical depth (AOD) during the daytime, as well as throughout the year, was revealed. Investigation into AOD, single-scattering albedo (SSA), and absorption aerosol optical depth (AAOD) revealed the dominance of fine-mode aerosols with low absorptivity. According to the results of the two aerosol classification methods, the dominant aerosol types were continental (accounting for 43.9%, method A) and non-absorbing aerosols (62.5%, method B). Longer term columnar AOP observations using remote sensing alongside other techniques in the rural areas in East China are still needed for accurate parameterization in the future.

scholarly journals Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks

2015 ◽  
Vol 8 (9) ◽  
pp. 9075-9103 ◽  
Author(s):  
R. D. García ◽  
O. E. García ◽  
E. Cuevas ◽  
V. E. Cachorro ◽  
A. Barreto ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Artificial Neural Networks ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Mineral Dust ◽  
Dust Particles ◽  
Filter Radiometer ◽  
Artificial Neural

Abstract. This paper presents the reconstruction of the 73 year time series of the aerosol optical depth (AOD) at 500 nm at the subtropical high-mountain Izaña Atmospheric Observatory (IZO) located in Tenerife (Canary Islands, Spain). For this purpose, we have combined AOD estimates from artificial neural networks (ANNs) from 1941 to 2001 and AOD measurements directly obtained with a Precision Filter Radiometer (PFR) between 2003 and 2013. The analysis is limited to summer months (July–August–September), when the largest aerosol load is observed at IZO (Saharan mineral dust particles). The ANN AOD time series has been comprehensively validated against coincident AOD measurements performed with a solar spectrometer Mark-I (1984–2009) and AERONET (AErosol RObotic NETwork) CIMEL photometers (2004–2009) at IZO, obtaining a rather good agreement on a daily basis: Pearson coefficient, R, of 0.97 between AERONET and ANN AOD, and 0.93 between Mark-I and ANN AOD estimates. In addition, we have analyzed the long-term consistency between ANN AOD time series and long-term meteorological records identifying Saharan mineral dust events at IZO (synoptical observations and local wind records). Both analyses provide consistent results, with correlations larger than 85 %. Therefore, we can conclude the reconstructed AOD time series captures well the AOD variations and dust-laden Saharan air mass outbreaks at short-term and long-term time scales and, thus, it is suitable to be used in climate analysis.

scholarly journals Retrieval of aerosol optical depth over land surfaces from AVHRR data

2013 ◽  
Vol 6 (1) ◽  
pp. 2227-2251 ◽  
Author(s):  
L. Mei ◽  
Y. Xue ◽  
A. A. Kokhanovsky ◽  
W. von Hoyningen-Huene ◽  
G. de Leeuw ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Reflectance ◽  
Aerosol Retrieval ◽  
Avhrr Data ◽  
Land Surfaces ◽  
Very High

Abstract. The Advanced Very High Resolution Radiometer (AVHRR) radiance data provide a global, long-term, consistent time series having high spectral and spatial resolution and thus being valuable for the retrieval of surface spectral reflectance, albedo and surface temperature. Long term time series of such data products are necessary for studies addressing climate change, sea ice distribution and movement, and ice sheet coastal configuration. These data have also been used to retrieve aerosol properties over ocean and land surfaces. However, the retrieval of aerosol over land and land surface albedo are challenging because of the information content of the measurement is limited and the inversion of these data products being ill defined. Solving the radiative transfer equations requires additional information and knowledge to reduce the number of unknowns. In this contribution we utilise an empirical linear relationship between the surface reflectances in the AVHRR channels at wavelengths of 3.75 μm and 2.1 μm, which has been identified in Moderate Resolution Imaging Spectroradiometer (MODIS) data. Next, following the MODIS dark target approach, the surface reflectance at 0.64 μm was obtained. The comparison of the estimated surface reflectance at 0.64 μm with MODIS reflectance products (MOD09) shows a strong correlation (R = 0.7835). Once this was established, the MODIS "dark-target" aerosol retrieval method was adapted to Advanced Very High Resolution Radiometer (AVHRR) data. A simplified Look-Up Table (LUT) method, adopted from Bremen AErosol Retrieval (BAER) algorithm, was used in the retrieval. The Aerosol Optical Depth (AOD) values retrieved from AVHRR with this method compare favourably with ground-based measurements, with a correlation coefficient R = 0.861 and Root Mean Square Error (RMSE) = 0.17. This method can be easily applied to other satellite instruments which do not have a 2.1 μm channel, such as those currently planned to geostationary satellites.

scholarly journals Retrieval of aerosol optical depth over land surfaces from AVHRR data

2014 ◽  
Vol 7 (8) ◽  
pp. 2411-2420 ◽  
Author(s):  
L. L. Mei ◽  
Y. Xue ◽  
A. A. Kokhanovsky ◽  
W. von Hoyningen-Huene ◽  
G. de Leeuw ◽  
...  
Keyword(s):  
Time Series ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Limited Information ◽  
Additional Information ◽  
Aerosol Retrieval ◽  
Avhrr Data ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Land Surfaces

Abstract. The Advanced Very High Resolution Radiometer (AVHRR) provides a global, long-term, consistent time series of radiance data in several wavebands which are used for the retrieval of surface spectral reflectance, albedo and surface temperature. Long-term time series of such data products are necessary for studies addressing climate change, sea ice distribution and movement, and ice sheet coastal configuration. AVHRR radiances have also been used to retrieve aerosol properties over ocean and land surfaces. However, the retrieval of aerosol over land is challenging because of the limited information content in the data which renders the inversion problem ill defined. Solving the radiative transfer equations requires additional information to reduce the number of unknowns. In this contribution we utilise an empirical linear relationship between the surface reflectances in the AVHRR channels at wavelengths of 3.75 μm and 2.1 μm, which has been identified in the Moderate Resolution Imaging Spectroradiometer (MODIS) data. Following the MODIS dark target approach, this relationship is used to obtain the surface reflectance at 0.64 μm. The comparison of the estimated surface reflectances with MODIS reflectance products (MOD09) shows a strong correlation. Once this was established, the MODIS "dark-target" aerosol retrieval method was adapted to AVHRR data. A simplified look-up table (LUT) method, adopted from the Bremen AErosol Retrieval (BAER) algorithm, was used in the retrieval. The aerosol optical depth (AOD) values retrieved from AVHRR with this method compare favourably with ground-based measurements, with 71.8% of the points located within ±(0.1 + 0.15τ) (τ is the AOD) of the identity line. This method can be easily applied to other satellite instruments which do not have a 2.1 μm channel, such as those currently planned to be used on geostationary satellites.

Variation in MERRA-2 aerosol optical depth over the Yangtze River Delta from 1980 to 2016

2018 ◽  
Vol 136 (1-2) ◽  
pp. 363-375 ◽  
Author(s):  
Enwei Sun ◽  
Huizheng Che ◽  
Xiaofeng Xu ◽  
Zhenzhu Wang ◽  
Chunsong Lu ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
The Yangtze River Delta

scholarly journals Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta During the 2014–2017 Period

2019 ◽  
Vol 16 (19) ◽  
pp. 3522 ◽  
Author(s):  
Cheng ◽  
Li ◽  
Chen ◽  
Hu ◽  
Yuan ◽  
...  
Keyword(s):  
Linear Regression ◽  
Aerosol Optical Depth ◽  
Influencing Factors ◽  
Optical Depth ◽  
Yangtze River ◽  
Geographical Area ◽  
Yangtze River Delta ◽  
River Delta ◽  
Spatiotemporal Variability ◽  
Spatial Coverage

Large amounts of aerosol particles suspended in the atmosphere pose a serious challenge to the climate and human health. In this study, we produced a dataset through merging the Moderate Resolution Imaging Spectrometers (MODIS) Collection 6.1 3-km resolution Dark Target aerosol optical depth (DT AOD) with the 10-km resolution Deep Blue aerosol optical depth (DB AOD) data by linear regression and made use of it to unravel the spatiotemporal characteristics of aerosols over the Pan Yangtze River Delta (PYRD) region from 2014 to 2017. Then, the geographical detector method and multiple linear regression analysis were employed to investigate the contributions of influencing factors. Results indicate that: (1) compared to the original Terra DT and Aqua DT AOD data, the average daily spatial coverage of the merged AOD data increased by 94% and 132%, respectively; (2) the values of four-year average AOD were high in the north-east and low in the south-west of the PYRD; (3) the annual average AOD showed a decreasing trend from 2014 to 2017 while the seasonal average AOD reached its maximum in spring; and that (4) Digital Elevation Model (DEM) and slope contributed most to the spatial distribution of AOD, followed by precipitation and population density. Our study highlights the spatiotemporal variability of aerosol optical depth and the contributions of different factors over this large geographical area in the four-year period, and can, therefore, provide useful insights into the air pollution control for decision makers.

Sign in / Sign up

Export Citation Format

Share Document