Spatial and seasonal variations of MODIS aerosol optical depth in East China during 2000-2012

2013 ◽  
Author(s):  
Tianyong Zhai ◽  
Qing Zhao ◽  
Runhe Shi ◽  
Wei Gao
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Seasonal Variations ◽  
East China

scholarly journals Estimating ground-level PM<sub>2.5</sub> in Eastern China using aerosol optical depth determined from the GOCI Satellite Instrument

2015 ◽  
Vol 15 (12) ◽  
pp. 17251-17281 ◽  
Author(s):  
J. Xu ◽  
R. V. Martin ◽  
A. van Donkelaar ◽  
J. Kim ◽  
M. Choi ◽  
...  
Keyword(s):  
Organic Matter ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Eastern China ◽  
Ground Level ◽  
East China ◽  
Chemical Transport Model ◽  
Near Surface ◽  
Significant Agreement

Abstract. We determine and interpret fine particulate matter (PM2.5) concentrations in East China for January to December 2013 at a horizontal resolution of 6 km from aerosol optical depth (AOD) retrieved from the Korean Geostationary Ocean Color Imager (GOCI) satellite instrument. We implement a set of filters to minimize cloud contamination in GOCI AOD. Evaluation of filtered GOCI AOD with AOD from the Aerosol Robotic Network (AERONET) indicates significant agreement with mean fractional bias (MFB) in Beijing of 6.7 % and northern Taiwan of −1.2 %. We use a global chemical transport model (GEOS-Chem) to relate the total column AOD to the near-surface PM2.5. The simulated PM2.5/AOD ratio exhibits high consistency with ground-based measurements (MFB = −0.52–8.0 %). We evaluate the satellite-derived PM2.5 vs. the ground-level PM2.5 in 2013 measured by the China Environmental Monitoring Center. Significant agreement is found between GOCI-derived PM2.5 and in-situ observations in both annual averages (r = 0.81, N = 494) and monthly averages (MFB = 13.1 %), indicating GOCI provides valuable data for air quality studies in Northeast Asia. The GEOS-Chem simulated chemical speciation of GOCI-derived PM2.5 reveals that secondary inorganics (SO42−, NO3−, NH4+) and organic matter are the most significant components. Biofuel emissions in northern China for heating are responsible for an increase in the concentration of organic matter in winter. The population-weighted GOCI-derived PM2.5 over East China for 2013 is 53.8 μg m−3, threatening the health and life expectancy of its 600 million residents.

scholarly journals Retrieval of the Fine-Mode Aerosol Optical Depth over East China Using a Grouped Residual Error Sorting (GRES) Method from Multi-Angle and Polarized Satellite Data

2018 ◽  
Vol 10 (11) ◽  
pp. 1838 ◽  
Author(s):  
Yang Zhang ◽  
Zhengqiang Li ◽  
Zhihong Liu ◽  
Juan Zhang ◽  
Lili Qie ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Residual Error ◽  
East China ◽  
Anthropogenic Aerosols ◽  
Aerosol Model ◽  
Retrieval Accuracy ◽  
Aerosol Loading ◽  
Fine Mode ◽  
Fine Mode Aerosol

The fine-mode aerosol optical depth (AODf) is an important parameter for the environment and climate change study, which mainly represents the anthropogenic aerosols component. The Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar (PARASOL) instrument can detect polarized signal from multi-angle observation and the polarized signal mainly comes from the radiation contribution of the fine-mode aerosols, which provides an opportunity to obtain AODf directly. However, the currently operational algorithm of Laboratoire d’Optique Atmosphérique (LOA) has a poor AODf retrieval accuracy over East China on high aerosol loading days. This study focused on solving this issue and proposed a grouped residual error sorting (GRES) method to determine the optimal aerosol model in AODf retrieval using the traditional look-up table (LUT) approach and then the AODf retrieval accuracy over East China was improved. The comparisons between the GRES retrieved and the Aerosol Robotic Network (AERONET) ground-based AODf at Beijing, Xianghe, Taihu and Hong_Kong_PolyU sites produced high correlation coefficients (r) of 0.900, 0.933, 0.957 and 0.968, respectively. The comparisons of the GRES retrieved AODf and PARASOL AODf product with those of the AERONET observations produced a mean absolute error (MAE) of 0.054 versus 0.104 on high aerosol loading days (AERONET mean AODf at 865 nm = 0.283). An application using the GRES method for total AOD (AODt) retrieval also showed a good expandability for multi-angle aerosol retrieval of this method.

Aerosol optical depth and its seasonal variations in Kwangju

2001 ◽  
Author(s):  
Young J. Kim ◽  
Seong-yun Ryu ◽  
Jeong-hye Kim ◽  
Jeong E. Kim
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Seasonal Variations

scholarly journals Merging aerosol optical depth data from multiple satellite missions to view agricultural biomass burning in Central and East China

2012 ◽  
Vol 12 (4) ◽  
pp. 10461-10492 ◽  
Author(s):  
Y. Xue ◽  
H. Xu ◽  
L. Mei ◽  
J. Guang ◽  
J. Guo ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Biomass Burning ◽  
Meteorological Data ◽  
Temporal Distribution ◽  
East China ◽  
Agricultural Biomass ◽  
Spatial Coverage ◽  
Modis Aod ◽  
Single Sensor

Abstract. Agricultural biomass burning (ABB) in Central and East China occurs every year from May to October and peaks in June. The biomass burning event in June 2007 was very strong. During the period from 26 May to 16 June 2007, ABB occurred mainly in Anhui, Henan, Jiangsu and Shandong provinces. A comprehensive set of aerosol optical depth (AOD) data, produced by a merger of AOD product data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging Spectroradiometer (MIRS), is used to study the spatial and temporal distribution of agricultural biomass aerosols in Central and East China combining with ground observations from both AErosol RObotic NETwork (AERONET) and China Aerosol Remote Sensing NETwork (CARSNET) measurements. We compared merged AOD data with single-sensor single-algorithm AOD data (MODIS Dark Target AOD data, MODIS Deep Blue AOD data, SRAP-MODIS AOD data and MISR AOD data). In this comparison, we found merged AOD products can improve the quality of AOD products from single-sensor single-algorithm data sets by expanding the spatial coverage of the study area and keeping the statistical confidence in AOD parameters. There existed high correlation (0.8479) between the merged AOD data and AERONET measurements. Our merged AOD data make use of synergetic information conveyed in all of the available satellite data. The merged AOD data were used for the analysis of the biomass burning event from 26 May to 16 June 2007 together with meteorological data. The merged AOD products and the ground observations from China suggest that biomass burning in Central and East China has had great impact on AOD over China. Influenced by this ABB, the highest AOD value in Beijing on 12 June 2007 reached 5.71.

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