Spatial and seasonal variations of aerosols over China from two decades of multi-satellite observations – Part 1: ATSR (1995–2011) and MODIS C6.1 (2000–2017)

Abstract. Aerosol optical depth (AOD) patterns and interannual and seasonal variations over China are discussed based on the AOD retrieved from the Along-Track Scanning Radiometer (ATSR-2, 1995–2002), the Advanced ATSR (AATSR, 2002–2012) (together ATSR) and the MODerate resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite (2000–2017). The AOD products used were the ATSR Dual View (ADV) v2.31 AOD and the MODIS/Terra Collection 6.1 (C6.1) merged dark target (DT) and deep blue (DB) AOD product. Together these datasets provide an AOD time series for 23 years, from 1995 to 2017. The difference between the AOD values retrieved from ATSR-2 and AATSR is small, as shown by pixel-by-pixel and monthly aggregate comparisons as well as validation results. This allows for the combination of the ATSR-2 and AATSR AOD time series into one dataset without offset correction. ADV and MODIS AOD validation results show similar high correlations with the Aerosol Robotic Network (AERONET) AOD (0.88 and 0.92, respectively), while the corresponding bias is positive for MODIS (0.06) and negative for ADV (−0.07). Validation of the AOD products in similar conditions, when ATSR and MODIS/Terra overpasses are within 90 min of each other and when both ADV and MODIS retrieve AOD around AERONET locations, show that ADV performs better than MODIS in autumn, while MODIS performs slightly better in spring and summer. In winter, both ADV and MODIS underestimate the AERONET AOD. Similar AOD patterns are observed by ADV and MODIS in annual and seasonal aggregates as well as in time series. ADV–MODIS difference maps show that MODIS AOD is generally higher than that from ADV. Both ADV and MODIS show similar seasonal AOD behavior. The AOD maxima shift from spring in the south to summer along the eastern coast further north. The agreement between sensors regarding year-to-year AOD changes is quite good. During the period from 1995 to 2006 AOD increased in the southeast (SE) of China. Between 2006 and 2011 AOD did not change much, showing minor minima in 2008–2009. From 2011 onward AOD decreased in the SE of China. Similar patterns exist in year-to-year ADV and MODIS annual AOD tendencies in the overlapping period. However, regional differences between the ATSR and MODIS AODs are quite large. The consistency between ATSR and MODIS with regards to the AOD tendencies in the overlapping period is rather strong in summer, autumn and overall for the yearly average; however, in winter and spring, when there is a difference in coverage between the two instruments, the agreement between ATSR and MODIS is lower. AOD tendencies in China during the 1995–2017 period will be discussed in more detail in Part 2 (a following paper: Sogacheva et al., 2018), where a method to combine AOD time series from ADV and MODIS is introduced, and combined AOD time series are analyzed.

[1]  J. Chen,et al.  A study of aerosol liquid water content based on hygroscopicity measurements at high relative humidity in the North China Plain , 2014 .

[2]  P. Kolmonen,et al.  Spatial and seasonal variations of aerosols over China from two decades of multi-satellite observations. Part 2: AOD time series for 1995-2017 combined from ATSR ADV and MODIS C6.1 and AOD tendencies estimation , 2018 .

[3]  Zhengqiang Li,et al.  Comprehensive Study of Optical, Physical, Chemical, and Radiative Properties of Total Columnar Atmospheric Aerosols over China: An Overview of Sun-Sky Radiometer Observation Network (SONET) Measurements , 2017 .

[4]  Michael D. King,et al.  Aerosol properties over bright-reflecting source regions , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Yong Xue,et al.  Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns , 2018 .

[6]  L. Remer,et al.  The Collection 6 MODIS aerosol products over land and ocean , 2013 .

[7]  H. Liao,et al.  Increases in aerosol concentrations over eastern China due to the decadal‐scale weakening of the East Asian summer monsoon , 2012 .

[8]  Robert C. Levy,et al.  MODIS Collection 6 aerosol products: Comparison between Aqua's e‐Deep Blue, Dark Target, and “merged” data sets, and usage recommendations , 2014 .

[9]  P. Thai,et al.  A review of biomass burning: Emissions and impacts on air quality, health and climate in China. , 2017, The Science of the total environment.

[10]  D. Winker,et al.  Overview of the CALIPSO Mission and CALIOP Data Processing Algorithms , 2009 .

[11]  M. Brewer.  Statistical Methods for Trend Detection and Analysis in Environmental Sciences ‐ edited by Chandler, R.E. & Marian Scott, E. , 2014 .

[12]  Zhanqing Li,et al.  Seasonal variations in aerosol optical properties over China , 2008 .

[13]  G. Brasseur,et al.  Air Pollution in Eastern Asia: An Integrated Perspective , 2017 .

[14]  Kostas Kourtidis,et al.  Space-borne observations of aerosol - cloud relations for cloud systems of different heights , 2017 .

[15]  Edith Rodriguez,et al.  Collocation mismatch uncertainties in satellite aerosol retrieval validation , 2017 .

[16]  G. Leeuw,et al.  Post-processing to remove residual clouds from aerosol optical depth retrieved using the Advanced Along Track Scanning Radiometer , 2016 .

[17]  Gerrit de Leeuw,et al.  Retrieval of aerosol optical depth over land using two‐angle view satellite radiometry during TARFOX , 1998 .

[18]  Xin Qian,et al.  A high-resolution inventory of air pollutant emissions from crop residue burning in China , 2018, Atmospheric Environment.

[19]  Michael J. Garay,et al.  Decadal-scale trends in regional aerosol particle properties and their linkage to emission changes , 2017 .

[20]  Zhipeng Wang,et al.  Development and Implementation of an Electronic Crosstalk Correction for Bands 27-30 in Terra MODIS Collection 6 , 2017, Remote. Sens..

[21]  Gerrit de Leeuw,et al.  The ADV/ASV AATSR aerosol retrieval algorithm: current status and presentation of a full-mission AOD dataset , 2016, Int. J. Digit. Earth.

[22]  Andreas Richter,et al.  Anthropogenic Sulphur Dioxide Load over China as Observed from Different Satellite Sensors , 2016 .

[23]  John P. Burrows,et al.  Remote sensing of aerosols over snow using infrared AATSR observations , 2011 .

[24]  Jin Huang,et al.  Enhanced Deep Blue aerosol retrieval algorithm: The second generation , 2013 .

[25]  Richard E. Chandler,et al.  Statistical Methods for Trend Detection and Analysis in the Environmental Sciences , 2011 .

[26]  Jianping Huang,et al.  Comparison of dust emissions, transport, and deposition between the Taklimakan Desert and Gobi Desert from 2007 to 2011 , 2017, Science China Earth Sciences.

[27]  H. Linderholm,et al.  Rain-season trends in precipitation and their effect in different climate regions of China during 1961–2008 , 2011 .

[28]  J. Quaas,et al.  How can aerosols affect the Asian summer monsoon ? Assessment during three consecutive pre-monsoon seasons from CALIPSO satellite data. , 2010 .

[29]  Junying Sun,et al.  Observations of relative humidity effects on aerosol light scattering in the Yangtze River Delta of China , 2015 .

[30]  Xiangao Xia,et al.  Ground-based aerosol climatology of China: aerosol optical depths from the China Aerosol Remote Sensing Network (CARSNET) 2002–2013 , 2015 .

[31]  Henrik Andersson,et al.  Environmental Research and Public Health Air Pollution Control Policies in China: a Retrospective and Prospects , 2022 .

[32]  Yuxiang Luo,et al.  A climatology of aerosol optical depth over China from recent 10 years of MODIS remote sensing data , 2014 .

[33]  Li Du,et al.  Spatial distribution, seasonal variation and regionalization of PM2.5 concentrations in China , 2015, Science China Chemistry.

[34]  Zhaoyan Liu,et al.  Asian dust transported one full circuit around the globe , 2009 .

[35]  Jiming Hao,et al.  Verification of anthropogenic emissions of China by satellite and ground observations , 2011 .

[36]  X. Dai,et al.  Trends and Variability in Aerosol Optical Depth over North China from MODIS C6 Aerosol Products during 2001–2016 , 2017 .

[37]  A. Smirnov,et al.  AERONET-a federated instrument network and data archive for aerosol Characterization , 1998 .

[38]  Eleni Marinou,et al.  Nine-year spatial and temporal evolution of desert dust aerosols over South and East Asia as revealed by CALIOP , 2017 .

[39]  Xin Wang,et al.  Variability of East Asia dust events and their long-term trend , 2008 .

[40]  Nicolas Theys,et al.  Cleaning up the air: effectiveness of air quality policy for SO 2 and NO x emissions in China , 2016 .

[41]  Jeffrey S. Reid,et al.  Has China been exporting less particulate air pollution over the past decade? , 2017 .

[42]  Tao Song,et al.  The Campaign on Atmospheric Aerosol Research Network of China: CARE-China , 2015 .

[43]  W. Paul Menzel,et al.  Improvements to Terra MODIS L1B, L2, and L3 science products through using crosstalk corrected L1B radiances , 2017, Optical Engineering + Applications.

[44]  Aristeidis K. Georgoulias,et al.  A study of the impact of synoptic weather conditions and water vapor on aerosol–cloud relationships over major urban clusters of China , 2015 .

[45]  G. Leeuw,et al.  Two decades of satellite observations of AOD over mainland China , 2017 .