Articles | Volume 12, issue 1
https://doi.org/10.5194/amt-12-607-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-12-607-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Jan 2019
Research article |
| 30 Jan 2019
| 30 Jan 2019
Technical note: Absorption aerosol optical depth components from AERONET observations of mixed dust plumes
Sung-Kyun Shin
School of Physics, Astronomy and Mathematics, University of Hertfordshire, Hatfield, Hertfordshire, UK
Matthias Tesche
School of Physics, Astronomy and Mathematics, University of Hertfordshire, Hatfield, Hertfordshire, UK
Leipzig Institute for Meteorology, Leipzig University, Leipzig, Germany
School of Physics, Astronomy and Mathematics, University of Hertfordshire, Hatfield, Hertfordshire, UK
Youngmin Noh
Department of Environmental Engineering, Pukyong National University, Busan, Republic of Korea
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- Spatio-temporal patterns and trends of the air pollution integrating MERRA-2 and in situ air quality data over Egypt (2013–2021) A. Masoud https://doi.org/10.1007/s11869-023-01357-6
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- Aerosol composition, transport, and radiative impact derived from ground-based and satellite remote sensing in the Central Himalaya P. Singh et al. https://doi.org/10.1016/j.scitotenv.2025.180657
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- Direct radiative forcing of light-absorbing carbonaceous aerosols in China L. Yang et al. https://doi.org/10.1016/j.atmosres.2024.107396
- The role of bulk material production in atmospheric aerosol loading: pathways to sustainable practices M. Alavinasab Ashgezari & G. Nabi Bidhendi https://doi.org/10.1088/2634-4505/ade003
- Climatological aspects of size-resolved column aerosol optical properties over a rural site in the southern peninsular India B. Madhavan et al. https://doi.org/10.1016/j.atmosres.2020.105345
- Global Aerosol Classification Based on Aerosol Robotic Network (AERONET) and Satellite Observation J. Lin et al. https://doi.org/10.3390/rs13061114
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- An AERONET-based methodology to retrieve black carbon light absorption and comparison with MERRA-2 data N. Dehkhoda et al. https://doi.org/10.1016/j.apr.2023.101994
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- Assessment of soiling prediction strategies to improve the accuracy of simulation models for parabolic trough solar thermal power plants J. Vargas-Palomo et al. https://doi.org/10.1016/j.applthermaleng.2026.131546
- Retrieval of Black Carbon Absorption Aerosol Optical Depth from AERONET Observations over the World during 2000–2018 N. Dehkhoda et al. https://doi.org/10.3390/rs14061510
- Evaluation and comparison of MERRA-2 AOD and DAOD with MODIS DeepBlue and AERONET data in Australia Y. Che et al. https://doi.org/10.1016/j.atmosenv.2022.119054
- Classification of aerosols over Saudi Arabia from 2004–2016 M. Ali et al. https://doi.org/10.1016/j.atmosenv.2020.117785
- Spatio-temporal variation of absorbing aerosol over South Africa using satellite measurements N. Onyeuwaoma & V. Sivakumar https://doi.org/10.1080/02786826.2025.2450206
- Remotely sensed BC columns over rapidly changing Western China show significant decreases in mass and inconsistent changes in number, size, and mixing properties due to policy actions Z. Liu et al. https://doi.org/10.1038/s41612-024-00663-9
- 3+2 + X: what is the most useful depolarization input for retrieving microphysical properties of non-spherical particles from lidar measurements using the spheroid model of Dubovik et al. (2006)? M. Tesche et al. https://doi.org/10.5194/amt-12-4421-2019
- Aerosol Optical Depth Measurements from a Simulated Low-Cost Multi-Wavelength Ground-Based Camera: A Clear Case over a Peri-Urban Area V. Boulisset et al. https://doi.org/10.3390/rs16010140
- Composite Aerosol Optical Depth Mapping over Northeast Asia from GEO-LEO Satellite Observations S. Ahn et al. https://doi.org/10.3390/rs13061096
- Assessment of aerosols over five cities of Angola based on MERRA–2 reanalysis data P. Campos et al. https://doi.org/10.1016/j.apr.2022.101569
- A Multi-Wavelength Deep Neural Network Framework for Synergistic Retrieval of AOD, FMF, and AAOD from TROPOMI B. Xu et al. https://doi.org/10.3390/rs18081139
- Wintertime aerosol properties of urban desert region of western India: Implications in regional climate assessment S. Roy et al. https://doi.org/10.1016/j.scitotenv.2023.161473
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Saved (final revised paper)
Latest update: 09 Jun 2026
Short summary
We present a methodology to infer the contribution of mineral dust and non-dust aerosol to the absorbing aerosol optical depth (AAOD) of mixed aerosol layers. The method presents an adaptation of a lidar-based aerosol-type separation technique to passive measurements with AERONET sun photometers by using lidar-specific parameters obtained from the AERONET inversion. The findings on BC-related AAOD are compared to CAMS aerosol reanalysis data with promising results for sites in east Asia.
We present a methodology to infer the contribution of mineral dust and non-dust aerosol to the...
