Journal of Environment Pollution and Human Health
ISSN (Print): 2334-3397 ISSN (Online): 2334-3494 Website: https://www.sciepub.com/journal/jephh Editor-in-chief: Dibyendu Banerjee
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Journal of Environment Pollution and Human Health. 2026, 14(2), 40-47
DOI: 10.12691/jephh-14-2-2
Open AccessArticle

Validation of MODIS Terra and Aqua Monthly Aerosol Optical Depth against AERONET Measurements over Dust-Affected Middle Eastern Sites

Yasir E. Mohieldeen1, , Ranya Elsheikh2 and Sarra Ouerghi2

1Independent Researcher, Doha, Qatar

2Department Applied Geography and GIS Program, Department of Humanities, College of Arts and Sciences, Qatar University, Doha, Qatar

Pub. Date: September 19, 2026

Cite this paper:
Yasir E. Mohieldeen, Ranya Elsheikh and Sarra Ouerghi. Validation of MODIS Terra and Aqua Monthly Aerosol Optical Depth against AERONET Measurements over Dust-Affected Middle Eastern Sites. Journal of Environment Pollution and Human Health. 2026; 14(2):40-47. doi: 10.12691/jephh-14-2-2

Abstract

This study evaluates the accuracy of monthly MODIS Terra and Aqua Collection 6.1 Level 3 aerosol optical depth (AOD) products- combining Dark Target and Deep Blue algorithms at 550 nm- against ground-based AERONET Version 3 Level 2 measurements at eight active stations located in and near arid regions. Satellite and AERONET monthly AOD values were compared using linear regression. Results show strong correlations for both platforms: Terra (r = 0.844, R² = 0.712) and Aqua (r = 0.828, R² = 0.685). Both sensors exhibit similar positive biases relative to AERONET (+0.083 for Terra, +0.082 for Aqua), indicating that MODIS tends to overestimate AOD. Terra shows slightly greater overestimation but better captures monthly variability than Aqua. Performance varies notably by station, likely reflecting differences in local aerosol composition, surface reflectance, coastal versus desert heterogeneity, and spatial mismatches between point-based AERONET measurements and MODIS's coarser 1° grid cells. Overall, MODIS monthly AOD products provide valuable data for regional-scale aerosol monitoring in dust-prone Middle Eastern environments. However, the study emphasizes that station-specific calibration and cautious interpretation are necessary when applying coarse-resolution MODIS data to localized dust and air-quality assessments, given the observed spatial variability in accuracy.

Keywords:
MODIS Terra Aqua AERONET aerosol optical depth Monthly AOD

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  Chen, A., et al., Surface albedo regulates aerosol direct climate effect. Nature Communications, 2024. 15(1): p. 7816.
 
[2]  Rezaei-Nokandeh, N., et al., Aerosol optical depth trends and variability over the Middle East from MODIS, MISR, OMI, and AERONET observations. Scientific Reports, 2025. 15(1): p. 41908.
 
[3]  Zhang, Y. and Y. Han, Direct measurement techniques for atmospheric aerosol: Physical properties review. Atmospheric Environment, 2025. 344: p. 121034.
 
[4]  Panda, S., et al., Chemical characterisation of fine aerosols in a smart city on the east coast of India: Seasonal variability and its impact on visibility impairment. Journal of Earth System Science, 2023. 132(1): p. 30.
 
[5]  Wang, Z., et al., Acute health impacts of airborne particles estimated from satellite remote sensing. Environment international, 2013. 51: p. 150-159.
 
[6]  Bilal, M., J.E. Nichol, and M. Nazeer, Validation of Aqua-MODIS C051 and C006 operational aerosol products using AERONET measurements over Pakistan. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015. 9(5): p. 2074-2080.
 
[7]  Ali, M.A. and M. Assiri, Analysis of AOD from MODIS-Merged DT–DB Products Over the Arabian Peninsula: MA Ali, M. Assiri. Earth Systems and Environment, 2019. 3(3): p. 625-636.
 
[8]  Ginoux, P., Prospero, J. M., Gill, T. E., Hsu, N. C., Zhao, M. , Global-scale attribution of anthropogenic and natural dust sources and their emission rates based on MODIS Deep Blue aerosol products. Reviews of Geophysics, 2012. 50.
 
[9]  Farahat, A. Comparative analysis of MODIS, MISR, and AERONET climatology over the Middle East and North Africa. in Annales Geophysicae. 2019. Copernicus Publications Göttingen, Germany.
 
[10]  Basart, S., et al., Aerosol characterization in Northern Africa, Northeastern Atlantic, Mediterranean basin and Middle East from direct-sun AERONET observations. Atmospheric Chemistry and Physics, 2009. 9(21): p. 8265-8282.
 
[11]  El-Nadry, M., et al., Urban health related air quality indicators over the Middle East and North Africa countries using multiple satellites and AERONET data. Remote Sensing, 2019. 11(18): p. 2096.
 
[12]  Farahat, A., et al. Analysis of aerosol absorption properties and transport over North Africa and the Middle East using AERONET data. in Annales Geophysicae. 2016. Copernicus Publications Göttingen, Germany.
 
[13]  Liaqut, A., S. Tariq, and I. Younes, A study on optical properties, classification, and transport of aerosols during the smog period over South Asia using remote sensing. Environmental Science and Pollution Research, 2023. 30(26): p. 69096-69121.
 
[14]  Dash, J. and B.O. Ogutu, Recent advances in space-borne optical remote sensing systems for monitoring global terrestrial ecosystems. Progress in Physical Geography, 2016. 40(2): p. 322-351.
 
[15]  Seidel, F. and C. Popp, Critical surface albedo and its implications to aerosol remote sensing. Atmospheric Measurement Techniques, 2012. 5(7): p. 1653-1665.
 
[16]  Andrews, E., et al., Comparison of AOD, AAOD and column single scattering albedo from AERONET retrievals and in situ profiling measurements. Atmospheric Chemistry and Physics, 2017. 17(9): p. 6041-6072.
 
[17]  Berhane, S.A., et al., A comprehensive analysis of AOD and its species from reanalysis data over the middle east and North Africa regions: Evaluation of model performance using machine learning techniques. Earth Systems and Environment, 2025. 9(4): p. 3683-3708.
 
[18]  Sheel, V., R.P. Guleria, and S. Ramachandran, Global and regional evaluation of a global model simulated AODs with AERONET and MODIS observations. International Journal of Climatology, 2017. 38: p. 269-289.
 
[19]  Omokpariola, D.O., Spatiotemporal analysis of atmospheric aerosols in African environments using MERRA-2 data (1980–2024): Impacts on climate extremes. Iscience, 2025. 28(8).
 
[20]  Xu, H., et al., A consistent aerosol optical depth (AOD) dataset over mainland China by integration of several AOD products. Atmospheric Environment, 2015. 114: p. 48-56.
 
[21]  Bibi, H., et al., Intercomparison of MODIS, MISR, OMI, and CALIPSO aerosol optical depth retrievals for four locations on the Indo-Gangetic plains and validation against AERONET data. Atmospheric Environment, 2015. 111: p. 113-126.
 
[22]  Kahn, R.A., Gaitley, B. J., Martonchik, J. V., Diner, D. J., Crean, K. A., & Holben, B., Multiangle Imaging Spectroradiometer (MISR) global aerosol optical depth validation based on 2 years of coincident Aerosol Robotic Network (AERONET) observations. . Journal of Geophysical Research: Atmospheres, 2005. 110(D10).
 
[23]  Holben, B.N., Eck, T. F., Slutsker, I. A., Tanre, D., Buis, J. P., Setzer, A., ... & Smirnov, A AERONET—A federated instrument network and data archive for aerosol characterization. . Remote sensing of environment, 1998. 1(66): p. 1-16.
 
[24]  Smirnov, A., Holben, B. N., Eck, T. F., Dubovik, O., & Slutsker, I., Cloud-screening and quality control algorithms for the AERONET database. . Remote sensing of environment, 2000. 73(3)(3): p. 337-349.
 
[25]  NASA, MODIS Standard Collection 6.1 Update, in Collection 6.1 (061) Executive Summary, A.D.T.I. Products, Editor. 2026.
 
[26]  Hsu, N.C., Jeong, M. J., Bettenhausen, C., Sayer, A. M., Hansell, R., Seftor, C. S., ... & Tsay, S. C., Enhanced Deep Blue aerosol retrieval algorithm: The second generation. Journal of Geophysical Research: Atmospheres, 2013. 118(16): p. 9296-9315.
 
[27]  Wei, J., et al., Performance of MODIS Collection 6.1 Level 3 aerosol products in spatial-temporal variations over land. Atmospheric Environment, 2019. 206: p. 30-44.
 
[28]  Wang, Y., et al., Evaluation and comparison of MODIS Collection 6.1 aerosol optical depth against AERONET over regions in China with multifarious underlying surfaces. Atmospheric Environment, 2019. 200: p. 280-301.
 
[29]  Wei, J., et al., MODIS Collection 6.1 aerosol optical depth products over land and ocean: validation and comparison. Atmospheric Environment, 2019. 201: p. 428-440.
 
[30]  Virtanen, T.H., Kolmonen, P., Sogacheva, L., Rodríguez, E., Saponaro, G., & de Leeuw, G., Collocation mismatch uncertainties in satellite aerosol retrieval validation. . Atmospheric Measurement Techniques, 2018(11(2)): p. 925 - 938.
 
[31]  Schutgens, N., Tsyro, S., Gryspeerdt, E., Goto, D., Weigum, N., Schulz, M., & Stier, P., On the spatio-temporal representativeness of observations. Atmospheric Chemistry and Physics, 2017. 17(16): p. 9761-9780.