Retrieval of Long-Term (1980–2024) Time Series of PM10 Concentration by an Empirical Method: The Paris, Cairo, and New Delhi Case Studies

Pluriannual time series of fine particle concentrations suspended in the atmosphere are often lacking. Such data is necessary in evaluating the efficiency of policies aiming to improve air quality in megacities. In this work, a recently developed empirical method is applied over the megacities of Paris, Cairo, and New Delhi. The method utilizes observations of the aerosol optical depth, Angström Exponent, and atmospheric precipitable water as inputs to estimate the PM10. The modeled values validated against their respective reference measurements exhibited the best performance at daily, weekly, and monthly averages when using inputs of the AERONET. When exploiting inputs of the CAMS and MERRA-2 reanalyses, the results were found to be satisfactory with MERRA-2 on the monthly scale. This allows the reconstruction of the variability of the PM10 for the last 45 years. Analysis shows that average annual PM10 concentration has decreased from 40 to 20 µg·m−3 in Paris, increased from 70 to 250 µg·m−3 in New Delhi, and stayed relatively stable (around 100 µg·m−3) in Cairo. Provided that at least one year of PM10 measurements are available to calibrate the empirical method, the method herein is replicable over other megacities around the world.