Feasibility of robust estimates of ozone production rates using a synergy of satellite observations, ground-based remote sensing, and models

Abstract

Ozone pollution is secondarily produced through a complex, non-linear chemical process. Our understanding of the spatiotemporal variations in photochemically produced ozone (i.e., PO₃) is limited to sparse aircraft campaigns and chemical transport models, which often carry significant biases. Hence, we present a novel satellite-derived PO₃ product informed by bias-corrected TROPOspheric Monitoring Instrument (TROPOMI) HCHO, NO₂, surface albedo data, and various models. These data are integrated into a parameterization that relies on HCHO, NO₂, HCHO / NO₂, jNO₂, and jO¹D. Despite its simplicity, it can reproduce ∼ 90 % of the variance in observationally constrained PO₃, with minimal biases in moderately to highly polluted regions. We map PO₃ across various regions with respect to July 2019 at a 0.1° × 0.1° spatial resolution, revealing accelerated values (> 8 ppbv h⁻¹) for numerous cities throughout Asia and the Middle East, resulting from elevated ozone precursors and enhanced photochemistry. In Europe and the United States, such high levels are only detected over Benelux, Los Angeles, and New York City. PO₃ maxima are observed in various seasons and are attributed to changes in photolysis rates, non-linear ozone chemistry, and fluctuations in HCHO and NO₂. Satellite errors result in moderate errors (10 %–20 %) in PO₃ estimates over cities on a monthly average basis, while these errors exceed 50 % in clean areas and under low light conditions. Using the current algorithm, we demonstrate that satellite data can provide valuable information for robust PO₃ estimation. This capability expands future research through the application of data to address significant scientific questions about locally produced ozone hotspots, seasonality, and long-term trends.