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This research article compares various regression methods for estimating surface nitrogen dioxide (NO2) concentrations using satellite data, specifically from the TROPOMI instrument. The study finds that multivariate linear regression with Anscombe-transformed inputs provides the best agreement with surface measurements, achieving a cross-validation R2 of 0.77 across the continental U.S. The results highlight the potential for using satellite data to accurately quantify surface NO2, which is crucial for ass

Author

christian kapta

Language

EN