לוח שנה משולב

Satellite instruments, such as TROPOMI, are routinelyused to quantify tropospheric nitrogen dioxide (NO2)based on its narrowband light absorption in the UV/visible spectral range. The key limitation of suchretrievals is that they can only return the „verticalcolumn density“ (VCD), defined as the integral of theNO2 concentration profile. The profile itself, whichdescribes the vertical distribution of NO2, remainsunknown.This presentation showcases „NitroNet“, the first NO2profile retrieval for TROPOMI. NitroNet is a neuralnetwork, which was trained on synthetic NO2 profilesfrom the regional chemistry and transport model WRFChem,operated on a European domain for the month ofMay 2019. The neural network receives NO2 VCDs fromTROPOMI alongside ancillary variables (meteorology,emission data, etc.) as input, from which it estimates NO2concentration profiles.The talk covers:• an introduction to satellite remote sensing of NO2.• the theoretical underpinnings of NitroNet, how themodel was trained, and how it was validated.• practical new applications that NitroNet enables.