Mapping the spatial distribution of NO<sub>2</sub> with in situ and remote sensing instruments during the Munich NO<sub>2</sub> imaging campaign

Abstract

Abstract. We present results from the Munich Nitrogen dioxide (NO2) Imaging Campaign (MuNIC), where NO2 near-surface concentrations (NSCs) and vertical column densities (VCDs) were measured with stationary, mobile, and airborne in situ and remote sensing instruments in Munich, Germany. The most intensive day of the campaign was 7 July 2016, when the NO2 VCD field was mapped with the Airborne Prism Experiment (APEX) imaging spectrometer. The spatial distribution of APEX VCDs was rather smooth, with a horizontal gradient between lower values upwind and higher values downwind of the city center. The NO2 map had no pronounced source signatures except for the plumes of two combined heat and power (CHP) plants. The APEX VCDs have a fair correlation with mobile multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations from two vehicles conducted on the same afternoon (r=0.55). In contrast to the VCDs, mobile NSC measurements revealed high spatial and temporal variability along the roads, with the highest values in congested areas and tunnels. The NOx emissions of the two CHP plants were estimated from the APEX observations using a mass-balance approach. The NOx emission estimates are consistent with CO2 emissions determined from two ground-based Fourier transform infrared (FTIR) instruments operated near one CHP plant. The estimates are higher than the reported emissions but are probably overestimated because the uncertainties are large, as conditions were unstable and convective with low and highly variable wind speeds. Under such conditions, the application of mass-balance approaches is problematic because they assume steady-state conditions. We conclude that airborne imaging spectrometers are well suited for mapping the spatial distribution of NO2 VCDs over large areas. The emission plumes of point sources can be detected in the APEX observations, but accurate flow fields are essential for estimating emissions with sufficient accuracy. The application of airborne imaging spectrometers for studying NSCs is less straightforward and requires us to account for the non-trivial relationship between VCDs and NSCs.

Identifying Sources of NOx emissions from Aircraft through Source Apportionment and Regression Models

“…With this method, emissions are back calculated from pollutant measurements acquired across an entire airshed. This is typically done with a remote sensing instrument -in orbit [13][14][15] or on an aircraft [16][17][18] . Analyses have been conducted for global megacities [19][20][21][22][23] and power plants 24,25 using the Tropospheric Monitoring Instrument (TROPOMI) and a complementary satellite instrument, the Ozone Monitoring Instrument (OMI).…”

Use of machine learning and principal component analysis to retrieve nitrogen dioxide (NO2) with hyperspectral imagers and reduce noise in spectral fitting

“…Therefore, it has been a stated and challenging goal of these ocean color missions to quantify NO 2 spatiotemporal variations with their lowerspectral-resolution measurements. NO 2 retrievals have been demonstrated with hyperspectral sensors on aircraft (Tack et al, 2017;Kuhlmann et al, 2022) and the Russian Resurs-P satellite (Postylyakov et al, 2017(Postylyakov et al, , 2019Zakharova et al, 2021); these sensors have somewhat higher spectral resolution than PACE and GLIMR.…”