Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO<sub>2</sub> measurements

Abstract

Abstract. We present high spatial resolution (up to 2.2×2.2 km2) simulations focussed over south-west Germany using the online coupled regional atmospheric chemistry model system MECO(n) (MESSy-fied ECHAM and COSMO models nested n times). Numerical simulation of nitrogen dioxide (NO2) surface volume mixing ratios (VMRs) are compared to in situ measurements from a network with 193 locations including background, traffic-adjacent and industrial stations to investigate the model's performance in simulating the spatial and temporal variability of short-lived chemical species. We show that the use of a high-resolution and up-to-date emission inventory is crucial for reproducing the spatial variability and resulted in good agreement with the measured VMRs at the background and industrial locations with an overall bias of less than 10 %. We introduce a computationally efficient approach that simulates diurnal and daily variability in monthly-resolved anthropogenic emissions to resolve the temporal variability of NO2. MAX-DOAS (Multiple AXis Differential Optical Absorption Spectroscopy) measurements performed at Mainz (49.99∘ N, 8.23∘ E) were used to evaluate the simulated tropospheric vertical column densities (VCDs) of NO2. We propose a consistent and robust approach to evaluate the vertical distribution of NO2 in the boundary layer by comparing the individual differential slant column densities (dSCDs) at various elevation angles. This approach considers details of the spatial heterogeneity and sensitivity volume of the MAX-DOAS measurements while comparing the measured and simulated dSCDs. The effects of clouds on the agreement between MAX-DOAS measurements and simulations have also been investigated. For low elevation angles (≤8∘), small biases in the range of −14 % to +7 % and Pearson correlation coefficients in the range of 0.5 to 0.8 were achieved for different azimuth directions in the cloud-free cases, indicating good model performance in the layers close to the surface. Accounting for diurnal and daily variability in the monthly-resolved anthropogenic emissions was found to be crucial for the accurate representation of time series of measured NO2 VMR and dSCDs and is particularly critical when vertical mixing is suppressed, and the atmospheric lifetime of NO2 is relatively long.

Five Years of Spatially Resolved Ground-Based MAX-DOAS Measurements of Nitrogen Dioxide in the Urban Area of Athens: Synergies with In Situ Measurements and Model Simulations

“…This suggests that the scatter in MAX-DOAS versus in situ measurements is to some degree dominated by spatial averaging effects. Although to our knowledge there is no other study comparing vertical and slant columns with in situ measurements simultaneously, our finding is supported by [43] who used in situ and MAX-DOAS NO 2 measurements to evaluate an atmospheric chemistry model. They showed that slant columns are more suitable for such a comparison because they account for the horizontal heterogeneity in the viewing direction in contrast to vertical columns, the retrievals of which involve more uncertainties and complexity.…”

Modelling of tropospheric NO₂ using WRF-Chem with optimized temporal NOₓ emission profiles derived from in-situ observations – Comparisons to in-situ, satellite, and MAX-DOAS observations over central Europe

“…Due to the short lifetime of NO x the observed concentrations closely follow the temporal profiles. As an initial starting point, the temporal profiles from Kumar et al (2021) were used. Although the proposed optimization method is rather unconventional, it has a few important benefits.…”

“…Figure 2h reveals that the overall NO x budget assumed for the simulated month is realistic, meaning that the corresponding monthly weighting factor is reasonable. Similarly, the daily profiles from Kumar et al (2021) were taken over without changes. What remains are the hourly profiles of each sector.…”

“…Mar et al (2016) report that the choice of the chemical mechanism used by WRF-Chem barely impacts the NO x underestimation by comparing simulations using the RADM2 and MOZART-4 chemical mechanisms. Kumar et al (2021) demonstrate in a simulation with the MECO(n) model system over Germany using TNO-MACC-III and regional emission data from the German Environmental Agency (UBA), that agreement between modelled NO 2 concentrations and in-situ observations improves greatly when diurnal and seasonal variability is added to the yearly resolved emission data using reasonably chosen hourly and monthly weighting factors ("temporal profiles"). This temporal upsampling has become common practice among the air quality modelling community and standard values for such temporal profiles have established (see Crippa et al (2020b); Kumar et al (2021) and the references within).…”

“…This temporal upsampling has become common practice among the air quality modelling community and standard values for such temporal profiles have established (see Crippa et al (2020b); Kumar et al (2021) and the references within). Kumar et al (2021) used improved temporal profiles derived from empirical proxies, e.g. car counts on highways at different hours of the day.…”