Estimating NOx emissions using S5-P TROPOMI

Estimating NOx emissions using S5-P TROPOMI: An adjoint-free 4DVAR approach

Zijlker, Tammo (TU Delft Electrical Engineering, Mathematics and Computer Science)

Heemink, A.W. (mentor)

Delft University of Technology

Applied Mathematics | Computational Science and Engineering

2020-08-11

This study aims to improve estimates of NOx emission strengths by assimilation of TROPOMI satellite retrievals in the LOTOS-EUROS chemical transport model. Nitrogen oxides (NO and NO2) play a pivotal role in atmospheric chemistry, are an important source of air pollution and contribute to nitrogen deposition over vulnerable natural areas. Therefore, it is paramount to have accurate estimates of emissions. Emissions are parameterised by multiplicative correction factors for NOx emission strengths from existing inventories. Optimal estimates of the correction factors are calculated by assimilation of TROPOMI NO2 retrievals in LOTOS-EUROS. This study proposes an adjoint-free approach to solving the 4DVAR data assimilation problem. Due to the near linearity of LOTOS-EUROS with respect to NO2, an approximate model is proposed that calculates NO2 concentrations from the background state and a linear combination of the influences of the parameters on the state. This approximate model is calculated from an ensemble of LOTOS-EUROS simulations with perturbed parameters. After substitution of the approximate model in the 4DVAR cost function, it is quadratic and the minimum can be calculated directly. For this approximate cost function, the optimal estimate of the parameters and the covariance of this estimation can be obtained with negligible computational costs. Twin experiments, where synthetic satellite observations are assimilated, show that the adjoint-free 4DVAR method is able to accurately minimise the cost function. Errors in estimated parameters are in agreement with the covariance calculated for the estimate. It was also shown that by using domain decomposition, it is possible to generate the approximate model from fewer simulations of LOTOS-EUROS and thereby increasing the computational efficiency of the method. In experiments using TROPOMI NO2 retrievals, the method performs well when modelled plumes align with the retrievals. However, differences between modelled plumes and retrievals, that are resolved by the high resolution of the TROPOMI instrument, may strongly hamper results as the method is only able to correct the intensity of the plumes but not their positions. This leads to an underestimation of NOx emission strengths. Further research is required to handle differences of plume positions in LOTOS-EUROS and TROPOMI retrievals to apply the method to actual TROPOMI retrievals. In addition, more research into domain decomposition may further increase computational efficiency of the method.

TROPOMI
Inverse Modelling
Data Assimilation
LOTOS-EUROS
Emission
NO2
NOx
4DVAR
Adjoint-based optimization

http://resolver.tudelft.nl/uuid:cb9a2652-6382-4dac-8c46-01a86b5d048f

Student theses

master thesis

© 2020 Tammo Zijlker