The aviation sector has set goals to reduce its carbon footprint, as the industry continues to grow. To capture the climate impact of millions of flights, climate models play a crucial role in this task. However, these climate models depend on information about the concentration and distribution of emissions around the globe. To provide such data, bottom-up emission inventories are used. These inventories model aircraft flight performance and engine emission characteristics to provide the best estimate of the geographical distribution of emissions due to aviation.

The research presented in this thesis aims to critically evaluate and improve existing implementations of global aviation emission inventories, with the ultimate goal of achieving more representative estimations of aircraft emissions and their distribution. The goal should be achieved without compromising on computational efficiency and the flexibility of the model. This work builds upon an existing emission inventory.

In order to achieve the goal of this study, revisions to the information, performance and emission models are incorporated. The first revision involves a more accurate representation of the actual engine equipped for each flight analysed. Next, flight trajectory correction factors (lateral inefficiency) are improved by using data provided in literature, derived from a large set of ADS-B trajectory data. Furthermore, the latest version of EUROCONTROL’s Base of Aircraft Data (BADA) performance model is implemented for all the aircraft which it covers (89% of total flown distance). For emission modelling, the Boeing Fuel Flow Method 2 (BFFM2) is kept for gaseous emissions; however, an updated method (MEEM), validated on a large set of engine manufacturer data and more recent measurement campaigns, is utilised for nvPM estimates.

Compared to existing global inventories for 2019, the updated model estimates total fuel burn at 250 Tg, slightly lower than the earlier estimate (254 Tg) and significantly below estimates by Teoh et al. (283 Tg) and Quadros et al. (297 Tg). On a per-kilometre basis, however, the fuel burn estimate is 2% lower than Rik Kroon’s but 9.6% higher than Teoh et al. The nitrogen oxides (NO𝑥) emission index closely aligns with benchmarks by Teoh et al. and Quadros et al., differing by less than 2.5%, yet is 11% lower than Rik Kroon’s due to performance model corrections. For nvPM emissions, notable discrepancies arise: mass emission estimates are higher by 62% and 39% compared to Rik Kroon and Quadros et al., respectively, but 43% lower than Teoh et al. Conversely, nvPM number emission estimates exceed those by Teoh et al. and Quadros et al. by approximately 60% and 54%, respectively. Geographically, emission hotspots align with previous studies, though data limitations cause under-representation in certain southern hemisphere routes, highlighting areas for future improvement.

Sensitivity analysis revealed that the performance model results are highly sensitive to the parameters used to determine cruise altitude and initial fuel mass estimate, with up to ±4% changes in nvPM emissions and fuel burn observed for heavy-weight aircraft. The uncertainty analysis using Monte Carlo simulations showed total uncertainties of ±9% for fuel consumption and emission indices uncertainties ranging from ±8% forNO𝑥 to ±40% for nvPM number and ±95% for nvPM mass, reflecting the significant impact of methodological assumptions and limited validation data on nvPM emissions.

The thesis concludes by confirming that the updates provided lead to an improvement in the estimation of the quantity and distribution of aviation emissions. Limitations related to the coverage of annual flights, the estimation of the take-off mass, and the uncertainty related to nvPM emissions are also identified. This work can serve as a baseline for future work in those aspects.