Methane is the most impactful greenhouse gas in the short term, and its mitigation can help reduce future warming, especially in the waste and coal mining sectors, which contribute to 20% of anthropogenic emissions. Emission monitoring enables mitigation and is possible through the daily global detections provided by the TROPOMI instrument. Low-resolution TROPOMI acquisitions can be used to guide high-resolution targeted observations from other satellites, allowing for site-level plume localisation. Further attribution to specific underlying activities or sub-areas at landfills and openpit coal mines is difficult due to their topography. Interferometric synthetic aperture radar (InSAR) can support this effort by using satellite-based SAR sensors to measure millimetre-accurate surface deformations. The small-baseline subset (SBAS) and hybrid phase-linking (PL) methods enable multi-year deformation monitoring over unstable areas by leveraging many acquisitions with short revisit times provided by the Sentinel-1 (S-1) C-band SAR constellation. However, their use over methane emission sites has been limited. This study combined measurements from high-resolution methane satellites with InSAR-derived surface deformations to enhance the use of InSAR methods and understanding of methane plume development at landfills and open-pit coal mines. S-1 workflows of varying complexity were compared alongside an Advanced Land Observing Satellite-2 (ALOS-2) based workflow, included for its longer L-band SAR wavelength. All S-1 workflows showed error values less than 16 mm annually when compared against GNSS-measured ground movement, with the most complex hybrid PL method showing the most precise results. Surface deformations were calculated over several super-emitters, identifying that standard SBAS methods often masked active dumping signals with subsidence trends, whereas the hybrid PL method uniquely captured rapid positive deformation spikes. In contrast, ALOS-2 measurements indicated a greater ability to capture the scale of deformations due to its wavelength but were restricted by spatial resolution and coverage. While correlations between deformation magnitude and emission rate were insignificant in landfills, positive surface deformations in coal mines showed a correlation with emission rates. Furthermore, spatial proximity analysis revealed that up to 97% of landfill plumes originated within 100 m of high-deformation clusters. These findings highlight the potential of current methods, particularly the hybrid PL method, for improved methane detection targeting over complex landfills and open-pit coal mine emitters. They are capable of identifying highly deforming areas corresponding to emissionproducing activity, such as dumping or mining, but cannot capture their full extent. To better measure deformation at these sites, next-generation L-band satellites with improved resolutions and revisit times should be used in combination with processing techniques that utilise ground-level data.

This study aims at speeding up the acquisition of meteorological data for use in the chemical transport model TM5 for calculating methane mixing ratios, by using AI to generate meteorological data. The study starts off with a literature review in which meteorology and AI is discussed, after which it has been decided that GraphCast is the most suitable forecasting model for this project. In order to match GraphCast’s output to TM5’s input, three processing steps have been defined and verified. Based upon this verification it appears that that the conversion of the temperature, humidity and horizontal massfluxes were successful, however the conversion of the vertical massflux was unsuccessful. Subsequently the new pipeline was integrated in TM5, followed by another verification step. From this step it once again appeared that the vertical massflux was incorrect, and was not incorporated. The remainder of the pipeline was incorporated. Finally GraphCast generated meteorological data was ran in TM5, with forecasting lengths ranging from 6 to 72 hours. From this step it appeared the meteorological data provided good results from TM5. The error to the reference simulations increased for longer forecasting times. Peculiarities were found in the stratosphere, where a poor forecast by GraphCast resulted in large errors in the methane mixing ratio of TM5, which would carry over in an error on the South Pole. Similarly a reduction in vertical resolution in the stratosphere resulted in similar errors. The quality of the data close to the surface has generally remained good though. Overall the performance of TM5 was still good, and despite improvements being possible, the results were encouraging.

In recent years, mitigation of the anthropogenic climate impact has become increasingly more important. Over the past decades, the aviation industry has grown significantly, making it a large contributor to greenhouse gases in the atmosphere. One such greenhouse gas is Ozone (O3) in the troposphere, which has a warming effect on the global climate. Aviation Nitrogen Oxides (NOx) emissions play a role in the formation and loss of O3 in the troposphere, however, the chemistry is highly non-linear which makes mitigation more complex. To gain a better understanding of the contribution of aviation to tropospheric O3, this thesis looks at how aviation’s tropospheric O3 contribution varies and how the Ozone Burden Efficiency (OBE) metric can be used to better explain these global variations. The OBE is a metric which quantifies the efficiency of the background chemistry and the global transportation phenomena to promote the net formation of O3. To conduct this research, chemistry climate simulation results of the ECHAM/MESSy Atmospheric Chemistry (EMAC) model were used for a period of 2003 to 2018.

The analysis showed that across the simulated time period aviation’s contribution to tropospheric O3 increased from about 1.6% to approximately 1.9%. Looking at the vertical spread of the aviation induced O3 showed that downwards transport of O3 drives global distributions, creating large O3 mixing ratios in the free troposphere under the flight altitudes. Furthermore, the analysis of the vertical spread showed that the percentage contribution of aviation to local O3 mixing ratios is larger at ground level than at flight altitudes, showing that aviation induced O3 also contributes to air quality.

Analysing the OBE, showed that the OBE of aviation for the whole troposphere is about 4.5 Tg (O3) · Tg−1 (NOx). Further analysis showed that the OBE in the planetary boundary layer is about 2.5 Tg (O3)· Tg−1 (NOx), whereas the OBE at flight altitudes is about 1.3 Tg (O3) · Tg−1 (NOx). The larger OBE at ground level is caused by the large scale downward transport of the formed O3 and the low amount of local NOx emissions, whereas at flight altitudes, the local NOx emissions are not as small compared to the local O3 burden. Furthermore, analysis of the OBE metric also shows that the OBE of aviation is largest in the free troposphere below the flight altitudes, where it is estimated to be around 8 Tg (O3) · Tg−1 (NOx). This result highlights the large amount of O3 which is transported downwards to lower altitudes from the flight levels. Overall, the analysis using the OBE metric shows that it is most useful for emission sectors where the emissions are dominated by NOx emissions rather than carbon species which also contribute towards the production of O3. However, this attribute of the OBE metric makes it difficult to use OBE values to compare different emissions sources.