Anthropogenically induced changes to the Earth's climate system are widely accepted to be one of the greatest threats to the sustainable future of humanity. Greenhouse gas emissions constitute the largest driving factor behind these changes, and with annual emissions still increasing further perturbation is projected. Accurate quantification of these emissions, broken down both spatially and sectorally, is vitally important in guiding effective policy for emission reduction at both national and international levels. This thesis focusses on methods to improve top-down estimates for greenhouse gas emissions within the UK, using data sampled on board the UK atmospheric research aircraft. Novel instrumentation and analytical techniques are presented and evaluated, based on measurements made as part of the GAUGE (Greenhouse gAs UK and Global Emissions) and MAMM (Methane and other greenhouse gases in the Arctic: Measurements, process studies and Modelling) projects. A new quantum cascade laser absorption spectrometer (QCLAS) for measuring CH4 and N2O on board the aircraft has been characterised. Its performance was evaluated over 17 flights during summer 2016, and a sensitivity to changes in aircraft cabin pressure was observed. A new calibration procedure was derived to minimise the effect of this sensitivity on the data, and the impact of this new procedure was quantified through analysis of in-flight target cylinder measurements and comparison against simultaneous CH4 measurements made using a previously characterised analyser. The impact of water vapour on the retrievals was also investigated, with superior results derived by directly including line broadening due to water vapour in the mole fraction retrieval algorithm. Applying the new calibration procedure to the data, total 1-sigma uncertainties of 2.47 ppb for CH4 and 0.54 ppb for N2O have been calculated for 1 Hz measurement. The British Isles CH4 flux has been derived for a case study on 12 May 2015, using aircraft and ground-based sampling and a combination of local dispersion modelling, global chemical transport modelling and a composite inventory comprised of anthropogenic and natural sources. A new multiple variable regression technique was used to compare measured and modelled CH4 mole fractions, and to derive scale factors used to estimate posterior fluxes based on prior inventory values. A maximal range for the total British Isles CH4 flux has been calculated to be 67 kg/s -- 121 kg/s, with a central estimate of 103 kg/s based on an assessment of the most likely apportionnment of model uncertainty. A further case study measuring CO2, CH4 and CO fluxes from London and surrounding urban areas using a mass balance technique has also been performed. Fluxes have been found to be a factor of ~0.7 lower for CH4, ~0.8 lower for CO, and ~1.3 higher for CO2, relative to a similar study in 2012. Likely sources of difference between the derived fluxes, as well as the overall utility of this technique, have been assessed.