Flux measurements of nitrogen oxides (NO.sub.x) were made over London using airborne eddy covariance from a low-flying aircraft. Seven low-altitude flights were conducted over Greater London, performing multiple overpasses across the city during eight days in July 2014. NO.sub.x fluxes across the Greater London region (GLR) exhibited high heterogeneity and strong diurnal variability, with central areas responsible for the highest emission rates (20-30 mg m.sup.-2 h.sup.-1). Other high-emission areas included the M25 orbital motorway. The complexity of London's emission characteristics makes it challenging to pinpoint single emissions sources definitively using airborne measurements. Multiple sources, including road transport and residential, commercial and industrial combustion sources, are all likely to contribute to measured fluxes. Measured flux estimates were compared to scaled National Atmospheric Emissions Inventory (NAEI) estimates, accounting for monthly, daily and hourly variability. Significant differences were found between the flux-driven emissions and the NAEI estimates across Greater London, with measured values up to 2 times higher in Central London than those predicted by the inventory. To overcome the limitations of using the national inventory to contextualise measured fluxes, we used physics-guided flux data fusion to train environmental response functions (ERFs) between measured flux and environmental drivers (meteorological and surface). The aim was to generate time-of-day emission surfaces using calculated ERF relationships for the entire GLR; 98 % spatial coverage was achieved across the GLR at 400 m.sup.2 spatial resolution. All flight leg projections showed substantial heterogeneity across the domain, with high emissions emanating from Central London and major road infrastructure. The diurnal emission structure of the GLR was also investigated, through ERF, with the morning rush hour distinguished from lower emissions during the early afternoon. Overall, the integration of airborne fluxes with an ERF-driven strategy enabled the first independent generation of surface NO.sub.x emissions, at high resolution using an eddy-covariance approach, for an entire city region.