Spatially Resolved Emissions of NOx and VOCs and Comparison to Inventories.

Abstract:

Recent trends in ambient concentrations of NO_x in the UK (and other European countries) have shown a general decrease over the period 1990 to 2002, followed by largely static concentrations from 2004 – present. This is not in line with the decreases predicted based on bottom up emission inventories and has lead to widespread non-compliance with EU Air Quality Directives. We present a method to quantify the geographic variability of emission of NO_x and selected VOCs at a city scale (London) using an aircraft platform. High frequency observations of NO_x and VOCs (10 Hz and 2 Hz, respectively) were made using low altitude flights across London and combined with 20 Hz micro-meteorological data to provide an emission flux using the aircraft eddy covariance technique. A continuous wavelet transformation was used to produce instantaneous fluxes along the flight transect and a parameterisation of a backward Lagrangian model used to calculate the flux footprint, attributing emission rates to specific areas in Greater London (see figure). The observed flux was compared to the UK National Atmospheric Emission Inventory (NAEI), which takes a “bottom up” approach to calculating emissions, involving estimates from different source sectors to produce yearly emission estimates. These were then modified using factors specific to each source to reflect the actual month, day and time of the flight, to provide a more meaningful comparison to the observation. A significant underestimation in the inventory NOx was observed ranging from 150–200% in outer London, to 300% in the central area. Potential reasons for this are discussed, including the poor treatment of real world emissions of NO_x from diesel vehicles in the inventory. We also compare measurements to the London Atmospheric Emissions Inventory (LAEI), which provides a more explicit treatment of the traffic emissions specific to London and which shows better agreement with the measurements.