Why time and space matters - arguments for the improvement of temporal emission profiles for atmospheric dispersion modeling of air pollutant emissions

Emissions of trace gases originating from anthropogenic activities are vital input data for chemical transport models (CTMs). Other key input datasets such as meteorological drivers, and biogeochemical and physical processes have been subject to detailed investigation and research in the recent past, while the representation of spatio-temporal aspects of emission data in CTMs has been somewhat neglected. Arguably, this has less impact on the regional to hemispheric or global scale, where the grid sizes of currently applied CTMs represent well mixed average concentrations or deposition values. Evaluating model output against ground-based observations or remote sensing results on these spatial levels may not to be overly sensitive to the temporal (and spatial) profiles of emission input data. With increasing level of detail and spatio-temporal resolution, CTMs applied to determine national or local scale air quality are likely prone to be more sensitive to the spatial and temporal patterns of anthropogenic emissions. The location and timing of emission events - for instance peaks of ammonia emissions following the spring and autumn application of manure and mineral fertilisers - may well determine local concentration or deposition episodes, while not necessarily affecting seasonal or even annual mean values. In a similar way, high levels of ambient ozone levels typically have very strong seasonal and diurnal variations, with effects on plants for instance varying greatly over time. In addition to that, the timing of occurrences of high ambient concentrations plays a vital role in the This paper illustrates the general need for taking into account the spatial and temporal resolution of air pollutant emissions, using some examples of recent work conducted in the UK for national scale atmospheric dispersion modeling