Separating Transported and Local Atmospheric Carbon Monoxide in Australasia with Satellite and Ground-based Remote Sensing

Abstract:

A range of measurement techniques are required to understand atmospheric composition. No single instrument can measure all you need to know about the atmosphere, due to differences in temporal and spatial scales. Satellites help interpret synoptic-scale contributions to composition, but provide little fine-scale information due to sparse measurement timing and spatial averaging. In contrast, ground-based solar-tracking FTIR instruments can capture fine-scale chemistry and dynamic influence, but being point measurements, have trouble identifying transported signals. Knowing the relative contribution of transported to local sources of atmospheric pollution is important for developing realistic air quality policies and providing accurate air quality forecasts.

In this study, we exploit the complementary limitations and sensitivities of two instruments to gain information about carbon monoxide (CO) sources at three stations in Australasia: Darwin and Wollongong in Australia and Lauder in New Zealand. Total column amounts of CO are compared between the satellite-borne Measurements of Pollution in the Troposphere (MOPITT) and ground-based solar FTIR instruments in the TCCON and NDACC networks. Several CO timeseries anomalies are highlighted as representative of pollution delivery pathways in relation to local, regional and long-distance contributions. Large-scale pollution events are captured by both instruments, but only the satellite instrument can provide regional and global context. MOPITT identifies long-range transport of pollution from biomass burning in South America and southern Africa, while the FTIR can additionally capture local urban and biomass burning influences. Unusually low CO, sourced from southern latitudes, is also measured by both instruments. Interannual variability is significantly different at each site and is diagnosed with chemical transport modeling (CAM-chem) to quantify the role of emissions versus meteorology.