Biomass burning at Cape Grim: exploring photochemistry using multi-scale modelling

We have tested the ability of a high-resolution chemical transport model (CTM) to reproduce biomass burning (BB) plume strikes and ozone (O-3) enhancements observed at Cape Grim in Tasmania, Australia, from the Robbins Island fire. The CTM has also been used to explore the contribution of near-field BB emissions and background sources to O-3 observations under conditions of complex meteorology. Using atmospheric observations, we have tested model sensitivity to meteorology, BB emission factors (EFs) corresponding to low, medium, and high modified combustion efficiency (MCE), and spatial variability. The use of two different meteorological models (TAPM-CTM and CCAM-CTM) varied the first (BB1) plume strike time by up to 15 h and the duration of impact between 12 and 36 h, and it varied the second (BB2) plume duration between 50 and 57 h. Meteorology also had a large impact on simulated O-3, with one model (TAPM-CTM) simulating four periods of O-3 enhancement, while the other model (CCAM) simulating only one period. Varying the BB EFs, which in turn varied the non-methane organic compound (NMOC) / oxides of nitrogen (NOx) ratio, had a strongly non-linear impact on simulated O-3 concentration, with either destruction or production of O-3 predicted in different simulations. As shown in previous work (Lawson et al., 2015), minor rainfall events have the potential to significantly alter EF due to changes in combustion processes. Models that assume fixed EF for O-3 precursor species in an environment with temporally or spatially variable EF may be unable to simulate the behaviour of important species such as O-3. TAPM-CTM is used to further explore the contribution of the Robbins Island fire to the observed O-3 enhancements during BB1 and BB2. Overall, TAPM-CTM suggests that the dominant source of O-3 observed at Cape Grim was aged urban air (age = 2 days), with a contribution of O-3 formed from local BB emissions. This work shows the importance of assessing model sensitivity to meteorology and EF and the large impact these variables can have in particular on simulated destruction or production of O-3 in regional atmospheric chemistry simulations. This work also shows the importance of using models to elucidate the contribution from different sources to atmospheric composition, where this is difficult using observations alone.