Influence of the choice of gas-phase mechanism on predictions of key gaseous pollutants during the AQMEII phase-2 intercomparison

Abstract The formulations of tropospheric gas-phase chemistry (“mechanisms”) used in the regional-scale chemistry-transport models participating in the Air Quality Modelling Evaluation International Initiative (AQMEII) Phase 2 are intercompared by the means of box model studies. Simulations were conducted under idealized meteorological conditions, and the results are representative of mean boundary layer concentrations. Three sets of meteorological conditions – winter, spring/autumn and summer – were used to capture the annual variability, similar to the 3-D model simulations in AQMEII Phase 2. We also employed the same emissions input data used in the 3-D model intercomparison, and sample from these datasets employing different strategies to evaluate mechanism performance under a realistic range of pollution conditions. Box model simulations using the different mechanisms are conducted with tight constraints on all relevant processes and boundary conditions (photolysis, temperature, entrainment, etc.) to ensure that differences in predicted concentrations of pollutants can be attributed to differences in the formulation of gas-phase chemistry. The results are then compared with each other (but not to measurements), leading to an understanding of mechanism-specific biases compared to the multi-model mean. Our results allow us to quantify the uncertainty in predictions of a given compound in the 3-D simulations introduced by the choice of gas-phase mechanisms, to determine mechanism-specific biases under certain pollution conditions, and to identify (or rule out) the gas-phase mechanism as the cause of an observed discrepancy in 3-D model predictions. We find that the predictions of the median diurnal cycle of O 3 over a set of emission conditions representing a network of station observations is within 4 ppbv (5%) across the different mechanisms. This variability is found to be very similar on both continents. There are considerably larger differences in predicted concentrations of NO x (up to ± 25%), key radicals like OH (40%), HO 2 (25%) and especially NO 3 (>100%). Secondary substances like H 2 O 2 (25%) or HNO 3 (10%), as well as key volatile organic compounds like isoprene (>100%) or CH 2 O (20%) differ substantially as well. Calculation of an indicator of the chemical regime leads to up to 20% of simulations being classified differently by different mechanism, which would lead to different predictions of the most efficient emission reduction strategies. All these differences are despite identical meteorological boundary conditions, photolysis rates, as well as identical biogenic and inorganic anthropogenic emissions. Anthropogenic VOC emissions only vary in the way they are translated in mechanism-specific compounds, but are identical in the total emitted carbon mass and its spatial distribution. Our findings highlight that the choice of gas-phase mechanism is crucial in simulations for regulatory purposes, emission scenarios, as well as process studies that investigate other components like secondary formed aerosol components. We find that biogenic VOCs create considerable variability in mechanism predictions and suggest that these, together with nighttime chemistry should be areas of further mechanism improvement.