Reduced-form and complex ACTM modelling for air quality policy development: A model inter-comparison. (January 2023) - Oxley, Tim; Vieno, Massimo; Woodward, Huw; ApSimon, Helen; Mehlig, Daniel; Beck, Rachel; Nemitz, Eiko; Reis, Stefan
Highlights: We show how reduced form and complex models can be applied in combination to inform air pollution policy development. We compare PM2.5 concentrations calculated by both a reduced-form and a complex ACTM, showing good agreement. Both models agree well with observations of PM2.5 and SIA concentrations from national monitoring networks. We present this comparison for the current (2018) and selected future (2040) emissions scenarios in the United Kingdom. We confirm the robustness of a reduced-form model to evaluate alternative futures, through comparison with an Eulerian ACTM. Abstract: Simulation models can be valuable tools in supporting development of air pollution policy. However, exploration of future scenarios depends on reliable and robust modelling to provide confidence in outcomes which cannot be tested against measurements. Here we focus on the UK Integrated Assessment Model, a fast reduced-form model with a purpose to support policy development with modelling of multiple alternative future scenarios, and the EMEP4UK model which is a complex Eulerian Atmospheric Chemistry Transport Model requiring significant computing resources. The EMEP4UK model has been used to model selected core scenarios to compare with UKIAM, and to investigate sensitivity studies such as the interannual variability in response to meteorological differences between years. This model intercomparison addresses total PM2.5, primary PM2.5 and Secondary Inorganic Aerosol concentrations for a baseline of 2018 and selected scenarios for projections to 2040. This work has confirmed the robustness of the UK Integrated Assessment Model for assessing alternative futures through a direct comparison with EMEP4UK. Both models have shown good agreement with measurements, and EMEP4UK shows an ability to replicate past trends. These comparisons highlight how a combination of reduced-form modelling (UKIAM) and complex chemical transport modelling (EMEP4UK) can be effectively used in support of air pollution policy development, informing understanding of projected futures in the context of emerging evidence and uncertainties.