Reduced-form and complex ACTM modelling for air quality policy development: A model inter-comparison.

Environ Int

UK Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian EH26 0QB, United Kingdom; University of Exeter Medical School, European Centre for Environment and Health, Knowledge Spa, Truro TR1 3HD, United Kingdom; The University of Edinburgh, School of Chemistry, Level 3, Murchison House, 10 Max Born Crescent, The King's Buildings, West Mains Road, Edinburgh EH9 3BF, United Kingdom.

Published: January 2023

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 PM, primary PM 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.

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Source
http://dx.doi.org/10.1016/j.envint.2022.107676DOI Listing

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