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

Area of Science:

• Atmospheric chemistry and transport modeling
• Environmental policy support tools
• Air quality forecasting

Background:

• Simulation models are crucial for air pollution policy, but future scenario exploration requires robust validation.
• The UK Integrated Assessment Model (UKIAM) is a fast, reduced-form model for policy support.
• The EMEP4UK model is a complex Eulerian Atmospheric Chemistry Transport Model.

Purpose of the Study:

• To compare the UKIAM with the EMEP4UK model for assessing future air pollution scenarios.
• To validate the robustness of UKIAM for policy development.
• To investigate model sensitivity to meteorological variability.

Main Methods:

• Model intercomparison of total PM2.5, primary PM2.5, and Secondary Inorganic Aerosol concentrations.
• Baseline year: 2018; Projections: 2040.
• Sensitivity studies including interannual variability due to meteorological differences.

Main Results:

• UKIAM demonstrated robustness for future scenario assessment when compared directly with EMEP4UK.
• Both models showed good agreement with available measurements.
• EMEP4UK successfully replicated historical air quality trends.

Conclusions:

• A combined approach using reduced-form (UKIAM) and complex (EMEP4UK) modeling effectively supports air pollution policy.
• This integrated modeling strategy enhances understanding of projected air quality futures.
• The findings provide confidence in using UKIAM for policy-relevant scenario analysis.