Performance characteristics of MM5–SMOKE–CMAQ for a summer photochemical episode in southeast England, United Kingdom

Abstract

In this study a modelling system consisting of Mesoscale Model (MM5), Sparse Matrix Operator Kernel Emissions (SMOKE) and Community Multiscale Air Quality (CMAQ) model has been applied to a summer photochemical period in southeast England, UK. Ozone (O 3), nitrogen dioxide (NO 2) and particulate matter (PM 2.5) concentrations modelled with different horizontal grid resolutions (9 and 3 km) were evaluated against available ground-level observations from the UK Automatic Urban and Rural Network (AURN) and London Air Quality Network (LAQN) for the period of 24–28 June 2001 with a focus on O 3 predictions. This effort, which represents the first comprehensive performance evaluation of the modelling system over a UK domain, reveals that CMAQ's ability to reproduce surface O 3 observations varies with O 3 concentrations. It underpredicts O 3 mixing ratios on high-O 3 days and overpredicts the maximum and minimum hourly O 3 values for most low-O 3 days. Model sensitivity analysis with doubled anthropogenic NO x or volatile organic compounds (VOC) emissions and analysis of the daylight-averaged levels of OX (sum of O 3 and NO 2) as a function of NO x revealed that the undereprediction of peak O 3 concentrations on high-O 3 days is caused by the underprediction of regional contribution and to a lesser extent local production, which might be related to the underestimation of European emissions in EMEP inventory and the lacked reactivity of the modelled atmosphere. CMAQ systematically underpredicts hourly NO 2 mixing ratios but captures the temporal variations. The normalized mean bias for hourly NO 2, although much larger than that for O 3, falls well within the generally accepted range of −20% to −50%. CMAQ with both resolutions (9 and 3 km) significantly underpredicts PM 2.5 mass concentrations and fails to reproduce its temporal variations. While model performance for O 3 and PM 2.5 are not very sensitive to model grid resolutions, a better agreement between modelled and measured hourly NO 2 mixing ratios was achieved with higher resolution. Further investigation into the uncertainties in meteorological input, uncertainties in emissions, as well as representation of physical and chemical processes (e.g. chemical mechanism) in the model is needed to identify the causes for the discrepancies between observations and predictions.