Overview and evaluation of the Community Multiscale Air Quality (CMAQ) model version 5.1

Abstract

Abstract. The Community Multiscale Air Quality (CMAQ) model is a comprehensive multi-pollutant air quality modeling system developed and maintained by the U.S. Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public which incorporates a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ; updates to the gas and aerosol chemistry; revisions to the calculations of clouds and photolysis; and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations generally result in greater afternoon and early evening mixing in the model, times when the model historically underestimates mixing. The result is higher ozone (O3) mixing ratios on average due to reduced NO titration and lower fine particulate matter (PM2.5) concentrations due to greater dilution of primary pollutants (e.g. elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O3 mixing ratios, primarily due to reduced cloudiness and reduced attenuation of photolysis in the model. Updates to the aerosol chemistry results in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing PM2.5 bias, while updates to the gas chemistry result in generally increased O3 in January and July (small) and slightly higher PM2.5 concentrations on average in both January and July. Overall, seasonal variation in simulated PM2.5 generally improves in the new model version, as concentrations decrease in the winter (when PM2.5 is overestimated by CMAQ v5.0.2) and increase in the summer (when PM2.5 is underestimated by CMAQ v5.0.2). Ozone mixing ratios are higher on average with v5.1 versus v5.0.2, resulting in higher O3 mean bias, as O3 tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O3 is low), however both the error and correlation are largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios showed that v5.1 tends to be slightly more responsive to reductions in NOx (NO + NO2), VOC and SOx (SO2 + SO4) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O3 due to large, widespread reductions in observed emissions. Finally, the computational efficiency of the model was significantly improved in v5.1, which keeps runtimes similar to v5.0.2 despite the added complexity to the model.