Abstract
The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US 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, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: 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 result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in 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 attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM2.5 bias (PM2.5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O3 and PM2.5 on average in January and July. Overall, the seasonal variation in simulated PM2.5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM2.5 concentrations decrease in the winter (when PM2.5 is generally overestimated by CMAQ) and increase in the summer (when PM2.5 is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. 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, O3 correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show 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.
Highlights
Numerous federal (e.g., United States Environmental Protection Agency, USEPA), state and private entities rely on numerical model simulations of atmospheric chemistry, transport and deposition of airborne emissions as well as the resulting pollutants as part of their decision-making process for air quality management and mitigation (e.g., Scheffe et al, 2007)
Unlike Foley et al (2010), in which several individual major scientific improvements in Community Multiscale Air Quality (CMAQ) v4.7 were evaluated incrementally, here we examine each scientific improvement separately by comparing simulations with the specific improvement removed to the base v5.1 simulation (CMAQv5.1_Base_NEIv1) which includes all the updates
It allows for easier examination of the effect of nonlinear increments on total model performance, as some updates to the modeling system may be affected by updates to other parts of the model, the effects of which on model performance may not be captured in an incremental testing format
Summary
Numerous federal (e.g., United States Environmental Protection Agency, USEPA), state and private entities rely on numerical model simulations of atmospheric chemistry, transport and deposition of airborne emissions as well as the resulting pollutants as part of their decision-making process for air quality management and mitigation (e.g., Scheffe et al, 2007). New versions of the CMAQ model have been released periodically over the past 15 years, with each new version consisting of numerous updates to the scientific algorithms within the model, while improving the quality of the input data used. The changes to the PX-LSM, ACM2 and MOL calculations in CMAQ had significant impact on the mixing within both WRF and CMAQ, and large impacts on the pollutant concentrations in CMAQ 4.4 evaluates the updates to the CB05e51 chemical mechanism These increments were chosen as the focus of this paper because they represent a fundamental change from the previously released model version and had the propensity to impact model performance for criteria pollutants. A comprehensive description of all the updates made in v5.1 and indepth technical documentation of those changes can be found on the CMAS Center website for the CMAQv5.1 release at https://cmaswiki-cempd.vipapps.unc.edu/index.php/
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