K. Wyat Appel

Overview of the atmospheric model evaluation tool (AMET) v1.1 for evaluating meteorological and air quality models

This paper describes the details of the Atmospheric Model Evaluation Tool (AMET) v1.1 created by scientists in the Atmospheric Modeling and Analysis Division (AMAD) of the U.S. Environmental Protection Agency (EPA). AMET was first developed to evaluate the performance of the 5th Generation Mesoscale Model (MM5) and the Weather Research and Forecasting (WRF) meteorological model output and was later extended to include capabilities for evaluating output data from the Community Multiscale Air Quality (CMAQ) model as well. AMET is designed to leverage several open-source software packages that are used in combination to 1) pair the modeled and observed values in time and space, 2) store these paired datasets in an easily accessible and searchable database and 3) access and analyze these data using a statistical package. Through this process, AMET is able to provide a convenient method for evaluating meteorological and air quality model predictions. The use of a searchable, relational database allows the entire dataset to be quickly subset into only those data that are of the most interest for the current analysis, a process that is often tedious and time consuming without the use of a database. In addition to common summary statistics (e.g. RMSE, bias, and correlation), several of the many analysis features available in AMET include scatter plots, time series plots, box plot and spatial plots as part of operational model evaluation. Additionally, several unique analysis functions are also available in AMET, and the system provides a framework within which users may extend the current functionality for their own custom analyses. While AMET was designed to work specifically with MM5, WRF and CMAQ model output, it could easily be modified to work with output data from other meteorological and air quality models.

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1

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.

On the implications of aerosol liquid water and phase separation for organic aerosol mass

Organic compounds and liquid water are major aerosol constituents in the southeast United States (SE US). Water associated with inorganic constituents (inorganic water) can contribute to the partitioning medium for organic aerosol when relative humidities or organic matter to organic carbon (OM/OC) ratios are high such that separation relative humidities (SRH) are below the ambient relative humidity (RH). As OM/OC ratios in the SE US are often between 1.8 and 2.2, organic aerosol experiences both mixing with inorganic water and separation from it. Regional chemical transport model simulations including inorganic water (but excluding water uptake by organic compounds) in the partitioning medium for secondary organic aerosol (SOA) when RH > SRH led to increased SOA concentrations,· particularly at night. Water uptake to the organic phase resulted in even greater SOA concentrations as a result of a positive feedback in which water uptake increased SOA, which further increased aerosol water and organic aerosol. Aerosol properties· such as the OM/OC and hygroscopicity parameter (κorg), were captured well by the model compared with measurements during the Southern Oxidant and Aerosol Study (SOAS) 2013. Organic nitrates from monoterpene oxidation were predicted to be the least water-soluble semivolatile species in the model, but most biogenically derived semivolatile species in the Community Multiscale Air Quality (CMAQ) model were highly water soluble and expected to contribute to water-soluble organic carbon (WSOC). Organic aerosol and SOA precursors were abundant at night, but additional improvements in daytime organic aerosol are needed to close the model–measurement gap. When taking into account deviations from ideality, including both inorganic (when RH > SRH) and organic water in the organic partitioning medium reduced the mean bias in SOA for routine monitoring networks and improved model performance compared to observations from SOAS. Property updates from this work will be released in CMAQ v5.2.

Trends in atmospheric reactive nitrogen for the Eastern United States

Reactive nitrogen can travel far from emission sources and impact sensitive ecosystems. From 2002 to 2006, policy actions have led to decreases in NO(x) emissions from power plants and motor vehicles. In this study, atmospheric chemical transport modeling demonstrates that these emissions reductions have led to a downward trend in ambient measurements of transported reactive nitrogen, especially atmospheric concentrations and wet deposition of nitrate. The trend in reduced nitrogen, namely ammonium, is ambiguous. As reduced nitrogen becomes a larger fraction of the reactive nitrogen budget, wide-spread NH(3) measurements and improved NH(3) emissions assessments are a critical need.

Coupling of organic and inorganic aerosol systems and the effect on gas–particle partitioning in the southeastern US

Several models were used to describe the partitioning of ammonia, water, and organic compounds between the gas and particle phases for conditions in the southeastern US during summer 2013. Existing equilibrium models and frameworks were found to be sufficient, although additional improvements in terms of estimating pure-species vapor pressures are needed. Thermodynamic model predictions were consistent, to first order, with a molar ratio of ammonium to sulfate of approximately 1.6 to 1.8 (ratio of ammonium to 2× sulfate, RN/2S ≈ 0.8 to 0.9) with approximately 70% of total ammonia and ammonium (NHx) in the particle. Southeastern Aerosol Research and Characterization Network (SEARCH) gas and aerosol and Southern Oxidant and Aerosol Study (SOAS) Monitor for AeRosols and Gases in Ambient air (MARGA) aerosol measurements were consistent with these conditions. CMAQv5.2 regional chemical transport model predictions did not reflect these conditions due to a factor of 3 overestimate of the nonvolatile cations. In addition, gas-phase ammonia was overestimated in the CMAQ model leading to an even lower fraction of total ammonia in the particle. Chemical Speciation Network (CSN) and aerosol mass spectrometer (AMS) measurements indicated less ammonium per sulfate than SEARCH and MARGA measurements and were inconsistent with thermodynamic model predictions. Organic compounds were predicted to be present to some extent in the same phase as inorganic constituents, modifying their activity and resulting in a decrease in [H+]air (H+ in μgm−3 air), increase in ammonia partitioning to the gas phase, and increase in pH compared to complete organic vs. inorganic liquid–liquid phase separation. In addition, accounting for nonideal mixing modified the pH such that a fully interactive inorganic–organic system had a pH roughly 0.7 units higher than predicted using traditional methods (pH = 1.5 vs. 0.7). Particle-phase interactions of organic and inorganic compounds were found to increase partitioning towards the particle phase (vs. gas phase) for highly oxygenated (O : C≥0.6) compounds including several isoprene-derived tracers as well as levoglu-cosan but decrease particle-phase partitioning for low O: C, monoterpene-derived species.

Performance Summary of the 2006 Community Multiscale Air Quality (CMAQ) Simulation for the AQMEII Project: North American Application

The CMAQ modeling system has been used to simulate the CONUS using 12-km by 12-km horizontal grid spacing for the entire year of 2006 as part of the Air Quality Model Evaluation International Initiative (AQMEII). The operational model performance for O3 and PM2.5 for the simulation was assessed. The model underestimates O3 mixing ratios in the winter, which is likely due to low O3 mixing ratios in the middle and lower troposphere from the lateral boundary conditions. PM2.5 performance varies seasonally and geographically, with PM2.5 overestimated in the winter and fall, while performance in the spring and summer is generally good, especially in the summer. PM2.5 concentrations are systematically higher in the AQMEII CMAQ simulation than in previous CMAQ simulations, primarily due to higher concentrations of TC and unspeciated PM2.5 mass, which may also be due to differences in the lateral boundary conditions.

Overview and Evaluation of the Community Multiscale Air Quality (CMAQ) Modeling System Version 5.2

A new version of the Community Multiscale Air Quality (CMAQ) model, version 5.2 (CMAQv5.2), is currently being developed, with a planned release date in 2017. The new model includes numerous updates from the previous version of the model (CMAQv5.1). Specific updates include a new windblown dust scheme; updates to the organic aerosol treatment; updates to the atmospheric chemistry, including the Carbon-Bond 6 chemical mechanism; and various updates to the cloud treatment in the model. In addition, a new lightning assimilation scheme has been implemented in WRF, the meteorological driver for the CMAQ simulations, which greatly improves the placement and intensity of precipitation, which in turn results in improved CMAQ performance. Comparisons between CMAQv5.1 and v5.2 show that ozone (O3) mixing ratios generally increase in the summer with CMAQv5.2, which results in increased bias, while fine particulate matter (PM2.5) concentrations also increase in the summer, which results in decreased bias.

Examining the Impact of an Updated Toluene Mechanism on Air Quality in the Eastern US

Model simulations were performed using the CB05 chemical mechanism containing the base and updated toluene mechanisms for the eastern US. The updated toluene mechanism increased monthly mean 8-h ozone by 1.0–2.0ppbv in urban areas of Chicago, the northeast US, Detroit, Cleveland, and Cincinnati compared to those with the base toluene chemistry. The updated chemistry reduced mean bias and root mean square error in ozone predictions when compared with observations greater than 85ppbv and increased mean secondary organic aerosol from toluene by a maximum of 4%.