Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

Abstract

<p><strong>Abstract.</strong> The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modelled processes were examined and enhanced to suitably represent the extended space and time scales for such applications. Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. The expansion of CMAQ to simulate the hemispheric scales provides a framework to examine interactions between atmospheric processes occurring at various spatial and temporal scales with physical, chemical, and dynamical consistency.</p>

Modeled Full‐Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution

“…We ran WRF over two stand-alone domains: (1) 108 × 108 km 2 (hereafter denoted as 108 km) northern hemispheric (HEMI, (−15°S to 90°N, −179°W to 179°E)) with a polar stereographic projection and (2) 36 × 36 km 2 (hereafter denoted as 36 km) Contiguous United States (CONUS, (18.3°N to 57.0°N, −136.9°W to −58.8°W)) with a Lambert conformal projection, as shown in Figure 1 . The CMAQ northern hemispheric application (HEMI) is a newer platform with 108 km horizontal resolution that has been used in recent studies ( Mathur et al, 2017 ; Sarwar et al, 2014 ; Xing et al, 2015 ), and this is the first study to use that application for studying the impacts of aircraft emissions. For the CONUS application, we used a traditional North American domain at a 36 km horizontal resolution.…”

“…In this study we investigate the impact of full-flight emissions on surface air quality at hemispheric and regional levels. Here the Community Multi-scale Air Quality (CMAQ) model with a domain covering the entire Northern Hemisphere ( Mathur et al, 2012 , 2017 ) at a horizontal grid cell resolution of 108 × 108 km 2 is used to study the aviation impact. This hemispheric model is ~2–4 times finer than the typical horizontal resolution (4° × 5°, 2° × 2.5°) used in prior global model studies.…”

Assessing PM2.5 model performance for the conterminous U.S. with comparison to model performance statistics from 2007-2015

“…Gas-phase chemistry was represented with the Carbon Bond 2006 mechanism (CB6r3; Emery et al, 2015), inorganic aerosol thermodynamics were based on ISORROPIA II (Fountoukis and Nenes, 2007;Nenes et al, 1998), primary organic aerosol (POA) was modeled as non-volatile (Appel et al, 2017;Simon and Bhave, 2012), and secondary organic aerosol (SOA) from volatile organic compounds was based on Pye et al (2017). Chemical boundary conditions (BCs) were developed from a CMAQ simulation on a larger domain that used BCs based on a hemispheric CMAQ simulation (Mathur et al, 2017). U.S. anthropogenic emissions were based on version 2 of the 2014 national emission inventory (NEI) (USEPA, 2019a).…”

Adding Four Dimensional Data Assimilation by Analysis Nudging to the Model for Prediction Across Scales – Atmosphere (Version 4.0)

“…Air quality models are often applied with relatively coarse horizontal resolution on hemispheric and global scales to provide boundary information for nested, higher-resolution regional models (Bullock et al, 2008;Jacobson and Ginnebaugh, 2010;Schere et al, 2012;Mathur et al, 2014). In various applications, this nested modeling 10 strategy has created unrealistic simulations at the lateral boundaries of internal model domains due to discontinuities in horizontal and vertical resolution and/or differing modeling assumptions between separate models used at each scale (Warner et al, 1997;Bullock et al, 2009;Tudor and Termonia, 2010;Mathur et al, 2017).…”