An evaluation of CMAQ NO₂ using observed chemistry‐meteorology correlations

Abstract

We evaluate nitrogen dioxide (NO2) simulations from a widely used air quality model, the Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) model, using ground‐ and satellite‐based observations. In addition to direct comparison of modeled and measured variables, we compare the response of NO2 to meteorological conditions and the ability of the model to capture these sensitivities over the continental U.S. during winter and summer periods of 2007. This is the first study to evaluate relationships between NO2 and meteorological variables using satellite data, the first to apply these relationships for model validation, and the first to characterize variability in sensitivities over a wide geographic and temporal scope. We find boundary layer height, wind speed, temperature, and relative humidity to be the most important variables in determining near‐surface NO2 variability. Consistent with earlier studies on NO2‐meteorology relationships, we find that, in general, NO2 responds negatively to planetary boundary height, negatively to wind speed, and negatively to insolation. Unlike previous studies, we find a slight positive association between precipitation and NO2, and we find a consistently positive average association between temperature and NO2. CMAQ agreed with relationships observed in ground‐based data from the EPA Air Quality System and the Ozone Monitoring Instrument over most regions. However, we find that the southwest U.S. is a problem area for CMAQ, where modeled NO2 responses to insolation, boundary layer height, and other variables are at odds with the observations.

Global high-resolution simulations of tropospheric nitrogen dioxide using CHASER V4.0

“…Global CTMs typically have a horizontal resolution of 2-5 • . Meanwhile, high-resolution simulations have been conducted using regional models, which have shown the ability to simulate observed high tropospheric NO 2 columns over major polluted regions such as East Asia, North America, and Europe (e.g., Uno et al, 2007;Kim et al, 2009;Huijnen et al, 2010a;Itahashi et al, 2014;Yamaji et al, 2014;Canty et al, 2015;Han et al, 2015;Harkey et al, 2015). High-resolution simulations can lead to improvements in two ways: (1) through reduced spatial representation gaps between observed and simulated fields and (2) via improved representation of large-scale concentration fields through a consideration of small-scale processes.…”

Evaluating current satellite capability to observe diurnal change in nitrogen oxides in preparation for geostationary satellite missions

“…We also evaluate whether the difference between morning and mid-day NO 2 values are similar between AQS and satellites. Due to the time-lag in peak values between surface and column NO 2 discussed in Fishman et al (2008), and the role of boundary layer height in determining diurnal variability of NO 2 discussed in Song et al (2011) andHarkey et al (2015), we would expect a lower level of agreement for temporal differences than we see for concurrent NO 2 values. Indeed, figure 2(c) shows a relatively weak agreement between diurnal change from satellites and diurnal change at the surface, with summer mean r 2 =0.25.…”

“…Our standard analysis approach allocates GOME-2 and OMI level-2 data products to 0.25°x 0.25°and 0.5°x 0.5°grids using the Wisconsin Horizontal Interpolation Program for Satellites (WHIPS) v2.1 (Harkey et al 2015), which utilizes the NASA OMNO2d gridding algorithm (Bucsela et al 2016). The WHIPS software allows users to apply a cloud filter, and we use only pixels with a cloud fraction less than 0.3.…”

Urban Emissions and Regional Air Quality in India

“…This allows nearly one-to-one comparison between modeled and satellite tropospheric columns. WHIPS has been used previously for model evaluation in numerous air quality studies in the U.S. [Harkey et al, 2015;Kemball-Cook et al, 2015], and here WHIPS is used to process satellite data for air quality model evaluation in India.…”