Urban heat island (UHI) effects can strengthen heat waves and air pollution episodes. In this study, the dampening impact of urban trees on the UHI during an extreme heat wave in the Washington, D.C., and Baltimore, Maryland, metropolitan area is examined by incorporating trees, soil, and grass into the coupled Weather Research and Forecasting model and an urban canopy model (WRF-UCM). By parameterizing the effects of these natural surfaces alongside roadways and buildings, the modified WRF-UCM is used to investigate how urban trees, soil, and grass dampen the UHI. The modified model was run with 50% tree cover over urban roads and a 10% decrease in the width of urban streets to make space for soil and grass alongside the roads and buildings. Results show that, averaged over all urban areas, the added vegetation decreases surface air temperature in urban street canyons by 4.1 K and road-surface and building-wall temperatures by 15.4 and 8.9 K, respectively, as a result of tree shading and evapotranspiration. These temperature changes propagate downwind and alter the temperature gradient associated with the Chesapeake Bay breeze and, therefore, alter the strength of the bay breeze. The impact of building height on the UHI shows that decreasing commercial building heights by 8 m and residential building heights by 2.5 m results in up to 0.4-K higher daytime surface and near-surface air temperatures because of less building shading and up to 1.2-K lower nighttime temperatures because of less longwave radiative trapping in urban street canyons.

An observation-constrained box model based on the Carbon Bond mechanism, version 5 (CB05), was used to study photochemical processes along the NASA P-3B flight track and spirals over eight surface sites during the September 2013 Houston, Texas deployment of the NASA Deriving Information on Surface Conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign. Data from this campaign provided an opportunity to examine and improve our understanding of atmospheric photochemical oxidation processes related to the formation of secondary air pollutants such as ozone (O₃). O₃ production and its sensitivity to NO_x and volatile organic compounds (VOCs) were calculated at different locations and times of day. Ozone production efficiency (OPE), defined as the ratio of the ozone production rate to the NO_x oxidation rate, was calculated using the observations and the simulation results of the box and Community Multiscale Air Quality (CMAQ) models. Correlations of these results with other parameters, such as radical sources and NO_x mixing ratio, were also evaluated. It was generally found that O₃ production tends to be more VOC-sensitive in the morning along with high ozone production rates, suggesting that control of VOCs may be an effective way to control O₃ in Houston. In the afternoon, O₃ production was found to be mainly NO_x-sensitive with some exceptions. O₃ production near major emissions sources such as Deer Park was mostly VOC-sensitive for the entire day, other urban areas near Moody Tower and Channelview were VOC-sensitive or in the transition regime, and areas farther from downtown Houston such as Smith Point and Conroe were mostly NO_x-sensitive for the entire day. It was also found that the control of NO_x emissions has reduced O₃ concentrations over Houston but has led to larger OPE values. The results from this work strengthen our understanding of O₃ production; they indicate that controlling NO_x emissions will provide air quality benefits over the greater Houston metropolitan area in the long run, but in selected areas controlling VOC emissions will also be beneficial.

Regulatory air quality models, such as the Community Multiscale Air Quality model (CMAQ), are used by federal and state agencies to guide policy decisions that determine how to best achieve adherence with National Ambient Air Quality Standards for surface ozone. We use observations of ozone and its important precursor NO₂ to test the representation of the photochemistry and emission of ozone precursors within CMAQ. Observations of tropospheric column NO₂ from the Ozone Monitoring Instrument (OMI), retrieved by two independent groups, show that the model overestimates urban NO₂ and underestimates rural NO₂ under all conditions examined for July and August 2011 in the US Northeast. The overestimate of the urban to rural ratio of tropospheric column NO₂ for this baseline run of CMAQ (CB05 mechanism, mobile NO_x emissions from the National Emissions Inventory; isoprene emissions from MEGAN v2.04) suggests this model may underestimate the importance of interstate transport of NO_x. This CMAQ simulation leads to a considerable overestimate of the 2-month average of 8 h daily maximum surface ozone in the US Northeast, as well as an overestimate of 8 h ozone at AQS sites during days when the state of Maryland experienced NAAQS exceedances. We have implemented three changes within CMAQ motivated by OMI NO₂ as well as aircraft observations obtained in July 2011 during the NASA DISCOVER-AQ campaign: (a) the modeled lifetime of organic nitrates within CB05 has been reduced by a factor of 10, (b) emissions of NO_x from mobile sources has been reduced by a factor of 2, and (c) isoprene emissions have been reduced by using MEGAN v2.10 rather than v2.04. Compared to the baseline simulation, the CMAQ run using all three of these changes leads to considerably better simulation of column NO₂ in both urban and rural areas, better agreement with the 2-month average of daily 8 h maximum ozone in the US Northeast, fewer number of false positives of an ozone exceedance throughout the domain, as well as an unbiased simulation of surface ozone at ground-based AQS sites in Maryland that experienced an ozone exceedance during July and August 2007. These modifications to CMAQ may provide a framework for use in studies focused on achieving future adherence to specific air quality standards for surface ozone by reducing emission of NO_x from various anthropogenic sectors.

The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO₂ at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 10¹⁵ molecules cm⁻². These slant columns are converted to tropospheric NO₂ vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO₂ from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO₂ slightly higher for the most polluted observations. Surface NO₂ mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO₂ measured in situ at the surface during the campaign (r = 0.85). NO₂ slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO₂ is resolvable over areas of traffic NO_x emissions and near individual petrochemical facilities.

The GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS) was developed in support of NASA's decadal survey GEO-CAPE geostationary satellite mission. GCAS is an airborne push-broom remote-sensing instrument, consisting of two channels which make hyperspectral measurements in the ultraviolet/visible (optimized for air quality observations) and the visible–near infrared (optimized for ocean color observations). The GCAS instrument participated in its first intensive field campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign in Texas in September 2013. During this campaign, the instrument flew on a King Air B-200 aircraft during 21 flights on 11 days to make air quality observations over Houston, Texas. We present GCAS trace gas retrievals of nitrogen dioxide (NO₂) and formaldehyde (CH₂O), and compare these results with trace gas columns derived from coincident in situ profile measurements of NO₂ and CH₂O made by instruments on a P-3B aircraft, and with NO₂ observations from ground-based Pandora spectrometers operating in direct-sun and scattered light modes. GCAS tropospheric column measurements correlate well spatially and temporally with columns estimated from the P-3B measurements for both NO₂ (r² = 0.89) and CH₂O (r² = 0.54) and with Pandora direct-sun (r² = 0.85) and scattered light (r² = 0.94) observed NO₂ columns. Coincident GCAS columns agree in magnitude with NO₂ and CH₂O P-3B-observed columns to within 10 % but are larger than scattered light Pandora tropospheric NO₂ columns by 33 % and direct-sun Pandora NO₂ columns by 50 %.