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Wintertime cold air outbreaks are periods of extreme cold, often persisting for several days and spanning hundreds of kilometers or more. They are commonly associated with intrusions of cold polar air into the midlatitudes, but it is unclear whether the air mass’s initial temperature in the Arctic or its cooling as it travels is the determining factor in producing a cold air outbreak. By calculating air parcel trajectories for a preindustrial climate model scenario, we study the role of the origin and evolution of air masses traveling over sea ice and land and resulting in wintertime cold air outbreaks over central North America. We find that not all Arctic air masses result in a cold air outbreak when advected into the midlatitudes. We compare trajectories that originate in the Arctic and result in cold air outbreaks to those that also originate in the Arctic but lead to median temperatures when advected into the midlatitudes. While about one-third of the midlatitude temperature difference can be accounted for by the initial height and temperature in the Arctic, the other two-thirds are a result of differences in diabatic heating and cooling as the air masses travel. Vertical mixing of cold surface air into the air mass while it travels dominates the diabatic cooling and contributes to the cold events. Air masses leading to cold air outbreaks experience more negative sensible heat flux from the underlying surface, suggesting that preconditioning to establish a cold surface is key to producing cold air outbreaks. Significance Statement Wintertime cold air outbreaks can cause temperatures to plummet tens of degrees below freezing over the northern United States, with the potential to damage agriculture, infrastructure, and human health. Accurate predictions under climate change could help mitigate these effects, but there is disagreement over whether cold air outbreaks have declined in line with the already-observed global warming trend or persisted in spite of it. Focusing on cold air outbreaks that originate from the Arctic, we find that there must be additional cooling of the traveling air mass by mixing with very cold surface air as it moves south over North America in order to result in a cold outbreak.

A series of meteorological measurements with a small Uncrewed Aircraft System (sUAS) was collected at Oliver Springs Airport, Tennessee. The sUAS provides a unique observing system capable of obtaining vertical profiles of meteorological data within the lowest few hundred meters of the boundary layer. The measurements benefit simulated plume predictions by providing more accurate meteorological data to a dispersion model. The sUAS profiles can be used directly to drive HYSPLIT dispersion simulations. When using sUAS data covering a small domain near a release and meteorological model fields covering a larger domain, simulated pollutants may be artificially increased or decreased near the domain boundary due to inconsistencies in the wind fields between the two meteorological inputs. Numerical experiments using the Weather Research and Forecasting (WRF) model with observational nudging reveal that incorporating sUAS data improves simulated wind fields and can significantly affect mixing characteristics of the boundary layer, especially during the morning transition period of the planetary boundary layer. We conducted HYSPLIT dispersion simulations for hypothetical releases for three case study periods using WRF meteorological fields with and without assimilating sUAS measurements. The comparison of dispersion results on 15 and 16 December 2021 shows that using sUAS observational nudging is more significant under weak synoptic conditions than strong influences from regional weather. Very different dispersion results were introduced by the meteorological fields used. The observational nudging produced not just a sUAS-nudged wind flow but also adjusted meteorological fields that further impacted the mixing calculation in HYSPLIT.

The continually changing atmospheric conditions over densely populated coastal urban regions make it challenging to produce models that accurately capture the complex interactions of anthropogenic and environmental emissions, chemical reactions, and unique meteorological processes, such as sea- and land-breeze circulations. The purpose of this study is to determine and identify the influence of synoptic scale wind patterns on the development of local scale sea breeze circulations and air quality over the New York City (NYC) metropolitan area. This study utilizes column integrated nitrogen dioxide observations made during the Long Island Sound Tropospheric Ozone Study (LISTOS) field campaign, ground level ozone observations, the HRRR numerical weather prediction model, and trajectory model simulations using the NOAA HYSPLIT model. A cluster analysis within the HYSPLIT modeling system was performed to determine that there were six unique synoptic scale transport pathways for NYC. Stagnant conditions or weak transport out of the northwest resulted in the worst air quality for NYC. Weak synoptic scale forcings associated with these conditions allowed for local scale sea breeze circulations to develop resulting in air pollution to recirculate and mix with freshly emitted pollutants.

Satellite retrievals of column mass loading of volcanic ash are incorporated into the HYSPLIT transport and dispersion modeling system for source determination, bias correction, and forecast verification of probabilistic ash forecasts of a short eruption of Bezymianny in Kamchatka. The probabilistic forecasts are generated with a dispersion model ensemble created by driving HYSPLIT with 31 members of the NOAA global ensemble forecast system (GEFS). An inversion algorithm is used for source determination. A bias correction procedure called cumulative distribution function (CDF) matching is used to very effectively reduce bias. Evaluation is performed with rank histograms, reliability diagrams, fractions skill score, and precision recall curves. Particular attention is paid to forecasting the end of life of the ash cloud when only small areas are still detectable in satellite imagery. We find indications that the simulated dispersion of the ash cloud does not represent the observed dispersion well, resulting in difficulty simulating the observed evolution of the ash cloud area. This can be ameliorated with the bias correction procedure. Individual model runs struggle to capture the exact placement and shape of the small areas of ash left near the end of the clouds lifetime. The ensemble tends to be overconfident but does capture the range of possibilities of ash cloud placement. Probabilistic forecasts such as ensemble-relative frequency of exceedance and agreement in percentile levels are suited to strategies in which areas with certain concentrations or column mass loadings of ash need to be avoided with a chosen amount of confidence.

Air pollutant emissions estimates by top-down methods are subject to a variety of errors and uncertainties. This work uses a known source, a coal-fired power plant, to explore those errors. The known emissions amount and location remove two major types of error, facilitating understanding of other types. Biases and random errors are distinguished. A Lagrangian dispersion model (HYSPLIT) is run forward in time from the known source, and virtual measurements of the resulting tracer plume are compared to actual measurements from research aircraft. Four flights in different years are used to illustrate a variety of conditions. The measurements are analyzed by a mass-balance method, and the assumptions of that method are discussed. Some of those assumptions can be relaxed in analysis of the modeled plume, allowing testing of their validity. Meteorological fields to drive HYSPLIT are provided by the European Center for Medium Range Weather Forecasts Fifth Reanalysis (ERA5). A unique feature of this work is the use of an ensemble of meteorological fields intrinsic to ERA5. This analysis supports reasonably large (30–40 %) uncertainties on top-down analyses.

NASA's Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011–2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea–United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a factor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori profiles) but mostly to OMI's large footprint (>312 km2).

Cities are greenhouse gas emission hot spots, making them targets for emission reduction policies. Effective emission reduction policies must be supported by accurate and transparent emissions accounting. Top-down approaches to emissions estimation, based on atmospheric greenhouse gas measurements, are an important and complementary tool to assess, improve, and update the emission inventories on which policy decisions are based and assessed. In this study, we present results from 9 research flights measuring CO2 and CH4 around New York City during the nongrowing seasons of 2018–2020. We used an ensemble of dispersion model runs in a Bayesian inverse modeling framework to derive campaign-average posterior emission estimates for the New York–Newark, NJ, urban area of (125 ± 39) kmol CO2 s–1 and (0.62 ± 0.19) kmol CH4 s–1 (reported as mean ± 1σ variability across the nine flights). We also derived emission estimates of (45 ± 18) kmol CO2 s–1 and (0.20 ± 0.07) kmol CH4 s–1 for the 5 boroughs of New York City. These emission rates, among the first top-down estimates for New York City, are consistent with inventory estimates for CO2 but are 2.4 times larger than the gridded EPA CH4 inventory, consistent with previous work suggesting CH4 emissions from cities throughout the northeast United States are currently underestimated.

The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model is a state-of-the-science atmospheric dispersion model that is developed and maintained at the National Oceanic Atmospheric Administration’s (NOAA) Air Resources Laboratory (ARL). In the early 2000s, HYSPLIT served as the starting point for development of the Stochastic Time-Inverted Lagrangian Transport (STILT) model that emphasizes backward-in-time dispersion simulations to determine source regions of receptors. STILT continued its separate development and gained a wide user base. Since STILT was built on a now outdated version of HYSPLIT and lacks long-term institutional support to maintain the model, incorporating STILT features into HYSPLIT allows these features to stay up to date. This paper describes the STILT features incorporated into HYSPLIT, which include: a new vertical interpolation algorithm for WRF derived meteorological input files, a detailed algorithm for estimating boundary layer height, a new turbulence parameterization, a vertical Lagrangian timescale that varies in time and space, a complex dispersion algorithm, and two new convection schemes. An evaluation of these new features was performed using tracer release data from the Cross Appalachian Tracer Experiment and the Across North America Tracer Experiment. Results show the dispersion module from STILT, which takes up to double the amount of time to run, is less dispersive in the vertical and in better agreement with observations than the existing HYSPLIT option. The other new modeling features from STILT were not consistently statistically different than existing HYSPLIT options. Forward-time simulations from the new model were also compared against backward-time equivalents and found to be statistically comparable to one another.

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 %.

This work presents a new high-resolution NO2 dataset derived from the NASA Ozone Monitoring Instrument (OMI) NO2 version 3.0 retrieval that can be used to estimate surface-level concentrations. The standard NASA product uses NO2 vertical profile shape factors from a 1.25° × 1° (∼ 110 km × 110 km) resolution Global Model Initiative (GMI) model simulation to calculate air mass factors, a critical value used to determine observed tropospheric NO2 vertical columns. To better estimate vertical profile shape factors, we use a high-resolution (1.33 km × 1.33 km) Community Multi-scale Air Quality (CMAQ) model simulation constrained by in situ aircraft observations to recalculate tropospheric air mass factors and tropospheric NO2 vertical columns during summertime in the eastern US. In this new product, OMI NO2 tropospheric columns increase by up to 160 % in city centers and decrease by 20–50 % in the rural areas outside of urban areas when compared to the operational NASA product. Our new product shows much better agreement with the Pandora NO2 and Airborne Compact Atmospheric Mapper (ACAM) NO2 spectrometer measurements acquired during the DISCOVER-AQ Maryland field campaign. Furthermore, the correlation between our satellite product and EPA NO2 monitors in urban areas has improved dramatically: r2 = 0.60 in the new product vs. r2 = 0.39 in the operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use both high-resolution and high-fidelity models in order to recalculate satellite data in areas with large spatial heterogeneities in NOx emissions. Although the current work is focused on the eastern US, the methodology developed in this work can be applied to other world regions to produce high-quality region-specific NO2 satellite retrievals.

Nitrogen dioxide (NO2) is a short-lived atmospheric pollutant that serves as an air quality indicator, and is itself a health concern. The Airborne Compact Atmospheric Mapper (ACAM) was flown on board the NASA UC-12 aircraft during the DISCOVER-AQ Maryland field campaign in July 2011. The instrument collected hyperspectral remote sensing measurements in the 304-910 nm range, allowing day-time observations of several tropospheric pollutants, including nitrogen dioxide (NO2), at an unprecedented spatial resolution of 1.5 × 1.1 km2. Retrievals of slant column abundance are based on the Differential Optical Absorption Spectroscopy (DOAS) method. For the Air Mass Factor (AMF) computations needed to convert these retrievals to vertical column abundance, we include high resolution information for the surface reflectivity by using bidirectional reflectance distribution function (BRDF) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). We use high-resolution simulated vertical distributions of NO2 from the Community Multiscale Air Quality (CMAQ) and Global Modeling Initiative (GMI) models to account for the temporal variation in atmospheric NO2 to retrieve middle- and lower-tropospheric NO2 columns (NO2 below the aircraft). We compare NO2 derived from ACAM measurements with in-situ observations from NASA's P-3B research aircraft, total column observations from the ground-based Pandora spectrometers, and tropospheric column observations from the space-based OMI instrument. The high-resolution ACAM measurements not only give new insights into our understanding of atmospheric composition and chemistry through observation of sub-sampling variability in typical satellite and model resolutions, but they also provide opportunities for testing algorithm improvements for forthcoming geostationary air quality missions.

Highly-resolved vertical profiles of ozone and reactive nitrogen in the lower troposphere were obtained using Millersville University's tethered balloon system and NASA's P-3B aircraft during the July 2011 Baltimore, MD/Washington DC and the September 2013 Houston, TX deployments of the NASA DISCOVER-AQ air quality field mission. The tethered balloon and surface measurement sites were located at Edgewood, MD and Smith Point, TX. The balloon profiles are used to connect aircraft data from the lowest portion of NASA's P-3B spirals (300 m AGL) to the surface thus creating complete profiles from the surface to 3–5 km AGL. The highest concentrations of surface ozone at these coastal sites resulted from mean flow transport of polluted air over an adjacent body of water followed by advection back over land several hours later, due to a bay or gulf breeze. Several meteorological processes including horizontal advection, vertical mixing, thermally direct circulation (i.e., bay, gulf, and, sea breezes) combined with chemical processes like photochemical production and deposition played a role in the local ozone maxima. Several small-scale, but highly polluted layers from the Chesapeake Bay advected landward over Edgewood, MD. The Houston Metro area was subject to large-scale recirculation of emissions from petrochemical sources by the Gulf of Mexico and Galveston Bay breezes.

Using the Community Multiscale Air Quality (CMAQ) model and the Benefits Mapping and Analysis Program - Community Edition (BenMAP-CE) tool, we estimate the benefits of anthropogenic emission reductions between 2002 and 2011 in the Eastern United States (US) with respect to surface ozone concentrations and ozone-related health and economic impacts, during a month of extreme heat, July 2011. Based on CMAQ simulations using emissions appropriate for 2002 and 2011, we estimate that emission reductions since 2002 likely prevented 10- 15 ozone exceedance days (using the 2011 maximum 8-hr average ozone standard of 75 ppbv) throughout the Ohio River Valley and 5- 10 ozone exceedance days throughout the Washington, DC - Baltimore, MD metropolitan area during this extremely hot month. CMAQ results were fed into the BenMAP-CE tool to determine the health and health-related economic benefits of anthropogenic emission reductions between 2002 and 2011. We estimate that the concomitant health benefits from the ozone reductions were significant for this anomalous month: 160-800 mortalities (95% confidence interval (CI): 70-1,010) were avoided in July 2011 in the Eastern U.S, saving an estimated $1.3-$6.6 billion (CI: $174 million-$15.5 billion). Additionally, we estimate that emission reductions resulted in 950 (CI: 90-2,350) less hospital admissions from respiratory symptoms, 370 (CI: 180-580) less hospital admissions for pneumonia, 570 (CI: 0-1650) less Emergency Room (ER) visits from asthma symptoms, 922,020 (CI: 469,960-1,370,050) less minor restricted activity days (MRADs), and 430,240 (CI: -280,350-963,190) less symptoms of asthma exacerbation during July 2011.Implications: We estimate the benefits of air pollution emission reductions on surface ozone concentrations and ozone-related impacts on human health and the economy between 2002 and 2011 during an extremely hot month, July 2011, in the eastern United States (US) using the CMAQ and BenMAP-CE models. Results suggest that, during July 2011, emission reductions prevented 10-15 ozone exceedance days in the Ohio River Valley and 5-10 ozone exceedance days in the Mid Atlantic; saved 160-800 lives in the Eastern US, saving $1.3 - $6.5 billion; and resulted in 950 less hospital admissions for respiratory symptoms, 370 less hospital admissions for pneumonia, 570 less Emergency Room visits for asthma symptoms, 922,020 less minor restricted activity days, and 430,240 less symptoms of asthma exacerbation.

NASA’s Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea-United States Air Quality Study (KORUS-AQ) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with a goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique data sets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a-priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 33.3 %. These show even larger differences with Pandora, reaching up to 53.1 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a factor of two lower in these highly polluted environments, due in part to inaccurate retrieval assumptions (e.g., a priori profiles), but mostly to OMI’s areal (> 312 km2) averaging.

Ozone production efficiency (OPE) represents the number of ozone (O3) molecules produced per molecule of NOx (NO2+NO), before NOx is converted to a sink or reservoir species. Observations from NASA's July 2011 DISCOVER-AQ (D-AQ) campaign in the Baltimore-Washington region are used to quantify OPE, which is compared to output from the Community Multiscale Air Quality (CMAQ) model. The baseline model run of CMAQ (CB05-TUCL mechanism; mobile NOx emissions from the National Emissions Inventory; biogenic emissions from BEIS model v3.61) underestimates observed OPE by 34 ± 20%. The payload of D-AQ lacked direct observations of HO2 and RO2, so we infer the rate at which these peroxy radicals react with NO (termed inROx) from observations of NO, NO2, O3, and j(NO2). The baseline run of CMAQ underestimates inROx by 35 ± 19%. A modified run of CMAQ with a factor of 10 reduction in the lifetime of organic nitrates, a factor of 2 reduction in mobile NOx emissions, an update to the thermal dissociation rate of PAN and PANX to the IUPAC 2014 value, and a correction for the rate constant for OH + PANX results in better overall model performance based on a number of comparisons to data that include column NO2 measured by the Ozone Monitoring Instrument, a value of OPE that is 21 ± 13% less than observed, and inROx that is low by 30 ± 19%. Sensitivity analysis indicates that the peroxy radical discrepancy involves either emission of VOCs other than isoprene or HCHO, or a problem with the model production of HO2 and RO2. Our analysis suggests surface O3 may exhibit stronger declines to further reductions of NOx than is indicated by baseline runs of CMAQ. Index terms: Troposphere: constituent transport and chemistry. Keywords: Air quality, Surface ozone, CMAQ, Ozone production efficiency

To investigate the variability of in situ profile shapes under a variety of meteorological and pollution conditions, results are presented of an agglomerative hierarchical cluster analysis of the in situ O3 and NO2 profiles for each of the four campaigns of the NASA DISCOVER-AQ mission. Understanding the observed profile variability for these trace gases is useful for understanding the accuracy of the assumed profile shapes used in satellite retrieval algorithms as well as for understanding the correlation between satellite column observations and surface concentrations. The four campaigns of the DISCOVER-AQ mission took place in Maryland during July 2011, the San Joaquin Valley of California during January–February 2013, the Houston, Texas, metropolitan region during September 2013, and the Denver-Front Range region of Colorado during July–August 2014. Several distinct profile clusters emerged for the California, Texas, and Colorado campaigns for O3, indicating significant variability of O3 profile shapes, while the Maryland campaign presented only one distinct O3 cluster. In contrast, very few distinct profile clusters emerged for NO2 during any campaign for this particular clustering technique, indicating the NO2 profile behavior was relatively uniform throughout each campaign. However, changes in NO2 profile shape were evident as the boundary layer evolved through the day, but they were apparently not significant enough to yield more clusters. The degree of vertical mixing (as indicated by temperature lapse rate) associated with each cluster exerted an important influence on the shapes of the median cluster profiles for O3, as well as impacted the correlations between the associated column and surface data for each cluster for O3. The correlation analyses suggest satellites may have the best chance to relate to surface O3 under the conditions encountered during the Maryland campaign Clusters 1 and 2, which include deep, convective boundary layers and few interruptions to this connection from complex meteorology, chemical environments, or orography. The regional CMAQ model captured the shape factors for O3, and moderately well captured the NO2 shape factors, for the conditions associated with the Maryland campaign, suggesting that a regional air quality model may adequately specify a priori profile shapes for remote sensing retrievals. CMAQ shape factor profiles were not as well represented for the other regions.

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 moleculescm−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 NOx 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 pushbroom 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) 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 %.

Measures to control surface ozone rely on quantifying production attributable to local versus regional (upwind) emissions. Here we simulate the relative contribution of local (i.e., within a particular state) and regional sources of surface ozone in the eastern United States (66–94°W longitude) for July 2002, 2011, and 2018 using the Comprehensive Air-quality Model with Extensions (CAMx). To determine how emissions and chemistry within the domain affect the production, loss, lifetime, and transport of trace gases, we initialize our model with identical boundary conditions in each simulation. We find that the photochemical lifetime of ozone has increased as emissions have decreased. The contribution of ozone from outside the domain (boundary condition ozone, BCO3) to local surface mixing ratios increases in an absolute sense by 1–2 ppbv between 2002 and 2018 due to the longer lifetime of ozone. The photochemical lifetime of ozone lengthens because the two primary gas phase sinks for odd oxygen (Ox ≈ NO2 + O3)—attack by hydroperoxyl radicals (HO2) on ozone and formation of nitrate—weaken with decreasing pollutant emissions. The relative role of BCO3 will also increase. For example, BCO3 represents 34.5%, 38.8%, and 43.6% of surface ozone in the Baltimore, MD, region during July 2002, 2011, and 2018 means, respectively. This unintended consequence of air quality regulation impacts attainment of the National Ambient Air Quality Standard for surface ozone because the spatial and temporal scales of photochemical smog increase; the influence of pollutants transported between states and into the eastern U.S. will likely play a greater role in the future.

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 NOx emissions from the National Emissions Inventory; isoprene emissions from MEGAN v2.04) suggests this model may underestimate the importance of interstate transport of NOx. 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 NOx 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 NOx from various anthropogenic sectors.

We quantify both the spatial and temporal variability of column integrated O3, NO2, CO, SO2, and HCHO over the Baltimore/Washington, DC area using output from the Weather Research and Forecasting model with on-line chemistry (WRF/Chem) for the entire month of July 2011, coinciding with the first deployment of the NASA Earth Venture program mission Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Using structure function analyses, we find that the model reproduces the spatial variability observed during the campaign reasonably well, especially for O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument will be the first NASA mission to make atmospheric composition observations from geostationary orbit and partially fulfills the goals of the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. We relate the simulated variability to the precision requirements defined by the science traceability matrices of these space-borne missions. Results for O3 from 0 to 2 km altitude indicate that the TEMPO instrument would be able to observe O3 air quality events over the Mid-Atlantic area, even on days when the violations of the air quality standard are not widespread. The results further indicated that horizontal gradients in CO from 0 to 2 km would be observable over moderate distances (≥20 km). The spatial and temporal results for tropospheric column NO2 indicate that TEMPO would be able to observe not only the large urban plumes at times of peak production, but also the weaker gradients between rush hours. This suggests that the proposed spatial and temporal resolutions for these satellites as well as their prospective precision requirements are sufficient to answer the science questions they are tasked to address.

This work presents a new high resolution NO2 dataset derived from the standard NASA Ozone Monitoring Instrument (OMI) NO2 version 3.0 retrieval that can be used to estimate surface level concentrations. The standard NASA product uses NO2 vertical profile shape factors from a 1.25° × 1° (~ 110 × 110 km) resolution Global Model Initiative (GMI) model simulation to calculate air mass factors, a critical value used to determine observed tropospheric NO2 vertical columns. To better estimate vertical profile shape factors, we use a high resolution Community Multi-scale Air Quality (CMAQ) model simulation (1.33 × 1.33 km) to generate tropospheric air mass factors and tropospheric NO2 columns during summertime in the eastern United States. Results show OMI NO2 tropospheric columns in this new product increase by up to 160 % in city centers, and decrease by 20–50 % in the rural areas outside of urban areas when compared to the operational product. This new product shows much better agreement with the Pandora NO2 spectrometer measurements acquired during the DISCOVER-AQ Maryland field campaign. Furthermore, the correlation between this satellite product and EPA NO2 monitors in urban areas has improved dramatically: r2 = 0.60 in new product, r2 = 0.39 in operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use high resolution models to re-calculate satellite data in areas with large spatial heterogeneities in NOx emissions. Although the current work is focused on the eastern United States, the methodology developed in this work can be applied to other world regions to produce high-quality region-specific NO2 satellite retrievals.

Data collected during the 2011 DISCOVER-AQ field campaign in the Baltimore Washington region were used to evaluate CO and NO x emissions in the National Emissions Inventory (NEI). The average emissions ratio for the region was seen to be 11.2 ± 1.2 mol CO/mol NO x , 21% higher than that predicted by the NEI. Comparisons between in situ and remote observations and CMAQ model output show agreement in CO emissions of 15 ± 11% while NO x emissions are overestimated by 51–70% in Maryland. Satellite observations of CO by MOPITT show agreement with the Community Multiscale Air Quality (CMAQ) model within 3% over most of the eastern United States. CMAQ NO y mixing ratios were a factor of two higher than observations and result from a combination of errors in emissions and PAN and alkyl nitrate chemistry, as shown by comparison of three CMAQ model runs. Point source NO x emissions are monitored and agree with modeled emissions within 1% on a monthly basis. Because of this accuracy and the NEI assertion that approximately 3/4 of emissions in the Baltimore Washington region are from mobile sources, the MOVES model's treatment of emissions from aging vehicles should be investigated; the NEI overestimate of NO x emissions could indicate that engines produce less NO x and catalytic converters degrade more slowly than assumed by MOVES2010. The recently released 2011 NEI has an even lower CO/NO x emissions ratio than the projection used in this study; it overestimates NO x emissions by an even larger margin. The implications of these findings for US air quality policy are that NO x concentrations near areas of heavy traffic are overestimated and ozone production rates in these locations are slower than models indicate. Results also indicate that ambient ozone concentrations will respond more efficiently to NO x emissions controls but additional sources may need to be targeted for reductions.

We use a 3-D regional atmospheric chemistry transport model (WRF-Chem) to examine ozone dry deposition in East Asia, which is an important but uncertain research area because of insufficient observation and numerical studies focusing on East Asia. Here we compare two widely used dry deposition parameterization schemes, the Wesely and M3DRY schemes, which are used in the WRF-Chem and Community Multiscale Air Quality (CMAQ) models, respectively. Simulated ozone dry deposition velocities with the two schemes under identical meteorological conditions show considerable differences (a factor of 2) owing to surface resistance parameterization discrepancies. Resulting ozone concentrations differ by up to 10 ppbv for a monthly mean in May when the peak ozone typically occurs in East Asia. An evaluation of the simulated dry deposition velocities shows that the Wesely scheme calculates values with more pronounced diurnal variation than the M3DRY and results in a good agreement with the observations. However, we find significant changes in simulated ozone concentrations using the Wesely scheme but with different surface type data sets, indicating the high sensitivity of ozone deposition calculations to the input data. The need is high for observations to constrain the dry deposition parameterization and its input data to improve the use of air quality models for East Asia.

To investigate the ability of column (or partial column) information to represent surface air quality, results of linear regression analyses between surface mixing ratio data and column abundances for O3 and NO2 are presented for the July 2011 Maryland deployment of the DISCOVER-AQ mission. Data collected by the P-3B aircraft, ground-based Pandora spectrometers, Aura/OMI satellite instrument, and simulations for July 2011 from the CMAQ air quality model during this deployment provide a large and varied data set, allowing this problem to be approached from multiple perspectives. O3 columns typically exhibited a statistically significant and high degree of correlation with surface data (R(sup 2) > 0.64) in the P- 3B data set, a moderate degree of correlation (0.16 < R(sup 2) < 0.64) in the CMAQ data set, and a low degree of correlation (R(sup 2) < 0.16) in the Pandora and OMI data sets. NO2 columns typically exhibited a low to moderate degree of correlation with surface data in each data set. The results of linear regression analyses for O3 exhibited smaller errors relative to the observations than NO2 regressions. These results suggest that O3 partial column observations from future satellite instruments with sufficient sensitivity to the lower troposphere can be meaningful for surface air quality analysis.

Meteorological and air-quality model simulations are analyzed alongside observations to investigate the role of the Chesapeake Bay breeze on surface air quality, pollutant transport, and boundary layer venting. A case study was conducted to understand why a particular day was the only one during an 11-day ship-based field campaign on which surface ozone was not elevated in concentration over the Chesapeake Bay relative to the closest upwind site and why high ozone concentrations were observed aloft by in situ aircraft observations. Results show that southerly winds during the overnight and early-morning hours prevented the advection of air pollutants from the Washington, D.C., and Baltimore, Maryland, metropolitan areas over the surface waters of the bay. A strong and prolonged bay breeze developed during the late morning and early afternoon along the western coastline of the bay. The strength and duration of the bay breeze allowed pollutants to converge, resulting in high concentrations locally near the bay-breeze front within the Baltimore metropolitan area, where they were then lofted to the top of the planetary boundary layer (PBL). Near the top of the PBL, these pollutants were horizontally advected to a region with lower PBL heights, resulting in pollution transport out of the boundary layer and into the free troposphere. This elevated layer of air pollution aloft was transported downwind into New England by early the following morning where it likely mixed down to the surface, affecting air quality as the boundary layer grew.

Urban nearshore regions are characterized by strong variability in atmospheric composition, associated with anthropogenic emissions and meteorological processes that influence the circulation and accumulation of atmospheric pollutants at the land-water interface. If not adequately corrected in satellite retrievals of ocean color, this atmospheric variability can impose a false impression of diurnal and seasonal changes in nearshore water quality and biogeochemical processes. Consideration of these errors is important for measurements from polar orbiting ocean color sensors but becomes critical for geostationary satellite missions having the capability for higher frequency and higher spatial resolution observations of coastal ocean dynamics. We examined variability in atmospheric NO2 over urban nearshore environments in the Eastern US, Europe, and Korea, using a new network of ground-based Pandora spectrometers and Aura-OMI satellite observations. Our measurements in the US and in Europe revealed clear diurnal and day-of-the-week patterns in total column NO2 (TCNO2), temporal changes as large as 0.8 DU within 4 h, and spatial variability as large as 0.7 DU within an area often covered by just a single OMI pixel. TCNO2 gradients were considerably stronger over the coastal cities of Korea. With a coarse resolution and an overpass at around 13:30 local time, OMI cannot detect this strong variability in NO2, missing pollution peaks from industrial and rush hour activities. Observations were combined with air quality model simulations and radiative transfer calculations to estimate the impact of atmospheric NO2 variability on satellite retrievals of coastal ocean remote sensing reflectance and biogeochemical variables (i.e., chlorophyll and CDOM).

During a classic heat wave with record high temperatures and poor air quality from July 18 to 23, 2011, an elevated reservoir of air pollutants was observed over and downwind of Baltimore, MD, with relatively clean conditions near the surface. Aircraft and ozonesonde measurements detected approximately 120 parts per billion by volume ozone at 800 meters altitude, but approximately 80 parts per billion by volume ozone near the surface. High concentrations of other pollutants were also observed around the ozone peak: approximately 300 parts per billion by volume CO at 1200 meters, approximately 2 parts per billion by volume NO2 at 800 meters, approximately 5 parts per billion by volume SO2 at 600 meters, and strong aerosol optical scattering (2 x 10 (sup 4) per meter) at 600 meters. These results suggest that the elevated reservoir is a mixture of automobile exhaust (high concentrations of O3, CO, and NO2) and power plant emissions (high SO2 and aerosols). Back trajectory calculations show a local stagnation event before the formation of this elevated reservoir. Forward trajectories suggest an influence on downwind air quality, supported by surface ozone observations on the next day over the downwind PA, NJ and NY area. Meteorological observations from aircraft and ozonesondes show a dramatic veering of wind direction from south to north within the lowest 5000 meters, implying that the development of the elevated reservoir was caused in part by the Chesapeake Bay breeze. Based on in situ observations, Community Air Quality Multi-scale Model (CMAQ) forecast simulations with 12 kilometers resolution overestimated surface ozone concentrations and failed to predict this elevated reservoir; however, CMAQ research simulations with 4 kilometers and 1.33 kilometers resolution more successfully reproduced this event. These results show that high resolution is essential for resolving coastal effects and predicting air quality for cities near major bodies of water such as Baltimore on the Chesapeake Bay and downwind areas in the Northeast.

Air quality models, such as the Community Multiscale Air Quality (CMAQ) model, indicate decidedly higher ozone near the surface of large interior water bodies, such as the Great Lakes and Chesapeake Bay. In order to test the validity of the model output, we performed surface measurements of ozone (O3) and total reactive nitrogen (NOy) on the 26-m Delaware II NOAA Small Research Vessel experimental (SRVx), deployed in the Chesapeake Bay for 10 daytime cruises in July 2011 as part of NASA’s GEO-CAPE CBODAQ oceanographic field campaign in conjunction with NASA’s DISCOVER-AQ air quality field campaign. During this 10-day period, the EPA O3 regulatory standard of 75 ppbv averaged over an 8-h period was exceeded four times over water while ground stations in the area only exceeded the standard at most twice. This suggests that on days when the Baltimore/Washington region is in compliance with the EPA standard, air quality over the Chesapeake Bay might exceed the EPA standard. Ozone observations over the bay during the afternoon were consistently 10e20% higher than the closest upwind ground sites during the 10-day campaign; this pattern persisted during good and poor air quality days. A lower boundary layer, reduced cloud cover, slower dry deposition rates, and other lesser mechanisms, contribute to the local maximum of ozone over the Chesapeake Bay. Observations from this campaign were compared to a CMAQ simulation at 1.33 km resolution. The model is able to predict the regional maximum of ozone over the Chesapeake Bay accurately, but NOy concentrations are significantly overestimated. Explanations for the overestimation of NOy in the model simulations are also explored.

Spatial and temporal dynamics in trace gas pollutants were examined over a major urban estuarine ecosystem, using a new network of ground-based Pandora spectrometers deployed at strategic locations along the Washington-Baltimore corridor and the Chesapeake Bay. Total column ozone (TCO3) and nitrogen dioxide (TCNO2) were measured during NASA’s DISCOVER-AQ and GeoCAPE-CBODAQ campaigns in July 2011. The Pandora network provided high-resolution information on air-quality variability, local pollution conditions, large-scale meteorological influences, and interdependencies of ozone and its major precursor, NO2. Measurements were used to compare with air-quality model simulations (CMAQ), evaluate Aura-OMI satellite retrievals, and assess advantages and limitations of space-based observations under a range of conditions. During the campaign, TCNO2 varied by an order of magnitude, both spatially and temporally. Although fairly constant in rural regions, TCNO2 showed clear diurnal and weekly patterns in polluted urban areas caused by changes in near-surface emissions. With a coarse resolution and an overpass at around 13:30 local time, OMI cannot detect this strong variability in NO2, missing pollution peaks from industrial and rush hour activities. Not as highly variable as NO2, TCO3 was mostly affected by large-scale meteorological patterns as observed by OMI. A clear weekly cycle in TCO3, with minima over the weekend, was due to a combination of weekly weather patterns and changes in near-surface NOx emissions. A Pandora instrument intercomparison under the same conditions at GSFC showed excellent agreement, within ±4.8DU for TCO3 and ±0.07DU for TCNO2 with no air-mass-factor dependence, suggesting that observed variability during the campaign was real.

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 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 NOx and 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 NOx 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 NOx 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 NOx sensitive with some exceptions. O3 production at 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 NOx sensitive for the entire day. It was also found that the control of NOx emissions has reduced O3 concentrations over Houston, but led to larger OPE values. The results from this work strengthen our understanding of O3 production; they indicate that controlling NOx 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.

Mercury contamination in the Great Lakes continues to have important public health and wildlife ecotoxicology impacts, and atmospheric deposition is a significant ongoing loading pathway. The objective of this study was to estimate the amount and source-attribution for atmospheric mercury deposition to each lake, information needed to prioritize amelioration efforts. A new global, Eulerian version of the HYSPLIT-Hg model was used to simulate the 2005 global atmospheric transport and deposition of mercury to the Great Lakes. In addition to the base case, 10 alternative model configurations were used to examine sensitivity to uncertainties in atmospheric mercury chemistry and surface exchange. A novel atmospheric lifetime analysis was used to characterize fate and transport processes within the model. Model-estimated wet deposition and atmospheric concentrations of gaseous elemental mercury (Hg(0)) were generally within ∼10% of measurements in the Great Lakes region. The model overestimated non-Hg(0) concentrations by a factor of 2–3, similar to other modeling studies. Potential reasons for this disagreement include model inaccuracies, differences in atmospheric Hg fractions being compared, and the measurements being biased low. Lake Erie, downwind of significant local/regional emissions sources, was estimated by the model to be the most impacted by direct anthropogenic emissions (58% of the base case total deposition), while Lake Superior, with the fewest upwind local/regional sources, was the least impacted (27%). The U.S. was the largest national contributor, followed by China, contributing 25% and 6%, respectively, on average, for the Great Lakes. The contribution of U.S. direct anthropogenic emissions to total mercury deposition varied between 46% for the base case (with a range of 24–51% over all model configurations) for Lake Erie and 11% (range 6–13%) for Lake Superior. These results illustrate the importance of atmospheric chemistry, as well as emissions strength, speciation, and proximity, to the amount and source-attribution of mercury deposition.

Surface ozone (O3) was analyzed to investigate the role of the bay breeze on air quality at two locations in Edgewood, Maryland (lat: 39.4°, lon: −76.3°) for the month of July 2011. Measurements were taken as part of the first year of NASA’s “Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality” (DISCOVER-AQ) Earth Venture campaign and as part of NASA’s Geostationary for Coastal and Air Pollution Events Chesapeake Bay Oceanographic campaign with DISCOVER-AQ (Geo-CAPE CBODAQ). Geo-CAPE CBODAQ complements DISCOVER-AQ by providing ship-based observations over the Chesapeake Bay. A major goal of DISCOVER-AQ is determining the relative roles of sources, photochemistry and local meteorology during air quality events in the Mid-Atlantic region of the U.S. Surface characteristics, transport and vertical structures of O3 during bay breezes were identified using in-situ surface, balloon and aircraft data, along with remote sensing equipment. Localized late day peaks in O3 were observed during bay breeze days, maximizing an average of 3 h later compared to days without bay breezes. Of the 10 days of July 2011 that violated the U.S. Environmental Protection Agency (EPA) 8 h O3 standard of 75 parts per billion by volume (ppbv) at Edgewood, eight exhibited evidence of a bay breeze circulation. The results indicate that while bay breezes and the processes associated with them are not necessary to cause exceedances in this area, bay breezes exacerbate poor air quality that sustains into the late evening hours at Edgewood. The vertical and horizontal distributions of O3 from the coastal Edgewood area to the bay also show large gradients that are often determined by boundary layer stability. Thus, developing air quality models that can sufficiently resolve these dynamics and associated chemistry, along with more consistent monitoring of O3 and meteorology on and along the complex coastline of Chesapeake Bay must be a high priority.

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.

Two fine-scale meteorological processes, fair-weather cumulus cloud development and a bay breeze, are examined along with their impacts on air chemistry. The impact of model resolution on fair-weather cumulus cloud development, transport of pollutants through clouds, sulfur dioxide to sulfate conversion in clouds, and the development of the Chesapeake Bay breeze are examined via 13.5, 4.5, 1.5, and 0.5 km resolution simulations covering the Washington – Baltimore area. Results show that as the resolution increases, more pollutants are transported aloft through fair-weather cumulus clouds causing an increase in the rate of oxidation of sulfur dioxide to sulfate aerosols. The high resolution model runs more nearly match observations of a local pollutant maximum near the top of the boundary layer and produce an increase in boundary layer venting with subsequent pollutant export. The sensitivity of sulfur dioxide to sulfate conversion rates to cloud processing is examined by comparing sulfur dioxide and sulfate concentrations from simulations that use two different methods to diagnose clouds. For this particular event, a diagnostic method produces the most clouds and the most realistic cloud cover, has the highest oxidation rates, and generates sulfur dioxide and sulfate concentrations that agree best with observations. The differences between the simulations show the importance of accurately simulating clouds in sulfate simulations. The fidelity of the model’s representation of the bay breeze is examined as a function of resolution. As the model resolution increases, a larger temperature gradient develops along the shoreline of the Chesapeake Bay causing the bay breeze to form sooner, push farther inland, and loft more pollutants upward. This stronger bay breeze results in low-level convergence, a buildup of near surface ozone over land and a decrease in the land-to-sea flux of ozone and ozone precursors as seen in measurements. The resulting 8 h maximum ozone concentration over the Bay is 10 ppbv lower in the 0.5 km simulation than in the 13.5 km simulation.

Satellite observations have the potential to provide an accurate picture of atmospheric chemistry and air quality on a variety of spatial and temporal scales. A key consideration in the design of new instruments is the spatial resolution required to effectively monitor air quality from space. In this paper, variograms have been used to address this issue by calculating the horizontal length scales of ozone within the boundary layer and free troposphere using both in situ aircraft data from five different NASA aircraft campaigns and simulations with an air-quality model. For both the observations and the model, the smallest scale features were found in the boundary layer, with a characteristic scale of about 50 km which increased to greater than 150 km above the boundary layer. The length scale changes with altitude. It is shown that similar length scales are derived based on a totally independent approach using constituent lifetimes and typical wind speeds. To date, the spaceborne observations of tropospheric constituents have been from several instruments including TOMS, GOME, MOPITT, TES, and OMI which, in general, have different weighting functions that need to be considered, and none really measures at the surface. A further complication is that most satellite measurements (such as those of OMI and GOME) are of the vertically integrated column. In this paper, the length scales in the column measurements were also of the order of 50 km. To adequately resolve the 50-km features, a horizontal resolution of at least 10 km would be desirable

SO2 in central China was measured in situ from an aircraft and remotely using the Ozone Monitoring Instrument (OMI) from the Aura satellite; results were used to develop a numerical tool for evaluating the tropospheric sulfur budget - sources, sinks, transformation and transport. In April 2008, measured ambient SO2 concentrations decreased from approx.7 ppbv near the surface to approx. 1 ppbv at 1800 m altitude (an effective scale height of approx.800 m), but distinct SO2 plumes were observed between 1800 and 4500 m, the aircraft's ceiling. These free tropospheric plumes play a major role in the export of SO2 and in the accuracy of OMI retrievals. The mean SO2 column contents from aircraft measurements (0.73 DU, Dobson Units) and operational OMI SO2 products (0.63+/-0.26 DU) were close. The OMI retrievals were well correlated with in situ measurements (r = 0.84), but showed low bias (slope = 0.54). A new OMI retrieval algorithm was tested and showed improved agreement and bias (r = 0.87, slope = 0.86). The Community Multiscale Air Quality (CMAQ) model was used to simulate sulfur chemistry, exhibiting reasonable agreement (r = 0.62, slope = 1.33) with in situ SO2 columns. The mean CMAQ SO2 loading over central and eastern China was 54 kT, approx.30% more than the estimate from OMI SO2 products, 42 kT. These numerical simulations, constrained by observations, indicate that ",50% (35 to 61 %) of the anthropogenic sulfur emissions were transported downwind, and the overall lifetime of tropospheric SO2 was 38+/-7 h.

[1] On 8–11 July 2007 the eastern United States experienced a severe heat wave and smog event with maximum temperatures approaching 38°C and maximum 8 h average ozone mixing ratios of 125 ppbv. We examine this episode with observations and numerical simulations using the Weather Research and Forecasting model with online chemistry (WRF/Chem with RADM2). The general features of this severe smog event–a broad area of high pressure, weak winds and heavy pollution, terminated by the passage of a cold front–were well simulated by the model. WRF/Chem underpredicted O3 maxima by 5–8 ppbv where air quality was poor, usually in the northeast, but overpredicted maxima by up to 16 ppbv where ozone amounts were low, usually in the southeast. Simulated O3 vertical profiles over Beltsville, Maryland, showed good agreement with ozonesonde measurements, but the model boundary layer was too deep on 9 July, contributing to the low bias over this region. The representation of NOx chemistry in RADM2 may lead to an underestimation of NOx lifetime and is likely partially responsible for low O3 biases in the most polluted area in the northeast. To simulate the maximum effect of nighttime multiphase NOy loss, we set the N2O5 heterogeneous hydrolysis reaction rate constant to zero. This increased the mean bias outside the area of highest ozone concentration but substantially improved O3 and NOy over most of the domain, especially in smoggy areas such as the rural, Pinnacles site.