Daily Satellite Observations of Nitrogen Dioxide Air Pollution Inequality in New York City, New York and Newark, New Jersey: Evaluation and Application.

Urban air pollution disproportionately harms communities of color and low-income communities in the U.S. Intraurban nitrogen dioxide (NO2) inequalities can be observed from space using the TROPOspheric Monitoring Instrument (TROPOMI). Past research has relied on time-averaged measurements, limiting our understanding of how neighborhood-level NO2 inequalities co-vary with urban air quality and climate. Here, we use fine-scale (250 m × 250 m) airborne NO2 remote sensing to demonstrate that daily TROPOMI observations resolve a major portion of census tract-scale NO2 inequalities in the New York City-Newark urbanized area. Spatiotemporally coincident TROPOMI and airborne inequalities are well correlated (r = 0.82-0.97), with slopes of 0.82-1.05 for relative and 0.76-0.96 for absolute inequalities for different groups. We calculate daily TROPOMI NO2 inequalities over May 2018-September 2021, reporting disparities of 25-38% with race, ethnicity, and/or household income. Mean daily inequalities agree with results based on TROPOMI measurements oversampled to 0.01° × 0.01° to within associated uncertainties. Individual and mean daily TROPOMI NO2 inequalities are largely insensitive to pixel size, at least when pixels are smaller than ∼60 km2, but are sensitive to low observational coverage. We statistically analyze daily NO2 inequalities, presenting empirical evidence of the systematic overburdening of communities of color and low-income neighborhoods with polluting sources, regulatory ozone co-benefits, and worsened NO2 inequalities and cumulative NO2 and urban heat burdens with climate change.

Microbial mechanisms and ecosystem flux estimation for aerobic NOy emissions from deciduous forest soils.

Reactive nitrogen oxides (NOy; NOy = NO + NO2 + HONO) decrease air quality and impact radiative forcing, yet the factors responsible for their emission from nonpoint sources (i.e., soils) remain poorly understood. We investigated the factors that control the production of aerobic NOy in forest soils using molecular techniques, process-based assays, and inhibitor experiments. We subsequently used these data to identify hotspots for gas emissions across forests of the eastern United States. Here, we show that nitrogen oxide soil emissions are mediated by microbial community structure (e.g., ammonium oxidizer abundances), soil chemical characteristics (pH and C:N), and nitrogen (N) transformation rates (net nitrification). We find that, while nitrification rates are controlled primarily by chemoautotrophic ammonia-oxidizing archaea (AOA), the production of NOy is mediated in large part by chemoautotrophic ammonia-oxidizing bacteria (AOB). Variation in nitrification rates and nitrogen oxide emissions tracked variation in forest communities, as stands dominated by arbuscular mycorrhizal (AM) trees had greater N transformation rates and NOy fluxes than stands dominated by ectomycorrhizal (ECM) trees. Given mapped distributions of AM and ECM trees from 78,000 forest inventory plots, we estimate that broadleaf forests of the Midwest and the eastern United States as well as the Mississippi River corridor may be considered hotspots of biogenic NOy emissions. Together, our results greatly improve our understanding of NOy fluxes from forests, which should lead to improved predictions about the atmospheric consequences of tree species shifts owing to land management and climate change.

Wintertime Nitrous Oxide Emissions in the San Joaquin Valley of California Estimated from Aircraft Observations.

Nitrous oxide (N2O) is a long-lived greenhouse gas that also destroys stratospheric ozone. N2O emissions are uncertain and characterized by high spatiotemporal variability, making individual observations difficult to upscale, especially in mixed land use source regions like the San Joaquin Valley (SJV) of California. Here, we calculate spatially integrated N2O emission rates using nocturnal and convective boundary-layer budgeting methods. We utilize vertical profile measurements from the NASA DISCOVER-AQ (Deriving Information on Surface Conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality) campaign, which took place January-February, 2013. For empirical constraints on N2O source identity, we analyze N2O enhancement ratios with methane, ammonia, carbon dioxide, and carbon monoxide separately in the nocturnal boundary layer, nocturnal residual layer, and convective boundary layer. We find that an established inventory (EDGAR v4.3.2) underestimates N2O emissions by at least a factor of 2.5, that wintertime emissions from animal agriculture are important to annual totals, and that there is evidence for higher N2O emissions during the daytime than at night.

Dry Deposition of Ozone over Land: Processes, Measurement, and Modeling.

Dry deposition of ozone is an important sink of ozone in near surface air. When dry deposition occurs through plant stomata, ozone can injure the plant, altering water and carbon cycling and reducing crop yields. Quantifying both stomatal and nonstomatal uptake accurately is relevant for understanding ozone's impact on human health as an air pollutant and on climate as a potent short-lived greenhouse gas and primary control on the removal of several reactive greenhouse gases and air pollutants. Robust ozone dry deposition estimates require knowledge of the relative importance of individual deposition pathways, but spatiotemporal variability in nonstomatal deposition is poorly understood. Here we integrate understanding of ozone deposition processes by synthesizing research from fields such as atmospheric chemistry, ecology, and meteorology. We critically review methods for measurements and modeling, highlighting the empiricism that underpins modeling and thus the interpretation of observations. Our unprecedented synthesis of knowledge on deposition pathways, particularly soil and leaf cuticles, reveals process understanding not yet included in widely-used models. If coordinated with short-term field intensives, laboratory studies, and mechanistic modeling, measurements from a few long-term sites would bridge the molecular to ecosystem scales necessary to establish the relative importance of individual deposition pathways and the extent to which they vary in space and time. Our recommended approaches seek to close knowledge gaps that currently limit quantifying the impact of ozone dry deposition on air quality, ecosystems, and climate.

Nitrogen cycling microbiomes are structured by plant mycorrhizal associations with consequences for nitrogen oxide fluxes in forests.

Volatile nitrogen oxides (N2 O, NO, NO2 , HONO, …) can negatively impact climate, air quality, and human health. Using soils collected from temperate forests across the eastern United States, we show microbial communities involved in nitrogen (N) cycling are structured, in large part, by the composition of overstory trees, leading to predictable N-cycling syndromes, with consequences for emissions of volatile nitrogen oxides to air. Trees associating with arbuscular mycorrhizal (AM) fungi promote soil microbial communities with higher N-cycle potential and activity, relative to microbial communities in soils dominated by trees associating with ectomycorrhizal (ECM) fungi. Metagenomic analysis and gene expression studies reveal a 5 and 3.5 times greater estimated N-cycle gene and transcript copy numbers, respectively, in AM relative to ECM soil. Furthermore, we observe a 60% linear decrease in volatile reactive nitrogen gas flux (NOy  ≡ NO, NO2 , HONO) as ECM tree abundance increases. Compared to oxic conditions, gas flux potential of N2 O and NO increase significantly under anoxic conditions for AM soil (30- and 120-fold increase), but not ECM soil-likely owing to small concentrations of available substrate ( NO 3 - ) in ECM soil. Linear mixed effects modeling shows that ECM tree abundance, microbial process rates, and geographic location are primarily responsible for variation in peak potential NOy flux. Given that nearly all tree species associate with either AM or ECM fungi, our results indicate that the consequences of tree species shifts associated with global change may have predictable consequences for soil N cycling.

Observing Nitrogen Dioxide Air Pollution Inequality Using High-Spatial-Resolution Remote Sensing Measurements in Houston, Texas.

Houston, Texas is a major U.S. urban and industrial area where poor air quality is unevenly distributed and a disproportionate share is located in low-income, non-white, and Hispanic neighborhoods. We have traditionally lacked city-wide observations to fully describe these spatial heterogeneities in Houston and in cities globally, especially for reactive gases like nitrogen dioxide (NO2). Here, we analyze novel high-spatial-resolution (250 m × 500 m) NO2 vertical columns measured by the NASA GCAS airborne spectrometer as part of the September-2013 NASA DISCOVER-AQ mission and discuss differences in population-weighted NO2 at the census-tract level. Based on the average of 35 repeated flight circuits, we find 37 ± 6% higher NO2 for non-whites and Hispanics living in low-income tracts (LIN) compared to whites living in high-income tracts (HIW) and report NO2 disparities separately by race ethnicity (11-32%) and poverty status (15-28%). We observe substantial time-of-day and day-to-day variability in LIN-HIW NO2 differences (and in other metrics) driven by the greater prevalence of NOx (≡NO + NO2) emission sources in low-income, non-white, and Hispanic neighborhoods. We evaluate measurements from the recently launched satellite sensor TROPOMI (3.5 km × 7 km at nadir), averaged to 0.01° × 0.01° using physics-based oversampling, and demonstrate that TROPOMI resolves similar relative, but not absolute, tract-level differences compared to GCAS. We utilize the high-resolution FIVE and NEI NOx inventories, plus one year of TROPOMI weekday-weekend variability, to attribute tract-level NO2 disparities to industrial sources and heavy-duty diesel trucking. We show that GCAS and TROPOMI spatial patterns correspond to the surface patterns measured using aircraft profiling and surface monitors. We discuss opportunities for satellite remote sensing to inform decision making in cities generally.

Observing Severe Drought Influences on Ozone Air Pollution in California.

Drought conditions affect ozone air quality, potentially altering multiple terms in the O3 mass balance equation. Here, we present a multiyear observational analysis using data collected before, during, and after the record-breaking California drought (2011-2015) at the O3-polluted locations of Fresno and Bakersfield near the Sierra Nevada foothills. We separately assess drought influences on O3 chemical production ( PO3) from O3 concentration. We show that isoprene concentrations, which are a source of O3-forming organic reactivity, were relatively insensitive to early drought conditions but decreased by more than 50% during the most severe drought years (2014-2015), with recovery a function of location. We find drought-isoprene effects are temperature-dependent, even after accounting for changes in leaf area, consistent with laboratory studies but not previously observed at landscape scales with atmospheric observations. Drought-driven decreases in organic reactivity are contemporaneous with a change in dominant oxidation mechanism, with PO3 becoming more NO x-suppressed, leading to a decrease in PO3 of ∼20%. We infer reductions in atmospheric O3 loss of ∼15% during the most severe drought period, consistent with past observations of decreases in O3 uptake by plants. We consider drought-related trends in O3 variability on synoptic time scales by analyzing statistics of multiday high-O3 events. We discuss implications for regulating O3 air pollution in California and other locations under more prevalent drought conditions.

An Atmospheric Constraint on the NO2 Dependence of Daytime Near-Surface Nitrous Acid (HONO).

Recent observations suggest a large and unknown daytime source of nitrous acid (HONO) to the atmosphere. Multiple mechanisms have been proposed, many of which involve chemistry that reduces nitrogen dioxide (NO2) on some time scale. To examine the NO2 dependence of the daytime HONO source, we compare weekday and weekend measurements of NO2 and HONO in two U.S. cities. We find that daytime HONO does not increase proportionally to increases in same-day NO2, i.e., the local NO2 concentration at that time and several hours earlier. We discuss various published HONO formation pathways in the context of this constraint.

Neighborhood-Level Nitrogen Dioxide Inequalities Contribute to Surface Ozone Variability in Houston, Texas.

In Houston, Texas, nitrogen dioxide (NO2) air pollution disproportionately affects Black, Latinx, and Asian communities, and high ozone (O3) days are frequent. There is limited knowledge of how NO2 inequalities vary in urban air quality contexts, in part from the lack of time-varying neighborhood-level NO2 measurements. First, we demonstrate that daily TROPOspheric Monitoring Instrument (TROPOMI) NO2 tropospheric vertical column densities (TVCDs) resolve a major portion of census tract-scale NO2 inequalities in Houston, comparing NO2 inequalities based on TROPOMI TVCDs and spatiotemporally coincident airborne remote sensing (250 m × 560 m) from the NASA TRacking Aerosol Convection ExpeRiment-Air Quality (TRACER-AQ). We further evaluate the application of daily TROPOMI TVCDs to census tract-scale NO2 inequalities (May 2018-November 2022). This includes explaining differences between mean daily NO2 inequalities and those based on TVCDs oversampled to 0.01° × 0.01° and showing daily NO2 column-surface relationships weaken as a function of observation separation distance. Second, census tract-scale NO2 inequalities, city-wide high O3, and mesoscale airflows are found to covary using principal component and cluster analysis. A generalized additive model of O3 mixing ratios versus NO2 inequalities reproduces established nonlinear relationships between O3 production and NO2 concentrations, providing observational evidence that neighborhood-level NO2 inequalities and O3 are coupled. Consequently, emissions controls specifically in Black, Latinx, and Asian communities will have co-benefits, reducing both NO2 disparities and high O3 days city wide.

Observational insights into aerosol formation from isoprene.

Atmospheric photooxidation of isoprene is an important source of secondary organic aerosol (SOA) and there is increasing evidence that anthropogenic oxidant emissions can enhance this SOA formation. In this work, we use ambient observations of organosulfates formed from isoprene epoxydiols (IEPOX) and methacrylic acid epoxide (MAE) and a broad suite of chemical measurements to investigate the relative importance of nitrogen oxide (NO/NO2) and hydroperoxyl (HO2) SOA formation pathways from isoprene at a forested site in California. In contrast to IEPOX, the calculated production rate of MAE was observed to be independent of temperature. This is the result of the very fast thermolysis of MPAN at high temperatures that affects the distribution of the MPAN reservoir (MPAN / MPA radical) reducing the fraction that can react with OH to form MAE and subsequently SOA (F(MAE formation)). The strong temperature dependence of F(MAE formation) helps to explain our observations of similar concentrations of IEPOX-derived organosulfates (IEPOX-OS; ~1 ng m(-3)) and MAE-derived organosulfates (MAE-OS; ~1 ng m(-3)) under cooler conditions (lower isoprene concentrations) and much higher IEPOX-OS (~20 ng m(-3)) relative to MAE-OS (<0.0005 ng m(-3)) at higher temperatures (higher isoprene concentrations). A kinetic model of IEPOX and MAE loss showed that MAE forms 10-100 times more ring-opening products than IEPOX and that both are strongly dependent on aerosol water content when aerosol pH is constant. However, the higher fraction of MAE ring opening products does not compensate for the lower MAE production under warmer conditions (higher isoprene concentrations) resulting in lower formation of MAE-derived products relative to IEPOX at the surface. In regions of high NOx, high isoprene emissions and strong vertical mixing the slower MPAN thermolysis rate aloft could increase the fraction of MPAN that forms MAE resulting in a vertically varying isoprene SOA source.

State-of-the-Science Data and Methods Need to Guide Place-Based Efforts to Reduce Air Pollution Inequity.

BACKGROUND: Recently enacted environmental justice policies in the United States at the state and federal level emphasize addressing place-based inequities, including persistent disparities in air pollution exposure and associated health impacts. Advances in air quality measurement, models, and analytic methods have demonstrated the importance of finer-scale data and analysis in accurately quantifying the extent of inequity in intraurban pollution exposure, although the necessary degree of spatial resolution remains a complex and context-dependent question. OBJECTIVE: The objectives of this commentary were to a) discuss ways to maximize and evaluate the effectiveness of efforts to reduce air pollution disparities, and b) argue that environmental regulators must employ improved methods to project, measure, and track the distributional impacts of new policies at finer geographic and temporal scales. DISCUSSION: The historic federal investments from the Inflation Reduction Act, the Infrastructure Investment and Jobs Act, and the Biden Administration's commitment to Justice40 present an unprecedented opportunity to advance climate and energy policies that deliver real reductions in pollution-related health inequities. In our opinion, scientists, advocates, policymakers, and implementing agencies must work together to harness critical advances in air quality measurements, models, and analytic methods to ensure success. https://doi.org/10.1289/EHP13063.

PM2.5 composition and sources in the San Joaquin Valley of California: A long-term study using ToF-ACSM with the capture vaporizer.

The San Joaquin Valley (SJV) of California has suffered persistent particulate matter (PM) pollution despite many years of control efforts. To further understand the chemical drivers of this problem and to support the development of State Implementation Plan for PM, a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) outfitted with a PM2.5 lens and a capture vaporizer has been deployed at the Fresno-Garland air monitoring site of the California Air Resource Board (CARB) since Oct. 2018. The instrument measured non-refractory species in PM2.5 continuously at 10-min resolution. In this study, the data acquired from Oct. 2018 to May 2019 were analyzed to investigate the chemical characteristics, sources and atmospheric processes of PM2.5 in the SJV. Comparisons of the ToF-ACSM measurement with various co-located aerosol instruments show good agreements. The inter-comparisons indicated that PM2.5 in Fresno was dominated by submicron particles during the winter whereas refractory species accounted for a major fraction of PM2.5 mass during the autumn associated with elevated PM10 loadings. A rolling window positive matrix factorization analysis was applied to the organic aerosol (OA) mass spectra using the Multilinear Engine (ME-2) algorithm. Three distinct OA sources were identified, including vehicle emissions, local and regional biomass burning, and formation of oxygenated species. There were significant seasonal variations in PM2.5 composition and sources. During the winter, residential wood burning and oxidation of nitrogen oxides were major contributors to the occurrence of haze episodes with PM2.5 dominated by biomass burning OA and nitrate. In autumn, agricultural activities and wildfires were found to be the main cause of PM pollution. PM2.5 concentrations decreased significantly after spring and were dominated by oxygenated OA during March to May. Our results highlight the importance of using seasonally dependent control strategies to mitigate PM pollution in the SJV.

Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ.

Global coupled chemistry-climate models underestimate carbon monoxide (CO) in the Northern Hemisphere, exhibiting a pervasive negative bias against measurements peaking in late winter and early spring. While this bias has been commonly attributed to underestimation of direct anthropogenic and biomass burning emissions, chemical production and loss via OH reaction from emissions of anthropogenic and biogenic volatile organic compounds (VOCs) play an important role. Here we investigate the reasons for this underestimation using aircraft measurements taken in May and June 2016 from the Korea-United States Air Quality (KORUS-AQ) experiment in South Korea and the Air Chemistry Research in Asia (ARIAs) in the North China Plain (NCP). For reference, multispectral CO retrievals (V8J) from the Measurements of Pollution in the Troposphere (MOPITT) are jointly assimilated with meteorological observations using an ensemble adjustment Kalman filter (EAKF) within the global Community Atmosphere Model with Chemistry (CAM-Chem) and the Data Assimilation Research Testbed (DART). With regard to KORUS-AQ data, CO is underestimated by 42% in the control run and by 12% with the MOPITT assimilation run. The inversion suggests an underestimation of anthropogenic CO sources in many regions, by up to 80% for northern China, with large increments over the Liaoning Province and the North China Plain (NCP). Yet, an often-overlooked aspect of these inversions is that correcting the underestimation in anthropogenic CO emissions also improves the comparison with observational O3 datasets and observationally constrained box model simulations of OH and HO2. Running a CAM-Chem simulation with the updated emissions of anthropogenic CO reduces the bias by 29% for CO, 18% for ozone, 11% for HO2, and 27% for OH. Longer-lived anthropogenic VOCs whose model errors are correlated with CO are also improved, while short-lived VOCs, including formaldehyde, are difficult to constrain solely by assimilating satellite retrievals of CO. During an anticyclonic episode, better simulation of O3, with an average underestimation of 5.5 ppbv, and a reduction in the bias of surface formaldehyde and oxygenated VOCs can be achieved by separately increasing by a factor of 2 the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to widespread NO x controls, can improve ozone pollution over East Asia.

The Ozone Water-Land Environmental Transition Study (OWLETS): An Innovative Strategy for Understanding Chesapeake Bay Pollution Events.

Coastal regions have historically represented a significant challenge for air quality investigations due to water-land boundary transition characteristics and a paucity of measurements available over water. Prior studies have identified the formation of high levels of ozone over water bodies, such as the Chesapeake Bay, that can potentially recirculate back over land to significantly impact populated areas. Earth-observing satellites and forecast models face challenges in capturing the coastal transition zone where small-scale meteorological dynamics are complex and large changes in pollutants can occur on very short spatial and temporal scales. An observation strategy is presented to synchronously measure pollutants 'over-land' and 'over-water' to provide a more complete picture of chemical gradients across coastal boundaries for both the needs of state and local environmental management and new remote sensing platforms. Intensive vertical profile information from ozone lidar systems and ozonesondes, obtained at two main sites, one over land and the other over water, are complemented by remote sensing and in-situ observations of air quality from ground-based, airborne (both personned and unpersonned), and shipborne platforms. These observations, coupled with reliable chemical transport simulations, such as the NOAA National Air Quality Forecast Capability (NAQFC), are expected to lead to a more fully characterized and complete land-water interaction observing system that can be used to assess future geostationary air quality instruments, such as the NASA Tropospheric Emissions: Monitoring of Pollution (TEMPO) as well as current low earth orbiting satellites, such as the European Space Agency's Sentinel 5-Precursor (S5-P) with its Tropospheric Monitoring Instrument (TROPOMI).

Modeling regional pollution transport events during KORUS-AQ: Progress and challenges in improving representation of land-atmosphere feedbacks.

This study evaluates the impact of assimilating soil moisture data from NASA's Soil Moisture Active Passive (SMAP) on short-term regional weather and air quality modeling in East Asia during the Korea-US Air Quality Study (KORUS-AQ) airborne campaign. SMAP data are assimilated into the Noah land surface model using an ensemble Kalman filter approach in the Land Information System framework, which is semi-coupled with the NASA-Unified Weather Research and Forecasting model with online chemistry (NUWRF-Chem). With SMAP assimilation included, water vapor and carbon monoxide (CO) transport from northern-central China transitional climate zones to South Korea is better represented in NUWRF-Chem during two studied pollution events. Influenced by different synoptic conditions and emission patterns, impact of SMAP assimilation on modeled CO in South Korea is intense (>30 ppbv) during one event and less significant (<8 ppbv) during the other. SMAP assimilation impact on air quality modeling skill is complicated by other error sources such as the chemical initial and boundary conditions (IC/LBC) and emission inputs of NUWRF-Chem. Using a satellite-observation-constrained chemical IC/LBC instead of a free-running, coarser-resolution chemical IC/LBC reduces modeled CO by up to 80 ppbv over South Korea. Consequently, CO performance is improved in the middle-upper troposphere whereas degraded in the lower troposphere. Remaining negative CO biases result largely from the emissions inputs. The advancements in land surface modeling and chemical IC/LBC presented here are expected to benefit future investigations on constraining emissions using observations, which can in turn enable more accurate assessments of SMAP assimilation and chemical IC/LBC impacts.

Characterizing CO and NO y Sources and Relative Ambient Ratios in the Baltimore Area Using Ambient Measurements and Source Attribution Modeling.

Modeled source attribution information from the Community Multiscale Air Quality model was coupled with ambient data from the 2011 Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality Baltimore field study. We assess source contributions and evaluate the utility of using aircraft measured CO and NO y relationships to constrain emission inventories. We derive ambient and modeled ΔCO:ΔNO y ratios that have previously been interpreted to represent CO:NO y ratios in emissions from local sources. Modeled and measured ΔCO:ΔNO y are similar; however, measured ΔCO:ΔNO y has much more daily variability than modeled values. Sector-based tagging shows that regional transport, on-road gasoline vehicles, and nonroad equipment are the major contributors to modeled CO mixing ratios in the Baltimore area. In addition to those sources, on-road diesel vehicles, soil emissions, and power plants also contribute substantially to modeled NO y in the area. The sector mix is important because emitted CO:NO x ratios vary by several orders of magnitude among the emission sources. The model-predicted gasoline/diesel split remains constant across all measurement locations in this study. Comparison of ΔCO:ΔNO y to emitted CO:NO y is challenged by ambient and modeled evidence that free tropospheric entrainment, and atmospheric processing elevates ambient ΔCO:ΔNO y above emitted ratios. Specifically, modeled ΔCO:ΔNO y from tagged mobile source emissions is enhanced 5-50% above the emitted ratios at times and locations of aircraft measurements. We also find a correlation between ambient formaldehyde concentrations and measured ΔCO:ΔNO y suggesting that secondary CO formation plays a role in these elevated ratios. This analysis suggests that ambient urban daytime ΔCO:ΔNO y values are not reflective of emitted ratios from individual sources.

Modeling NH4NO3 Over the San Joaquin Valley During the 2013 DISCOVER-AQ Campaign.

The San Joaquin Valley (SJV) of California experiences high concentrations of particulate matter NH4NO3 during episodes of meteorological stagnation in winter. A rich data set of observations related to NH4NO3 formation was acquired during multiple periods of elevated NH4NO3 during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaign in SJV in January and February 2013. Here NH4NO3 is simulated during the SJV DISCOVER-AQ study period with the Community Multiscale Air Quality (CMAQ) model, diagnostic model evaluation is performed using the DISCOVER-AQ data set, and integrated reaction rate analysis is used to quantify HNO3 production rates. Simulated NO3- generally agrees well with routine monitoring of 24-hr average NO3-, but comparisons with hourly average NO3- measurements in Fresno revealed differences at higher time resolution. Predictions of gas-particle partitioning of total nitrate (HNO3 + NO3-) and NHx (NH3 + NH4+) generally agree well with measurements in Fresno, although partitioning of total nitrate to HNO3 is sometimes overestimated at low relative humidity in afternoon. Gas-particle partitioning results indicate that NH4NO3 formation is limited by HNO3 availability in both the model and ambient. NH3 mixing ratios are underestimated, particularly in areas with large agricultural activity, and additional work on the spatial allocation of NH3 emissions is warranted. During a period of elevated NH4NO3, the model predicted that the OH + NO2 pathway contributed 46% to total HNO3production in SJV and the N2O5 heterogeneous hydrolysis pathway contributed 54%. The relative importance of the OH + NO2 pathway for HNO3 production is predicted to increase as NOx emissions decrease.

Frequency and Impact of Summertime Stratospheric Intrusions over Maryland during DISCOVER-AQ (2011): New Evidence from NASA's GEOS-5 Simulations.

Aircraft observations and ozonesonde profiles collected on July 14 and 27, 2011, during the Maryland month-long DISCOVER-AQ campaign, indicate the presence of stratospheric air just above the planetary boundary layer (PBL). This raises the question of whether summer stratospheric intrusions (SIs) elevate surface ozone levels and to what degree they influence background ozone levels and contribute to ozone production. We used idealized stratospheric air tracers, along with observations, to determine the frequency and extent of SIs in Maryland during July 2011. On 4 of 14 flight days, SIs were detected in layers that the aircraft encountered above the PBL from the coincidence of enhanced ozone, moderate CO, and low moisture. Satellite observations of lower tropospheric humidity confirmed the occurrence of synoptic scale influence of SIs as do simulations with the GEOS-5 Atmospheric General Circulation Model. The evolution of GEOS-5 stratospheric air tracers agree with the timing and location of observed stratospheric influence and indicate that more than 50% of air in SI layers above the PBL had resided in the stratosphere within the previous 14 days. Despite having a strong influence in the lower free troposphere, these events did not significantly affect surface ozone, which remained low on intrusion days. The model indicates similar frequencies of stratospheric influence during all summers from 2009-2013. GEOS-5 results suggest that, over Maryland, the strong inversion capping the summer PBL limits downward mixing of stratospheric air during much of the day, helping to preserve low surface ozone associated with frontal passages that precede SIs.