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BackgroundNetworks of tower-based CO2 mole fraction sensors have been deployed in and around cities across the world to quantify anthropogenic CO2 emissions from metropolitan areas. A critical aspect in these approaches is the separation of atmospheric signatures from distant sources and sinks (i.e., the background) from local emissions and biogenic fluxes. We examined CO2 enhancements compared to forested and agricultural background towers in Indianapolis, Indiana, USA, as a function of season and compared them to modeled results, as a part of the Indianapolis Flux (INFLUX) project.ResultsAt the INFLUX urban tower sites, daytime growing season enhancement on a monthly timescale was up to 4.3 – 6.5 ppm, 2.6 times as large as those in the dormant season, on average. The enhancement differed significantly depending on choice of background and time of year, being 2.8 ppm higher in June and 1.8 ppm lower in August using a forested background tower compared to an agricultural background tower. A prediction based on land cover and observed CO2 fluxes showed that differences in phenology and drawdown intensities drove measured differences in enhancements. Forward modelled CO2 enhancements using fossil fuel and biogenic fluxes indicated growing season model-data mismatch of 1.1 ± 1.7 ppm for the agricultural background and 2.1 ± 0.5 ppm for the forested background, corresponding to 25 – 29 % of the modelled CO2 enhancements. The model-data total CO2 mismatch during the dormant season was low, – 0.1 ± 0.5 ppm. ConclusionsBecause growing season biogenic fluxes at the background towers are large, the urban enhancements must be disentangled from the biogenic signal, and growing season increases in CO2 enhancement could be misinterpreted as increased anthropogenic fluxes if the background ecosystem CO2 drawdown is not considered. The magnitude and timing of enhancements depend on the land cover type and net fluxes surrounding each background tower, so a simple box model is not appropriate for interpretation of these data. Quantification of the seasonality and magnitude of the biological fluxes in the study region using high-resolution and detailed biogenic models is necessary for the interpretation of tower-based urban CO2 networks for cities with significant vegetation.

Background Networks of tower-based CO2 mole fraction sensors have been deployed by various groups in and around cities across the world to quantify anthropogenic CO2 emissions from metropolitan areas. A critical aspect in these approaches is the separation of atmospheric signatures from distant sources and sinks (i.e., the background) from local emissions and biogenic fluxes. We examined CO2 enhancements compared to forested and agricultural background towers in Indianapolis, Indiana, USA, as a function of season and compared them to modeled results, as a part of the Indianapolis Flux (INFLUX) project. Results At the INFLUX urban tower sites, daytime growing season enhancement on a monthly timescale was up to 4.3–6.5 ppm, 2.6 times as large as those in the dormant season, on average. The enhancement differed significantly depending on choice of background and time of year, being 2.8 ppm higher in June and 1.8 ppm lower in August using a forested background tower compared to an agricultural background tower. A prediction based on land cover and observed CO2 fluxes showed that differences in phenology and drawdown intensities drove measured differences in enhancements. Forward modelled CO2 enhancements using fossil fuel and biogenic fluxes indicated growing season model-data mismatch of 1.1 ± 1.7 ppm for the agricultural background and 2.1 ± 0.5 ppm for the forested background, corresponding to 25–29% of the modelled CO2 enhancements. The model-data total CO2 mismatch during the dormant season was low, − 0.1 ± 0.5 ppm. Conclusions Because growing season biogenic fluxes at the background towers are large, the urban enhancements must be disentangled from the biogenic signal, and growing season increases in CO2 enhancement could be misinterpreted as increased anthropogenic fluxes if the background ecosystem CO2 drawdown is not considered. The magnitude and timing of enhancements depend on the land cover type and net fluxes surrounding each background tower, so a simple box model is not appropriate for interpretation of these data. Quantification of the seasonality and magnitude of the biological fluxes in the study region using high-resolution and detailed biogenic models is necessary for the interpretation of tower-based urban CO2 networks for cities with significant vegetation.

Four in situ cavity ring-down spectrometers (G2132-i, Picarro, Inc.) measuring methane dry mole fraction (CH4), carbon dioxide dry mole fraction (CO2), and the isotopic ratio of methane (δ13CH4) were deployed at four towers in the Marcellus Shale natural gas extraction region of Pennsylvania. In this paper, we describe laboratory and field calibration of the analyzers for tower-based applications and characterize their performance in the field for the period January–December 2016. Prior to deployment, each analyzer was tested using bottles with various isotopic ratios, from biogenic to thermogenic source values, which were diluted to varying degrees in zero air, and an initial calibration was performed. Furthermore, at each tower location, three field tanks were employed, from ambient to high mole fractions, with various isotopic ratios. Two of these tanks were used to adjust the calibration of the analyzers on a daily basis. We also corrected for the cross-interference from ethane on the isotopic ratio of methane. Using an independent field tank for evaluation, the standard deviation of 4 h means of the isotopic ratio of methane difference from the known value was found to be 0.26 ‰ δ13CH4. Following improvements in the field tank testing scheme, the standard deviation of 4 h means was 0.11 ‰, well within the target compatibility of 0.2 ‰. Round-robin style testing using tanks with near-ambient isotopic ratios indicated mean errors of −0.14 to 0.03 ‰ for each of the analyzers. Flask to in situ comparisons showed mean differences over the year of 0.02 and 0.08 ‰, for the east and south towers, respectively. Regional sources in this region were difficult to differentiate from strong perturbations in the background. During the afternoon hours, the median differences of the isotopic ratio measured at three of the towers, compared to the background tower, were &minus0.15 to 0.12 ‰ with standard deviations of the 10 min isotopic ratio differences of 0.8 ‰. In terms of source attribution, analyzer compatibility of 0.2 ‰ δ13CH4 affords the ability to distinguish a 50 ppb CH4 peak from a biogenic source (at −60 ‰, for example) from one originating from a thermogenic source (−35 ‰), with the exact value dependent upon the source isotopic ratios. Using a Keeling plot approach for the non-afternoon data at a tower in the center of the study region, we determined the source isotopic signature to be −31.2 ± 1.9 ‰, within the wide range of values consistent with a deep-layer Marcellus natural gas source.

A Comprehensive Air-Quality Model with Extensions (CAMx) version 6.10 simulation was assessed through comparison with data acquired during NASA’s 2011 DISCOVER-AQ Maryland field campaign. Comparisons for the baseline simulation (CB05 chemistry, EPA 2011 National Emissions Inventory) show a model overestimate of NOy by +86.2% and an underestimate of HCHO by −28.3%. We present a new model framework (CB6r2 chemistry, MEGAN v2.1 biogenic emissions, 50% reduction in mobile NOx, enhanced representation of isoprene nitrates) that better matches observations. The new model framework attributes 31.4% more surface ozone in Maryland to electric generating units (EGUs) and 34.6% less ozone to on-road mobile sources. Surface ozone becomes more NOx-limited throughout the eastern United States compared to the baseline simulation. The baseline model therefore likely underestimates the effectiveness of anthropogenic NOx reductions as well as the current contribution of EGUs to surface ozone.

A Comprehensive Air-Quality Model with Extensions (CAMx) version 6.10 simulation was assessed through comparison with data acquired during NASA's 2011 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Maryland field campaign. Comparisons for the baseline simulation (Carbon Bond 2005 (CB05) chemistry, Environmental Protection Agency 2011 National Emissions Inventory) show a model overestimate of NOy by +86.2% and an underestimate of HCHO by -28.3%. We present a new model framework (Carbon Bond 6 Revision 2 chemistry (CB6r2), Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.1 biogenic emissions, 50% reduction in mobile NOx, enhanced representation of isoprene nitrates) that better matches observations. The new model framework attributes 31.4% more surface ozone in Maryland to electric generating units (EGUs) and 34.6% less ozone to on-road mobile sources. Surface ozone becomes more NOx limited throughout the eastern United States compared to the baseline simulation. The baseline model therefore likely underestimates the effectiveness of anthropogenic NOx reductions as well as the current contribution of EGUs to surface ozone.

Mitigating ozone pollution involves reducing ozone production and relies on complex air-quality models to design reduction strategies and determine their effectiveness. However, modeled ozone does not always agree with observations. A complementary approach is to measure the ozone production rate directly, leading to the development of the Measurement of Ozone Production Sensor (MOPS). Two improved second-generation MOPSv2s were deployed for NASA's DISCOVER-AQ field campaign in

Volatile Organic Compounds (VOCs) were collected in canister samples during NASA’s Deriving Information on Surface conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission in July 2011. Twenty three samples were collected at the surface and analyzed for OH reactivity, temporal variability, and relationships with atmospheric dynamics in an effort to have some insight into VOC behaviors at Edgewood, MD during a short period of time. Alkenes and oxygenated volatile organic compounds (VOCs) were the most abundant and the most reactive VOCs measured over the site. Source attribution of the measured species indicates that biogenically sourced VOCs account for half the calculated OH reactivity at the site. A case study of 2 days of canister samples and ozonesondes were used to investigate VOC dynamics over the site. A stable boundary layer present on 21 July prevented a lofted layer of pollution from mixing to the ground, causing relative anthropogenic VOC contributions to decrease, increasing the relative biogenic and oxygenated mixing ratios throughout the day. Mixing of the residual layer to the ground on 22 July enhanced the anthropogenic VOCs, and high temperatures increased biogenic emissions leading to a day that with high ozone and VOC measurements.

Recent intensive sampling and numerical modeling studies have given insights to the processes driving atmospheric chemistry in the mid-Atlantic region. We summarize the meteorology and air quality measurements conducted as part of the NASA Deriving Information on Surface Conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign and other mid-Atlantic sampling intensives during July 2011. We review the important findings of the work contained within the Processes Impacting NEar-Surface Atmospheric Pollutants (PINESAP) special issue and highlight the importance of intensive sampling campaigns as a means of gaining understanding of atmospheric chemistry in a changing climate.

Biological volatile organic compounds (BVOCs), such as isoprene and monoterpenes, are emitted in large amounts from forests. Quantification of the flux of BVOCs is critical in the evaluation of the impact of these compounds on the concentrations of atmospheric oxidants and on the production of secondary organic aerosol. A disjunct eddy accumulation (DEA) sampler system was constructed for the measurement of speciated BVOC fluxes. Unlike traditional eddy covariance (EC), the relatively new technique of disjunct sampling differs by taking short, discrete samples that allow for slower sampling frequencies. Disjunct sample airflow is directed into cartridges containing sorbent materials at sampling rates proportional to the magnitude of the vertical wind. Compounds accumulated on the cartridges are then quantified by thermal desorption and gas chromatography. Herein, we describe our initial tests to evaluate the disjunct sampler including the application of vertical wind measurements to create optimized sampling thresholds. Measurements of BVOC fluxes obtained from DEA during its deployment above a mixed hardwood forest at the University of Michigan Biological Station (Pellston, MI) during the 2009 CABINEX field campaign are reported. Daytime (09:00 a.m. to 05:00 p.m. LT) isoprene fluxes, when averaged over the footprint of the tower, were 1.31 mg m−2 h−1 which are comparable to previous flux measurements at this location. Speciated monoterpene fluxes are some of the first to be reported from this site. Daytime averages were 26.7 μg m−2 h−1 for α-pinene and 10.6 μg m−2 h−1 for β-pinene. These measured concentrations and fluxes were compared to the output of an atmospheric chemistry model, and were found to be consistent with our knowledge of the variables that control BVOCs fluxes at this site.

Four in-situ cavity ring-down spectrometers (G2132-i, Picarro, Inc.) measuring methane dry mole fraction (CH4), carbon dioxide dry mole fraction (CO2) and the isotopic ratio of methane (δ13CH4) were deployed at four towers in the Marcellus Shale natural gas extraction region of Pennsylvania. The calibration of the continuous isotopic methane analyzers used in this study required both a linear calibration and a mole fraction correction, and a correction for cross-interference from ethane. In this paper, we describe laboratory and field calibration of the analyzers for tower-based applications, and characterize their performance in the field for the period January–December 2016. Prior to deployment, each analyzer was calibrated using high methane mole fraction air bottles with various isotopic ratios, from biogenic to thermogenic source values, diluted in zero air. Furthermore, at each tower location, three field calibration tanks were employed, from ambient to high mole fractions, with various isotopic ratios. By testing multiple calibration schemes, we determined an optimized field calibration method. A method to correct for cross interference from ethane is also described. Using an independent field tank for evaluation, the standard deviation of 4-hour means of the isotopic ratio of methane difference from the known value was found to be 0.26 ‰ δ13CH4. Following improvements in the field calibration tank sampling scheme, the standard deviation of 4-hour means was 0.11 ‰, well within the target compatibility of 0.2 ‰. Round robin style testing using tanks with near ambient isotopic ratios indicated mean errors of −0.14 to 0.03 ‰ for each of the analyzers. Flask to in-situ comparisons showed mean differences over the year of 0.02 and 0.08 ‰, for the East and South towers, respectively. Regional sources in this region were difficult to differentiate from strong perturbations in the background. During the afternoon hours, the median enhancements of isotopic ratio measured at three of the towers, compared to the background tower, were −0.15 to 0.12 ‰ with standard deviations of the 10-min isotopic ratio enhancements of 0.8 ‰. In terms of source attribution, analyzer compatibility of 0.2 ‰ δ13CH4 affords the ability to distinguish a 50 ppb CH4 peak from a biogenic source from one originating from a thermogenic source. Using a Keeling plot approach for the non-afternoon data at a tower in the center of the study region, we determined the source isotopic signature to be −31.2 ‰, consistent with a deep-layer Marcellus natural gas source.

A twelve-station tower-based observation network measuring CO2, CH4, and CO was deployed in and around the Indianapolis, IN metropolitan area as part of the Indianapolis Flux Experiment (INFLUX). Measurements began in 2010 and the full network was deployed by 2013. Observations were made at heights ranging from 39 to 136 m above ground level using existing communication towers. Several towers in the network had multiple measurement levels. Cavity ring-down spectrometers (CRDS) were used at all twelve sites and at least one calibrated reference tank was sampled daily at each site. Real time data communications were performed via cellular modems and data were transmitted daily for processing and quality assurance checks. Data quality control procedures were utilized to ensure compatibility within the INFLUX tower network and with global standards. For example, field target/calibration tanks were used to detect long-term instrument drift and instrument failure. Network-wide round robin tests were performed every 1–2 years to detect possible target tank drift and ensure network-wide comparability between measurements. NOAA flask packages were deployed at six of the INFLUX towers to provide a flask to in-situ direct comparison of the atmospheric samples. Results from these activities demonstrate that the compatibility of the CO2, CH4, and CO INFLUX in-situ tower-based measurements are less than or equal to 0.18 ppm CO2, 1.0 ppb for CH4, and 6 ppb for CO.

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.

Total-column nitrogen dioxide (NO2) data collected by a ground-based sun-tracking spectrometer system (Pandora) and an photolytic-converter-based in-situ instrument collocated at NASA’s Langley Research Center in Hampton, Virginia were analyzed to study the relationship between total-column and surface NO2 measurements. The measurements span more than a year and cover all seasons. Surface mixing ratios are estimated via application of a planetary boundary-layer (PBL) height correction factor. This PBL correction factor effectively corrects for boundary-layer variability throughout the day, and accounts for up to ≈75 % of the variability between the NO2 data sets. Previous studies have made monthly and seasonal comparisons of column/surface data, which has shown generally good agreement over these long average times. In the current analysis comparisons of column densities averaged over 90 s and 1 h are made. Applicability of this technique to sulfur dioxide (SO2) is briefly explored. The SO2 correlation is improved by excluding conditions where surface levels are considered background. The analysis is extended to data from the July 2011 DISCOVER-AQ mission over the greater Baltimore, MD area to examine the method’s performance in more-polluted urban conditions where NO2 concentrations are typically much higher.

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.

We performed an atmospheric inversion of the CO2 fluxes over Iowa and the surrounding states, from June to December 2007, at 20 km resolution and weekly timescale. Eight concentration towers were used to constrain the carbon balance in a 1000×1000 km2 domain in this agricultural region of the US upper midwest. The CO2 concentrations of the boundaries derived from CarbonTracker were adjusted to match direct observations from aircraft profiles around the domain. The regional carbon balance ends up with a sink of 183 Tg C±35 Tg C over the area for the period June–December, 2007. Potential bias from incorrect boundary conditions of about 0.55 ppm over the 7 months was corrected using mixing ratios from four different aircraft profile sites operated at a weekly time scale, acting as an additional source of uncertainty of 24 Tg C. We used two different prior flux estimates, the SiBCrop model and the inverse flux product from the CarbonTracker system. We show that inverse flux estimates using both priors converge to similar posterior estimates (20 Tg C difference), in our reference inversion, but some spatial structures from the prior fluxes remain in the posterior fluxes, revealing the importance of the prior flux resolution and distribution despite the large amount of atmospheric data available. The retrieved fluxes were compared to eddy flux towers in the corn and grassland areas, revealing an improvement in the seasonal cycles between the two compared to the prior fluxes, despite large absolute differences due to representation errors. The uncertainty of 34 Tg C (or 34 g C m2) was derived from the posterior uncertainty obtained with our reference inversion of about 25 to 30 Tg C and from sensitivity tests of the assumptions made in the inverse system, for a mean carbon balance over the region of −183 Tg C, slightly weaker than the reference. Because of the potential large bias (~24 Tg C in this case) due to choice of background conditions, proportional to the surface but not to the regional flux, this methodology seems limited to regions with a large signal (sink or source), unless additional observations can be used to constrain the boundary inflow.

A Lagrangian experiment was conducted over Iowa during the daytime (9:00–17:30 LT) on June 19, 2007 as part of the North American Carbon Program's Mid-Continent Intensive using a light-weight and operationally flexible aircraft to measure a net drawdown of CO2 concentration within the boundary layer. The drawdown can be related to net ecosystem exchange when anthropogenic emissions are estimated using a combination of the Vulcan fossil fuel emissions inventory coupled with a source contribution analysis using HYSPLIT. Results show a temporally and spatially averaged net CO2 flux of −9.0 ± 2.4 μmol m−2 s−1 measured from the aircraft data. The average flux from anthropogenic emissions over the measurement area was 0.3 ± 0.1 μmol CO2 m−2 s−1. Large-scale subsidence occurred during the experiment, entraining 1.0 ± 0.2 μmol CO2 m−2 s−1 into the boundary layer. Thus, the CO2 flux attributable to the vegetation and soils is −10.3 ± 2.4 μmol m−2 s−1. The magnitude of the calculated daytime biospheric flux is consistent with tower-based eddy covariance fluxes over corn and soybeans given existing land-use estimates for this agricultural region. Flux values are relatively insensitive to the choice of integration height above the boundary layer and emission footprint area. Flux uncertainties are relatively small compared to the biospheric fluxes, though the measurements were conducted at the height of the growing season.

An analysis is presented for both ground- and satellite-based retrievals of total column ozone and nitrogen dioxide levels from the Washington, D.C., and Baltimore, Maryland, metropolitan area during the NASA-sponsored July 2011 campaign of Deriving Information on Surface COnditions from Column and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Satellite retrievals of total column ozone and nitrogen dioxide from the Ozone Monitoring Instrument (OMI) on the Aura satellite are used, while Pandora spectrometers provide total column ozone and nitrogen dioxide amounts from the ground. We found that OMI and Pandora agree well (residuals within ±25 % for nitrogen dioxide, and ±4.5 % for ozone) for a majority of coincident observations during July 2011. Comparisons with surface nitrogen dioxide from a Teledyne API 200 EU NOx Analyzer showed nitrogen dioxide diurnal variability that was consistent with measurements by Pandora. However, the wide OMI field of view, clouds, and aerosols affected retrievals on certain days, resulting in differences between Pandora and OMI of up to ±65 % for total column nitrogen dioxide, and ±23 % for total column ozone. As expected, significant cloud cover (cloud fraction >0.2) was the most important parameter affecting comparisons of ozone retrievals; however, small, passing cumulus clouds that do not coincide with a high (>0.2) cloud fraction, or low aerosol layers which cause significant backscatter near the ground affected the comparisons of total column nitrogen dioxide retrievals. Our results will impact post-processing satellite retrieval algorithms and quality control procedures.

The current network of ground-based monitors for ozone (O3) is limited due to the spatial heterogeneity of O3 at the surface. Satellite measurements can provide a solution to this limitation, but the lack of sensitivity of satellites to O3 within the boundary layer causes large uncertainties in satellite retrievals at the near-surface. The vertical variability of O3 was investigated using ozonesondes collected as part of NASA’s Deriving Information on Surface Conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign during July 2011 in the Baltimore, MD/Washington D.C. metropolitan area. A subset of the ozonesonde measurements was corrected for a known bias from the electrochemical solution strength using new procedures based on laboratory and field tests. A significant correlation of O3 over the two sites with ozonesonde measurements (Edgewood and Beltsville, MD) was observed between the mid-troposphere (7–10 km) and the near-surface (1–3 km). A linear regression model based on the partial column amounts of O3 within these subregions was developed to calculate the near-surface O3 using mid-tropospheric satellite measurements from the Tropospheric Emission Spectrometer (TES) onboard the Aura spacecraft. The uncertainties of the calculated near-surface O3 using TES mid-tropospheric satellite retrievals and a linear regression model were less than 20 %, which is less than that of the observed variability of O3 at the surface in this region. These results utilize a region of the troposphere to which existing satellites are more sensitive compared to the boundary layer and can provide information of O3 at the near-surface using existing satellite infrastructure and algorithms.

[1] Air quality and meteorological measurements were conducted at the Chemistry and Physics of the Atmospheric Boundary Layer Experiment (CAPABLE) site during the summers of 2009 and 2010 in Hampton, Virginia. Significant differences in surface ozone mixing ratios were observed between the two years and are correlated with meteorological parameters such as temperature, humidity, and cloud cover. The number of exceedance days for ozone set by the U.S. Environmental Protection Agency within this region has been decreasing for the past decade, especially in urban areas. There were no exceedance days with respect to ozone in 2009, and there were four exceedance days in 2010. The four highest ozone daily maxima and the two exceedance days observed during the 2010 measurement period were coincident with sea breeze phenomena. In one case, surface ozone increased at a rate of 14.6 ppb h−1 with the passage of a sea breeze front. A comprehensive multilinear regression model as well as an operational forecast was unable to resolve the high ozone observed during sea breeze events. As the number of exceedance days per year within this region continues to decrease, accurately forecasting sea breezes may become more important for the forecasting of pollution events.

The National Air Quality Forecast Capability (NAQFC) and an experimental version of the NAQFC (NAQFC-β) provided flight decision support during the July 2011 NASA DISCOVER-AQ field campaign around Baltimore, Maryland. Ozone forecasts from the NAQFC and NAQFC-β were compared to surface observations at six air quality monitoring stations in the DISCOVER-AQ domain. A bootstrap algorithm was used to test for significant bias and error in the forecasts from each model. Both models produce significant positively biased forecasts in the morning while generally becoming insignificantly biased in the afternoon during peak ozone hours. The NAQFC-β produces higher forecast bias, higher forecast error, and lower correlations than the NAQFC. Forecasts from the two models were also compared to each other to determine the spatial and temporal extent of significant differences in forecasted ozone using a bootstrap algorithm. The NAQFC-β tends to produce an average background ozone mixing ratio of at least 3.51 ppbv greater than the NAQFC throughout the domain at 95 % significance. The difference between the two models is significant during the overnight and early morning hours likely due to the way the Carbon Bond 5 mechanism in the NAQFC-β handles reactive nitrogen recycling and organic peroxide species. The value of information each model provides was tested using a static cost-loss ratio model. By standard measures of forecast skill, the NAQFC generally outperforms the NAQFC-β; however, the NAQFC-β provides greater value of information. This is because standard measures of forecast skill often hide the sensitivity of end users’ needs to forecast error.