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A real-time air quality forecasting system was developed using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to provide support for flight planning activities during the NOAA Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) and NASA Synergistic TEMPO Air Quality Science (STAQS) 2023 field campaigns. The forecasting system operated on two separate domains centered on Chicago, IL, and New York City, NY, and provided 72-hour predictions of atmospheric composition, aerosols, and clouds. This study evaluates the Chicago-centered forecasting system's 1-, 2-, and 3-day ozone (O3) forecast skill for Chiwaukee Prairie, WI, a rural area downwind of Chicago that often experiences high levels of O3 pollution. Comparisons to vertical O3 profiles collected by a Tropospheric Ozone Lidar Network (TOLNet) instrument revealed that forecast skill decreases as forecast lead time increases. When compared to surface measurements, the forecasting system tended to underestimate O3 concentrations on high O3 days and overestimate on low O3 days at Chiwaukee Prairie regardless of forecast lead time. Using July 25, 2023, as a case study, analyses show that the forecasts underestimated peak O3 levels at Chiwaukee Prairie during this regionwide bad air quality day. Wind speed and direction data indicates that this underestimation can partially be attributed to lake breeze simulation errors. Surface fine particulate matter (PM2.5) measurements, Geostationary Operational Environmental Satellite-16 (GOES-16) aerosol optical depth (AOD) data, and back trajectories from the NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model show that transported Canadian wildfire smoke impacted the Lake Michigan region on this day. Errors in the forecasted chemical composition and transport of the smoke plumes also contributed to underpredictions of O3 levels at Chiwaukee Prairie on July 25, 2023. The results of this work help identify improvements that can be made for future iterations of the WRF-Chem forecasting system. Implications: Air quality forecasting is an important tool that can be used to inform the public about upcoming high pollution days so that individuals may plan accordingly to limit their exposure to health-damaging air pollutants. Forecasting also helps scientists make decisions about where to make observations during air quality field campaigns. A variety of observational datasets were used to evaluate the accuracy of an air quality forecasting system that was developed for NOAA and NASA field campaigns that occurred in the summer of 2023. These evaluations inform areas of improvement for future development of this air quality forecasting system. [ABSTRACT FROM AUTHOR]

The El Niño–Southern Oscillation (ENSO) is a major driver of interannual variability in both tropical latitudes and midlatitudes and has been found to have a strong impact on the distribution of tropospheric ozone in the tropical Pacific in satellite observational datasets, chemical transport models, and chemistry–climate simulations. Here we analyze interannual variability in tropical tropospheric ozone by applying composite analysis, empirical orthogonal function (EOF) analysis, and multiple linear regression to the Real-time Air Quality Modeling System (RAQMS) Aura (RAQMS-Aura) chemical reanalysis. As shown in similar studies, the dominant mode of interannual variability in tropical tropospheric ozone is driven by ENSO. ENSO composites show that the ENSO signature in tropospheric ozone is strongest near the tropopause. We also show an enhancement in tropical ozone over the maritime continent below 700 hPa during El Niño that is dependent on the magnitude of the biomass burning emissions in the region. We reconstruct the ENSO variability in tropical tropospheric ozone through a multiple linear regression of principal components for precipitation and CO. The multiple linear regression quantifies that variability in biomass burning contributes to ENSO variability in tropical tropospheric ozone, though the dominant driver is convective precipitation. [ABSTRACT FROM AUTHOR]

In California, emission control strategies have been implemented to reduce air pollutants. Here we estimate the changes in nitrogen oxides (NOx = NO + NO2) emissions in 2005-2010 using a state-of-the-art four-dimensional variational approach. We separately and jointly assimilate surface NO2 concentrations and tropospheric NO2 columns observed by Ozone Monitoring Instrument (OMI) into the regional-scale Sulfur Transport and dEposition Model (STEM) chemical transport model on a 12 × 12 km2 horizontal resolution grid in May 2010. The assimilation generates grid-scale top-down emission estimates, and the updated chemistry fields are evaluated with independent aircraft measurements during the NOAA California Nexus (CalNex) field experiment. The emission estimates constrained only by NO2 columns, only by surface NO2, and by both indicate statewide reductions of 26%, 29%, and 30% from ~0.3 Tg N/yr in the base year of 2005, respectively. The spatial distributions of the emission changes differ in these cases, which can be attributed to many factors including the differences in the observation sampling strategies and their uncertainties, as well as those in the sensitivities of column and surface NO2 with respect to NOx emissions. The updates in California's NOx emissions reduced the mean error in modeled surface ozone in the Western U.S., even though the uncertainties in some urban areas increased due to their NOx-saturated chemical regime. The statewide reductions in NOx emissions indicated from our observationally constrained emission estimates are also reflected in several independently developed inventories: ~30% in the California Air Resources Board bottom-up inventory, ~4% in the 2008 National Emission Inventory, and ~20% in the annual mean top-down estimates by Lamsal et al. using the global Goddard Earth Observing System (GEOS)-Chem model and OMI NO2 columns. Despite the grid-scale differences among all top-down and bottom-up inventories, they all indicate stronger emission reductions in the urban regions. This study shows the potential of using space-/ground-based monitoring data and advanced data assimilation approach to timely and independently update NOx emission estimates on a monthly scale and at a fine grid resolution. The well-evaluated results here suggest that these approaches can be applied more broadly.

Ozone is a pollutant formed in the atmosphere by photochemical processes involving nitrogen oxides (NO x) and volatile organic compounds (VOCs) when exposed to sunlight. Tropospheric boundary layer ozone is regularly measured at ground stations and sampled infrequently through balloon, lidar, and crewed aircraft platforms, which have demonstrated characteristic patterns with altitude. Here, to better resolve vertical profiles of ozone within the atmospheric boundary layer, we developed and evaluated an uncrewed aircraft system (UAS) platform for measuring ozone and meteorological parameters of temperature, pressure, and humidity. To evaluate this approach, a UAS was flown with a portable ozone monitor and a meteorological temperature and humidity sensor to compare to tall tower measurements in northern Wisconsin. In June 2020, as a part of the WiscoDISCO20 campaign, a DJI M600 hexacopter UAS was flown with the same sensors to measure Lake Michigan shoreline ozone concentrations. This latter UAS experiment revealed a low-altitude structure in ozone concentrations in a shoreline environment showing the highest ozone at altitudes from 20–100 m a.g.l. These first such measurements of low-altitude ozone via a UAS in the Great Lakes region revealed a very shallow layer of ozone-rich air lying above the surface. [ABSTRACT FROM AUTHOR]

The quantification of aerosol size distributions is crucial for understanding the climate and health impacts of aerosols, validating models, and identifying aerosol sources. This work provides one of the first continuous measurements of aerosol size distribution from 1.02 to 8671 nm near the shore of Lake Michigan. The data were collected during the Lake Michigan Ozone Study (LMOS 2017), a comprehensive air quality measurement campaign in May and June 2017. The time-resolved (2-min) size distribution are reported herein alongside meteorology, remotely sensed data, gravimetric filters, and gas-phase variables. Mean concentrations of key aerosol parameters include PM2.5 (6.4 μg m-3), number from 1 to 3 nm (1.80x104 cm-3) and number greater than 3 nm (8x103 cm-3). During the field campaign, approximately half of days showed daytime ultrafine burst events, characterized by particle growth from sub 10 nm to 25–100 nm. A specific investigation of ultrafine lake spray aerosol was conducted due to enhanced ultrafine particles in onshore flows coupled with sustained wave breaking conditions during the campaign. Upon closer examination, the relationships between the size distribution, wind direction, wind speed, and wave height did not qualitatively support ultrafine particle production from lake spray aerosol; statistical analysis of particle number and wind speed also failed to show a relationship. The alternative hypothesis of enhanced ultrafine particles in onshore flow originating mainly from new particle formation activity is supported by multiple lines of evidence. [ABSTRACT FROM AUTHOR]

We investigate the benefit of assimilating high spatial‐temporal resolution nitrogen dioxide (NO2) measurements from a geostationary (GEO) instrument such as Tropospheric Emissions: Monitoring of Pollution (TEMPO) versus a low‐earth orbit (LEO) platform like TROPOspheric Monitoring Instrument (TROPOMI) on the inverse modeling of nitrogen oxides (NOx) emissions. We generated synthetic TEMPO and TROPOMI NO2 measurements based on emissions from the COVID‐19 lockdown period. Starting with emissions levels prior to the lockdown, we use the Weather Research and Forecasting Model coupled with Chemistry/Data Assimilation Research Testbed (WRF‐Chem/DART) to assimilate these pseudo‐observations in Observing System Simulation Experiments to adjust NOx emissions and quantify how well the assimilation of TEMPO versus TROPOMI measurements recovers the lockdown‐induced emissions changes. We find that NOx emission biases can be ameliorated using half as many simulation days when assimilating GEO observations, and the estimated NOx emissions in 23 out of 29 major urban regions in the US are more accurate. The root mean square error and coefficient of determination of posterior NOx emissions are reduced by 12.5%–41.5% and 1.5%–17.1%, respectively, across different regions. We conduct sensitivity experiments that use different data assimilation (DA) configurations to assimilate synthetic GEO observations. Results demonstrate that the temporal width of the DA window introduces −10% to −20% biases in the emissions inversion and constraining both NOx concentrations and emissions simultaneously yields the most accurate NOx emissions estimates. Our work serves as a valuable reference on how to appropriately assimilate GEO observations for constraining NOx emissions in future studies. Plain Language Summary: Nitrogen oxides (NOx) are major air pollutants and precursors to tropospheric ozone and secondary inorganic aerosols. The diverse natural and anthropogenic sources of NOx pose a challenge for NOx emissions estimates. Inverse modeling techniques which use observations to infer emissions can be applied to improve our understanding of anthropogenic NOx emissions. This study aims to compare the ability of the new geostationary (GEO) instrument Tropospheric Emissions: Monitoring of Pollution (TEMPO) and the existing low‐earth orbit instrument TROPOspheric Monitoring Instrument (TROPOMI) to constrain NOx emissions. Synthetic TEMPO and TROPOMI NO2 measurements are generated and assimilated to constrain NOx emissions in an idealized experiment in which the "true" emissions are known. The results show the true NOx emissions can be retrieved using half as many simulation days when assimilating GEO NO2 observations. Moreover, the experiment that assimilates GEO NO2 observations improves the accuracy of estimated NOx emissions by 12.5%–41.5% and 1.5%–17.1% in terms of root mean square error and coefficient of determination, respectively, across different air quality regions. The NOx emissions in most urban regions are better constrained when assimilating GEO NO2 data. We also propose best practices for assimilating GEO NO2 observations, which can serve as reference for future research. Key Points: True NOx emissions can be recovered using half as many simulation days when assimilating synthetic Tropospheric Emissions: Monitoring of Pollution (TEMPO) observations rather than TROPOspheric Monitoring InstrumentAssimilating synthetic TEMPO observations improve emissions inversion accuracy by 13%–42% across different regions of USThe best estimates of NOx emissions are achieved by using short data assimilation window (e.g., 30 min) and updating concentrations/emissions jointly [ABSTRACT FROM AUTHOR]

Ozone is a pollutant formed in the atmosphere by photochemical processes involving nitrogen oxides (NOx) and volatile organic compounds (VOCs) when exposed to sunlight. Tropospheric boundary layer ozone is regularly measured at ground stations and sampled infrequently through balloon, lidar, and crewed aircraft platforms, which have demonstrated characteristic patterns with altitude. Here, to better resolve vertical profiles of ozone within the atmospheric boundary layer, we developed and evaluated an uncrewed aircraft system (UAS) platform for measuring ozone and meteorological parameters of temperature, pressure, and humidity. To evaluate this approach, an UAS was flown with a portable ozone monitor and a meteorological temperature and humidity sensor to compare to tall tower measurements in northern Wisconsin. In June 2020, as a part of the WiscoDISCO20 campaign, a DJI M600 hexacopter UAS was flown with the same sensors to measure Lake Michigan shoreline ozone concentrations. This latter UAS experiment revealed low-altitude structure in ozone concentrations in a shoreline environment showing highest ozone at altitudes from 20-100 mAGL. These first such measurements of lowaltitude ozone via UAS in the Great Lakes Region revealed a very shallow layer of ozone rich air lying above the surface. [ABSTRACT FROM AUTHOR]

We evaluate two high-resolution Lake Michigan air quality simulations during the 2017 Lake Michigan Ozone Study campaign. These air quality simulations employ identical chemical configurations but use different input meteorology. The AP-XM configuration follows the U.S. Environmental Protection Agency (EPA)-recommended modeling practices, whereas the YNT_SSNG employs different parameterization schemes and satellite-based inputs of sea surface temperatures, green vegetative fraction, and soil moisture and temperature. Overall, we find a similar performance in the model simulations of hourly and maximum daily average 8 h (MDA8) ozone, with the AP-XM and YNT_SSNG simulations showing biases of -11.42 and -13.54 ppbv (parts per billion by volume), respectively, during periods when the observed MDA8 was greater than 70 ppbv. However, for the two monitoring sites that observed high-ozone events, the AP-XM simulation better matched observations at Chiwaukee Prairie, and the YNT_SSNG simulation better matched observations at the Sheboygan Kohler-Andrae (KA) State Park. We find that the differences between the two simulations are largest for column amounts of ozone precursors, particularly NO 2. Across three high-ozone events, the YNT_SSNG simulation has a lower NO 2 column bias (0.17×1015 mol cm -2) compared to the AP-XM simulation (0.31×1015 mol cm -2). The YNT_SSNG simulation also has an advantage in that it better captures the structure of the boundary layer and lake breeze during the 2 June high-ozone event, although the timing of the lake breeze is about 3 h too early at Sheboygan. Our results are useful for informing an air quality modeling framework for the Lake Michigan area. [ABSTRACT FROM AUTHOR]

High-resolution simulations were performed to assess the impact of different parameterization schemes, surface datasets, and analysis nudging on lower-tropospheric conditions near Lake Michigan. Simulations were performed where climatological or coarse-resolution surface datasets were replaced by high-resolution, real-time datasets depicting the lake surface temperatures (SSTs), green vegetation fraction (GVF), and soil moisture and temperature (SOIL). Comparison of two baseline simulations employing different parameterization schemes (referred to as AP-XM and YNT, respectively) showed that the AP-XM simulation produced more accurate analyses on the outermost 12 km resolution domain but that the YNT simulation was superior for higher-resolution nests. The diurnal evolution of the surface energy fluxes was similar in both simulations on the 12 km grid but differed greatly on the 1.3 km grid where the AP-XM simulation had a much smaller sensible heat flux during the daytime and a physically unrealistic ground heat flux. Switching to the YNT configuration led to more accurate 2 m temperature and 2 m water vapor mixing ratio analyses on the 1.3 km grid. Additional improvements occurred when satellite-derived surface datasets were incorporated into the modeling platform, with the SOIL dataset having the largest positive impact on temperature and water vapor. The GVF and SST datasets also produced more accurate temperature and water vapor analyses but had degradations in wind speed, especially when using the GVF dataset. The most accurate simulations were obtained when using the high-resolution SST and SOIL datasets and analysis nudging above 2 km a.g.l. (above ground level). These results demonstrate the value of using high-resolution satellite-derived surface datasets in model simulations. [ABSTRACT FROM AUTHOR]

High-resolution simulations were performed to assess the impact of different parameterization schemes, surface initialization datasets, and analysis nudging on lower-tropospheric conditions near Lake Michigan. Simulations were run where climatological or coarse-resolution surface initialization datasets were replaced by high-resolution, real-time datasets depicting lake surface temperatures (SST), green vegetation fraction (GVF), and soil moisture and temperature (SOIL). Comparison of a baseline simulation employing a configuration similar to that used at the Environmental Protection Agency ("EPA") to another simulation employing an alternative set of parameterization schemes (referred to as "YNT") showed that the EPA configuration produced more accurate analyses on the outermost 12-km resolution domain, but that the YNT configuration was superior for higher-resolution nests. The diurnal evolution of the surface energy fluxes was similar in both simulations on the 12-km grid but differed greatly on the 1.3-km grid where the EPA simulation had much smaller sensible heat flux during the daytime and physically unrealistic ground heat flux. Switching to the YNT configuration led to substantial decreases in root mean square error for 2-m temperature and 2-m water vapor mixing ratio on the 1.3-km grid. Additional improvements occurred when the high-resolution satellite-derived surface datasets were incorporated into the modeling platform, with the SOIL dataset having the largest positive impact on temperature and water vapor. The GVF and SST datasets also produced more accurate temperature and water vapor analyses, but degradations in wind speed, especially when using the GVF dataset. The most accurate simulations were obtained when using the high-resolution SST and SOIL datasets and analysis nudging above 2 km AGL. [ABSTRACT FROM AUTHOR]

High-resolution simulations were performed to assess the impact of different parameterization schemes, surface initialization datasets, and analysis nudging on lower-tropospheric conditions near Lake Michigan. Simulations were run where climatological or coarse-resolution surface initialization datasets were replaced by high-resolution, real-time datasets depicting lake surface temperatures (SST), green vegetation fraction (GVF), and soil moisture and temperature (SOIL). Comparison of a baseline simulation employing a configuration similar to that used at the Environmental Protection Agency ("EPA") to another simulation employing an alternative set of parameterization schemes (referred to as "YNT") showed that the EPA configuration produced more accurate analyses on the outermost 12-km resolution domain, but that the YNT configuration was superior for higher-resolution nests. The diurnal evolution of the surface energy fluxes was similar in both simulations on the 12-km grid but differed greatly on the 1.3-km grid where the EPA simulation had much smaller sensible heat flux during the daytime and physically unrealistic ground heat flux. Switching to the YNT configuration led to substantial decreases in root mean square error for 2-m temperature and 2-m water vapor mixing ratio on the 1.3-km grid. Additional improvements occurred when the high-resolution satellite-derived surface datasets were incorporated into the modeling platform, with the SOIL dataset having the largest positive impact on temperature and water vapor. The GVF and SST datasets also produced more accurate temperature and water vapor analyses, but degradations in wind speed, especially when using the GVF dataset. The most accurate simulations were obtained when using the high-resolution SST and SOIL datasets and analysis nudging above 2 km AGL. [ABSTRACT FROM AUTHOR]

Satellite observations of tropospheric NO 2 columns can provide top-down observational constraints on emissions estimates of nitrogen oxides (NOx). Mass-balance-based methods are often applied for this purpose but do not isolate near-surface emissions from those aloft, such as lightning emissions. Here, we introduce an inverse modeling framework that couples satellite chemical data assimilation to a chemical transport model. In the framework, satellite-constrained emissions totals are inferred using model simulations with and without data assimilation in the iterative finite-difference mass-balance method. The approach improves the finite-difference mass-balance inversion by isolating the near-surface emissions increment. We apply the framework to separately estimate lightning and anthropogenic NOx emissions over the Northern Hemisphere for 2019. Using overlapping observations from the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI), we compare separate NOx emissions inferences from these satellite instruments, as well as the impacts of emissions changes on modeled NO 2 and O 3. OMI inferences of anthropogenic emissions consistently lead to larger emissions than TROPOMI inferences, attributed to a low bias in TROPOMI NO 2 retrievals. Updated lightning NOx emissions from either satellite improve the chemical transport model's low tropospheric O 3 bias. The combined lighting and anthropogenic emissions updates improve the model's ability to reproduce measured ozone by adjusting natural, long-range, and local pollution contributions. Thus, the framework informs and supports the design of domestic and international control strategies. [ABSTRACT FROM AUTHOR]

High concentrations of ozone along the coastline of Lake Michigan are a persistent air quality management challenge. Complementing observations during the 2017 Lake Michigan Ozone Study (LMOS 2017), WRF‐Chem modeling was used to quantify sensitivity of modeled ozone (O3) to anthropogenic nitrogen oxides (NOx) and volatile organic compound (VOC) emissions, including to changes in volatile chemical product (VCP). The daily maximum 8 hr average (MDA8) over the high ozone region of Lake Michigan decreased by 2.7 ppb with exclusion of VCP from the inventory, and was sensitive to both NOx and VOC changes, with greater sensitivity to NOx. Close to urban centers, MDA8 ozone was VOC‐sensitive. Clusters of coastal receptor sites were identified based on similarity in response to emission perturbations, with most clusters being NOx‐sensitive and NOx‐sensitivity increasing with distance from major emission sources. The 2 June 2017 ozone event, which has received considerable focus, is shown to be atypical due to unusually strong and spatially extended VOC‐sensitive behavior. WRF‐Chem integrated reaction rate analysis was used to compute radical termination rates due to NOx (LNOx) and to radical‐radical reactions (LROx). LROx/LNOx and formaldehyde to NO2 ratio (FNR) were shown to be predictive of modeled MDA8 ozone sensitivity, but with variation in predictive power as a function of time of day, which has implications for air quality management use of FNR from geostationary satellites. Plain Language Summary: Surface ozone is an air pollutant of concern due to human health impacts. In locations with elevated ozone concentrations, including coastal regions around Lake Michigan, ozone pollution is managed by controlling emissions of the two classes of chemicals that drive ozone chemistry: volatile organic compounds (VOCs) and nitrogen oxides (NOx). However, due to large reductions in emissions of NOx and VOC over the past 20 years, the leverage that future reductions will have is uncertain. Reductions of 4–5 ppb (∼7%) are needed in several locations, relative to 2017–2019 concentrations, to meet the 2015 ozone standard of 70 ppb. In this paper, we use simulations of atmospheric chemistry and airflow over the Midwestern US to address this issue. By comparing simulations based on different VOC and NOx emissions, we find that reductions in NOx emissions have more influence on ozone than reductions in VOC emissions, except for a small zone downwind of Chicago. On high ozone days over Lake Michigan, a 10% decrease in VOC (NOx) emissions can lower ozone in the key high ozone zone over southern Lake Michigan by 0.4% (0.8%). Volatile chemical products, an uncertain component of emission inventories, are responsible for 2.7 ppb (∼4%) of ozone. Key Points: Outside of a small (85 km) zone downwind of Chicago, ozone concentrations and production near Lake Michigan is generally NOx‐sensitiveOn event days 10% decrease in volatile organic compound emission can lower MDA8 by 0.4% and 10% decrease in nitrogen oxides emission can lower MDA8 by 0.8% over Lake MichiganVolatile chemical product emissions were modeled to produce an average 2.7 ppb ozone increase over the lake [ABSTRACT FROM AUTHOR]

We use the Weather Research and Forecasting with Chemistry (WRF-Chem) model with new implementations of GOES-16 wildfire emissions and plume rise based on fire radiative power (FRP) to interpret aerosol observations during the 2019 NASA-NOAA FIREX-AQ field campaign and perform model evaluations. We compare simulated aerosol concentrations and optical properties against observations of black carbon aerosol from the NOAA Single Particle Soot Photometer (NOAA-SP2), organic aerosol from the CU High-Resolution Aerosol Mass Spectrometer (HR-AMS), and aerosol backscatter coefficients from the high-spectral-resolution lidar (HSRL) system. This study focuses on the Williams Flats fire in Washington, which was repeatedly sampled during four science flights by the NASA DC-8 (3–8 August 2019). The emissions and plume-rise methodologies are implemented following NOAA's operational High-Resolution Rapid Refresh coupled with Smoke (HRRR-Smoke) forecasting model. In addition, new GOES-16 FRP-based diurnal cycle functions are developed and incorporated into WRF-Chem. The FIREX-AQ observations represented a diverse set of sampled environments ranging from fresh/aged smoke from the Williams Flats fire to remnants of plumes transported over long distances. The Williams Flats fire resulted in significant aerosol enhancements during 3–8 August 2019, which were substantially underestimated by the standard version of WRF-Chem. The simulated black carbon (BC) and organic carbon (OC) concentrations increased between a factor of 92–125 (BC) and a factor of 28–78 (OC) with the new implementation compared to the standard WRF-Chem version. These increases resulted in better agreement with the FIREX-AQ airborne observations for BC and OC concentrations (particularly for fresh smoke sampling phases) and aerosol backscatter coefficients. The model still showed a low bias in simulating the aerosol loadings observed in aged plumes from Williams Flats. WRF-Chem with the FRP-based plume rise simulated similar plume heights to the standard plume-rise model in WRF-Chem. The simulated plume heights (for both versions) compared well with estimated plume heights using the HSRL measurements. Therefore, the better agreement with observations was mainly driven by the higher emissions in the FRP-based version. The model evaluations also highlighted the importance of accurately accounting for the wildfire diurnal cycle and including adequate representation of the underlying chemical mechanisms, both of which could significantly impact model forecasting performance. [ABSTRACT FROM AUTHOR]

Satellite observations of tropospheric NO2 columns can provide top-down observational constraints on emissions estimates of nitrogen oxides (NOx). Mass-balance based methods are often applied for this purpose, but do not isolate near surface emissions from those aloft, such as lightning emissions. Here, we introduce an inverse modeling framework that couples satellite chemical data assimilation to a chemical transport model and infers satellite-constrained emissions totals using the iterative finite-difference mass-balance method. The approach improves the finite-difference mass-balance inversion by isolating the near-surface emissions increment. We apply the framework to estimate lightning and anthropogenic NOx emissions over the Northern Hemisphere. Using overlapping observations from the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI), we compare NOx emissions inferences from these satellite instruments, as well as the impacts of emissions changes on modeled NO2 and O3. OMI inferences of anthropogenic emissions consistently lead to larger emissions than TROPOMI inferences, attributed to a low bias in TROPOMI NO2 retrievals. Updated lightning NOx emissions from either satellite improve the chemical transport model's low tropospheric O3 bias. Combined lightning and anthropogenic updates inferred from satellite observations can improve the model's ability to represent background and ground-level O3 concentrations, an ongoing policy consideration in the U.S. as domestic and international emissions control strategies evolve. [ABSTRACT FROM AUTHOR]

The mesoscale meteorology of lake breezes along Lake Michigan impacts local observations of high-ozone events. Previous manned aircraft and UAS observations have demonstrated non-uniform ozone concentrations within and above the marine layer over water and within shoreline environments. During the 2021 Wisconsin's Dynamic Influence of Shoreline Circulations on Ozone (WiscoDISCO-21) campaign, two UAS platforms, a fixed-wing (University of Colorado RAAVEN) and a multirotor (Purdue University DJI M210), were used simultaneously to capture lake breeze during forecasted high-ozone events at Chiwaukee Prairie State Natural Area in southeastern Wisconsin from 21–26 May 2021​​​​​​​. The RAAVEN platform (data DOI: 10.5281/zenodo.5142491, de Boer et al., 2021) measured temperature, humidity, and 3-D winds during 2 h flights following two separate flight patterns up to three times per day at altitudes reaching 500 m above ground level (a.g.l.). The M210 platform (data DOI: 10.5281/zenodo.5160346, Cleary et al., 2021a) measured vertical profiles of temperature, humidity, and ozone during 15 min flights up to six times per day at altitudes reaching 120 ma.g.l. near a Wisconsin DNR ground monitoring station (AIRS ID: 55-059-0019). This campaign was conducted in conjunction with the Enhanced Ozone Monitoring plan from the Wisconsin DNR that included Doppler lidar wind profiler observations at the site (data DOI: 10.5281/zenodo.5213039, Cleary et al., 2021b). [ABSTRACT FROM AUTHOR]

Ground-based thermodynamic and kinematic profilers were placed adjacent to the western shore of Lake Michigan at two sites as part of the 2017 Lake Michigan Ozone Study. The southern site near Zion, Illinois, hosted a microwave radiometer (MWR) and a sodar wind profiler, while the northern site in Sheboygan, Wisconsin, featured an Atmospheric Emitted Radiance Interferometer (AERI), a Doppler lidar, and a High Spectral Resolution Lidar (HSRL). Each site experienced several lake-breeze events during the experiment. Composite time series and time–height cross sections were constructed relative to the lake-breeze arrival time so that commonalities across events could be explored. The composited surface observations indicate that the wind direction of the lake breeze was consistently southeasterly at both sites regardless of its direction before the arrival of the lake-breeze front. Surface relative humidity increased with the arriving lake breeze, though this was due to cooler air temperatures as absolute moisture content stayed the same or decreased. The profiler observations show that the lake breeze penetrated deeper when the local environment was unstable and preexisting flow was weak. The cold air associated with the lake breeze remained confined to the lowest 200 m of the troposphere even if the wind shift was observed at higher altitudes. The evolution of the lake breeze corresponded well to observed changes in baroclinicity and calculated changes in circulation. Collocated observations of aerosols showed increases in number and mass concentrations after the passage of the lake-breeze front. [ABSTRACT FROM AUTHOR]

We use the Weather Research and Forecasting with Chemistry (WRF-Chem) model with new implementations of GOES-16 fire radiative power (FRP) based wildfire emissions and plume-rise to interpret aerosol observations during the 2019 NASA-NOAA FIREX-AQ field campaign and perform model evaluations. We compare simulated aerosol concentrations and optical properties against observations of black carbon aerosol from the NOAA Single Particle Soot Photometer (NOAA-SP2), organic aerosol from the CU High Resolution Aerosol Mass Spectrometer (HR36 AMS) and aerosol backscatter coefficients from the High Spectral Resolution Lidar (HSRL) system. This study focuses on the Williams Flats fire in Washington, which was repeatedly sampled during four science flights by the NASA DC-8 (August 3 – August 8, 2019). The emissions and plume-rise methodologies are implemented following NOAA’s operational High Resolution Rapid Refresh coupled with Smoke (HRRR-Smoke) forecasting model. In addition, new GOES-16 FRP based diurnal cycle functions are developed and incorporated in WRF-Chem. The FIREX-AQ observations represented a diverse set of sampled environments ranging from fresh/aged smoke from the Williams Flats fire to remnants of plumes transported over long distances. The Williams Flats fire resulted in significant aerosol enhancements during August 3- 8, 2019, which were substantially underestimated by the standard version of WRF-Chem. The simulated BC and OC concentrations increased between 92 – 125 times (BC) and 28-78 times (OC) with the new implementation compared to the standard WRF-Chem version. These increases resulted in better agreement with the FIREX-AQ airborne observations for BC and OC concentrations (particularly for fresh smoke sampling phases) and aerosol backscatter coefficients. The model still showed a low bias in simulating the aerosol loadings observed in aged plumes from Williams Flats. WRF-Chem with the FRP-based plumerise simulated similar plume heights to the standard plumerise model in WRF-52 Chem. The simulated plume heights (for both versions) compared well with estimated plume heights using the HSRL measurements. Therefore, the improvements in the model simulation were mainly driven by the higher emissions in the FRP55 based version. The model evaluations also highlighted the importance of accurately accounting for the wildfire diurnal cycle and including adequate representation of the underlying chemical mechanisms, both of which could significantly impact model forecasting performance. [ABSTRACT FROM AUTHOR]

The meso-scale meteorology of lake breezes along Lake Michigan impacts local observations of high ozone events. Previous manned aircraft and UAS observations have demonstrated non-uniform ozone concentrations within and above the marine layer over water and within shoreline environments. During the 2021 Wisconsin's Dynamic Influence of Shoreline Circulations on Ozone (WiscoDISCO-21) campaign, two UAS platforms, a fixed-wing (University of Colorado RAAVEN) and a multirotor (Purdue University DJI M210), were used simultaneously to capture lake breeze during forecasted high ozone events at Chiwaukee Prairie State Natural Area in southeastern Wisconsin from May 21-26, 2021. The RAAVEN platform (data DOI: 10.5281/zenodo.5142491) measured temperature, humidity, and 3-D winds during 2-hour flights following two separate flight patterns up to 3 times per day at altitudes reaching 500 m above ground level. The M210 platform (data DOI: 10.5281/zenodo.5160346) measured vertical profiles of temperature, humidity and ozone during 15-minute flights up to 6 times per day at altitudes reaching 120 m above ground level (AGL) near to a WI-DNR ground monitoring station (AIRS ID: 55-059-0019). This campaign was conducted in conjunction with the Enhanced Ozone Monitoring plan from WI-DNR that included Doppler lidar wind profiler observations at the site (data DOI:10.5281/zenodo.5213039). [ABSTRACT FROM AUTHOR]

Ten years of stratospheric geopotential height data are analyzed in an attempt to determine whether there are preferred flow regimes in the Northern Hemisphere winter stratosphere. The data are taken from Stratospheric Sounding Units on board NOAA satellites. The probability density estimate of the amplitude of the wavenumber 1 10-mb height is found to be bimodal. The density distribution is composed of a dominant large-amplitude mode and a less frequent low-amplitude mode. When the wavenumber 1 10-mb height data are projected onto the phase plane defined by the 10-mb zonal-mean winds and wavenumber 1 100-mb heights, three preferred regimes are evident. The small-amplitude mode separates into a strong zonal wind-weak wave regime and a weak zonal wind-weak wave regime. The large-amplitude mode is an intermediate zonal wind-strong wave regime. Transitions between the large-amplitude regime and the weak zonal wind-weak wave regime are found to be associated with major stratospheric warmings. The clustering of the stratospheric data into the preferred flow regimes is interpreted in light of the bifurcation properties of the Holton and Mass model. The interannual variability of the Northern Hemisphere winter stratosphere is interpreted in terms of the relative frequency of the observed preferred regimes.

Wildfire smoke influences on air quality and atmospheric chemistry have been underscored by the increasing fire prevalence in recent years, and yet, the connection between fire, smoke emissions, and the subsequent transformation of this smoke in the atmosphere remains poorly constrained. Toward improving these linkages, we present a new method for coupling high time‐resolution satellite observations of fire radiative power with in situ observations of smoke aerosols and trace gases. We apply this technique to 13 fire plumes comprehensively characterized during the recent FIREX‐AQ mission and show that changes in fire radiative power directly translate into changes in conserved smoke tracers (CO2, CO, and black carbon aerosol) observed in the downwind smoke plume. The correlation is particularly strong for CO2 (mean r > 0.9). This method is important for untangling the competing effects of changing fire behavior versus the influence of dilution and atmospheric processing on the downwind evolution of measured smoke properties. Key Points: Geostationary satellite observations of fire radiative power are highly correlated with in situ airborne measurements of primary‐emission smoke tracersHigh‐resolution satellite observations are needed to disentangle how fire activity and plume dilution impact the downwind evolution of smokeDiurnal fire activity for wildfires observed during FIREX‐AQ is best parameterized using a bimodal Gaussian distribution to inform models [ABSTRACT FROM AUTHOR]

Airborne and ground-based Pandora spectrometer NO 2 column measurements were collected during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound region, which coincided with early observations from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOMI NO 2 Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NO 2. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (r2= 0.92 and slope of 1.03), with the largest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representativity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representativity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250 m × 250 m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (r2=0.96) than Pandora measurements are with TROPOMI (r2=0.84). The largest outliers between TROPOMI and the reference measurements appear to stem from too spatially coarse a priori surface reflectivity (0.5 ∘) over bright urban scenes. In this work, this results during cloud-free scenes that, at times, are affected by errors in the TROPOMI cloud pressure retrieval impacting the calculation of tropospheric air mass factors. This factor causes a high bias in TROPOMI TrVCs of 4 %–11 %. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19 %–33 % during the LISTOS timeframe of June–September 2018. Part of this low bias is caused by coarse a priori profile input from the TM5-MP model; replacing these profiles with those from a 12 km North American Model–Community Multiscale Air Quality (NAMCMAQ) analysis results in a 12 %–14 % increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7 %–19 % low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets. [ABSTRACT FROM AUTHOR]

Abundant NO[sub 2] column measurements from airborne and ground-based Pandora spectrometers were collected as part of the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound region and coincided with early measurements from the Sentinel-5P TROPOMI instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOspheric Monitoring Instrument (TROPOMI) NO[sub 2] Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NO[sub 2]. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (r[sup 2]=0.92 and slope of 1.03) with the biggest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representivity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representivity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250 m × 250 m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (r[sup 2]=0.96) than Pandora measurements are with TROPOMI (r[sup 2]=0.84). The largest outliers between TROPOMI and the reference measurements are caused by errors in the TROPOMI retrieval of cloud pressure impacting the calculation of tropospheric air mass factors in cloud-free scenes. This factor causes a high bias in TROPOMI TrVCs of 4-11 %. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19-33% during the LISTOS timeframe of June-September 2018. Part of this low bias is caused by coarse a priori profile input from TM5-MP model; replacing these profiles with those from a 12 km NAMCMAQ analysis results in a 12-14 % increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7-19 % low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets. [ABSTRACT FROM AUTHOR]

NASA deployed the GeoTASO airborne UV–visible spectrometer in May–June 2017 to produce high-resolution (approximately 250m×250m) gapless NO2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. The results collected show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO2 observations (r2=0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and spatial heterogeneity that may be observed differently by the sunward-viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO (Tropospheric Emissions: Monitoring Pollution), TROPOMI (TROPOspheric Monitoring Instrument), and OMI (Ozone Monitoring Instrument), the agreement with Pandora measurements degraded, particularly for the most polluted columns as localized large pollution enhancements observed by Pandora and GeoTASO are spatially averaged with nearby less-polluted locations within the larger area representative of the satellite spatial resolutions (aircraft-to-Pandora slope: TEMPO scale =0.88 ; TROPOMI scale =0.77 ; OMI scale =0.57). In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well at least up to pollution scales of 30×1015 molecules cm -2. Two publicly available OMI tropospheric NO2 retrievals are found to be biased low with respect to these Pandora observations. However, the agreement improves when higher-resolution a priori inputs are used for the tropospheric air mass factor calculation (NASA V3 standard product slope =0.18 and Berkeley High Resolution product slope =0.30). Overall, this work explores best practices for satellite validation strategies with Pandora direct-sun observations by showing the sensitivity to product spatial resolution and demonstrating how the high-spatial-resolution NO2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high-temporal-resolution ground-based column observations to evaluate the influence of spatial heterogeneity on validation results. [ABSTRACT FROM AUTHOR]

We report on the sensitivity of enhanced ozone (O3) production, observed during lake breeze circulation along the coastline of Lake Michigan, to the concentrations of nitrogen oxides (NOx = NO + NO2) and volatile organic compounds (VOCs). We assess the sensitivity of O3 production to NOx and VOC on a high O3 day during the Lake Michigan Ozone Study 2017 using an observationally constrained chemical box model that implements the Master Chemical Mechanism (MCM v3.3.1) and recent emission inventories for NOx and VOCs. The Master Chemical Mechanism model is coupled to a backward air mass trajectory analysis from a ground supersite in Zion, IL, where an extensive series of measurements of O3 precursors and their oxidation products, including hydrogen peroxide (H2O2), nitric acid (HNO3), and particulate nitrates (NO3−) serve as model constraints. We evaluate the chemical evolution of the Chicago‐Gary urban plume as it advects over Lake Michigan and demonstrate how modeled indicators of VOC‐ versus NOx‐sensitive regimes can be constrained by measurements at the trajectory endpoint. Using the modeled ratio of the instantaneous H2O2 and HNO3 production rates (PH2O2/PHNO3), we suggest that O3 production over the urban source region is strongly VOC sensitive and progresses towards a more NOx‐sensitive regime as the plume advects north along the Lake Michigan coastline on this day. We also demonstrate that ground‐based measurements of the mean concentration ratio of H2O2 to HNO3 describe the sensitivity of O3 production to VOC and NOx as the integral of chemical production along the plume path. Key Points: Direct observations of H2O2/HNO3 at an urban plume endpoint can be used to assess the integrated O3 sensitivity to NOx and VOC emissionsIndicators of O3 sensitivity show that the urban plume traveling over Lake Michigan evolves from VOC towards NOx‐sensitive O3 productionO3, H2O2, HNO3, and NO3− provide unique constraints to predict the response of O3 to changes in VOC and NOx emissions in coastal regions [ABSTRACT FROM AUTHOR]

NASA deployed an airborne UV/Visible spectrometer, GeoTASO, in May-June 2017 to produce high resolution (approximately 250 x 250 m), gapless NO2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. Results show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO2 observations (r² = 0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and also spatial heterogeneity that may be observed differently by the sunward viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO, TROPOMI, and OMI, the agreement with Pandora measurements is degraded as localized polluted plumes observed by Pandora are spatially averaged over larger areas (aircraft-to-Pandora slope: TEMPO scale = 0.88; TROPOMI scale = 0.77; OMI scale = 0.57). This behavior suggests that satellite products are representative of individual Pandora observations up to a certain pollution scale that depends on satellite spatial resolution. In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well up to pollution scales of 30 x 1015 molecules cm-2. Two publicly available OMI tropospheric NO2 retrievals are both found to be biased low with respect to Pandora observations (NASA V3 Standard Product slope = 0.18 and Berkeley High Resolution Product slope = 0.30). However, the agreement improves when higher resolution a priori inputs are used for the tropospheric air mass factor calculation. Overall, this work explores best practices for satellite validation strategies by showing the sensitivity to product spatial resolution and demonstrates how the high spatial resolution NO2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high temporal resolution surface observations to evaluate the influence of spatial heterogeneity on validation results. [ABSTRACT FROM AUTHOR]

Ambient air pollution from ozone and fine particulate matter is associated with premature mortality. As emissions from one continent influence air quality over others, changes in emissions can also influence human health on other continents. We estimate global air pollution-related premature mortality from exposure to PM2.5 and ozone, and the avoided deaths from 20 % anthropogenic emission reductions from six source regions, North America (NAM), Europe (EUR), South Asia (SAS), East Asia (EAS), Russia/Belarus/Ukraine (RBU) and the Middle East (MDE), three emission sectors, Power and Industry (PIN), Ground Transportation (TRN) and Residential (RES) and one global domain (GLO), using an ensemble of global chemical transport model simulations coordinated by the second phase of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP2), and epidemiologically-derived concentration-response functions. We build on results from previous studies of the TF-HTAP by using improved atmospheric models driven by new estimates of 2010 emissions, with more source and receptor regions, new consideration of source sector impacts, and new epidemiological mortality functions. We estimate 290,000 (95 % CI: 30,000, 600,000) premature O3-related deaths and 2.8 million (0.5 million, 4.6 million) PM2.5-related premature deaths globally for the baseline year 2010. While 20 % emission reductions from one region generally lead to more avoided deaths within the source region than outside, reducing emissions from MDE and RBU can avoid more O3-related deaths outside of these regions than within, and reducing MDE emissions also avoids more PM2.5-related deaths outside of MDE than within. In addition, EUR, MDE and RBU have more avoided O3-related deaths from reducing foreign emissions than from domestic reductions. For six regional emission reductions, the total avoided extraregional mortality is estimated as 10,300 (6,700, 13,400) deaths/year and 42,000 (12,400, 60,100) deaths/year through changes in O3 and PM2.5, respectively. Interregional transport of air pollutants leads to more deaths through changes in PM2.5 than in O3, even though O3 is transported more on interregional scales, since PM2.5 has a stronger influence on mortality. In sectoral emission reductions, TRN emissions account for the greatest fraction (26–53 % of global emission reduction) of O3-related premature deaths in most regions, except for EAS (58 %) and RBU (38 %) where PIN emissions dominate. In contrast, PIN emission reductions have the greatest fraction (38–78 % of global emission reduction) of PM2.5-related deaths in most regions, except for SAS (45 %) where RES emission dominates. The spread of air pollutant concentration changes across models contributes most to the overall uncertainty in estimated avoided deaths, highlighting the uncertainty in results based on a single model. Despite uncertainties, the health benefits of reduced intercontinental air pollution transport suggest that international cooperation may be desirable to mitigate pollution transported over long distances. [ABSTRACT FROM AUTHOR]

The recent update on the US National Ambient Air Quality Standards (NAAQS) of the ground-level ozone (O3) can benefit from a better understanding of its source contributions in different US regions during recent years. In the Hemispheric Transport of Air Pollution experiment phase 1 (HTAP1), various global models were used to determine the O3 source-receptor (SR) relationships among three continents in the Northern Hemisphere in 2001. In support of the HTAP phase 2 (HTAP2) experiment that studies more recent years and involves higher-resolution global models and regional models' participation, we conduct a number of regional-scale Sulfur Transport and dEposition Model (STEM) air quality base and sensitivity simulations over North America duringMay-June 2010. STEM's top and lateral chemical boundary conditions were downscaled from three global chemical transport models' (i.e., GEOS-Chem, RAQMS, and ECMWF C-IFS) base and sensitivity simulations in which the East Asian (EAS) anthropogenic emissions were reduced by 20%. The mean differences between STEM surface O3 sensitivities to the emission changes and its corresponding boundary condition model's are smaller than those among its boundary condition models, in terms of the regional/period-mean (<10%) and the spatial distributions. An additional STEM simulation was performed in which the boundary conditions were downscaled from a RAQMS (Realtime Air Quality Modeling System) simulation without EAS anthropogenic emissions. The scalability of O3 sensitivities to the size of the emission perturbation is spatially varying, and the full (i.e., based on a 100% emission reduction) source contribution obtained from linearly scaling the North American mean O3 sensitivities to a 20% reduction in the EAS anthropogenic emissions may be underestimated by at least 10%. The three boundary condition models' mean O3 sensitivities to the 20% EAS emission perturbations are 8%(May-June 2010)/~11%(2010 annual) lower than those estimated by eight global models, and the multi-model ensemble estimates are higher than the HTAP1 reported 2001 conditions. GEOS-Chem sensitivities indicate that the EAS anthropogenic NOx emissions matter more than the other EAS O3 precursors to the North American O3, qualitatively consistent with previous adjoint sensitivity calculations. In addition to the analyses on large spatial-temporal scales relative to the HTAP1, we also show results on subcontinental and event scales that are more relevant to the US air quality management. The EAS pollution impacts are weaker during observed O3 exceedances than on all days in most US regions except over some high-terrain western US rural/remote areas. Satellite O3 (TES, JPL-IASI, and AIRS) and carbon monoxide (TES and AIRS) products, along with surface measurements and model calculations, show that during certain episodes stratospheric O3 intrusions and the transported EAS pollution in?uenced O3 in the western and the eastern US differently. Free-running (i.e., without chemical data assimilation) global models underpredicted the transported background O3 during these episodes, posing difficulties for STEM to accurately simulate the surface O3 and its source contribution. Although we effectively improved the modeled O3 by incorporating satellite O3 (OMI and MLS) and evaluated the quality of the HTAP2 emission inventory with the Royal Netherlands Meteorological Institute-Ozone Monitoring Instrument (KNMI-OMI) nitrogen dioxide, using observations to evaluate and improve O3 source attribution still remains to be further explored. [ABSTRACT FROM AUTHOR]

The recent update on the US National Ambient Air Quality Standards of the ground-level ozone (O3) can benefit from a better understanding of its source contributions in different US regions during recent years. In the Hemispheric Transport of Air Pollution experiment Phase 1 (HTAP1), various global models were used to determine the O3 source-receptor relationships among three continents in the North Hemisphere in 2001. In support of the HTAP Phase 2 (HTAP2) experiment that studies more recent years and involves higher-resolution global models and regional models' participation, we conduct a number of regional scale Sulfur Transport and dEposition Model (STEM) air quality base and sensitivity simulations over North America during May-June 2010. The STEM top and lateral chemical boundary conditions were downscaled from three global chemical transport models' (i.e., GEOS-Chem, RAQMS, and ECMWF C-IFS) base and sensitivity simulations (in which the East Asian anthropogenic emissions were reduced by 20 %). We perform analyses not only on large spatial/temporal scales relative to the HTAP1 works, but also on subcontiental- and event-scale that are more relevant to the US air quality management. The differences between STEM surface O3 sensitivities (including the 24 h mean and the US policy-relevant maximum daily 8 h average (MDA8) metric averaged throughout the study period and during a selected pollution transport event) and its corresponding boundary condition model's are often smaller than those among its boundary condition models. The STEM sensitivities are also compared with the mean sensitivities estimated by multi-global models, which are higher than the HTAP1 reported 2001 conditions, as well as the 2001-2005 conditions studied using the tagged tracer approach. This indicates the increasing impacts of the East Asian anthropogenic pollution on North America during 2001-2010. The GEOS-Chem sensitivities indicate that the East Asian anthropogenic NOx emissions matter more than the other East Asian O3 precursors to the North American O3, qualitatively consistent with previous adjoint sensitivity calculations. An additional STEM simulation was performed in which the boundary conditions were downscaled from a global RAQMS simulation without East Asian anthropogenic emissions, to assess the scalability of O3 sensitivities to the size of the emission perturbation. The scalability is spatially varying, and the full source contribution obtained by linearly scaling the North American regional mean O3 sensitivity to the 20 % reduction in the East Asian emissions may be underestimated. Satellite NO2 (KNMI OMI) and O3 (TES, JPL-IASI, OMI, MLS, and AIRS) products help detect pollution episodes, quantify or/and reduce the uncertainties in the bottom-up NOx emissions and the model transported background O3. Based on model calculations and satellite/surface observations during a selected event, we show the different influences from stratospheric O3 intrusions along with the transported East Asian pollution on O3 in the western and the eastern US. Future directions of using satellite data in air quality research are also suggested. [ABSTRACT FROM AUTHOR]

Stable carbon isotopic compositions of watersoluble organic carbon (WSOC) and organic molecular markers were measured to investigate the relative contributions of the sea surface sources to the water-soluble fraction of submicron organic aerosols collected over the eastern equatorial Pacific during the Tropical Ocean tRoposphere Exchange of Reactive halogens and Oxygenated VOCs (TORERO)/KA-12-01 cruise. On average, the watersoluble organic fraction of the total carbon (TC) mass in submicron aerosols was ~30-35% in the oceans with the low chlorophyll a (Chl a/ concentrations, whereas it was ~60% in the high-Chl a regions. The average stable carbon isotope ratio of WSOC (δ13CWSOC) was -19.8±2.0, which was systematically higher than that of TC (δ13CTC) (-21.8&#;1.4). We found that in the oceans with both high and low Chl a concentrations the δ13CWSOC was close to the typical values of δ13C for dissolved organic carbon (DOC), ranging from -22 to -20 in surface seawater of the tropical Pacific Ocean. This suggests an enrichment of marine biological products in WSOC aerosols in the study region regardless of the oceanic area. In particular, enhanced levels of WSOC and biogenic organic marker compounds together with high values of WSOC/ TC (~60%) and δ13CWSOC were observed over upwelling areas and phytoplankton blooms, which was attributed to planktonic tissues being more enriched in δ13C. The δ13C analysis estimated that, on average, marine sources contribute ~90±25% of the aerosol carbon, indicating the predominance of marine-derived carbon in the submicron WSOC. This conclusion is supported by Lagrangian trajectory analysis, which suggests that the majority of the sampling points on the ship had been exposed to marine boundary layer (MBL) air for more than 80%of the time during the previous 7 days. The combined analysis of the δ13C and monosaccharides, such as glucose and fructose, demonstrated that DOC concentration was closely correlated with the concentration levels of submicron WSOC across the study region regardless of the oceanic area. The result implies that DOC may characterize background organic aerosols in the MBL over the study region. [ABSTRACT FROM AUTHOR]

Chronic high surface ozone (O3) levels and the increasing sulfur oxides (SOx = SO2+SO4) ambient concentrations over South Coast (SC) and other areas of California (CA) are affected by both local emissions and long-range transport. In this paper, multi-scale tracer, full-chemistry and adjoint simulations using the STEM atmospheric chemistry model are conducted to assess the contribution of local emission sources to SC O3 and to evaluate the impacts of transported sulfur and local emissions on the SC sulfur budget during the ARCTAS-CARB experiment period in 2008. Senstivity simulations quantify contributions of biogenic and fire emissions to SC O3 levels. California biogenic and fire emissions contribute 3-4ppb to near-surface O3 over SC, with larger contributions to other regions in CA. During a long-range transport event from Asia starting from 22 June, high SOx levels (up to ~0.7 ppb of SO2 and ~ 1.3 ppb of SO4) is observed above ~6 km, but they did not affect CA surface air quality. The elevated SOx observed at 1-4 km is estimated to enhance surface SOx over SC by ~0.25 ppb (upper limit) on ~24 June. The near-surface SOx levels over SC during the flight week are attributed mostly to local emissions. Two anthropogenic SOx emission inventories (Els) from the California Air Resources Board (CARB) and the US Environmental Protection Agency (EPA) are compared and applied in 60 km and 12 km chemical transport simulations, and the results are compared with observations. The CARB El shows improvements over the National Emission Inventory (NEI) by EPA, but generally underestimates surface SC SOx, by about a factor of two. Adjoint sensitivity analysis indicated that SO2 levels at 00:00 UTC (17:00 local time) at six SC surface sites were influenced by previous day maritime emissions over the ocean, the terrestrial emissions over nearby urban areas, and by transported SO2 from the north through both terrestrial and maritime areas. Overall maritime emissions contribute 10-70% of SO2 and 20-60% fine SO4 on-shore and over the most terrestrial areas, with contributions decreasing with inland distance from the coast. Maritime emissions also modify the photochemical environment, shifting O3 production over coastal SC to more VOC-limited conditions. These suggest an important role for shipping emission controls in reducing fine particle and 03 concentrations in SC. [ABSTRACT FROM AUTHOR]