NO2 retrievals from NOAA-20 OMPS: Algorithm, evaluation, and observations of drastic changes during COVID-19.

We present the first NO2 measurements from the Nadir Mapper of Ozone Mapping and Profiler Suite (OMPS) instrument aboard the NOAA-20 satellite. NOAA-20 OMPS was launched in November 2017, with a nadir resolution of 17 × 13 km2 similar to the Ozone Monitoring Instrument (OMI). The retrieval of NOAA-20 NO2 vertical columns were achieved through the Direct Vertical Column Fitting (DVCF) algorithm, which was uniquely designed and successfully used to retrieve NO2 from OMPS aboard Suomi National Polar-orbiting Partnership (SNPP) spacecraft, predecessor to NOAA-20. Observations from NOAA-20 reveal a 20-40% decline in regional tropospheric NO2 in January-April 2020 due to COVID-19 lockdown, consistent with the findings from other satellite observations. The NO2 retrievals are preliminarily validated against ground-based Pandora spectrometer measurements over the New York City area as well as other U.S. Pandora locations. It shows OMPS total columns tend to be lower in polluted urban regions and higher in clean areas/episodes associated with relatively small NO2 total columns, but generally the agreement is within ±2.5 × 1015 molecules/cm2. Comparisons of stratospheric NO2 columns exhibit the excellent agreement between OMPS and OMI, validating OMPS capability in capturing the stratospheric background accurately. These results demonstrate the high sensitivity of OMPS to tropospheric NO2 and highlight its potential use for extending the long-term global NO2 record.

Declines and peaks in NO2 pollution during the multiple waves of the COVID-19 pandemic in the New York metropolitan area.

The COVID-19 pandemic created an extreme natural experiment in which sudden changes in human behavior and economic activity resulted in significant declines in nitrogen oxide (NO x ) emissions, immediately after strict lockdowns were imposed. Here we examined the impact of multiple waves and response phases of the pandemic on nitrogen dioxide (NO2) dynamics and the role of meteorology in shaping relative contributions from different emission sectors to NO2 pollution in post-pandemic New York City. Long term (> 3.5 years), high frequency measurements from a network of ground-based Pandora spectrometers were combined with TROPOMI satellite retrievals, meteorological data, mobility trends, and atmospheric transport model simulations to quantify changes in NO2 across the New York metropolitan area. The stringent lockdown measures after the first pandemic wave resulted in a decline in top-down NO x emissions by approx. 30% on top of long-term trends, in agreement with sector-specific changes in NO x emissions. Ground-based measurements showed a sudden drop in total column NO2 in spring 2020, by up to 36% in Manhattan and 19%-29% in Queens, New Jersey (NJ), and Connecticut (CT), and a clear weakening (by 16%) of the typical weekly NO2 cycle. Extending our analysis to more than a year after the initial lockdown captured a gradual recovery in NO2 across the NY/NJ/CT tri-state area in summer and fall 2020, as social restrictions eased, followed by a second decline in NO2 coincident with the second wave of the pandemic and resurgence of lockdown measures in winter 2021. Meteorology was not found to have a strong NO2 biassing effect in New York City after the first pandemic wave. Winds, however, were favorable for low NO2 conditions in Manhattan during the second wave of the pandemic, resulting in larger column NO2 declines than expected based on changes in transportation emissions alone. Meteorology played a key role in shaping the relative contributions from different emission sectors to NO with low-speed (< 5 ms-1) SW-SE winds enhancing contributions from the high-emitting power-generation sector in NJ and Queens and driving particularly high NO2 pollution episodes in Manhattan, even during - and despite - the stringent early lockdowns. These results have important implications for air quality management in New York City, and highlight the value of high resolution NO2 measurements in assessing the effects of rapid meteorological changes on air quality conditions and the effectiveness of sector-specific NO x emission control strategies.

Improving surface PM2.5 forecasts in the United States using an ensemble of chemical transport model outputs: 2. bias correction with satellite data for rural areas.

This work serves as the second of a two-part study to improve surface PM2.5 forecasts in the continental U.S. through the integrated use of multi-satellite aerosol optical depth (AOD) products (MODIS Terra/Aqua and VIIRS DT/DB), multi chemical transport model (CTM) (GEOS-Chem, WRF-Chem and CMAQ) outputs and ground observations. In part I of the study, a multi-model ensemble Kalman filter (KF) technique using three CTM outputs and ground observations was developed to correct forecast bias and generate a single best forecast of PM2.5 for next day over non-rural areas that have surface PM2.5 measurements in the proximity of 125 km. Here, with AOD data, we extended the bias correction into rural areas where the closest air quality monitoring station is at least 125 - 300 km away. First, we ensembled all of satellite AOD products to yield the single best AOD. Second, we corrected daily PM2.5 in rural areas from multiple models through the AOD spatial pattern between these areas and non-rural areas, referred to as "extended ground truth" or EGT, for today. Lastly, we applied the KF technique to update the bias in the forecast for next day using the EGT. Our results find that the ensemble of bias-corrected daily PM2.5 from three models for both today and next day show the best performance. Together, the two-part study develops a multi-model and multi-AOD bias correction technique that has the potential to improve PM2.5 forecasts in both rural and non-rural areas in near real time, and be readily implemented at state levels.

The Korea-United States Air Quality (KORUS-AQ) field study.

The Korea-United States Air Quality (KORUS-AQ) field study was conducted during May-June 2016. The effort was jointly sponsored by the National Institute of Environmental Research of South Korea and the National Aeronautics and Space Administration of the United States. KORUS-AQ offered an unprecedented, multi-perspective view of air quality conditions in South Korea by employing observations from three aircraft, an extensive ground-based network, and three ships along with an array of air quality forecast models. Information gathered during the study is contributing to an improved understanding of the factors controlling air quality in South Korea. The study also provided a valuable test bed for future air quality-observing strategies involving geostationary satellite instruments being launched by both countries to examine air quality throughout the day over Asia and North America. This article presents details on the KORUS-AQ observational assets, study execution, data products, and air quality conditions observed during the study. High-level findings from companion papers in this special issue are also summarized and discussed in relation to the factors controlling fine particle and ozone pollution, current emissions and source apportionment, and expectations for the role of satellite observations in the future. Resulting policy recommendations and advice regarding plans going forward are summarized. These results provide an important update to early feedback previously provided in a Rapid Science Synthesis Report produced for South Korean policy makers in 2017 and form the basis for the Final Science Synthesis Report delivered in 2020.

Effect of Polyoxymethylene (POM-H Delrin) offgassing within Pandora head sensor on direct sun and multi-axis formaldehyde column measurements in 2016 - 2019.

Analysis of formaldehyde measurements by the Pandora spectrometer systems between 2016 and 2019 suggested that there was a temperature dependent process inside Pandora head sensor that emitted formaldehyde. Some parts in the head sensor were manufactured from thermal plastic polyoxymethylene homopolimer (E.I. Du Pont de Nemour & Co., USA: POM-H Delrin®) and were responsible for formaldehyde production. Laboratory analysis of the four Pandora head sensors showed that internal formaldehyde production had exponential temperature dependence with a damping coefficient of 0.0911±0.0024 °C-1 and the exponential function amplitude ranging from 0.0041 DU to 0.049 DU. No apparent dependency on the head sensor age and heating/cooling rates was detected. The total amount of formaldehyde internally generated by the POM-H Delrin components and contributing to the direct sun measurements were estimated based on the head sensor temperature and solar zenith angle of the measurements. Measurements in winter, during colder (<10°C) days in general and at high solar zenith angles (> 75 °) were minimally impacted. Measurements during hot days (>28°C) and small solar zenith angles had up to 1 DU (2.69×1016 molecules/cm2) contribution from POM-H Delrin parts. Multi-axis differential slant column densities were minimally impacted (< 0.01 DU) due to the reference spectrum collected within a short time period with a small difference in head sensor temperature. Three new POM-H Delrin free Pandora head sensors (manufactured in summer 2019) were evaluated for temperature dependent attenuation across the entire spectral range (300 to 530 nm). No formaldehyde or any other absorption above the instrumental noise was observed across the entire spectral range.

Characteristics of HONO and its impact on O3 formation in the Seoul Metropolitan Area during the Korea-US Air Quality Study.

Photolysis of nitrous acid (HONO) is recognized as an early-morning source of OH radicals in the urban air. During the Korea-US air quality (KORUS-AQ) campaign, HONO was measured using quantum cascade - tunable infrared laser differential absorption spectrometer (QC-TILDAS) at Olympic Park in Seoul from 17 May, 2016 to 14 June, 2016. The HONO concentration was in the range of 0.07-3.46 ppbv, with an average of 0.93 ppbv. Moreover, it remained high from 00:00-05:00 LST. During this time, the mean concentration was higher during the high-O3 episodes (1.82 ppbv) than the non-episodes (1.20 ppbv). In the morning, the OH radicals that were produced from HONO photolysis were 50% higher (0.95 pptv) during the high-O3 episodes than the non-episodes. Diurnal variations in HOx and O3 concentrations were simulated by the F0AM model, which revealed a difference of ~20 ppbv in the daily maximum O3 concentrations between the high-O3 episodes and non-episodes. Furthermore, the HONO concentration increased with an increase in relative humidity (RH) up to 80%; the highest HONO was associated with the top 10% NO2 in each RH group, confirming that NO2 is one of the main precursors of HONO. At night, the conversion ratio of NO2 to HONO was estimated to be 0.88×10-2 h-1; this ratio was found to increase with an increase in RH. The Aitken mode particles (30-120 nm), which act as catalyst surfaces, exhibited a similar tendency with a conversion ratio that increased along with RH, indicating the coupling of surfaces with HONO conversion. Using an artificial neural network (ANN) model, HONO concentrations were successfully simulated with measured variables (r2 = 0.66 as an average of five models). Among these variables, NOx, aerosol surface area, and RH were found to be the main factors affecting the ambient HONO concentrations. The results reveal that RH facilitates the conversion of NO2 to HONO by constraining the availability of aerosol surfaces. This study demonstrates the coupling of HONO with the HOx-O3 cycle in the Seoul Metropolitan Area (SMA) and provides practical evidence of the heterogeneous formation of HONO by employing the ANN model.

Overview of the Lake Michigan Ozone Study 2017.

The Lake Michigan Ozone Study 2017 (LMOS 2017) was a collaborative multiagency field study targeting ozone chemistry, meteorology, and air quality observations in the southern Lake Michigan area. The primary objective of LMOS 2017 was to provide measurements to improve air quality modeling of the complex meteorological and chemical environment in the region. LMOS 2017 science questions included spatiotemporal assessment of nitrogen oxides (NO x = NO + NO2) and volatile organic compounds (VOC) emission sources and their influence on ozone episodes; the role of lake breezes; contribution of new remote sensing tools such as GeoTASO, Pandora, and TEMPO to air quality management; and evaluation of photochemical grid models. The observing strategy included GeoTASO on board the NASA UC-12 aircraft capturing NO2 and formaldehyde columns, an in situ profiling aircraft, two ground-based coastal enhanced monitoring locations, continuous NO2 columns from coastal Pandora instruments, and an instrumented research vessel. Local photochemical ozone production was observed on 2 June, 9-12 June, and 14-16 June, providing insights on the processes relevant to state and federal air quality management. The LMOS 2017 aircraft mapped significant spatial and temporal variation of NO2 emissions as well as polluted layers with rapid ozone formation occurring in a shallow layer near the Lake Michigan surface. Meteorological characteristics of the lake breeze were observed in detail and measurements of ozone, NOx, nitric acid, hydrogen peroxide, VOC, oxygenated VOC (OVOC), and fine particulate matter (PM2.5) composition were conducted. This article summarizes the study design, directs readers to the campaign data repository, and presents a summary of findings.

Comprehensive evaluations of diurnal NO2 measurements during DISCOVER-AQ 2011: effects of resolution-dependent representation of NO x emissions.

Nitrogen oxides (NO x =NO+NO2) play a crucial role in the formation of ozone and secondary inorganic and organic aerosols, thus affecting human health, global radiation budget, and climate. The diurnal and spatial variations in NO2 are functions of emissions, advection, deposition, vertical mixing, and chemistry. Their observations, therefore, provide useful constraints in our understanding of these factors. We employ a Regional chEmical and trAnsport model (REAM) to analyze the observed temporal (diurnal cycles) and spatial distributions of NO2 concentrations and tropospheric vertical column densities (TVCDs) using aircraft in situ measurements and surface EPA Air Quality System (AQS) observations as well as the measurements of TVCDs by satellite instruments (OMI: the Ozone Monitoring Instrument; GOME-2A: Global Ozone Monitoring Experiment - 2A), ground-based Pandora, and the Airborne Compact Atmospheric Mapper (ACAM) instrument in July 2011 during the DISCOVER-AQ campaign over the Baltimore-Washington region. The model simulations at 36 and 4 km resolutions are in reasonably good agreement with the regional mean temporospatial NO2 observations in the daytime. However, we find significant overestimations (underestimations) of model-simulated NO2 (O3) surface concentrations during night-time, which can be mitigated by enhancing nocturnal vertical mixing in the model. Another discrepancy is that Pandora-measured NO2 TVCDs show much less variation in the late afternoon than simulated in the model. The higher-resolution 4 km simulations tend to show larger biases compared to the observations due largely to the larger spatial variations in NO x emissions in the model when the model spatial resolution is increased from 36 to 4 km. OMI, GOME-2A, and the high-resolution aircraft ACAM observations show a more dispersed distribution of NO2 vertical column densities (VCDs) and lower VCDs in urban regions than corresponding 36 and 4 km model simulations, likely reflecting the spatial distribution bias of NO x emissions in the National Emissions Inventory (NEI) 2011.

Evaluating Sentinel-5P TROPOMI tropospheric NO2 column densities with airborne and Pandora spectrometers near New York City and Long Island Sound.

Airborne and ground-based Pandora spectrometer NO2 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 NO2 Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NO2. 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 2 =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 250m×250m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (r 2 = 0.96) than Pandora measurements are with TROPOMI (r 2 = 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.

An automated common algorithm for planetary boundary layer retrievals using aerosol lidars in support of the U.S. EPA Photochemical Assessment Monitoring Stations Program.

A unique automated planetary boundary layer (PBL) retrieval algorithm is proposed as a common cross-platform method for use with commercially available ceilometers for implementation under the redesigned U.S. Environmental Protection Agency Photochemical Assessment Monitoring Stations program. This algorithm addresses instrument signal quality and screens for precipitation and cloud layers before the implementation of the retrieval methodology using the Haar wavelet covariance transform method. Layer attribution for the PBL height is supported with the use of continuation and time-tracking parameters, and uncertainties are calculated for individual PBL height retrievals. Commercial ceilometer retrievals are tested against radiosonde PBL height and cloud-base height during morning and late afternoon transition times, critical to air quality model prediction and when retrieval algorithms struggle to identify PBL heights. A total of 58 radiosonde profiles were used and retrievals for nocturnal stable layers, residual layers and mixing layers were assessed. Overall good agreement was found for all comparisons with one system showing limitations for the cases of nighttime surface stable layers and daytime mixing layer. It is recommended that nighttime shallow stable layer retrievals be performed with a recommended minimum height or with additional verification. Retrievals of residual layer heights and mixing layer comparisons revealed overall good correlations to radiosonde heights (correlation coefficients, r2, ranging from 0.89 - 0.96 and bias ranging from ~ -131 to +63 m, and r2 from 0.88 - 0.97 and bias from -119 to +101 m, respectively).

Improving Surface PM2.5 Forecasts in the United States Using an Ensemble of Chemical Transport Model Outputs: 1. Bias Correction With Surface Observations in Nonrural Areas.

This work is the first of a two-part study that aims to develop a computationally efficient bias correction framework to improve surface PM2.5 forecasts in the United States. Here, an ensemble-based Kalman filter (KF) technique is developed primarily for nonrural areas with approximately 500 surface observation sites for PM2.5 and applied to three (GEOS-Chem, WRF-Chem, and WRF-CMAQ) chemical transport model (CTM) hindcast outputs for June 2012. While all CTMs underestimate daily surface PM2.5 mass concentration by 20-50%, KF correction is effective for improving each CTM forecast. Subsequently, two ensemble methods are formulated: (1) the arithmetic mean ensemble (AME) that equally weights each model and (2) the optimized ensemble (OPE) that calculates the individual model weights by minimizing the least-square errors. While the OPE shows superior performance than the AME, the combination of either the AME or the OPE with a KF performs better than the OPE alone, indicating the effectiveness of the KF technique. Overall, the combination of a KF with the OPE shows the best results. Lastly, the Successive Correction Method (SCM) was applied to spread the bias correction from model grids with surface PM2.5 observations to the grids lacking ground observations by using a radius of influence of 125 km derived from surface observations, which further improves the forecast of surface PM2.5 at the national scale. Our findings provide the foundation for the second part of this study that uses satellite-based aerosol optical depth (AOD) products to further improve the forecast of surface PM2.5 in rural areas by performing statistical analysis of model output.

Investigation of factors controlling PM2.5 variability across the South Korean Peninsula during KORUS-AQ.

The Korea - United States Air Quality Study (May - June 2016) deployed instrumented aircraft and ground-based measurements to elucidate causes of poor air quality related to high ozone and aerosol concentrations in South Korea. This work synthesizes data pertaining to aerosols (specifically, particulate matter with aerodynamic diameters <2.5 micrometers, PM2.5) and conditions leading to violations of South Korean air quality standards (24-hr mean PM2.5 < 35 µg m-3). PM2.5 variability from AirKorea monitors across South Korea is evaluated. Detailed data from the Seoul vicinity are used to interpret factors that contribute to elevated PM2.5. The interplay between meteorology and surface aerosols, contrasting synoptic-scale behavior vs. local influences, is presented. Transboundary transport from upwind sources, vertical mixing and containment of aerosols, and local production of secondary aerosols are discussed. Two meteorological periods are probed for drivers of elevated PM2.5. Clear, dry conditions, with limited transport (Stagnant period), promoted photochemical production of secondary organic aerosol from locally emitted precursors. Cloudy humid conditions fostered rapid heterogeneous secondary inorganic aerosol production from local and transported emissions (Transport/Haze period), likely driven by a positive feedback mechanism where water uptake by aerosols increased gas-to-particle partitioning that increased water uptake. Further, clouds reduced solar insolation, suppressing mixing, exacerbating PM2.5 accumulation in a shallow boundary layer. The combination of factors contributing to enhanced PM2.5 is challenging to model, complicating quantification of contributions to PM2.5 from local versus upwind precursors and production. We recommend co-locating additional continuous measurements at a few AirKorea sites across South Korea to help resolve this and other outstanding questions: carbon monoxide/carbon dioxide (transboundary transport tracer), boundary layer height (surface PM2.5 mixing depth), and aerosol composition with aerosol liquid water (meteorologically-dependent secondary production). These data would aid future research to refine emissions targets to further improve South Korean PM2.5 air quality.

Factors controlling surface ozone in the Seoul Metropolitan Area during the KORUS-AQ campaign.

To understand the characteristics of air quality in the Seoul Metropolitan Area, intensive measurements were conducted under the Korea-United States Air Quality (KORUS-AQ) campaign. Trace gases such as O3, NOx, NOy, SO2, CO, and volatile organic compounds (VOCs), photochemical byproducts such as H2O2 and HCHO, aerosol species, and meteorological variables including planetary boundary layer height were simultaneously measured at Olympic Park in Seoul. During the measurement period, high O3 episodes that exceeded the 90 ppbv hourly maximum occurred on 14 days under four distinct synoptic meteorological conditions. Furthermore, local circulation such as land-sea breeze and diurnal evolution of the boundary layer were crucial in determining the concentrations of precursor gases, including NOx and VOC as well as O3. During such episodes, the nighttime NOx and VOC and daytime UV levels were higher compared to non-episode days. The overall precursor levels and photochemical activity were represented fairly well by variations in the HCHO, which peaked in the morning during the high O3 episodes. This study revealed that toluene was the most abundant VOC in Seoul, and its concentration increased greatly with NOx due to the large local influence under stagnant conditions. When O3 was highly elevated concurrently with PM2.5 under dominant westerlies, NOx and VOCs were relatively lower and CO was noticeably higher than in other episodes. Additionally, the O3 production efficiency was the highest due to a low NOx with the highest NOz/NOy ratio among the four episodes. When westerlies were dominant in transport-south episode, the nighttime concentration of O 3 remained as high as 40~50 ppbv due to the minimum level of NOx titration. Overall, the Seoul Metropolitan Area is at NOx-saturated and VOC-limited conditions, which was diagnosed by indicator species and VOC/NOx ratios.

Taehwa Research Forest: A receptor site for severe domestic pollution events in Korea during 2016.

During the May-June 2016 International Cooperative Air Quality Field Study in Korea (KORUS-AQ), light synoptic meteorological forcing facilitated Seoul metropolitan pollution outflow to reach the remote Taehwa Research Forest (TRF) site and cause regulatory exceedances of ozone on 24 days. Two of these severe pollution events are thoroughly examined. The first, occurring on 17 May 2016, tracks transboundary pollution transport exiting eastern China and the Yellow Sea, traversing the Seoul Metropolitan Area (SMA), and then reaching TRF in the afternoon hours with severely polluted conditions. This case study indicates that although outflow from China and the Yellow Sea were elevated with respect to chemically unperturbed conditions, the regulatory exceedance at TRF was directly linked in time, space, and altitude to urban Seoul emissions. The second case studied, occurring on 09 June 2016, reveals that increased levels of biogenic emissions, in combination with amplified urban emissions, were associated with severe levels of pollutions and a regulatory exceedance at TRF. In summary, domestic emissions may be causing more pollution than by trans-boundary pathways, which have been historically believed to be the major source of air pollution in South Korea. The case studies are assessed with multiple aircraft, model (photochemical and meteorological) simulations, in-situ chemical sampling, and extensive ground-based profiling at TRF. These observations clearly identify TRF and the surrounding rural communities as receptor sites for severe pollution events associated with Seoul outflow, which will result in long-term negative effects to both human health and agriculture in the affected areas.

Evaluating the impact of spatial resolution on tropospheric NO2 column comparisons within urban areas using high-resolution airborne data.

NASA deployed the GeoTASO airborne UV-Visible spectrometer in May-June 2017 to produce high resolution (approximately 250 × 250 m) 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, TROPOMI, and OMI, 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 both 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.

A Call for an Aloft Air Quality Monitoring Network: Need, Feasibility, and Potential Value.

Changing precursor emission patterns in conjunction with stringent health protective air quality standards necessitate accurate quantification of nonlocal contributions to ozone pollution at a location due to atmospheric transport, that by nature predominantly occurs aloft nocturnally. Concerted efforts to characterize ozone aloft on a continuous basis to quantify its contribution to ground-level concentrations, however, are lacking. By applying our classical understanding of air pollution dynamics to analyze variations in widespread surface-level ozone measurements, in conjunction with process-based interpretation from a comprehensive air pollution modeling system and detailed backward-sensitivity calculations that quantitatively link surface-level and aloft pollution, we show that accurate quantification of the amount of ozone in the air entrained from aloft every morning as the atmospheric boundary layer grows is the key missing component for characterizing background pollution at a location, and we propose a cost-effective continuous aloft ozone measurement strategy to address critical scientific gaps in current air quality management. Continuous aloft air pollution measurements can be achieved cost-effectively through leveraging advances in sensor technology and proliferation of tall telecommunications masts. Resultant improvements in ozone distribution characterization at 400-500 m altitude are estimated to be 3-4 times more effective in characterizing the surface-level daily maximum 8-h average ozone (DM8O3) than improvements from surface measurements since they directly quantify the amount of pollution imported to a location and furnish key missing information on processes and sources regulating background ozone and its modulation of ground-level concentrations. Since >80% of the DM8O3 sensitivity to tropospheric ozone is potentially captured through measurements between 200 and 1200 m altitude (a possible design goal for future remote sensing instrumentation), their assimilation will dramatically improve air quality forecast and health advisories.

The first evaluation of formaldehyde column observations by improved Pandora spectrometers during the KORUS-AQ field study.

The Korea-United States Air Quality Study (KORUS-AQ) conducted during May-June 2016 offered the first opportunity to evaluate direct-sun observations of formaldehyde (HCHO) total column densities with improved Pandora spectrometer instruments. The measurements highlighted in this work were conducted both in the Seoul megacity area at the Olympic Park site (37.5232° N, 27.1260° E; 26 ma.s.l.) and at a nearby rural site downwind of the city at the Mount Taehwa research forest site (37.3123° N, 127.3106° E; 160ma.s.l.). Evaluation of these measurements was made possible by concurrent ground-based in situ observations of HCHO at both sites as well as overflight by the NASA DC-8 research aircraft. The flights provided in situ measurements of HCHO to characterize its vertical distribution in the lower troposphere (0-5km). Diurnal variation in HCHO total column densities followed the same pattern at both sites, with the minimum daily values typically observed between 6:00 and 7:00 local time, gradually increasing to a maximum between 13:00 and 17:00 before decreasing into the evening. Pandora vertical column densities were compared with those derived from the DC-8 HCHO in situ measured profiles augmented with in situ surface concentrations below the lowest altitude of the DC-8 in proximity to the ground sites. A comparison between 49 column densities measured by Pandora vs. aircraft-integrated in situ data showed that Pandora values were larger by 16% with a constant offset of 0.22DU (Dobson units; R 2 = 0.68). Pandora HCHO columns were also compared with columns calculated from the surface in situ measurements over Olympic Park by assuming a well-mixed lower atmosphere up to a ceilometer-measured mixed-layer height (MLH) and various assumptions about the small residual HCHO amounts in the free troposphere up to the tropopause. The best comparison (slope = 1.03±0.03; intercept = 0.29±0.02DU; and R 2 = 0.78±0.02) was achieved assuming equal mixing within ceilometer-measured MLH combined with an exponential profile shape. These results suggest that diurnal changes in HCHO surface concentrations can be reasonably estimated from the Pandora total column and information on the mixed-layer height. More work is needed to understand the bias in the intercept and the slope relative to columns derived from the in situ aircraft and surface measurements.

The Dawn of Geostationary Air Quality Monitoring: Case Studies from Seoul and Los Angeles.

With the near-future launch of geostationary pollution monitoring satellite instruments over North America, East Asia, and Europe, the air quality community is preparing for an integrated global atmospheric composition observing system at unprecedented spatial and temporal resolutions. One of the ways that NASA has supported this community preparation is through demonstration of future space-borne capabilities using the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument. This paper integrates repeated high-resolution maps from GeoTASO, ground-based Pandora spectrometers, and low Earth orbit measurements from the Ozone Mapping and Profiler Suite (OMPS), for case studies over two metropolitan areas: Seoul, South Korea on June 9th, 2016 and Los Angeles, California on June 27th, 2017. This dataset provides a unique opportunity to illustrate how geostationary air quality monitoring platforms and ground-based remote sensing networks will close the current spatiotemporal observation gap. GeoTASO observes large differences in diurnal behavior between these urban areas, with NO2 accumulating within the Seoul Metropolitan Area through the day but NO2 peaking in the morning and decreasing throughout the afternoon in the Los Angeles Basin. In both areas, the earliest morning maps exhibit spatial patterns similar to emission source areas (e.g., urbanized valleys, roadways, major airports). These spatial patterns change later in the day due to boundary layer dynamics, horizontal transport, and chemistry. The nominal resolution of GeoTASO is finer than will be obtained from geostationary platforms, but when NO2 data over Los Angeles are up-scaled to the expected resolution of TEMPO, spatial features discussed are conserved. Pandora instruments installed in both metropolitan areas capture the diurnal patterns observed by GeoTASO, continuously and over longer time periods, and will play a critical role in validation of the next generation of satellite measurement.. These case studies demonstrate that different regions can have diverse diurnal patterns and that day-to-day variability due to meteorology or anthropogenic patterns such as weekday/weekend variations in emissions is large. Low Earth orbit measurements, despite their inability to capture the diurnal patterns at fine spatial resolution, will be essential for intercalibrating the geostationary radiances and cross-validating the geostationary retrievals in an integrated global observing system.

Assessment of Mixed-Layer Height Estimation from Single-wavelength Ceilometer Profiles.

Differing boundary/mixed-layer height measurement methods were assessed in moderately-polluted and clean environments, with a focus on the Vaisala CL51 ceilometer. This intercomparison was performed as part of ongoing measurements at the Chemistry And Physics of the Atmospheric Boundary Layer Experiment (CAPABLE) site in Hampton, Virginia and during the 2014 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaign that took place in and around Denver, Colorado. We analyzed CL51 data that were collected via two different methods (BLView software, which applied correction factors, and simple terminal emulation logging) to determine the impact of data collection methodology. Further, we evaluated the STRucture of the ATmosphere (STRAT) algorithm as an open-source alternative to BLView (note that the current work presents an evaluation of the BLView and STRAT algorithms and does not intend to act as a validation of either). Filtering criteria were defined according to the change in mixed-layer height (MLH) distributions for each instrument and algorithm and were applied throughout the analysis to remove high-frequency fluctuations from the MLH retrievals. Of primary interest was determining how the different data-collection methodologies and algorithms compare to each other and to radiosonde-derived boundary-layer heights when deployed as part of a larger instrument network. We determined that data-collection methodology is not as important as the processing algorithm and that much of the algorithm differences might be driven by impacts of local meteorology and precipitation events that pose algorithm difficulties. The results of this study show that a common processing algorithm is necessary for LIght Detection And Ranging (LIDAR)-based MLH intercomparisons, and ceilometer-network operation and that sonde-derived boundary layer heights are higher (10-15% at mid-day) than LIDAR-derived mixed-layer heights. We show that averaging the retrieved MLH to 1-hour resolution (an appropriate time scale for a priori data model initialization) significantly improved correlation between differing instruments and differing algorithms.

Performance Evaluation and Community Application of Low-Cost Sensors for Ozone and Nitrogen Dioxide.

This study reports on the performance of electrochemical-based low-cost sensors and their use in a community application. CairClip sensors were collocated with federal reference and equivalent methods and operated in a network of sites by citizen scientists (community members) in Houston, Texas and Denver, Colorado, under the umbrella of the NASA-led DISCOVER-AQ Earth Venture Mission. Measurements were focused on ozone (O3) and nitrogen dioxide (NO2). The performance evaluation showed that the CairClip O3/NO2 sensor provided a consistent measurement response to that of reference monitors (r² = 0.79 in Houston; r² = 0.72 in Denver) whereas the CairClip NO2 sensor measurements showed no agreement to reference measurements. The CairClip O3/NO2 sensor data from the citizen science sites compared favorably to measurements at nearby reference monitoring sites. This study provides important information on data quality from low-cost sensor technologies and is one of few studies that reports sensor data collected directly by citizen scientists.