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 (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. This dataset is associated with the following publication: Judd, L., J. Al-Saadi, J. Szykman, L. Valin, A. Nehrir, S. Janz, M. Kowalewski, R. Swap , D. Williams, H. Eskes, J.P. Veefkind, A. Cede, M. Mueller, M. Gebetsberger, and R.B. Pierce. Evaluating Sentinel-5P TROPOMI tropospheric NO2 column densities with airborne and Pandora spectrometers near New York City and Long Island Sound. Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau, GERMANY, 13(11): 6113-6140, (2020).

EPA, in collaboration with NASA, collected upward-viewing UV/visible solar radiance measurements at air quality stations in the New York City region. From these radiances, NO2 vertical column densities (molecules cm-2) are retrieved for comparison to retrieved NO2 column from a downward viewing, satellite-based UV/visible instrument, the NOAA Ozone Mapping and Profiler Suite (OMPS) . This dataset is associated with the following publication: Huang, X., K. Yang, S. Kondragunta, Z. Weir, L. Valin, J. Szykman, and M. Goldberg. NO2 retrievals from NOAA-20 OMPS: Algorithm, evaluation, and observations of drastic changes during COVID-19. ATMOSPHERIC ENVIRONMENT. Elsevier B.V., Amsterdam, NETHERLANDS, 290: 119367, (2022).

The links in this ScienceHub entry provide a path to access archived data collected by EPA ORD researchers contributing to this publication. These include datasets collected in New Jersey, Connecticut and New York. These data collection efforts contributed to the larger Long Island Sound Tropospheric Ozone Study (LISTOS), 2023. The data files relevant to this publication are those archiving ground-based in situ formaldehyde data measurements and the Pandora level 0 radiance measurements, from which total column formaldehyde is retrieved, and compared to that retrieved from airborne and satellite-based radiance measurements. Each dataset has a DOI included in its metadata, with contract information for relevant principal investigators and data managers. These DOI are generated by NASA and by the Pandonia Global Network through collaborations with EPA Office of Research and Development. This dataset is associated with the following publication: Tao, M., A. Fiore, A. Karambelas, P. Miller, L. Valin, L. Judd, M. Tzortziou , A. Whitehill, A. Teora, Y. Tian, K. Civerolo, D. Tong, S. Ma, S. Adamo, and T. Holloway. Insights Into Summertime Surface Ozone Formation From Diurnal Variations in Formaldehyde and Nitrogen Dioxide Along a Transect Through New York City. JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 130(9): e2024JD040922, (2025).

Citywide raster files of annual average predicted surface for nitrogen dioxide (NO2), fine particulate matter (PM2.5), black carbon (BC), and nitric oxide (NO); summer average for ozone (O3) and winter average for sulfure dioxide (SO2). Description: Annual average predicted surface for nitrogen dioxide (NO2), fine particulate matter (PM2.5), black carbon (BC), and nitric oxide (NO); summer average for ozone (O3) and winter average for sulfure dioxide (SO2). File type is ESRI grid raster files at 300 m resolution, NAD83 New York Long Island State Plane FIPS, feet projection. Prediction surface generated from Land Use Regression modeling of December 2008- December 2019 (years 1-11) New York Community Air Survey monitoring data.As these are estimated annual average levels produced by a statistical model, they are not comparable to short term localized monitoring or monitoring done for regulatory purposes. For description of NYCCAS design and Land Use Regression Modeling process see: nyc-ehs.net/nyccas

The links in this ScienceHub entry provide a path to access archived data collected by EPA ORD researchers contributing to this publication. These include datasets collected at a number of locations within the United States in collaboration with various state and local air monitoring agencies. The data files relevant to this publication are those archiving the Pandora level 0 radiance measurements, from which total column formaldehyde is retrieved, and compared to that retrieved from airborne and satellite-based radiance measurements. Each dataset has a DOI included in its metadata, with contract information for relevant principal investigators and data managers. These DOI are generated by NASA and by the Pandonia Global Network through collaborations with EPA Office of Research and Development. This dataset is associated with the following publication: Rawat, P., J. Crawford, K. Travis, L.M. Judd, M.A. Demetillo, L. Valin, J. Szykman, A. Whitehill, E. Baumann, and T. Hanisco. Maximizing the scientific application of Pandora column observations of HCHO and NO2. Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau, GERMANY, 18(13): 2899-2917, (2025).