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As part of the Pandonia Global Network (PGN), Pandora spectrometers are widely deployed around the world. These ground-based, remote-sensing instruments are federated such that they employ a common algorithm and data protocol for reporting on trace gas column densities and lower atmospheric profiles using two modes based on direct-sun and sky-scan observations. To aid users in the analysis of Pandora observations, the PGN standard quality assurance procedure assigns flags to the data indicating high, medium, and low quality. This work assesses the suitability of these data quality flags for filtering data in the scientific analysis of nitrogen dioxide (NO2) and formaldehyde (HCHO), two critical precursors controlling tropospheric ozone production. Pandora data flagged as high quality assures scientifically valid data and is often more abundant for direct-sun NO2 columns. For direct-sun HCHO and sky-scan observations of both molecules, large amounts of data flagged as low quality also appear to be valid. Upon closer inspection of the data, independent uncertainty is shown to be a better indicator of data quality than the standard quality flags. After applying an independent uncertainty filter, Pandora data flagged as medium or low quality in both modes can be demonstrated to be scientifically useful. Demonstrating the utility of this filtering method is enabled by correlating contemporaneous but independent direct-sun and sky-scan observations. When evaluated across 15 Pandora sites in North America, this new filtering method increased the availability of scientifically useful data by as much as 90 % above that tagged as high quality. A method is also developed for combining the direct-sun and sky-scan observations into a single dataset by accounting for biases between the two observing modes and differences in measurement integration times. This combined data provides a more continuous record useful for interpreting Pandora observations against other independent variables such as hourly observations of surface ozone. When Pandora HCHO columns are correlated with surface ozone measurements, data filtered by independent uncertainty exhibits similarly strong and more robust relationships than high-quality data alone. These results suggest that Pandora data users should carefully assess data across all quality flags and consider their potential for useful application to scientific analysis. The present study provides a method for maximizing use of Pandora data with expectation of more robust satellite validation and comparisons with ground-based observations in support of air quality studies. [ABSTRACT FROM AUTHOR]

Past work has shown that traffic patterns in the USA and resulting NO x emissions vary by day of week, with NO x emissions typically being higher on weekdays than weekends. This pattern of emissions leads to different levels of ozone on weekends versus weekdays and can be leveraged to understand how local ozone formation changes in response to NO x emission perturbations in different urban areas. Specifically, areas with lower NO x but higher ozone on the weekends (the weekend effect) can be characterized as NO x -saturated and areas with both lower NO x and ozone on weekends (the weekday effect) can be characterized as NO x -limited. In this analysis, we assess maximum daily 8 h average (MDA8) ozone weekend–weekday differences across 51 USA nonattainment areas using 18 years of observed and modeled data from 2002–2019, using the following two metrics: mean MDA8 ozone and percentage of days with MDA8 ozone > 70 ppb (parts per billion). In addition, we quantify the modeled and observed trends in these weekend–weekday differences across this period of substantial NO x emission reductions in the USA. The model assessment is carried out using U.S. Environmental Protection Agency (EPA)'s Air QUAlity TimE Series Project (EQUATES) Community Multiscale Air Quality (CMAQ) model dataset. We identify three types of MDA8 ozone trends occurring across the USA, namely transitioning chemical regime, disappearing weekday effect, and no trend. The transitioning chemical regime trend occurs in a subset of large urban areas that were NO x -saturated (i.e., volatile organic compound (VOC)-limited) at the beginning of the analysis period but transitioned to mixed chemical regimes or NO x -limited conditions by the end of the analysis period. Nine areas have strong transitioning chemical regime trends using both modeled and observed data and with both metrics indicating strong agreement that they are shifting to more NO x -limited conditions: Milwaukee, Houston, Phoenix, Denver, the Northern Wasatch Front, the Southern Wasatch Front, Las Vegas, Los Angeles – San Bernardino County, Los Angeles – South Coast, and San Diego. The disappearing weekday effect was identified for multiple rural and agricultural areas of California which were NO x -limited for the entire analysis period but appear to become less influenced by local day-of-week emission patterns in more recent years. Finally, we discuss a variety of reasons why there are no trends in certain areas including complex impacts of heterogeneous source mixes and stochastic impacts of meteorology. Overall, this assessment finds that the EQUATES modeling simulations indicate more NO x -saturated conditions than the observations but do a good job of capturing year-to-year changes in weekend–weekday MDA8 ozone patterns. [ABSTRACT FROM AUTHOR]

Past work has shown that traffic patterns in the US and resulting NOX emissions vary by day of week, with NOX emissions typically higher on weekdays than weekends. This pattern of emissions leads to different levels of ozone on weekends versus weekdays and can be leveraged to understand how local ozone formation changes in response to NOX emissions perturbations in different urban areas. Specifically, areas with lower NOX but higher ozone on the weekends (the weekend effect) can be characterized as NOX -saturated and areas with both lower NOX and ozone on weekends (the weekday effect) can be characterized as NOX-limited. In this analysis we assess ozone weekend-weekday differences across US nonattainment areas using 18 years of observed and modeled data from 2002-2019 using two metrics: mean ozone and percentage of days > 70 ppb. In addition, we quantify the modeled and observed trends in these weekend-weekday differences across this period of substantial NOX emissions reductions in the US. The model assessment is carried out using EPA's Air QUAlity TimE Series Project (EQUATES) CMAQ dataset. We identify 3 types of ozone trends occuring across the US: disappearing weekend effect, disappearing weekday effect, and no trend. The disappearing weekend effect occurs in a subset of large urban areas that were NOX -saturated (i.e., VOC-limited) at the beginning of the analysis period but transitioned to mixed chemical regimes or NOX-limited conditions by the end of the analysis period. Nine areas have disappearing weekend effect trends in both datasets and with both metrics indicating strong agreement that they are shifting to more NOX-limited conditions: Milwaukee, Houston, Phoenix, Denver, Northern Wasatch Front, Southern Wasatch Front, Las Vegas, Los Angeles - San Bernardino County, Los Angeles - South Coast, and San Diego. The disappearing weekday effect was identified for multiple rural and agricultural areas of California which were NOX -limited for the entire analysis period but appear to become less influenced by local day of week emission patterns in more recent years. Finally, we discuss a variety of reasons why there are no statistically significant trends in certain areas including complex impacts of heterogeneous source mixes and stochastic impacts of meteorology. Overall, this assessment finds that the EQUATES modeling simulations indicate more NOX-saturated conditions than the observations but do a good job of capturing year-to-year changes in weekend-weekday ozone patterns. [ABSTRACT FROM AUTHOR]

Quantum chemistry and RRKM/master equation calculations are used to characterize the effect of the vinyl group on the chemistry of the methyl vinyl carbonyl oxide. Natural bond order analysis revealed that the vinyl group weakens the C=O bond of the carbonyl oxide, also dioxole formation, which has a CBS-QB3 reaction barrier of 13.9 kcal/mol, and it is found to be favored over vinyl hydroperoxide formation, dioxirane formation, and collisional stabilization.

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 (NOx) 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 NOx emissions by approx. 30% on top of long-term trends, in agreement with sector-specific changes in NOx 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 and Connecticut, 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 biasing 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 NO2 pollution in the city, 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 NOx emission control strategies. [ABSTRACT FROM AUTHOR]

Satellite nitrogen dioxide (NO2) measurements are used extensively to infer nitrogen oxide emissions and their trends, but interpretation can be complicated by background contributions to the NO2 column sensed from space. We use the step decrease of US anthropogenic emissions from the COVID‐19 shutdown to compare the responses of NO2 concentrations observed at surface network sites and from satellites (Ozone Monitoring Instrument [OMI], Tropospheric Ozone Monitoring Instrument [TROPOMI]). After correcting for differences in meteorology, surface NO2 measurements for 2020 show decreases of 20% in March–April and 10% in May–August compared to 2019. The satellites show much weaker responses in March–June and no decrease in July–August, consistent with a large background contribution to the NO2 column. Inspection of the long‐term OMI trend over remote US regions shows a rising summertime NO2 background from 2010 to 2019 potentially attributable to wildfires. Plain Language Summary: Nitrogen oxides (NOx) emitted from combustion are a major source of air pollution. Satellite observations of nitrogen dioxide (NO2) have been used to infer NOx emissions, but this inference is complicated by NO2 present in background air. Here, we show that this NO2 background results in a muted response of the satellite observations to the abrupt drop in NOx emissions from the US COVID‐19 shutdown. The NO2 background over the US has increased in the past decade, masking the effect of emission decreases. Understanding this background NO2 and its rise is critical for the interpretation of satellite observations. Key Points: COVID‐19 US shutdown led to 22%–26% reductions of surface NO2 in March–April 2020Satellite NO2 data show muted response to COVID‐19 shutdown because of NO2 background contribution to tropospheric column sensed from spaceSummertime NO2 background has been rising in the US over the past decade and complicates the interpretation of trends in satellite NO2 data [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]

The parent and substituted vinoxy radicals are key intermediates in both combustion and atmospheric chemistry. Experiment and theory indicate that vinoxy radicals react with moderate facility with molecular oxygen to form alpha-oxoperoxy radicals.

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]

Determining effective strategies for mitigating surface ozone (O3) pollution requires knowledge of the relative ambient concentrations of its precursors, NO x, and VOCs. The space-based tropospheric column ratio of formaldehyde to NO2 (FNR) has been used as an indicator to identify NO x-limited versus NO x-saturated O3 formation regimes. Quantitative use of this indicator ratio is subject to three major uncertainties: (1) the split between NO x-limited and NO x-saturated conditions may shift in space and time, (2) the ratio of the vertically integrated column may not represent the near-surface environment, and (3) satellite products contain errors. We use the GEOS-Chem global chemical transport model to evaluate the quantitative utility of FNR observed from the Ozone Monitoring Instrument over three northern midlatitude source regions. We find that FNR in the model surface layer is a robust predictor of the simulated near-surface O3 production regime. Extending this surface-based predictor to a column-based FNR requires accounting for differences in the HCHO and NO2 vertical profiles. We compare four combinations of two OMI HCHO and NO2 retrievals with modeled FNR. The spatial and temporal correlations between the modeled and satellite-derived FNR vary with the choice of NO2 product, while the mean offset depends on the choice of HCHO product. Space-based FNR indicates that the spring transition to NO x-limited regimes has shifted at least a month earlier over major cities (e.g., New York, London, and Seoul) between 2005 and 2015. This increase in NO x sensitivity implies that NO x emission controls will improve O3 air quality more now than it would have a decade ago. [ABSTRACT FROM AUTHOR]

We describe ground and space-based measurements of spatial and temporal variation of NO2 in four California metropolitan regions. The measurements of weekly cycles and trends over the years 2005-2008 observed both from the surface and from space are nearly identical to each other. Observed decreases in Los Angeles and the surrounding cities are 46% on weekends and 9%/year from 2005-2008. Similar decreases are observed in the San Francisco Bay area and in Sacramento. In the San Joaquin Valley cities of Fresno and Bakersfield weekend decreases are much smaller, only 27%, and the decreasing trend is only 4%/year. We describe evidence that the satellite observations provide a uniquely complete view of changes in spatial patterns over time. For example, we observe variations in the spatial pattern of weekday-weekend concentrations in the Los Angeles basin with much steeper weekend decreases at the eastern edge of the basin. We also observe that the spatial extent of high NO2 in the San Joaquin Valley has not receded as much as it has for other regions in the state. Analysis of these measurements is used to describe observational constraints on temporal trends in emission sources in the different regions. [ABSTRACT FROM AUTHOR]

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 (NO 2 ) dynamics and the role of meteorology in shaping relative contributions from different emission sectors to NO 2 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 NO 2 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 NO 2 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 NO 2 cycle. Extending our analysis to more than a year after the initial lockdown captured a gradual recovery in NO 2 across the NY/NJ/CT tri-state area in summer and fall 2020, as social restrictions eased, followed by a second decline in NO 2 coincident with the second wave of the pandemic and resurgence of lockdown measures in winter 2021. Meteorology was not found to have a strong NO 2 biassing effect in New York City after the first pandemic wave. Winds, however, were favorable for low NO 2 conditions in Manhattan during the second wave of the pandemic, resulting in larger column NO 2 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 NO 2 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 NO 2 measurements in assessing the effects of rapid meteorological changes on air quality conditions and the effectiveness of sector-specific NO x emission control strategies.

Satellite nitrogen dioxide (NO 2 ) measurements are used extensively to infer nitrogen oxide emissions and their trends, but interpretation can be complicated by background contributions to the NO 2 column sensed from space. We use the step decrease of US anthropogenic emissions from the COVID-19 shutdown to compare the responses of NO 2 concentrations observed at surface network sites and from satellites (Ozone Monitoring Instrument [OMI], Tropospheric Ozone Monitoring Instrument [TROPOMI]). After correcting for differences in meteorology, surface NO 2 measurements for 2020 show decreases of 20% in March-April and 10% in May-August compared to 2019. The satellites show much weaker responses in March-June and no decrease in July-August, consistent with a large background contribution to the NO 2 column. Inspection of the long-term OMI trend over remote US regions shows a rising summertime NO 2 background from 2010 to 2019 potentially attributable to wildfires., (© 2021. The Authors.)

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 ( 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., Competing Interests: Competing interests. The authors declare that they have no conflict of interest.

NASA deployed the GeoTASO airborne UV-Visible spectrometer in May-June 2017 to produce high resolution (approximately 250 × 250 m) gapless NO 2 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 NO 2 observations (r 2 =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 30×10 15 molecules cm -2 . Two publicly available OMI tropospheric NO 2 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 NO 2 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.

Determining effective strategies for mitigating surface ozone (O 3 ) pollution requires knowledge of the relative ambient concentrations of its precursors, NO x , and VOCs. The space-based tropospheric column ratio of formaldehyde to NO 2 (FNR) has been used as an indicator to identify NO x -limited versus NO x -saturated O 3 formation regimes. Quantitative use of this indicator ratio is subject to three major uncertainties: (1) the split between NO x -limited and NO x -saturated conditions may shift in space and time, (2) the ratio of the vertically integrated column may not represent the near-surface environment, and (3) satellite products contain errors. We use the GEOS-Chem global chemical transport model to evaluate the quantitative utility of FNR observed from the Ozone Monitoring Instrument over three northern midlatitude source regions. We find that FNR in the model surface layer is a robust predictor of the simulated near-surface O 3 production regime. Extending this surface-based predictor to a column-based FNR requires accounting for differences in the HCHO and NO 2 vertical profiles. We compare four combinations of two OMI HCHO and NO 2 retrievals with modeled FNR. The spatial and temporal correlations between the modeled and satellite-derived FNR vary with the choice of NO 2 product, while the mean offset depends on the choice of HCHO product. Space-based FNR indicates that the spring transition to NO x -limited regimes has shifted at least a month earlier over major cities (e.g., New York, London, and Seoul) between 2005 and 2015. This increase in NO x sensitivity implies that NO x emission controls will improve O 3 air quality more now than it would have a decade ago.