Observing Nitrogen Dioxide Air Pollution Inequality Using High-Spatial-Resolution Remote Sensing Measurements in Houston, Texas.

Houston, Texas is a major U.S. urban and industrial area where poor air quality is unevenly distributed and a disproportionate share is located in low-income, non-white, and Hispanic neighborhoods. We have traditionally lacked city-wide observations to fully describe these spatial heterogeneities in Houston and in cities globally, especially for reactive gases like nitrogen dioxide (NO2). Here, we analyze novel high-spatial-resolution (250 m × 500 m) NO2 vertical columns measured by the NASA GCAS airborne spectrometer as part of the September-2013 NASA DISCOVER-AQ mission and discuss differences in population-weighted NO2 at the census-tract level. Based on the average of 35 repeated flight circuits, we find 37 ± 6% higher NO2 for non-whites and Hispanics living in low-income tracts (LIN) compared to whites living in high-income tracts (HIW) and report NO2 disparities separately by race ethnicity (11-32%) and poverty status (15-28%). We observe substantial time-of-day and day-to-day variability in LIN-HIW NO2 differences (and in other metrics) driven by the greater prevalence of NOx (≡NO + NO2) emission sources in low-income, non-white, and Hispanic neighborhoods. We evaluate measurements from the recently launched satellite sensor TROPOMI (3.5 km × 7 km at nadir), averaged to 0.01° × 0.01° using physics-based oversampling, and demonstrate that TROPOMI resolves similar relative, but not absolute, tract-level differences compared to GCAS. We utilize the high-resolution FIVE and NEI NOx inventories, plus one year of TROPOMI weekday-weekend variability, to attribute tract-level NO2 disparities to industrial sources and heavy-duty diesel trucking. We show that GCAS and TROPOMI spatial patterns correspond to the surface patterns measured using aircraft profiling and surface monitors. We discuss opportunities for satellite remote sensing to inform decision making in cities generally.

Interannual changes in atmospheric oxidation over forests determined from space.

The hydroxyl radical (OH) is the central oxidant in Earth's troposphere, but its temporal variability is poorly understood. We combine 2012-2020 satellite-based isoprene and formaldehyde measurements to identify coherent OH changes over temperate and tropical forests with attribution to emission trends, biotic stressors, and climate. We identify a multiyear OH decrease over the Southeast United States and show that with increasingly hot/dry summers the regional chemistry could become even less oxidizing depending on competing temperature/drought impacts on isoprene. Furthermore, while global mean OH decreases during El Niño, we show that near-field effects over tropical rainforests can alternate between high/low OH anomalies due to opposing fire and biogenic emission impacts. Results provide insights into how atmospheric oxidation will evolve with changing emissions and climate.

COVID-19 perturbation on US air quality and human health impact assessment.

The COVID-19 stay-at-home orders issued in the United States caused significant reductions in traffic and economic activities. To understand the pandemic's perturbations on US emissions and impacts on urban air quality, we developed near-real-time bottom-up emission inventories based on publicly available energy and economic datasets, simulated the emission changes in a chemical transport model, and evaluated air quality impacts against various observations. The COVID-19 pandemic affected US emissions across broad-based energy and economic sectors and the impacts persisted to 2021. Compared with 2019 business-as-usual emission scenario, COVID-19 perturbations resulted in annual decreases of 10-15% in emissions of ozone (O3) and fine particle (PM2.5) gas-phase precursors, which are about two to four times larger than long-term annual trends during 2010-2019. While significant COVID-induced reductions in transportation and industrial activities, particularly in April-June 2020, resulted in overall national decreases in air pollutants, meteorological variability across the nation led to local increases or decreases of air pollutants, and mixed air quality changes across the United States between 2019 and 2020. Over a full year (April 2020 to March 2021), COVID-induced emission reductions led to 3-4% decreases in national population-weighted annual fourth maximum of daily maximum 8-h average O3 and annual PM2.5. Assuming these emission reductions could be maintained in the future, the result would be a 4-5% decrease in premature mortality attributable to ambient air pollution, suggesting that continued efforts to mitigate gaseous pollutants from anthropogenic sources can further protect human health from air pollution in the future.

An Inversion Framework for Optimizing Non-Methane VOC Emissions Using Remote Sensing and Airborne Observations in Northeast Asia During the KORUS-AQ Field Campaign.

We aim to reduce uncertainties in CH2O and other volatile organic carbon (VOC) emissions through assimilation of remote sensing data. We first update a three-dimensional (3D) chemical transport model, GEOS-Chem with the KORUSv5 anthropogenic emission inventory and inclusion of chemistry for aromatics and C2H4, leading to modest improvements in simulation of CH2O (normalized mean bias (NMB): -0.57 to -0.51) and O3 (NMB: -0.25 to -0.19) compared against DC-8 aircraft measurements during KORUS-AQ; the mixing ratio of most VOC species are still underestimated. We next constrain VOC emissions using CH2O observations from two satellites (OMI and OMPS) and the DC-8 aircraft during KORUS-AQ. To utilize data from multiple platforms in a consistent manner, we develop a two-step Hybrid Iterative Finite Difference Mass Balance and four-dimensional variational inversion system (Hybrid IFDMB-4DVar). The total VOC emissions throughout the domain increase by 47%. The a posteriori simulation reduces the low biases of simulated CH2O (NMB: -0.51 to -0.15), O3 (NMB: -0.19 to -0.06), and VOCs. Alterations to the VOC speciation from the 4D-Var inversion include increases of biogenic isoprene emissions in Korea and anthropogenic emissions in Eastern China. We find that the IFDMB method alone is adequate for reducing the low biases of VOCs in general; however, 4D-Var provides additional refinement of high-resolution emissions and their speciation. Defining reasonable emission errors and choosing optimal regularization parameters are crucial parts of the inversion system. Our new hybrid inversion framework can be applied for future air quality campaigns, maximizing the value of integrating measurements from current and upcoming geostationary satellite instruments.

Unraveling pathways of elevated ozone induced by the 2020 lockdown in Europe by an observationally constrained regional model using TROPOMI.

Questions about how emissions are changing during the COVID-19 lockdown periods cannot be answered by observations of atmospheric trace gas concentrations alone, in part due to simultaneous changes in atmospheric transport, emissions, dynamics, photochemistry, and chemical feedback. A chemical transport model simulation benefiting from a multi-species inversion framework using well-characterized observations should differentiate those influences enabling to closely examine changes in emissions. Accordingly, we jointly constrain NO x and VOC emissions using well-characterized TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO2 columns during the months of March, April, and May 2020 (lockdown) and 2019 (baseline). We observe a noticeable decline in the magnitude of NO x emissions in March 2020 (14 %-31 %) in several major cities including Paris, London, Madrid, and Milan, expanding further to Rome, Brussels, Frankfurt, Warsaw, Belgrade, Kyiv, and Moscow (34 %-51 %) in April. However, NO x emissions remain at somewhat similar values or even higher in some portions of the UK, Poland, and Moscow in March 2020 compared to the baseline, possibly due to the timeline of restrictions. Comparisons against surface monitoring stations indicate that the constrained model underrepresents the reduction in surface NO2. This underrepresentation correlates with the TROPOMI frequency impacted by cloudiness. During the month of April, when ample TROPOMI samples are present, the surface NO2 reductions occurring in polluted areas are described fairly well by the model (model: -21 ± 17 %, observation: -29 ± 21 %). The observational constraint on VOC emissions is found to be generally weak except for lower latitudes. Results support an increase in surface ozone during the lockdown. In April, the constrained model features a reasonable agreement with maximum daily 8 h average (MDA8) ozone changes observed at the surface (r = 0.43), specifically over central Europe where ozone enhancements prevail (model: +3.73 ± 3.94 %, + 1.79 ppbv, observation: +7.35 ± 11.27 %, +3.76 ppbv). The model suggests that physical processes (dry deposition, advection, and diffusion) decrease MDA8 surface ozone in the same month on average by -4.83 ppbv, while ozone production rates dampened by largely negative J NO 2 [ NO 2 ] - k NO + O 3 [ NO ] [ O 3 ] become less negative, leading ozone to increase by +5.89 ppbv. Experiments involving fixed anthropogenic emissions suggest that meteorology contributes to 42 % enhancement in MDA8 surface ozone over the same region with the remaining part (58 %) coming from changes in anthropogenic emissions. Results illustrate the capability of satellite data of major ozone precursors to help atmospheric models capture ozone changes induced by abrupt emission anomalies.

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.

The ACE-MAESTRO instrument on SCISAT: description, performance, and preliminary results.

The Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (MAESTRO) instrument on the SCISAT satellite is a simple, compact spectrophotometer for the measurement of atmospheric extinction, ozone, nitrogen dioxide, and other trace gases in the stratosphere and upper troposphere as part of the Atmospheric Chemistry Experiment (ACE) mission. We provide an overview of the instrument from requirements to realization, including optical design, prelaunch and on-orbit performance, and a preliminary examination of retrievals of ozone and NO(2).