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The unequal spatial distribution of ambient nitrogen dioxide (NO₂), an air pollutant related to traffic, leads to higher exposure for minority and low socioeconomic status communities. We exploit the unprecedented drop in urban activity during the COVID-19 pandemic and use high-resolution, remotely sensed NO₂ observations to investigate disparities in NO₂ levels across different demographic subgroups in the United States. We show that, prior to the pandemic, satellite-observed NO₂ levels in the least White census tracts of the United States were nearly triple the NO₂ levels in the most White tracts. During the pandemic, the largest lockdown-related NO₂ reductions occurred in urban neighborhoods that have 2.0 times more non-White residents and 2.1 times more Hispanic residents than neighborhoods with the smallest reductions. NO₂ reductions were likely driven by the greater density of highways and interstates in these racially and ethnically diverse areas. Although the largest reductions occurred in marginalized areas, the effect of lockdowns on racial, ethnic, and socioeconomic NO₂ disparities was mixed and, for many cities, nonsignificant. For example, the least White tracts still experienced ∼1.5 times higher NO₂ levels during the lockdowns than the most White tracts experienced prior to the pandemic. Future policies aimed at eliminating pollution disparities will need to look beyond reducing emissions from only passenger traffic and also consider other collocated sources of emissions such as heavy-duty vehicles.

Observing the spatial heterogeneities of NO2 air pollution is an important first step in quantifying NOX emissions and exposures. This study investigates the capabilities of the Tropospheric Monitoring Instrument (TROPOMI) in observing the spatial and temporal patterns of NO2 pollution in the continental United States. The unprecedented sensitivity of the sensor can differentiate the fine‐scale spatial heterogeneities in urban areas, such as emissions related to airport/shipping operations and high traffic, and the relatively small emission sources in rural areas, such as power plants and mining operations. We then examine NO2 columns by day‐of‐the‐week and find that Saturday and Sunday concentrations are 16% and 24% lower respectively, than during weekdays. We also analyze the correlation of daily maximum 2‐m temperatures and NO2 column amounts and find that NO2 is larger on the hottest days (>32°C) as compared to warm days (26°C–32°C), which is in contrast to a general decrease in NO2 with increasing temperature at moderate temperatures. Finally, we demonstrate that a linear regression fit of 2019 annual TROPOMI NO2 data to annual surface‐level concentrations yields relatively strong correlation (R2 = 0.66). These new developments make TROPOMI NO2 satellite data advantageous for policymakers and public health officials, who request information at high spatial resolution and short timescales, in order to assess, devise, and evaluate regulations. Plain Language Summary Nitrogen oxides are a group of air pollutants released after fossil fuel combustion. A constituent of nitrogen oxides, nitrogen dioxide (NO2), can be observed by satellite instruments due to its chemical properties. In this project, we average together images of NO2 pollution gathered by the Tropospheric Monitoring Instrument satellite instrument over the United States in order to better determine the spatial distribution of NO2 air pollution. We find that this newest satellite instrument can observe air pollution with unprecedented clarity, similar to how HDTV is an advancement over regular TV. For example, we quantify pollution near individual airports, shipping areas, and major interstates; previous satellite instruments were unable to quantify air pollution with this type of precision. We also average the satellite data over different intervals to better determine cycles of air pollution. We find that NO2 air pollution is 16% lower on Saturdays and 24% lower on Sundays. Additionally, we find that NO2 pollution is larger on the hottest summer days as compared to typical summer days. These developments demonstrate how this new satellite instrument can advantageous for policymakers and health officials, who request information at high spatial resolution and short timescales, in order to assess, devise, and evaluate regulations Key Points The high instrument sensitivity of Tropospheric Monitoring Instrument (TROPOMI) can measure NO2 pollution with unprecedented clarity compared to predecessor instruments We can now quantify pollution hotspots within cities such as those related to airport/shipping operations and high traffic areas Annual column NO2 observed by TROPOMI has good correlation (R2 = 0.66) with EPA surface observations without any surface‐to‐column conversion

SignificanceEmissions from the fossil fuel industry are one of the major sources of atmospheric methane. Gas leakages due to accidents in the oil and gas sector can release large amounts of methane within short periods of time. Although these emissions are very challenging to monitor, satellite measurement platforms offer a promising approach by regularly scanning the entire globe. This study demonstrates this capability of satellite measurements by reporting atmospheric measurements of methane emission from a natural gas well blowout in Ohio in 2018. Assuming a constant emission rate during the whole event, we find the total methane emission from the 20-d blowout to be equivalent to a substantial fraction of the annual total anthropogenic emission of several European countries. Methane emissions due to accidents in the oil and natural gas sector are very challenging to monitor, and hence are seldom considered in emission inventories and reporting. One of the main reasons is the lack of measurements during such events. Here we report the detection of large methane emissions from a gas well blowout in Ohio during February to March 2018 in the total column methane measurements from the spaceborne Tropospheric Monitoring Instrument (TROPOMI). From these data, we derive a methane emission rate of 120 ± 32 metric tons per hour. This hourly emission rate is twice that of the widely reported Aliso Canyon event in California in 2015. Assuming the detected emission represents the average rate for the 20-d blowout period, we find the total methane emission from the well blowout is comparable to one-quarter of the entire state of Ohio’s reported annual oil and natural gas methane emission, or, alternatively, a substantial fraction of the annual anthropogenic methane emissions from several European countries. Our work demonstrates the strength and effectiveness of routine satellite measurements in detecting and quantifying greenhouse gas emission from unpredictable events. In this specific case, the magnitude of a relatively unknown yet extremely large accidental leakage was revealed using measurements of TROPOMI in its routine global survey, providing quantitative assessment of associated methane emissions.

Anthropogenic nitrogen oxide (NO x ) emissions are closely associated with human activities. In recent years, global human activity patterns have changed significantly owing to the COVID‐19 epidemic and international energy crisis. However, their effects on NO x emissions are not yet fully understood. In this study, we developed a two-step inversion framework using NO 2 observations from the TROPOMI satellite and the GEOS-Chem global atmospheric chemical transport model, and inferred global anthropogenic NO x emissions from 2019 to 2022, focusing on China, the United States (U.S.), and Europe. Our results indicated an 1.68% reduction in NO x emissions in 2020 and a 5.72% rebound in 2021 across all regions. China rebounded faster than the others, surpassing its 2019 levels by July 2020. In 2022, emissions declined in all regions, driven mainly by the Omicron variant, energy shortages, and clean energy policies. Our findings provide valuable insights for the development of effective future emission management strategies.

The TROPOspheric Monitoring Instrument (TROPOMI), launched in October 2017 on board the Sentinel-5 Precursor (S5P) satellite, monitors the composition of the Earth's atmosphere at an unprecedented horizontal resolution as fine as 3.5 × 5.5 km2. This paper assesses the performances of the TROPOMI formaldehyde (HCHO) operational product compared to its predecessor, the OMI (Ozone Monitoring Instrument) HCHO QA4ECV product, at different spatial and temporal scales. The parallel development of the two algorithms favoured the consistency of the products, which facilitates the production of long-term combined time series. The main difference between the two satellite products is related to the use of different cloud algorithms, leading to a positive bias of OMI compared to TROPOMI of up to 30 % in tropical regions. We show that after switching off the explicit correction for cloud effects, the two datasets come into an excellent agreement. For medium to large HCHO vertical columns (larger than 5 × 1015 molec. cm−2) the median bias between OMI and TROPOMI HCHO columns is not larger than 10 % (< 0.4 × 1015 molec. cm−2). For lower columns, OMI observations present a remaining positive bias of about 20 % (< 0.8 × 1015 molec. cm−2) compared to TROPOMI in midlatitude regions. Here, we also use a global network of 18 MAX-DOAS (multi-axis differential optical absorption spectroscopy) instruments to validate both satellite sensors for a large range of HCHO columns. This work complements the study by Vigouroux et al. (2020), where a global FTIR (Fourier transform infrared) network is used to validate the TROPOMI HCHO operational product. Consistent with the FTIR validation study, we find that for elevated HCHO columns, TROPOMI data are systematically low (−25 % for HCHO columns larger than 8 × 1015 molec. cm−2), while no significant bias is found for medium-range column values. We further show that OMI and TROPOMI data present equivalent biases for large HCHO levels. However, TROPOMI significantly improves the precision of the HCHO observations at short temporal scales and for low HCHO columns. We show that compared to OMI, the precision of the TROPOMI HCHO columns is improved by 25 % for individual pixels and by up to a factor of 3 when considering daily averages in 20 km radius circles. The validation precision obtained with daily TROPOMI observations is comparable to the one obtained with monthly OMI observations. To illustrate the improved performances of TROPOMI in capturing weak HCHO signals, we present clear detection of HCHO column enhancements related to shipping emissions in the Indian Ocean. This is achieved by averaging data over a much shorter period (3 months) than required with previous sensors (5 years) and opens new perspectives to study shipping emissions of VOCs (volatile organic compounds) and related atmospheric chemical interactions.

Nitrogen dioxide (NO2) is one of the main air quality pollutants of concern in many urban and industrial areas worldwide, and particularly in the European region, where in 2017 almost 20 countries exceeded the NO2 annual limit values imposed by the European Commission Directive 2008/50/EC (EEA, 2019). NO2 pollution monitoring and regulation is a necessary task to help decision makers to search for a sustainable solution for environmental quality and population health status improvement. In this study, we propose a comparative analysis of the tropospheric NO2 column spatial configuration over Europe between similar periods in 2019 and 2020, based on the ESA Copernicus Sentinel-5P products. The results highlight the NO2 pollution dynamics over the abrupt transition from a normal condition situation to the COVID-19 outbreak context, characterized by a short-time decrease of traffic intensities and industrial activities, revealing remarkable tropospheric NO2 column number density decreases even of 85% in some of the European big cities. The validation approach of the satellite-derived data, based on a cross-correlation analysis with independent data from ground-based observations, provided encouraging values of the correlation coefficients (R2), ranging between 0.5 and 0.75 in different locations. The remarkable decrease of NO2 pollution over Europe during the COVID-19 lockdown is highlighted by S-5P products and confirmed by the Industrial Production Index and air traffic volumes.

Satellite-based estimates of ground-level nitrogen dioxide (NO2) concentrations are useful for understanding links between air quality and health. A longstanding question has been why prior satellite-derived surface NO2 concentrations are biased low with respect to ground-based measurements. In this work we demonstrate that these biases are due to both the coarse resolution of previous satellite NO2 products and inaccuracies in vertical mixing assumptions used to convert satellite-observed tropospheric columns to surface concentrations. We develop an algorithm that now allows for different mixing assumptions to be used based on observed NO2 conditions. We then apply this algorithm to observations from the TROPOMI satellite instrument, which has been providing NO2 column observations at an unprecedented spatial resolution for over a year. This new product achieves estimates of ground-level NO2 with greater accuracy and higher resolution compared to previous satellite-based estimates from OMI. These comparisons also show that TROPOMI-inferred surface NO2 concentrations from our updated algorithm have higher correlation and lower bias than those found using TROPOMI and the prior algorithm. TROPOMI-inferred estimates of the population exposed to NO2 conditions exceeding health standards are at least three times higher than for OMI-inferred estimates. These developments provide an exciting opportunity for air quality monitoring.

This paper presents an analysis of tropospheric NO2 column measurements from the TROPOspheric Monitoring Instrument onboard the Copernicus Sentinel 5 Precursor satellite (TROPOMI/S5P) for an oceanic area in the central Mediterranean on 2 July 2018. The day and area were selected because of the stable and cloud-free weather conditions with low wind speeds throughout most of the area, while covering one of the busiest worldwide international shipping corridors. In addition, the area was affected by sunglint, i.e. sunlight that is directly reflected by the ocean surface waves to the satellite which greatly enhances the signal-to-noise ratio of the satellite observations. The satellite measurements reveal plume-like emission structures in tropospheric NO2 columns while automated identification signal (AIS) data of ship locations reveal a total of 185 ships in the area. Combined with information about wind speed and wind direction within 3 h prior to the TROPOMI/S5P overpass, the ship tracks can almost perfectly be aligned with the plume-like tropospheric NO2 structures. In addition, information about ship length and ship speed, combined with an analysis of ship tracks and ship position, reveal that nearly all emission plume-like tropospheric NO2 structures can be attributed to the largest ships, mostly container ships and crude oil tankers. Overall, our results show for the first time ever that NO2 emission plumes from ships can be detected and attributed to individual ships using satellite measurements, while also providing strong support for using satellite sunglint measurements.

Even though methane concentrations have contributed an estimated 23% of climate forcing, part of the recent increases in the global methane background concentrations remain unexplained. Satellite remote sensing has been used extensively to constrain emission inventories, for example with the TROPOspheric Monitoring Instrument which has been measuring methane since November 2017. We have identified enhancements of methane over 61 urban areas around the world and estimate their emissions using a two-dimensional Gaussian model. We show that methane emissions from urban areas may be underestimated by a factor of 3–4 in the Emissions Database for Global Atmospheric Research (EDGAR) greenhouse gas emission inventory. Scaling our results to the 385 urban areas with more than 2 million inhabitants suggests that they could account for up to 22% of global methane emissions. The emission estimates of the 61 urban areas do not correlate with the total or sectoral EDGAR emission inventory. They do however correlate with estimated rates of untreated wastewater, varying from 33 kg person −1 year −1 for cities with zero untreated wastewater to 138 kg person −1 year −1 for the cities with the most untreated wastewater. If this relationship were confirmed by higher resolution remote sensing or in situ monitoring, we estimate that reducing discharges of untreated wastewater could reduce global methane emissions by up to 5%–10% while at the same time yielding significant ecological and human co-benefits.

Monitoring methane emissions is crucial in mitigating climate change as it has a relatively short atmospheric lifetime of about 12 years and a significant radiative forcing impact. To measure the impact of methane-controlling policies and techniques, a deep understanding of methane emissions is of great importance. Remote sensing offers scalable approaches for monitoring methane emissions at various scales, from point-source high-resolution monitoring to regional and global estimates. The TROPOMI satellite instrument provides daily XCH 4 data globally, offering the opportunity to monitor methane at a moderate spatial resolution with an acceptable level of sensitivity. To infer emissions from TROPOMI data, we used the prior emission estimates from global and national inventories and the GEOS-Chem chemical transport model to simulate atmospheric methane along with actual observations of TROPOMI. In this study, methane emissions from Toronto, Montreal, New York, Los Angeles, Houston, and Mexico City have been estimated using the analytical solution of Bayesian inversion using the cloud-based Integrated Methane Inversion (IMI) framework. Using the result from ensemble inversions, and city boundaries, the average total emissions were as follows: Toronto 230.52 Gg a −1 , Montreal 111.54 Gg a −1 , New York 144.38 Gg a −1 , Los Angeles 207.03 Gg a −1 , Houston 650.16 Gg a −1 , and Mexico City 280.81 Gg a −1 . The resulting gridded scale factors ranged from 0.22 to 6.2, implying methane prior emission underestimations in most of these cities. As such, this study underscores the key role of remote sensing in accurately assessing urban methane emissions, informing essential climate mitigation efforts.