Abstract The Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission, launched in April 2023 as the first geostationary sensor dedicated to monitoring air quality over North America, provides both traditional aerosol optical depth (AOD) retrievals and novel aerosol layer height (ALH) products. In this study, we report on the use of AOD and ALH for estimating surface‐level particulate matter with a diameter less than 2.5 μm (PM2.5) at hourly resolution using a geographically weighted regression (GWR) approach. We assess three methods: (a) using AOD alone, (b) applying multivariate linear regression with both AOD and ALH as inputs, and (c) using boundary layer AOD derived from column AOD and ALH as inputs to the GWR algorithm. Results show that the method using boundary layer AOD outperforms AOD‐only retrievals in regions where ALH exceeds 3 km and performs comparably to the AOD‐only method elsewhere. Ten‐fold cross‐validation yields an overall R2 of 0.47, a mean bias of 0.10 μg/m3, and an RMSE of 6.08 μg/m3 using the boundary‐layer AOD method. By contrast, the multivariate regression method yields the weakest performance. To enhance PM2.5 estimation further, we develop a strategy that integrates TEMPO and Advanced Baseline Imager retrievals. In this approach, sensor averaged PM2.5 estimates are used, except in two cases where TEMPO alone is favored due to its superior skill: when ALH exceeds 3 km or when TEMPO aerosol detection identifies blowing dust.

Abstract Despite improvements in ambient air quality in the US in recent decades, many people still experience unhealthy levels of pollution. At present, national‐level alert‐day identification relies predominately on surface monitor networks and forecasters. Satellite‐based estimates of surface air quality have rapidly advanced and have the capability to inform exposure‐reducing actions to protect public health. At present, we lack a robust framework to quantify public health benefits of these advances in applications of satellite‐based atmospheric composition data. Here, we assess possible health benefits of using geostationary satellite data, over polar orbiting satellite data, for identifying particulate air quality alert days (24hr PM2.5 > 35 μg m−3) in 2020. We find the more extensive spatiotemporal coverage of geostationary satellite data leads to a 60% increase in identification of person‐alerts (alert days × population) in 2020 over polar‐orbiting satellite data. We apply pre‐existing estimates of PM2.5 exposure reduction by individual behavior modification and find these additional person‐alerts may lead to 1,200 (800–1,500) or 54% more averted PM2.5‐attributable premature deaths per year, if geostationary, instead of polar orbiting, satellite data alone are used to identify alert days. These health benefits have an associated economic value of 13 (8.8–17) billion dollars ($2019) per year. Our results highlight one of many potential applications of atmospheric composition data from geostationary satellites for improving public health. Identifying these applications has important implications for guiding use of current satellite data and planning future geostationary satellite missions.

With the launch of Tropospheric Emissions: Monitoring of Pollution (TEMPO) and Geostationary Environment Monitoring System (GEMS) instruments in geostationary (GEO) orbit, we are entering a new era of air quality monitoring. These hourly observations of trace gases and aerosols need to be thoroughly evaluated for the time of the day biases that stem from solar-satellite viewing conditions. Because observations made from low earth orbit (LEO) satellite sensors such as TROPOspheric Monitoring Instrument (TROPOMI) and Ozone Mapping and Profiler Suite (OMPS) are well characterized, comparisons can be made to understand viewing geometry dependent biases in GEMS and TEMPO retrievals and develop soft calibration methods. We developed a Kalman filter approach that combines tropospheric nitrogen dioxide column (tropNO2) data from TROPOMI and GEMS. The spatial and temporal variability in tropNO2 comes from GEMS whereas TROPOMI tropNO2 observations are added to the Kalman filter process as observations that nudge GEMS tropNO2. The relative weighting is influenced by the observation error covariance from GEMS and TROPOMI. Analysis of the GEMS tropNO2 data reveals its systematic biases, while applying the Kalman filter method to merge the GEMS and TROPOMI will yield a more accurate NO2 product. Accuracy of the merged tropNO2 data is determined by comparing the merged dataset against ground-based measurements from the Pandonia Global Network. We will present the methodology and case studies application of the merged dataset.

The atmospheric composition instrument (ACX) on NOAA's GeoXO mission will enhance NOAA's air quality monitoring capabilities by providing hourly high-resolution observations of air pollutants over North America, like its predecessor, NASA's TEMPO mission. We are developing and implementing an advanced algorithm for accurate NO2 retrieval from GeoXO ACX. Applying this algorithm to GEMS and TEMPO, we demonstrate in this presentation the success of rapid production of high-quality NO2 data soon after the mission starts to collect Earthview measurements. We describe the technique for instrument characterization and identification of instrument artifacts for improving retrieval precisions, and the soft calibration approach for removing systematic biases in NO2 retrieval. Using TROPOMI as a transfer standard, we show consistent NO2 slant columns are retrieved from GEMS and TEMPO using the GeoXO ACX NO2 algorithm.

Methane (CH4) is the second most significant contributor to climate change after carbon dioxide (CO2), accounting for approximately 20% of the contributions from all well-mixed greenhouse gases. Understanding the spatiotemporal distributions and the relevant long-term trends is crucial to identifying the sources, sinks, and impacts on climate. Hyperspectral thermal infrared (TIR) sounders, including the Atmospheric Infrared Sounder (AIRS), the Cross-track Infrared Sounder (CrIS), and the Infrared Atmospheric Sounding Interferometer (IASI), have been used to measure global CH4 concentrations since 2002. This study analyzed nearly 20 years of data from AIRS and CrIS and confirmed a significant increase in CH4 concentrations in the mid-upper troposphere (around 400 hPa) from 2003 to 2020, with a total increase of approximately 85 ppb, representing a +4.8% increase in 18 years. The rate of increase was derived using global satellite TIR measurements, which are consistent with in situ measurements, indicating a steady increase starting in 2007 and becoming stronger in 2014. The study also compared CH4 concentrations derived from the AIRS and CrIS against ground-based measurements from NOAA Global Monitoring Laboratory (GML) and found phase shifts in the seasonal cycles in the middle to high latitudes of the northern hemisphere, which is attributed to the influence of stratospheric CH4 that varies at different latitudes. These findings provide insights into the global budget of atmospheric composition and the understanding of satellite measurement sensitivity to CH4.

This study investigated the impact of COVID-19 lockdowns on satellite aerosol optical depth (AOD), to explore the hypothesis that if changes in economic activity are seen in emissions of NO 2 , an aerosol precursor, then AOD should change commensurably. We developed a technique to filter AOD data to isolate changes associated with anthropogenic emissions. Overall, in 37 of the 43 cities that were identified as top oxides of nitrogen (NO x ) emitters from their transportation sectors, AODs decreased by 21.2% ± 7.8%, 18.9% ± 11.7%, 27% ± 12.4%, 22.9% ± 7.6% in the United States, India, western Europe, and China, respectively—an average of 22.4% ± 7.4%. In contrast, AODs increased on average by 11.7% ± 8.4% in Taiwan, where economic stimulus was used as a strategy during the pandemic. This analysis implies NO x and volatile organic compounds emissions reductions from the transportation sector can be targeted, and by transitioning 6 million light duty vehicles from gasoline to electricity, the US can achieve 21% improvement in AOD.

The mass concentration of fine particulate matter (PM2.5; diameters less than 2.5 μm) estimated from geostationary satellite aerosol optical depth (AOD) data can supplement the network of ground monitors with high temporal (hourly) resolution. Estimates of PM2.5 over the United States (US) were derived from NOAA's operational geostationary satellites Advanced Baseline Imager (ABI) AOD data using a geographically weighted regression with hourly and daily temporal resolution. Validation versus ground observations shows a mean bias of -21.4% and -15.3% for hourly and daily PM2.5 estimates, respectively, for concentrations ranging from 0 to 1000 μg/m3. Because satellites only observe AOD in the daytime, the relation between observed daytime PM2.5 and daily mean PM2.5 was evaluated using ground measurements; PM2.5 estimated from ABI AODs were also examined to study this relationship. The ground measurements show that daytime mean PM2.5 has good correlation (r > 0.8) with daily mean PM2.5 in most areas of the US, but with pronounced differences in the western US due to temporal variations caused by wildfire smoke; the relation between the daytime and daily PM2.5 estimated from the ABI AODs has a similar pattern. While daily or daytime estimated PM2.5 provides exposure information in the context of the PM2.5 standard (> 35 μg/m3), the hourly estimates of PM2.5 used in Nowcasting show promise for alerts and warnings of harmful air quality. The geostationary satellite based PM2.5 estimates inform the public of harmful air quality ten times more than standard ground observations (1.8 vs. 0.17 million people per hour).

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.

Following past studies to quantify decadal trends in global carbon monoxide (CO) using satellite observations, we update estimates and find a CO trend in column amounts of about −0.50 % per year between 2002 to 2018, which is a deceleration compared to analyses performed on shorter records that found −1 % per year. Aerosols are co-emitted with CO from both fires and anthropogenic sources but with a shorter lifetime than CO. A combined trend analysis of CO and aerosol optical depth (AOD) measurements from space helps to diagnose the drivers of regional differences in the CO trend. We use the long-term records of CO from the Measurements of Pollution in the Troposphere (MOPITT) and AOD from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Other satellite instruments measuring CO in the thermal infrared, AIRS, TES, IASI, and CrIS, show consistent hemispheric CO variability and corroborate results from the trend analysis performed with MOPITT CO. Trends are examined by hemisphere and in regions for 2002 to 2018, with uncertainties quantified. The CO and AOD records are split into two sub-periods (2002 to 2010 and 2010 to 2018) in order to assess trend changes over the 16 years. We focus on four major population centers: Northeast China, North India, Europe, and Eastern USA, as well as fire-prone regions in both hemispheres. In general, CO declines faster in the first half of the record compared to the second half, while AOD trends show more variability across regions. We find evidence of the atmospheric impact of air quality management policies. The large decline in CO found over Northeast China is initially associated with an improvement in combustion efficiency, with subsequent additional air quality improvements from 2010 onwards. Industrial regions with minimal emission control measures such as North India become more globally relevant as the global CO trend weakens. We also examine the CO trends in monthly percentile values to understand seasonal implications and find that local changes in biomass burning are sufficiently strong to counteract the global downward trend in atmospheric CO, particularly in late summer.

The COVID-19 pandemic related lockdown measures have led to dramatic reductions in air pollution across the globe [1]–[5]. Observations of trace gases and aerosols from ground and satellite have shown a reduction in concentrations from pre-lockdown to the lockdown phase because of reduced emissions from the transportation and industrial sectors. Most studies have used Google or Apple cell phone data to assess reduced mobility [5]. Our study used the derived on-road emissions data for 2019 and 2020 for five different locations in the US (four urban and one rural region) to quantify NOx (NO+NO 2 ) emissions reductions from cars and trucks during the lockdown to study the impact on air quality (NO 2 , PM2.5, and aerosol optical depth as indicators of air quality). Those findings are reported in [6]. The consistency between bottom-up emissions estimates and satellite observed NO 2 concentrations for these five locations will give us confidence in using the satellite NO 2 data elsewhere in the globe in analyzing co-emitted pollutants such as aerosols.

The COVID-19 pandemic has infected almost 73 million people and is responsible for over 1.63 million fatalities worldwide since early December 2019, when it was first reported in Wuhan, China. In the early stages of the pandemic, social distancing measures, such as lockdown restrictions, were applied in a non-uniform way across the world to reduce the spread of the virus. While such restrictions contributed to flattening the curve in places like Italy, Germany, and South Korea, it plunged the economy in the United States to a level of recession not seen since WWII, while also improving air quality due to the reduced mobility. Using daily Earth observation data (Day/Night Band (DNB) from the National Oceanic and Atmospheric Administration Suomi-NPP and NO2 measurements from the TROPOspheric Monitoring Instrument TROPOMI) along with monthly averaged cell phone derived mobility data, we examined the economic and environmental impacts of lockdowns in Los Angeles, California; Chicago, Illinois; Washington DC from February to April 2020—encompassing the most profound shutdown measures taken in the U.S. The preliminary analysis revealed that the reduction in mobility involved two major observable impacts: (i) improved air quality (a reduction in NO2 and PM2.5 concentration), but (ii) reduced economic activity (a decrease in energy consumption as measured by the radiance from the DNB data) that impacted on gross domestic product, poverty levels, and the unemployment rate. With the continuing rise of COVID-19 cases and declining economic conditions, such knowledge can be combined with unemployment and demographic data to develop policies and strategies for the safe reopening of the economy while preserving our environment and protecting vulnerable populations susceptible to COVID-19 infection.

The Outgoing Longwave Radiation (OLR) package was first developed as a stand-alone application, and then integrated into the National Oceanic and Atmospheric Administration (NOAA) Unique Combined Atmospheric Processing System (NUCAPS) hyperspectral sounding retrieval system. An objective of this package is to provide near-real-time OLR products derived from the Cross Track Infrared Sounder (CrIS) onboard the Joint Polar Satellite System (JPSS) satellites. It was initially developed and validated with CrIS onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite, and has been expanded to JPSS-1 (renamed NOAA-20 after launch) datasets that are currently available to the public. In this paper, we provide the results of detailed validation tests with NOAA-20 CrIS for large and wide representative conditions at a global scale. In our validation tests, the observations from Clouds and Earth’s Radiant Energy System (CERES) on Aqua were treated as the absolute reference or “truth”, and those from SNPP CrIS OLR were used as the transfer standard. The tests were performed on a 1°×1° global spatial grid over daily, monthly, and yearly timescales. We find that the CrIS OLR products from NOAA-20 agree exceptionally well with those from Aqua CERES and SNPP CrIS OLR products in all conditions: the daily bias is within ±0.6 Wm−2, and the standard deviation (STD) ranges from 4.88 to 9.1 Wm−2. The bias and the STD of OLR monthly mean are better, within 0.3 and 2.0 Wm−2, respectively. These findings demonstrate the consistency between NOAA-20 and SNPP CrIS OLR up to annual scales, and the robustness of NUCAPS CrIS OLR products.

Earth and Space Science Open Archive This preprint has been submitted to and is under consideration at Journal of Geophysical Research - Atmospheres. ESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing an older version [v1]Go to new versionFingerprints of a New Normal Urban Air Quality in the United StatesAuthorsShobhaKondraguntaiDZigangWeiiDBrianMcDonaldiDDanielGoldbergDanielTongiDSee all authors Shobha KondraguntaiDCorresponding Author• Submitting AuthorNational Oceanic and Atmospheric Administration (NOAA)iDhttps://orcid.org/0000-0001-8593-8046view email addressThe email was not providedcopy email addressZigang WeiiDIM Systems GroupiDhttps://orcid.org/0000-0002-5283-3974view email addressThe email was not providedcopy email addressBrian McDonaldiDNOAA Chemical Sciences LaboratoryiDhttps://orcid.org/0000-0001-8600-5096view email addressThe email was not providedcopy email addressDaniel GoldbergGeorge Washington Universityview email addressThe email was not providedcopy email addressDaniel TongiDGMUiDhttps://orcid.org/0000-0002-4255-4568view email addressThe email was not providedcopy email address

This paper provides an overview of the validation of National Oceanic and Atmospheric Administration (NOAA) operational retrievals of atmospheric carbon trace gas profiles, specifically carbon monoxide (CO), methane (CH4) and carbon dioxide (CO2), from the NOAA-Unique Combined Atmospheric Processing System (NUCAPS), a NOAA enterprise algorithm that retrieves atmospheric profile environmental data records (EDRs) under global non-precipitating (clear to partly cloudy) conditions. Vertical information about atmospheric trace gases is obtained from the Cross-track Infrared Sounder (CrIS), an infrared Fourier transform spectrometer that measures high resolution Earth radiance spectra from NOAA operational low earth orbit (LEO) satellites, including the Suomi National Polar-orbiting Partnership (SNPP) and follow-on Joint Polar Satellite System (JPSS) series beginning with NOAA-20. The NUCAPS CO, CH4, and CO2 profile EDRs are rigorously validated in this paper using well-established independent truth datasets, namely total column data from ground-based Total Carbon Column Observing Network (TCCON) sites, and in situ vertical profile data obtained from aircraft and balloon platforms via the NASA Atmospheric Tomography (ATom) mission and NOAA AirCore sampler, respectively. Statistical analyses using these datasets demonstrate that the NUCAPS carbon gas profile EDRs generally meet JPSS Level 1 global performance requirements, with the absolute accuracy and precision of CO 5% and 15%, respectively, in layers where CrIS has vertical sensitivity; CH4 and CO2 product accuracies are both found to be within ±1%, with precisions of ≈1.5% and ⪅0.5%, respectively, throughout the tropospheric column.

Most countries around the world took actions to control COVID-19 spread that included social distancing, limiting air and ground travel, closing schools, suspending sports leagues, closing factories etc., leading to economic shutdown. The reduced traffic and human movement compared to Business as Usual (BAU) scenario was tracked by Apple and Android cellphone use; the data showed substantial reductions in mobility in most metropolitan areas. For example in Washington D.C., average distance traveled by people was ~13 km and by April when lockdown was in full effect, the distance reduced to ~5 km. Consistent with reduced mobility, air quality as indicated by satellite observations decreased substantially. Granted that year to year variability in weather patterns can have influence on observed NO2 and aerosol concentrations, but the drop in tropospheric nitrogen dioxide (NO2) observed by Sentinel 5P Tropospheric Ozone Monitoring Instrument (TROPOMI) and Suomi NPP Ozone Mapping Profiling Suite (OMPS) observations of NO2 was significant; reductions in observed NO2 were between 15% to 50% between February and April 2020 depending on location and similar reductions in NO2 amount in March and April 2020 compared to March and April 2019. Further, the changes in NO2 across the continental U.S. between 2020 and 2019 correlated well with on-road emissions but did not correlate with changes in emissions from power plants. In the first quarter of 2020, the total amount of NOx emitted on road were 200 times and 7 times larger than that from power plants in LA and NYC, respectively. These findings confirm that power plants are no longer the major source of NO2 in the United States. We also found positive correlation between NO2 and Suomi NPP Visible Infrared Imaging Radiometer Suite (VIIRS) aerosol optical depth measurements in these urban regions indicating common source sectors for NO2 and aerosols/aerosol precursors.

During COVID-19 pandemic in 2020, many cities and areas were shutdown to control the virus spread. The shutdown introduced reduced emissions from vehicles and power plants. In this study, we studied the impact on pollution by analyzing Suomi NPP satellite Visible Infrared Imaging Radiometer Suite (VIIRS) aerosol optical depth (AOD); AOD is a proxy for particulate pollution in the atmosphere. The investigation is performed over several areas and cities around the globe, i.e. China, India, Europe, the United States, New York city, Los Angeles, etc. In general, reductions in AOD compared to the previous years are found in these areas but with some differences. In China, where the pollution in general is high than the other areas, the reduction in AOD is the most obvious. However, in Europe and the United States, the reduction in AOD is less obvious. In India, the effect is in between. Comparing reductions in S5P Tropospheric Ozone Monitoring Instrument (TROPOMI) nitrogen dioxide (NO2) and AOD, we found that they sometimes co-vary and sometimes do not. The possible reason is that NO2 and aerosols do not have the same life time and therefore may not always co-exist at the same time and place. NO2 has a shorter life time and therefore tends to be observed close to the source region. Because of longer life time of aerosols, the aerosols from smoke, dust, and pollution can be transported with long distance and interfere with those from local sources. To tease out the AOD reductions from lockdown compared to business as usual (BAU), AOD data were analyzed using NO2 as a filter. Using this approach we found marginal reductions to particulate pollution in some regions to reductions of up to 20% in other regions. Analysis of particulate pollution in 2020 compared to BAU globally and regionally will be presented.