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Lightning, one of the major sources of nitrogen oxides (NOx) in the atmosphere, contributes to the tropospheric concentration of ozone and to the oxidizing capacity of the atmosphere. Lightning produces between 2 and 8 Tg N yr−1 globally and on average about 250 ± 150 mol NOx per flash. In this work, we estimate the moles of NOx produced per flash (LNOx production efficiency) in the Pyrenees (Spain, France and Andorra) and in the Ebro Valley (Spain) by using nitrogen dioxide (NO2) and cloud properties from the TROPOspheric Monitoring Instrument (TROPOMI) as well as lightning data from the Earth Networks Global Lightning Network (ENGLN) and from the EUropean Co-operation for LIghtning Detection (EUCLID). The Pyrenees are one of the areas in Europe with the highest lightning frequencies, which, along with their remoteness as well as their very low NOx background, enables us to better distinguish the LNOx signal produced by recent lightning in TROPOMI NO2 measurements. We compare the LNOx production efficiency estimates for eight convective systems in 2018 using two different sets of TROPOMI research products provided by the Royal Netherlands Meteorological Institute (KNMI) and the Deutsches Zentrum für Luft- und Raumfahrt (DLR). According to our results, the mean LNOx production efficiency in the Pyrenees and in the Ebro Valley, using a 3 h chemical lifetime, ranges between 14 and 103 mol NOx per flash from the eight systems. The mean LNOx production efficiency estimates obtained using both TROPOMI products and ENGLN lightning data differ by ∼ 23 %, while they differ by ∼ 35 % when using EUCLID lightning data. The main sources of uncertainty when using ENGLN lightning data are the estimation of background NOx that is not produced by lightning and the time window before the TROPOMI overpass that is used to count the total number of lightning flashes contributing to freshly produced LNOx. The main source of uncertainty when using EUCLID lightning data is the uncertainty in the detection efficiency of EUCLID.

Separating the stratospheric and tropospheric contributions in satellite retrievals of atmospheric NO2 column abundance is a crucial step in the interpretation and application of the satellite observations. A variety of stratosphere–troposphere separation algorithms have been developed for sun-synchronous instruments in low Earth orbit (LEO) that benefit from global coverage, including broad clean regions with negligible tropospheric NO2 compared to stratospheric NO2. These global sun-synchronous algorithms need to be evaluated and refined for forthcoming geostationary instruments focused on continental regions, which lack this global context and require hourly estimates of the stratospheric column. Here we develop and assess a spatial filtering algorithm for the upcoming TEMPO geostationary instrument that will target North America. Developments include using independent satellite observations to identify likely locations of tropospheric enhancements, using independent LEO observations for spatial context, consideration of diurnally varying partial fields of regard, and a filter based on stratospheric to tropospheric air mass factor ratios. We test the algorithm with LEO observations from the OMI instrument with an afternoon overpass, and from the GOME-2 instrument with a morning overpass.We compare our TEMPO field of regard algorithm against an identical global algorithm to investigate the penalty resulting from the limited spatial coverage in geostationary orbit, and find excellent agreement in the estimated mean daily tropospheric NO2 column densities (R2 = 0.999, slope = 1.009 for July and R2 = 0.998, slope = 0.999 for January). The algorithm performs well even when only small parts of the continent are observed by TEMPO. The algorithm is challenged the most by east coast morning retrievals in the wintertime (e.g., R2 = 0.995, slope = 1.038 at 14:00 UTC). We find independent global LEO observations (corrected for time of day) provide important context near the field-of-regard edges. We also test the performance of the TEMPO algorithm without these supporting global observations. Most of the continent is unaffected (R2 = 0.924 and slope = 0.973 for July and R2 = 0.996 and slope = 1.008 for January), with 90 % of the pixels having differences of less than ±0.2×1015 molecules cm−2 between the TEMPO tropospheric NO2 column density and the global algorithm. For near-real-time retrieval, even a climatological estimate of the stratospheric NO2 surrounding the field of regard would improve this agreement. In general, the additional penalty of a limited field of regard from TEMPO introduces no more error than normally expected in most global stratosphere–troposphere separation algorithms. Overall, we conclude that hourly near-real-time stratosphere–troposphere separation for the retrieval of NO2 tropospheric column densities by the TEMPO geostationary instrument is both feasible and robust, regardless of the diurnally varying limited field of regard.

We describe the new version 3.0 NASA Ozone Monitoring Instrument (OMI) standard nitrogen dioxide (NO2) products (SPv3). The products and documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/). The major improvements include (1) a new spectral fitting algorithm for NO2 slant column density (SCD) retrieval and (2) higher-resolution (1° latitude and 1.25° longitude) a priori NO2 and temperature profiles from the Global Modeling Initiative (GMI) chemistry–transport model with yearly varying emissions to calculate air mass factors (AMFs) required to convert SCDs into vertical column densities (VCDs). The new SCDs are systematically lower (by ∼ 10–40 %) than previous, version 2, estimates. Most of this reduction in SCDs is propagated into stratospheric VCDs. Tropospheric NO2 VCDs are also reduced over polluted areas, especially over western Europe, the eastern US, and eastern China. Initial evaluation over unpolluted areas shows that the new SPv3 products agree better with independent satellite- and ground-based Fourier transform infrared (FTIR) measurements. However, further evaluation of tropospheric VCDs is needed over polluted areas, where the increased spatial resolution and more refined AMF estimates may lead to better characterization of pollution hot spots.

The Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite has been providing global observations of the ozone layer and key atmospheric pollutant gases, such as nitrogen dioxide (NO2) and sulfur dioxide (SO2), since October 2004. The data products from the same instrument provide consistent spatial and temporal coverage and permit the study of anthropogenic and natural emissions on local-to-global scales. In this paper, we examine changes in SO2 and NO2 over some of the world's most polluted industrialized regions during the first decade of OMI observations. In terms of regional pollution changes, we see both upward and downward trends, sometimes in opposite directions for NO2 and SO2, for different study areas. The trends are, for the most part, associated with economic and/or technological changes in energy use, as well as regional regulatory policies. Over the eastern US, both NO2 and SO2 levels decreased dramatically from 2005 to 2015, by more than 40 and 80 %, respectively, as a result of both technological improvements and stricter regulations of emissions. OMI confirmed large reductions in SO2 over eastern Europe's largest coal-fired power plants after installation of flue gas desulfurization devices. The North China Plain has the world's most severe SO2 pollution, but a decreasing trend has been observed since 2011, with about a 50 % reduction in 2012–2015, due to an economic slowdown and government efforts to restrain emissions from the power and industrial sectors. In contrast, India's SO2 and NO2 levels from coal power plants and smelters are growing at a fast pace, increasing by more than 100 and 50 %, respectively, from 2005 to 2015. Several SO2 hot spots observed over the Persian Gulf are probably related to oil and gas operations and indicate a possible underestimation of emissions from these sources in bottom-up emission inventories. Overall, OMI observations have proved valuable in documenting rapid changes in air quality over different parts of the world during last decade. The baseline established during the first 11 years of OMI is indispensable for the interpretation of air quality measurements from current and future satellite atmospheric composition missions.

We assess the standard operational nitrogen dioxide (NO2) data product (OMNO2, version 2.1) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite using a combination of aircraft and surface in~situ measurements as well as ground-based column measurements at several locations and a bottom-up NOx emission inventory over the continental US. Despite considerable sampling differences, NO2 vertical column densities from OMI are modestly correlated (r = 0.3–0.8) with in situ measurements of tropospheric NO2 from aircraft, ground-based observations of NO2 columns from MAX-DOAS and Pandora instruments, in situ surface NO2 measurements from photolytic converter instruments, and a bottom-up NOx emission inventory. Overall, OMI retrievals tend to be lower in urban regions and higher in remote areas, but generally agree with other measurements to within ± 20%. No consistent seasonal bias is evident. Contrasting results between different data sets reveal complexities behind NO2 validation. Since validation data sets are scarce and are limited in space and time, validation of the global product is still limited in scope by spatial and temporal coverage and retrieval conditions. Monthly mean vertical NO2 profile shapes from the Global Modeling Initiative (GMI) chemistry-transport model (CTM) used in the OMI retrievals are highly consistent with in situ aircraft measurements, but these measured profiles exhibit considerable day-to-day variation, affecting the retrieved daily NO2 columns by up to 40%. This assessment of OMI tropospheric NO2 columns, together with the comparison of OMI-retrieved and model-simulated NO2 columns, could offer diagnostic evaluation of the model.

We describe a new algorithm for the retrieval of nitrogen dioxide (NO2) vertical columns from nadir-viewing satellite instruments. This algorithm (SP2) is the basis for the Version 2.1 OMI This algorithm (SP2) is the basis for the Version 2.1 Ozone Monitoring Instrument (OMI) NO2 Standard Product and features a novel method for separating the stratospheric and tropospheric columns. NO2 Standard Product and features a novel method for separating the stratospheric and tropospheric columns. The approach estimates the stratospheric NO2 directly from satellite data without using stratospheric chemical transport models or assuming any global zonal wave pattern. Tropospheric NO2 columns are retrieved using air mass factors derived from high-resolution radiative transfer calculations and a monthly climatology of NO2 profile shapes. We also present details of how uncertainties in the retrieved columns are estimated. The sensitivity of the retrieval to assumptions made in the stratosphere–troposphere separation is discussed and shown to be small, in an absolute sense, for most regions. We compare daily and monthly mean global OMI NO2 retrievals using the SP2 algorithm with those of the original Version 1 Standard Product (SP1) and the Dutch DOMINO product. The SP2 retrievals yield significantly smaller summertime tropospheric columns than SP1, particularly in polluted regions, and are more consistent with validation studies. SP2 retrievals are also relatively free of modeling artifacts and negative tropospheric NO2 values. In a reanalysis of an INTEX-B validation study, we show that SP2 largely eliminates an ~20% discrepancy that existed between OMI and independent in situ springtime NO2 SP1 measurements.

We retrieve slant column NO2 from the super-zoom mode of the Ozone Monitoring Instrument (OMI) to explore its utility for understanding NOx emissions and variability. Slant column NO2 is operationally retrieved from OMI (Boersma et al., 2007; Bucsela et al., 2006) with a nadir footprint of 13 × 24 km2, the result of averaging eight detector elements on board the instrument. For 85 orbits in late 2004, OMI reported observations from individual "super-zoom" detector elements (spaced at 13 × 3 km2 at nadir). We assess the spatial response of these individual detector elements in-flight and determine an upper-bound on spatial resolution of 9 km, in good agreement with on-ground calibration (7 km FWHM). We determine the precision of the super-zoom mode to be 2.1 × 1015 molecules cm−2, approximately a factor of √8 lower than an identical retrieval at operational scale as expected if random noise dominates the uncertainty. We retrieve slant column NO2 over the Satpura power plant in India; Seoul, South Korea; Dubai, United Arab Emirates; and a set of large point sources on the Rihand Reservoir in India using differential optical absorption spectroscopy (DOAS). Over these sources, the super-zoom mode of OMI observes variation in slant column NO2 of up to 30 × the instrumental precision within one operational footprint.

We present a new retrieval of tropospheric NO2 vertical column density from the Ozone Monitoring Instrument (OMI) based on high spatial and temporal resolution terrain and profile inputs. We compare our NO2 product, the Berkeley High-Resolution (BEHR) product, with operational retrievals and find that the operational retrievals are biased high (30 %) over remote areas and biased low (8 %) over urban regions. Additionally, we find non-negligible impacts on the retrieved NO2 column for terrain pressure (±20 %), albedo (±40 %), and NO2 vertical profile (−75 %–+10 %). We validate the operational and BEHR products using boundary layer aircraft observations from the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS-CA) field campaign which occurred in June 2008 in California. Results indicate that columns derived using our boundary layer extrapolation method show good agreement with satellite observations (R2 = 0.65–0.83; N = 68) and provide a more robust validation of satellite-observed NO2 column than those determined using full vertical spirals (R2 = 0.26; N = 5) as in previous work. Agreement between aircraft observations and the BEHR product (R2 = 0.83) is better than agreement with the operational products (R2 = 0.65–0.72). We also show that agreement between satellite and aircraft observations can be further improved (e.g. BEHR: R2 = 0.91) using cloud information from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument instead of the OMI cloud product. These results indicate that much of the variance in the operational products can be attributed to coarse resolution terrain pressure, albedo, and profile parameters implemented in the retrievals.

From 13 July–9 August 2007, 25 ozonesondes were launched from Las Tablas, Panama as part of the Tropical Composition, Cloud, and Climate Coupling (TC4) mission. On 5 August, a strong convective cell formed in the Gulf of Panama. World Wide Lightning Location Network (WWLLN) data indicated 563 flashes (09:00–17:00 UTC) in the Gulf. NO2 data from the Ozone Monitoring Instrument (OMI) show enhancements, suggesting lightning production of NOx. At 15:05 UTC, an ozonesonde ascended into the southern edge of the now dissipating convective cell as it moved west across the Azuero Peninsula. The balloon oscillated from 2.5–5.1 km five times (15:12–17:00 UTC), providing a unique examination of ozone (O3) photochemistry on the edge of a convective cell. Ozone increased at a rate of ~1.6–4.6 ppbv/hr between the first and last ascent, resulting cell wide in an increase of ~(2.1–2.5) × 106 moles of O3. This estimate agrees to within a factor of two of our estimates of photochemical lightning O3 production from the WWLLN flashes, from the radar-inferred lightning flash data, and from the OMI NO2 data (~1.2, ~1.0, and ~1.7 × 106 moles, respectively), though all estimates have large uncertainties. Examination of DC-8 in situ and lidar O3 data gathered around the Gulf that day suggests 70–97% of the O3 change occurred in 2.5–5.1 km layer. A photochemical box model initialized with nearby TC4 aircraft trace gas data suggests these O3 production rates are possible with our present understanding of photochemistry.

A challenge for the quantitative analysis of tropospheric nitrogen dioxide (NO2) column data from satellite observations is posed partly by the lack of satellite-independent observations for validation. We performed such observations of the tropospheric NO2 column using the ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) technique in the North China Plain (NCP) from 29 May to 29 June, 2006. Comparisons between tropospheric NO2 columns measured by MAX-DOAS and the Ozone Monitoring Instrument (OMI) onboard the Aura satellite indicate that OMI data (the standard product, version 3) over NCP may have a positive bias of 1.6×1015 molecules cm−2 (20%), yet within the uncertainty of the OMI data. Combining these results with literature validation results for the US, Europe, and Pacific Ocean suggests that a bias of +20%/−30% is a reasonable estimate, accounting for different regions.

We present a new algorithm for the near-real time retrieval – within 3 h of the actual satellite measurement – of tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI). The retrieval is based on the combined retrieval-assimilation-modelling approach developed at KNMI for off-line tropospheric NO2 from the GOME and SCIAMACHY satellite instruments. We have adapted the off-line system such that the required a priori information – profile shapes and stratospheric background NO2 – is now immediately available upon arrival (within 80 min of observation) of the OMI NO2 slant columns and cloud data at KNMI. Slant columns for NO2 are retrieved using differential optical absorption spectroscopy (DOAS) in the 405–465 nm range. Cloud fraction and cloud pressure are provided by a new cloud retrieval algorithm that uses the absorption of the O2-O2 collision complex near 477 nm. On-line availability of stratospheric slant columns and NO2 profiles is achieved by running the TM4 chemistry transport model (CTM) forward in time based on forecast ECMWF meteo and assimilated NO2 information from all previously observed orbits. OMI NO2 slant columns, after correction for spurious across-track variability, show a random error for individual pixels of approximately 0.7×1015 molec cm−2. Cloud parameters from OMI's O2-O2 algorithm have similar frequency distributions as retrieved from SCIAMACHY's Fast Retrieval Scheme for Cloud Observables (FRESCO) for August 2006. On average, OMI cloud fractions are higher by 0.011, and OMI cloud pressures exceed FRESCO cloud pressures by 60 hPa. A sequence of OMI observations over Europe in October 2005 shows OMI's capability to track changeable NOx air pollution from day to day in cloud-free situations.