Volatile organic compounds (VOCs) are important precursors to the formation of ozone (O3) and secondary organic aerosols (SOA) and can also have direct human health impacts. The emissions of VOCs remain poorly characterized due to the complexity and variability of their sources. The VOC levels in Beijing during the winter campaign (APHH) were investigated using a dispersion model (NAME), and a chemical box model (AtChem2) in order to understand how chemistry and transport affect the VOC concentrations in Beijing. Emissions of VOCs in Beijing and contributions from outside Beijing were modelled using the NAME dispersion model combined with the emission inventories and were used to initialize the AtChem2 box model. The modelled concentrations of VOCs from the NAME-AtChem2 combination were then compared to the output of a chemical transport model (GEOS-Chem). The results from the emission inventories and the NAME air mass pathways suggest that industrial sources to the south of Beijing and within Beijing during the winter campaign are very important in controlling the VOC levels in Beijing. A number of scenarios with different nitrogen oxides to ozone ratios (NOx/O3) and hydroxyl (OH) levels were simulated to determine the changes in VOC levels. In Beijing over 80 % of VOC are emitted locally during winter. Most scenarios are in good agreement with daily GEOS-Chem simulations, with the best agreements seen for the modelled concentrations of ethanol, benzene and propane with correlation coefficients of 0.67, 0.63 and 0.64 respectively. Furthermore, the production of formaldehyde in an air mass within 24 h of travel from Beijing was investigated, and it was estimated that 90 % of formaldehyde in Beijing is secondary, produced from oxidation of non-methane volatile organic compounds (NMVOCs). The benzene/CO and toluene/CO ratios during the campaign are very similar to the ratio derived from literature for 2014 in Beijing, however more data are needed to enable investigation of more species over longer timeframes to determine whether this ratio can be applied to predicting VOCs in Beijing. The results suggest that VOC concentrations in Beijing are driven predominantly by sources within Beijing and by local atmospheric chemistry during the winter. Moreover, the relationship of the NOx/VOC and O3 shows that the VOCs during the winter campaign are possibly emitted from similar sources as NOx.

The United States has one of the world's largest oil and gas (O&G) industries, yet the health impacts and inequities from pollutants produced along the O&G lifecycle remain poorly characterized. Here, we model the contribution of major lifecycle stages (upstream, midstream, downstream, and end-use) to air pollution and estimate the associated chronic health outcomes and racial-ethnic disparities across the contiguous US in 2017. We estimate lifecycle annual burdens of 91,000 premature deaths attributable to fine particles (PM2.5), nitrogen dioxide (NO2), and ozone, 10,350 PM2.5-attributable preterm births, 216,000 incidences of NO2-attributable childhood-onset asthma, and 1610 lifetime cancers attributable to hazardous air pollutants (HAPs). Racial-ethnic minorities experience the greatest disparities in exposure and health burdens across almost all lifecycle stages. The greatest absolute disparities occur for Black and Asian populations from PM2.5 and ozone, and the Asian population from NO2 and HAPs. Relative inequities are most extreme from downstream activities, especially in Louisiana and Texas.

Free tropospheric (FT) nitrogen dioxide (NO2) plays a critical role in atmospheric oxidant chemistry as a source of tropospheric ozone and of the hydroxyl radical (OH). It also contributes significantly to satellite-observed tropospheric NO2 columns, which should be considered when using these columns to quantify surface emissions of nitrogen oxide radicals (NOx ≡ NO + NO2). But large uncertainties remain in the sources and chemistry of FT NO2 because observations are sparse. Here, we construct a cloud-sliced FT NO2 (700 to 300 hPa) product from the Tropospheric Emissions: Monitoring of Pollution (TEMPO) geostationary satellite instrument over North America. This product provides higher data density and quality than previous products from low Earth orbit instruments, including the first observations of the FT NO2 diurnal cycle in different seasons. Combined with coincident observations from the Geostationary Lightning Mapper, the TEMPO data imply that lightning is the dominant source of FT NOx in nonwinter seasons. Comparison of TEMPO FT NO2 data with the Goddard Earth Observation System-Composition Forecasts (GEOS-CF) atmospheric chemistry model shows overall consistent magnitudes, seasonality, and diurnal variation, with a midday minimum in nonwinter seasons from photochemical loss. However, there are major discrepancies that we attribute to GEOS-CF's use of a standard cloud-top-height-based scheme for the lightning NOx source. We find that this scheme underestimates offshore lighting flash density and misrepresents the diurnal cycle of lightning over land. Our FT NO2 product provides a unique resource for improving the lightning NOx parameterization in atmospheric models and the ability to use NO2 observations from space to quantify surface NOx emissions.

Surface concentrations of nitrogen oxides (NOx) are increasing at rates of up 10% per year in cities in Africa, as inferred with trends in long-term satellite observations of tropospheric columns of nitrogen dioxide (NO2). This is being driven by rapid population growth and urbanization in the absence of air quality policies. Models needed to inform air quality policies use out-of-date inventories for cities in Africa due to absence of detailed temporal and spatial information about emission and activity factors of sources unique to African cities. Here we apply a recently improved method of deriving city NOx emissions from satellite observations of NO2 that builds on the well-established rotation of each city NO2 plume along a consistent direction and selecting a single sampling area around the city centre to fit a modified Gaussian to calculate emissions. The improved method uses a more efficient fit routine and multiple sampling areas to eliminate subjective area selection and increase the success of deriving annual emissions from ~50% to 100%. Such an approach is ideal for African cities that have wide-ranging sizes due to the different development stages of countries and urban centres in Africa. Work is underway to quantify NOx emissions for more cities in Africa than has been achieved with global studies using 2019 observations of NO2 from the TROPOspheric Monitoring Instrument (TROPOMI). The resultant NOx emissions will then be compared to emissions estimates from widely used global (EDGAR, CEDS, HTAP) and regional (DACCIWA, DICE-Africa) inventories to assess shortcomings in inventories and the influence of these on designing evidence-based air quality policies and regulations.

Cities in South and Southeast Asia are developing rapidly without routine, up-to-date knowledge of air pollutant precursor emissions. This data deficit can potentially be addressed for nitrogen oxides (NO) by deriving city NO emissions from satellite observations of nitrogen dioxide (NO) sampled under windy conditions. NO plumes of isolated cities are aligned along a consistent wind-rotated direction and a best-fit Gaussian is applied to estimate emissions. This approach currently relies on non-standardized selection of the area to sample around the city centre and Gaussian fits often fail or yield non-physical parameters. Here, we automate this approach by defining many (54) sampling areas that we test with TROPOspheric Monitoring Instrument (TROPOMI) NO observations for 2019 over 19 cities in South and Southeast Asia. Our approach is efficient, adaptable to many cities, standardizes and eliminates sensitivity of the Gaussian fit to sampling area choice, and increases success of deriving annual emissions from 40-60% with one sampling area to 100% (all 19 cities) with 54. The annual emissions we estimate range from 16±5 mol s for Yangon (Myanmar) and Bangalore (India) to 125±41 mol s for Dhaka (Bangladesh). With the enhanced success of our approach, we find evidence from comparison of our top-down emissions to past studies and to inventory estimates that the wind rotation and EMG fit approach may be biased, as it does not adequately account for spatial and seasonal variability in NO photochemistry. Further methodological development is needed to enhance its accuracy and to exploit it to derive sub-annual emissions.

Natural emissions (vegetation, soil, and lightning) are the dominant sources of non-methane biogenic volatile organic compounds (BVOCs) and nitrogen oxides (NOx≡ NO + NO2) released into the atmosphere over Africa. BVOCs and NOx interact with each other and strongly impact their own chemical lifetimes and degradation pathways, in particular through their influence on hydroxyl radical levels. To account for this intricate interplay between NOx and VOCs, we design and apply a novel inversion setup aiming at simultaneous optimization of monthly VOC and NOx emissions in 2019 in a regional chemistry-transport model, based on Tropospheric Ozone Monitoring Instrument (TROPOMI) HCHO and NO2 satellite observations. The TROPOMI-based inversions suggest substantial underestimations of natural NOx and VOC emissions used as a priori in the model. The annual flux over Africa increases from 125 to 165 Tg yr−1 for isoprene, from 1.9 to 2.4 TgN yr−1 for soil NO emissions, and from 0.5 to 2.0 TgN yr−1 for lightning NO emissions. Despite the NOx emission increase, evaluation against in situ NO2 measurements at seven rural sites in western Africa displays significant model underestimations after optimization. The large increases in lightning emissions are supported by comparisons with TROPOMI cloud-sliced upper-tropospheric NO2 volume mixing ratios, which remain underestimated by the model even after optimization. Our study strongly supports the application of a bias correction to the TROPOMI HCHO data and the use of a two-species constraint (vs. single-species inversion), based on comparisons with isoprene columns retrieved from the Cross-track Infrared Sensor (CrIS).

Landscape fires in subtropical southern Africa (2-20°S) are a prominent regional source of nitrogen oxides (NO x ) and ammonia (NH3), affecting climate and air quality as precursors of tropospheric ozone and aerosols. Here we evaluate GEOS-Chem model skill at reproducing satellite observations of vertical column densities of NO2 from TROPOMI and NH3 from IASI driven with three distinct and widely used biomass burning inventories (FINNv2.5, GFEDv4s, GFASv1.2). We identify that GFASv1.2 use of fire radiative power and a NO x emission factor that is almost half that used by the other two inventories is most consistent with TROPOMI and that FINNv2.5 use of active fires and landscape-specific fuel loads and biomass consumed is most consistent with IASI. We use a simple mass-balance inversion to calculate top-down NO x emissions of 1.9 ± 0.6 Tg NO for June-October and NH3 emissions of 1.2 ± 0.4 Tg for July-October. All inventories collocate NO x and NH3 emissions, whereas most of the pronounced emissions of NO x and NH3 are separate and have distinct seasonality in the top-down estimate. We infer with GEOS-Chem more efficient ozone production (13 Tg ozone per Tg NO) with the top-down informed NO x emissions than the inventory emissions, as GFASv1.2 NO x is almost 20% less than top-down NO x and the 2.3- to 2.5-times greater FINNv2.5 and GFEDv4s NO x reduces sensitivity of ozone formation to NO x . Both NO x and NH3 top-down emissions are unaffected by use of plume injection heights, limited to GFASv1.2 in GEOS-Chem, and NH3 is insensitive to acidic sulfate and nitrate aerosol emissions absent in all inventories. The top-down emissions estimates and comparison to satellite observations suggest a hybrid bottom-up approach could be adopted to discern byproducts of smouldering and flaming fires.

Space-borne remote sensing of atmospheric chemical constituents is crucial for monitoring and better understanding global and regional air quality. Since the 1990s, the continuous development of instruments onboard low-Earth orbiting (LEO) satellites has led to major advances in air quality research by providing daily global measurements of atmospheric chemical species. The next generation of atmospheric composition satellites measures from the geostationary Earth orbit (GEO) with hourly temporal resolution, allowing the observation of diurnal variations of air pollutants. The first two instruments of the GEO constellation coordinated by the Committee on Earth Observation Satellites (CEOS), the Geostationary Environment Monitoring Spectrometer (GEMS) for Asia and the Tropospheric Emissions: Monitoring of Pollution (TEMPO) for North America, were successfully launched in 2020 and 2023, respectively. The European component, Sentinel-4, is planned for launch in 2025. This work provides an overview of satellite missions for atmospheric composition monitoring and the state of the science in air quality research. We cover recent advances in retrieval algorithms, the modeling of emissions and atmospheric chemistry, data assimilation, and the application of machine learning based on satellite data. We discuss the challenges and opportunities in air quality research in the era of GEO satellites and provide recommendations on research priorities for the near future.

Oil and gas account for more than two-thirds of energy consumed in the US. The high-temperature combustion from this use yields large quantities of nitrogen oxides (NOx) that modulate the oxidative fate of isoprene, a precursor of health-hazardous air pollutants ozone, formaldehyde, and fine particulate matter (PM2.5). The COVID-19 pandemic and resulting lockdowns provided a unique opportunity to examine changes in ozone and PM2.5 linked to dramatic reduction in vehicle emissions. These occurred mostly in early spring when photochemistry is weak, biogenic emissions of isoprene are nascent, and ozone is titrated by vehicular nitric oxide (NO) emissions. Here, we use the 3D chemical transport model GEOS-Chem nested over contiguous US at a spatial resolution of 0.25º × 0.3125º (~28 km latitude × ~27 km longitude) to examine the complex influence of all oil and gas consumption or end-use activities on summertime (June-August) air pollutants in the eastern US where large cities, roadways and seasonal isoprene emission hotspots coincide. The model is driven with air pollutant precursor emissions for end-use activities from the US EPA National Emissions Inventory (NEI) for non-mobile sources and from the Fuel-based Inventory for Vehicular Emissions (FIVE) for mobile sources. We find that in the eastern US, end-use activities account for most NOx (59% of NO and 57% of nitrogen dioxide, NO2) and most (63% or 0.28 µg m-3) aerosol-phase nitrate. As ammonia, predominantly from agricultural activity, buffers aerosol acidity, end-use activities also indirectly contribute to 21% (0.10 µg m-3) of aerosol-phase ammonium. The influence on aerosol sulfate is negligible. NO from oil and gas end-use activities also modulates the proportion of isoprene that oxidizes via the NO and HO2 pathways that in turn affects yields of formaldehyde and other reactive oxygenated volatile organic compounds (VOCs) as well as isoprene secondary organic aerosol (SOA) precursors. NOx from oil and gas end-use activities enhances formaldehyde abundance by 0.3 ppb by increasing the proportion of isoprene reacting via the NO oxidation pathway that yields formaldehyde (and other oxygenated VOCs) promptly and in higher yields than the competing HO2 (low-NOx) oxidation pathway. This influence on reactive VOCs also adds 8 ppb of maximum daily mean 8-hour ozone, the metric used to assess the impact of ozone on health. Suppression of the HO2 oxidation pathway and isoprene SOA precursors only decreases SOA by 0.02 µg m-3. The net contribution of oil and gas end-use activities to PM2.5 is 1.2 µg m-3 or 12% of eastern US summertime mean PM2.5. Our results suggest multiple, substantial improvements to summertime air quality by ending reliance on oil and gas.

Lightning is a crucial driver of nitrogen oxides (NOx) in the free troposphere where tropospheric ozone formation is limited by the availability of NOx. NOx production per lightning flash in models is typically represented with a single temporally and spatially static value, likely affecting the accuracy in simulating past, present, and future lightning NOx and consequent changes in tropospheric ozone (O3) and other oxidants. We determine spatially (0.5° × 0.625°) varying hourly NOx production rates (mol N fl⁻¹) using literature reported relationships between NOx yields and lightning flash radiant energies from Lightning Imaging Sensors (LIS) aboard the Tropical Rainfall Measuring Mission (TRMM) and the International Space Station (ISS). The diurnal and spatial variability of the radiant energies from the LIS instruments are assessed to be overall consistent with optical energies from the Geostationary Lightning Mapper (GLM) instrument, which monitors the Americas every 5 minutes. The diurnal variability between the two datasets differs by < 15%. Our lighting NOx production rates are added to GEOS-Chem, yielding global emissions of 6.5 Tg N yr-1 for 2015-2019, closely aligning with 5.8 Tg N yr-1 in the original parameterised representation, but with large differences in the spatial distribution of lightning NOx. Our updated parameterisation causes increases of > 50 pptv in NO2 across the troposphere, particularly in the tropics coincident with deep convection. The resultant changes in tropospheric composition improve agreement with satellite-derived vertical profiles of NO2 obtained via cloud-slicing TROPOMI by decreasing the model underestimate in free tropospheric NO2. Assessment against cloud-sliced O3 is underway.

Lightning is the dominant source of nitrogen oxides (NOx) in the free troposphere. Yet, its representation in models is highly parameterised, limiting our ability to determine past and future changes in lightning NOx and causing errors in model representation of tropospheric ozone and NOx. Models such as GEOS-Chem use fixed lightning NOx production rates constrained with historic satellite instrument observations of ozone. A new approach is to model NOx production per flash (mol N fl-1) using lightning energy dependent NOx yields and lightning flash radiant energy data from the space-based lightning imaging sensor (LIS) aboard both the Tropical Rainfall Measuring Mission (TRMM) satellite and the International Space Station (ISS). This updated approach is then used in GEOS-Chem to compute total lightning NOx yields through the Harmonized Emissions Component (HEMCO), rather than using fixed values. The updated annual lightning NOx emissions total 6.5 Tg N, similar to the original parameterised representation (5.8 Tg N), but with much greater variability in NOx production rates. The original implementation uses 260 mol N fl-1 everywhere except the northern extratropics that are at 500 mol fl-1. In the updated implementation, values range from 27 to 632 mol N fl-1 over the ocean and from 66 to 482 mol N fl-1 over land. Greater values over the ocean are due to oft-reported much more energetic maritime lightning. To test the effect on tropospheric ozone and NOx, we are currently comparing seasonal mean GEOS-Chem and TROPOMI-derived vertical profiles of ozone and NO2. The TROPOMI-derived values, obtained by cloud-slicing partial columns over optically thick clouds, we have previously evaluated to be consistent with NASA DC-8 aircraft measurements in the free troposphere for cloud-sliced NO2 (differences < 20 pptv) and the global ozonesonde network for cloud-sliced ozone across the whole troposphere (differences < 35 ppbv). This offers the means to assess the representation of lightning NOx and better understand its influence on tropospheric NOx and ozone.

In the next few decades a large increase in population is expected to occur on the African continent, leading to a doubling of the current population, which will reach 2.5 billion by 2050. At the same time, Africa is experiencing substantial economic growth. As a result, air pollution and greenhouse gas emissions will increase considerably with significant health impacts to people in Africa. In the decades ahead, Africa’s contribution to climate change and air pollution will become increasingly important. The time has come to determine the evolving role of Africa in global environmental change. We are building an Atmospheric Composition Virtual Constellation, as envisioned by the Committee on Earth Observation Satellites (CEOS), by adding to our polar satellites, geostationary satellites in the Northern Hemisphere : GEMS over Asia (launch 2022); TEMPO over the USA (launch 2023) and Sentinel 4 over Europe to be launched in the 2024 timeframe. However, there are currently no geostationary satellites envisioned over Africa and South-America, where we expect the largest increase in emissions in the decades to come.In this paper the scientific need for geostationary satellite measurements over Africa will be described, partly based on several recent research achievements related to Africa using space observations and modeling approaches, as well as first assessments using the GEMS data over Asia, and TEMPO over the USA. Our ambition is to develop an integrated community effort to better characterize air quality and climate-related processes on the African continent.

There are close to 6000 megaconstellation satellites in low-Earth orbit comprising 65% of all satellites orbiting Earth. The growth in satellite megaconstellations has driven surges in rocket launches and re-entry destruction of spent satellites. This has contributed to large increases in emissions of pollutants that are very effective at depleting stratospheric ozone and altering climate, due to direct injection of pollutants into the upper layers of the atmosphere where turnover rates are very slow. An additional 540,000 megaconstellation satellites are proposed, yet the environmental impacts of emissions from current and future satellite megaconstellations remain uncharacterized and unregulated. Here we calculate emissions of the dominant pollutants from megaconstellation and non-megaconstellation rocket launches and re-entries from 2020 to 2022 to determine the effect on climate and stratospheric ozone. Pollutants include black carbon (BC), nitrogen oxides (NOx≡NO+NO2), water vapour (H2O), carbon monoxide (CO), alumina aerosol (Al2O3) and chlorine species (Cly≡HCl+Cl2+Cl) from rocket launches and nitrogen oxides (NOx≡NO) and alumina aerosol (Al2O3) from re-entries. Launch emissions are calculated by determining the vertical distribution of propellant consumption for each rocket stage and calculating and applying vertically resolved propellant specific emission indices that account for additional oxidation in the hot rocket plume and changes in atmospheric composition with altitude. To quantify the re-entry emissions, the mass of re-entering objects is compiled for all objects (spacecraft, rocket stages, fairings, and components) re-entering Earth’s atmosphere in 2020-2022. Many objects, accounting for 12-16% of re-entry mass, are not geolocated, so the longitude and latitude of re-entry is bounded by the reported orbital inclination. Object class and object reusability are used to define the chemical composition and mass ablation profile of each re-entering object. We find that total propellant consumed has nearly doubled from ~38 Gg in 2020 to ~67 Gg in 2022 and re-entry mass has increased from ~3.3 Gg in 2020 to ~5.6 Gg in 2022. Megaconstellation re-entries accounted for 8-12% of the Al2O3 and NOx re-entry emissions in 2020-2022, due to increased megaconstellation launches and short (~2 years) lifespan of most (85%) megaconstellation satellites. Anthropogenic re-entry emissions of NOx (~4.2 Gg) and Al2O3 (~0.96 Gg) in 2022 equal a third of the natural meteoritic injection of NOx and surpass the natural injection by 7 times for Al2O3. The annual emissions for 2020-2022 will be used to predict the rise in emissions up to 2029 from megaconstellation and non-megaconstellation rocket launches and object re-entries for input to the 3D atmospheric chemistry transport model GEOS-Chem coupled to a radiative transfer model to simulate stratospheric ozone depletion and radiative forcing attributable to a decade of satellite megaconstellation emissions.

In polluted cities with large sources of NOx, rapid photolysis of nitrous acid (HONO) may be a major daytime source of the main atmospheric oxidant, OH. Current understanding of urban HONO is problematic. Its abundance is generally underestimated by models, and urban and rural networks. Campaigns with in situ instruments routinely identify a mystery midday HONO source. These measurements do not directly measure HONO and offer no insight into its vertical distribution. We use remotely sensed daytime differential slant column density (dSCD) measurements of HONO from a Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument which was installed on a 60 m rooftop during summer 2022 on the Bloomsbury University College London (UCL) campus. Modelled (GEOS-Chem) and surface network measurements of air quality and meteorology are used to characterise conditions conducive to HONO detection. To be detected, dSCDs must exceed the detection limit, which we define as 2 times the root mean square of the fit of residuals divided by the maximum absorption cross section of HONO. We find that MAX-DOAS HONO dSCDs at elevation angles measuring the lowest layers of the atmosphere are only ever above the instrument detection limit in winter mornings (8:30 am–12:00 pm local time), suggesting substantial nighttime accumulation of HONO. This early morning HONO decreases rapidly (within 3-4 hours) to below detection after sunrise. Consistent characteristics of these mornings include cloud-free, cold (< 0°C) and calm conditions (wind speeds < 2.5 m s-1), a shallow boundary layer (< 100 m), substantial surface ozone depletion (< 10 µg m-3), and relatively large contribution of NO to total NOx (NO/NOx mass ratio ³ 0.3). Work is underway to further characterise urban HONO using 190 m measurements of NOx from the Central London BT Tower observatory and assess the reaction kinetics balancing HONO loss and formation. New knowledge of HONO gained from MAX-DOAS measurements will then be used to evaluate best understanding of urban HONO as simulated with the GEOS-Chem model.

Reactive oxidized nitrogen (NOy) in the upper troposphere (UT) influences global climate, air quality, and tropospheric oxidants, but this understanding is limited by knowledge of the relative contributions of individual NOy components in this undersampled layer. Here, we use sporadic NASA DC-8 aircraft campaign observations, after screening for plumes and stratospheric influence, to characterize UT NOy composition and to evaluate current knowledge of UT NOy as simulated by the GEOS-Chem model. The use of DC-8 data follows confirmation that these intermittent data reproduce NOy seasonality from routine commercial aircraft observations (2003–2019), supporting the use of DC-8 data to characterize UT NOy. We find that peroxyacetyl nitrate (PAN) dominates UT NOy (30 %–64 % of NOy), followed by nitrogen oxides (NOx≡ NO + NO2) (6 %–18 %), peroxynitric acid (HNO4) (6 %–13 %), and nitric acid (HNO3) (7 %–11 %). Methyl peroxy nitrate (MPN) makes an outsized contribution to NOy (14 %–24 %) over the Southeast US relative to the other regions sampled (2 %–7 %). GEOS-Chem, sampled along DC-8 flights, exhibits much weaker seasonality than the DC-8, underestimating summer and spring NOy and overestimating winter and autumn NOy. The model consistently overestimates peroxypropionyl nitrate (PPN) by ∼ 10–16 pptv or 10 %–90 % and underestimates NO2 by 6–36 pptv or 31 %–65 %, as the model is missing PPN photolysis. A model underestimate in MPN of at least ∼ 50 pptv (13-fold) over the Southeast US results from uncertainties in processes that sustain MPN production as air ages. Our findings highlight that a greater understanding of UT NOy is critically needed to determine its role in the nitrogen cycle, air pollution, climate, and the abundance of oxidants.

AbstractSatellite megaconstellation (SMC) missions are spurring rapid growth in rocket launches and anthropogenic re-entries. These events inject pollutants and carbon dioxide (CO2) in all atmospheric layers, affecting climate and stratospheric ozone. Quantification of these and other environmental impacts requires reliable inventories of emissions. We present a global, hourly, 3D, multi-year inventory of air pollutant emissions and CO2 from rocket launches and object re-entries spanning the inception and growth of SMCs (2020–2022). We use multiple reliable sources to compile information needed to build the inventory and conduct rigorous and innovative cross-checks and validations against launch livestreams and past studies. Our inventory accounts for rocket plume afterburning effects, applies object-specific ablation profiles to re-entering objects, and quantifies unablated mass of objects returning to Earth. We also identify all launches and objects associated with SMC missions, accounting for 37–41% of emissions of black carbon particles, carbon monoxide, and CO2 by 2022. The data are provided in formats for ease-of-use in atmospheric chemistry and climate models to inform regulation and space sustainability policies.

Routine observations of the vertical distribution of tropospheric nitrogen oxides (NOx equivalent to NO + NO2) are severely lacking, despite the large influence of NOx on climate, air quality, and atmospheric oxidants. Here, we derive vertical profiles of global seasonal mean tropospheric NO2 by applying the cloud-slicing method to TROPOspheric Monitoring Instrument (TROPOMI) columns of NO2 retrieved above optically thick clouds. The resultant NO2 is provided at a horizontal resolution of 1 degrees x 1 degrees for multiple years (June 2018 to May 2022), covering five layers of the troposphere: two layers in the upper troposphere (180-320 hPa and 320-450 hPa), two layers in the middle troposphere (450-600 hPa and 600-800 hPa), and the marine boundary layer (800 hPa to the Earth's surface). NO2 in the terrestrial boundary layer is obtained as the difference between TROPOMI tropospheric columns and the integrated column of cloud-sliced NO2 in all layers above the boundary layer. Cloud-sliced NO2 typically ranges from 20-60 pptv throughout the free troposphere, and spatial coverage ranges from > 60 % in the mid-troposphere to < 20 % in the upper troposphere and boundary layer. When both datasets are abundant and sampling coverage is commensurate, our product is similar (within 10-15 pptv) to NO2 data from NASA DC-8 aircraft campaigns. However, such instances are rare. We use cloud-sliced NO2 to critique current knowledge of the vertical distribution of global NO2, as simulated by the GEOS-Chem chemical transport model, which has been updated to include peroxypropionyl nitrate (PPN) and aerosol nitrate photolysis, liberating NO2 in the lower troposphere and mid-troposphere for aerosol nitrate photolysis and in the upper troposphere for PPN. Multiyear GEOS-Chem and cloud-sliced means are compared to mitigate the influence of interannual variability. We find that for cloud-sliced NO2, interannual variability is similar to 10 pptv over remote areas and similar to 25 pptv over areas influenced by lightning and surface sources. The model consistently underestimates NO2 across the remote marine troposphere by similar to 15 pptv. At the northern midlatitudes, GEOS-Chem overestimates mid-tropospheric NO2 by 20-50 pptv as NOx production per lightning flash is parameterised to be almost double that of the rest of the world. There is a critical need for in situ NO2 measurements in the tropical terrestrial troposphere to evaluate cloud-sliced NO2 there. The model and cloud-sliced NO2 discrepancies identified here need to be investigated further to ensure confident use of models to understand and interpret factors affecting the global distribution of tropospheric NOx, ozone, and other oxidants.

The influence of oil and gas end-use activities on ambient air quality is complex and understudied, particularly in regions where intensive end-use activities and large biogenic emissions of isoprene coincide. In these regions, vehicular emissions of nitrogen oxides (NOx NO + NO2) modulate the oxidative fate of isoprene, a biogenic precursor of the harmful air pollutants ozone, formaldehyde, and particulate matter (PM2.5). Here, we investigate the direct and indirect influence of the end-use emissions on ambient air quality. To do so, we use the GEOS-Chem model with focus on the eastern United States (US) in summer. Regional mean end-use NOx of 1.4 ppb suppresses isoprene secondary organic aerosol (OA) formation by just 0.02 mu g m(-3) and enhances abundance of the carcinogen formaldehyde by 0.3 ppb. Formation of other reactive oxygenated volatile organic compounds is also enhanced, contributing to end-use maximum daily mean 8-h ozone (MDA8 O-3) of 8 ppb. End-use PM2.5 is mostly (67%) anthropogenic OA, followed by 20% secondary inorganic sulfate, nitrate and ammonium and 11% black carbon. These adverse effects on eastern US summertime air quality suggest potential for severe air quality degradation in regions like the tropics with year-round biogenic emissions, growing oil and gas end-use and limited environmental regulation.

The UK is set to impose a stricter ambient annual mean fine particulate matter (PM2.5) standard than was first adopted fourteen years ago. This necessitates strengthened knowledge of the magnitude and sources that influence urban PM2.5 in UK cities to ensure compliance and improve public health. Here, we use a regional-scale chemical transport model (GEOS-Chem), validated with national ground-based observations, to quantify the influence of specific sources within and transported to the mid-sized UK city Leicester. Of the sources targeted, we find that agricultural emissions of ammonia (NH3) make the largest contribution (3.7 μg m−3 or 38 % of PM2.5) to annual mean PM2.5 in Leicester. Another important contributor is long-range transport of pollution from continental Europe accounting for 1.8 μg m−3 or 19 % of total annual mean PM2.5. City sources are a much smaller portion (0.2 μg m−3; 2 %). We also apply GEOS-Chem to the much larger cities Birmingham and London to find that agricultural emissions of NH3 have a greater influence than city sources for Birmingham (32 % agriculture, 19 % city) and London (25 % agriculture, 13 % city). The portion from continental Europe is 16 % for Birmingham and 28 % for London. Action plans aimed at national agricultural sources of NH3 and strengthened supranational agreements would be most effective at alleviating PM2.5 in most UK cities.