The nitrogen cycle has been heavily perturbed due to ever growing agriculture, industry, transport and domestic production. It is believed that we now have reached a point where the nitrogen biochemical flow has exceeded its planetary boundary for a safe operating zone. This goes together with a cascade of impacts on human health and ecosystems. To better understand and address these impacts, there is a critical need to quantify the global nitrogen cycle and monitor its perturbations on all scales, down to the urban or agricultural source.

The Nitrosat concept, which was proposed most recently in the framework of ESA’s Earth Explorer 11 call, has for overarching objective to simultaneously identify the emission contributions of NH₃ and NO₂ from farming activities, industrial complexes, transport, fires and urban areas. The specific Nitrosat science goals are to:

• Quantify the emissions of NH₃ and NO₂ on the landscape scales, to expose individual sources and characterize the temporal patterns of their emissions.
• Quantify the relative contribution of agriculture, in its diversity of sectors and practices, to the total emissions of reactive nitrogen.
• Quantify the contribution of reactive nitrogen to air pollution and its impact on human health.
• Constrain the atmospheric dispersion and surface deposition of reactive nitrogen and its impacts on ecosystems and climate; and contribute to monitoring policy progress to reduce nitrogen deposition in Natura 2000 areas in Europe.
• Reduce uncertainties in the contribution of reactive nitrogen to climate forcing, atmospheric chemistry and interactions between biogeochemical cycles.

To achieve these objectives, Nitrosat would consist of an infrared Imaging Fourier Transform Spectrometer and a Visible Imaging Pushbroom Spectrometer. These imaging spectrometers will measure NH₃ and NO₂ (respectively) at 500 m, which is the required spatial scale to differentiate, identify and quantify the main point and area sources in a single satellite overpass. Source regions would be probed from once a week to once a month to reveal the seasonal patterns. Combined with air quality models, assimilation and inverse modelling, these measurements would allow assessing the processes that are relevant for the human disruption of the nitrogen cycle and their resulting effects, in much more detail than what will be achieved with the satellite missions that are planned in the next decade. In this way, Nitrosat would enable informed evaluations of future policies on nitrogen emission control.

How to cite: Coheur, P.-F., Levelt, P., Clarisse, L., Van Damme, M., Eskes, H., Veefkind, P., Clerbaux, C., Dentener, F., Erisman, J. W., Schaap, M., Sutton, M. A., and Van Roozendael, M.: Nitrosat, a satellite mission concept for mapping reactive nitrogen at the landscape scale, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9932, https://doi.org/10.5194/egusphere-egu21-9932, 2021.

Satellite observations provide unique information on the amount and spatial distribution of tropospheric NO2. Several studies use such datasets for deriving NOx emissions. However, due to nonlinearities in the NOx chemistry (i.e., the dependency of the OH concentration and thus the NO2 lifetime on the NO2 concentration), the observed column densities of NO2 are not directly proportional to the underlying NOx emissions. Consequently, a certain reduction in NOx emissions could result in disproportionate reduction of the corresponding NO2 columns, which could be stronger or weaker depending on the chemical state (O3, NOx and VOC levels) and conditions like temperature, humidity and acitinic flux. This effect complicates the quantification of NOx emissions from satellite measurements of NO2, and e.g. biases the emission reduction as derived from the reduction of NO2 column densities observed during recent lockdowns.  

Here we quantify the nonlinearity of the NOx system for different cities as well as power plants by investigating the effect of reduced NOx emissions on days of rest, i.e. Fridays/Sundays in Muslim/Christian culture, respectively. The reduction of NOx emissions is thereby quantified based on the continuity equation by calculating the divergence of the mean NO2 flux. This method has been proven to be sensitive for localized sources, where the uncertainties due to NO2 lifetime are small (Beirle et al., Sci. Adv., 2019). This reduction in emissions is then set in relation to the corresponding reduction of NO2 columns integrated around the source, which strongly depend on the NO2 lifetime.

How to cite: Beirle, S., Dörner, S., Kumar, V., and Wagner, T.: Weekly cycle of NOx emissions as laboratory of atmospheric chemistry, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1339, https://doi.org/10.5194/egusphere-egu21-1339, 2021.

We present the results of two projects completed for the Finnish Ministry of the Environment that assessed the capability of satellites in supporting traditional in situ air quality (AQ) measurements. These projects analysed the correlation of co-located NO₂ measurements from the TROPOspheric Monitoring Instrument (TROPOMI, measuring in molec./cm²) and traditional air quality stations (measuring in µg/m³) in Finland and Europe in 2018 and 2019, and used the results to estimate annual mean ground-level NO₂ concentrations in Finland’s 14 different AQ monitoring regions.

We find that the correlation is dependent on the location of the AQ station, with city stations having a higher correlation than rural background stations. This is expected, as the variability of NO₂ levels in Finnish rural areas is usually within TROPOMI’s random measurement error. We also find that the estimated annual mean regional ground level NO₂ concentrations compare well to the in situ measurements, as the associated uncertainties provide reliable upper estimates for ground level concentrations. These estimates were used to establish that annual NO₂ concentrations were below the EU limit in two AQ monitoring regions with no active ground stations.

We also analyse TROPOMI’s and the Ozone Monitoring Instrument’s (OMI) ability to study the spatial distribution of NO₂ over Finland using gridded maps. Oversampled TROPOMI measurements are able to distinguish relatively small sources such as roads, airports and refineries, and the difference in concentrations between weekdays and weekends. TROPOMI is also able to detect emissions from different sources of NO₂ such as cities, mining sites and industrial areas. Long time series measurements from OMI show decreasing NO₂ levels over Finland between 2005 and 2018.

The studies were conducted on behalf of the Finnish Ministry of the Environment, and showcase how satellite measurements can be used to supplement traditional air quality measurements in areas with poor ground station coverage. Launched in 2017, TROPOMI is currently the highest-resolution air quality sensing satellite, and its societal uses are only beginning to be realised. Future Sentinel missions, especially the geosynchronous Sentinel-4, will further extend satellite air quality monitoring capabilities and enable continuous daytime observations in cloud-free conditions.

How to cite: Virta, H., Sundström, A.-M., Ialongo, I., and Tamminen, J.: Evaluating Satellite Capability in Supporting Traditional Air Quality Monitoring for the Finnish Ministry of the Environment, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7073, https://doi.org/10.5194/egusphere-egu21-7073, 2021.

Nitrogen oxides (NO_x  = NO+ NO₂) are harmful to human health and are precursors of other key air pollutants like ozone (O₃) and particulate matter (PM). Since the lifetime of NO_x is short and its main sources are anthropogenic emissions like fuel combustion from traffic and industry, near-surface NO_x concentrations are highly variable in space and time. To assess the impact of NO₂ on public health, maps of high spatial and temporal resolution are critical. In this study, we present hourly near-surface NO₂ concentrations at 100 m resolution for Switzerland and northern Italy that are produced using machine learning, specifically an extreme gradient-boosted tree ensemble. The model was trained with in situ observations from European Air Quality e-Reporting data repositories (Airbase). Satellite NO₂ observations from the TROPospheric Monitoring Instrument (TROPOMI) were compiled together with land use data, meteorological data and topography as covariates. Evaluation against in situ observations not used for the training shows that the dynamic maps produced in this study reproduce the spatio-temporal variation in near-surface NO₂ concentrations with high accuracy (R² = 0.59, MAE = 7.69 µg/m³). In addition, we demonstrate how public health studies can utilize such high-resolution maps for unbiased assessment of population exposure that can account for home addresses and mobility of individuals. Comparing the relative importance of the different covariates based on two different metrics, total information gain and averaged local feature importance, show a leading contribution of the TROPOMI observations despite their rather coarse resolution (3.5 km × 5.5 km) and daily update. TROPOMI NO₂ observations were particularly important for the quality of the NO₂ maps during periods of unusual NO₂ reductions (e.g., during COVID19 lockdown) and when detailed emission-related covariates like traffic density, that may not be available in other regions of the globe, were not included in the model. Since all data used in our study are publicly available, our approach can be readily extended to other regions in Europe or applied worldwide.

How to cite: Kim, M., Kuhlmann, G., Emmenegger, L., and Brunner, D.: Importance of satellite observations for high-resolution mapping of near-surface NO2 by machine learning, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4181, https://doi.org/10.5194/egusphere-egu21-4181, 2021.

Most of the anthropogenic emissions of nitrogen oxides (NOx = NO₂ + NO) are linked to burning of fossil fuels for energy production, transportation or industrial processes. However, biomass burning and in particular large wild fires in tropical and sub-tropical regions can also be large sources of nitrogen oxides at least locally. Depending on the size of the fires, particles and gases can be lifted into the free troposphere and even higher, increasing the atmospheric lifetime of NOx and enabling long range transport.

The TROPOMI instrument on board of Sentinel 5 precursor (S5p) is a nadir viewing UV/vis imaging spectrometer launched in October 2017 and operationally providing data since July 2018. One of the main products that can be retrieved from TROPOMI spectra is tropospheric and total column NO₂. Compared to previous UV/vis satellite instruments such as GOME, SCIAMACHY, GOME2 and OMI, TROPOMI has a higher spatial resolution of 3.5 x 5.5 km². This reduced foot print size enables detection and evaluation of more localised sources such as individual fires and their plumes, and better separation of different contributions to the overall NO₂ loading.

In this presentation, IUP-Bremen TROPOMI NO₂ retrievals are evaluated for biomass burning signatures during the years 2018 to 2020, three years with very different burning seasons. The amounts and spatial distributions of NO₂ from fires are compared between the years and between different fire regions, and their impact on regions downwind of the sources is investigated.

How to cite: Richter, A., Lange, K., Latsch, M., and Burrows, J. P.: Investigating fire NOx emissions with TROPOMI, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10108, https://doi.org/10.5194/egusphere-egu21-10108, 2021.

The development of horizontal drilling and hydraulic fracturing has led to a steep increase in the U.S. production of natural gas and crude oil from shale formations since the mid 2000s. Associated with this industrial activity are emissions of ground-level ozone precursors such as nitrogen oxides (NOx). Satellite data are important in this context, because surface measurements are limited or non-existent in rural regions, where most U.S. oil and gas production operations take place. Here we use TROPOMI NO₂ observations to study NOx emissions coming from oil and natural gas production sites. Applying the divergence method we quantify basin wide emissions from well pad fields and aim to push spatial and temporal resolution of this technique. The divergence was method introduced by Beirle et al. (Science Advances 2019) to quantify point source emissions. It relies on calculating the divergence of the NO₂ flux to derive NOx sources and estimating the NO₂ lifetime to quantify sinks. Our analysis will include an assessment of different methods to constrain the NO₂ lifetime, which becomes particularly important when applying this method to larger areas. Further we will compare our results with bottom-up derived emissions. Here we use the Fuel-based Oil & Gas (FOG) inventory that calculates NOx emissions based on fuel consumption. Initial results show good agreement for the Permian Basin (NM, TX) and we will expand our analysis to other U.S. basins.

How to cite: Dix, B., Francoeur, C., McDonald, B., Serrano, R., Veefkind, P., Levelt, P., and de Gouw, J.: NOx emissions from U.S. oil and gas production using TROPOMI NO2 and the divergence method, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13554, https://doi.org/10.5194/egusphere-egu21-13554, 2021.

The Athabasca Oil Sands Region (AOSR) in Alberta, Canada is one of the largest sources of extractable oil in the world. To better understand its impact, Environment and Climate Change Canada led two intensive measurement campaigns, in 2013 (August to September) and 2018 (April to July).  Each included airborne measurements in which dozens of species were measured using a variety of in situ instruments. In this presentation, a method is described in which these aircraft measurements were examined to find species that were well correlated with NO_x (the sum of NO and NO₂) in order to derive their annual emissions. The species found to have a good correlation with NO_x were black carbon, CO, HCN, HONO, CH₄, and SO₂. The annual emissions were found by applying individual species to NO_x ratios to the satellite-derived NO_x emissions from the TROPOspheric Monitoring Instrument (TROPOMI). The emissions derived in this way were compared with emissions reported to the National Pollutant Release Inventory (NPRI), as well as emissions derived from the aircraft measurements using the Top-down Emission Rate Retrieval Algorithm (TERRA). Additionally, Ozone Monitoring Instrument (OMI) NO_x emissions were used to estimate historical changes in species emissions over time, between 2005 and 2020.

How to cite: Moser, S., Griffin, D., Wren, S., McLinden, C., Liggio, J., Wheeler, M., Wentzell, J. J. B., Mittermeier, R., Hayden, K., Darlington, A., Leithead, A., and Krotkov, N.: Emissions from the Canadian oil sands:  Merging aircraft and satellite observations to derive emissions of pollutants co-emitted with NOx, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10274, https://doi.org/10.5194/egusphere-egu21-10274, 2021.

Airborne imaging DOAS and ground-based stationary and mobile DOAS measurements were conducted during the ESA funded S5P-VAL-DE-Ruhr campaign in September 2020 in the Ruhr area. The Ruhr area is located in Western Germany and is a pollution hotspot in Europe with urban character as well as large industrial emitters. The measurements are used to validate data from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) with focus on the NO₂ tropospheric vertical column product.

Seven flights were performed with the airborne imaging DOAS instrument, AirMAP, providing continuous maps of NO₂ in the layers below the aircraft. These flights cover many S5P ground pixels within an area of about 40 km side length and were accompanied by ground-based stationary measurements and three mobile car DOAS instruments. Stationary measurements were conducted by two Pandora, two zenith-sky and two MAX-DOAS instruments distributed over three target areas, partly as long-term measurements over a one-year period.

Airborne and ground-based measurements were compared to evaluate the representativeness of the measurements in time and space. With a resolution of about 100 x 30 m², the AirMAP data creates a link between the ground-based and the TROPOMI measurements with a resolution of 3.5 x 5.5 km² and is therefore well suited to validate TROPOMI's tropospheric NO₂ vertical column.

The measurements on the seven flight days show strong variability depending on the different target areas, the weekday and meteorological conditions. We found an overall low bias of the TROPOMI operational NO₂ data for all three target areas but with varying magnitude for different days. The campaign data set is compared to custom TROPOMI NO₂ products, using different auxiliary data, such as albedo or a priori vertical profiles to evaluate the influence on the TROPOMI data product. Analyzing and comparing the different data sets provides more insight into the high spatial and temporal heterogeneity in NO₂ and its impact on satellite observations and their validation.

How to cite: Lange, K., Meier, A. C., Van Roozendael, M., Wagner, T., Ruhtz, T., and Schüttemeyer, D. and the S5p-VAL-DE-Ruhr campaign team: Validation of Sentinel-5P TROPOMI tropospheric NO2 with airborne imaging, ground-based stationary, and mobile DOAS measurements from the S5P-VAL-DE-Ruhr campaign, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10637, https://doi.org/10.5194/egusphere-egu21-10637, 2021.

Sulfur dioxide (SO₂) is known as a major air pollutant harmful to human health. Furthermore, it is a precursor gas of sulfate aerosol, which exerts a direct negative radiative forcing and thus leads to climate cooling. Anthropogenic SO₂ sources are primarily associated with the combustion of sulfur-rich fossil fuels. While the operation of flue gas desulfurization devices has led to large SO₂ reductions in western Europe, a hotspot of anthropogenic SO₂ sources remains in the Balkan region as recently observed from space by the TROPOMI instrument on the Sentinel-5P satellite. Large coal-fired power plants with no or only incomplete SO₂ removal cause these high emissions.

Targeting these strong emitters, the DLR Falcon 20 aircraft was equipped with an isotopically on-line calibrated Chemical Ionization Ion Trap Mass Spectrometer (CI-ITMS) to obtain detailed in situ SO₂ observations during the METHANE-To-Go-Europe aircraft campaign in autumn 2020. These SO₂ measurements were complemented by in situ observations of greenhouse gases (CO₂, CH₄), aerosol number concentrations, and other short-lived pollutants (CO, NO, NO_y). Two flights, on November 2^nd and 7^th 2020, focused on characterizing the pollution plumes downwind of two coal-fired power plants located in Bosnia-Herzegovina (Tuzla) and Serbia (Nikola Tesla), respectively. These power plants belong to the ten strongest SO₂ emitters in Europe, and according to the World Health Organization, both countries are among the most polluted ones in Europe.

We present a detailed analysis of the two DLR Falcon flights with strongly enhanced SO₂ mixing ratios (exceeding 50 ppb), which were observed at low flight altitude (<1 km). Respective flight patterns were designed to allow for the evaluation of the TROPOMI vertical SO₂ column densities, and both flights were performed during cloud-free conditions. The airborne measurements and satellite data will also be complemented by hourly ground-based SO₂ measurements near both power plants. In addition, measurements are combined with state-of-the art model simulations from (i) the regional atmospheric chemistry climate model MECO(n); (ii) the atmospheric transport and dispersion model HYSPLIT; and (iii) the chemistry coupled Weather Research and Forecasting model WRF-Chem to improve the emission quantification of these power plants.

How to cite: Klausner, T., Huntrieser, H., Aufmhoff, H., Baumann, R., Fiehn, A., Gottschaldt, K.-D., Hedelt, P., Ilić, P., Jöckel, P., Kurilić, S. M., Loyola, D., Makroum, I., Mertens, M., Podraščanin, Z., and Roiger, A.: First airborne in situ SO2 observations of two coal-fired power plants in Serbia and Bosnia-Herzegovina: Potential for top-down emission estimate and satellite validation , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5912, https://doi.org/10.5194/egusphere-egu21-5912, 2021.

A recent method uses satellite measurements to estimate lifetimes and emissions of trace-gases from point sources (Fioletov et al., 2015). Emissions are retrieved by fitting measured vertical column densities (VCDs) of trace-gases to a three-dimensional function of the wind speed and spatial coordinates. In this study, a plume model generated “synthetic” satellite observations of prescribed emissions to examine the accuracy of the retrieved emissions. The Lagrangian transport and dispersion model FLEXPART (v10.0) modelled the plume from a point source over a multi-day simulation period at a resolution much higher than current satellite observations. The study aims to determine how various assumptions in the retrieval method and local meteorological conditions affect the accuracy and precision of emissions. These assumptions include that the use of a vertical mean of the wind profile is representative of the transport of the plume’s vertical column. In the retrieval method, the VCDs’ pixel locations are rotated around the source based on wind direction so that all plumes have a common wind direction. Retrievals using a vertical mean wind for rotation will be compared to retrievals using VCDs determined by rotating each altitude of the vertical profile of trace-gas using the respective wind-direction. The impact of local meteorological factors on the two approaches will be presented, including atmospheric mixing, vertical wind shear, and boundary layer height. The study aims to suggest which altitude(s) of the vertical profile of winds results in the most accurate retrievals given the local meteorological conditions. The study will also examine the impact on retrieval accuracy due to satellite resolution, trace-gas lifetime, plume source altitude, number of overpasses, and random and systematic errors. Sensitivity studies repeated using a second, “line-density”, retrieval method will also be presented (Adams et al., 2019; Goldberg et al., 2019).

How to cite: Davis, Z., Griffin, D., Jia, Y., Tegtmeier, S., Loria, M., and McLinden, C. A.: Examining the accuracy of satellite retrievals of trace-gas emissions and lifetimes using high-resolution plume modelling., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9897, https://doi.org/10.5194/egusphere-egu21-9897, 2021.

Hydrogen cyanide (HCN) is one of the most abundant cyanides present in the global atmosphere, and is a tracer of biomass burning, especially for peatland fires. The HCN lifetime is 2–5 months in the troposphere but several years in the stratosphere. Understanding the physical and chemical mechanisms of HCN variability is important due to its non-negligible role in the nitrogen cycle. The main source of tropospheric HCN is biomass burning with minor contributions from industry and transport. The main loss mechanism of atmospheric HCN is the reaction with the hydroxyl radical (OH). Ocean uptake is also important, while in the stratosphere oxidation by reaction with O(¹D) needs to be considered.

HCN variability can be investigated using chemical model simulations, such as three-dimensional (3-D) chemical transport models (CTMs). Here we use an adapted version of the TOMCAT 3-D CTM at a 1.2°x1.2° spatial resolution from the surface to ~60 km for 12 idealised HCN tracers which quantify the main loss mechanisms of HCN, including ocean uptake, atmospheric oxidation reactions and their combinations. The TOMCAT output of the HCN distribution in the period 2004-2020 has been compared with HCN profiles measured by the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) over an altitude grid from 6 to 42 km. HCN model data have also been compared with ground-based measurements of HCN columns from NDACC FTIR stations and with in-situ volume mixing ratios (VMRs) from NOAA ground-based measurement sites.

The model outputs for the HCN tracer with full treatment of the loss processes generally agree well with ACE-FTS measurements, as long as we use recent laboratory values for the atmospheric loss reactions. Diagnosis of the individual loss terms shows that decay of the HCN profile in the upper stratosphere is due mainly to the O(¹D) sink. In order to test the magnitude of the tropospheric OH sink and the magnitude of the ocean sink, we also show the comparisons of the model tracers with surface-based observations. The implications of our results for understanding HCN and its variability are then discussed.

How to cite: Bruno, A. G., Harrison, J. J., Moore, D. P., Chipperfield, M. P., and Pope, R. J.: Investigation of atmospheric hydrogen cyanide: a modelling perspective, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8865, https://doi.org/10.5194/egusphere-egu21-8865, 2021.

Satellite observations have great potential for monitoring emissions and concentrations of atmospheric species. This is especially true for atmospheric ammonia (NH₃), which varies greatly in space and time and is difficult to measure in-situ due to its sticky nature.  NH₃ measurements are important as NH₃ is a significant contributor to the production of secondary inorganic aerosols (PM2.5) and can add excessive reactive nitrogen to the environment. In this study we demonstrate how satellite remote sensing observations can be used to monitor changes in NH₃ concentrations by evaluating timeseries of Cross-Track Infrared Sounder (CrIS) satellite data with in-situ NH₃ concentrations and meteorological parameters (i.e. soil temperature and soil moisture). We provide an example demonstrating the capability to monitor the annual springtime increase in atmospheric NH₃ concentrations in Netherlands, which is mainly associated with farming practices (e.g. manure spreading on fields in the springtime). We then combine these satellite observations of NH₃ with meteorological conditions, with the goal of developing a model to predict the timing of ammonia emissions based on past agricultural practices in the area (e.g. artificial fertilizer and manure spreading).    

How to cite: Bashalkhanova, O., Shephard, M., Dammers, E., Kovachik, A., Wichink Kruit, R., and Cady-Pereira, K.: Application of Cross-Track Infrared Sounder (CrIS) Instrument for Remote Detection of Agricultural NH3 Emissions over Netherlands, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5581, https://doi.org/10.5194/egusphere-egu21-5581, 2021.

While ammonia (NH3) at its current levels is known to be a hazard to environmental and human health, the atmospheric budget is still quite uncertain. This can largely be attributed to the short lifetime of ammonia in combination with an overall lack of (dense) in-situ measurement networks. The capability to observe ammonia distributions with satellites has opened new ways to study the atmospheric ammonia budget. Previous studies have demonstrated the capability of current ammonia satellite sensors to resolve emissions from point like sources, biomass burning, and constraining emission sources at a regional level with methods involving the use of air quality models.

In this study, we present the first spatially resolved ammonia emission estimates across the globe using a consistent methodology based solely on ammonia satellite observations from the Cross-track Infrared Sounder (CrIS) instrument and ECMWF ERA5 wind fields. The concept was evaluated for North Western Europe and demonstrated the ability to constrain annual emissions at county- to provincial-levels with most deviations within the bounds found in the error analysis. Furthermore, we show that for some regions the spatial patterns found in the satellite observations are consistent while others do not match the current inventories. Finally, the results indicate that the absolute emission levels tend to be underestimated for parts of the globe.

How to cite: Dammers, E., Shephard, M., White, E., Griffin, D., Chow, E., Fioletov, V., Kharol, S., Cady-Pereira, K., van der Graaf, S., Tokaya, J., Schaap, M., and McLinden, C.: Satellite based county- to provincial-level ammonia emissions estimates, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7729, https://doi.org/10.5194/egusphere-egu21-7729, 2021.

Ammonia plays an important role for air, soil and water quality, as well as aerosol formation and plant growth. Accurate estimates of emission rates of ammonia from wildfires are crucial to understand the impact on human health and ecosystems. However, ground-based measurements of ammonia are sporadic. Satellite measurements can help address this monitoring gap. The Cross-track Infrared Sounder (CrIS) product provides a unique tool because some information on the vertical distribution of ammonia is derived from the profile retrievals in addition to vertical column densities (VCDs). Emission rates are retrieved by fitting measured vertical column densities (VCDs) to a three-dimensional function of the wind speed and spatial coordinates. This method requires VCDs to be rotated given the wind-direction to remove wind-direction as a fitting variable. The vertical information given by CrIS provides the potential for more accurate emission estimates as wind-direction and -speed at each profile level can be taken into account. The application of the vertical profile of wind also allows more accurate estimates of plume width, which can vary significantly in the traditional VCD rotation depending on the altitudes of wind used for the rotation. This approach was developed and validated using synthetic satellite measurements of plumes simulated by the FLEXPART (v10.0) model to better understand the impact of variability in the vertical profile of the wind. The methodology was then applied using CrIS satellite observations to estimate forest fire emissions of NH3. Preliminary results of this study will be presented.

How to cite: Eckert, E., Davis, Z. Y. W., Shephard, M. W., McLinden, C. A., Griffin, D., Tegtmeier, S., Jia, Y., and Cady-Pereira, K. E.: Estimating wildfire emissions of ammonia using Cross-track Infrared Sounder (CrIS) profile information, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12102, https://doi.org/10.5194/egusphere-egu21-12102, 2021.

For measurements from any instrument there is a minimum detection limit below which the sensor cannot measure (i.e., non-detects). Measurements of trace gases from satellite instruments can also suffer from a significant number of non-detects, especially for species with very low atmospheric concentrations  and that have a very weak or absent signals (signal-to-noise<1) in the spectral region used to detect the species (e.g., ammonia).  For ammonia, these non-signal conditions generally occur when thick clouds obscure the ammonia signal, or atmospheric conditions generates too weak of a radiometric signal to detect (e.g., very low concentrations). Presented is a robust approach to explicitly identify and account for cloud-free satellite observations that are below the detection limit of the sensor (which occur principally in  non-source regions) for the Cross-Track Infrared Sounder (CrIS) Fast Physical Retrieval (CFPR) ammonia (NH₃) product. This approach uses the newly developed CrIS Ammonia Cloud Detection Algorithm (CACDA) to compute a cloud flag based on the CrIS IMG (CIMG) product . The CIMG product uses coincident Visible Infrared Imaging Radiometer Suite (VIIRS) brightness temperatures and cloud fractions mapped onto CrIS Field of Views (FOV). This cloud flag is used to separate CrIS FOVs without signal due to clouds from FOVs that are below the detection limit due to the atmospheric state (referred to as non-detects).  Survival data is generated from in-situ surface observations from non-emission source regions to produce ammonia concentration values under CrIS non-detect conditions. Accounting for these non-detects can be significant in reducing bias of averaged values (i.e., Level 3 products) in regions or conditions with low concentration amounts (e.g. wintertime, non-agriculture regions, etc.), with little impact on concentrations in emission regions. This presentation will provide examples and evaluations of the CACDA and the inclusion of non-detects in the CFPR generated ammonia product. This will include comparisons of annual and seasonal averages of surface level ammonia concentrations with and without survival data to demonstrate the reduction in bias.

How to cite: White, E., Shephard, M., Cady-Periera, K., Kharol, S., Dammers, E., Chow, E., Tobin, D., Quinn, G., O'Brien, J., and Bash, J.: Accounting for Non-detects in Satellite Retrievals: Application Using CrIS Ammonia Observations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9109, https://doi.org/10.5194/egusphere-egu21-9109, 2021.

The Syrian civil war started in 2011, with dramatic social, political, economic, and environmental consequences over the whole area of Syria and nearby countries. Agriculture, in particular, suffered massively. Several studies used satellite-retrieved data and imagery to examine the spatio-temporal changes in the region, due to the civil war. For instance, open-source satellite imagery could show the damage in urban areas, and provide an estimate of the number of people affected by the crisis.

In this study, we investigate the impacts of the Syrian civil war on atmospheric ammonia (NH₃) emitted from industrial and agricultural activities during the 2008-2019 period. Our analyses are based on the NH₃ measurements from the IASI instruments onboard the Metop satellites. Firstly, land-use changes and a decrease in agricultural emissions are explored over the country. We also investigate the changes in atmospheric NH₃ over an ammonia plant, which activities have been suspended due to several conflict-related events. We show that the NH₃ columns retrieved from IASI are directly affected by the war, and those periods of intense conflict and siege are reflected in lower NH₃ concentrations, which are not driven by meteorology. The interpretation of the identified changes in atmospheric NH₃ is supported by the analyses of NO₂ columns from GOME-2 as well as satellite imagery and land cover data. The latter is used to highlight the change in croplands’ area over the years, and the satellite images are used to show the activity of the ammonia plant.

How to cite: Abeed, R., Safieddine, S., Clarisse, L., Van Damme, M., Coheur, P.-F., and Clerbaux, C.: The effects of the Syrian civil war on atmospheric NH3 as seen from IASI, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12171, https://doi.org/10.5194/egusphere-egu21-12171, 2021.

N₂O is the third anthropogenic greenhouse gas, after CO₂ and CH₄. N₂O is about a 1000 times less abundant than CO₂, but is a much stronger greenhouse gas (265 times stronger, for the same amount of gas). N₂O has an atmospheric lifetime of about 120 years, and resides mostly in the troposphere and lower stratosphere. N₂O is also the principal source of nitrogen in the stratosphere, participating in the ozone destruction.

Although N₂O emissions are mostly natural as a part of biogeochemical cycles, a significant part of the emissions is anthropogenic, linked to agriculture, industry and transport. The N₂O concentrations are continuously increasing since the industrial era. Because its greenhouse potential is very high, identifying and regulating the anthropogenic N₂O emissions is crucial for climate change mitigation.

The Infrared Atmospheric Sounding Interferometer (IASI) is a nadir viewing satellite instrument, measuring the outgoing radiation in the Infrared range. It flies on board the Metop satellite series, on a polar sun-synchronous orbit, and has been providing data since 2006 with a succession of 3 instruments. The follow-up instrument, IASI-NG (new generation), is already in preparation and will not only ensure data continuity for at least an additional decade, but it will also provide improved performances.

In this work, we present N₂O profiles with a limited resolution of maximum 2 degrees of freedom, and the corresponding integrated columns, retrieved from IASI measurements using a new retrieval strategy. We assess the quality of our data through comparisons with Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) measurements. We will discuss the main “trouble makers” in this retrieval, i.e. the non-retrieved parameters that have the highest impact on the resulting N₂O data quality. Finally, we will discuss a preliminary trend assessment derived from the retrieved time series covering 13-years.

How to cite: Vandenbussche, S., Langerock, B., and De Mazière, M. and the NDACC FTIR team and TCCON Partners: N2O retrievals from IASI: a new strategy, its validation and a preliminary 13-years trend assessment, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10153, https://doi.org/10.5194/egusphere-egu21-10153, 2021.

Formaldehyde (HCHO) is an operational L2 product of the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor platform (S5P) (De Smedt et al., 2018).

International shipping is a significant source of pollutants including CO2, nitrogen oxides (NOx), sulfur oxides (SOx), volatile organic compounds, particulate matter, and black carbon. Shipping lanes are well known to be detected in NO₂ satellite observations (e.g., Beirle et al., 2004; Richter et al., 2004, 2011; Vinken et al 2014, Georgoulias et al., 2019). SO2 signal from ships has also been reported in OMI SO2 observations (Theys et al. 2014). However, so far only one study has reported the detection of an HCHO signal from ships using GOME-1 observations (Marbach et al. 2009). In a recent paper, it has been shown that the TROPOMI measurements allow for the detection of NO₂ pollution plumes from individual ships (Georgoulias et al., 2020).

In this work, we investigate the detection of a HCHO signal over shipping lanes in the Indian Ocean. When averaging several months of TROPOMI HCHO observations, at least two shipping lanes are clearly visible in the Indian Ocean. They are located over known shipping corridors from India and from Africa. We estimate the intensity of the HCHO columns along those tracks as a function of the season. We compare their location and relative intensity with TROPOMI NO2 observations. The possible impact of the a priori profiles is considered, as well as the impact of cloud filtering. Wind fields, which have been recently added in the HCHO L2 files, are used in order to study the intensity of the signal as a function of wind speeds. The HCHO background transported from continental sources is removed using a first-order estimation. The OMI QA4ECV HCHO and NO2 datasets between 2005 and 2020 are included in the analysis using 5 years averaged data, in order to study possible changes in the respective line intensities and locations. The detection of such a small signal is an illustration of the improved detection limit of HCHO columns with TROPOMI measurements.

How to cite: De Smedt, I., Theys, N., Yu, H., Vlietinck, J., Lerot, C., Romahn, F., Cheng, Z., Chan, K. L., Hedelt, P., Loyola, D., and Van Roozendael, M.: Identification of a HCHO signal in S5P/TROPOMI data over shipping lanes in the Indian Ocean, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16453, https://doi.org/10.5194/egusphere-egu21-16453, 2021.

How to cite: Sundström, A.-M., Majamäki, E., Jalkanen, J.-P., Ialongo, I., and Tamminen, J.: Detecting single ship plumes from TROPOMI NO2 data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14623, https://doi.org/10.5194/egusphere-egu21-14623, 2021.

The TROPOMI and OMI satellite sensors provide an exciting perspective on the sources, dispersion, and fate of air pollution emitted by the international shipping industry. Recently it proved possible to detect plumes of NO₂ from individual ships with high-resolution measurements from TROPOMI, especially when observed under sun-glint conditions.  In principle, this allows the quantification of NO_x emissions from ocean-going ships, but an outstanding scientific question is under which atmospheric conditions ship plumes are best detected. The effects of viewing geometries, local wind speed, partial cloud cover, emission strength as well as chemical boundary conditions on NO₂ plume detectability are still a challenge to understand.

Here we investigate TROPOMI’s ability to detect NO₂ pollution from the international shipping sector under different measurement conditions, and we compare it to that of its predecessor OMI. Uncertainties in cloud properties – and thereby in the resulting Air Mass Factors – are one of the leading sources of uncertainty in the TROPOMI NO₂ retrieval. These become increasingly important when investigating small NO₂ enhancements close to the Earth’s surface in partly cloudy scenes, i.e. thos from shipping.

We examine for the first time the new TROPOMI-FRESCO+DDS algorithm which uses a wider spectral window for the O₂-A band than the original FRESCO+, increasing its sensitivity to low clouds. We cross-evaluate the resulting cloud properties against the operational TROPOMI-FRESCO+, VIIRS and OMCLDO2 algorithms on a pixel-by-pixel basis. This comparison reveals it is likely that FRESCO+ cloud heights are biased high by around 100hPa, leading to an overestimated AMF and thus low biased NO₂ columns for (partially) cloudy scenes. We explore the AMF correction based on FRESCO+DDS to improve the operational TROPOMI NO₂ retrieval for ship plume detection and discuss implications for the detection of COVID-19 associated reductions in shipping, and hence pollution levels over European seas.

This work is funded by the Netherlands Human Environment and Transport Inspectorate, the Dutch ministry of Infrastructure and Water Management, and the SCIPPER project which receives funding from the European Union’s Horizon 2020 research and innovation program under grant agreement Nr.814893.

How to cite: Rieß, C., Boersma, F., van Vliet, J., Eskes, H., van Geffen, J., Stammes, P., Boot, W., de Laat, J., Peters, W., and Veefkind, P.: Improving cloud retrievals for accurate detection of ship NO2 plumes from S5P-TROPOMI, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9662, https://doi.org/10.5194/egusphere-egu21-9662, 2021.

Atmospheric Carbonyl Sulfide (COS) is a useful tracer for assessing gross primary production (GPP). COS is also an important contributor to stratospheric sulfate aerosols (SSA) which cool the climate. However, the global budget of COS remains unresolved due to insufficient observations. We implemented a linear inversion framework within the TM5-4DVAR global chemistry transport model constrained by NOAA surface network to investigate the sources and sinks of COS (Ma et al., 2020). To close the gap between sources and sinks, we focused on inversions that optimize what is thought to be a “missing” source amounting to 432 GgS a^-1. We found that a tropical missing source was likely, which could either be an indication of an underestimated ocean source, or overestimated biosphere uptake. Additionally, we found the biosphere uptake to be underestimated at higher latitudes of the Northern Hemisphere. Inversions were validated with HIPPO aircraft data, NOAA airborne profiles and satellite data (MIPAS, TES and ACE-FTS), indicating an underestimation of COS in troposphere. We further implemented a first-order dependency of COS biosphere flux on COS mole fractions in the atmosphere boundary layer, which renders the inversions nonlinear. As expected based on the known drawdown of COS by biosphere uptake, it is found that the dependence of the biosphere flux on COS mole fractions reduced the budget gap by 137 GgS a^-1. We further optimized COS fluxes separately over ocean and land, accounting for the first-order dependency of biosphere uptake on COS mole fractions. These results suggest that the missing COS sources may originate from the ocean (207 GgS a^-1), despite recent work in which the ocean is explicitly studied suggesting otherwise.  Understanding this apparent discrepancy will be an important topic to elucidate. In the future, we plan to take the advantage of available satellite data products to better constrain the COS flux budget in the tropics. COS products from the MIPAS and TES satellites are good candidates for data assimilation in the current model.

How to cite: Ma, J., Kooijmans, L. M. J., Cho, A., Montzka, S. A., Glatthor, N., Worden, J. R., Kuai, L., Atlas, E. L., and Krol, M. C.: Inverse modelling of Carbonyl Sulfide (COS): towards nonlinear model and satellite data assimilation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8972, https://doi.org/10.5194/egusphere-egu21-8972, 2021.

Halogen radicals can drastically alter the atmospheric chemistry. In the polar regions, this is made evident by the ozone desctruction in the stratosphere (ozone hole) but also by localized destruction of boundary layer ozone during polar springs. These recurrent episodes of catalytic ozone depletion are caused by enhanced concentrations of reactive bromine compounds. The proposed mechanism by which these are released into the atmosphere is called bromine explosion - reactive bromine is formed autocatalytically from the condensed phase.

The spatial resolution of S-5P/TROPOMI of up to 3,5 km x 5.5 km² allows improved localization and a finer specification of these events compared to previous satellite measurements. Together with the better than daily coverage over the polar regions, this allows investigations of the spatiotemporal variability of enhanced BrO levels and their relation to different possible bromine sources and release mechanisms.

Here, we present tropospheric BrO column densities retrieved from TROPOMI measurements using Differential Optical Absorption Spectroscopy (DOAS). We developed an algorithm capable of separating tropospheric and stratospheric partial columns without further external (model) input only relying on measured NO₂and O₃, by utilizing a modified version of a k-means clustering and other methods from statistical data analysis.

Selected events from the polar springs in 2019 and 2020 are further analyzed and discussed with regards to sea ice coverage and meteorological influences.

How to cite: Schöne, M., Sihler, H., Warnach, S., Borger, C., Beirle, S., Wagner, T., and Platt, U.: Tropospheric polar BrO derived from S5-P/TROPOMI, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6791, https://doi.org/10.5194/egusphere-egu21-6791, 2021.

Iodine compounds are emitted from the ocean and ice covered areas through organic and inorganic pathways involving macroalgae and microalgae as well as inorganic surface processes and volcanic eruptions. Iodine monoxide (IO) molecules are produced after photolysis of precursors and reaction with ozone. IO is thus an indicator of active iodine chemistry, and impacts on ozone levels, the NO/NO₂ ratio and particle formation. Rapid changes in Polar sea ice coverage and conditions may affect iodine levels in Polar Regions with respective consequences for tropospheric composition in the Arctic and Antarctic.

Remote sensing of IO faces the challenge that IO column densities are fairly small with a maximum absorption optical depth on the order of a few times 10^-4, which is close to the detection limit of satellite instruments. IO column densities are retrieved from several satellite sensors including SCIAMACHY (2002 to 2012), GOME-2 (since 2006) and TROPOMI (since 2017) by using Differential Optical Absorption Spectroscopy. Previous studies have shown slightly enhanced IO column densities above the Antarctic Region and in a strong volcanic plume, while IO column densities in the Arctic remain mostly below the detection limit. These areas are in the focus of iodine measurements from space. Retrieval quality and resulting IO column densities are investigated and compared between the different sensors with a focus on the recent instrument TROPOMI.

The small IO absorption signal complicates the identification of optimal retrieval settings, such as the choice of an adequate wavelength window. Aspects for quality control are discussed. In addition to the immediate retrieval RMS, also the IO standard deviation in (reference) areas with expected low IO absorption, consistency checks with other retrieval parameters as well as plausibility of IO column density results are considered. Finally, the idea of an ensemble retrieval strategy is discussed, which is based on the fact that for small trace gas quantities, the retrieval result depends unfavourably on the fit settings. After selection of reasonable quality criteria, the remaining fit parameter sets are all used for the retrieval of IO. The selected ensemble of parameter sets yields a result for IO as well as uncertainty estimates induced by the choice of fit settings. Due to computational effort, application of this strategy is restricted to case studies.

How to cite: Schoenhardt, A., Richter, A., Blechschmidt, A.-M., Bracher, A., and Burrows, J. P.: Analysing the retrieval quality and column densities of iodine monoxide from multiple satellite sensors, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13719, https://doi.org/10.5194/egusphere-egu21-13719, 2021.

A novel algorithm for total column water vapor (TCWV) retrieval, which uses a combination of satellite-based measurements in the near-infrared (NIR) and infrared (IR) spectrum, is presented. The algorithm is built with a modular approach so that it can be used for a wide array of passive sensors. It is based on a fast forward model for NIR and IR bands at the water vapor absorption peaks in use on current and future instruments. 

An Ocean Land & Colour Imager (OLCI) TCWV retrieval for land surfaces has been developed, building on earlier work done for MERIS and MODIS, including extensive validation exercises using well-established ground-based TCWV observations as reference. The retrieval is extended to a synergy with IR measurements at 11 and 12um from the Sea and Land Surface Temperature Radiometer (SLSTR), also onboard the Sentinel-3 satellites. This allows more accurate TCWV retrievals over dark water surfaces. 

Moreover, support is planned for the polar-orbiting meteorological satellite instruments such as METimage on Metop - Second Generation (Metop-SG) and geostationary instruments such as the Flexible Combined Imager (FCI) onboard Meteosat Third Generation (MTG). 

Application examples of the newly derived TCWV observations include studying the potential of assimilating OLCI’s high spatial resolution TCWV fields in Numerical Weather Prediction (NWP) as well as detection of convective initiation in TCWV fields before the onset of clouds and precipitation within the German project RealPEP.

How to cite: El Kassar, J. R., Carbajal Henken, C., Preusker, R., and Fischer, J.: Multi-Sensor Retrieval Algorithm for Daytime Total Column Water Vapor from Passive Imagers, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12776, https://doi.org/10.5194/egusphere-egu21-12776, 2021.

The lockdown measures taken to combat the COVID-19 virus implemented in a majority of countries worldwide have had a dramatic impact on the anthropogenic pollutant emissions, related to a drastic reduction of road and air traffic, as well as part of the industrial activities. In our contribution we investigate the presence of COVID-19-related imprints in air quality as observed from space, focussing on worldwide industrial/highly populated regions where strong lockdown measures have been taken (e.g., China, Europe, US). This is done by exploiting the observations of the TROPOMI instrument onboard the Copernicus Sentinel-5P platform, for a number of trace gases which are indicators of anthropogenic activity. We make use of the TROPOMI operational product portfolio, which includes tropospheric NO2, CO, SO2, and HCHO. These operational data products are complemented by other scientific products such as the BIRA-IASB glyoxal (CHOCHO) retrievals and a new SO2 retrieval algorithm called COBRA. The reductions in NO2 observed by TROPOMI have been documented already in the recent literature for several regions and countries worldwide. In our contribution we focus on the combined observations of multiple trace gases, which provides not only information about how much primary (NOx) emissions decreased, but also gives region-to-region insights and constraints on the overall changes in atmospheric composition as a result of these lockdowns.

How to cite: Eskes, H., Levelt, P., Stein, D., DeSmedt, I., Aben, I., van Roozendael, M., Stavrakou, J., Bauwens, M., Lerot, C., Veefkind, P., Borsdorff, T., Verhoelst, T., Loyola, D., and Romahn, F.: Air Quality Impacts of COVID-19 Lockdown Measures using high-resolution observations of multiple trace gases from S5P/TROPOMI, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13216, https://doi.org/10.5194/egusphere-egu21-13216, 2021.

The worldwide spread of Covid-19 pandemic caused a dramatic cutback of human activities and triggered a large-scale atmospheric composition experiment. This unfortunate situation provides the opportunity to investigate the response of atmospheric composition to the shutdown measures. Our focus will be on China, where the pandemic emerged in January 2020, and thence strict lockdowns were enforced. Substantial, large-scale decreases in pollutants levels over China and subsequent recovery were revealed by spaceborne observations from TROPOMI instrument on board Sentinel-5 Precursor, as well as by in situ measurements. Most published work on this topic relied on observed changes in column abundances of nitrogen dioxide (NO₂), a predominantly anthropogenic compound and an important precursor for ozone production and secondary aerosol formation. Our work adds to this picture by studing the evolution of two other satellite-derived compounds, formaldehyde (HCHO) and peroxyacylnitrate (PAN), observed by TROPOMI and IASI, respectively. HCHO is an intermediate product in the chemical processing of volatile organic compounds (VOCs) of anthropogenic and natural origin. PAN is formed in the oxidation of anthropogenic and biogenic VOCs, and constitute the principal tropospheric NO_x reservoir, enabling the transport and release of NO_x away from the sources. Chemistry-transport simulations of PAN are challenging due to large uncertainties in formation mechanisms and precursor emissions. We will evaluate and analyze the observed variability of NO₂, HCHO, and PAN columns using model simulations with the MAGRITTE v1.1 regional CTM run at 0.5^ox0.5^o resolution over China for 2019 and 2020. The model uses updated anthropogenic emissions from the CONFORM dataset, which takes into account the reductions during the shutdowns based on traffic and other economic activity data. 

How to cite: Stavrakou, T., Müller, J.-F., Bauwens, M., Doumbia, T., Elguindi, N., Darras, S., Claire Granier, C. G., Yiming Liu, Y. L., Shi, X., Bouarar, I., Brasseur, G., Wang, T., Eskes, H., De Smedt, I., Clarisse, L., Coheur, P. F., and Franco, B.: Covid-19-related air composition changes over China based on TROPOMI and IASI observations, in situ data and model simulations , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12942, https://doi.org/10.5194/egusphere-egu21-12942, 2021.

During the COVID-19 pandemic outbreak at the beginning of 2020, many Chinese urban agglomerations experienced noticeable air quality improvement. For example, recent analysis of surface measurements suggested that the concentration of NO₂ decreased by on average 30% during the pandemic lockdown period in China in 2020 compared to 2019, although how much of this reduction is due to the pandemic or other factors (such as weather variation) is uncertain. We apply TROPOMI (Tropospheric Ozone Monitoring Instrument) NO₂ Level 2 data (converted to Level 3 data) to analyzing the spatial and temporal evolution of NO₂ in major Chinese city clusters including Jing-Jin-Ji and Yantze River Delta. These observational results are compared with monitoring station data, as well as predicted results from machine learning techniques and a chemical transport model (SILAM), taking meteorological factors into account. We then evaluate the impact of COVID-19 and lockdown measures on the concentration of NO₂ comprehensively. For example, initial results indicate the NO₂ concentration in Shanghai area decreased by about 37% during late January to early March in 2020, comparing the prediction by a machine learning technique (random forest) and the observed surface data, partly due to the pandemic control measures. It is expected the COVID-19 pandemic would be a long-term challenge accompanying the human development. Based on these findings, relevant mechanism of NO₂ pollution and control, affected by the pandemic and periodic lockdown measures in China, will be discussed.

How to cite: Jia, Z., Yuan, Y., Pan, Q., Jin, J., and Gao, S.: Evaluating the influence of COVID-19 pandemic on NO2 concentration variation in selected regions in China using TROPOMI data, surface measurements and modeling approaches, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11969, https://doi.org/10.5194/egusphere-egu21-11969, 2021.

Ozone in the troposphere has mainly two sources, the first one is stratospheric intrusion the second one is chemical reactions following the emissions of primary pollutions such as NOx and VOCS.

We combine TROPOMI total ozone columns with Microwave Limb Sounding ozone profiles assimilated to BASCOE to retrieve tropospheric ozone columns.

Based on a first analysis we observe a decrease of tropospheric ozone during April and May 2020. The lockdown as measure against the Corona pandemic also caused an economic shutdown, and thereby a reduction of primary pollutants mainly NOx. Within the cities centres the lack of NOx caused an increase in tropospheric ozone, due to non linear effects in the ozone NOx chemistry. Outside the cities however a decrease might be expected. Thereby the tropospheric ozone reduction in April May might be caused by the lockdown due to the COVID-19.

However the natural variabilty is high caused by metrological conditions. To redcue the influnece of indiviual metrological situation the timeseries is expanded to the past by using additional sensors like GOME-2 and OMI, combined with the BASCOE reanalysis data set BRAM. The tropospheric columns are haromized using the same time and latitude depended bias added as for harmonizing the total columns. Therby we generated a typical anual mean data set, where the exceptional year of 2020 can be compared to.

How to cite: Heue, K.-P., Lerot, C., Romahn, F., Chabrillat, S., Christophe, Y., Errera, Q., Coldewey-Egbers, M., and Loyola, D.: Tropospheric ozone based on S5P-BASCOE and extension to the past based on OMI and GOME-2 observation., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14237, https://doi.org/10.5194/egusphere-egu21-14237, 2021.

How to cite: Pimlott, M., Pope, R., Chipperfield, M., Kerridge, B., Siddans, R., and Latter, B.: Investigation of European tropospheric ozone trends using multiple satellite records, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8264, https://doi.org/10.5194/egusphere-egu21-8264, 2021.

The TROPOspheric Monitoring Instrument (TROPOMI), on board the Sentinel 5 precursor (S5p) satellite, was launched in October 2017. The TROPOMI instrument has high spatial resolution and daily coverage of the Earth. About two years of level 2 data (versions up to 2.1.4) of OFFL GODFIT ozone and OCRA/ROCINN CRB (fraction and height) are available. Using these datasets, we derive tropical tropospheric ozone using the convective CCD cloud differential method for tropical tropospheric column ozone (TTCO) [DU] and the CSL cloud slicing method for upper tropospheric ozone volume mixing ratios (TUTO) [ppbv].

The CCD algorithm was optimized for TROPOMI with respect to the reference sector Above Cloud Column Ozone field (ACCO) by adjusting it in time and latitude space in order to reduce data gaps in the daily ACCO vectors. Daily total ozone gridded data with a latitude/longitude resolution of 0.5°/1° are used to minimize the error from stratospheric ozone changes.

The CSL algorithm (CHOVA: Cloud Height induced Ozone Variation Analysis) was developed to fully exploit the S5p instruments characteristics. The data is spatially sampled to a 2° latitude/longitude grid. A temporal sampling of cloud/ozone data is not necessary anymore due to the high amount of S5p measurements. Comparisons with NASA/GSFC SHADOZ ozone sondes show good agreement (low bias and high dispersion) for both methods taking into account the principal differences between sonde point measurements and satellite sampled mean value. The CHOVA results from the pacific sector are now used as input for the CCD method to adjust the height dependent columns to a fixed pressure level.    

The work on TROPOMI/S5P geophysical products is funded by ESA and national contributions from the Netherlands, Germany, Belgium, and Finland.

How to cite: Eichmann, K.-U., Weber, M., and Burrows, J. P.: Tropical Tropospheric Ozone from Sentinel-5P TROPOMI data: Synergy of CCD/CSL retrievals, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13343, https://doi.org/10.5194/egusphere-egu21-13343, 2021.

Ecosystems and human health are severely harmed by elevated concentrations of tropospheric ozone, in the short and the long term. Monitoring ozone at all relevant spatial and temporal scales simultaneously is a challenge for a global observing system due to the large variability of ozone levels in the troposphere. Space-based sensors provide near-global coverage at the synoptic scale, but their accuracy is limited since the large stratospheric O3 column shields the view on the relatively small tropospheric ozone concentrations. In contrast, in-situ soundings by balloons are sparse, but these are more accurate and at a high vertical resolution. As a result, the geophysical information that can be inferred from tropospheric ozone data records differs.

We present a comprehensive comparison of the spatial and temporal patterns in tropical tropospheric ozone column observations by nadir-viewing satellite sensors (Sentinel-5 Precursor/TROPOMI, EOS-Aura/OMI and Metop-B/GOME-2) and ozonesondes for the period 2018-2020. We discuss how each data record perceives well-known structures and cycles such as the zonal wave-one, the seasonal cycle and biomass burning periods. Imprints of (sensor-dependent) sampling characteristics are generally less relevant on large scales. However, these can dominate the uncertainty budget when satellite data are used at their finest sampling resolution. Nonetheless, we recognise the signature of the Madden-Julian Oscillation and hints of Kelvin wave activity.

How to cite: Hubert, D., Heue, K.-P., Lambert, J.-C., Verhoelst, T., Keppens, A., Compernolle, S., Dehn, A., Kollonige, D. E., Lerot, C., Loyola, D., Romahn, F., Thompson, A. M., Veefkind, P., and Zehner, C. and the SHADOZ ozonesonde station PIs and staff: Geophysical patterns in tropical tropospheric ozone by TROPOMI, OMI, GOME-2B and ozonesonde, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11687, https://doi.org/10.5194/egusphere-egu21-11687, 2021.

The Ozone Mapping and Profiler Suite, on board of Suomi National Polar-orbiting Partnership (OMPS/NPP) since 2012, features a combination of limb and nadir sensors. This feature allows the use of the limb-nadir matching technique to retrieve tropospheric ozone columns on a global scale, with a single satellite. Using a single instrument avoids additional calibrations and interpolations of the input data for the retrieval. The limb-nadir matching method subtracts the stratospheric ozone column from limb observations (OMPS-LP) from the nadir derived total ozone column (OMPS-NM), using the tropopause height to define the troposphere. Most of the other satellite's retrievals methods are limited either geographically or to a certain altitude range, as e.g. the Convective Cloud Differential method (CCD). In the case of TROPOMI/S5P, the CCD method is used to retrieve tropospheric ozone columns in the tropics, up to 270 hPa.

The single instrument limb-nadir matching was applied for the first time with SCIAMACHY/Envisat (2002-2012). OMPS/NPP provides thus a unique opportunity to extend the time series from SCIAMACHY, in generating a consistent long-term dataset for trend analysis.

Here, we present the new OMPS tropospheric ozone dataset, generated by the limb-nadir matching technique. The dataset is validated using ozonesondes, and compared with the CCD tropospheric ozone product from TROPOMI/S5P, which flies a few minutes apart in the same orbit as OMPS.

How to cite: Orfanoz-Cheuquelaf, A., Arosio, C., Rozanov, A., Weber, M., Ladstätter-Weißenmayer, A., and Burrows, J.: New tropospheric ozone dataset from OMPS/NPP, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12189, https://doi.org/10.5194/egusphere-egu21-12189, 2021.

The NASA TOMS V9 (TOMS-V9) total ozone retrieval algorithm is tested
for sensitvity to boundary-layer ozone and suitability to make daily
maps of tropospheric ozone residual (TOR).  Daily maps of TOR are
derived by differencing co-located MERRA-2 assimilated MLS
stratospheric column ozone (SCO) from total column ozone from the Aura
Ozone Monitoring Instrument (OMI).  The TOMS-V9 algorithm uses a few
discrete channels with an order of magnitude range in ozone
senstivity. We compare the TOR results from TOMS-V9 with results from
several hyper-spectral total ozone retrievals: GODFIT v4 (BIRA-IASB),
OMI-DOAS (KNMI), and total ozone from the SAO PROFOZ algorithm. We
compare all satellite-retrieved TOR with TOR derived from ozonesondes,
lidar, and the Goddard Modeling Initiative (GMI) model simulation.

How to cite: Ziemke, J., Kramarova, N., Haffner, D., and Bhartia, P.: Evaluation of tropospheric ozone residual measurements derived from TOMS-V9 and hyper-spectral total ozone algorithms, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13945, https://doi.org/10.5194/egusphere-egu21-13945, 2021.