Air Quality II

Operational monitoring of atmospheric gaseous and particular species of both tropospheric as well as stratospheric provenance sensed by satellite instruments are performed routinely in the Laboratory of Atmospheric Physics, Thessaloniki, Greece, using a suite of different ground based instruments. These include both a single and double Brewer spectrophotometer, multiple MAX-DOAS instruments, a Raman aerosol Lidar as well as a NILU-UV sun photometer, a CIMEL photometer, among others. Most of the data records provided by these instruments span the better part of two decades. In the following we will focus on validating TROPOMI/S5P total ozone columns, total, stratospheric and tropospheric NO₂ and HCHO using the MAX-DOAS instruments and absorbing aerosol height using the Raman Lidar system. The high spatial resolution of the TROPOMI/S5P TOCs will permit the investigation on the effect of the temporal difference between the measurements, as well as other contributing factors.

A MAX-DOAS system has been operating since 2011 on the rooftop of the Physics Department in the Aristotle University of Thessaloniki at the Laboratory of Atmospheric Physics (LAP), which is located in the city center of Thessaloniki, Greece. A second MAX-DOAS system is operating since 2016 at the Center of Interdisciplinary Research and Innovation (CIRI) of AUTH located at the suburbs of the city, about 10 km to the South-East. The combined monitoring ability at both an urban and suburban location can prove to be extremely informative in identifying urban gradients in NO₂ and HCHO loading and thus allowing their verification from high spatial resolution space-born observations, as well as possible features in the daily variability of the ozone content over the city.

A Raman Lidar system is co-located in LAP, operating since 2000 as part of the European Aerosol Research Lidar Network (EARLINET) and will be employed to examine the variability of the aerosol load via its verification to the TROPOMI/S5P Absorbing Layer Height for cases of elevated aerosol layers such as Saharan dust events and biomass burning episodes.  Routine, dedicated Raman lidar measurements during such episodes, like those performed in EARLINET, are important to study the sensitivity of the newly developed S5P/ALH product for different aerosol types.

The TROPOspheric Monitoring Instrument (TROPOMI) spectrometer aboard the Copernicus Sentinel-5P (S5P) satellite, launched on 13 Oct. 2017, measures several trace gases as well as some aerosol and cloud properties with a resolution of 7 x 3.5 km² at nadir, achieving global coverage each day.

TROPOMI nitrogen dioxide (NO₂) tropospheric columns are retrieved using a DOAS algorithm combined with an integrated modelling/retrieval-assimilation approach based on the TM5-MP chemistry-transport model (operating at 1x1 degree resolution), to derive air-mass factors and to estimate stratospheric columns. Developments from the EU QA4ECV project (www.qa4ecv.eu) have been included in the retrieval to ensure consistency.

This contribution describes the components of the TROPOMI NO₂ tropospheric and vertical column retrieval, focussing on data quality issues and the latest improvements in the operational algorithm, as well as prospects for future developments and use of the data for monitoring NO₂ sources and air quality.

Off-line NO₂ data of the operational (E2) phase, started 30 April 2018, and near-real time (NRT) data as of 3 July 2018 are available from the Copernicus Open Access Hub (s5phub.copernicus.eu).

Since two decades, satellite instruments like GOME(-2), SCIAMACHY, and OMI allow the global retrieval of tropospheric NO₂, with increasing spatial resolution. By temporal averaging, spatial patterns of anthropogenic sources can be clearly identified. In these averaged maps, the effective NO_x lifetimes and emissions can even be quantified from the NO₂ decay downwind from large NO_x sources.

TROPOMI offers a high spatial resolution of 3.5 km times 7 km, which is more than 10 times better than OMI (nadir). This allows to detect also weaker sources and to partly resolve the spatial distribution of NO_x sources within a megacity or urban areas. In addition, TROPOMI offers a high signal to noise ratio, leading to low noise in daily maps of tropospheric NO₂, such that emission plumes from cities and large power plants are clearly visible. Thus, methods that have been applied to long-term means in the past can now be applied to daily measurements as well.

Single day measurements generally provide much higher contrast compared to temporal means, as upwind columns are lower than the mean, while downwind columns are far higher than the mean. From the upwind measurements, constraints on spatial extent of sources can be derived. From the downwind decay, a combined lifetime/emission fit can be performed on daily basis rather than for temporal means as done in previous studies. From multiple days, thus statistical analysis of the mean and variability of both NO_x emissions and lifetime can be performed, allowing to investigate the consistency of the methodology and to infer temporal changes of emissions and potentially also the NO₂ lifetime on daily basis.

Here we present first results of the analysis of lifetime/emission fits on daily basis, focussing on the Saudi-Arabian capital Riyadh.

Airborne hazards like volcanic plumes, desert dust clouds, and smoke from wildfires, pose a risk for aviation. Information on the location, height, type, and mass density of these aerosol plumes is important to assess the risks and warrant air safety. Remote sensing by satellites and ground-based instruments is used to provide the required observational data. The timely distribution of the information to the aviation sector is a challenge, but crucial for early warning and flight (re-)planning. In the EUNADICS-AV project an information system is being set up, as a demonstrator, consisting of observations from satellite, ground and airplane, combined with atmospheric transport modelling, to provide this information to the aviation sector.

EUNADICS-AV stands for European Natural Airborne Disaster Information and Coordination System for Aviation. The main objective of this European project is closing the significant gap in European-wide data and information availability during airborne hazards. Aviation is one of the most critical ways of transport in this century. Even short interruptions in flight schedules can cause major economic damage. Therefore, information from observations are crucial for decision making. Several satellite data sources are considered in the EUNADICS-AV project, especially from the European Meteosat (SEVIRI) and Metop (GOME-2 and IASI) satellites. Also, the Sentinel satellites which recently became available, Sentinel-3 (SLSTR) and Sentinel-5P (TROPOMI), are used as data sources.

It appears that the TROPOMI L2 data products are very useful for hazard monitoring for several reasons. First of all, TROPOMI has true daily global coverage, so all sources of events, like volcanoes, are observed daily. Secondly, the relatively high spatial resolution of 3.5x7 km² is useful to outline the plumes accurately. Thirdly, the instrument has a high sensitivity for the presence of gases relevant to detection of airborne hazards, like NO₂, SO₂ and CO. Moreover, the simultaneous detection of several aerosol and trace gas products for the same area helps to identify the type of aerosols. We find that the combination of the TROPOMI L2 products: Aerosol Index, SO₂, CO, and cloud/aerosol height (using the O₂ A-band) leads to a strong synergy and enables discrimination of important aerosol types. We present several cases of hazardous events where the TROPOMI data products are useful for selecting the types of aerosols and estimate the plume heights.

The EUNADICS-AV project has received funding from the European Union’s Horizon 2020 research programme for Societal challenges - smart, green and integrated transport under grant agreement no. 723986.

Nowadays a vast amount of operational satellite-based Earth Observations (EO) products are available, many of which have the potential to be useful for air quality applications. In order to better exploit these data, a three-year ESA funded project Satellite based Monitoring Initiative for Regional Air quality (SAMIRA) was established in 2016. The overall goal of SAMIRA is to improve regional and local air quality monitoring through synergetic use of satellite data, output from chemical transport models and data from in situ air quality monitoring networks. This is a collaborative effort of a team located in four countries (Poland, Romania, The Czech Republic, and Norway), where the capitals, the Gorj county in Romania, and the Silesia region, the border area between Poland and The Czech Republic, periodically suffer from air pollution.

We present an overview of results obtained in the first half of the project. While SAMIRA is ultimately intended as a NRT demonstration, we first concentrated on work with historical datasets, which cover the period June to September 2014. For this period WRF-Chem output was generated on a 1 km x 1 km local grid for the particular polluted areas mentioned above and on a 5 km x 5 km European grid for improved PM forecasts using in situ data assimilation.

A first activity is the further development of an algorithm for the retrieval of aerosol optical depth (AOD) from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI). Visualisation of SEVIRI AOD 15 min maps and their respective uncertainties are shown for the four countries. In a next step particulate matter (PM₂_.₅) is derived from SEVIRI AOD using micro-physical properties from GADS/OPAC and mass mixing ratios of aerosol species from WRF-Chem model. Look-up tables (LUT) with extinction efficiencies for a range of possible mixtures of aerosols and different humidity conditions are generated. We show hourly PM₂_.₅ maps obtained with this method and present comparisons with in situ air quality station data. Data fusion techniques are employed to utilize satellite products of atmospheric composition for European- and National scale air quality mapping. The additional benefit of satellite-based monitoring over existing monitoring techniques (in situ, models) is tested by combining hourly, daily and annual data using geostatistical methods and demonstrated for nitrogen dioxide (NO₂), sulphur dioxide (SO₂), and AOD/PM for rural and urban areas. Air quality applications, in particular within a city, require very high spatial resolutions, which are not yet available from satellites. In order to address this issue we have developed a spatial downscaling technique for satellite-based air quality products. The method applies a combination of area-to-point kriging and regression and essentially combines a high-resolution but often biased proxy dataset with the coarse-resolution but assumed to be unbiased satellite observations (from Aura/OMI and Sentinel-5/TROPOMI). In a final step we summarize the validation efforts for evaluating the quality of the generated products and activities linking to interested users.

Nitrogen dioxide (NO₂) plays a key role in both stratospheric and tropospheric chemistry. This contribution focuses on the algorithm development and refinement for the retrieval of NO₂ columns for the GOME-2 satellite instrument. Furthermore, the improved algorithm is adapted to measurements from the TROPOMI instrument with a spatial resolution as high as 7*3.5 km².

A larger 425-497 nm wavelength fitting window is used in the differential optical absorption spectroscopy (DOAS) retrieval of the NO₂ slant column density, with corrections for the GOME-2 slit function variations over time and along orbit. The STRatospheric Estimation Algorithm from Mainz (STREAM) is optimized for the determination of the NO₂ stratospheric column density. To calculate the tropospheric AMF, a new directional surface albedo database based on GOME-2 observations is used to account for bidirectional reflectance distribution function (BRDF) effect. In addition, the new version 3.0 OCRA/ROCINN cloud parameters using the more realistic Clouds-As-Layers model are applied, in which clouds are treated as optically uniform layers of light-scattering particles (water droplets).

We present the improvements in the NO₂ retrieval algorithm for GOME-2 and we show validations of the GOME-2 NO₂ data using ground-based MAX-DOAS measurements. We present the first results from TROPOMI and we show verifications of the TROPOMI NO₂ data using GOME-2 measurements.