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Evaluating the Potential of Satellite Measurements in Air Quality

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EGU General Assembly 2020 EGU2020-8301 Evaluating the Potential of Satellite Measurements in Air Quality Monitoring: A Project for the Finnish Ministry of the Environment Henrik Virta, Anu-Maija Sundström, Iolanda Ialongo, and Johanna Tamminen Finnish Meteorological Institute, Space and Earth Observation Centre, Helsinki, Finland 1 Project description • Aim: to evaluate what potential satellite measurements have in complementing traditional in situ air quality measurements. • Performance of current instruments evaluated using gridded maps and statistical comparisons with collocated in situ station measurements in Finland. • Focus on NO2 measurements done by the TROPOMI instrument; SO2, CO, and aerosols also covered. • Commissioned by the Finnish Ministry of the Environment. • Study period: April 2018 to June 2019. 2 Nitrogen dioxide (NO2) • Internationally recognized air pollutant (WHO, EU, USA). • Increases in concentrations linked to increased mortality. • Concentration limits set by law. • Mainly emitted from combus- tion engines, biomass burning, soil bacteria, and lightning. Pixabay 3 TROPOMI instrument • Launched in October 2017 aboard Sentinel-5 Precursor. • Part of EU’s Copernicus Earth monitoring programme. • Hyperspectral imager measuring NO2, O3, CH4, CO, SO2, CH2O, clouds, and aerosols. • Ground resolution 7x3.5km (5.5x3.5km as of August 2019). Sentinel-5P. ESA/ATG medialab 4 Gridded maps ] • TROPOMI Tropospheric NO Kovdor 2 2 - measurements oversampled (avg.) to 2.5x2.5 km grid Between cm . 15.4.2018–30.6.2019. molec [ • Helsinki capital region stands out, Kostomuksha 2 as do the cities of Turku and Tampere (among the most populous in Finland). • Two light dots just east of northern Finland are the Russian mining Tampere Tropospheric NO Tropospheric towns of Kostomuksha and Kovdor. St. Petersburg Turku Helsinki 5 Weak winds (<3m s-1) Gridded maps ] • If only measurements made during 2 weak winds are included, effect of - emissions transport is reduced cm . → sources of NO2 more visiBle. molec [ • Smaller towns now stand out, as 2 do main highways (e.g. Between Helsinki and Tampere). • Wind: ERA5 reanalysis product used to calculate average Boundary layer wind speed. Tropospheric NO Tropospheric 6 Need of new Helsinki capital region stations? • TROPOMI Tropospheric NO2 ] 2 oversampled (averaged) to - 1x1km grid. Helsinki-Vantaa airport cm . • Highest concentrations near Ring III molec Ring I [ Helsinki-Vantaa airport and just 2 north of Helsinki city centre. • Ring I Finland’s busiest road: not clearly visible on map → due to TROPOMI ovp time? NO Tropospheric Permanent AQ stations marked by filled circles, 7 temporary stations by hollow circles. TROPOMI overpass time 19.4.2018–30.6.2019 Helsinki, Mäkelänkatu 70 Middle 50% • TROPOMI on an afternoon Hourly averages 60 Time series avg. orbit: overpasses between TROPOMI ovps. ] morning and afternoon peaks -3 50 in NO2 due to commuter traffic 40 → highest concentrations not captured, measurements 30 concentration [µg m represent ~midday average. 2 20 NO • Important to remember when 10 interpreting measurements! 0 01 03 05 07 09 11 13 15 17 19 21 23 Finnish time A classic example of the NO2 diurnal cycle from the Mäkelänkatu air quality station. TROPOMI overpass 8 times marked with grey vertical lines. TROPOMI vs. air quality stations AveragePääkaupunkiseudun of different Helsinki asemien AQ keskiarvo stations • Correlation of TROPOMI and air 1015 R=0.1439, N=9 3.3 quality station measurements Pirkkola ] ] 2 2 3.2 evaluated using scatter plots. - • Collocation criteria: TROPOMI . cm 3.1 Tikkurila [molek./cm Kumpula 2 molec 3 pixels above station chosen, [ station measurements linearly 2 Kallio 2 Mäkelänkatu 2.9 Mannerheimintie interpolated to overpass time. Leppävaara 2.8 • Poor correlation of collocated 2.7 Luukki meas. averages: only ~0.14 2.6 TROPOMI Trop. NO TROPOMITrop. TROPOMI alailmakehän NO Vartiokylä 2.5 0 10 20 30 40 9 Ilmanlaatuaseman NO [µg/m-33] AQ station NO2 [µg2 m ] City centre aggregation • Measurement aggregation by AverageKeskustan of Finnish mittausasemien city centre keskiarvo AQ stations 1015 R=0.7448, N=9 averaging together all city centre 3.2 Vantaa ] ] 3 2 2 stations. - Helsinki 2.8 Espoo • Correlation improved: ~0.74 . cm 2.6 [molek./cm 2 molec • TROPOMI pixels cannot capture [ 2.4 2 variability within a small area 2.2 such as city centre → poor corre- 2 lation with individual stations. Tampere 1.8 Turku • Better correlation when 1.6 Rauma Pori comparing city centres. NO TROPOMITrop. TROPOMI alailmakehän NO 1.4 Oulu Raahe 1.2 5 10 15 20 25 10 3 Ilmanlaatuaseman NO [µg/m-3 ] AQ station NO2 [µg2 m ] Effect of boundary layer wind AverageKeskustan of mittausasemiencity centre AQ stationskeskiarvo (<3m (<3m/s) s-1) • Advection of NO2 emissions 1015 R=0.788, N=9 affects correlation by 5.5 ] ] Helsinki 2 2 dispersing emissions over a - 5 Espoo larger area. Vantaa . cm 4.5 • If only measurements during [molek./cm 2 molec 4 [ weak winds considered, 2 correlation is improved: ~0.79 3.5 • Northernmost studied city Oulu 3 Turku is outlier. May be due to snow Tampere 2.5 and ice cover (port city). Rauma 2 TROPOMI Trop. NO TROPOMITrop. TROPOMI alailmakehän NO Oulu Pori Raahe 1.5 5 10 15 20 25 30 11 3 Ilmanlaatuaseman NO [µg/m-3 ] AQ station NO2 [µg2 m ] Comparison of European cities KeskustanAverage of mittausasemien city centre AQ keskiarvostations (<3m(<3m/s) s-1) • Study also extended to some 1015 R=0.9471, N=7 16 European cities. PariisiParis ] ] 2 2 • Data from European - 14 . cm LondonLontoo Environment Agency. 12 [molek./cm 2 molec [ • Data very well correlated: ~0.95 2 10 • Helsinki appears as a notable 8 HampuriHamburg outlier. Observed in situ vs. 6 TROPOMI differences require Helsinki further investigation. 4 TROPOMI Trop. NO TROPOMITrop. TROPOMI alailmakehän NO TallinnaTallinn TukholmaStockholm Oslo 2 30 40 50 60 70 12 3 Ilmanlaatuaseman NO [µg/m-3] AQ station NO2 2[µg m ] Conclusions • TROPOMI oversampled grids a feasible tool to characterize regional spread of NO2 emissions and sources. • Could be used to plan placement of ground stations. • Overpass time of TROPOMI must be accounted for. • Correlation of TROPOMI and air quality station measurements between individual cities is good. • TROPOMI could be used as a tool to estimate NO2 concentrations in cities lacking any ground stations. • First such report delivered to the FME. • Societal interest in satellite measurements growing, thanks to TROPOMI’s unprecedented spatial resolution. 13 References Sundström, A.-M., Virta, H., Ialongo, I., and Tamminen, J., 2020: Satelliittihavaintojen hyödyntäminen ilmanlaadun seurannassa. Raportteja – Rapporter – Reports 2020:1, Finnish Meteorological Institute, Helsinki, Finland. doi: 10.35614/isbn.9789523360983 See also Ialongo, I., Virta, H., Eskes, H., Hovila, J., and Douros, J., 2020: Comparison of TROPOMI/Sentinel-5 Precursor NO2 product with ground-based observations in Helsinki and first societal applications. EGU2020-9963 at 7 May 2020, 8:30–10:15 7 May 2020 EGU2020-8301.
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