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Workshop: Emissies schatten vanuit de ruimte

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1 Workshop: Emissies schatten vanuit de ruimte
Bas Mijling, Ronald van der A Emissiesymposium Lucht ● 17 juni ● Utrecht

2 Overzicht Meten van luchtvervuling uit de ruimte
Van concentraties naar emissies NOx emissies in China en Zuid Afrika Andere emissies Conclusies en vooruitblik

3 Measuring air pollution from space

4 Atmospheric Composition
(Ar) - Carbon dioxide (CO2) - Ozone (O3) - Nitrogen dioxide (NO2) - ... Samenstelling van droge lucht. N2: 78%, O2: 20.9%, Ar: 0.9%. De overige 0.1% bestaat uit sporegassen zoals CO2 (383 ppm), ozon ( ppm), NO2 (0.02 ppm) CO2 is bekend van het broeikas-effect

5 The Ozone Monitoring Instrument (OMI)
EOS Aura satellite

6 Sun-synchronous Orbit
km altitude Always same orientations towards sun:rotates eastward about 1 degree each day. Each orbit experiences about 30 minutes darkness and 72 minutes sunlight OMI local overpass time: 13:00 Daily global coverage

7 Measuring trace gases from space

8 spectral irradiance [W/m2/nm]
2.5 2.0 1.5 1.0 0.5 wavelength [nm] spectral irradiance [W/m2/nm]

9 spectral irradiance [W/m2/nm]
2.5 2.0 1.5 1.0 0.5 wavelength [nm] spectral irradiance [W/m2/nm]

10 ozone (O3) nitrogen dioxide (NO2) spectral irradiance [W/m2/nm]
2.5 2.0 1.5 1.0 0.5 wavelength [nm] spectral irradiance [W/m2/nm] nitrogen dioxide (NO2)



13 Air pollution from space

14 Air pollution from space

15 Air pollution from space
Shanghai Beijing Hong Kong

16 From concentrations to emissions

17 Basic tools NO2 retrievals from OMI and GOME2 CHIMERE 0.25 °×0.25°

18 Chemical transport model
Meteorology Emission inventory Air pollution concentrations Chemical transport model

19 Difference between simulation and observation...
simulated by model (2008) observed from space (2008) Als je satellietobservaties kunt gebruiken voor emissiebepalingen, dan sla je twee vliegen in een klap: Je kunt nauwkeuriger de luchtvervuiling simuleren (betere luchtkwaliteitsverwachtingen) Je kunt emissiebronnen controleren (houden fabrieken zich wel aan de regels) ...mainly caused by wrong emissions

20 How to find emissions from concentrations?
( wind

21 Properties of DECSO* From concentrations to emissions
Takes transport into account enables high resolution (~2525 km2) Relatively fast enables operational emission estimation Emission updates by addition enables detection new hotspots enables relocation existing hotspots NO2 retrievals from OMI or GOME-2 CHIMERE 0.25° x 0.25° (A) DECSO is relatively fast: (1) Forward model run (2) Sensitivity calculation (3) Inverse with Kalman Filter (4) Emission update (B) DECSO takes transport into account, enabling a high resolution (typically in order of satellite footprint) (A) + (B): DECSO can be implemented operationally Emission results downloadable at GlobEmission website * Daily Emission estimates Constrained by Satellite Observations

22 NOx in China

23 Air pollution from space
Shanghai Beijing Hong Kong

24 Bevolkingsdichtheid China

25 Change in NO2 column densities over China
SCIAMACHY mean tropospheric NO2 2003 2006

26 China: Economic indicators
Average annual income per capita, China’s electricity production, GDP per capita in the Netherlands: € (2006) China’s urbanization, Number of vehicles in Beijing, GDP in China still factor of 10 lower than in Europe. Source: China Statistical Yearbook, China Daily (17/2/09)

27 Shanghai 1995 Shanghai 2010

28 Luchtvervuiling Beijing
17 miljoen inwoners; elk jaar nieuwe inwoners erbij 3.3 miljoen auto’s; elke dag 1000 nieuwe auto’s erbij Zware industrie dicht bij de stad Kolengestookte kachels en fornuizen

29 Beijing smog, januari 2013

30 Air quality measures No construction activities
Closure or translation of polluting industry 30% reduction coal-fired power plants Ban high emission vehicles Traffic system with odd/even number plate


32 Emission results China
original emissions new emissions New power plants in Inner Mongolia Distinct emissions along great rivers No emissions in North Korea Ship tracks

33 NOx emission trends Based on GOME-2 observations from 2007-2010
The results in this and following slides are based on 4 years of GOME-2 data ( ). Almost all Chinese provinces show positive emission trends. Economic crisis and air quality measures cause an negative trend for Japan and South Korea. The relative emission trends in (d) show that the fasted growing provinces are also in the interior. Is the economy of the interior catching up with the richer coastal provinces? Based on GOME-2 observations from

34 The DECSO algorithm also provides information on source-receptor relations.
The colored areas show the NO2 column over North and South Korea, separated by its origin. Red shows the monthly emissions (see right vertical axis) Grey shows the part of the NO2 column with an age older than 24h (which is not tracked by the DECSO algorithm). North Korea: Only a small part of NO2 is emitted locally. Most is imported from South Korea (Seoul) and China (Shenyang) South Korea: Emission and concentration factor 10 larger. NO2 concentrations mostly by local emission However: substantial part comes from sea (light blue). Intensive shipping around the peninsula!

35 NOx in South Africa

36 South Africa: Emissions characterized by few hot spots (power plants, heavy industry)
Apriori emissions taken from EDGAR v4.2 Total emissions too low Location and strength of hot spots generally wrong

37 EDGAR v4.2 low high EDGAR v4.2 200 km

38 DECSO low high DECSO exp09_omi/crab2 200 km


40 Majuba power plant

41 Matimba power plant

42 vanadium mine

43 Sasol company oil from coal

44 Biomass burning in Mozambique

45 Other species


47 CH2O (formaldehyde) by GOME-2

48 NMVOC from fire emissions

49 C5H8 (isoprene) emissions

50 PM2.5 / PM10 emissions by MODIS

51 NH3 by IASI NH3 total column distribution above Europe (5-yr weighted mean from morning overpass)

52 Conclusions & Outlook

53 Emission estimation from space: Standing on the shoulders of giants
Inversion algorithm Chemical transport modeling Satellite retrievals

54 Current state Relative new technology: quality improving rapidly
Already giving useful complementary information for regions with unknown or outdated emissions Urban scale Monthly emission inventories

55 Shortcomings Not all species can be detected from space
Total emissions: difficult to infer sectorial contributions

56 (Near) Future Better satellite observations
Switch from scientific to operational missions TROPOMI (spatial resolution) Geostationairy (temporal resolution) Better chemical transport models Better inversion algorithms

57 More information

58 Vragen?

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