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Workshop: Emissies schatten vanuit de ruimte Bas Mijling, Ronald van der A Emissiesymposium Lucht ● 17 juni 2014 ● Utrecht.

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Presentation on theme: "Workshop: Emissies schatten vanuit de ruimte Bas Mijling, Ronald van der A Emissiesymposium Lucht ● 17 juni 2014 ● Utrecht."— Presentation transcript:

1 Workshop: Emissies schatten vanuit de ruimte Bas Mijling, Ronald van der A Emissiesymposium Lucht ● 17 juni 2014 ● Utrecht

2 Overzicht Meten van luchtvervuling uit de ruimte Van concentraties naar emissies NO x emissies in China en Zuid Afrika Andere emissies Conclusies en vooruitblik

3 Measuring air pollution from space

4 Atmospheric Composition - Carbon dioxide (CO 2 ) - Ozone (O 3 ) - Nitrogen dioxide (NO 2 ) -... (N 2 ) (O 2 ) (Ar)

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 wavelength [nm] spectral irradiance [W/m 2 /nm]

9 wavelength [nm] spectral irradiance [W/m 2 /nm]

10 wavelength [nm] spectral irradiance [W/m 2 /nm] ozone (O 3 ) nitrogen dioxide (NO 2 )



13 Air pollution from space


15 Shanghai Beijing Hong Kong

16 From concentrations to emissions

17 Basic tools NO 2 retrievals from OMI and GOME2 CHIMERE 0.25 °×0.25°

18 Chemical transport model Meteorology Emission inventory Air pollution concentrations

19 Difference between simulation and observation......mainly caused by wrong emissions simulated by model (2008) observed from space (2008)

20 How to find emissions from concentrations? wind ( ( ( (

21 Properties of DECSO* Takes transport into account enables high resolution (~25  25 km 2 ) Relatively fast enables operational emission estimation Emission updates by addition enables detection new hotspots enables relocation existing hotspots * Daily Emission estimates Constrained by Satellite Observations From concentrations to emissions CHIMERE 0.25° x 0.25° NO 2 retrievals from OMI or GOME-2

22 NO x in China

23 Air pollution from space Shanghai Beijing Hong Kong

24 Bevolkingsdichtheid China

25 Change in NO 2 column densities over China 2003 SCIAMACHY mean tropospheric NO

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

27 Shanghai 1995Shanghai 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 New power plants in Inner Mongolia Distinct emissions along great rivers original emissions new emissions No emissions in North Korea Ship tracks

33 Based on GOME-2 observations from NO x emission trends


35 NO x 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 lowTotal emissions too low Location and strength of hot spots generally wrongLocation and strength of hot spots generally wrong

37 EDGAR v4.2 low high 200 km

38 DECSO low high 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 CH 2 O (formaldehyde) by GOME-2

48 NMVOC from fire emissions

49 C 5 H 8 (isoprene) emissions

50 PM 2.5 / PM 10 emissions by MODIS

51 NH 3 by IASI NH 3 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 Satellite retrievals Chemical transport modeling Inversion algorithm

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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