Detection of ship NO 2 emissions over Europe from satellite observations

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Detection of ship NO 2 emissions over Europe from satellite observations Huan Yu DOAS seminar 24 April 2015 Ship Emissions to Atmosphere Reporting Service (SEARS project)

Outline Introduction Shipping NO 2 over European waters from existing satellite datasets Potential of future instruments on shipping NO 2 detection

Soot, NO x, SO 2, VOCs. Ship emissions Ship powered by fossil fuel much dirtier than fuels used in land based engines much larger emissions than the other sources. Ship emissions seen causing 60,000 deaths a year --- 7 th of November 2007, Reuters

Ship emissions from satellite observations Trace gases: GOME, SCIAMAMCHY, OMI, GOME-2 (near future: TROPOMI, Sentinel-4/5 ) First discovered by 6-year GOME NO 2 data (Beirle,2004) over Indian Ocean: Owing to better spatial resolution/signal-to-noise of SCIAMACHY/OMI/GOME- 2 sensor, more shipping NO 2 was detected (Richter, 2004, 2011; Marmer, 2009; Ialongo, 2014; Vinken, 2014):

Ship emissions from satellite observations Trace gases: GOME, SCIAMAMCHY, OMI, GOME-2 (near future: TROPOMI, Sentinel-4/5 ) First discovered by 6-year GOME NO 2 data (Beirle,2004) over Indian Ocean: Owing to better spatial resolution/signal-to-noise of SCIAMACHY/OMI/GOME- 2 sensor, more shipping NO 2 was detected (Richter, 2004, 2011; Marmer, 2009; Ialongo, 2014; Vinken, 2014): Long-term trend of shipping NO 2 have been analysed. 1 2 1 2 3 4 3 4

Ship emissions from satellite observations Marbach (2009) detected the enhanced HCHO signal from GOME over Indian Ocean, which is probably contributed from ships, but no other HCHO enhancements have been reported in the literature so far. Recently, Theys (2015) improved OMI SO 2 products, the weak SO 2 signal can be captured over the Red Sea and the strait of Gibraltar, where have intense shipping. GOME SCDs High-pass filtered

Ship emissions from satellite observations Aerosol: The perturbation of a cloud layer by ship-generated aerosol changes the cloud reflectivity and is identified by long curves in satellite images MODIS RGB map

Shipping NO 2 from existing satellite data records Dataset: OMI: April October, 2005-2010, VZA<50, CF<30% GOME-2: April October, 2007-2010, CF<30%, only forward scan pixels (pixel size: 40x80km 2 ) Several shipping tracks are clearly showed in NO 2 map (Southern Europe) A few ship lanes over Northern Europe are discussed in the literature, but it is not very clear in the maps. GOME-2 NO 2 distribution is more extended spatially, because of relatively larger pixel size than OMI.

Shipping NO 2 from existing satellite data records Dataset: OMI: April October, 2005-2010, VZA<50, CF<30% GOME-2: April October, 2007-2010, CF<30%, only forward scan pixels (pixel size: 40x80km 2 ) Several shipping tracks are clearly showed in NO 2 map (Southern Europe) A few ship lanes over Northern Europe are discussed in the literature, but it is not very clear in the maps. GOME-2 NO 2 distribution is more extended spatially, because of relatively larger pixel size than OMI. High pass filtered maps: smoothed the field (boxcar, OMI: 2 1 ; GOME-2: 4 2 ) and then be subtracted from the average.

Aim: Sensitivity study for detection of shipping NO 2 effects of spatial resolution / cloud fraction / meteorology on ship detection Regions: Case Instrument (Period) Criteria of data selection 1 GOME-2 (2007-2010) CF<30% 2 CF<30% 3 CF<100% OMI 4 CF<15% (2005-2010) 5 CF<30%, VZA<50 6 CF<30%, WS<5m/s

Results Strongest shipping signal A B C D E F G H I Most important factor (black line: reference): 1. OMI calm day observations (wind speed<5m) meteorology condition 2. GOME-2 observations Spatial resolution 3. All OMI observations cloud contamination

Seasonal variation North Europe Shipping signals are not visible during winter over North Europe regions.

Potential of future instruments on shipping NO 2 detection Instruments: TROPOMI (2016), Sentinel-4 Current shipping NO 2 products are mainly limited by four factors: Signal to noise ratio Spatial resolution Cloud contamination lack of information on chemistry and transport within the ship plume Improved by TROPOMI & S4 CTM model: CHIMERE Emission: EDGAR v4.2 (0.1 0.1 for shipping emission) Spatial resolution: 9 9km 2 Vertical resolution: 19 layers, up to 7km

TROPOMI observations Nadir TROPOMI vs. OMI Edge NO 2 error(tropomi) ~ NO 2 error(omi) ~ 0.7x10 15 NO 2 error(tropomi) ~ 0.7x10 15 x 2 NO 2 error(tropomi) ~ 0.7x10 15 x2

Sentinel-4 observations Spatial resolution & Signal-to-Noise Ratio: similar with TROPOMI Hourly measurement during daytime (S4) vs. daily measurement (TROPOMI) Number of S4 measurements per day having an observation zenith angle smaller than 75 and a solar zenith angle smaller than 85. Number of observations (per day): Summer: ~10 (south), decreasing with latitudes Winter: >12

Spatial resolution Instrument GOME-2 OMI TROPOMI Sentinel-4 Pixel Size (km 2 ) 40 80 13 24 at nadir 24 128 at edge 7 7 8 8

Improvement of spatial resolution TROPOMI resolution Mediterranean OMI resolution Bay of Biscay

SNR Simulated TROPOMI measurements Simulated OMI measurements Integration along ship track 1.4x10 15 1.0x10 15 0.7x10 15 1.0x10 15 Monthly mean 0.7x10 15 Monthly mean Simulated NO 2 maps for TROPOMI (left) and OMI (right) for one orbit (top) and for monthly mean (bottom) Error level of NO 2 columns is improved by a factor of 2 for TROPOMI Compared to TROPOMI, Noise level of monthly NO 2 maps for S-4 measurements will improve by a factor of 3 (~10 measurements per day)

Cloud representation Requirements for cloud product: Similar definition with cloud product used in trace gas retrieval better spatial resolution than TROPOMI/S4 MODIS/SEVIRI OMI CF Relation between OMI CF and MODIS COT MODIS CF MODIS cloud optical thickness (COT) Clear-sky scenes (effective CF<20%-30%): MODIS COT < 2

SEVIR COT vs. OMI CF Similar results with the relation between MODIS COT and OMI CF Clear-sky scenes (effective CF<20%-30%): SEVIRI COT < 2

Cloud-free observations OMI CF at OMI resolution CF at TROPOMI resolution Cloud-free data : Mediterranean is 2 times more than North Sea Summer is 2 times more than Winter Fractions of cloud free pixels over selected regions TROPOMI (solid) vs. OMI (dashed)

Cloud-free observations OMI 5~10 times more than OMI/TROPOMI S4 1 month: 30x75% = 22.5 ~200 measurements 30x60% = 18 ~120 measurements

Wind Field Calm day: wind speed (surface-500m) < 5m/s Over Northern European waters, the number of calm situations is few, especially in winter. Very difficult to detect shipping NO 2 over North of Europe.

Measurements with sun-glint geometry Sun glint occurs in imagery when the water surface and sun orientation is such that the sun light is directly reflected towards the sensor, which results in enhanced surface signals. The sun glint angle (Ω glint ) is defined as the angle for which sun glint would occur if the ocean was a perfect mirror. The deviation from this angle ( Ω glint ) can be defined as: cos Ω glint = cos θ cos θ 0 + sin θ sin θ 0 cos(φ φ 0 ) Where θ is the viewing zenith angle, θ 0 is the solar zenith angle, φ is the viewing azimuth angle, φ 0 is the solar azimuth angle. Geometrical sun glint occurs when the sun glint deviation angle is smaller than 18 OMI Cloud fraction products No sun-glint correction in OMI cloud products, therefore, observations with sun-glint geometry show the enhanced cloud fractions.

Effect of sun-glint on shipping NO 2 detection Average of OMI observations with Ω sunglint <18 Average of OMI observations with Ω sunglint >18 Measurements with CF>30% are filtered. Satellite measurements over water with sunglint geometry increase shipping NO 2 signal by 35-50%.

Summary OMI and GOME-2 NO 2 data records could clearly show several shipping lanes over European waters. However, the detection is limited in several aspects, especially spatial resolution, meteorology condition and cloud contamination. Owing to their higher spatial resolutions compared to OMI, TROPOMI and S4 will not only better characterize the ship signals from narrow ship tracks, but will also increase the number of measurements allowing to improve the detection of shipping NO 2. If integrated along the ship track, the detection of shipping NO 2 signal could be achieved daily (TROPOMI) or hourly (S4). Clouds and meteorology are as important as SNR over high latitudes, in particular during the cold season. Observations under sun glint geometry increase the shipping NO 2 signals by 30-50%.