Ship emissions of SO2 and NO2: DOAS measurements from airborne platforms

Abstract. A unique methodology to measure gas fluxes of SO2 and NO2 from ships using optical remote sensing is described and demonstrated in a feasibility study. The measurement system is based on Differential Optical Absorption Spectroscopy using reflected skylight from the water surface as light source. A grating spectrometer records spectra around 311 nm and 440 nm, respectively, with the telescope pointed downward at a 30° angle from the horizon. The mass column values of SO2 and NO2 are retrieved from each spectrum and integrated across the plume. A simple geometric approximation is used to calculate the optical path. To obtain the total emission in kg h−1 the resulting total mass across the plume is multiplied with the apparent wind, i.e. a dilution factor corresponding to the vector between the wind and the ship speed. The system was tested in two feasibility studies in the Baltic Sea and Kattegat, from a CASA-212 airplane in 2008 and in the North Sea outside Rotterdam from a Dauphin helicopter in an EU campaign in 2009. In the Baltic Sea the average SO2 emission out of 22 ships was (54 ± 13) kg h−1, and the average NO2 emission was (33 ± 8) kg h−1, out of 13 ships. In the North Sea the average SO2 emission out of 21 ships was (42 ± 11) kg h−1, NO2 was not measured here. The detection limit of the system made it possible to detect SO2 in the ship plumes in 60% of the measurements when the described method was used. A comparison exercise was carried out by conducting airborne optical measurements on a passenger ferry in parallel with onboard measurements. The comparison shows agreement of (−30 ± 14)% and (−41 ± 11)%, respectively, for two days, with equal measurement precision of about 20%. This gives an idea of the measurement uncertainty caused by errors in the simple geometric approximation for the optical light path neglecting scattering of the light in ocean waves and direct and multiple scattering in the exhaust plume under various conditions. A tentative error budget indicates uncertainties within 30–45% but for a reliable error analysis the optical light path needs to be modelled. A ship emission model, FMI-STEAM, has been compared to the optical measurements showing an 18% overestimation and a correlation coefficient (R2) of 0.6. It is shown that a combination of the optical method with modelled power consumption can estimate the sulphur fuel content within 40%, which would be sufficient to detect the difference between ships running at 1% and at 0.1%, limits applicable within the IMO regulated areas.

[1]  W. Munk,et al.  Measurement of the Roughness of the Sea Surface from Photographs of the Sun’s Glitter , 1954 .

[2]  J. Grainger,et al.  Anomalous Fraunhofer Line Profiles , 1962, Nature.

[3]  U. Platt,et al.  Simultaneous measurement of atmospheric CH2O, O3, and NO2 by differential optical absorption , 1979 .

[4]  Roderic L. Jones,et al.  Rotational Raman scattering and the ring effect in zenith‐sky spectra , 1995 .

[5]  Ann Carine Vandaele,et al.  Measurements of the NO2 absorption cross-section from 42 000 cm−1 to 10 000 cm−1 (238–1000 nm) at 220 K and 294 K , 1998 .

[6]  Reflection of Spectral Sky Irradiance on the Surface of the Sea and Related Properties , 1999 .

[7]  Naoto Ebuchi,et al.  Probability distribution of surface wave slope derived using Sun glitter images from geostationary meteorological satellite and surface vector winds from scatterometers , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[8]  William J. Plant A new interpretation of sea-surface slope probability density functions , 2003 .

[9]  A. McGonigle,et al.  A miniaturised ultraviolet spectrometer for remote sensing of SO2 fluxes: a new tool for volcano surveillance , 2003 .

[10]  Steffen Beirle,et al.  Estimate of nitrogen oxide emissions from shipping by satellite remote sensing , 2004 .

[11]  John P. Burrows,et al.  Airborne multi-axis DOAS measurements of tropospheric SO 2 plumes in the Po-valley , Italy , 2005 .

[12]  Yugo Kanaya,et al.  Comparison of box-air-mass-factors and radiances for Multiple-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) geometries calculated from different UV/visible radiative transfer models , 2006, Atmospheric Chemistry and Physics.

[13]  Stefan Kraus,et al.  DOASIS: a framework design for DOAS , 2006 .

[14]  Erin H. Green,et al.  Mortality from ship emissions: a global assessment. , 2007, Environmental science & technology.

[15]  R. Prinn,et al.  Monocyclic Aromatic Hydrocarbons in Kathmandu During the Winter Season , 2008 .

[16]  John P. Burrows,et al.  SO 2 Retrieval from SCIAMACHY using the Weighting Function DOAS (WFDOAS) technique: comparison with Standard DOAS retrieval , 2008 .

[17]  J. Kukkonen,et al.  A modelling system for the exhaust emissions of marine traffic and its application in the Baltic Sea area , 2009 .

[18]  Claudia Rivera,et al.  Tula industrial complex (Mexico) emissions of SO 2 and NO 2 during the MCMA 2006 field campaign using a mobile mini-DOAS system , 2009 .

[19]  M. Zahniser,et al.  Emissions of NOx, SO2, CO, and HCHO from commercial marine shipping during Texas Air Quality Study (TexAQS) 2006 , 2009 .

[20]  J. Mellqvist,et al.  Measurements of industrial emissions of alkenes in Texas using the solar occultation flux method , 2010 .