Global nitrogen and sulfur inventories for oceangoing ships


  • James J. Corbett,

  • Paul S. Fischbeck,

  • Spyros N. Pandis


We present geographically resolved global inventories of nitrogen and sulfur emissions from international maritime transport for use in global atmospheric models. Current inventories of globally resolved sources of natural and anthropogenic emissions do not include the significant contribution of SO2 or NOx from oceangoing ships [Benkovitz et al., 1996]. We estimate the global inventory of ship emissions, using current emission test data for ships [Carlton et al., 1995] and a fuel-based approach similar to that used for automobile inventories [Singer and Harley, 1996]. This study estimates the 1993 global annual NOx and SO2 emissions from ships to be 3.08 teragrams (Tg, or 1012 g) as N and 4.24 Tg S, respectively. Nitrogen emissions from ships are shown to account for more than 14% of all nitrogen emissions from fossil fuel combustion, and sulfur emissions exceed 5% of sulfur emitted by all fuel combustion sources including coal. Ship sulfur emissions correspond to about 20% of biogenic dimethylsulfide (DMS) emissions. In regions of the Northern Hemisphere, annual sulfur emissions from ships can be of the same order of magnitude as estimates of the annual flux of DMS [Chin et al., 1996]. Monthly inventories of ship sulfur and nitrogen emissions presented in this paper are geographically characterized on a 2° × 2° resolution. Temporal and spatial characteristics of the inventory are presented. Uncertainty in inventory estimates is assessed: the fifth and ninety-fifth percentile values for global nitrogen emissions are 2.66 Tg N and 4.00 Tg N, respectively; the fifth and ninety-fifth percentile values for sulfur emissions are 3.29 Tg S and 5.61 Tg S, respectively. We suggest that these inventories, available via the Ship Emissions Assessment (SEA) web site, be used in models along with the Global Emissions Inventory Activity (GEIA) inventories for land-based anthropogenic emissions and modeled with ocean-biogenic inventories for DMS.