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Geospatial Modeling of Ship Traffic and Air Emissions. Chengfeng Wang , Ph.D. California Air Resources Board Presentation for the US Environmental Protection Agency March 25, 2008. Background. Globally, ship emissions non-negligible Regionally, ship emissions can be significant
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Geospatial Modeling of Ship Traffic and Air Emissions Chengfeng Wang , Ph.D. California Air Resources Board Presentation for the US Environmental Protection Agency March 25, 2008
Background • Globally, ship emissions non-negligible • Regionally, ship emissions can be significant • Spatially resolved ship emissions inventory needed for • Emission impact modeling • Regulatory analysis • Producing spatially-resolved ship emissions has been challenging
ExistingApproaches • Bottom-up approach • Emissions estimated & allocated spatially based on historical ship movement data, ship particulars, emission factors, and assumed locations • Principally used for smaller scale inventory • Top-down approach • Assigns global ship emissions totals based on spatial proxy of emissions intensity • Used for larger scale emissions inventory
Top-downApproach • Strengths • Quicker, demands relatively fewer resources & costs less • Improved by updating global inventory, emissions intensity proxy • Multi-scale nature of the top-down approach • Weaknesses • Significant uncertainty of global totals • Statistical & spatial sampling bias proxy identified • Sources not sufficiently characterized
Ship Traffic, Energy and Environment Model (STEEM) Reported Ship Positions Ship Movements Empirical Waterway Network Solved Shipping Routes Ship Attributes Ship Emissions Inventory
Overview of STEEM • Solves routes on an empirical global waterway network using ArcGIS Network Analyst • Estimates emissions based on: • Nearly complete historical ship movements • Individual ship engine installed power & ship speed • Hours of operation from ship speed & length of routes • Allocates emissions based on locations of routes
Data Sources • Ship position data • International Comprehensive Ocean-Atmosphere Data Set (ICOADS) • Automated Mutual-assistance Vessel Rescue System (AMVER) data set • Ship movement data • U.S. Army Corps of Engineers (USACE) Foreign Traffic Entrances & Clearances data set • Lloyd's Shipping Information Database • Ship attribute data • Lloyd's ship registry data
Building Empirical Waterway Network ~9000 segments & ~1700 ports ~170,000 ship trips/yr in North America
Illustration of Real World Route Captain Ed Page, The emerging world of vessel tracking
Segment ID Ship ID Trip ID Route ID Port ID Establish Relationships • Movements Data Set • ~170,000 North American trips • ~1,800 ports world wide • ~21,000 routes (unique pair of ports for a group of ships) Solve Waterway Network using ArcGIS Network Analyst
Ship ID Trip ID Route ID Segment ID Ship Attributes Segment Length & Area Emissions in Each Segment Estimate & Assign Emissions Emissions from Each Ship Trip
Spatial Distribution in Multimodal Context Spatial Distribution in Multimodal Context Base year 2002 inventory: applied network model (STEEM), activity based methods for “all” NA traffic
Validation: No systematic bias, but room to improve – toward convergence at all scales We are interested to learn how port-based adjustments contribute to these insights
Validation: No systematic bias, but room to improve – toward convergence at all scales We are interested to learn how port-based adjustments contribute to these insights
Future Improvement • Refine waterway network • Solve network by vessel type • Account for seasonality • Account for navigation constraints • Using ship tracking & monitoring data to: • Validate solved routes • Improve near port ship speed & load profiles • Improve estimation of hoteling emissions • Characterize temporal dynamics of ship traffic
Vessel Traffic Intensity Based on AIS Data Container Vessel Bulk Carrier Fishing Vessel Tug Boat
Acknowledgments: Collaborators, sponsors, colleagues • STEEM Model and North American Inventory: • California Air Resources Board; Council on Environmental Cooperation, EPA, other agencies • http://www.ocean.udel.edu/cms/jcorbett/sea/NorthAmericanSTEEM/ • Global inventory improvements and modeling: • Jeremy Firestone; James Winebrake; Clean Air Task Force; Prasad Kasibhatla • NOAA Right Whale Research Grant; ICTC 2k2 team; US DOT Center for Climate Change; US DOT Maritime Administration
References • Corbett, J.J., C. Wang, and J. Firestone, Estimation, Validation, and Forecasts of Regional Commercial Marine Vessel Inventories-Tasks 1 and 2: Baseline Inventory and Ports Comparison Final Report. 2006, Prepared for CARB. • Wang, C., J.J. Corbett, and J. Firestone, Modeling energy use and emissions from North American shipping: Application of the ship traffic, energy, and environment model. Environmental Science and Technology, 2007. 41(9): p. 3226-3232. • Wang, C., J.J. Corbett, and J. Firestone, Improving spatial representation of global ship emissions inventories. Environmental Science and Technology, 2008. 42(1): p. 193-199. • Wang, C., J. Callahan, and J.J. Corbett. Geospatial modeling of ship traffic and air emissions. in 2007 ESRI International User Conference. 2007. San Diego, California. • Wang, C. and J.J. Corbett, Geographical characterization of ship traffic and emissions, in Inland Waterways; Ports and Channels; and the Marine Environment. 2005. p. 90-99. • Wang, C., J.J. Corbett, and J.J. Winebrake, Cost-effectiveness of reducing sulfur emissions from ships. Environmental Science and Technology, 2007. 41(24): p. 8233-8239.
Contact Information Chengfeng Wang, Ph.D. California Air Resources Board 1001 I Street, Sacramento, CA 95812 Phone: (916) 322-1719 E-Mail: cwang@arb.ca.gov