Different sources of data on past oil spill incidents contain different kinds of information about each incident and different degrees of accuracy. The appropriate data can be used to develop spill statistics and spill rate relationships. This paper examines data on reported oil spills that have occurred in the United States. Characteristics studied include the number of spills, spill sizes, spill sources, and the types of oil spilled. Studying characteristics of past spills can help government and industry to determine the scope of oil spill prevention policies and response planning methods. The main data sources used for this paper include the Oil Spill Intelligence Report's International Oil Spill Statistics annual summaries and the National Response Center online database. This report provides a discussion of the accuracy of information from sources of oil spill data, to help support the development of spill statistics and spill rate relationships.

The Emergency Response Notification System database was searched for information on the size of spills, the sources of spills, and the types of oils spilled for both inland and coastal waters. The results of this analysis indicate that the vast majority of spills for both inland and coastal waters are minor discharges, that the sources of the spills differ for inland versus coastal waters, with pipelines representing a minor source for both water systems, and that a wide variety of materials are spilled in both inland and coastal water systems, with crude oil being a more significant contributor for coastal waters.

The Emergency Response Notification System (ERNS) is a database of notifications of releases of oil and hazardous substances reported to the National Response Center or EPA regional offices. Initial data entered is based on reports made during the incident, often before the full extent of the release is known. This initial notification data is used by EPA and other agencies to determine appropriate response actions; if ERNS data is incomplete, the responders will learn more details through follow-up phone calls and site visits. Unfortunately, additional information discovered through the response process, and from other sources, are not always incorporated back into ERNS. Thus, ERNS data are a combination of initial reports and more accurate follow-up incident data. ERNS data is widely used by the regulating and response agencies, students, environmental firms, attorneys, environmental groups, information services, and other groups for purposes ranging from regulatory decisions and site assessments to research papers and environmental “report cards.” Also, EPA's Emergency Response program uses the data for follow-up actions and to better characterize and understand the oil and hazardous substance release problem in each region. Some of these uses are significantly impacted by the inconsistencies in ERNS data collection and updates. This study will analyze several different types of ERNS “data quality,” such as data completeness and data accuracy, and will compare two or three different EPA regional offices' operating procedures and their impact on ERNS data quality. It will also evaluate which data elements appear to be most critical to “data quality.” The conclusions should help ERNS data users more effectively use the data, and should assist EPA in managing the process. Perhaps most importantly, the conclusions should help EPA shape the future of ERNS and of data management in the Emergency Response program.

This poster presentation demonstrates how geographic information systems (GISs) are being employed by the United States Environmental Protection Agency's (EPA) Oil Pollution Response and Prevention Center (OPRPC) and regional oil program offices to assist in preventing, preparing for, and responding to oil spills within the United States. Over the past 2 years, EPA's OPRPC has played a key role in facilitating the exchange of spatial data within EPA as well as with various federal, state, and local organizations. Significant advancements have been made in collecting, analyzing, managing, and sharing spatial data, and many opportunities for additional coordination lie ahead.

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