Assessing the Accuracy of Self-reported Pollution Data

Duke University, Durham NC

Investigators

Abstract

Information provision is increasingly used as a regulatory tool. The Environmental Protection Agency's Toxics Release Inventory (TRI) program requires manufacturing facilities that handle threshold amounts of specific chemicals to report yearly their releases and transfers of these toxic substances. This project investigates how accurate TRI data are and what factors give rise to errors or evasion in self-reporting. The proposed research uses two different methods to assess the accuracy of TRI data. For 12 of the chemicals covered by TRI reporting, the EPA samples air concentrations of these chemicals using a network of monitors across the country. Geographic information systems (GIS) software allow one to determine which polluting facilities are within range of the EPA's monitors. The researchers can thus compare how measured trends in pollution from monitoring data match self-reported trends on air releases by the polluting facilities. To investigate potential divergences between the monitoring data and TRI figures, the analysis will also explore how the nature of the surrounding community, state environmental enforcement, and company and facility-level characteristics affect the apparent accuracy of the reported TRI air emissions. The comparison of reported TRI figures with expected distributions of emissions digits offers a second way to assess the accuracy of pollution data. The key insight is that if facilities are estimating emissions with a downward bias, the overall distribution of digits will not follow the same pattern as the actual digits in the monitor data. This research will demonstrate the degree that selected physical monitoring and analysis of data patterns for statistical bias can help determine the accuracy of self-reported data.