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SUMMARY Hazardous Materials Transportation Incident Data for Root Cause Analysis The objective of this project is to develop a set of potential measures that would enable offi- cials to more effectively use incident reporting databases to identify major contributors (root causes) to hazardous materials (hazmat) transport accidents for all modes of transport. The focus of this study is accidents, namely those incidents in which the vehicle or vessel was involved in a crash event (as opposed to a stationary release from a loose fitting). In the discus- sion to follow, the terms "accident" and "crash" are used interchangeably. Although multi- modal in emphasis, because hazmat truck crashes are dominant, the emphasis in this report is on hazmat truck accidents. For this project, the study team used the following definition of root cause: One or more contributing factors that lead to the occurrence of a transportation accident and/or affect the severity of its consequences. The research team recognized that in order to effectively determine the root cause of a haz- mat crash or a series of crashes, data on diverse parameters needed to be collected and analyzed. Hazardous Materials Serious Crash Analysis: Phase 2 (Battelle 2005) developed a matrix listing the parameters believed to provide a more comprehensive understanding of the accident envi- ronment. The five categories into which parameters fall are (1) vehicle, (2) driver, (3) packag- ing, (4) infrastructure, and (5) situational. In some cases, an individual parameter could shed light on root cause but, in many cases, analyses of two or more parameters are needed. In effect, a systems analysis is required. The matrix, although designed specifically for the highway (truck) mode, is applicable to other modes. The five major parameters and key variables under each are shown in Table S-1. Note that, in addition to these major parameters, institutional characteristics, such as com- pany financial condition, organizational structure, and safety culture, can play an important role in contributing to accident potential. For the purposes of this study, it is assumed that these con- siderations are embedded in the likelihood that the major parameter variables emerge as causal factors. For example, an organization with a poor safety culture is more likely to utilize a young driver with little experience and an invalid license. Chapter 2, Literature Review, describes the results of a literature review conducted for the project. The review of relevant transportation accident data collection and analysis literature over the past three decades reveals some important findings and implications regarding the current state of the art of root cause analysis. These can be separated into: (1) recognition of problems and (2) proposed solutions. As early as 1981, there was acknowledgement that analyzing trans- portation safety using empirical accident data was problematic. Since then, numerous studies have cited five basic problems: 1. Inconsistent reporting practices within and across regions, 2. Non-reporting of reportable accidents, 3. Missing information in accident report records, 1

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2 Hazardous Materials Transportation Incident Data for Root Cause Analysis Table S-1. Accident parameters. Vehicle Driver Packaging Infrastructure Situational Configuration Age Package Type Road Surface Pre-Crash Condition Cargo Body Experience Quantity Shipped Road Condition Dangerous Event GVW Condition Quantity Lost Road Type Vehicle Speed Vehicle Defect Valid License Age (Cargo Tank) Traffic Way Impact Location Vehicle Response Citation Issued Rollover Protection Access Control Primary Reason Driver Response Inspection History Speed Limit Accident Type Training Design Specification Number of Lanes Weather Condition Location Light Condition Time of Day Health Consequences 4. Inaccurate information included in accident report records, and 5. Data elements needed for root cause analysis do not appear on the report form. The literature also contains suggestions for addressing data quality problems. Among the strategies being implemented or under consideration are the following: Posting available accident data on the Internet for review and feedback regarding its accuracy, Designing standardized accident reports toward a goal of more uniform data collection, Making extensive use of electronic data entry, Using sampling techniques to target certain types of accidents, Including common identifiers in complementary accident databases so as to integrate key causal information while avoiding duplication of effort, and Providing better training for law enforcement officials and other data entry personnel to enable them to collect and process information in a consistent, complete, accurate, and more timely manner. Many of these strategies offer considerable potential, and are among those that were given careful consideration in the hazmat root cause analysis study. Chapter 3, Summary of Interviews with Carriers, Shippers, and Database Managers, gives the results of a survey (conducted by mail, phone, and in person) of carriers, shippers, and accident database managers. The results show that when carriers and shippers experience a hazmat acci- dent, several maintain accident databases that contain information that is much more extensive than the information that is required to be reported to federal databases. The investigators record environmental factors and long-term qualitative data that would be helpful in understanding how the hazmat accident occurred and, therefore, is useful for determining how the accident could have been prevented (if prevention was possible). In some instances, factors such as driver crim- inal history, crash history, and cell phone usage would have helped determine whether the acci- dent was due to the driver, which, if true, could result in an action taken to discipline or suspend the driver. In one case, corrective action was taken by a company to make the driver more aware of these external factors, enabling the driver to prevent future accidents of a similar nature. On the other hand, if factors such as existing traffic/weather conditions and functionality of trucking equipment indicate that the fault of the accident was external to the driver, a change in driving procedures could be considered. Chapter 4, Database Analysis, focuses on an analysis of the most important available databases for determining root cause. These databases include the Motor Carrier Management Informa- tion System (MCMIS); Hazardous Materials Incident Reporting System (HMIRS); Fatality Analysis Reporting System (FARS); Trucks Involved in Fatal Accidents (TIFA); Large Truck

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Summary 3 Crash Causation Study (LTCCS); NTSB analyses; Railroad Accident/Incident Reporting System (RAIRS); and Marine Information for Safety and Law Enforcement (MISLE). The MCMIS, TIFA, LTCCS, and FARS databases focus on truck crashes, NTSB investigates all commercial air- craft crashes and certain rail and truck accidents, HMIRS includes all modes, RAIRS focuses on rail, and MISLE is water based. The following provides a brief summary of the characteristics and function of each database and, where applicable, selected potential measures for improving the capability of the database for identifying root causes. MCMIS includes four major files: Registration, Crash, Inspection, and Company Safety Pro- file. The Crash file was developed in 1992 to record information on serious accidents involving a truck, bus, or light vehicle transporting hazmat. The process of reporting serious accidents begins with the state agency responsible for filing the MCMIS crash report to screen the Police Accident Reports (PARs) to identify serious heavy truck and bus accidents. Once the state report- ing agency finds an accident that meets the requirements for reporting to FMCSA, the informa- tion from the PAR for the vehicle is coded into the MCMIS Crash file format and transferred to FMCSA for MCMIS Crash file inclusion. Although the managers of the MCMIS Crash file have made great strides in improving the qual- ity of the data, additional enhancements are suggested for this database to be more useful in iden- tifying contributing and root causes of accidents. The single biggest improvement in MCMIS crash reporting would be if the existing parameter fields were completely populated. Some fields should be required to be filled, particularly those related to the vehicle, carrier, driver, route characteris- tics, and point-of-contact information. Since 2000, the DRIVER_CONDITION_CODE field has not been required. This field should be filled out again. This is the only field that captures driver performance in MCMIS. For trucks carrying hazardous materials, it is suggested that all five haz- mat fields be completely and accurately filled. Presently, in records where one or more of these fields indicates a vehicle as carrying hazardous materials, all five fields are completely filled out less than 15% of the time. The DOT number should be entered for all serious crashes involving haz- ardous materials. Currently, a DOT number is entered for only 80% of the vehicles carrying haz- ardous materials. Finally, the LOCATION field should be specified in a manner that enables the accident location to be found on a map. Presently this is the case for roughly 30% of the time. HMIRS is maintained by the Pipeline and Hazardous Materials Safety Administration (PHMSA) and can be considered to be a relational database. In accordance with 49 CFR 171.16, all carriers of hazardous materials by road, rail, water, or air must fill out DOT Form F 5800.1 and submit it to PHMSA within 30 days for a reportable hazmat incident. The reportable inci- dent could occur during loading/unloading, while in transit, or while in temporary storage when traveling between the hazmat shipment origin and its final destination. The great majority of incidents involve a hazmat spill. For a complete description of the package, vehicle, driver, and roadway characteristics asso- ciated with an accident, HMIRS must be joined with MCMIS for trucks and RAIRS for rail. Until the recent restructuring of HMIRS, the biggest impediment to joining the two databases was a lack of common fields. HMIRS now has a field to enter the DOT number and this field is being populated almost 90% of the time. The DOT number also is entered for about 90% of the MCMIS records designated as hazmat placarded. Assuming the non-reporting is random, the DOT number can be used to join about 80% of the accidents that meet both the HMIRS and MCMIS reporting criteria. Since all carriers of placarded quantities of hazardous material must register with both FMCSA and PHMSA, they must have a DOT number and there should be no blank entries in either database. The following potential measures could enhance the ability of HMIRS to identify root causes of hazmat accidents.

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4 Hazardous Materials Transportation Incident Data for Root Cause Analysis 1. Require that the DOT number be an input for all reports filed with PHMSA for in-transit incidents. 2. Perform an additional quality assurance (Q/A) check on carrier names to verify that the name being entered corresponds to the name provided on the annual PHMSA registration form. 3. Require PKGFAIL entries to be filled out for all reports submitted to PHMSA. 4. Continue to emphasize that carriers must file a Form DOT F 5800.1 if there was damage to lading systems on cargo tanks of 1,000 gallons or greater, even without a spill. 5. Capture driver condition information without compromising the confidentiality of the driver. FARS was considered in concert with the TIFA file. The FARS file is the primary national crash database for fatal traffic accidents. It is a census of all fatal motor vehicle traffic crashes. The TIFA file covers all medium and heavy trucks involved in a fatal crash, and includes virtually all FARS variables for the crash, vehicle, and driver. TIFA survey data supplement FARS data for trucks. The TIFA data include a more accurate identification and description of trucks in fatal crashes, along with details about the cargo, configuration, motor carrier operating the vehicle, and crash type. Both TIFA and FARS collect information about hazardous materials in the cargo. In the dis- cussion of the variables that identify hazmat cargo in FARS, there are reasons to believe that the TIFA file identifies hazmat cargo more accurately. Therefore, the TIFA program could be mod- ified to add the following additional information about hazmat cargo: MC number of the cargo tank. This information has been collected in the past as part of a spe- cial data collection effort, so the feasibility of collecting this information has been demonstrated. Quantity of hazardous material transported. Cargo weight could be included. The pro- gram should consider whether to capture the quantity in terms of liquid measure, where appropriate. LTCCS was designed as a one-time study to compile a comprehensive set of accident data for approximately 1,000 large truck accidents. The data compilation began in 2001 and was com- pleted in 2003, although analysis of the data is still ongoing. Comprehensive studies, such as LTCCS, are needed to obtain contributing and root causes of accidents. These initiatives can be focused on a sample of all the accidents occurring in the United States, provided that the weighting of the sampling is known. However, there are significant advantages to performing a selected number of accident investigations annually rather than per- forming a larger intensive study over a one-to-two-year period as was done for LTCCS. RAIRS is managed by the Federal Railroad Administration (FRA) as a tool to prevent railroad accidents. This comprehensive accident reporting system was implemented in its present form in 1975. FRA regulations require that all accidents in which damage to track and equipment exceeds a specified monetary threshold (adjusted periodically for inflation) must be reported using Form FRA F 6180.54, the Rail Equipment Accident/Incident Report, which records 52 different variables regarding the circumstances and cause of the accident. Beyond this, major railroads maintain their own internal databases. These typically contain all of the information necessary to comply with FRA reporting requirements, and often have additional data that indi- vidual railroads believe is useful for their own safety analysis purposes. These efforts are significant to root cause analysis in several respects. The FRA reporting requirements ensure that all accidents of consequence are subjected to an analysis of the circum- stances of the accident, and that both primary and, if applicable, secondary causes of the acci- dent be determined and reported to FRA. In some cases, these may require fairly intensive analy- sis of the accident scene if there is some uncertainty about the cause. The major railroads employ specially trained individuals responsible for performing this function. Understanding all of these aspects is pertinent to root cause analysis of hazmat releases caused by railroad accidents.

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Summary 5 The MISLE database supports the Marine Safety and Operations Programs. MISLE contains vast amounts of data ranging from detailed vessel characteristics, cargo carriage authorities, and involved party identities, to data on bridges, facilities, and waterways, to records of U.S. Coast Guard activities involving all of these and more. MISLE activities include law enforcement boardings and sightings, marine inspections and investigations, pollution and response inci- dents, and search and rescue operations. In addition, MISLE manages the information flow involving the administration of all of these activities from the initial triggering event to incident management and response, and the resulting follow-on actions. MISLE development was initi- ated in 1992 and became fully operational in 2002. Much of the MISLE database is accessible only to Coast Guard staff. Furthermore, the MISLE data become available to the general public only for closed cases, and it can take several years to close many of the MISLE-reported incidents. This might be one of the reasons why, as part of this study, it was not possible to find common events reported to both HMIRS and MISLE. In its present form, lack of timeliness, access, and interconnectivity are considered insurmountable barriers for MISLE use. The NTSB accident investigations and reports are investigations of individual accidents. While all commercial aircraft crashes are included, there are certain rail and truck accidents that are also selected for investigation by the NTSB. In order to move toward the identification of root and contributing causes, interested parties need to utilize all available data related to either a single hazmat crash or an entire population. The NTSB has developed a methodol- ogy that, through intensive detailed investigation, often leads to the identification of a root cause or causes. NTSB's detailed approach to accident investigation should provide insights to officials and researchers desiring to collect data on a particular hazmat incident or set of hazmat crashes. Potential Measures for Improving the Identification of Contributing and Root Causes of Hazmat Accidents The following measures could enhance the ability of the major databases to support more effective identification of the root causes of hazmat accidents. Development of an information system capable of capturing the data for thousands of hazmat acci- dents that occur each year. The information system would not reside in a single database and would be characterized by the following: The use of a number of relatable databases, analysis tools, and reports contained in an infor- mation system that, in their totality, include the information in sufficient detail and qual- ity to identify root and contributing causes of accidents. The capability to build on the databases that currently are used to collect information on hazmat crashes. To identify the root and contributing causes of various classes of accidents, the analyst must be able to relate inventory information to accident tables. Inventory information, including the following factors, characterizes the hazmat information system: 1. Driver characteristics (e.g., age and experience); 2. Hazmat package characteristics (e.g., tank type and age); 3. Vehicle characteristics, carrier characteristics, and mileage traveled; 4. Infrastructure information in sufficient detail to identify causal factors relating to the loca- tion of the accident; and 5. Situational information relating to the driver's decision making.

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6 Hazardous Materials Transportation Incident Data for Root Cause Analysis With this information, a regulatory analyst could mine a dataset and search for factors that are over-represented in one or more classes of accidents. Agency personnel could then use accidents where those factors are present and conduct detailed follow-up investigations to col- lect the additional information required to identify contributing causes for the selected classes of hazmat accidents. Currently, PHMSA is completing Phase I of the Multi Modal Hazmat Intelligence Portal (HIP) system. The system is being designed to acquire hazmat information to be stored at a single location. Under HIP, data from a number of agencies will be available, including finan- cial information on the carrier, shipper, manufacturer, and packaging company for Phase I. Only part of the information contained in the system will be made available to the public. Although FMCSA is participating, sharing hazmat crashes in the MCMIS database is not part of the system. The incorporation of this crash file in the future could enhance the usefulness of the system. Add inventory data in databases (truck focus). Inventory data could be added as fields in the major accident databases or supplemental databases (such as PHMSA's Registration Database or the MCMIS Census File) can be cou- pled to the accident records through the U.S.DOT number and provide insights into the car- rier's fleet characteristics and overall safety performance. Link data from HMIRS, MCMIS, RAIRS, and other information sources. Existing fields could be used to link individual hazmat crashes in different databases. Fields that describe the event location, such as latitude/longitude (lat/long) coordinates, street addresses, river and rail mile points, and Federal Information Processing (FIPS) codes, could be added and/or better quality controlled (using GIS technology) to facilitate linking of data- bases. Another opportunity to accommodate database linking is through the use of commod- ity codes, provided that a more uniform referencing system can be employed across modes. Common accident identifiers would encourage data integration, validation, and sharing. For all hazmat truck crashes, the DOT number must be correctly reported and entered into the crash file. The use of a police accident report (PAR) number would be another possibility for linking traffic accidents. To ensure that this takes place, a copy of the PAR could be sub- mitted with the crash. MCMIS also would need to enforce its rule that the report number sub- mitted to the crash file include the PAR number. From the PAR, the geographic location (using FIPS codes) and the time of the incident could be entered into MCMIS. Develop a system for each database that will target about 5% of hazmat crashes for more detailed investigation. This approach supports the ability to perform special investigations of a particular class of mode-specific accidents where a statistically significant sample is necessary. The following examples represent potential selections for this targeting: Hazmat crashes involving rollovers of tank trucks in order to more effectively identify root causes so preventive measures could be implemented; Crashes involving a particular hazmat commodity, such as propane, to determine if these accidents are over-represented as a class of accidents and, if so, what measures could be developed to decrease both their number and severity; Hazmat crashes occurring on a particular type of roadway, track class, or involving a cer- tain category of driver based on age and experience; and A random sample of all accidents for further characterization of the entire dataset. Although not exclusively for crashes involving hazmat, targeted accident data collection has already been partially implemented. FRA currently supplements selected rail accidents in the RAIRS data with about 100 detailed accident investigation reports published annually. The Coast Guard does a few detailed accident investigations and the NTSB investigates almost all air crashes as well selected serious crashes for rail and truck modes. LTCCS obtained a large number of parameters for approximately 1,000 heavy truck accidents. The TIFA approach that

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Summary 7 provides detailed analyses for all fatal large truck crashes is a feasible data collection model for this purpose because it is performed annually, relies on telephone calls to check information, and is less expensive than the LTCCS approach. The Hazardous Materials Serious Crash Analy- sis: Phase 2 (Battelle 2005) effectively applied a similar approach as that used in TIFA to a sam- ple of hazmat crashes found in MCMIS for a particular year. In addition, the project used information for the same crash found in HMIRS, wherever possible. Ensure data completeness and accuracy. Data completeness includes accidents that are not reported as well as accident reports with incomplete data. Incomplete reports can have a negative effect on accident analysis since a com- plete record of cause and effect is not captured. When the negative consequences of under- reported accidents and incomplete reporting are combined, the ability of an analyst to draw conclusions from the data is significantly compromised. To avoid this from happening, the fol- lowing measures could be taken--some of which apply to improvements that can be made to data entry while others are focused on the conduct of more thorough accident investigations: Completion of the values for all parameters; no credible information system can operate using records in which many fields are blank. Use of computerized data collection to enforce and validate data coding. Flagging of required fields in the databases such that the system will not accept the record until those fields are complete. Development of incentives to reward those who provide complete and accurate data for a database. Electronic submission of all crash reports to the major databases, such as MCMIS and HMIRS, using the Web to facilitate accuracy. Addition of "error trapping" to all databases in order to eliminate errors by applying a program that would test whether certain logical connections have been made within the same accident record. An effort to ensure that all applicable hazmat accidents are included in a database through such measures as instituting training for all who collect and enter data, and searching media reports for applicable accidents. Add additional information to enhance the ability of the databases to identify root causes of haz- mat accidents. Add latitude and longitude to all databases to provide the exact location of a hazmat crash and assist in identifying the same accident when it appears in more than one database. Add information on the quantity shipped, available from the shipping papers, and an esti- mate of the quantity spilled if there is a spill, in addition to completing the four HM fields in MCMIS (Placard Y/N, UN Number, Hazardous Material Name, and HM Class). Add the PAR number for serious hazmat crashes so they can be linked to those police reports. Include non-spill hazmat crashes in HMIRS for all crashes involving placarded shipments that meet the criteria for "MCMIS serious crashes." Include digital photos of the accident scene in all of the major databases. For HMIRS and MCMIS, include violations for drivers that occurred during the crash. Conclusion The research conducted under this project has demonstrated that there has been considerable progress during the past 20 years in the development and refinement of databases that include hazmat accidents. The project focused on identifying strategies for improving the identification of the root causes of hazmat accidents using these databases. The project findings provide researchers and officials with an overview and analysis of the individual databases and resulted

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8 Hazardous Materials Transportation Incident Data for Root Cause Analysis in many potential measures for improving specific databases. Implementation of the major measures--including establishing an information system, linking databases to take advantage of accident descriptions in more than one database, performing detailed sampling of a specific set of crashes to assemble more detailed information, and the adoption of techniques to improve data quality and completeness--could yield the greatest improvements in the ability of inter- ested parties to conduct root cause analysis. This, in turn, will enable officials to identify prob- lems whose solutions or mitigation will result in an improvement in hazmat shipment safety. Follow-On Project If implemented, the findings of this report, Hazardous Materials Transportation Incident Data for Root Cause Analysis, could lead to the enhanced identification of root and contributing causes of hazmat crashes. Implementation of the potential measures identified will present both tech- nical and institutional challenges. Consequently, the project team suggests that to evaluate the feasibility of implementation, a pilot program be implemented to demonstrate that the system will work effectively in identifying root causes. The team suggests that the pilot test involve link- ing the HMIRS database, which provides excellent data on the hazmat material and package, with the MCMIS database, which provides superior data on the driver and accident environment. These data could be supplemented by other sources such as telephone calls to carriers. Finally, the pilot test would demonstrate the system's ability to identify root causes and use these results to suggest improvements in hazmat safety.