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Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies (2011)

Chapter: Chapter 5 - Collect and Validate New Data

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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
×
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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
×
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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
×
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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
×
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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
×
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Page 54
Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
×
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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
×
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Suggested Citation:"Chapter 5 - Collect and Validate New Data." National Academies of Sciences, Engineering, and Medicine. 2011. Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies. Washington, DC: The National Academies Press. doi: 10.17226/14559.
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The project team collects new (original) HMCFS data based on the project scoping (see Chap- ter 3) and gaps in existing data (see Chapter 4). As discussed in Section 4.4, new data collection may be conducted concurrently with existing data collection, as warranted by the project’s objectives and associated data requirements. It is likely that the project team will enlist the participation of volunteers or other project participants to assist with new data collection. Figure 5-1 shows a flow chart of the HMCFS process focusing on new data collection and validation. Collection of new data specifically for an HMCFS may include the following: • Interviews with shippers and receivers, carriers, emergency managers and responders, and other key informants; and • Traffic surveys ranging from very simple truck counts to much more complex examination of shipping manifests. 43 C H A P T E R 5 Collect and Validate New Data Considerations for New Data Collection Collection of new data tends to be focused on roadway commercial and service truck transport because • Locally relevant hazmat transport data for roadways are generally lacking or more difficult to obtain from existing data sources. • Locally relevant hazmat transport data for non-roadway modes (railroad, waterway, and pipeline) are generally available from existing data sources. • Roadways often serve as connectors to railroad, waterway, pipeline, and air terminals. New data also may be collected for other modes, particularly railroads, when traffic variation by time of day, day of week, or season of the year are desired. Procedures for new data collection that are discussed in this guidebook for roadways are conceptually similar to new data collection procedures for other modes. 5.1 Conduct Interviews Hazmat shippers, receivers, and carriers; emergency managers and responders; and other key informants can be interviewed by the project team about their knowledge of hazmat transport, including what is transported, to/from where, when, and how. This step goes beyond simply requesting existing information from these sources as described in Chapter 4. Interviews can be

44 Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies Figure 5-1. The HMCFS new data collection and validation process. Things to Consider When Conducting Interviews • The potential number of interviews is large and correspondingly time consum- ing, so a listing of contacts should be developed and prioritized. • Interview information can be tabulated or written in list or paragraph form and summarized for each shipper, hazardous material, transport mode, etc. • Although conducting interviews can be intimidating, the process becomes easier as interviewers become more experienced. • The amount of information from interviews can seem initially overwhelming. Tasking a subcommittee with conducting and compiling interview data can yield a great deal of information over time, especially if interviews are con- ducted on an on-going basis (for example, each subcommittee member con- ducts one interview per week).

helpful for developing a general understanding of transport patterns within a jurisdiction or those originating and terminating in a jurisdiction. Extensive interviews are needed to develop an empir- ical understanding of hazmat transport over a network. Interview information also is important for guiding data collection, including verification of data collection locations and times. 5.1.1 Interviews with Hazmat Shippers, Receivers, and Carriers For entities that are known to store hazmat (Tier II or locally required reports may be a source of this information), or entities that are located along or known to ship/receive/carry hazmat over transport corridors that are of key interest, suggested interview discussion points include the following: • What hazardous materials are shipped/received/carried? • What is the origin, destination, or both, of the hazardous mate- rials? • When are the hazardous materials shipped/received/carried by time of day, day of week, season of year, etc., and what is the fre- quency of shipment? • How are the hazardous materials shipped/received/carried (modes)? • Over what transport routes are the hazardous materials carried? • How much (number of shipments, volumes, etc.) hazardous material is shipped/received/ carried? 5.1.2 Interviews with Emergency Responders and Managers, and Other Key Informants Emergency responders deal with hazards on a daily basis and are a valuable source of real-life information. Ultimately, they are among the primary beneficiaries of the HMCFS, but they may be skeptical about the value of the effort if they are not familiar with the concept. Including emer- gency responders on the interview team can go a long way toward enhancing the quality of infor- mation provided and understood by interviewers. Keep in mind that local jurisdictional and “turf” issues may also affect the type and amount of information that can be obtained in inter- views. Buy-in and approval from senior agency officials may help encourage staff participation. Suggested interview discussion points for emergency management and response personnel, or other key informants, include the following: • With which areas of the jurisdiction are you experienced? • What have you observed regarding locations, times, methods, frequency, and content of haz- mat transport? • Are there corridors or network segments that seem to be a higher priority for understanding hazmat transport? If so, do you have suggestions for data collection locations and times? • Are there particular locations that are a higher risk for truck incidents and accidents than others? • Do you know of other individuals who should be contacted about hazmat transport in the jurisdiction? 5.2 Considerations for Field Data Collection The bulk of the effort for the project team and project participants for most HMCFS projects will be the collection of new data about hazmat transport by roadways. This is because obtaining locally specific information about hazmat transport by roadway usually requires some form of Collect and Validate New Data 45 Communicating with facilities and carriers is one way of obtaining commodity flow infor- mation. Cambria County LEPC in Pennsylvania talks with local industry plant managers to verify the types of hazmat shipments identi- fied through vehicle and placard counts. They use information provided by railroads to ver- ify railcar and placard counts.

traffic survey through human observation. Existing data sources provide information at state or national levels, and although many large metropolitan areas and states have implemented moni- toring systems on key transportation routes, typically, the systems are not very useful for describ- ing hazmat-specific transportation information. Also, vehicle-mounted sensor systems (e.g., RFID tags) for public monitoring of truck traffic and hazmat cargos are not on the immediate horizon. This does not mean that truck traffic information that was collected using automated systems is not useful for an HMCFS. Truck traffic volume data can be used to identify locations where hazmat data collection may be focused or be used to validate manual count information. Infor- mation about daily and seasonal variations in truck traffic patterns also can be identified from data collected by automated traffic counter systems, and weigh-in-motion (WIM) data can be used to estimate proportions of empty versus loaded trucks. General and truck traffic levels can be used to identify locations and times where the driving population may be at greater risk for hazmat incidents, or where roadway congestion will present response challenges. These data are typically maintained by state transportation agencies. However, trends for overall truck traffic may not directly apply to hazmat truck traffic, especially where seasonal variations in hazmat production, processing, or consumption apply. 46 Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies Considerations for Selecting Traffic Survey Locations • The safety of data collection personnel and the driving public is paramount. Consider Incident Command System principles in planning to collect new data, as applicable. • Data collection personnel require a clear view of the roadway section(s) for which they are to collect information. Visibility requirements for placard counts may be more restrictive given placard sizes. • Intersections allow data collectors to identify the turning movements of vehicles, including the road that the vehicle is turning from and the road onto which the vehicle is turning. • Parking lots of fueling stations, shopping centers, abandoned buildings, high- way maintenance, and material storage lots, roadway turnouts, or drives in the public right of way can make good data collection locations. License and weight stations (when open) also can be good data collection locations. • Nighttime counts require sufficient lighting to allow identification, vehicle type, placards, or other factors. Lighting also should provide sufficient driver visibility to assure safety of data collectors and the driving public. • Dry grass, weeds, or other debris under running (or hot) vehicles can ignite fires. • Selecting locations that do not impede or endanger the driving public or incon- venience property owners is essential. Permission for collection of data on pri- vate property should be obtained when necessary. Objections are rare when property owners understand the purpose and nature of the data collection, provided that business and personal activities are not impeded. • Coordination with local emergency management and law enforcement is important to provide pubic legitimacy, promote participation, and enhance use of the results. Passers-by may report traffic observers as engaging in suspicious activities, especially around industrial facilities or military installations. A letter about the data collection effort from the LEPC or other local agency may be useful to help answer questions from law enforcement or security personnel who are following up on such reports.

Traffic surveys for an HMCFS involve collecting vehicle, placard, or shipping manifest infor- mation, or combinations of these tasks. The traffic observations are recorded and analyzed to describe hazmat flows, as discussed in Chapter 6. It is important that traffic surveyors be able to collect data safely, efficiently, and effectively. 5.2.1 Determining Count Intervals Many LEPCs and other local entities use volunteers for HMCFS data collection. Time and schedule availability may be limited for volunteers, and data collection may be conducted dur- ing times of extreme temperatures—very cold or very hot—requiring data collection to be per- formed from the inside of vehicles. Attention and accuracy of data collection are limited to a few hours at a time per individual, maximum. Thus, there needs to be a balance between traffic count intervals that are optimal and those that are practical. Following are some recommendations for determining count intervals. • Using count intervals in even fractions of an hour simplifies the extrapolation of counting seg- ments into 1-hour periods; 1-hour counts are preferred, and 30-minute or 15-minute counts are secondary options. • Conducting at least 30-minute or 1-hour counts reduces the effects of traffic variation while providing sufficient timeframes for recording traffic counts. • Longer count durations are possible, but they should be recorded in separate 30-minute or 1-hour segments. • Starting count intervals on the half-hour or hour can ease data analysis for differences in traf- fic patterns by time of day. 5.2.2 Training Data Collectors Maintaining consistency and accuracy of collected data directly affects the validity of HMCFS conclusions. This can be particularly challenging when using volunteers who have a variety of edu- cational training and occupational backgrounds. Key members of the project team should prac- tice and be familiar with all types of data collection methods that will be used for the project—for example, vehicle counts, placard counts, interviews—before providing training to other project participants. Not only will this help identify data collection pitfalls, needs, and procedures, but it also can help validate that the data collection locations, information, and sampling/precision requirements are appropriate to meeting the project’s objectives. After the key members of the project team understand the data collection process and requirements, they can provide training to other team members. Training can include the following, as applicable: • Safety procedures, notifications, and scheduling/coordination of data collection; • Methods for identifying vehicles; • Methods for identifying placards; • Procedures for recording data; • Recommended locations for data collection; • Recommended interview questions; and • Other information relevant to the HMCFS project. Training can be performed through presentations at general meetings, specific training meetings, individually, or in small groups. It also will be helpful to include “real-time” data collection exer- cises at the end of training sessions to provide trainees with an opportunity to work through the “nuts and bolts” of vehicle or placard observations and data recording procedures. It is important to remember that conducting traffic surveys can seem intimidating at first for many volunteers, but the process soon becomes much easier for data collectors as they gain experience. This can be facil- itated by having data collectors work in pairs, especially in the initial stages of a data collection effort. Collect and Validate New Data 47

5.2.3 Scheduling Data Collection (Sampling) Keeping in mind the physical and practical limitations of traffic data collection, the goal for sur- veying trucks or other vehicles is to collect information that is sufficient to identify the following: • General traffic patterns and • Differences in traffic patterns for different days and times, as required by objectives. The sampling framework used for data collection should be driven by the HMCFS objectives (discussed in Section 2.2), the type and level of traffic that is observed, and the need to identify differ- ences in traffic patterns for different times of the day, different days of the week, from week to week, or month or season of the year. Obviously, a greater amount of good quality, well sampled data increases the potential reliability of hazmat and traffic flow descrip- tions. However, more data requires more time for collecting, pro- cessing, analyzing, and validating. As with any study that involves sampling, there is a trade-off between data collection feasibility, efficiency, and the ideal. In many cases, the goal of an HMCFS may be to develop a general understanding of the characteristics of hazmat flow patterns. This often can be accomplished using low-level sampling frameworks and limited data. As the critical nature of HMCFS objectives increases, high-level sampling frameworks and more data may be required. Table 5-1 provides a summary of traffic sampling framework examples, as well as the advantages and disadvantages of each. Appendix D.2, Let HMCFS Objectives Guide Sampling, 48 Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies The LEPC in Polk County, Texas, used a focused data collection effort on two major highway corridors for their commodity flow study. Overall project direction was handled by the county’s emergency management office. Data collection on one corridor was scheduled and coordinated by a volunteer fire chief. Data collection on another corridor was scheduled and coordinated by a pipeline com- pany employee. Volunteers from three local volunteer fire departments, a local amateur radio club, a county commissioner, and a city mayor all participated. Truck and placard counts for each corridor were collected over a 1-month period, and all days of the week and times of day were covered. Sampling Framework Sampling Examples Advantages Disadvantages Convenience As available for data collectors Easiest for data collectors; minimum scheduling management Difficult to reliably identify traffic patterns at any one location or timeframe Representative One location per major roadway, at different times of day on any given weekday, during any season Easy to conduct over time for data collectors; moderate scheduling management; moderate degree of information about traffic patterns for roadway; low–to-moderate level of data collection resources required Cannot be used to reliably characterize traffic on different segments of same road or other roads, determine seasonal traffic patterns, or transport patterns throughout a network Cluster Multiple locations per major roadway, at different times of day, on multiple days of week, during multiple seasons High degree of information about traffic patterns throughout a transportation network High degree of scheduling management; may require high level of time commitment from data collectors or other data collection resources Stratified or Proportional Dependent on traffic characteristics on given network segment; less data are required for low traffic volumes, and more data for high traffic volumes Very high degree of information about traffic patterns throughout a transportation network; focuses effort on high-priority segments Requires statistical calculations to determine sampling requirements; extremely high degree of scheduling management; may require high level of data collection resources Random At random times of day, days of week, seasons of year, for a specific network segment Very high degree of information about traffic patterns on sampled network segment Requires statistical calculations to determine sampling requirements; extremely high degree of schedule management; requires high level of data collection resources Census All traffic data for all times of day, days of week, and seasons of year, for specific network segment or entire network Complete information about traffic patterns at sample locations Nearly impossible to attain with current systems; requires an extreme degree of data reduction Table 5-1. Sampling frameworks, examples, advantages, and disadvantages.

Collect and Validate New Data 49 For More Information About Sampling Local entities that are concerned about sampling requirements are encouraged to • Review Appendix C.2 and Appendix H. If you still have questions, seek the advice of a transportation planner, consultant, university faculty member, or other individual with training in statistical sampling and traffic analysis. • Review other sources of information about traffic data collection and sampling, including – Traffic Monitoring Guide (TMG), U.S.DOT, Federal Highway Administration, Office of Highway Policy Administration, 2001. Available online at http://www.fhwa.dot.gov/ohim/tmguide/. Oriented to traffic data collection by state DOTs, it includes discussions about sampling considerations and truck data collection using FHWA’s vehicle classification system. – Introduction to Traffic Engineering: A Manual for Data Collection and Analy- sis, Thomas R. Currin, Thomson Learning, 2001. An easy-to-use overview of different data collection techniques for various traffic studies, including data collection at intersections. – Traffic Engineering Handbook, 6th Edition, edited by Walter H. Kraft, Institute of Transportation Engineers, 2009. The primary reference for transportation engineering professionals. It includes chapters on traffic characteristics, sam- pling, and analysis. suggests guidelines for matching HMCFS objectives with sampling frameworks. Appendix E contains additional information about data collection using the different sampling frameworks. 5.2.4 Determining Precision of Traffic and Hazmat Data The precision of traffic and hazmat characterization data also determine what can be identi- fied about hazmat flows in a community. Traffic information may include the following: • Number of vehicles observed (e.g., trucks), discussed in Section 5.3.1.1; • Types and configurations of vehicles observed (e.g., van versus flatbed trucks, straight trucks versus tractor-trailer trucks, etc.), discussed in Section 5.3.1.2; • Types of hazmat placards observed, discussed in Section 5.3.2; • Combinations of vehicle and hazmat placard observations, discussed in Section 5.3.3; • Vehicle and/or hazmat placard observations on both roadway directions or at intersections at the same time, discussed in Section 5.3.4; or • Number of containers or packages in a shipment—this can be considerably difficult for most truck traffic surveys to determine, except for shipping manifest surveys, discussed in Section 5.3.5. Hazmat characterization information may include the following: • Whether a vehicle is carrying hazmat over placarding threshold levels (e.g., whether a truck does/does not have a placard); • Hazmat class or division (e.g., as indicated by type of placard); • UN/NA placard ID number (e.g., as indicated on a placard or on the side of a tank); or • Specific material/chemical information, which can be considerably difficult for most truck traffic surveys to determine, except for shipping manifest surveys.

Together, information about traffic levels and hazmat content will be used to develop an understanding about when, where, and how much hazmat is being transported in a jurisdiction, as discussed in Chapter 6. Appendix D.3, Let HMCFS Objectives Guide Precision, contains further information about matching HMCFS objectives with data precision requirements. Table 5-2 pro- vides a summary of various traffic and hazmat content survey methods that can be used to obtain different levels of data precision and identify the commodity flows—quantities and characteri- zation of transported hazmat. 5.3 Collect Field Data The project team members and other project participants collect field data after sampling and precision levels have been determined, the survey method has been selected, survey locations have been identified, and data collectors have been trained. As discussed in the previous section, collection of most new HMCFS data will be through manual surveys of commercial truck traf- fic. Focusing the surveys on certain sizes of commercial vehicles—for example, DOT Class 3 trucks and above (over 10,000 lbs. gross vehicle weight)—helps the project team focus data col- lection on vehicles most likely to be transporting hazmat. Appendix J.1 contains sample images of truck types and configurations, as well as placard con- figurations. It can be used as a “cheat sheet” for data collectors. The truck types and configuration examples are grouped in eight different categories (“A” for standard gas and liquid tanks through 50 Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies Survey Method Description What It Provides What It Requires Total Truck Surveys A count of the total number of observed trucks Information about overall truck traffic levels during sampled time periods Assumptions about hazmat transported on observed trucks (e.g., that hazmat transport conforms to national averages); assumptions about types and configurations of trucks used to transport hazmat Truck Type and Configuration Surveys A count of observed trucks by truck type and configuration Information about truck traffic levels, by type and configuration, during sampled time periods Assumptions about hazmat transported on observed trucks by type and configuration (e.g., that hazmat transport conforms with national averages) UN/NA Placard ID Surveys ID and count of observed hazmat placards Information about the number and types of hazmat placards present during sampled time periods Assumptions about truck traffic patterns and the types and configurations of trucks used to transport hazmat Total Truck Combined with UN/NA Placard ID Surveys A count of the total number of observed trucks and ID and count of observed hazmat placards Information about overall truck traffic levels and the number and types of hazmat placards present during sampled time periods Assumptions about types and configurations of trucks used to transport hazmat; data collectors who can record truck count information and placard information Truck Type and Configuration Combined with UN/NA Placard ID Surveys A count of observed trucks by truck type and configuration and ID and count of observed hazmat placards Information about truck traffic levels by type and configuration and the number and types of hazmat placards present during sampled time periods Data collectors who can record truck type and configuration and placard information; may require more training of volunteers on data collection process and monitoring of collected data to ensure consistency Directional and Intersection Surveys Observation of trucks and/or placards on multiple road directions or at intersections at the same time Information for more than one roadway lane collected at a single location; may reduce number of data collectors needed Experienced data collectors; more training of volunteers on data collection process, and monitoring of collected data to ensure consistency Manifest Surveys Review of information found on shipping papers and interviews of truck drivers Highly specific information about hazmat shipment content for both placarded and unplacarded loads Coordination with local, state, or federal license and weigh stations or patrol units; potentially, a very intensive data collection process for high-traffic roadways Table 5-2. Traffic and hazmat placard survey methods.

“H” for other trucks). The truck type and configuration categories are the same as the VIUS cat- egories identified in Appendix H. These groupings are useful because they differentiate between truck types and configurations that are more and less likely to be carrying hazmat. The placard identification examples are taken from the 2008 ERG (5). The cheat sheet only provides truck and placard examples, and is not exhaustive of all truck types and placards. See Appendix H and the 2008 ERG for more information about the truck and placard types included in each category. Several different truck or hazmat placard surveys are described in this section, ranging from simple truck counts to complex truck type and configuration and placard ID counts at intersec- tions. The selection of a particular survey method will depend on the following: • Level of information needed to support HMCFS objectives; • Local conditions (e.g., visibility); • Traffic levels; • Available data collection resources (e.g., number of data collectors); • Ability of data collectors; and • Assumptions that the project team is willing to make about truck or hazmat traffic patterns. Traffic survey information may be recorded using a variety of mechanisms, but a simple clipboard with tabulation sheets should work effectively for most applications. The tabulation sheets should include the following information: • Location and direction of roadway, • Date and day of week, • Time period (start and end), • Data collector name(s), • Weather conditions, • Page numbers (if multiple pages used for same location/date/time period), • A location for notes or comments about data collection, and • Vehicle count information. Accurate documentation is key to data usability. Complete and accurate documentation may be highly variable when multiple data collectors participate in the project. The project team should be sure that each data collection record is properly completed and documented, especially for location and direction, date and day of week, and time period fields. This information also can be used to help track volunteer effort expended (remember that travel time and mileage to and from data collection locations can be additional when used for in-kind match). Data collection sheets are provided in Appendix J for each survey type, which are discussed in the following sections. Application of survey data for identifying hazmat flows is summarized in Table 5-2, and use of survey data for estimating hazmat flows is described in Appendix K. The project team should review these sections before selecting a commercial vehicle survey method for the HMCFS. 5.3.1 Commercial Vehicle Surveys 5.3.1.1 Total Truck Surveys Surveys of the total number of commercial vehicles (trucks) are usually very easy for data col- lectors to conduct: they simply count the number of commercial vehicles that are observed at individual locations during a specified timeframe, and make a “tally mark” (in sets of five) on a data sheet for each count. A blank total truck count sheet and a completed example sheet are provided in Appendix J.2. The sheet provides for seven different truck count periods. If additional space is needed for each time period, simply continue on the next line or next page, making sure to note that the time periods are the same. Remember that using these data will require assump- tions about the types and percentage of vehicles carrying hazardous materials—for example, that Collect and Validate New Data 51

national-level percentages of hazmat transport by truck apply to the location. Use of these data for estimating commodity flows is discussed in Appendix K.4. 5.3.1.2 Truck Type and Configuration Surveys Other information about types of commercial vehicles can be collected in addition to total vehicle counts. Most DOT vehicle classification counts by automated systems use FHWA’s des- ignation of vehicle class by tonnage and number of axles per vehicle. This type of information is not very useful for hazmat classifications. Rather, trucks can be classified according to cargo body types and configurations as discussed above. These counts will allow national averages for haz- mat transportation, by hazmat class and division, to be applied for each truck type and config- uration, rather than a national average for all trucks regardless of type and configuration. This also may serve as a basis for identifying future changes in truck traffic patterns in the jurisdic- tion, and may provide information useful for other local planning applications (i.e., transporta- tion planning)—for example, some truck types are more frequently heavier or overloaded than others, which affects roadway infrastructure maintenance cycles. Appendix H shows how the 2002 VIUS data were evaluated for truck cargo body types and configurations relative to hazmat transportation. A blank sample truck type and configuration count sheet corresponding to the VIUS categories and a completed example sheet are provided in Appendix J.3. A different sheet should be used for each count period. Remember that using these data will require assumptions about the percentage of vehicles that are carrying hazardous materials, for example, that national-level percentages of hazmat transport by truck type and configuration apply to the location. Use of these data for estimating commodity flows is dis- cussed in Appendix K.5. 5.3.2 UN/NA Placard ID Surveys A count of hazmat placards provides better information about the types of hazmat transported in an area than simply counting trucks and assuming that a certain percentage of them carries hazardous materials. The goals of a placard count are as follows: • To identify whether a vehicle is placarded or has a UN/NA placard ID; • To identify the class/division of the transported material(s), which is indicated by color and pattern of placard (see Appendix A); and • To identify information—words or numbers—written on the placard (see Appendix B). Addi- tional markings may be present on the vehicle/vessel, for example, an orange UN number on ISO tanks and some tank trailers, or “Marine Pollutant.” Some vehicles do not have a hazmat class/division or 4-digit placard ID, but use a “Dangerous” placard for when they are transport- ing combinations of hazardous materials above threshold quantities. The data collection procedure for UN/NA placard ID counts is similar to the procedure for truck counts, except that instead of counting trucks, the placard information is recorded. Because placarded trucks only make up around 4 to 5 percent of commercial trucks, on average, this may result in relatively low placard counts for many locations and time intervals. A blank placard count sheet and a completed example sheet are provided in Appendix J.4. Multiple placards on the same truck should be circled to differentiate between all placards observed and the number of placarded trucks observed. The sample sheet provides for seven different truck count periods. Remember that this type of data count will not provide information about the types and con- figurations of trucks carrying the hazardous materials or traffic levels, so it has limited applicabil- ity for some HMCFS objectives (for example, maximum scenario definitions). It is also important 52 Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies

to remember that vehicles carrying less-than-placard-threshold levels can still be carrying haz- ardous materials, so a count of placarded vehicles will not yield a complete picture of hazmat transport. Use of placard count data combined with truck count data for estimating commodity flows is discussed in Appendix K.6. Use of placard ID data for estimating commodity flows is dis- cussed in Appendix K.7. 5.3.3 Combined Commercial Vehicle and UN/NA Placard ID Surveys 5.3.3.1 Total Truck and UN/NA Placard ID Surveys A more intensive data collection technique is to combine truck counts with UN/NA placard ID counts. Observations of placards and trucks are recorded for the same locations and times. This allows for both identification of the percentage of placarded trucks for the time period, and identification of the hazmat placards. A blank sample truck and placard ID count sheet and a completed example sheet are provided in Appendix J.5. Multiple placards on the same truck should be circled to differentiate between all placards observed and the number of placarded trucks observed. The sample sheet provides for four different truck/placard count periods. Remember that this type of data count will not provide information about the types and con- figurations of trucks carrying the hazardous materials or traffic levels, so it has limited applicabil- ity for some HMCFS objectives (for example, maximum scenario definitions). It is also important to remember that vehicles carrying less-than-placard-threshold levels can still be carrying haz- ardous materials, so a count of placarded vehicles will not yield a complete picture of hazmat transport. Use of these data for estimating commodity flows is discussed in Appendix K.8. 5.3.3.2 Truck Type and Configuration and UN/NA Placard ID Surveys A combined count of truck type and configuration and hazmat placard IDs increases the com- plexity of the data count. These counts can be used to identify overall truck traffic levels, propor- tions of truck traffic by type and configuration and the percentages of placarded trucks for each category, and identification of the hazmat placards. This information also can be used for rough estimates of relative quantities (small, medium, or large amounts) of transported hazardous materials—for example, depending on their configurations, a straight tank truck may have a capacity of around 3,000 gallons while a tractor-trailer tank truck may have a capacity of around Collect and Validate New Data 53 Things to Keep in Mind for Conducting Placard Surveys Placard surveys require observation of placarded vehicles as they pass by data col- lection locations. Good visibility of the observed traffic lanes is required, and an experienced data collector who is using binoculars is beneficial. Although this counting technique results in direct information about the hazmat transportation patterns in an area, it is more specific and difficult to conduct than truck type counts for the following reasons: • Placards are less than 1 square foot in size, and placard numbers are 3.5 inches tall. • Although vehicles are required to display placards on front, side, and back of the transported unit, the placement of the placards is not the same for each vehicle. • High speeds and congested traffic can make it difficult for even experienced observers to identify every placard, especially when placards are obscured by other vehicles.

9,000 gallons. Also keep in mind that many tank trailers with placards on them are empty and either cleaned or—more likely—contain residual product. A blank truck type and configuration and placard ID count sheet and a completed example sheet are provided in Appendix J.6. Multiple placards on the same truck should be circled to differenti- ate between all placards observed and the number of placarded trucks observed. Separate count sheets should be used for each period. The spacing provided in rows for different truck type/ configurations should accommodate either the number of tally marks for trucks or identification of hazmat placards for most roadways for a 30-minute count. Multiple sheets may be used if needed during the same time period, noting the multiple page numbers for the same time period. Use of these data for estimating commodity flows is discussed in Appendix K.9. As with other counts of placard ID information, it is important to remember that vehicles carrying less-than- placard-threshold levels still can be carrying hazardous materials, so a count of placarded vehi- cles will not yield a complete picture of hazmat transport. Although collection of combined truck and placard data is manageable for a single data collector for roads with low traffic volumes, it can be particularly challenging for high-traffic-volume locations. For these locations, it is almost essential to have data collectors working in pairs. 5.3.4 Directional and Intersection Surveys The truck and placard ID traffic survey examples provided in Sections 5.3.2 and 5.3.3 assume that data are collected for only one direction of a single roadway per time period. Another level of complexity is for recording traffic data for both roadway directions, and/or at a three-way or four-way roadway intersection. For example, rather than having eight data collection locations for a four-way intersection (one for each direction of each roadway segment), the information can be collected at a single location. Potentially, this can reduce the number of data collectors needed, but it also can be a very intensive effort for busy roadways or intersections, and is best accomplished using experienced data collectors. A blank sample data sheet is provided in Appendix J.7 that can be used for collecting truck type and configuration (corresponding to the VIUS categories) and placard ID information for both directions of a roadway, or at an intersection. Each data sheet provides for recording information for up to 25 trucks. For each truck, the truck type, configuration, placard ID, and directional infor- mation (as applicable) are recorded by circling the corresponding categories. Each truck type cate- gory is listed for groups “A” through “H” as shown on the example sheet provided in Appendix J.1. Truck configurations are shown for straight trucks (ST), tractor-trailers or straight trucks with a trailer (TT), and tractor with multi-trailer (MT) configurations. Placard categories are provided for the nine hazmat classes along with a tenth category for other placards, e.g., “Dangerous,” “Marine Pollutant,” etc., and there is space for recording more specific placard information such as numbers or words. “Un” is used to identify “unknown” or “uncertain” information for all categories. The sheet also allows for identification of directional movements for both directions of a road- way or for turning movements at intersections. If recording both directions of a single roadway (and not at an intersection), the data collector can indicate the direction of travel for each truck (e.g., “NB” for northbound trucks, or “SB” for southbound trucks). This can be done using either the “Approaching On” or “Departing On” columns—although both columns are marked in the example sheet, using both columns is not absolutely necessary for single-direction truck traffic surveys since the directions are the same for an individual truck. (That is, in single-direction sur- veys, all northbound trucks continue northbound. In this case it would be possible to use only one column to indicate direction.) If recording data at intersections, the data collector indicates the direction that the truck was travelling when it approached the intersection and the direction a truck was travelling after it 54 Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies

turned (departed the intersection). For example, a truck approaching northbound toward an intersection would be indicated as NB in the Approaching On column, and if it turns eastbound at the intersection would be indicated as EB in the Departing On column. For roads and inter- sections that do not correspond directly to north, south, east, and west, the data collector may have to adopt these directions as frames of reference, and be sure to note which direction corre- sponds to which roadway segment, etc. Since each count sheet provides for collection of data from only 25 trucks, it is likely that many data sheets will be needed for a single count period on a busy roadway or intersection. This type of data collection effort, data processing (tabulation), and analysis can be intensive. For addi- tional information about collecting, processing, and analysis of intersection data, see the sources provided earlier in this chapter in the example titled “For More Information about Sampling,” or seek assistance from a transportation engineering or planning professional. These sources may also provide examples of alternate directional or intersection traffic survey data collection sheet configurations. Analysis of these data will be similar to data analyzed in Appendix K.4 through K.9, depending on the type of data that were collected. 5.3.5 Shipping Manifest Surveys Shipping manifest surveys can fill an important information gap for hazmat traffic flows since they can be used to identify hazmat shipments in both placarded and unplacarded vehicles, ship- ment sizes and packing methods, specific materials, and shipment origin and destination (which can yield information about how the vehicle will travel through a jurisdiction). Unfortunately, shipping manifest surveys also can be the most labor-intensive manual hazmat traffic survey to conduct. In this method, access to trucking shipping manifests is obtained by working with license and weight bureaus of authorized local and state police services, or similar vehicle inspection author- ities. Shipping manifests are reviewed as part of the inspection process, and truck drivers may be interviewed regarding their most likely route. Shipping paper information of interest from the 2008 ERG (5) is shown in Appendix B, but it should be noted that information formatting and location on shipping papers is widely variable. DOE has conducted shipping manifest studies for 24-hour continuous counts at license and weigh stations in cooperation with state enforcement agencies. Information collected includes the following: • Time of day, • Shipment origin/destination, • Truck type, • Placard class/division and UN/NA ID, • Material description, and • Shipment weight. Additional information from driver interviews also may be recorded. Depending on the infor- mation desired, a table or chart can be used for multiple truck manifests, or a single page or a notebook may be used for each truck or manifest record. 5.4 Validate New Data The new data are validated as they are collected and compiled by the project team. Validation helps ensure that the collected new data meet the data requirements of the HMCFS objectives. This can be done in advance of the actual data analysis. For example, users might ask themselves, Collect and Validate New Data 55

does precision of collected data match data requirements? What other information might help meet the HMCFS objective data requirements? Addressing the following additional concerns helps the project team underscore the validity of the HMCFS data: • Are data appropriately documented? • Are there data outliers or questionable values? • Are data collected at similar locations consistent? • Is information consistent across different sources (existing and new data from interviews, databases, surveys, etc.)? Hopefully, an HMCFS project has many different participants. However, a commonly con- tributing factor to data validity problems is the fact that the data are collected by people. This is an inherent source of error in every project using human data collectors, and it is impossible to avoid. Data validity concerns identified by the project team early in the data collection phase can be addressed much more easily than at the end of data collection. The project team may wish to review the data collection procedures with volunteers, make sure that new data collection loca- tions enable accurate and efficient data collection, and review the data collection sampling and precision frameworks versus the data requirements. Remember that at least some variation in traf- fic should be expected and may be substantial for certain locations. Further validation of the data will take place as data are analyzed. Analysis of HMCFS data is described in Chapter 6. 56 Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies

Next: Chapter 6 - Analyze and Document Data »
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TRB’s Hazardous Materials Cooperative Research Program (HMCRP) Report 3: Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies is designed to support risk assessment, emergency response preparedness, resource allocation, and analyses of hazardous commodity flows across jurisdictions.

The guidebook updates the U.S. Department of Transportation’s Guidance for Conducting Hazardous Materials Flow Surveys. All modes of transportation, all classes and divisions of hazardous materials, and the effects of seasonality on hazardous materials movements are discussed in the guidebook.

The contractor’s final report and appendices (unedited by TRB), which documents the research supporting the development of the guidebook, are available online.

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