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Analyze and Document Data 59 Table 6-1. Hazmat flow data characteristics, by source, for railway, pipeline, waterway, and airway transport modes. Hazmat Commodity Flow Data Characteristics Trans. Hazmat Commodity Mode Flow Data Source Spatial Temporal Metrics/ Material Sampling Applicability Framework Units Description Framework Railway, Variable, includes Annual, Value, Pipeline, BTS Commodity Flow overall hazmat, Stratified State/national every 5 tons, and Waterway, Survey class/division, (national) years ton-miles Airway and UN/NA ID Railway, Pipeline, FHWA Freight Analysis Value and State/national Annual SCTG Variable Waterway, Framework tons Airway STB Carload Waybill Regional/state Shipment No. of tons Specific Stratified Railway Sample data (assume routes) date or carloads commodity (national) As provided Railroad carrier As provided No. of Census (for Railway Local network (class, specific information (annual) carloads hazmat) commodity?) PHMSA National Pipeline Assumed Assumed Crude, nat'l. gas, Assumed Pipeline Local network Mapping System continuous continuous petrol. prods., etc. continuous Commodity Waterway USACE reports Local network Annual No. of tons Census groups USACE reports with Commodity Waterway commodity code/ placard Local network Annual No. of tons groups w/assoc. Census ID cross reference UN/NA IDs As provided No. of tons USACE reports with As provided Waterway Local network (seasonal or or Census carrier, facility info (spec. commod.?) monthly?) shipments 6.2 Truck/Roadway Data Analysis The project team has many approaches for analysis of existing and new roadway data, depend- ing on the type of information collected. Examples of these approaches are summarized in Tables 6-3 and 6-4. Table 6-3 lists hazmat flow characteristics and Table 6-4 lists hazmat flow data analy- sis output characteristics for these examples. Table 6-4 also lists the level of HMCFS objective to which these approaches correspond. Analysis of hazmat flows corresponding to many of the examples listed in Tables 6-3 and 6-4 are discussed in Appendix K. Note that specific applica- tions, relevance, and effort required may not conform to these example summaries. They are not exhaustive of all potential analysis possibilities using the existing or new data sources discussed in Chapters 4 and 5. 6.3 Document the Data After analyzing the existing and new HMCFS data, the project team prepares, summarizes, and documents the HMCFS data for presentation to the core team. Remember that the purpose of the HMCFS process is to enhance a local jurisdiction's ability to estimate or quantify the risks

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60 Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies Table 6-2. Hazmat flow data output, applicability, relevance, and analysis effort required, by source, for railway, pipeline, waterway, and airway transport modes. Local Required Trans. Hazmat Commodity Hazmat Commodity Flow Data Analysis Output Max. Appl. HMCFS Analysis Mode Flow Data Source Characteristics Level Relevance Effort Railway, Lists, tables, or spreadsheets of flow information, may be displayed Pipeline, BTS Commodity Flow Minimum using charts; source of data for other federal freight data Low Low Waterway, Survey Scenario publications Airway Railway, Lists, tables, spreadsheets, or maps of flow information, may be Pipeline, FHWA Freight Minimum displayed using charts; data sourced from other federal freight data Low High Waterway, Analysis Framework Scenario publications Airway STB Carload Waybill Lists, tables, or spreadsheets of estimated commodity flows over Equipment Low Railway High Sample data rail lines in region Needs Medium Railroad carrier Lists, tables, spreadsheets, or maps of commodity flows over rail Comprehensive Medium Railway Medium information lines, as available Planning High Comprehensive Pipeline NPMS data Tables or maps of pipeline types and locations Medium Low Planning Maximum Waterway USACE reports Tables or spreadsheets of commodity group flows Low Low Scenario USACE reports with Tables or spreadsheets of commodity group flows with associated Emerg. Waterway commod. code/placard Medium Medium placard IDs Planning ID cross reference Tables, spreadsheets, or maps of specific commodity or commodity USACE reports with Comprehensive Waterway group flows in waterways, along with associated placard IDs, as LowHigh MediumHigh carrier, facility info Planning available that are present associated with the flow of hazardous material into, out of, within, and through an area. This ability depends on the following three critical components: 1. Identifying where, when, and how hazardous material is transported; 2. Identifying what is transported (type of hazardous material and associated characteristics); and 3. Determining the consequences associated with incident occurrence (incident likelihood and who may be impacted). 6.3.1 Identifying Hazmat Flows With a wide range of data sources and HMCFS objectives, the project team's potential options for identifying hazmat flows range considerably. Generally, the flow information is used to assess risks, and provides context for the decisions associated with the HMCFS project's objectives and emergency planning and response. Flow estimates might use only existing data, a mix of exist- ing and new data, or all new data. The sampling and precision of the source data determines the specificity of information that can be concluded about hazmat transport. Examples of how haz- mat flows can be analyzed and documented are provided in Appendix K. 6.3.2 Risk Estimation Procedures for conducting risk assessment calculations are well established and depend on specific characteristics of the local setting, commodities that are transported, and modes of trans-

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Analyze and Document Data 61 Table 6-3. Hazmat flow data characteristics, by source, for truck/roadway transport mode. Hazmat Flow Data Characteristics Hazmat Commodity Flow Data Source Spatial Temporal Metrics/ Sampling Material Description Applicability Framework Units Framework Every 5 Includes overall hazmat, Stratified CFS State/national Value, tons, and ton-miles years class/division, and UN/NA ID (national) Entire county or Stratified FAF Annual Estimated value and tons Commodity groups state (national) HPMS data Must apply VIUS data for Local network Annual Estimated total and hazmat trucks Unknown w/VIUS data hazmat classes Truck count Local network, as Must apply VIUS data for Stratified As collected Total trucks, estimated hazmat trucks w/VIUS data collected hazmat classes (national) Truck type count Local network, as Total trucks, trucks by type/configuration, Must apply VIUS data for Stratified As collected w/VIUS data collected estimated hazmat trucks hazmat classes, by truck type (national) Placard count Local network, as As collected Total trucks, percent trucks with placard None As sampled w/truck count collected Local network, as Specific Placard ID count As collected Number and type of placards As sampled collected placard ID Truck count w/ Local network, as Total trucks, percent trucks with and without Specific As collected As sampled placard ID count collected placard, number and type of placards placard ID Truck type and Total trucks, trucks by type/configuration, Local network, as Specific configuration count As collected percent trucks with placard by type and As sampled collected placard ID w/placard ID count configuration, number and type of placards Interviews with Truck/ As carriers, shippers, As provided (seasonal or monthly?) As provided As provided Roadway provided receivers Truck/ Manifest surveys As collected Shipment volume/weight Specific commodity name As sampled Roadway port. Risk estimation is especially applicable for designation of hazmat route analysis but can also be useful for other HMCFS objectives. When based on sufficient existing or new data, hazmat flows can be characterized by com- modity movements (e.g., tons, carloads, or number of vehicle/placard observations) on a spatial (e.g., each route or route segment) and temporal (e.g., daily, monthly, annually, etc.) basis. Risk is identified by combining the commodity flow information with historical incident/accident information to identify potential impacts on populations or environmentally sensitive areas. It is important to remember that such estimates can be highly inaccurate when low-level sampling techniques or small sample sizes are used, or the data are imprecise. Some suggested sources for further information on hazmat transport risk analysis are as follows: Highway Routing of Hazardous Materials: Guidelines for Applying Criteria (13). Guidelines for Chemical Transportation Risk Analysis (26). EPA's ALOHA software and the Emergency Response Guidebook (available from PHMSA) were used 6.3.3 Spatial Elements of Risk Estimation to determine potential hazmat A focus on the routes or segments with hazmat flows that contribute most incident impact radii and identify significantly to the overall risk in the study area can provide insight into bet- high risk areas along major trans- ter management techniques and even risk mitigation. Considerations for spa- port corridors in Arizona. High risk tial analyses of hazmat transport and risk estimation include the following: and environmentally sensitive Routes or route segments contribute significantly to risk when they are hotspots were identified on maps. characterized by high frequency of hazmat flows.

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62 Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies Table 6-4. Hazmat flow data output, applicability, relevance, and analysis effort required, by source, for truck/roadway transport mode. Local Hazmat Commodity Maximum Required Hazmat Commodity Flow Data Analysis Output Characteristics HMCFS Flow Data Source Objective Level Effort Relevance Lists, tables, or spreadsheets of flow information, may be displayed Minimum CFS Low Low using charts; source of data for other federal freight data publications Scenario Minimum FAF Lists or tables of commodity groups for county Low High Scenario HPMS data with Lists or tables of commodity classes expected to be present in Minimum Low Low VIUS data community; chart of truck traffic patterns as supported by data Scenario Truck count with Lists or tables of commodity classes expected to be present in Minimum Low Low VIUS data community; chart of truck traffic patterns as supported by data Scenario Medium Truck type count with Lists or tables of commodity classes expected to be present in Minimum Low Medium VIUS data community; chart of truck traffic patterns as supported by data Scenario Medium Lists or tables of hazmat presence or absence at surveyed locations Placard count with Minimum Low Low (percent trucks with hazmat placard); chart of truck traffic patterns as truck count Scenario Medium Medium supported by data Lists, tables, or charts of placard IDs observed by road network Resource Medium Medium Placard ID count segment and/or time Scheduling High High Lists, tables, charts, or maps of placard IDs observed by road network Truck count with Medium segment and/or time; proportion of truck traffic with placard; chart of Route Designation High placard ID count High truck traffic patterns as supported by data Truck type and Lists, tables, charts, or maps of placard IDs observed by road network configuration count segment and/or time; proportion of truck traffic with placard, by truck Route Designation High High with placard ID count type; chart of truck traffic patterns as supported by data Interviews with Lists, tables, charts, or maps of specific commodity carried, by road carriers, shippers, Legal Takings High High network, as supported by data receivers Lists, tables, charts, or maps of specific commodity carried, including Manifest surveys Legal Takings High High quantity, road network, and truck type, as supported by data Routes or route segments that frequently exceed capacity, are narrow or winding, are frequently under construction, have (draw) bridges, tunnels, or other bottlenecks are often characterized by high accident rates and become priorities for more extensive analysis. Routes or route segments with special populations located nearby--such as schools, hospitals or nursing homes--also receive high priority. Routes or route segments with truck stops, weigh stations, rest stops, and siding-tracks may receive attention because of the associated delays along the route, increasing the duration that transported hazardous materials are present. 6.3.4 Temporal Elements of Risk Estimation As supported by the data, the HMCFS should consider the temporal patterns of hazmat trans- port by time of day, day of the week, or season of the year. Considerations for temporal analyses of hazmat transport and risk estimation include the following: Metropolitan and large urban areas usually exhibit daily traffic patterns that can have a signifi- cant impact on hazmat flows and thus need to be considered.

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Analyze and Document Data 63 Figure 6-2. Variation in traffic patterns by time of day. Source: FHWA Traffic Monitoring Guide (14), Figure 2-2-1. Daily variations in overall traffic patterns and flows may arise due to shift changes, commutes to work, and school hours. Communities that lack major through-routes will typically have substantially less traffic during the dead-of-night hours than during daylight hours. When compared with daylight-hour traffic, communities with major through-routes may see only a moderate reduction in traffic on these routes during the dead-of-night hours. Nearly all communities in the United States exhibit weekly traffic patterns, with weekdays and weekends exhibiting marked differences. Many areas experience seasonal variations in traffic associated with the economic activity of the area (e.g., agricultural areas have planting and harvesting seasons, petroleum refining areas have seasonal production patterns, etc.). Figure 6-2 illustrates variations in traffic patterns as a percentage of daily traffic by time of day, taken from FHWA's Traffic Monitoring Guide (14). This figure illustrates differences between rural and urban cars, business day trucks, and through trucks on an example highway where each curve represents 100 percent of traffic for each vehicle category (i.e., just over 4 percent of through truck traffic per time period times 24 hours equals 100 percent). A jurisdiction's traffic flows may show very different patterns, especially across roadway types (highways, arterials, secondary roads, etc.) 6.3.5 Hazmat Incident/Accident Likelihoods Careful examination of local incident/accident history can help inform emergency response staffing, scheduling, and resource allocation decisions. If incident or accident data and traffic volume data are available, the likelihood of a hazmat accident is determined by multiplying the accident rate by the volume of hazmat traffic. Areas that have not experienced prior incidents can estimate incident likelihood based on state, regional, or national averages. Figure 6-3 provides an example of how incident or accident data may be analyzed, applied to hourly frequencies of serious in-transit hazmat highway incidents reported to PHMSA between 2002 and 2008 across the United States. Two patterns are readily apparent in these data. First, the weekendweekday difference indicates that weekends have lower accident rates--beginning around 4 A.M. on Saturday morning and continuing through to Monday morning rush hour at around 5 A.M. Secondly, the weekday pattern is relatively stable across days of the week--characterized by a

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64 Guidebook for Conducting Local Hazardous Materials Commodity Flow Studies Figure 6-3. Hourly frequencies of highway in-transit incidents classified as "HMIS Serious." Source: Texas Transportation Institute (using HMIS microdata). slight increase in the early morning hours (i.e., right after midnight and declining after 3 or 4 A.M.), then increasing into the early hours of the workday (i.e., reaching a peak around 8 to 10 A.M.), and declining throughout the rest of the day (i.e., reaching low levels again around 10 or 11 P.M.). Local patterns may differ from these national trends, and apparent differences should be understood in light of local conditions. Jurisdictions with access to local accident information may be able to develop similar charts, whether for incidents involving hazardous materials, all truck accidents, or traffic accidents in the entire driving population. Note that patterns of truck traffic accidents may not directly compare with those of general traffic accidents, with truck acci- dents tending to be higher in the early daytime hours, and general traffic accidents higher later in the day. Unique spikes or dips that are not related to specific local conditions may require fur- ther validation. Interviews with key informants, such as emergency managers and responders, will be useful to the validation process. 6.3.6 Properties of Hazardous Materials Identifying every single hazardous material likely to be transported through an area is extremely difficult--especially when the nature of the hazmat flows in the area are complex and variable. Some jurisdictions find it advisable to concentrate on general classes of materials (e.g., flamma- bles, corrosives) being transported. When detailed data (i.e., UN/NA placard IDs) are available, they can be used to identify implications of various types of incidents in terms of their potential consequences.

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Analyze and Document Data 65 Identifying Hazards and Initial Response Guidelines Commodity information may be used to identify potential hazard zones around routes or route segments in the study area. For example 1) Nearly all communities have flows of fuels, including UN/NA placard ID number 1203 (i.e., gasohol, gasoline, or motor spirits) among others. The 2008 ERG indicates that this material is highly flammable and will ignite easily by heat, sparks, or flames, and may form explosive vapors when mixed with air. The potential for irritation of the skin and eyes if inhaled or contacted are included among the health impacts. Procedures outlined in the 2008 ERG (Guide Number 128) indicate immediate isolation of the spill or leak to a distance of 50 meters, with downwind evac- uation for large spills of at least 300 meters, and up to 800 meters in all direc- tions if the tank (car or truck) is involved in fire. 2) Many communities have flows of anhydrous ammonia (UN/NA placard ID 1005, ERG Guide Number 125) and chlorine (UN/NA placard ID 1017, ERG Guide Number 124). The 2008 ERG suggests initial isolation of 30 and 60 meters for small spills of ammonia and chlorine, respectively, with daytime downwind evacuations of 0.1 and 0.2 km, respectively. Small nighttime spills increase the recommended evacuation distances to 0.2 and 1.6 km, respectively. The 2008 ERG suggests isolation of 150 and 600 meters for large spills of ammonia and chlorine, respectively, and downwind daytime evacuation zones of 0.8 and 3.5 km, respectively. Nighttime distances expand to 2.3 and 8.0 km for large spills of ammonia and chlorine, respectively. Considerations for Identifying At-Risk Populations The residential population in the potential hazard zone is of critical importance, especially during certain times (e.g., evenings, late nights, and weekends). Retail and commercial areas are of particular interest during peak use periods (e.g., shopping malls during the holiday season, office buildings during typical work hours). Special populations require special attention, especially those located in (or near) the potential hazard zone. Planners may wish to focus on special-population facilities that reside in a confluence of potential hazard zones associated with various routes or route segments. Congregations of people for special gatherings (e.g., large sporting or enter- tainment events, fairs, religious or political events) also may require focused attention. Event planners may wish to consider relocating some events to venues outside the potential hazard zones.