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The Role of Transit in Emergency Evacuation
4
Evidence from the 38 Largest Urbanized Areas
This chapter examines the role of transit in emergency evacuation in the 38 largest urbanized areas (UAs)—the primary focus of the committee’s charge. It begins with a profile of the 38 areas and a summary of the committee’s assessment of the role of transit in the publicly available emergency response and evacuation plans of the major jurisdictions within these UAs and their respective states. The chapter then turns to a discussion of the results of the case studies conducted by the committee, which provide an in-depth look at the multiple roles transit can play in emergency evacuation, as well as some of the factors limiting that role. The chapter ends with a series of findings.
Profile of the 38 UAs
The committee prepared a statistical profile of the 38 UAs to provide an overview of many of the factors discussed in the previous chapter that may affect the role of transit in an emergency evacuation and to help select the case study sites. The profile is limited to those factors that could be quantified. Indicators were developed on six topics: UA size, potential demand for transit service, supply of transit and other public transportation equipment (i.e., school buses), number of transit agencies (an indicator of coordination complexity), roadway congestion, and predominant types of recent disasters (see Box 4-1). The primary data sources are U.S. census data for information on population, land area, demographic statistics, and car ownership; the National Transit Database for data on transit agency size, service area, and equipment by type; the annual bus fleet survey of the top 100 school districts for school bus numbers; the Urban Mobility Report of the Texas Transportation Institute for the congestion indicator; and the annual Federal Emergency Management Agency (FEMA) database on presidentially declared disasters for data on the most common disasters by state.
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The Role of Transit in Emergency Evacuation
BOX 4-1
Indicators by Category of Interest for Statistical Profile of 38 Urbanized Areas
Size of Urbanized Area
Population
Land area (in square miles)
Transit service area of largest provider (in square miles)
Transit population served of largest provider
Potential Demand for Transit Service
Carless households
Housing units without cars
Percent of housing units without cars
Seniors
Householders living alone and ≥65 years of age
Percent of householders living alone and ≥65 years of age
Recent immigrants
Number of foreign born, entry ≥2000
Population ≥5 years of age who speak English less than “very well”
Percent of population ≥5 years of age who speak English less than “very well”
Poor (below the poverty line)
Population living below the poverty line
Percent of population living below the poverty line
Persons with disabilities
Population ≥5 years of age with a disability
Percent of population ≥5 years of age with a disability
Commuters
Number of workers ≥16 years of age using transit (excluding taxi)
Supply
Density of urbanized area (population per square mile)
Number of cars
Number of buses (for transit agencies with ≥100 vehicles operated in maximum service)
Number of railcars (for transit agencies with ≥100 vehicles operated in maximum service)
Number of demand response vehicles (for transit agencies with ≥100 vehicles operated in maximum service)
Number of school buses
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The Role of Transit in Emergency Evacuation
Coordination
Number of transit agencies (with ≥100 vehicles operated in maximum service)
Congestion
Travel time index
Disasters
Predominant type
The UA designation, which originated in the study request, proved to be a constraint. Census data are available by UA, but transit and school bus data are not; the boundaries of transit service areas and school bus districts are not coterminous with census-defined borders of the UAs. Even so, every effort was made to include the major transit properties and school districts in a UA. The focus on UAs, however, was useful from another perspective. UAs represent the most densely populated part of a region, where transit service is likely to be most extensive, and thus where the need for transit could be significant in an emergency evacuation.
The results of the statistical profile are summarized in Table 4-1 and shown in detail in Annex 4-1.1 The profile, particularly the detailed statistics, reveals the variety of conditions even among the largest UAs—the 38 selected for this study. For example, population ranges in size from just over 1 million for New Orleans (pre-Katrina) to 17.8 million for the New York–Newark UA.2 Even more relevant from the perspective of transit service provision, population density (population per square mile)—a good proxy for the levels of transit supply to be found in an area—ranges from
1
Sylvia He, PhD candidate in the School of Policy, Planning and Development at the University of Southern California, collected the data, working with committee member Evelyn Blumenberg under the general supervision of the committee.
2
In the interest of brevity, once an individual UA has been mentioned, its name is shortened when used again.
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a low of 1,783 in Atlanta to a high of 7,068 in Los Angeles. In low-density Atlanta, the largest transit system, the Metropolitan Atlanta Rapid Transit Authority, covers only one-quarter of the land area and provides service to about 40 percent of the population of the Atlanta UA. By contrast, in high-density Los Angeles, the Los Angeles County Metropolitan Transportation Authority bus system covers nearly three-quarters (73 percent) of the land area and provides service to a roughly equivalent percentage of the population in the Los Angeles UA.
The 38 UAs also differ in more direct measures of transit system availability. Nearly half—17 of 38—generally those in the bottom triad with respect to population size3—are served by only one transit agency (see Table 4-1).4 The inventory of available transit equipment (e.g., buses, railcars, demand response vehicles) is also low for this group of UAs (i.e., ≤1 transit vehicle per 1,000 persons), even though the data represent the maximum levels of equipment likely to be operational in the event of an emergency.5 At the other end of the spectrum, with the exception of Boston and Houston, the largest UAs—those in the top triad with respect to population size—are served by two or more transit agencies; the very largest UAs—New York and Los Angeles—have 17 and 9 transit providers, respectively. Not surprisingly, the supply of transit equipment is also larger in these areas; New York, Chicago, and Los Angeles lead the group, with 18.5, 6.6, and 5.3 transit vehicles per 1,000 persons, respectively. In sum, the differences among UAs, particularly with respect to the number and size of transit agencies and the density of the population served, suggest that there is no single set of circumstances, or planning template, regarding the provision of transit service, even among this pool of the 38 largest UAs.
What the UAs do appear to have in common is relatively large numbers of special-needs populations—carless households, older residents living
3
The exceptions in terms of population size are Boston and Houston, which are defined here as large UAs (i.e., in the top triad of the 38 UAs).
4
For the purposes of this profile, only transit agencies with ≥100 vehicles operated in maximum service (VOMS) were included.
5
The Federal Transit Administration defines VOMS as the number of revenue vehicles operated to meet annual maximum service requirements. This is the revenue vehicle count during the peak season during the week and day that maximum service is provided. VOMS exclude atypical days or one-time special events.
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TABLE 4-1 Summary Profile of 38 Largest Urbanized Areas
Urbanized Area
Size: Large, Medium, Small UAsa
Carless Households: Number of Housing Units Without Carsb
Car Availability: Cars/1,000 Personsc
Atlanta
L
99,835
646
Baltimore
M
132,965
578
Boston
L
219,213
579
Chicago
L
436,049
548
Cincinnati
S
64,934
658
Cleveland
M
83,920
637
Columbus
S
37,761
672
Dallas–Fort Worth–Arlington
L
99,384
621
Denver–Aurora
M
59,522
692
Detroit
L
147,695
635
Houston
L
108,281
580
Indianapolis
S
37,801
671
Kansas City
S
43,034
679
Las Vegas
S
47,282
585
Los Angeles–Long Beach–Santa Ana
L
437,913
541
Miami
L
207,476
576
Milwaukee
S
67,646
608
Minneapolis–St. Paul
M
84,472
659
New orleans
S
70,328
523
New York–Newark
L
2,102,874
425
Orlando
S
29,700
640
Philadelphia
L
319,899
556
Phoenix–Mesa
M
76,756
614
Pittsburgh
M
106,557
610
Portland
M
55,749
667
Providence
S
54,658
613
Riverside–San Bernardino
S
39,397
540
Sacramento
S
43,859
631
St. Louis
M
81,489
646
San Antonio
S
45,888
569
San Diego
M
78,393
613
San Francisco–Oakland
L
174,176
584
San Jose
S
29,147
663
Seattle
M
91,536
696
Tampa–St. Petersburg
M
74,404
645
Virginia Beach
S
45,688
632
Washington
L
181,846
607
San Juan
M
205,563
388
aThe 38 largest UAs are divided into three groups, with roughly even numbers in each group: 12 large UAs, 12 medium UAs, and 14 small UAs.
bSource: 2000 Census of Population and Housing (SF3-Table H44).
cNumber of cars is from 2000 Census of Population and Housing (SF3-Table H46).
dNumber of transit vehicles per 1,000 persons (buses + railcars + demand response vehicles); number of transit vehicles is from 2005 National Transit Database for all UA transit properties with ≥100 vehicles operated in maximum service.
eSource: 2005 National Transit Database, Appendix D; all UA transit properties with ≥100 vehicles operated in maximum service.
fSource: FEMA (declared disasters by state); top three disasters (disasters in parenthesis are tied with respect to frequency) and disasters that occurred more than five times in the past 15 years (1992–2006).
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Transit Availability: Transit/1,000 Personsd
Coordination: No. of Transit Agenciese
Disasters: Predominant Typef
0.86
2
Tornadoes, severe storms, heavy rain
1.24
1
Severe storms, hurricanes (flooding, tornadoes)
2.14
1
Flooding, severe storms (heavy rain, blizzards)
6.59
3
Flooding, severe storms, tornadoes
0.37
1
Severe storms, flooding, tornadoes
0.75
2
Severe storms, flooding, tornadoes
0.28
1
Severe storms, flooding, tornadoes
1.28
4
Severe storms, flooding, tornadoes
1.43
1
Severe storms, flooding (wildfires, mudslides, landslides)
0.81
2
Severe storms, flooding, tornadoes
1.94
1
Severe storms, flooding, tornadoes
0.20
1
Severe storms, flooding, tornadoes
0.34
1
Severe storms, flooding, tornadoes
0.44
1
Flooding, severe storms (heavy rain, wildfires)
5.30
9
Flooding, severe storms, landslides, mudslides, earthquakes
2.22
5
Hurricanes, flooding, tropical storms, severe storms, tornadoes
0.68
1
Severe storms, flooding, tornadoes
1.50
3
Flooding, severe storms, tornadoes
0.48
1
Severe storms (flooding, hurricanes, tropical storms)
18.54
17
Severe storms, flooding, tornadoes
0.38
1
Hurricanes, flooding, tropical storms, severe storms, tornadoes
2.57
2
Flooding, severe storms, tropical depressions
0.97
3
Severe storms, flooding, wildfires
1.47
2
Flooding, severe storms, tropical depressions
0.98
2
Severe storms, flooding (landslides, mudslides, earthquakes)
0.33
1
Blizzards
0.45
2
Flooding, severe storms, landslides, mudslides, earthquakes
0.38
1
Flooding, severe storms, landslides, mudslides, earthquakes
0.67
2
Severe storms, flooding, tornadoes
0.54
1
Severe storms, flooding, tornadoes
1.16
4
Flooding, severe storms, landslides, mudslides, earthquakes
4.26
8
Flooding, severe storms, landslides, mudslides, earthquakes
0.59
1
Flooding, severe storms, landslides, mudslides, earthquakes
3.73
4
Severe storms, flooding, landslides
0.45
2
Hurricanes, flooding, tropical storms, severe storms, tornadoes
0.39
1
Severe storms, flooding, tornadoes
2.95
4
Severe storms (hurricanes, flooding, blizzards)
3.34
2
Flooding, severe storms, hurricanes
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alone, people living below the poverty line, and people with a disability (see Annex 4-1). All these special-needs groups are potential users of transit in an emergency evacuation. However, the transit fleet inventory suggests that, with the exception of a few UAs, the numbers of paratransit and other demand response vehicles available to serve many of the groups who might need assistance in an evacuation are small. [It is difficult to get a sense of the total shortfall from the inventory numbers. Many buses are Americans with Disabilities Act (ADA)-equipped and could serve those who are carless but ambulatory in an evacuation. Similarly, ADA-accessible school buses could be used to supplement transit service for the same group. This type of detail was not available in the summary statistics.] Moreover, the spatial distribution of special-needs populations, together with the availability of transit and school bus drivers and equipment to serve them at the time of an emergency, determines the extent to which transit and other public transportation providers can play a significant role in an evacuation. The indicators—with their summary averages and percentages—fall short of providing this vital information.
With the exception of San Juan and New York, the UAs show similar and significant levels of car ownership relative to transit availability per 1,000 persons (see Table 4-1). Even taking into account the greater carrying capacity of transit vehicles, the numbers serve as a reminder that cars will be the primary mode of transportation in an emergency evacuation.
Results of the Committee’s Plan Assessment
Using the contextual data provided by the statistical profile of the 38 UAs, the committee undertook an assessment of the emergency response and evacuation plans of each UA and its respective state to ascertain the extent to which transit is included in these plans. At the outset of the study, the intent was to draw on the in-depth reviews prepared by the U.S. Department of Homeland Security (DHS) in its Nationwide Plan Review of 56 states and territories and the 75 largest UAs (DHS 2006). Unfortunately, confidentiality issues precluded the committee from accessing all but the summary data from that review, which are discussed in Chapter 2 and the literature review in Appendix B. Therefore, the committee commissioned a small project to access information that could be gleaned from
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online documents.6 The primary purpose was to evaluate each of the UAs to determine whether it had an emergency response and evacuation plan and whether and to what extent the plan considered the use of transit resources in an emergency evacuation.7
Internet searches were used to locate relevant publicly available emergency planning documents for each UA and its respective state. When no documents could be found, a follow-up call was made to determine whether they could be located. In some cases, plans were not available to the public for security reasons; in other cases, technical problems precluded accessing the documents. Of the 33 UAs reviewed,8 16 had made publicly available at least portions of an emergency response or evacuation plan, while 17 either did not have publicly available plans or were in the process of drafting or revising them.
The documents of the 16 UAs with publicly available plans were reviewed to answer 14 questions; both the questions and a summary matrix of the results can be found in Appendix C.9 In 11 of the 16 UAs, transit was included in emergency evacuation plans. However, only seven plans clearly indicated transit’s role in the chain of command in the event of an emergency, and an equivalent number identified available transit equipment. Only six plans described transit’s role in evacuating special-needs populations, and details were scant regarding methods for identifying these populations, communicating with them about what to do in an emergency, identifying pickup locations for those who are ambulatory, and specifying where transit passengers would be taken (see Appendix C for more details). In summary, only seven plans contained sufficient detail to lend credibility to the role of transit in emergency evacuation.
The committee concluded that the data gathered through its plan review were inadequate to analyze in any depth or to assess reliably the role of tran-
6
Both budgetary considerations and the already significant survey demands on relevant respondents prevented the committee from conducting an in-depth survey of its own.
7
The work was performed by Joseph M. Maltby and Aaron D. Green, JD candidates at the George Mason University School of Law, both of whom had prior experience as legal interns for DHS’s Critical Infrastructure Protection Program.
8
Five of the 38 UAs were handled as case studies, which included detailed assessments of the role of transit (see Appendix D).
9
For cost reasons, the detailed data for each UA have been made available in electronic form only (onlinepubs.trb.org/Onlinepubs/sr/sr294appendixC.pdf).
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sit in the emergency response and evacuation plans of the 33 UAs. Although it was not focused on transit, a recent online review of the content of the websites of all 50 state emergency management agencies (Liu 2008) found similar limitations. Slightly more than half (56 percent) of the websites included crisis communications or emergency management plans. In the researcher’s opinion, the reluctance to post plans reflects the security concerns of the post–September 11 environment. Websites that provided information on disasters were focused on terrorism, rather than on those disasters likely to occur in the respective states. Moreover, the websites did a poor job of targeting special-needs populations. For example, only one-third had foreign-language access; 38 percent included information for the disabled; and only 16 percent had information targeting the elderly.
These findings raise a more general issue about the appropriate level of emergency information that should be made publicly available. The committee believes that the public should be informed about area emergency evacuation plans and how transit will be deployed in an emergency. An informed public, particularly special-needs populations, is critical to preparedness in an emergency incident. However, sensitive operational details should be excluded from emergency planning documents and only “sanitized” versions made publicly available. FEMA could provide a template for suitable presentation formats as part of its guidance to state, local, and tribal governments.
Results of the Committee’s Case Studies
In response to its charge, the committee conducted five in-depth case studies to enhance its understanding of the various roles transit can play in an emergency evacuation. The case study results are summarized here and presented in greater detail in Appendix D.
Selection of Case Study Sites
The committee used the statistical profile summarized above to help guide its selection of case study sites. The final selection was made on the basis of five criteria:
Size of UA,
Mix of transit system types (e.g., bus, rail),
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Large special-needs populations,
Different types of disaster threats and experience with disasters, and
Jurisdictional complexity.
With regard to size, the larger UAs were of particular interest because they typically have large transit systems with the potential to play a major role in an emergency evacuation. That said, as noted in Chapter 1, the committee was interested in selecting one medium-sized UA to examine the extent to which scale issues make a significant difference in response capacity. Having sites with a mix of different transit systems was also important, including UAs with large heavy-rail systems; UAs with large bus systems; and UAs that draw on other types of public transport, such as ferries or intercity passenger rail (e.g., Amtrak). The presence of large special-needs populations was a key criterion, which most of the UAs met. Variation in the types of disasters faced was another selection criterion; recent experience with a disaster was also desirable. Finally, UAs that posed challenges from the perspective of jurisdictional complexity were of interest. Also factored into the selection process was the ability to identify a lead committee member who could help organize and conduct each site visit. The application of these criteria resulted in the selection of five case study sites—the Chicago, Houston, Los Angeles–Long Beach–Santa Ana, New York–Newark, and Tampa–St. Petersburg UAs (see Table 4-2).
At each of the case study sites, representatives of city and county emergency management agencies, transit agencies, state and local departments of transportation (DOTs), and other relevant agencies [e.g., school districts, metropolitan planning organizations (MPOs)] were interviewed. The questionnaires that guided the interviews can be found in Appendix D.
Roles of Transit in an Emergency
The case studies provide good examples of the breadth of roles transit can play in an emergency evacuation. The committee also supplemented its site visits with information about individual UAs from briefings at its meetings and from other case studies that were brought to its
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TABLE 4-2 Criteria for Selection of Case Study Sites and Rating of Five Selected Sites
Urbanized Area
Population Sizea
Type of Transit System
Special-Needs Populationsb
Predominant Type of Disaster
Jurisdictional Complexityc
Chicago
Large
Rail and bus
15 percent carless households; 14 percent speak English less than “very well”
Flooding, severe storms, tornadoes; terrorism threat
Medium
Houston
Large
Predominantly bus
14 percent of population living below the poverty line; 20 percent speak English less than “very well”
Severe storms, flooding, tornadoes; experience with Hurricane Rita
Low
Los Angeles–Long Beach–Santa Ana
Large
Predominantly bus
17 percent of population living below the poverty line; 28 percent speak English less than “very well”
Flooding, severe storms, landslides, mudslides, earthquakes; terrorism threat
High
New York–Newark
Large
Rail, bus, and ferry
32 percent carless households; 14 percent of population living below the poverty line; 17 percent speak English less than “very well”
Severe storms, flooding, tornadoes; terrorism (September 11, 2001)
High
Tampa–St. Petersburg
Medium
Bus
17 percent of population with a disability; 11 percent of households living alone and ≥65
Hurricanes, flooding, tropical and severe storms, tornadoes; recent hurricane experience
Low
aSee Table 4-1 for explanation of ranking.
bSee Annex 4-1 for indicators.
cLow = 1–2 transit agencies; medium = 3–4 transit agencies; high = ≥5 transit agencies.
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profit organizations.26 Funding priorities currently include public education on disaster preparedness and recovery, coordination of relief efforts of statewide private-sector organizations, and improved training and operations capabilities of agencies with lead or support responsibilities in the Florida Comprehensive Emergency Management Plan.
Findings
In this chapter, the committee has attempted to provide a picture of the role of transit in the evacuation plans of the nation’s 38 largest UAs. The statistical profile of the UAs suggests a diversity of conditions that makes it difficult to generalize—differences in the size and density of their populations, the size and coverage of the major transit systems that serve them, the types of emergencies they face, and their jurisdictional complexities. One common element among most of the UAs is their relatively large numbers of special-needs populations, who are potential users of transit in an emergency. Moreover, with the exception of some of the largest UAs (e.g., Chicago, Los Angeles, New York, San Francisco), the gap between the numbers of carless households and the supply of transit equipment is large. The numbers of paratransit and other demand response vehicles are particularly low relative to the size of populations with disabilities who need such vehicles for transport in an evacuation. In addition, the location of special-needs populations in a particular UA, their actual need for transit in an emergency evacuation, and the availability of drivers and equipment to serve them at the time of an incident remain largely unknown.
Similarly, the committee could not assess with any reliability the extent to which transit is included in the emergency response and evacuation plans of the 38 UAs. The plans of 11 of the 16 UAs with publicly available online documents mention transit, but sufficient detail is provided in only seven to indicate a credible role for transit in evacuation plans.
The committee’s five in-depth case studies proved to be a more rewarding source of information, but that information cannot be generalized to the other 33 UAs. Nevertheless, the case studies illustrate the wide range
26
A competitive grant program is also available to municipalities that have an emergency management program and are signatories to the Statewide Mutual Aid Agreement. Eligible grantees may apply annually for one grant, not to exceed $50,000.
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of roles transit can play in emergency evacuation and raise many issues likely to affect its role in other UAs. The primary role for transit is to evacuate those without a car, either by bus or by rail, away from an emergency site to area shelters or outside the UA during a major disaster. Transit’s role in evacuation can be augmented by other modes of public transport, such as school buses, commuter and intercity rail, and ferries, as evidenced by several of the case studies.
Transit has a special role to play in evacuating special-needs populations. Many are likely to need assistance and require trained drivers or, at a minimum, accessible equipment, which is often provided by paratransit operators. The emergency evacuation of special-needs populations, however, poses a major challenge in all the case study sites with the exception of Tampa, which has targeted its transit and school bus resources to evacuating these populations. In the other case study sites, the large size of special-needs populations and the no-notice nature of many of the incidents faced increase the complexity of both identifying and planning for the evacuation of these groups.
Another role for transit is to bring emergency responders and equipment to incident sites. Finally, transit can aid in recovery, both in returning evacuees to their initial point of departure and in providing general transport following an emergency if travel by private vehicle is difficult.
The most detailed roles for transit are found in the plans of those case study sites that face advance-notice incidents, such as hurricanes. Emergency evacuation plans and transit’s role in those plans are more process oriented in those sites where no-notice incidents are more likely.
Together, the case studies suggest many of the factors that can make transit a successful partner in evacuation. These include collaboration with emergency managers in evacuation planning and integration with emergency operations plans. In all the case study sites, the primary transit agencies are part of evacuation plans; transit staffs are represented on the decision-making team when activation of EOCs is required; and transit operators have the capability of communicating with emergency managers and with other transit providers in real time, although few have fully interoperable systems. Communication with potential transit users, both the general public and special-needs populations, is recognized as critical, both in advance of and particularly during an emergency, but
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the case study sites vary in their approaches to and the effectiveness of their communications. Transit agencies participate in exercises and drills in several of the case study sites, an important means of practicing for an emergency evacuation. Finally, plans for workforce availability, asset deployment and safety, and mutual-aid agreements to help meet surge demands in an emergency evacuation are all recognized as important to the successful use of transit, but they are addressed to varying degrees by the case study sites.
The case studies also suggest the limits of transit’s role in an emergency evacuation. The most obvious limit is damage to the system itself. In the event of an earthquake in Los Angeles or another terrorist event in New York City, transit operators would shut down service until the integrity of the system had been verified. Another limitation is the lack of a regional approach to evacuation and the use of transit. Few case study sites had planned for a major disaster and integrated transit agencies into an evacuation scenario that could involve multiple jurisdictions and states in a region. Emergency planners have begun to develop more coordinated regional evacuation plans, and some transit agencies are part of these efforts, but progress is slow. New DHS grant funds for regional catastrophic preparedness could help, but the funds are currently limited to the largest urban areas.
A third limitation is the fact that transit systems operate as part of a transportation network in a UA and thus may be hampered by system congestion and capacity constraints in an evacuation—issues largely outside their control. Bus systems, which operate on area highways, are particularly vulnerable to local congestion and capacity bottlenecks. The problems are especially acute in the central business districts of large UAs, such as New York and Chicago, where buses have to negotiate both pedestrian and vehicular traffic. But congestion and capacity constraints are also manifest in newer UAs such as Houston, or at the suburban or exurban fringe of UAs both new and old should an evacuation extend outside the UA, as it did during Hurricane Rita. Those UAs having extensive and redundant rail networks with good system connectivity possess an important asset in an emergency evacuation, as was amply demonstrated in New York City and Washington, D.C., in the aftermath of the terrorist attacks of September 11. Few UAs, however, have such extensive rail transit systems.
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The solutions to many of these limitations, particularly those involving capacity additions and removal of bottlenecks, require long-term capital funding from both federal and state sources and must compete with other budgetary priorities. Improving the efficiency of existing operations through deployment of ITS technologies and contraflow operations on selected highways, where conditions permit, can be effective, but these solutions also require funds. The case studies provide examples of states, such as Florida and Texas, that play an important role in funding projects aimed at improving evacuation capability, largely to address the recurring hurricanes to which these areas are susceptible. Even among the case study sites, however, such support is the exception rather than the rule.
In the following and final chapter, the committee’s recommendations with respect to funding as well as a range of measures that could enhance transit’s role in emergency evacuation are presented.
References
Abbreviations
AASHTO Association of American State Highway and Transportation Officials
DHS Department of Homeland Security
MIPRC Midwest Interstate passenger Rail Commission
511 Coalition. 2008. 511 Usage Statistics. www.deploy511.org.
AASHTO Journal. 2006. D.C. Opens New Emergency Call Center for Multiple Jurisdictions. Vol. 106, No. 39.
DHS. 2006. Nationwide Plan Review, Phase 2 Report. June 16. www.dhs.gov/xlibrary/assets/Prep_NationwidePlanReview.pdf.
Liu, B. F. 2008. Online Disaster Preparation: Evaluation of State Emergency Management Web Sites. Natural Hazards Review, Vol. 1, No. 9, pp. 43–48.
Kendra, J., T. Wachtendorf, and E. Quarantelli. 2003. The Evacuation of Lower Manhattan by Water Transport on September 11: An Unplanned “Success,” Forum. Joint Commission Journal on Quality and Safety, Vol. 29, No. 6, pp. 316–318.
MIPRC. 2006. Responding Regionally: The Role of Passenger Rail in Midwestern Emergency Planning. www.miprc.org/portal/uploads/lkliewer/MIPRC_rail_&_emergency_preparedness_report.pdf.
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ANNEX 4-1 Detailed Statistical Profile of 38 Urbanized Areas
Urbanized Area
Size
Population (2000)a
Land Area (square miles)a
Transit Service Area of Largest Provider (square miles)b
Transit Population Served of Largest Providerb
Atlanta
3,500,000
1,963
498
1,355,000
Baltimore
2,076,000
683
1,795
2,078,000
Boston
4,032,000
1,736
3,244
4,510,000
Chicago
8,308,000
2,123
356
3,709,000
Cincinnati
1,503,000
672
262
845,000
Cleveland
1,787,000
647
458
1,412,000
Columbus
1,133,000
398
325
1,058,000
Dallas–Fort Worth–Arlington
4,146,000
1,407
689
2,250,000
Denver–Aurora
1,985,000
499
2,326
2,598,000
Detroit
3,903,000
1,261
144
951,000
Houston
3,823,000
1,295
1,285
2,797,000
Indianapolis
1,219,000
563
373
792,000
Kansas City
1,352,000
584
396
757,000
Las Vegas
1,314,000
286
280
1,785,000
Los Angeles–Long Beach–Santa Ana
11,789,000
1,668
1,224
8,493,000
Miami
4,919,000
1,116
306
2,380,000
Milwaukee
1,309,000
487
237
940,000
Minneapolis–St. Paul
2,389,000
894
596
1,762,000
New Orleans
1,009,000
198
75
485,000
New York–Newark
17,800,000
3,353
321
8,008,000
Orlando
1,157,000
453
2,538
1,537,000
Philadelphia
5,149,000
1,800
836
3,331,000
Phoenix–Mesa
2,907,000
799
515
1,439,000
Pittsburgh
1,753,000
852
775
1,415,000
Portland
1,583,000
474
574
1,254,000
Providence
1,175,000
504
299
846,000
Riverside–San Bernardino
1,507,000
439
2,725
1,498,000
Sacramento
1,393,000
369
248
1,035,000
St. Louis
2,078,000
829
574
1,007,000
San Antonio
1,328,000
408
1,213
1,487,000
San Diego
2,674,000
782
570
2,102,000
San Francisco–Oakland
2,996,000
527
93
834,000
San Jose
1,538,000
260
326
1,760,000
Seattle
2,712,000
954
2,134
1,788,000
Tampa–St. Petersburg
2,062,000
802
254
578,000
Virginia Beach
1,384,000
527
369
1,211,000
Washington
3,934,000
1,157
692
1,306,000
San Juan
2,217,000
892
198
1,177,000
OCR for page 112
The Role of Transit in Emergency Evacuation
Urbanized Area
Demand
Carless Householdsc
Seniorsd
Housing Units Without Cars
Percent of Housing Units Without Cars
Householder Living Alone and ≥65
Percent of Households Living Alone and ≥65
Atlanta
99,835
8
68,919
5
Baltimore
132,965
16
76,045
9
Boston
219,213
14
152,326
10
Chicago
436,049
15
260,385
9
Cincinnati
64,934
11
58,458
10
Cleveland
83,920
12
79,579
11
Columbus
37,761
8
32,300
7
Dallas–Fort Worth–Arlington
99,384
7
86,658
5
Denver–Aurora
59,522
8
58,818
7
Detroit
147,695
10
146,170
10
Houston
108,281
11
78,596
5
Indianapolis
37,801
8
43,030
8
Kansas City
43,034
8
43,579
8
Las Vegas
47,282
10
42,834
8
Los Angeles–Long Beach–Santa Ana
437,913
11
288,083
7
Miami
207,476
11
223,250
11
Milwaukee
67,646
13
52,796
10
Minneapolis–St. Paul
84,472
9
73,789
8
New Orleans
70,328
18
35,367
10
New York–Newark
2,102,874
32
657,966
10
Orlando
29,700
7
31,915
7
Philadelphia
319,899
16
198,154
10
Phoenix–Mesa
76,756
7
95,320
8
Pittsburgh
106,557
15
97,264
13
Portland
55,749
9
50,581
8
Providence
54,658
12
51,435
11
Riverside–San Bernardino
39,397
9
30,418
6
Sacramento
43,859
8
45,412
8
St. Louis
81,489
10
76,789
9
San Antonio
45,888
10
35,303
7
San Diego
78,393
8
83,524
9
San Francisco–Oakland
174,176
15
107,709
9
San Jose
29,147
6
36,068
7
Seattle
91,536
8
84,942
7
Tampa–St. Petersburg
74,404
9
102,958
11
Virginia Beach
45,688
9
41,775
8
Washington
181,846
12
105,604
7
San Juan
205,563
28
66,603
9
OCR for page 113
The Role of Transit in Emergency Evacuation
Recent Immigrantsd
Number of Foreign Born, Entry ≥2000
Population ≥5 Years Who Speak English Less Than “Very Well”
Percent of Population ≥5 Years Who Speak English Less Than “Very Well”
182,576
309,073
9
49,914
75,010
4
171,643
371,534
10
306,385
1,050,086
14
20,416
25,826
2
21,365
60,570
4
35,030
46,106
4
242,703
670,082
17
74,045
189,556
10
91,839
186,787
5
229,066
755,097
20
29,660
45,097
4
29,084
55,819
4
70,321
203,416
15
683,329
3,078,504
28
393,540
1,101,880
23
20,435
63,524
5
72,670
137,853
6
7,979
31,906
4
908,066
2,779,817
17
50,621
121,190
11
131,556
278,775
6
168,031
392,001
13
15,620
26,208
2
62,927
145,085
9
30,213
103,217
9
66,254
364,495
23
74,672
173,921
13
34,783
51,085
3
46,073
190,012
15
115,752
401,071
16
187,222
597,956
21
106,204
318,718
23
124,766
249,789
10
60,230
131,549
7
16,071
31,026
2
254,984
472,303
13
18,048
N.A.
N.A.
OCR for page 114
The Role of Transit in Emergency Evacuation
Urbanized Area
Demand
Poor (below poverty line)e
Disabledd
Population Living Below Poverty Line
Percent of Population Living Below Poverty Line
Population ≥5 Years with a Disability
Percent of Population ≥5 Years with a Disability
Atlanta
329,370
10
346,408
10
Baltimore
223,637
11
276,686
15
Boston
345,562
9
453,759
12
Chicago
890,127
11
912,085
12
Cincinnati
143,599
10
207,231
15
Cleveland
195,668
11
250,308
16
Columbus
122,682
11
138,780
13
Dallas–Fort Worth–Arlington
462,881
11
468,076
12
Denver–Aurora
163,522
8
205,260
11
Detroit
434,974
11
553,977
16
Houston
533,269
14
416,926
11
Indianapolis
108,931
9
169,420
15
Kansas City
124,340
9
170,822
13
Las Vegas
141,432
11
158,880
12
Los Angeles–Long Beach–Santa Ana
1,934,022
17
1,257,885
11
Miami
676,102
14
662,918
14
Milwaukee
149,701
12
162,754
14
Minneapolis–St. Paul
171,317
7
248,106
11
New Orleans
200,558
20
146,169
16
New York–Newark
2,425,106
14
2,049,640
12
Orlando
126,529
11
139,443
12
Philadelphia
569,503
11
686,741
15
Phoenix–Mesa
339,140
12
362,136
12
Pittsburgh
180,555
11
247,247
16
Portland
154,416
10
203,871
13
Providence
137,423
12
180,401
17
Riverside–San Bernardino
249,020
17
194,139
12
Sacramento
181,692
13
217,835
16
St. Louis
215,827
11
274,473
14
San Antonio
205,654
16
191,053
15
San Diego
326,304
13
278,394
12
San Francisco–Oakland
306,923
10
355,837
12
San Jose
114,229
8
132,616
9
Seattle
235,272
9
362,354
14
Tampa–St. Petersburg
226,341
11
337,507
17
Virginia Beach
143,443
11
169,714
14
Washington
301,542
8
358,415
10
San Juan
954,400
44
531,539
25
OCR for page 115
The Role of Transit in Emergency Evacuation
Commutersd
Supply
Number of Workers ≥16 Years Using Public Transport (excluding taxi)
Density (population/square mile)a
Number of Carsf
Number of Busesg
Number of Railcarsg
76,592
1,783
2,259,474
522
182
75,257
3,041
1,199,359
786
222
225,408
2,323
2,335,339
880
855
455,494
3,914
4,556,398
2,296
2,015
20,279
2,238
988,620
325
0
38,232
2,761
1,137,494
542
39
11,427
2,849
761,395
228
0
39,785
2,946
2,574,101
721
118
43,998
3,979
1,373,001
928
46
27,324
3,094
2,477,867
650
0
61,108
2,951
2,218,830
1,161
17
7,179
2,205
818,388
120
0
8,890
2,330
918,514
220
0
24,346
4,597
769,220
270
0
309,762
7,068
6,377,100
3,785
337
83,315
4,407
2,833,715
1,156
122
20,648
2,687
796,064
433
0
60,175
2,671
1,574,425
970
23
25,343
5,102
527,750
306
66
2,452,978
5,309
7,556,605
8,413
8,404
11,918
2,554
740,354
197
0
228,103
2,861
2,861,024
1,359
688
36,059
3,638
1,784,139
518
0
56,441
2,057
1,069,874
997
55
62,380
3,340
1,056,073
613
87
16,212
2,332
720,713
208
0
10,598
3,434
814,340
276
0
15,521
3,776
878,390
226
56
27,697
2,506
1,342,524
396
34
16,602
3,257
756,094
355
0
37,726
3,419
1,639,155
567
28
235,696
6,130
1,749,161
1,699
751
23,403
5,914
1,019,342
366
34
104,670
2,844
1,886,777
1,865
35
13,553
2,571
1,330,955
303
8
8,565
2,647
875,121
276
331,185
3,401
2,389,134
1,791
758
31,851
2,486
860,978
3,303
0
OCR for page 116
The Role of Transit in Emergency Evacuation
Urbanized Area
Supply
Number of Demand Response Vehiclesg
Number of School Busesh
Atlanta
157
382 (city)/820 (Fulton Co.)
Baltimore
230
915
Boston
407
611
Chicago
2,274
1,760
Cincinnati
43
N.A.
Cleveland
169
N.A.
Columbus
47
668
Dallas–Fort Worth–Arlington
436
1,450 (Dallas)/443 (FW)
Denver–Aurora
456
478 (Denver)/N.A.
Detroit
162
697
Houston
763
1,011
Indianapolis
76
512
Kansas City
123
442
Las Vegas
172
1,279
Los Angeles–Long Beach–Santa Ana
1,178
2,500 (LA)/439 (LA Co.)
Miami
941
1,886
Milwaukee
242
1,200
Minneapolis–St. Paul
400 (Minn.)/423 (St. Paul)
423
New Orleans
111
N.A.
New York–Newark
1,727
7,307 (NYC)
Orlando
183
1,271
Philadelphia
525
1,473
Phoenix–Mesa
456
N.A./413 (Mesa)
Pittsburgh
420
N.A.
Portland
276
305
Providence
120
N.A.
Riverside–San Bernardino
173
N.A.
Sacramento
98
N.A.
St. Louis
243
N.A.
San Antonio
181
400
San Diego
560
601
San Francisco–Oakland
1,806
N.A.
San Jose
192
N.A.
Seattle
1,829
465
Tampa–St. Petersburg
142
1,400 (Hillsborough Co.)/839 (Pinellas Co.)
Virginia Beach
112
760
Washington
398
N.A.
San Juan
38
N.A.
Note: N.A. data not available.
aSource: 2000 Census of Population and Housing as summarized in the Federal Transit Agency’s 2005 National Transit Database.
bSource: 2005 National Transit Database, profiles over and under 200,000 in population.
cSource: 2000 Census of Population and Housing (SF3-Table H44).
dSource: American Community Survey 2005.
eSource: 2000 Census of Population and Housing (SF3-Table P88).
fSource: 2000 Census of Population and Housing (SF3-Table H46).
gIncludes all UA transit properties with 100 vehicles operated in maximum service. Source: 2005 National Transit Database, Appendix D. Data for New orleans are for 2004.
OCR for page 117
The Role of Transit in Emergency Evacuation
Coordination: Number of Transit Agenciesi
Congestion: Travel Time Indexj
Disasters: Predominant Typek
2
1.34
Tornadoes, severe storms, heavy rain
1
1.3
Severe storms, hurricanes (flooding, tornadoes)
1
1.27
Flooding, severe storms (heavy rain, blizzards)
3
1.47
Flooding, severe storms, tornadoes
1
1.18
Severe storms, flooding, tornadoes
2
1.09
Severe storms, flooding, tornadoes
1
1.19
Severe storms, flooding, tornadoes
4
1.35
Severe storms, flooding, tornadoes
1
1.33
Severe storms, flooding (wildfires, mudslides, landslides)
2
1.29
Severe storms, flooding, tornadoes
1
1.36
Severe storms, flooding, tornadoes
1
1.22
Severe storms, flooding, tornadoes
1
1.08
Severe storms, flooding, tornadoes
1
1.3
Flooding, severe storms (heavy rain, wildfires)
9
1.5
Flooding, severe storms, landslides, mudslides, earthquakes
5
1.38
Hurricanes, flooding, tropical storms, severe storms, tornadoes
1
1.13
Severe storms, flooding, tornadoes
3
1.26
Flooding, severe storms, tornadoes
1
1.15
Severe storms (flooding, hurricanes, tropical storms)
17
1.39
Severe storms, flooding, tornadoes
1
1.3
Hurricanes, flooding, tropical storms, severe storms, tornadoes
2
1.28
Flooding, severe storms, tropical depressions
3
1.31
Severe storms, flooding, wildfires
2
1.09
Flooding, severe storms, tropical depressions
2
1.29
Severe storms, flooding (landslides, mudslides, earthquakes)
1
1.16
Blizzards
2
1.35
Flooding, severe storms, landslides, mudslides, earthquakes
1
1.32
Flooding, severe storms, landslides, mudslides, earthquakes
2
1.16
Severe storms, flooding, tornadoes
1
1.23
Severe storms, flooding, tornadoes
4
1.4
Flooding, severe storms, landslides, mudslides, earthquakes
8
1.41
Flooding, severe storms, landslides, mudslides, earthquakes
1
1.34
Flooding, severe storms, landslides, mudslides, earthquakes
4
1.3
Severe storms, flooding, landslides
2
1.28
Hurricanes, flooding, tropical storms, severe storms, tornadoes
1
1.18
Severe storms, flooding, tornadoes
4
1.37
Severe storms (hurricanes, flooding, blizzards)
2
N.A.
Flooding, severe storms, hurricanes
hSource: School Bus Fleet 2005 Annual Top 100 School District Fleet Survey.
iSource: 2005 National Transit Database, Appendix D. Includes all U.S. transit properties with ≥100 vehicles operated in maximum service. Data for New orleans are for 2004.
jDefined as the ratio of peak-period travel time to free-flow travel time; used as a measure of congestion. A value of 1.35, for example, indicates that a 20-minute free-flow trip takes 27 minutes in the peak hour. Source: Schrank and Lomax, The 2007 Urban Mobility Report, Texas Transportation Institute.
kSource: FEMA (declared disasters by state); top three disasters (disasters in parentheses are tied with respect to frequency) and disasters that occurred more than five times in the past 15 years (1992–2006).
