Performance Measurement Framework for Highway Capacity Decision Making (2009)

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96A P P E N D I X B High-Value Data InvestmentsEnvironmental Factors: Water Quality and Watersheds Synopsis of Performance Measures The performance measures identified below capture both traditional and “future thinking” metrics on water quality and watershed health. Measures are used to model potential impacts, gauge whether proposed projects would pass envi- ronmental review, and, in general, assess compliance with the Clean Water Act, the National Environmental Policy Act (NEPA), the Endangered Species Act (ESA), and other envi- ronmental laws and regulations. • Water quality parameters: Chemical, biological, and physi- cal parameters are used to model, estimate, monitor, and manage impacts on water quality, water quality standards compliance, impaired water bodies and Total Maximum Daily Loads (TMDLs.) There are numerous metrics, span- ning data on nutrients, sediment, oxygen demand, biological factors (e.g., macroinvertebrate and periphyton populations, fish assemblages, single species indicators), hydrological indi- cators (see also hydromodification), petroleum hydrocar- bons, and others. Depending on the potentially affected water bodies and their designated uses, specific pollutant loads are moni- tored to ensure adherence to legally binding water quality standards. For example, the National Primary Drinking Water Regulations (NPDWRs) or primary standards are legally enforceable standards that apply to public drinking water systems. The NPDWRs relate to a list of specific con- taminants and their maximum contaminant levels (MCLs) in the following contaminant categories: Microorganisms, Disinfectants, Disinfection Byproducts, Inorganic Chemi- cals, Organic Chemicals, and Radionuclides (1). A common “roll-up” measure used by DOTs and other agencies to gauge their water quality impacts for transporta- tion construction sites is the percent of agency projects “incompliance” versus “out of compliance” with water quality standards for downstream water bodies. • Hydromodification measures: These measures are based on hydrological data and are used to model, estimate, mon- itor, and manage the impact on water quality, water qual- ity standards, impaired water bodies and TMDLs, etc. due to the alteration of water bodies. These include tracking of stream widening/downcutting, physical habitat, dry and wet weather flows, flooding, and stream temperature. Hydrological data are typically geospatial and derived from in-situ monitoring. Other less common measures are used for “beyond compli- ance” agency strategic planning and target setting, project alter- native identification and project selection, project monitoring, and adaptive management purposes. While some DOTs and MPOs have proactively engaged in efforts to measure these kinds of parameters, doing so typically requires close collabora- tion with other agencies and entities that collect related data, as well as additional primary data collection and analysis. These “beyond compliance” measures include the following: • Impact on priority water quality protection areas: Impact of capacity enhancement projects on nonregulated water quality in priority water quality protection areas. • Disturbance of riparian, floodplain, or sensitive areas: The change in quality, quantity, location, and functioning of areas adjacent to affected water bodies that strongly influence water quality. • Construction related impacts: Predicted impact on “beyond compliance” water quality during highway expan- sion construction. • Contaminants from highway runoff, stormwater, and other nonpoint sources: Estimate of water quality impacts from highway runoff and stormwater. • Changes in impervious surfaces: The estimated water quality and watershed health impact due to the additional

97impervious surfaces likely to occur in a drainage basin as a result of highway capacity projects. • Consistency with water resource and watershed management/protection plans: Degree of highway capac- ity project plan consistency with water resource and water- shed management plans. Sources of Data for Current Measures • Primary Data Sources: Data on water quality parameters, including biological, chemical, and physical parameters, are largely collected and managed within state agencies, including state DOTs and MPOs, state environmental agencies (those that oversee implementation of the Clean Water Act), natural resource agencies, and sometimes, state departments of health, depending on where state- specific authority lies for water quality monitoring and related health-based requirements. Much of the data is geospatial, composed largely of GIS data layers and remote sensing data. Water quality monitoring data is often also translated into geospatial for both predictive/modeling and monitoring and ongoing management purposes. Local and regional agencies such as counties also collect and manage related data. The U.S. Environmental Protection Agency implements Clean Water Act programs (and related data collection) in a handful of states that do not have del- egated authority to do so. National standards, criteria, and datasets are used as well to serve as general references and the basis or starting points for many state and local datasets and standards. Many of these national sources are listed below. – The USGS National Hydrography Dataset (NHD) is a comprehensive digital spatial dataset that contains infor- mation about surface water features such as lakes, ponds, streams, rivers, springs, and wells. Some of the antici- pated end-user applications of the NHD are multiuse hydrographic modeling and water-quality studies of fish habitats. USGS also provides several analytical NHD tools on line (2). – 303(d) List of Impaired Waters and Associated TMDL Information: Under Section 303(d) of the Clean Water Act, states, territories, and authorized tribes are required to develop lists of waters which do not meet or are not expected to meet applicable water quality standards. The law requires that these jurisdictions establish priority rankings for water on the lists and develop action plans, called Total Maximum Daily Loads (TMDL), to improve water quality. EPA has developed reporting guidance for integrated water quality reports, including TMDL sched- ule development and prioritization (3). A compilation of all state reports on 303(d) water bodies and TMDLs is available at the EPA web site (4).– State and tribal water quality standards constitute the baseline of water quality standards in effect for Clean Water Act purposes. Any revisions determined to be less stringent must be approved by EPA prior to use in Clean Water Act programs. These standards are available state- by-state and tribe-by-tribe and are compiled by EPA (5). Other Widely Used Sources of Data and Related Tools • Watershed management plans. EPA provides grant fund- ing for watershed planning with watershed management plan requirements under Section 319 of the Clean Water Act. However, not all watershed management plans are developed under EPA funding, and because watershed management plans are developed at the local level, there is no single repository for all of these plans. A large number of watershed management plans are available at the state and local levels by searching on the Internet. Other water- shed data, such as geographic location, USGS streamflow data, and relevant citizens groups, is available on EPA’s national “Surf Your Watershed” webpage, described below. Watershed data also is available through each EPA Region’s watershed webpage, a compilation of which is located on this page: http://www.epa.gov/owow/watershed/links.html. • National Water Quality Standards Database (WQSDB) Release 9.0 (December 2007) EPA has developed a National Water Quality Standards Database (WQSDB) to improve public access to information on how the waters they care about are being protected, and how actions in their water- shed can help or harm those waters. The on-line database consists of a compilation of “designated uses,” used by each state to describe the functions each water body is intended to support – fishing, swimming, drinking water source, or some other use. For some states, tribes, and territories, tables and maps of uses also are available. http://www.epa.gov/ wqsdatabase/ • Impervious Surface Analysis Tool: The Impervious Surface Analysis Tool (ISAT) is used to calculate the percentage of impervious surface area of user-selected geographic areas (e.g., watersheds, municipalities, subdivisions). The National Oceanic and Atmospheric Administration (NOAA) Coastal Services Center and the University of Connecticut Nonpoint Education for Municipal Officials (NEMO) Program devel- oped this tool for coastal and natural resource managers. ISAT is available as an ArcView® 3.x, ArcGIS 8.x or an ArcGIS 9.x extension. http://www.csc.noaa.gov/crs/cwq/ isat.html • Nonpoint Source Pollution and Erosion Comparison Tool (N-SPECT): N-SPECT is a complex yet user-friendly geo- graphic information system (GIS) extension that helps coastal managers and local decision makers predict poten-

98tial water-quality impacts from nonpoint source pollution and erosion. Users first enter information about their area (land cover, elevation, precipitation, and soil characteristics) to create the baseline information. They can then add differ- ent land cover change scenarios (such as a development) to get information about potential changes in surface water runoff, nonpoint source pollution, and erosion. N-SPECT has been applied in coastal areas around the U.S., the Caribbean, Central America, and the South Pacific. It oper- ates most effectively in medium-to-large watersheds having low-to-moderate topographic relief. http://www.csc.noaa. gov/crs/cwq/nspect.html • EPA WATERS Expert Query Tool: The WATERS Expert Query Tool is a web-based application that allows users to create queries to display or extract data concerning impaired and assessed waters and associated, approved Total Maximum Daily Loads. For more information, see: http://www.epa.gov/waters/tmdl/expert_query.html • Other data and tools for general public use: – EPA EnviroMapper for Water: The publicly available EnviroMapper for Water is a web-based Geographic Information System (GIS) application that dynamically displays information about bodies of water in the United States. It allows users to create customized maps that por- tray the nation’s surface waters along with a collection of environmental data. Where completed, data are available on Waters, Water Quality Standards, Assessed Waters, Beaches, Sewage No Discharge Zones, and Nonpoint Source Projects. It could be used as an initial scanning tool in lieu of having a more extensive plan or database with this information at hand. For more information, see: http://www.epa.gov/waters/enviromapper/index.html – Surf Your Watershed geospatial-based system which includes watershed profiles, citizen-based groups at work in each watershed, river corridors and wetlands restora- tion efforts, a 303(d) list fact sheet for each watershed, links to USGS watershed information, etc. See: http:// cfpub.epa.gov/surf/locate/index.cfm Performance Data Gaps • Watershed data and the connectivity between water qual- ity at particular highway-related locations with water- shed health: Watershed protection plans and related data about priority watershed protection areas/units, watershed health vulnerabilities, and watershed-level (or subwater- shed unit level) watershed health metrics that can clearly be tied to highway capacity projects. Although these kinds of data are being worked on by some agencies and collab- orations (e.g., see the Maryland 301 case study), most agencies are struggling with having the right data and ana- lytical tools to plan and design highway capacity projectsthat protect or enhance watershed health in a clear and definable way. • Data on nonpoint-source pollution and related analyti- cal tools: Data on point source dischargers is routinely tracked and well documented under federal NPDES per- mitting and related regulations and rules. Today, the big- ger data challenge surrounds nonpoint sources which many experts believe to be the bigger threat to water qual- ity in addition to being significantly harder to track and manage. Nonpoint source data and analytical modeling and decision-making tools are generally lacking, yet are of great interest to parties that want to protect water quality to both attain and move beyond regulatory compliance. • Impervious surface information and related modeling and predictive analytical tools: Data at the watershed and subwatershed unit levels for impervious surfaces and how highway capacity projects could or would affect impervious surfaces is needed but not readily available. This is a two- part challenge: a) having the necessary data; and b) having the tools and technologies to use the data to understand highway impacts. • Stormwater management data: There is a growing con- sensus that improved stormwater management is critical to protecting water quality, particularly in urban areas or other areas with large percentages of impervious surfaces or other factors that contribute to significant stormwater pollutant loads. Data and tools that go beyond TMDL best manage- ment practices are needed to solve this problem because existing tools and technologies are not achieving desired water quality protection or enhancement results. High-Value Data Investment Opportunities The four data gap areas described above – watershed data, nonpoint source pollution data, impervious surface data, and stormwater management data – all pose strong oppor- tunities for high-value data investments that could make significant strides in water quality protection beyond what already is known and practiced. Although work is being done in each of these areas, specific work that links highway capac- ity planning to data availability and realistic approaches for DOTs and MPOs in these areas is still needed. The other high-value data investment opportunity is to develop local and statewide partnerships with other agencies and entities that collected relevant data and have a mutual interest in protecting water quality and watershed health. In many if not most areas, data, tools, and even measures exist that can help to enable project selection, planning, mitigation, etc. that will substantially enhance water quality protection over the status quo DOT approach which often considers these factors late in the process and is limited to regulatory compliance. The Ecosystem Enhancement Project in North Carolina (see case

99study) is one example of a cross-agency partnership that has resulted in the protection of several priority watershed areas while simultaneously resulting in significant reductions in the wait time for environmental review and permitting for state transportation projects. Environmental Factors – Ecosystems, Biodiversity, and Habitat Synopsis of Performance Measures Transportation systems affect ecosystems, biodiversity, and habitat in a variety of ways, including road kill; loss and degradation of natural areas; air, water, soil, and noise pollu- tion; and introduction of invasive species. Although some DOTs are implementing improved planning approaches to address these issues, these impacts have traditionally not been considered until the NEPA permitting process if they have been considered at all. Species listed for protection under the Endangered Species Act (ESA) are one of the few performance measures consis- tently tracked by DOTs that are related to ecosystems, bio- diversity, and habitat. Animal-vehicle collisions are often tracked as well. However, DOTs rarely track impact of trans- portation on habitat areas, consistency of transportation plans with wildlife, habitat and resource management plans, or native plant community disturbance. There are notable exam- ples, however, where states or DOTs have made ecosystems, biodiversity, and habitat a priority, including North Carolina, Florida, California, Colorado, Maryland, and Washington. More often, these issues arise in relation to specific transporta- tion projects and their potential impacts. The key data needs for assessing transportation impacts to ecosystems, biodiversity, and habitat include: • Landscape and ecosystem data: land use; natural areas; wet- lands; lakes and streams; habitat size, quality, and location; native vegetation communities. This includes endangered or threatened ecosystems and high-quality ecosystems that are worthy of protection. • Species data: Species of concern (federal and state listed species) and their life-cycle habitat needs; invasive species and degree of threat to native species. • Road impacts data: road kills and chronic road kill sites; species movement/migration routes affected by roads and obstacles to movement (culverts, etc.); habitat fragmenta- tion due to roads; water, air, soil, and noise pollution; poten- tial contribution to further land use changes (typically from less developed to more developed). Transportation agencies do not typically collect or main- tain environmental and natural resource data beyond thosethey are required to have for NEPA, ESA, or other regulatory compliance purposes. Instead, this data is more commonly collected and maintained by federal, state, tribal, and local environmental, natural resource, or fish and wildlife agencies. Some private organizations such as The Nature Conservancy or local land trusts also collect and maintain some of this data. Sources of Data for Current Measures • Primary data sources: Some landscape data is available at a national level. U.S. EPA and USGS offer GIS data layers for hydrology, land use, and wetlands; U.S. Fish and Wildlife Service and NOAA Fisheries maintain lists of federally pro- tected species. However, assessment of local and specific environmental impacts typically requires up-to-date data that has been “ground-truthed,” often at a local level. State and local entities often develop higher-scale landscape data to provide increased detail and accuracy. Other Widely Used Sources of Data • State Wildlife Action Plans: Under the State Wildlife Grants (SWG) Program and the Wildlife Conservation and Restoration Program (WCRP), each state is encouraged to produce a Comprehensive Wildlife Conservation Strategy (CWCS) – or Wildlife Action Plan. Developed in consul- tation with local stakeholders and reviewed by a National Advisory Acceptance Team, the Plans set a vision and a plan of action for wildlife conservation and funding in each state. While fish and wildlife agencies have led the Wildlife Action Plan development process, the aim has been to cre- ate a comprehensive strategic vision for conserving the state’s wildlife. A summary of state Wildlife Action Plans as well as links to contacts and more information on each state’s plan is available at: http://www.teaming.com/pdf/ StateWildlifeActionPlansReportwithState Summaries.pdf • Ecoregional Conservation Assessments: The Nature Con- servancy has produced Ecoregional Conservation Assess- ments for much of the United States. These are designed to identify an efficient network of lands where the viabil- ity of a region’s biological diversity could be maximized by abating major threats. Assessments are systematic and comprehensive analyses that represent a new, synthetic data source for thousands of species. Most assessments include a summary report describing the assessment process and methods used, as well as a geodatabase, metadata, and schema graphic. • ESA Critical Habitat and Recovery Plans: The U.S. Fish and Wildlife Service and NOAA Fisheries have designated crit- ical habitats and developed recovery plans for many ESA listed species. These plans and critical habitat areas provide data to help guide transportation planning and mitigation.

100• Natural Heritage Programs: Natural Heritage Programs are located in each state and are variously housed in state wildlife or natural resource agencies, universities, or as stand- alone entities. These programs maintain data and infor- mation on rare and endangered species and threatened ecosystems. They operate under the umbrella organization NatureServe, which offers a decision-support system for land use planning and resource management called Vista that 1) identifies conservation elements; 2) summarizes conservation value; 3) generates conservation solutions; 4) evaluates land use scenarios; and 5) explores sites and creates mitigation plans. Vista uses ESRI’s ArcMAP 9.1 GIS mapping technology. Performance Data Gaps • Data on landscapes, species, and road impacts are incon- sistently maintained across the country. Significant quanti- ties of data related to ecosystems, biodiversity, and habitat are collected, but the collection, assessment, maintenance, and distribution of that data is highly fragmented. In any given state or location, this data could be collected and maintained by literally dozens of federal, state, local, tribal, academic, and private entities. Moreover, the datasets are likely to be kept in multiple formats and be appropriate for the limited set of purposes for which it was collected. High-Value Data Investment Opportunities • Interagency collaboration/integrated planning: Collecting and maintaining ecosystem, biodiversity, and habitat data is largely beyond the mandate, scope, and expertise of trans- portation agencies. In addition, numerous other entities already maintain much of this data. To address this issue, a number of DOTs have moved to an interagency and collab- orative approach to transportation planning. By forming partnerships with environmental, natural resource, and fish and wildlife agencies and other entities, DOTs can leverage the data and knowledge of those entities to reduce conflicts and improve the efficiency and effectiveness of transporta- tion planning. Through partnerships, DOTs also can seek assistance from those entities in collecting data that would be tailored to transportation needs. • Interagency collaboration is promoted in Eco-logical (6) as a mechanism for developing an ecosystem approach to infrastructure development, which recommends creating a Regional Ecosystem Framework. This consists of an “over- lay” of maps of agencies’ individual plans, accompanied by descriptions of conservation goals in the defined region(s). A Regional Ecosystem Framework is intended to help agen- cies develop a joint understanding of the locations and potential impacts of proposed infrastructure actions. Withthis understanding, they can more accurately identify the areas in most need of protection, and better predict and assess cumulative resource impacts. A Regional Ecosystem Framework also can streamline infrastructure development by identifying ecologically significant areas, potentially impacted resources, regions to avoid, and mitigation opportunities before new projects are initiated. • GIS data sharing agreements and web-based GIS data access: Transportation planners can benefit from having direct access to GIS and other data held by environmental, natural resource, and fish and wildlife agencies and enti- ties. Because this data tends to be dynamically updated, acquiring static data layers is only partially beneficial. Some states and interagency partnerships have developed GIS data sharing agreements among agencies that allow direct access to current GIS data over the web. This provides trans- portation planners with up-to-date information. Examples include the Oregon Explorer web site (7), which provides a natural resources digital library. New York State has a statewide GIS Data Sharing Cooperative. Environmental Factors – Wetlands Synopsis of Performance Measures Wetlands measures in widespread use by DOTs today focus on tracking quantity not quality of wetlands. Performance reporting confirms that throughout the nation an estimated 1,100 to 2,400 acres of wetlands are impacted annually as a result of federally funded highway projects (8). Two wetland- related performance measures are commonly tracked by state DOTs to support management of their wetland mitigation programs. U.S. DOT reports that 92 percent of DOTs provide the following information to FHWA annually (9): • Wetland Losses Measure: Tracks total annual statewide wetland acreage losses as a result of transportation project construction. • Wetland Replacement Measure: Tracks total annual statewide wetland acreage replaced in compensatory miti- gation as a result of transportation project construction. Use of wetland losses and replacement acreage measures, in combination, provide a useful statewide gauge of the quan- tity of impacts to wetlands associated with transportation projects. They do not, however, provide a good indication of the ecological consequences for wetlands of losses or replace- ments. Ecological impacts depend not just on acreages, but also on 1) the location, types, and quality of wetlands lost; and 2) the location, types, and long-term success of mitigation sites. Data on these variables is more complex to gather than basic acreage data. It is fragmentary in reach and located

101among many agencies, while new methods are constantly evolving to improve data availability. Use of wetland quality- related data, particularly by DOTs, is in its infancy. Sources of Data for Current Measures • Primary Data Source: Data are collected by state trans- portation agency environmental personnel from review and collation of information available in internal project records and other sources, particularly Section 404 permit program-related field surveys. Data reported to FHWA on or around the close of each federal fiscal year, but may easily be reported on a calendar year basis. Other Widely Used Sources of Data • National Wetlands Inventory (NWI) – A nationwide col- lection of digital wetlands data maintained by U.S. Fish and Wildlife Service and available for public use. Data is dis- played on base maps that cover more than 90 percent of the lower 48 states. It generally shows the location, size, and function of wetlands. The maps are prepared from analy- sis of high-altitude imagery. Wetlands are identified based on vegetation, visible hydrology, and geography. • State-Level Wetlands Inventories – Some states have created their own state-level wetland inventories, e.g., the Wisconsin Department of Natural Resources’ Wisconsin Wetland Inventory or the Michigan Department of Environmental Quality Michigan Wetland Inventory that often supplement NWI information. Performance Data Gaps • Data on Wetland Quality – Traditional regulatory approaches for mitigating wetland impacts of transporta- tion projects (and the performance measures described above) place an emphasis on mitigating the quantity of wetlands affected. A growing consensus is emerging, how- ever, that case-by-case mitigation of “local symptoms” rather than mitigation that addresses watershed-wide issues is failing to halt environmental degradation. Federal trans- portation legislation now favors offsite banking mitigation, where per unit ecological benefits are usually higher than onsite mitigation. • A watershed-wide approach to mitigation acknowledges that some wetlands have greater ecological value than others. DOTs, however, typically do not have easy access to data on the ecological value of wetlands in the vicinity of planned projects that would enable them to adopt watershed-wide planning strategies. Consideration of statewide wetland quality data early in project development would offer DOTs additional flexibility to select project alignments that bothminimize mitigation costs and strengthen stewardship of the environment. • Data on Success of Wetland Mitigation Sites – As many as 50 percent of wetland mitigation sites are unsuccessful. Federal regulations require monitoring of mitigation sites, however, states’ monitoring practices vary and few states track mitigation site performance beyond a site-specific scale. High-Value Data Investment Opportunities • Develop Remote-Sensing-Based Data for Collecting, Ana- lyzing, and Presenting Wetland Quality Data on a Regional or Statewide Scale – Wetland quality data is traditionally developed using time intensive field surveys and is there- fore carried out only for site-specific locations on an as- needed basis. Remote sensing is a widespread technology that relies on various types of imagery (often taken via satellite) to enable creation of data where gathering tradi- tional data would be impossibly time consuming. Several states, including Minnesota (10) are experiment- ing with use of remotely sensed data as a technique for gauging wetland quality across large regions. DOTs, as well as many other organizations, could use this information to streamline their wetland-related activities and enhance their stewardship of the environment. Work is needed to develop methods for collecting, analyzing, and presenting data. Key data development needs include: – Development of partnerships between DOTs and others to use remote sensing imagery to assess wetlands based on plant community structure and diversity, as deter- mined by the pixel diversity of images detected from multispectral remote imagery; – Development of expertise within DOTs in the funda- mentals of remote sensing (platforms, physical basis, visual interpretation, automated image interpretation); – Collection of appropriate photogrammetry (air and satellite photography); – Use of digital image processing (multispectral analysis, image rectification, enhancement, pattern recognition) software to translate imagery – Raster analysis (data analysis, overlay, spatial character- ization); and – Approaches for presenting information in ways that are useful to project developers at DOTs and their resource agency partners. Remote sensing imagery offers a credible baseline of infor- mation to evaluate alternatives early in the process [of NEPA], and eliminating unnecessary and costly detailed analysis. • Develop Data for Tracking Statewide Effectiveness of Wetland Mitigation Sites. North Carolina DOT’s moni-

102toring program provides an example of site-specific data reporting (11). Washington State DOT is now reporting statewide mitigation success rates and might offer a model for development of suitable measures. Key data develop- ment needs include: – Selection of appropriate biological and hydrological measurement metrics for measuring success over a mitigation site’s lifespan; – Securing resources to cover costs of collecting data; – Development of easy-to-use but accurate yardsticks that provide a gradient between “success” and “failure,” based on analysis of many variables; and – Data storage and reporting mechanisms. Wetland mitigation site success rate data offers an emerg- ing tool for evaluating DOTs’ progress as effective environ- mental stewards. Environmental Factors – Environmental Health Synopsis of Performance Measures Environmental health typically refers to the impact on human health and well being due to physical, chemical, bio- logical, and other components of the surrounding environ- ment. While other environmental and safety factors addressed in this report have potential to affect public health, this envi- ronmental health factor focuses on air toxics – a factor that has received increasing attention in highway capacity expan- sion projects in recent years. Mobile source air toxics (MSAT) are a byproduct of vehicle emissions and are a known or suspected contributor to numerous cancer and noncancer human health problems. The U.S. Environmental Protection Agency (EPA) has identified six priority MSATs: acetaldehyde, acrolein, benzene, 1,3-butadiene, diesel particulate matter, and formaldehyde. Because the science on air toxics is still evolving, there are no established criteria for determining when MSAT emissions should be considered a significant issue in the NEPA context. The FHWA issued interim guidance for NEPA documenta- tion related to air toxics in February 2006 (12) which advises DOTs to limit project-specific assessments of MSATs to situ- ations where projects are expected to result in meaningful dif- ferences in MSAT emissions between project alternatives or increases in potential public exposure to MSATs. Despite cur- rent data limitations in many areas, DOTs can benefit from tracking performance measures in the following areas to better anticipate and respond to air toxics issues and concerns that may arise related to highway capacity expansion projects: • Concentrations of Six Priority MSATs: Tracks monitored and/or modeled air quality status related to six priorityMSATs. While the focus of DOT measurement activities should be on tracking air toxics emissions associated with mobile sources and capacity expansion plans, it is increas- ingly important for DOTs to track (and in special circum- stances, collaborate on) environmental agency efforts to monitor ambient air toxics concentrations. • Proximity of Vulnerable Populations Potentially Affected by MSATs: Tracks the amount and location of potentially vulnerable populations (e.g., housing units, schools, hos- pitals, nursing homes) proximate to highways or major roadways. Proximity of sensitive receptors to highways and major roadways can be an important planning factor since air toxics concentrations tend to tail off rapidly within 300 meters of roadways. In many areas, ambient monitoring of air toxics concen- trations is not currently available and such monitoring may not be feasible for state or local environmental agencies to collect given current priorities and resources. In these situ- ations, emission inventories and modeling are the primary source of information on local or regional air quality status related to MSATs. The proliferation of air toxics monitor- ing activities (including near-roadway studies), however, are increasing the availability of data for analysis and benchmarking of local and regional air toxics air quality status. Even when information on ambient concentrations of air toxics (monitored or modeled) is available, challenges exist with translating this information to assess public exposure and associated human health risks. While many MSATs have documented cancerous and noncancerous health effects, it can be difficult to determine program or project-specific risks from this information. Even while understanding of MSAT health effects is evolving, however, information on the effi- cacy of various near-road air toxics mitigation measures is growing, as illustrated by the Watt Avenue, Sacramento, Cal- ifornia case study highlights. Sources of Data for Current Measures • Primary Data Sources: MSATs are a relatively new and emerging area for data collection, analysis and performance measurement in the context of transportation planning and projects. Data on air toxics emissions and increasingly on ambient concentrations of MSATs are collected by EPA and state and local environmental agencies. The availabil- ity of information on human health risk varies for each MSAT. Scientific studies are used to develop Unit Risk Fac- tors that can translate ambient concentrations into cancer- related health risk estimates. Reference Concentrations also are commonly set to assess when noncancer health effects may occur.

103Information on the proximity of sensitive receptors in trans- portation corridors is collected by some transportation and environment agencies and is often a component of geographic information systems (GIS) supporting transportation, land use, and environmental planning. Potential Sources of Data • National Air Toxics Assessment (NATA) and Emissions Inventories – EPA conducted National Air Toxics Assess- ments (NATA) in 1996 and 1999 to evaluate the distribu- tion of air toxics across the United States (13). The NATA data were used to compile national emissions inventories on air toxics, estimate air toxics levels across the nation, estimate population exposures, and characterize public health risks. EPA also seeks to estimate the national levels of air toxics through its National Emissions Inventories (NEI) (14). NEI includes estimates of HAP emissions from mobile sources. EPA has developed compilations of NEI data for 1996, 1999, and 2002, and is working to provide additional compilations every three years. State and local agencies also may assemble air toxics emission inventories on a periodic basis. Information from air toxics emissions inventories and modeling efforts can be highly useful to identify transportation corridors and areas where ambient air toxics concentrations may be of particular concern when considering the proximity of sensitive receptors and/or the air quality status relative to other urban areas in the U.S. • National Air Toxics Trends Stations (NATTS) Network – EPA launched a national air toxics data monitoring effort in 2004, which is referred to as the National Air Toxics Trends Station (NATTS) program. The NATTS program currently is comprised of 25 monitoring sites in urban areas across the U.S. and generates data regularly on ambient concentrations of 21 air toxics, including the six priority MSATs. The EPA-sponsored Urban Air Toxics Monitoring Program (UATMP) is another important source of ambi- ent air toxics monitoring data, which currently includes air toxics monitoring data for 59 sampling sites in urban areas (15). Some state and local environmental agencies also make their own air toxics monitoring data available on-line. • Community-Scale Near-Roadway Air Toxics Studies – Information from an increasing array of site-specific studies of near-roadway air toxics concentrations and associated health effects are becoming available. EPA’s community-scale air toxics monitoring grant program is providing funding to state and local agencies to conduct air toxics monitoring to better assess air toxics concentra- tions and health risks from sources such as roadways, rail yards and ports. FHWA also is supporting pilot studies on transportation-related air toxics issues in Nevada, North Carolina, and Michigan. Several other studies are being con-ducted in California by parties, including UC Davis and by the Air Resources Board and Caltrans. While the findings from these and other site-specific near-roadway studies may not be easily transferable to other locations, it is anticipated that findings from these studies will increasingly inform public comments on DOT planning and projects across the U.S. Data from these site-specific studies can be used to inform qualitative risk assessment by DOTs, as well as to inform assessment of potential mitigation measures that could be proposed to address potential air toxics “hot spots” near vulnerable populations. Performance Data Gaps • Data on Ambient Air Toxics Concentrations – The avail- ability of data from air toxics monitoring is limited in many areas of the U.S. While some states, such as Califor- nia, have extensive air toxics monitoring programs and networks of sampling sites, many other parts of the U.S. have limited monitoring data. Even if there is a monitor- ing station located in an urban area, its proximity to a particular transportation corridor and other confound- ing factors (e.g., meteorology, effects of stationary sources of MSATs) can severely limit the usefulness of available monitoring data. • Data on Impact of Vehicle Fuel Mix Changes on Air Toxics – There appears to be substantial uncertainty regard- ing how changes over the next few decades in fuel mix and vehicle types will impact the prevalence of different MSATs. While experts anticipate that cleaner vehicles and cleaner fuels will substantially decrease mobile-source air toxics emissions, changes in fuel mix may result in significant increases in certain individual MSATs even while overall air toxic emissions are declining. • Data on Human Health Risks Associated with Exposure to MSATs – While the prevalence of studies on cancer and noncancer health effects of exposure to various MSATs is increasing, many uncertainties remain. In 2007, the Health Effects Institute released a report on the state of research on exposure and health effects associated with MSATs (16). High-Value Data Investment Opportunities • Develop Local Partnerships to Monitor MSAT Concen- trations – Exploring partnerships with state and local envi- ronmental agencies and EPA can enable cost-effective ambient monitoring of near-road air toxics concentrations in key areas of concern. In many cases, data already may exist through emerging sampling and trends sites. For urban areas where no monitoring exists, partnerships with state and local environmental agencies can be used to lever-

104age EPA resources for monitoring through the NATTS pro- gram or the Community-Scale Air Toxics Monitoring grant program. There also is an opportunity to expand on the work being done by UC Davis to study the efficacy of vari- ous cost-effective measures to mitigate near-road exposure to MSATs through additional pilot studies. • Conduct Meta-Analysis of Site-Specific MSAT Studies – The proliferation of pilot projects to assess the preva- lence and health effects of MSATs, including the FHWA- sponsored studies, are providing increasing opportunities to look across existing and emerging studies to assess pat- terns and the extent to which findings may be transferable. In the future, it may not be necessary to invest in near-road air toxics monitoring in areas where cost-effective “best practice” mitigation measures can be proposed to address public concerns related to air toxics “hotspots.” • Improve Data on MSAT Exposure and Health Effects – The Health Effects Institute’s November 2007 review of the literature on MSAT exposure and health effects makes a series of recommendations for improving the state of knowledge. While many of these recommendations are outside the purview of DOTs, dialogue and partnerships with public health and environment agencies can help to advance some of these efforts to improve understanding of MSAT health. Environmental Factors – Climate Change Synopsis of Performance Measures Climate change measures are only beginning to be intro- duced as part of state DOT and MPO decision making, and there is not yet a consistent approach to climate change data and model projections. Climate change considerations for transportation include two distinct areas that require differ- ent information and measures: • Greenhouse Gas Emissions from Transportation Mea- sures: Assesses the actual or projected levels of greenhouse gas emissions from existing or proposed transportation projects; and • Impacts of Climate Change on Transportation Measures: Assesses the risk and vulnerability of transportation systems and facilities to the effects of climate change. Greenhouse Gas Emissions from Transportation A growing number of states and regional governments are beginning to track and calculate greenhouse gas (GHG) emis- sions from mobile sources. Over 35 states have set Climate Action Plans that include either goals or specific targets for reducing transportation GHG emissions. Some plans focuson travel demand strategies; while others focus on fuel effi- ciency, introduction of alternative fuels, and vehicle tech- nologies to reduce consumption of carbon-based fuels. Most notably, California has passed legislation creating light-duty vehicle GHG standards to take effect beginning in 2009 and phased in through 2016. The emission standards apply to the full fuel cycle and will result in a 34 percent reduction in GHG emissions from passenger cars and light-duty trucks and a 25 percent reduction in emissions from light-duty trucks. Roughly a dozen other states, including most of the North- east states as well as Florida, have adopted California’s GHG standards along with the California Low-Emission Vehicle (LEV) standards for criteria pollutants and precursors. The standards have not yet been implemented, however, due to legal challenges. The U.S. Environmental Protection Agency is developing a draft rule regarding GHG emissions through fuels and technologies. Measures of greenhouse gas emissions can be generated at a system level by measuring fuel consumption and calculat- ing the levels of carbon dioxide and other GHGs emitted by the burning of carbon-based fuels. At the project level, rough measures of emissions can be derived based on estimates of vehicle miles of travel (VMT) and fuel economy. Much of this information currently is available. More accurate estimates would incorporate information on average speeds, drive cycles, and vehicle types as well. Generating this information requires more complex assumptions and/or use of more advanced models or microsimulation. Impacts of Climate Change on Transportation Measures of risk to climate change require the integration of multiple factors regarding the location and condition of infra- structure, the probability of impact, and the degree of severity of individual and cumulative impacts of climate factors. Typi- cal climate factors include changes in: • Temperature (average annual temperature and daily extremes); • Precipitation (average annual precipitation and intensity of individual rainfall events); • Sea level rise; • Storm surge; • Severe storm activity (including frequency of severe storms as well as the intensity of individual storm events); • Coastal and inland erosion; • Ice and snow melt; and • Permafrost condition (range, thawing). The climate factors relevant to a DOT vary according to the region involved. To assess risk to transportation infrastruc- ture and services, data on these climate factors is incorporated

105with information about facility condition, location, and level of significance to mobility and service continuity. Sources of Data for Current Measures • Primary Data Source, Greenhouse Gases from Mobile Sources: Fuel consumption data is available through annual reports generated by the Energy Information Agency of the U.S. Department of Energy, as well as from individual state reports. VMT data is tracked by individual DOTs, and VMT projections are developed by both state DOTs and regional planning agencies through travel demand model- ing. Fleet composition and vehicle fuel economy data is maintained by the U.S. Department of Transportation, and by individual states. • Primary Data Source, Impacts of Climate Change on Transportation: Information on both the location and condition of infrastructure facilities (highways, airports, transit facilities) is maintained by a variety of state and local transportation agencies. Private-sector owner/operators maintain data on location and condition of ports, rail- roads, and freight facilities. Trend information on temper- ature, precipitation, and storm activity is maintained by the National Climatic Data Center of U.S. NOAA, as well as by state Offices of Climatology. Climate model projec- tions are conducted by NOAA research offices, including the Center for National Climatic and Atmospheric Research (NCAR); NASA; and other federal agencies. Federal cli- mate research across federal agencies is coordinated by the U.S. Climate Change Science Program. Other Widely Used Sources of Data • Conditions and Performance Report – The U.S. Federal Highway Administration issues annual reports on the con- dition of surface infrastructure through its Federal High- way Statistics, Conditions and Performance, and Highway Economics Reporting Systems Reports. Other modal agen- cies issue parallel reports. Performance Data Gaps There are several data gaps that need to be addressed to accu- rately assess performance on climate change. Greenhouse Gas Emissions from Transportation • Alternative fuels emissions data – While current direct (tailpipe) emissions are well understood, the shift toward nonpetroleum fuels (e.g., ethanol, biofuels) has led to increasing uncertainty due to fuel life-cycle emissions. While models are available to estimate these emissions, the growing role of alternative fuels will continue to increase uncertainty in this area.Impacts of Climate Change on Transportation • Region-level projections for changes in climate condi- tions – Several global circulation models (GCMs), recog- nized by the Intergovernmental Panel on Climate Change (IPCC) are available that provide global projections of climate change. These models are used by researchers to generate projections at national and regional scales. As mod- eling science progresses, the ability to generate regional- level climate scenarios is advancing. A combination of trend information with potential climate scenarios can provide useful ranges of potential impacts that can be used for transportation decisions. However, the current state of science involves levels of uncertainty that preclude specific projections at more localized scales. • Standardized data on locations and elevations of infra- structure – Information is often not readily available regard- ing both land elevations and actual infrastructure elevations, or is not yet available in geospatial format. This information is critical in coastal areas and other sensitive locations. • Standardized geospatially based data on environmental trends – While data on environmental trends is collected and available from science and resource agencies, it is often not readily usable by transportation agencies. Improved packaging of data in terms of scale, geographic/political boundaries, and geospatial coding would greatly improve the usefulness of environmental trend data. High-Value Data Investment Opportunities Greenhouse Gas Emissions from Transportation: Improve Life-Cycle Modeling and Travel Activity Behavior Models Two primary areas of data improvement are required to enhance GHG emissions tracking and benefits analysis. • Life-cycle models: Life-cycle models of GHG emissions still require improvements to understand the tradeoffs avail- able in fuel policies. • Travel behavior: The effectiveness and cost effectiveness of travel activity behavior pattern measures, especially with regard to externalities, is still not well understood. Better grasping of the implications of these two areas is critical to best reducing GHGs from transportation. Impacts of Climate Change on Transportation: Develop Geospatial Data Integrating Transportation Information with Environmental Trends and Climate Change Projections A geospatially based platform to integrate transportation and climate information would support DOTs in identifying infrastructure at risk and selecting and prioritizing adaptation

106and investment strategies. These integrated datasets would include the following: Transportation Data • Location of transportation facilities, including roads, rail- roads, airports, ports, and intermodal facilities; • Location of emergency evacuation routes; • Land and facility elevations; and • Location of protective structures (levees, dikes). Environmental Trend Data • Precipitation levels (seasonal averages and patterns of intense rainfall events); • Temperature (seasonal averages; extreme highs and lows); • Relative sea level rise; • Storm surge heights; and • Location and duration of flooding events. Climate Scenario Projections (model-based scenarios of ranges of potential climate change based on assumptions of emission levels) • Precipitation levels (seasonal averages and patterns of intense rainfall events); • Temperature (seasonal averages; extreme highs and lows); • Relative sea level rise (integrating subsidence and sea level rise resulting from thermal expansion and ice melt); and • Severe storm frequency and intensity. Storm Surge and Flooding Scenarios • Storm surge heights at various levels of storm/hurricane intensity; and • Areas of inundation at various levels of extreme precipitation. Development and analysis of this data will require interdisci- plinary partnerships between transportation and environmen- tal agencies. The following steps should be taken to advance this area of measurement to support more robust risk analysis and planning, and to track agency success in ensuring reliable per- formance and protecting transportation assets: • Develop partnerships between DOTs and regional plan- ning agencies with environmental agencies and climate researchers to develop agreement on data requirements, standards, and geospatial integration • Develop probabilistic risk assessment methodologies to incorporate risk, vulnerability, and uncertainty into siting, design, and investment decisions • Develop approaches for presenting information in ways that are useful to planners, project developers and designengineers, operations and emergency management person- nel, land use planners, and environmental/science agency partners. Community Factors – Land Use Synopsis of Performance Measures One broad category of land use measures involves the land “consumed” by a project or program of projects – either directly as a result of the project’s footprints, or the indirect impacts of induced growth/development associated with the project. At a project level, it is common to measure direct impacts of the project, and for major capacity investments the estimation of indirect impacts is becoming more common. Land use mea- sures also are commonly used at a regional level in long-range planning, especially the amount of land consumed for urban development as a result of a given transportation land use sce- nario or plan. Land consumed by or lost to a project or its indi- rect impacts can be broken down by the specific type of land (e.g., agriculture, forest, wetland, vacant, developed). Direct impacts are relatively easy to evaluate and simply require information on the land use or land cover for the proj- ect area, as well as the project footprint. Indirect impacts are much more challenging, as they require a method of forecast- ing the specific growth impacts of a project (general location and density of development). Land use forecasting models and methods, however, are better suited for examining gen- eral trends in development patterns rather than predicting the precise spatial impacts. Furthermore, simple forecasts of “land consumed” do not evaluate the underlying value of the land for ecological or human purposes, and people may place dif- ferent values on any given type of land use. Because of the dif- ficulty inherent in forecasting indirect land use impacts and the subjectivity of whether many land use impacts are consid- ered “good” or “bad,” land use impacts are often evaluated from a qualitative rather than a quantitative perspective. An alternative set of land use performance measures eval- uates the consistency of the project with local and/or regional land use plans and policies – for example, whether the project serves a designated growth area, or is likely to induce growth consistent with local and/or regional objectives for growth. If growth policy areas have been designated, quantifiable mea- sures can be defined to determine whether the project is inside or outside such an area (although this does not address the question of whether the project will actually induce growth in the desired policy area). Otherwise, the assessment of these measures typically is done from a qualitative, descriptive standpoint. Sources of Data for Current Measures Local jurisdictions (e.g., counties and cities) typically maintain data on both existing and planned land use by category. Such

107data were traditionally kept in the form of a hard-copy map, but now are maintained by most jurisdictions in electronic format. In an increasing number of metropolitan areas, the MPO or other regional planning agency has aggregated local land use data into a regional database for regional planning purposes, although this database may or may not be updated regularly. Existing and planned land use data is most often maintained at a polygon level. Local jurisdictions (and some- times regional agencies) also maintain parcel-level data, used for tax assessment purposes, which include information on existing land use (type of use, square footage, value, etc.) Land use data are often inconsistently categorized across juris- dictions (e.g., different density or use categories), and may not be available in rural areas, especially those lacking compre- hensive plans or zoning. Therefore, aggregating data across a project study area can sometimes be a challenge. Environmental databases of land cover (e.g., forest, grass- land, cultivated, urbanized), wetlands, natural areas, and other natural features represent an additional source of land use data to augment the local sources which consider primarily human and urbanized uses. [The term ‘land use’ typically refers to the purpose for which humans are using the land and can be distinguished from the term ‘land cover’, which empha- sizes the natural or artificial coverage of the land (forest, grass- land, wetland, agriculture, etc. with “urbanized” typically one all-encompassing category).] These data are typically main- tained by a state or national environmental agency. Examples include the National Land Cover Map and hydrography (sur- face water and streams) by the U.S. Geological Survey (USGS). Wetlands and other environmental data are discussed under separate topic areas. Orthophotography (aerial photos corrected for terrain and spatial location) represents an additional source of land use data, which may be used on its own for visual inspection, or processed to identify different types of land uses and land cover. Orthophotography also is available from the USGS. Land use forecasting models are a source of data on future land use. Most models (such as UrbanSim, MEPLAN, and TRANUS) operate at a relatively coarse level (e.g., population and employment by regional subdistrict or traffic analysis zone), although tools such as UPLAN have been developed to disaggregate land use forecasts to a more detailed level for policy analysis purposes. Scenario planning models such as INDEX, CommunityViz, and PLACE3S can be used to develop land use measures for different future scenarios, and a num- ber of custom models or planning tools have been developed throughout the country (e.g., LUCIS in Florida). Performance Data Gaps Data on existing land use are generally quite good, except in some localities (primarily rural areas or smaller communities)where local jurisdictions do not conduct land use planning or maintain comprehensive land use plan data. As previously noted, however, aggregating data into a consistent format across multiple jurisdictions can sometimes be a challenge. For tracking land use changes over time, systems are needed to ensure that land use databases are routinely updated to reflect new construction or other changes in use. A small but growing number of areas have comprehensive tracking sys- tems that allow factors such as land conversion and the type, density, etc. of uses at a small area level to be monitored on a timely basis. Without such a system in place, it can be diffi- cult to evaluate actual growth patterns (e.g., amount inside versus outside policy areas) on a timely basis. As previously noted, land use forecasting methods gener- ally involve quite a bit of uncertainty. Furthermore, robust models can be time-consuming and resource-intensive to develop. While the state of the practice is improving, there are inherent uncertainties related to the difficulty in pre- dicting human behavior which, combined with the level of effort required for comprehensive data collection and model development, mean that forecasting of land use impacts is likely to remain an imprecise activity in the foreseeable future. High-Value Data Investment Opportunities At a metropolitan area level, efforts to integrate local land use data into a regional view have proven extremely valuable for regional planning efforts as well as project or corridor planning efforts that span multiple jurisdictions. Further data integra- tion efforts should be encouraged, along with systems to main- tain regional databases with real-time updates from local jurisdictions. Because land use data collected and maintained at the county and city level are usually collected at different res- olutions using different classification schemes, agreement on a common generalized regional land use classification scheme would be of great value. Innovative institutional arrangements to build interjurisdictional and interagency partnerships for data collection and integration could be pursued in order to achieve success in this area. Data integration should include geospatial tracking of build- ing permit data to support monitoring of land use changes over time. Satellite imagery can be used for routine verification of land use changes. Portland Metro’s Regional Land Information System (RLIS) is an example of a regional data integration sys- tem that includes existing land use, building permits, planned land use, and other data at a parcel level. RLIS has been used to compare actual with planned population and employment growth in designated growth centers, and to track the density and location of new development in the region. Remote sensing, based on aerial or satellite imagery, is a promising source of data on existing land use/land cover,

108especially describing the physical features of the use. Remote sensing has been used to develop land use databases in areas where local data are inadequate or an inordinate amount of effort would be required to aggregate databases. It also may be used to develop metrics of the design of the built environ- ment, such as building coverage, parking lot coverage, set- backs, transportation facility widths, etc. that may relate to transportation and/or environmental impacts. A final area for leveraging existing data is public/private sector agreements that enable access to privately maintained land use data (such as real estate records.) Models for ensur- ing protection from disclosure of proprietary data and for creating value propositions that enable this type of data sharing would be of value. Community Factors – Archeological and Historical Sites Synopsis of Performance Measures Federal agencies are required to preserve and enhance cul- tural resources, including historic and archeological sites of significance. Transportation officials are required to work with federal and state agencies to identify historic proper- ties that could be affected by a transportation project, and explore what those effects are likely to be. A discussion of the likely effects on historic sites is a requirement in the environmental documentation. The level of detail of this discussion must be on a scale related to the importance of the properties, and the expected impact of the project on those properties. To meet these regulations, most DOTs address impacts to historic, cultural, and archeological resources through the NEPA process, where it is required (17). In addition to NEPA, Section 106 of the National Historic Preservation Act requires that federal agencies identify sites in a project area that are listed in, or are eligible for, the National Register of Historic Places, determine how any sites may be affected by the pro- posed project, explore alternatives to lessen any negative impacts, and work with the State Historic Preservation Offi- cers and/or the Tribal Historic Preservation Officers to reach an agreement about employing measures to mitigate the antic- ipated effects. Under this legislation, federal agencies are required to allow the Advisory Council on Historic Preserva- tion an opportunity to comment on all projects affecting his- toric properties either listed in, or determined eligible for listing, in the National Register. Measures The measures used by DOTs to fulfill the requirements in the NEPA and Section 106 process are typically binary and qual-itative. These questions are typically answered to meet the requirements: • Will the project have adverse or beneficial effects on his- toric or cultural resources? • Will the project have substantial impacts to Indian trust resources or sacred sites? • How will any adverse effects be mitigated? Sources of Data for Current Measures • Primary Data Source: Data used by DOTs for this process is available through the National Register Infor- mation System (18). This on-line database lists all prop- erties on the register and provides street addresses and links to any other pertinent information. Another source of information is the State Historic Preservation Office (SHPO). These offices manage the process of surveying, evaluating and nominating historic buildings, sites, struc- tures, districts and objects for the National Register. Beyond this basic function, SHPOs vary in the type of information they provide. Other Widely Used Sources of Data • Department of Defense Agencies – Some department of defense agencies manage historic properties under Sec- tion 110 of the National Historic Preservation Act, and some have developed GIS databases to be able to map these sites. The U.S. Army Air Force has developed a Cultural Resources Geospatial Data Integration, Air Combat Com- mand which is a model GIS that will be implemented through the Internet. • GIS-Based Cultural Resource Databases – An increas- ing number of DOTs with cultural resources databases are utilizing them in a GIS format, enabling them to map the locations of the sites and conduct spatial analysis. Historic site data layers can be combined with environ- mental layers to conduct locational analyses on more than one factor in this framework. Pennsylvania, Wyoming, and New Mexico are three examples of states with cul- tural and historic resources GIS databases and mapping capabilities. • Historic Property Screening Tools (HPST) – The Historic Property Screening Tool (HPST) was developed through a National Cooperative Highway Research Program (NCHRP) project. HPST is a database management tool for cultural resource inventory information and historic contexts. The tool records National Register eligibility decisions and guides the user through the National Register decision-making criteria. The HPST requires that agencies adapt to a specific and consistent reporting structure.

109• ElectronicCulturalResources Evaluation Library (ECRL) – Also developed through NCHRP, ECRL improves accessibil- ity to National Register evaluation documents and historic contexts. The use of ECRL provides a portal where agen- cies can store their documentation and access documents from other agencies. • Archeological Predictive Models – Locations of archeo- logical sites are often unknown prior to project construc- tion. Discovery of a significant archeological site can stall a project for months or more, incurring great cost and inconvenience for agencies, taxpayers and residents. However, models can be used to predict the probability of finding an archeological site on the basis of the rela- tionships between known sites and a variety of environ- mental factors. These models are specific to a certain region, based on topography, vegetation, climate, other environmental factors, and known characteristics of ancient populations. Minnesota DOT had developed Mn/Model, a good example of an archeological predic- tive model. Performance Data Gaps Since this process traditionally does not happen until the project has been planned and programmed, the identification of impacts to historic sites can bring an already programmed project to a standstill, causing significant delay, an increase in costs, and lead to negative relations with stakeholder groups, tribal agencies, and communities. The key to incorporating these decisions into the process at an earlier stage is easy access to comprehensive and accurate data with locations and significance of sites. Standardizing this system through tools such as the HPST or ECRL would create consistency among states and projects. Linking this to a GIS is the next step. Finally, utilizing cultural resource data layers in conjunction with environmental data layers for alternative review during the long-range planning and preprogram studies phase would provide the most value. High-Value Data Investment Opportunities • Develop Comprehensive GIS-based Tool to Incorporate Environmental, Land Use, Transportation, and Cultural Resource Data – Many agencies are utilizing this technol- ogy, but have not integrated the analysis process. Florida’s Efficient Transportation Decision-Making Process (ETDM) combines collaboration and review among agencies (including the Division of Historical Resources) with an Internet-accessible GIS application called the Environ- mental Screening Tool (EST). GIS analyses, approved by each resource agency, are performed for each project to identify potential impacts to resources (19).Community Factors – Social Synopsis of Performance Measures Most of the performance measures included in the “Social” factor have not been traditionally measured in transportation planning. Some are difficult to measure or find data for; some have just been considered qualitatively; some have only been considered in other types of planning studies. The following five measures are included in the “Social” factor: • Community Cohesion: Project’s impact (either positive or negative) on the sense of community that exists at the neighborhood level, and on the physical attributes that define and bound the neighborhood. • Noise: Impact of noise from construction or ongoing operation of the project. • Visual Quality: Overall visibility of the project, and its consistency with the surrounding visual landscape. • Emergency Response Time: Project’s impact on ability of police, fire, and EMTs to respond to emergencies. • Citizen concerns and priorities addressed by a project: Transportation-related issues of greatest concern to citizens. With the exception of noise impacts, which are a required consideration in the NEPA process, these measures currently are not reported in any systematic way nationwide. Federal requirements for public participation and input have lead to “citizen concerns and priorities addressed by a project” being considered in some form during project planning in recent years, though often more as part of the process rather than a separate measure. Community cohesion impacts are not measured consis- tently across jurisdictions, and often not at all. They are gen- erally incorporated into the public outreach process through delineation of neighborhoods, identification of key destina- tions, and primary pedestrian routes. Community cohesion impacts are usually shown as a compilation of individual fac- tors (such as homes relocated or change in pedestrian travel times), but rarely as a single combined factor. Similarly, mar- ket research techniques have been used to assign priority scores to different projects or improvement types, based on citizens’ stated priorities. Noise impacts are part of environmental review as required by NEPA and FHWA. FHWA requires noise analysis for all Federal-aid highway projects. Current noise levels are ana- lyzed through field surveys as well as the use of the FHWA Traffic Noise Model (TNM). TNM also is used to forecast future noise (20). Emergency response time is increasing in importance after SAFETEA-LU and increased funding and focus on safety and security. SAFETEA-LU has made Strategic Highway Safety Plans (SHSPs) a requirement for all state DOTs, and man-

110dates that such plans be “data-driven, four to five-year com- prehensive plan that integrates the ‘4 Es’: engineering, educa- tion, enforcement, and emergency medical services (EMS)” (21). Emergency response time is a component of highway safety, and any capacity project that improves response times would likely be the result of a need identified in the SHSP. Existing response times are measured through existing EMS data or through the use of travel demand models. Future response times would be measured using a travel demand model, or may be estimated based on the removal of a known bottleneck or barrier, such as a railroad grade crossing. An example of GIS-based data sources include FDOT’s Sociocul- tural Effects analysis, which uses the Environmental Screen- ing Tool, part of the ETDM process, to look at EMS locations. Visual quality has not typically been measured in a trans- portation planning context, and there is little precedent. Some areas, particularly tourist destinations or areas where partic- ular aesthetics are of special importance have methods for assessing visual impacts. These generally follow a method whereby scores are assigned to existing or proposed structures based on their adherence to some accepted visual standards of color, texture, reflectivity, and other physical qualities. Sources of Data for Current Measures Community Cohesion • Census, state, or regional population and housing data and corresponding GIS files. MPOs and states usually have their own socioeconomic datasets. Most agencies prefer to use locally produced data when available, and supplement them with national datasets. Further, state and regional agencies that collect these data also tend to provide fore- casts. These datasets are usually available on-line. • Business location data from proprietary sources. • Land-use datasets or tax assessment datasets are often avail- able from local planning agencies or tax assessors. These provide locations of commercial and residential properties. • Neighborhood association meeting records. • Walking trip data and model results. Walking trip data may be collected by a city transportation or planning department. Noise • Volume, speed, and vehicle types on roadway being studied. These data come from state DOT and local or regional trans- portation agency traffic counts; speed sensors; travel surveys; license plate surveys; or study specific data collection. • Type and location of existing sound barriers from the agency maintaining the roadway of interest. • Locations of homes and population from land-use datasets, aerial maps, or site-specific data collection.• Pavement data from agency maintaining roadway of interest or HPMS dataset. • Field surveys of noise levels for sites of interest. • FHWA Traffic Noise Model. Visual Quality • GIS data on locations of homes, land use, ground cover, elevation (contours), and location of “major landmarks.” • Site-specific data collection on predetermined visual qual- ities of interest, such as color, texture, or reflectivity. Emergency Response Time • GIS data on district (tract, block, etc.) boundaries; street network (GIS or traffic model); and emergency vehicle dispatch locations. • Existing EMS data from local EMS agencies. These data can include EMS dispatch locations and response times. • Travel demand models and GIS-based tools. Future response times would be measured using a travel demand model, or may be estimated based on the removal of a known bottleneck or barrier, such as a railroad grade crossing. An example of GIS-based data sources include FDOT’s Socio- cultural Effects analysis, which uses the Environmental Screening Tool (EST), part of the ETDM process, to look at EMS dispatch locations. The EST is a web-based GIS tool integrated to an extensive statewide GIS database of over 300 layers, allowing all stakeholder agencies to perform their analyses through a centralized location. It uses existing GIS web publishing technology to create a virtual project analy- sis environment accessible to the dozens of separate resource agencies that participate in Florida’s ETDM process. Citizen Concerns and Priorities Addressed by a Project • Surveys, interviews, and other outreach; and • Market research techniques are sometimes used to assign priority scores to different projects or improvement types, based on citizens’ stated priorities (22). Performance Data Gaps Much data, particularly at the project-specific level, would have to be collected for a specific study site to get a meaning- ful result for measures such as noise, visual quality, citizen con- cerns and priorities, and community cohesion. Other specific, typical data gaps include: • Current and forecasted pedestrian movements are often not included in traditional travel demand models or in transportation agencies’ standard data collection.

111• Information on business locations, community “cen- ters,” or residential areas can be difficult to find at early stages and without in-depth site visits. Sometimes land-use datasets may be available, but this is not consistent nation- wide. Further, these datasets may not be up-to-date. • Actual existing response times from EMS data are often not readily available to planners. High-Value Data Investment Opportunities • Land-use datasets are not only useful for many of the Social measures identified above, but are increasingly important in every level of transportation planning and modeling. Increased investment by state, county, MPO, and local governments in up-to-date land-use datasets will yield increased efficiency and accuracy in transportation plan- ning, modeling, and performance reporting. Generally, land use data, when available, is maintained by local munic- ipalities, counties, or MPOs. At the very least, these govern- ments often have assessors’ records or zoning maps already in place and in GIS format; collecting and assembling these datasets into a land-use dataset for application to transportation studies is a fairly low-cost method in well- populated areas. For statewide or sparsely populated areas, various remote sensing technologies – which are more costly – may be required. • Coordination with local EMS agencies, and inclusion of those agencies in stakeholder outreach, is a low-cost way of obtaining actual existing response times. Further, input of these agencies can help identify transportation investments that can improve EMS response times. Community Factors – Environmental Justice Synopsis of Performance Measures Environmental justice measures attempt to examine the dis- tributed effects of proposed transportation projects on dif- ferent population groups that cut across racial, ethnic, and income groups. As such, an environmental justice measure is not a standalone measure to be developed and examined in a vacuum, but rather it entails looking at the results of numerous measures, throughout all the factor areas, to eval- uate how the benefits and costs of a project – social, financial, or otherwise – differ between different groups. In order to be applicable to this type of analysis, an indica- tor need only be measurable over a discrete geographic space. This “second level” measure will be highly dependent on the use of GIS analysis tools to spatially link the results of other measures to the demographics of interest. There are count- less measures that could be developed in this way, and someexamples include: access to jobs and markets; person-hours of delay; noise levels; air quality; and sidewalk connectivity. It also is important to consider that project benefits and costs do not always correspond to the location of the improve- ment itself. The use of “select link” analysis will aid in deter- mining who is actually using a particular section of road, which is key to assessing the distribution of positive or nega- tive impacts. A select link analysis is performed as part of the travel demand modeling process, and identifies the origins and destinations of all users, current or predicted, of a partic- ular roadway segment. For example, widening an existing expressway in a low-income urban community will result in negative impacts to that community: potential acquisition of right-of-way and demolition of buildings; increased noise; potentially increased pollution; and decreased community cohesion, among other possible issues. However, a travel demand model has shown substantial travel-time savings for users of the facility and increased access to job centers. A select-link analysis done during travel demand modeling can help determine the number of users from that particular low- income community, their average travel-time savings with the widened highway, and their improved access to job centers. Sources of Data for Current Measures Environmental justice measures will start with data and results from measures in other factors. The most important data specific to environmental justice are those that deter- mine where groups of interest reside: • MPOs and states usually have their own standards and socioeconomic datasets. Most agencies prefer to use locally produced data when available, and supplement them with national datasets. Further, state and regional agencies that collect these data also tend to provide forecasts. These datasets are usually available on-line. • The Census Transportation Planning Package (CTPP) is a useful tool for identifying existing travel patterns by race, ethnicity, and income group as part of an existing condi- tions analysis (23). • Census data are commonly used to provide demographic information by Census tract or block. • GIS software and layers are often joined with the available socioeconomic data to identify environmental justice areas of interest geographically. • Travel demand models are used usually at the city or regional level to support the application of other measures, such as travel-time reduction, to specifically identified groups or geographic areas. A select-link analysis of an improved roadway, for example, can identify if users from geographically identified environmental justice zones of interest are benefiting from the improvement.

112Performance Data Gaps Using GIS to identify Environmental Justice zones of interest is fairly straightforward if using Census data, and can be done at a fairly localized level (down to the Census Block Group level). This is suitable for looking at localized impacts, such as construction impacts or air quality issues stemming from congestion. The more sophisticated components of Environmental Justice analysis, such as travel impacts (select link analysis or CTPP origin-destination analysis) represent the more labor- and time-intensive aspects of the analysis, as most existing travel demand models do not explicitly integrate all types of socioeconomic data necessary to examine Environmental Justice-related travel impacts. Some relevant data, such as population, employment, and population by income, are typ- ically included at the travel analysis zone (TAZ) level in a model. Other potential divisions of interest, such as racial, ethnic, or mobility impaired groups, are usually not included. These data may be divided geographically in ways that do not easily correspond to the TAZ divisions in a model. Integrat- ing additional Environmental Justice-related geographic data into the ongoing travel demand modeling process would save considerable time and effort. Another potential data gap is caused by the time lapse in available Census data. Implementation of the American Com- munity Survey as a replacement for the Long Form of the decennial Census will result in more timely socioeconomic data, but many regions may wish to collect and maintain their own data sets. If a region or state currently has no equivalent to the Census datasets, establishing one would be a major undertaking; such data, however, are invaluable to public agency and private-sector analyses above and beyond trans- portation studies. High-Value Data Investment Opportunities Increased communication and interaction between trans- portation agencies and agencies responsible for socioeconomic data collection and forecasting would benefit the accuracy and level of detail of socioeconomic datasets. This may help to refine existing statewide or regional datasets using knowledge gained through transportation studies. Transportation agen- cies may get a more “hands-on” feel for conditions in a par- ticular area, and through the course of a planning study may examine numerous different socioeconomic datasets, which may be further supplemented by surveys. Surveys can be used to gather data on: • Local socioeconomic conditions; • Local travel patterns by socioeconomic group; and • Conditions or perceived conditions related to noise and congestion.Community perceptions can be helpful in weighting vari- ous types of benefits and costs to be consistent with the val- ues of those impacted. Before-and-after studies to evaluate whether predicted impacts actually took place after imple- menting a particular transportation improvement can help refine or modify existing data collection practices and analyt- ical methodologies. Similarly, it also is important to gather information from planning documents and local surveys on previous impact-producing projects that have been recently completed. Feeding these data back into state or regional socioeconomic datasets can improve accuracy for future studies. Environmental Justice analysis necessarily consists of a qualitative analysis component, but must be supported by high-quality socioeconomic and geographic data. Web-based GIS tools such as Florida’s Environmental Screening Tool (EST) offer an ideal venue for examining applicable quanti- tative data in a way that allows each stakeholder agency to look at the same data in the context of their particular exper- tise, and then craft a thoughtful response based on all avail- able information, quantitative or otherwise. The EST is a web-based GIS tool integrated to an extensive statewide GIS database of over 300 layers, allowing all stakeholder agencies to perform their analyses through a centralized location. It uses existing GIS web publishing technology to create a vir- tual project analysis environment accessible to the dozens of separate resource agencies that participate in Florida’s ETDM process. Appendix B References 1. See: http://www.epa.gov/safewater/contaminants/index.html. 2. http://nhd.usgs.gov/index.html. 3. http://www.epa.gov/owow/tmdl/2008_ir_memorandum.html. 4. http://iaspub.epa.gov/waters/national_rept.control. 5. http://www.epa.gov/waterscience/standards/wqslibrary/index.html. 6. Eco-logical: An Ecosystem Approach to Developing Infrastructure Projects. U.S. DOT, Research and Innovative Technology Admin- istration. Cambridge, Massachusetts. DOT-VNTSC-FHWA-06-01 7. http://www.oregonexplorer.info/ 8. http://www.fhwa.dot.gov/environment/wetland/scanrpt/intro.htm. 9. http://www.bts.gov/programs/statistical_policy_and_research/ source_and_accuracy_compendium/wetland_impact.html. 10. http://www.pca.state.mn.us/water/wetlands/cwamms.html. 11. http://www.ncdot.org/doh/preconstruct/pe/neu/Monitoring/. 12. http://www.fhwa.dot.gov/environment/airtoxic/020306guid mem.htm 13. http://www.epa.gov/ttn/atw/nata1999/index.html. 14. http://www.epa.gov/ttn/chief/net/). 15. Information on monitoring efforts can be found at http://www. epa.gov/ttn/amtic/ airtoxpg.html. Data from air toxics monitoring activities, as well as an increasing number of State and local air toxics monitoring networks, is available in EPA’s Air Quality System data- base: http://www.epa.gov/ttn/airs/airsaqs/. 16. Health Effects Institute. Mobile-Source Air Toxics: A Critical Review of the Literature on Exposure and Health Effects. Special Report 16, 2007. http://pubs.healtheffects.org/view.php?id=282.

11317. Section 4(f ) of the Department of Transportation Act prohibits FHWA and other federal transportation agencies from using land from a historic site of national, state, or local significance unless there is no feasible and prudent alternative to use of the land, and actions are taken to reduce all possible harm to the site. The Section 4(f ) evaluation is a requirement in the NEPA documentation. 18. For more information: http://www.nps.gov/history/nr/research/ nris.htm.19. For more information: http://etdmpub.fla-etat.org/est/. 20. For more information: http://www.fhwa.dot.gov/environment/ noise/faq_nois.htm. 21. For more information: http://safety.fhwa.dot.gov/safetealu/shsp guidance.htm. 22. For more information: http://www.csu.edu.au/research/crsr/PDF- files/Stolp.pdf. 23. For more information: http://www.fhwa.dot.gov/environment/ ejustice/effect/crosstabs.html.