Assessing and Comparing Environmental Performance of Major Transit Investments (2012)

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H-1 Appendix H – List of Candidate Environmental Performance Metrics The metrics presented below represent the original list assembled and considered by the project team in Phase 1 of this research. This list was originally presented to the project panel as part of a technical memorandum, and later included as part of the Phase 1 Interim Report. From this list were selected the metrics evaluated in more detail in Phase 2.

H-2 Table H.1 Candidate Environmental Performance Metrics Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Category Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 1 Energy Use and GHG Emissions 2 Benefits or Impacts 3 Net change in energy con- sumption (BTUs) Fuel use, energy content, energy input to manufacture [See below by “source”] • Proxy indicator of environmental and social impacts related to energy use; avoids issue of geographic discrimination based on electricity grid. • Not a direct measure of any envi- ronmental or social impacts; differ- ent fuels have different impacts. 4 Net change in GHG emissions Emission factors by vehicle and fuel type, emissions from manufacture [See below by “source”] • Most direct measure of climate change- related impact. • Not a direct measure of energy security impact (e.g., foreign oil). 5 Net change in petroleum use Petroleum fuel use [See below by “source”] • Most direct measure of energy security impact. • Not a direct measure of GHG emissions. 6 Sources 7 Direct operating – transit and private vehicles • VMT by vehicle type (roadway, transit) • Fuel consumption and/or emission rates (miles/gallon, BTU/ gallon, gallon/mile) for all vehicles with changing service levels • Speeds by vehicle type • Energy content or GHG emission factors (BTU/ gallon, GHG/gallon) • VMT and speeds: travel demand model, transit operating plans • Fuel consumption or emission rates: MOVES, EMFAC, manufacturers’ data • Energy or GHG factors: U.S. DOE • Most significant emissions impact/benefit. • Change in regional emissions very small compared to total emissions, and may not be reliably estimated by travel demand model. 8 Transit and private vehicles – full fuel cycle (upstream and downstream) Fuel-cycle emission rates • U.S. DOE – GREET Model • U.S. EPA – eGRID (electricity) • Essential if alternative fuel transit vehicles or electric propulsion are to be evaluated. • Added information probably not worth the additional effort if only fossil-fuel vehicles are evaluated. 9 Transit construction – activity, embodied in materials • Materials inputs • Construction activity • Energy or GHG factors for these • Research on construc- tion and embodied emissions (Chester, NCHRP 25-25/58, NJDOT) • Impacts shown to be nontrivial. • Highway project evaluations cur- rently do not include this factor.

H-3 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 10 Transit infrastructure – oper- ations and maintenance • Energy and materials inputs • Energy or GHG factors for these • Research on life-cycle emissions (Chester) • Impacts shown to be nontrivial. • Highway project evaluations cur- rently do not include this factor. 11 Transit vehicles – manufac- ture, disposal • Energy or GHG factors • Research on life-cycle emissions (Chester) • Impacts shown to be nontrivial. • Would require analysis of avoided auto ownership and associated savings for fair comparison. 12 Avoided infrastructure (highway) • Amount of highway infrastructure need avoided through transit construction • Materials inputs • Construction activity • Energy or GHG factors for these • Research on construc- tion and embodied emissions (Chester, NCHRP 25-25/58, NJDOT) • Inclusion may be one way of “leveling playing field” if highway project evalua- tion does not include similar metrics. • Difficult to attribute a particular amount of “avoided” highways to transit construction. • Inconsistent with NEPA and New Start practice of comparing project build with no-build. 13 Ways of Expressing or Normalizing 14 Total [See above] • Direct measure of gross impact/benefit. • Not normalized by scale of project. 15 Per passenger-mile: all modes +Total passenger miles in study area with and with- out project Regional travel demand model • Measure of transportation system efficiency. • Size of impact will depend upon study area – larger area will dilute impact. 16 Per passenger-mile: transit +Total transit passenger miles in study area with and without project Regional travel demand or transit ridership fore- casting model • More narrow measure of transit service efficiency; can help transit agencies focus on efficient service. • Size of impact will depend upon study area – larger area will dilute impact. • Does not account for emissions from private vehicles. 17 Per capita (service area) +Total population in ser- vice area Regional travel demand or transit ridership fore- casting model • Accounts for benefits of reductions in passenger-miles per capita. • Size of impact will depend upon study area – larger area will dilute impact. 18 Per unit cost of project +Annualized cost of project (capital + operating) Project financial analysis • Direct measure of cost-effectiveness; normalizes for project scale.

H-4 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 19 Proxy Measures 20 Change in VMT • Net change in regional VMT • Regional travel demand model • Measure of private vehicle use; proxy for other impacts, including air quality, infrastructure needs, community impacts. • Does not account for added energy use or GHG emissions from new transit service. 21 Consistency of project with regional or local energy or climate action plan • Is project included in plan as GHG reduction measure? • Plan document • Yes/no indicator of project’s value for energy/GHG reduction. • Plan development already may have analyzed benefits of project. • Does not indicate magnitude or cost-effectiveness of benefits. • Many areas will not have specific projects identified in a plan. 22 “Best in class” efficient/low- carbon transit vehicle purchasing GHG emissions per seat-mi • Manufacturer specifi- cations for or other test data for fuel/energy intensity, GHG factors by fuel type • Proxy for minimizing direct operating emissions. • Does not account for load factors and overall efficiency of transit ver- sus alternatives. 23 Best management practices for GHG reduction in construc- tion and transit agency operations • Efficiency standards for construction equipment and fleet vehicles • Guidelines for GHG reducing construction practices (e.g., idle reduction, use of recycled materials) • Contracting guidelines or documents • Agency policies, oper- ating procedures, etc. • Proxy for minimizing construction and maintenance emissions. • Does not assess magnitude of GHG reduction. • Would require development of guidelines for BMPs. 23a Land use multiplier (travel benefits associated with more compact land use) • Travel and land use patterns in region • Travel demand mod- eling, statistical evalu- ation, and GIS analysis to develop region- specific multiplier • Potentially simple method for accounting for additional GHG benefits of reduced travel due to more compact land use patterns, if multipliers for different regions can be developed. • Currently, a national “default” has been established but this multiplier can vary widely by region and is data-intensive to calculate locally.

H-5 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 24 Air Quality and Public Health 25 Air Quality Benefits or Impacts 26 Net change in criteria pollu- tant emissions and precur- sors – by source 27 Direct operating emissions – transit and private vehicles • Change in VMT by vehicle type (highway, transit) • Emission rates (g/mi) for all vehicles with changing service levels • Changes in vehicle speeds on highway network • VMT: Travel demand model (highway), transit operating plans • Fuel consumption or emis- sion rates: MOVES, manu- facturers’ data, AEO • Speeds: regional travel model, transit operating plans • Most significant emissions impact. • Change in regional emissions may be very small compared to total emissions, and may not be reliably estimated by travel demand model. • Same emission reduction may have different benefits depending upon existing air quality issues. 28 Construction activities • Activity levels and emission rates for con- struction vehicles Models developed by UC- Davis for Caltrans, Rutgers for NJDOT, NCHRP 25-25(58) • May be particular impacts of localized concern. • Lack of reliable, easy to use data and analysis methods. • Does not consider temporary changes in normal traffic emissions. 29 Other nonlocalized emissions, including upstream fuel, station and facility operations • Life-cycle emission factors • U.S. DOE – GREET Model • USEPA – eGRID (electricity) • More complete accounting of emissions/air quality impacts. • Impacts of a particular pollutant may vary widely depending upon where emissions take place. 30 Change in ambient air quality (concentration of pollutants) 31 Maximum concentrations of locally significant pollutants (CO, NO2, PM, toxics) • Emissions by location (vicinity of project) • Meteorological and topographical data • Background concentrations • Microscale emissions models (e.g., CAL3QHC) • Dispersion models (CALINE, AERMOD, CMAQ, etc.) • NATA (air toxics concen- trations and emissions by census tract) • Well-established evaluation methods. • New one-hour NO2 NAAQS rele- vant to health benefits and mobile sources. • Data-intensive to model, although may be possible to do more simply for toxics using NATA data.

H-6 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 32 Maximum concentrations of regionally significant pollu- tants (ozone, secondary PM, acid rain precursors) • Emissions by location (throughout region) • Meteorological data • Background concentrations • Mesoscale and regional air quality models • Extremely data and time-intensive to model. • Impacts of a single transit project are not likely to create measurable differences on a regional scale. 33 Exposure measures 34 Change in population expo- sure index for criteria pollu- tants and air toxics • Changes in emissions (mobile and stationary source) by TAZ/ subarea • Population by TAZ/ subarea • Background concentra- tions (optional) • Regional travel demand model • Locations of electricity generation plants and emission rates per KWh • NATA (background concentrations) • Easiest health-related indicator to calculate. • May be better indicator of benefit of local pollutant exposure across projects of dif- fering extent and demographic scope. • May not be directly related to health outcomes. • Changes in emissions from electric- ity generation may not be readily obtainable. • Assumes resident population is proxy for exposure. 35 Change in population exposed to unhealthful air quality • Change in air quality by TAZ/subarea – fre- quency of NAAQS expected exceedances of standards • Population in areas with air quality changes • Ambient air quality concentration models (per above), combined with population data • Acknowledges importance of NAAQS as “threshold” level related to health effects. • Difficult to calculate. • Transit project likely to have only incremental impact. 36 Health impacts 37 Health benefit index • Changes in emissions by TAZ/subarea • Population by TAZ/ subarea • “Potency” of each pollutant • Regional travel demand model • USEPA, literature (potency) • Feasible to calculate from available data. • Rough proxy for exposure and health impact.

H-7 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 38 Incidence of pollution-related mortality and morbidity (e.g., asthma, lung cancer) • Background emissions and changes in emis- sions over time by TAZ/subarea • Population by TAZ/ subarea • Dose-response functions for each pollutant • Regional travel demand model • USEPA – NATA (back- ground concentrations) • USEPA, literature (dose-response) • USEPA BENMAP methods • Measure most directly related to ultimate health outcomes. • Focus on criteria and toxic air pollutants most relevant to mobile sources. • Difficult to calculate at present (though models are emerging). 39 Proxy Air Quality Measures 40 NAAQS nonattainment status EPA listings of nonattain- ment status EPA “Green Book” • Readily available indicator of areas with air quality problems. • Does not indicate transit project’s “benefits,” either in terms of attainment of standards, or expo- sure of population to unhealthful pollutants. • Differences between areas just above and below NAAQS overem- phasized; degree of nonattainment only indicated for ozone. • Designation may be out of date. 41 Air Quality Index • Daily air quality readings • Calculated by EPA for six pollutants in major MSAs; see AirData web site • Preferable to nonattainment status as a readily-available indicator of severity of air quality problem across areas. • Does not indicate transit project’s “benefits” in terms of contributing towards air quality improvement. 42 Conformity of LRTP or TIP containing transit project with AQ objectives • Conformity analysis of LRTP or TIP containing transit project • Regional travel demand model and emission factors • Identifies whether project is part of trans- portation plan that meets AQ objectives. • Transit project just one part of overall plan performance; does not indicate incremental benefit or impact of project. • All plans/TIPs ultimately need to be conforming to receive Federal funding. 43 Change in VMT • Net change in regional VMT • Regional travel demand model • Measure of private vehicle use; proxy for other impacts, including GHG, infra- structure needs, community impacts, physical activity benefits. • Does not account for added emis- sions from new transit service.

H-8 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 45 Best management practices for emissions reduction in construction and transit agency operations • Emissions standards for construction equipment and fleet vehicles • Guidelines for emission reducing construction practices (e.g., idle reduction, dust control) • Contracting guidelines or documents • Agency policies, oper- ating procedures, etc. • Proxy for minimizing construction and maintenance emissions. • Does not assess magnitude of emissions reduction. • Would require development of guidelines for BMPs. 105 Physical Activity (Proxy Measures) Direct Impacts 105a Forecast number of daily nonmotorized access trips • Transit ridership fore- cast, including access mode choice • Travel demand fore- casting model • Most closely related metric to actual physical activity generated by project than can reasonably be forecasted using available data. • Access mode choice models may have limited accuracy. • Does not account for additional physical activity by station area residents not directly using transit. Proxy Measures 106 Percent population within half-mile walk of transit stop • Location of transit sta- tions, population by block group/tract/TAZ • Street networks identi- fying walkable routes • GIS overlay or network analysis • Basic measure of access to transit. • Does not indicate utility of avail- able transit. • Analysis of street/walking route network requires more work than simple spatial overlay, but spatial overlay may not indicate walk accessibility. 107 Station area or corridor walk- ability and bikeability metrics (connectivity, sidewalk avail- ability, miles of bike lanes/ capita, LOS, etc.) • Local land use and transportation plans and policies • Qualitative assessment • Not a direct outcome of transit investment, but rather of any related land use and infrastructure changes.

H-9 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 46 Ecology, Habitat, and Water Quality 47 Sources 48 I. Direct: Construction activities (short-term) • See below under specific “Benefits or Impacts” (Water Quality) 49 II. Direct: Facility and Operations • See below under specific “Benefits or Impacts” (all impacts) 50 III. Indirect – Induced growth/land use changes 51 Benefits or Impacts 52 Water Quality 53 Hydromodification – change in sediment and nutrient load, temperature, water velocity, erosion, barriers • Physical/hydrological characterization of receiving water bodies and associated riparian areas • Coefficients for estimated pollutant load due to anticipated hydromodification 54 Direct • Project footprint • Project plans • Direct wetland impacts generally considered in NEPA evaluation. • Requires detailed data and modeling. • May be small compared to indirect impacts. 55 Indirect • Location and characteristics of development • Land use forecasting model • Site design requirements • May be significant compared to direct impacts. • Impossible to forecast accurately. 56 Change in riparian or floodplain areas • Area, quality, and func- tioning of riparian areas • Locations of floodplains

H-10 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 57 Direct • Project footprint • Project plans • Direct impacts generally considered in NEPA evaluation. • May be small compared to indirect impacts. 58 Indirect • Location of development • Land use forecasting model • May be significant compared to direct impacts. • Impossible to forecast accurately. 59 Water quality standards compliance • Identification of receiving waters • 303(d) list of impaired waters • TMDLs for receiving waters • Coefficients for pre- dicted pollutant loading 60 Direct • Project footprint • Project plans • Direct impacts generally considered in NEPA evaluation. • May be small compared to indirect impacts. 61 Indirect • Location and characte- ristics of development • Land use forecasting model • Site design requirements • May be significant compared to direct impacts. • Impossible to forecast accurately. 62 Wetlands 63 Net change in acreage of (high-quality) wetlands • Locations of wetlands (by quality/ significance) • GIS wetlands database • GIS habitat database from Regional Ecologi- cal Framework or State Wildlife Action Plan 64 Direct • Project footprint • Project plans • Direct wetland impacts generally con- sidered in NEPA evaluation. • May be small compared to indirect impacts. 65 Indirect • Location of development • Land use forecasting model • May be significant compared to direct impacts. • Difficult or impossible to forecast accurately.

H-11 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 66 Habitat/Ecosystems 67 Change in acres of frag- mented or threatened critical habitat • Actual or expected locations of critical habitat • GIS habitat database from Regional Ecologi- cal Framework or State Wildlife Action Plan 68 Direct • Project footprint • Project plans • Direct ecological impacts generally consi- dered in NEPA evaluation. • May be small compared to indirect impacts. 69 Indirect • Location of development • Land use forecasting model • May be significant compared to direct impacts. • Impossible to forecast accurately. 70 Change in acres of native and invasive plants • Vegetation maps • GIS habitat database 71 Direct • Project footprint • Landscape plans • Project plans • May be small compared to indirect impacts. 72 Indirect • Location of development • Landscaping characteristics • Land use forecasting model or indicator of likely impact • Landscaping requirements • May be significant compared to direct impacts. • Impossible to forecast accurately. 73 Land with Resource Value 74 Acres of (prime) farmland, forest land, open space 75 Direct • Project footprint • Land use cover by type • Project plans • Land cover database • Direct impacts generally considered in NEPA evaluation. • May be small compared to indirect impacts. 76 Indirect • Location of development • Land use forecasting model or indicator of likely impact • May be significant compared to direct impacts. • Difficult or impossible to forecast accurately.

H-12 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 77 Proxy Measures 78 Water Quality 79 Impervious surface area 80 Direct • Project footprint • Project plans • May be small compared to indirect impacts. 81 Indirect • Location and characte- ristics of development • Forecasts of land use by type/density • Coefficients for percent impervious surface area by type of development • Any requirements related to impervious surface in development • May be significant compared to direct impacts. • Widely used indicator of water impacts. • Does not require knowing precise loca- tion of induced development. • Difficult to forecast land use impacts associated with project, even in general sense. 82 Impingement upon water quality protection areas • Locations of ground- water and sourcewater protection areas, water bodies training into impaired waters • Local and regional watershed protection plans 83 Direct • Project footprint • Project plans • May be small compared to indirect impacts. 84 Indirect • Location of development • Land use forecasts • May be significant compared to direct impacts. • Impossible to forecast accurately. 85 Wetlands, Habitat/ Ecosystems, and Other Land with High Resource Value 86 Direct: 87 Acres of land used for trans- portation purposes • Project footprint • GIS analysis of project plans • Easy to calculate direct impact measure. • No indication of environmental value of land.

H-13 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 88 Indirect: 89 Acres of land developed in corridor due to project • Development by future analysis year, with and without project • Land use forecasting model, or qualitative assessment • Indirect land use impacts likely to be much more significant than direct impacts. • Very difficult to forecast. • Not clear how to define baseline: simple with versus without tran- sit comparison? Transit systems versus highway systems? 90 Ratio of already-developed land in corridor to undevel- oped land (greenfields) • Location of project • Local land use plans • Local or regional land use plan data in GIS format • Scaled/normalized indicator of potential indirect impacts without requiring land use forecast or detailed environ- mental data. • Does not indicate likelihood that land in project influence area will actually be developed because of project, or environmental impacts of such development. 93 Potentially impacted acreage of wetlands, critical habitat, and/or other land with high resource value • Locations of wetlands, critical habitat, or other land with high resource value (protected ver- sus unprotected) • Influence areas where develop- ment is likely to occur • Wetlands or habitat data- base or assessment (see above) • Existing designated conser- vation areas • Influence indicator based on proximity to project or accessibility change • Indicator of indirect impacts that avoids need for precise forecast of land development. • Measure of potential rather than actual impact. 94 Potentially impacted acreage, weighted by ecosystem ser- vice value • Same as previous, with addition of ecosystem service values for different land use types • Ecosystem service value methods being developed for SHRP2 Project C06B • Improves on previous indicator by assigning ecological signi- ficance to potential impacts. • Requires data on ecosystem ser- vice values. 95 Adequacy of state or regional habitat protection plans and consistency of project with plans • Existence of regional habitat protection/conservation plans • Quality of plans and implemen- tation authority in terms of ability to protect critical habitat • Qualitative evaluation of plans and implementation capacity • Can indicate potential for avoiding/mitigating habitat impacts without forecasting land use changes. • Not an actual measure of impact. • Many areas will not have regional conservation plans, although all states have wildlife action plans with varying degrees of focus and quality. • Subjective assessment. 96 Qualitative assessment of expected impacts on sensitive land use • Location of project • Proximity to developable lands • Market and policy factors influencing development in impact area • Local land use plans • Expert knowledge, Delphi process • Easier to apply than quantita- tive forecast; can incorporate expert judgment. • May be available from environ- mental documentation. • Subjective; difficult to reliably know potential impacts or trans- late into quantitative impact metric.

H-14 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 97 Community and Quality of Life 98 Benefits or Impacts 99 Environmental and Social Quality 100 Noise – Percent residents exposed to greater than xx DB noise from transportation sources • Location of transporta- tion facilities, traffic volumes • Noise emitted from tran- sit vehicles and facilities • Detailed information on population by area (block) • Traffic forecasts • Transit project operating data • Census population data • Could indicate whether net noise benefit or impact from transit facili- ties, considering reduced VMT. • Labor/data-intensive to conduct analysis. 101 Community cohesion/ disruption • Location and geometric characteristics of trans- portation facilities • Traffic volumes • Neighborhood connections/linkages • Transportation network data • Traffic forecasts • Qualitative assessment considering community input 102 Aesthetics/visual quality • Location and appearance of transportation facilities • Indirect impacts – land use changes in com- munity resulting from project • Community preferences • Qualitative assessment of visual impact • Indirect – land use forecasts/assessment • Visual preference surveys • Difficult to forecast/reliably predict indirect impacts of project. 103 Resident perceptions of com- munity quality • Resident ratings of vari- ous community attributes • Community surveys • Self-identified measures of livability/ quality of life. • Difficult to forecast/reliably predict impacts of project. 104 Historical, cultural, and archeological resources • Location and value of key resources • State and local historical preservation offices • Archeological resource databases • Evaluation required in NEPA and Section 106 process.

H-15 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 108 Transportation Choices 109 Transit LOS index • Existing and proposed levels of transit service (frequencies, service coverage) by area • Transit capacity and quality of service manual (CUTR) • More sophisticated transit availability measure. • Still does not indicate how accessi- ble destinations are via transit. 110 Accessibility index by non- auto modes (to jobs, services) • Travel demand model data – population, employment by type, travel times by mode • Travel demand model analysis • Basic measures for auto, transit easy to develop from travel demand model as applied to ridership forecasting. • More work needed to evaluate accessibility to specific services, or match between resident skills and jobs. 111 Percent population within half-mile walk of transit stop (See above for Physical Activity) 112 Walkability and bikeability metrics (See above for Physical Activity) 113 Housing Affordability 114 Number of affordable units within half-mile walk of transit • Location of transit stations • Location of affordable housing units (existing, planned) • Local housing data • Indicates population most likely to bene- fit from transit. • Housing prices and affordability can change over time; no fore- casting methods available. • May be more important to look at housing plans/policies than existing characteristics. 114a Affordable housing policies • Local and state land use policies and programs related to affordable housing provision • Qualitative assessment • May be more feasible than quantitative assessment. • Subjective; difficult to account for variations in contexts and needs across projects.

H-16 Table H.1 Candidate Environmental Performance Metrics (continued) Category Data Needs and Sources Use of Measure as a Transit Performance Metric: Row # Subcategory or Measure Data Requirements (for Forecasting) Data Sources and Analysis Methods Advantages Disadvantages 115 Safety and Security 116 Transportation-related acci- dents or fatalities per capita (auto, ped, bike, transit) • VMT and/or PMT by mode • Accident rates by mode • VMT/PMT from travel demand forecasting model • Analysis of local/ regional crash data • Forecasts of nonmotorized travel and future crash rates may not be reliable. • Cannot forecast any project-specific impact aside from that related to VMT/PMT by mode. 117 Crime rates • Transit investment could potentially influence crime rates in combination with development and demographic changes in community. • Numerous factors influence crime rates aside from transportation investments; cannot be forecast. 118 Support for Existing Communities 119 Percent of station area or corridor land that already is developed • Existing land use data • GIS analysis • Basic measure of serving existing communities. • Does not indicate developed land that is not “community” – e.g., industrial, or underutilized – or not compatible with transit (e.g., low- density single-family). 120 Percent of station area or corridor land that already is developed in “transit- supportive” patterns • Existing land use data • GIS analysis, based on qualitative and quan- titative metrics (den- sity, mix, walkability, use types) • Adds information on extent to which transit is reinforcing compatible com- munities (versus serving noncompatible communities). 121 Total population living in station areas or corridor • Population data • GIS analysis • Considers population benefiting in existing communities – not just land area of communities served. • May not indicate distribution/ location of population or “com- munities” in relation to transit stations.