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					 Approaches and Limitations in
Assessing Public Health Impacts
 of Transportation Infrastructure
            Chad Bailey
           US EPA OTAQ
          January 24, 2008
             UC Davis
              Overview
• Relevant policy context
• Health and transportation
• General approaches taken
• Review of common analysis methods used
  in analysis of transportation projects
• Proposals for improvement
             Policy Context
• National Environmental Policy Act
  – Requires documentation and consideration of
    impacts of major Federal activities, including
    infrastructure decisions
  – Wave of EIS documents addressing near-
    road issues in context of toxics
• NAAQS Attainment Demonstration
  – Areas with localized hotspots
  – Benefits and costs of local controls
Demand for        Where health fits…
  time
                                               Public Health
                             Air pollution
    Demand for                                                               Obesity
      goods                                                Personal
                             Gas                            activity
                                             SOV
                             tax
                                                                                  Transit

                                                                Land Use
    Rail, ships,             Highways
                                               Petroleum
     planes                                                                      Water
                                                                                 quality

                                   Trucks
                                                                 Biofuels
                                                                                   Puller
             IM, rail, air
                                               Invasive                            Vehicle
              terminals
                                                species        Demand for          Infrastructure

                                                               real estate         Impact
              Traditional NEPA Focus
Demand for
  time
                                               Public Health
                             Air pollution
    Demand for                                                               Obesity
      goods                                                Personal
                             Gas                            activity
                                             SOV
                             tax
                                                                                  Transit

                                                                Land Use
    Rail, ships,             Highways
                                               Petroleum
     planes                                                                      Water
                                                                                 quality

                                   Trucks
                                                                 Biofuels
                                                                                   Puller
             IM, rail, air
                                               Invasive                            Vehicle
              terminals
                                                species        Demand for          Infrastructure

                                                               real estate         Impact
    Spectrum of Approaches
   (What I‟ve heard out there)

Qualitative
discussion    Emissions
              (Regional/
               Corridor)   Emissions
                           (Link-level)
                                          Dispersion


                                                       Quantitative risk
                                                       characterization
      Spectrum of Approaches
     (What I‟ve heard out there)

  Qualitative
  discussion    Emissions
                (Regional/
                 Corridor)    Emissions
                              (Link-level)
                                             Dispersion


                                                          Quantitative risk
Description of health concerns,                           characterization
emission sources, population
impacts, weight of evidence, and
uncertainties
    Spectrum of Approaches
   (What I‟ve heard out there)

Qualitative
discussion    Emissions
              (Regional/
               Corridor)    Emissions
                            (Link-level)
                                           Dispersion


                                                        Quantitative risk
    Emissions inventory for                             characterization
    large areas without local
    detail.
    Spectrum of Approaches
   (What I‟ve heard out there)

Qualitative
discussion    Emissions
              (Regional/
               Corridor)   Emissions
                           (Link-level)
                                          Dispersion


                                                       Quantitative risk
                                                       characterization

              Quantifies and presents emissions
              on each road link affected by a
              project
    Spectrum of Approaches
   (What I‟ve heard out there)

Qualitative
discussion    Emissions
              (Regional/
               Corridor)   Emissions
                           (Link-level)
                                          Dispersion


                                                       Quantitative risk
                                                       characterization


                                Estimates ambient
                                concentration of relevant
                                species and compares with
                                some threshold of concern
                                (e.g. NAAQS)
    Spectrum of Approaches
   (What I‟ve heard out there)

Qualitative
discussion    Emissions
              (Regional/
               Corridor)   Emissions
                           (Link-level)
                                          Dispersion


                                                       Quantitative risk
                                                       characterization



                                          Predicts cancer and non-cancer
                                          risks under EPA toxics framework
                                          (URE/RfC)
          Qualitative Approaches
• Done well                            • Done poorly
   – Objectively describes                 – “Cherry picks” information
     relevant issues                         to support desired outcome
   – Makes statements in                   – Assertions made without
     keeping with current                    regard to professional
     professional norms within               practices and best
     relevant fields                         practices
   – Addresses areas where                 – Uses laundry list of
     quantifiable impacts are not            uncertainties to cast doubt
     possible                                on health concerns
   – Describes consequences                – Treats quantifiable
     of being unable to quantify             information as the only
     impacts                                 useful material

P.S. As currently implemented, no discernable impact on decision making!
                        Example
• “The tools to predict how MSATs disperse are also
  limited. The EPA's current regulatory models, CALINE3
  and CAL3QHC, were developed and validated more
  than a decade ago for the purpose of predicting episodic
  concentrations of carbon monoxide (CO) to determine
  compliance with the NAAQS. The CALINE4 model used
  in California is an improvement on the CALINE3-based
  EPA models, but like them was built primarily for CO
  analysis, has not been specifically validated for use with
  other materials such as MSATs.”
   – CalTrans District 7 I-5 Improvement FEIS
       Emissions-only Analyses
• Done well                            • Done poorly
   – Characterizes trends in              – Selects only “hotbutton”
     emissions from all relevant            pollutants
     processes (tailpipe, evap, road      – Limits analysis to very small
     dust, tire/brake wear)                 number of factors without
   – Reveals influence of                   regard to influence on results
     technology, traffic flow and         – Limits trends analyses to
     composition, land use choices          “official” land use future
   – Presents scenarios reflecting        – Aggregates emissions inputs
     different assumptions and              and reporting to larger spatial
     inputs (e.g. speed model)              domains without information
   – Identifies alternatives that           on proximity to sensitive
     bring emissions closer to              receptors
     populations                          – Dismisses local emissions as
   – Presents local-regional                a trivial % of regional inventory
     tradeoffs (e.g. IM freight)
     Example:
Atlanta‟s “Northwest
      Corridor”
  Toxics Paradigm Approaches
• Done well                   • Done Poorly
  – Quantifies locations of     – Suggests excessive
    highest population            precision
    exposure                       • Lung cancer
  – Provides objective          – Reduces all
    metrics for comparison        information to “a
    between scenarios             number”
  – Allows transparent          – Downplays
    discussion of                 unquantifiable risks
    acceptable risk             – Non-cancer outcomes
                                  treated under
                                  threshold paradigm
Example: Diesel PM at Truck Stops
Best AERMOD Run with Background Excluded


                                 12              10
                                       16

   2                                                  8
                        10
                 8
   4
   6

                                                 22
                 10   12
                         14                 24
                        16
                      18 20 22
          14




                        Hartley et al., 2006
   The typical tools of the trade…
• Emission factors
  – MOBILE6.2 or CT-EMFAC
• Dispersion model
  – CALINE3/4, CAL3QHC, or AERMOD
• Simplified exposure assumptions
  – Residential outdoor receptors, no indoor sources
  – Some “sensitive” receptors (e.g. schools)
  – Time-activity models rarely used for projects
• Dose-response estimates or NAAQS
  – Cancer IUR and non-cancer RfC/RfD from IRIS or
    OEHHA
  – CO, PM10, PM2.5, NO2 NAAQS
    Missing in Most EIS Analyses
•    An integrative approach
    1. Objective characterization of qualitative information
       (e.g. hazard ID)
    2. Identification of influential assumptions and
       variables (e.g. “upstream” drivers)
    3. Use of ranges of impact for uncertain quantitative
       information
    4. Verification of coherence with best practices in AQ,
       risk assessment, and public health decision-making
    5. Discussion of literature of mitigation
Missing (1): Objective characterization
       of qualitative information
• FHWA (2006): “Some recent studies have reported that
  proximity to roadways is related to adverse health
  outcomes -- particularly respiratory problems. Much of
  this research is not specific to MSATs, instead surveying
  the full spectrum of both criteria and other pollutants.
  The FHWA cannot evaluate the validity of these studies,
  but more importantly, they do not provide information
  that would be useful to alleviate the uncertainties listed
  above and enable us to perform a more comprehensive
  evaluation of the health impacts specific to this project.”

• American Academy of Pediatrics (2004): “Siting of
  school and child care facilities should include
  consideration of proximity to roads with heavy traffic and
  other sources of air pollution. New schools should be
  located to avoid „hot spots‟ of localized pollution.”
     Recent Literature Reviews
• Exposure:
   – Zhou and Levy (2007) BMC Public Health: “our findings emphasize that
     policymakers should be able to develop reasonable estimates of the
     „zone of influence‟ of mobile sources, provided that they can clarify the
     pollutant of concern, the general site characteristics, and the underlying
     definition of spatial extent that they wish to utilize”
• Health
   – Salam et al. (2008) Curr Opin Pulm Med:
       • “There is consistent evidence that living near traffic sources is associated
         with asthma occurrence and exacerbations.”
   – Samet (2007) Inhal Tox:
       • “To date, the findings indicate associations of traffic indicators with increased
         risk for multiple adverse health effects including asthma and allergic
         diseases, cardiac effects, respiratory symptoms, reduced lung function
         growth, adverse reproductive outcomes, premature mortality, and lung
         cancer.”
   – Adar et al. (2007) Inhal Tox:
       • “In summary, we found consistent evidence from a variety of study designs
         that links traffic-related pollution with adverse cardiovascular health
         outcomes.”
                 Observation
• Transportation agencies use
  – decision criteria more tolerant of Type II (false
    negative) than Type I (false positive) errors in regards
    to public health
  – use information quality criteria more stringent than
    journal editors and reviewers
• Many agencies and parties
  – Focus on “high profile” pollutants, such as diesel PM
    and air toxics
  – Implicitly tie health to technology, which may/not be
    accurate assumption…
Defining Environmental Progress




       2003 EPA Emission Trends Report
Evidence that reducing tailpipe PM
             helps…




Li et al, 2003
                     …but not 100%
• Lwebuga-Mukasa et al. (2004)
   – 10 year retrospective study of
     residents along Peace Brdige
     border crossing corridor in
     Buffalo, NY area
   – Highest astma prevalance and
     health care utilization rates in
     ZIP codes closest to bridge
     complex
   – From 1991-1996, overall
     national asthma
     hospitalization declined, while
     it increased by a statistically
     significant amount during the
     same period in the study area
   – Authors attribute to NAFTA
 Missing (2): “Upstream” influences
      on air quality projections
• Gaps in regional travel models (ref: TRB Report 288)
   – Very poor ability to predict goods movement or travel time
     reliability
   – Large traffic analysis zones limit analysis of non-motorized travel
   – Generally fixed land use scenarios
       • “Forecast by negotiation” in around 1/3 of MPOs
       • Assume that local zoning/land use plans are static
   – Limitations prevent “out of box” thinking about solutions:
       •   Behavioral strategies
       •   Congestion pricing
       •   Intermodal vs. highway freight trade-offs
       •   Farmer‟s markets vs. international food trade
       •   Urban bike rental fleets
       •   Private transit markets, etc.
Addressing Regional Travel Model
 Limitations at the Project Level
• Make influential assumptions known
  – Projections based on static inputs are only
    one scenario of the future
• Explicitly outline which decisions affect
  projections (in and out of project manager
  control)
  – Local land use authority aims?
  – Multimodal availability?
 An Example of Land Use-Highway
           Interaction
• Wasatch Front
  Regional Council
  model
   – Baseline land use
     assumptions compared
     with UrbanSim land
     use simulator
• Studied effect of land
  use changes on
  congestion estimates
• Large differences
  found in areas of high
  low-density growth


                            Waddell et al. (2003)
Missing (3): Expressing Uncertain
      Information as Ranges
• Not every quantity can be characterized
  with precision, but that doesn‟t imply
  irrelevance
• Important to objectively describe ranges of
  data, particularly when diverse sets of
  inputs are possible (controversy)
    Addressing Uncertain Health
            Information
• Ballpark magnitudes of health effects
  – “What if” these effects are real?
  – “What if” attributable to toxics, PM, or road dust?
  – How do alternatives vary in their potential impacts?
• Approaches addressing uncertainty
  – Decision tree (branches assigned probability that
    health result is true, based on expert judgment)?
  – Insurance simulation (what would zero-profit life and
    health insurers charge for standard coverage based
    on strength and likelihood of causal association)?
  – Advanced simulation (e.g. prospective life table)
Example Decision Tree to Show Ranges
(Way too simple, also should apply to mitigation, costs)
                                    For two project alternatives. Given:
                                    •50,000 person study area
                                    •3% more people “exposed” by living within 100 m
                                    of freeway or 50 m of major urban road for build
                     Hoek           vs. no build
             p
                                    •Relative risk of exposure = 1.41 (Hoek), 1.18
 Mortality       q                  (Finkelstein), 0 (Reject studies as false)
                      Finkelstein
  Effect
                                    Excess Mortality =
             1-p-q
                                    Annual Mortality Rate * Excess Risk from
                     False          Exposure * Total Population * Fraction of
                                    Population Exposed
                                    •(816/100K)(1.41-1)(50,000)(3/100) = 5.02
                                    •(816/100K)(1.18-1)(50,000)(3/100)=2.20
                                    •(816/100K)(1-1)(50,000)(3/100)= 0
                                    E(Excess Mortality) = p + 0.44q +0(1-p-q)
                                    Assume p = 0.25, q = 0.25, E = 1.8
   Missing (4): Coherence with
      Professional Practice
• Agencies and advocates often use methods that
  favor their desired outcomes
   – “Summary of Existing Credible Scientific Evidence
     Relevant to Evaluating the Impacts of MSATs”
     (FHWA Interim Guidance on Air Toxics)
   – Sierra Club‟s 2004 Highway Health Hazards
• Rarely references totality of relevant literature
• Commonalities
   – Lack of public process or peer review
   – Continual “reinvention” of the wheel
                 Example
• “But, although transportation and air
  quality models are constantly being tested
  and improved, models to calculate the
  dispersion of PM2.5 and air toxics, and the
  resulting concentrations at any given point,
  have not been adopted for regulatory use.”
  – Michigan DOT, DEIS for Detroit Intermodal
    Freight Terminal
       Improving Data Quality
• Quality assurance project plans (QAPP)
  – Ensures relevant data and assumptions are made
    explicit
  – Ensures that standards for information acceptability
    are documented
  – Places all contributors to analytic outcomes on level
    playing field (substantive, procedural)
• Peer review
• All Federal (and some state) agencies are
  subject to information quality requirements
         Missing (5): Mitigation
• Generally limited to construction:
  – Low-sulfur diesel in diesel equipment
  – Idling restriction
  – Retrofit in some cases
• No discussion of novel mitigation options
  –   Windbreaks (e.g. barriers, vegetation)
  –   HVAC intake location
  –   Longer-wearing concrete
  –   Truck routes
  –   Weight and length limits
  –   The list goes on…
                Conclusions
• Commonly employed methods for analyzing
  impacts of transportation projects provide little
  public health information
• Limitations include lack of objective qualitative
  information, “upstream” analytical problems,
  error preference bias, and lack of adherence to
  contemporary standards of practice
• Numerous well-accepted methods exist for
  dealing with uncertain health information
• Data quality objectives can help!
Moving toward quality!

				
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