Dispersion Modeling for Mobile Source Applications

Transcription

1 Dispersion Modeling for Mobile Source Applications Chad Bailey EPA Office of Transportation and Air Quality Regional, State, and Local Air Modelers Workshop Philadelphia, PA May 14,

2 Overview Upcoming dispersion model applications Modeling guidance for highway and transit projects under transportation conformity National Environmental Policy Act Implications for the modeling community Issues to address in these applications 2

3 The Nutshell Regulatory and NEPA applications of dispersion models to roadways and other transportation projects are likely to increase over the next months EPA is producing guidance this year on modeling PM impacts of transportation projects The public (and NGOs) are increasingly requesting dispersion modeling of traffic-related air pollutants as part of NEPA Modeling issues that might be coming your way! 3

4 Near Road Air Quality St. Louis, MO 1997 Concentrations of primary pollutants are elevated in proximity of major roadways, etc. Zone of influence can reach meters downwind Upwind Downwind PM µg/m 3 Lamoree & Turner, 1999 Raleigh, NC, 2006 Some studies suggest over 1 km downwind during stable conditions Steepest gradient closest to road Ultrafine particle count (#/cm 3 ) Hagler et al.,

5 Multiple Pollutants NO 2 and air toxics BTEX Particle number 5

6 Where We Are: Growing Body of Health Research Studies With Keywords "Traffic, Pollution, Epidemiology" in PubMed Medical Database Number of Published Studies * * Projected based on studies published to date (dark shade). 6

7 Health Effects General agreement in public health literature Populations near roadways experience a wide range of adverse health outcomes Several recent survey articles Samet (2007): general public health Adar and Kaufmann (2007): cardiovascular Salam et al. (2008): asthma Brabeck and Forsberg (2009): allergies Remaining questions Relevant pollutants / sources Safe distance Effect of standards 7

8 Sufficient evidence to infer a likely causal relation Exacerbation of respiratory symptoms in asthmatic children Sufficient OR Suggestive but not sufficient New onset asthma incidence and asthma prevalence in children Suggestive but not sufficient All-cause mortality Cardiovascular mortality Cardiovascular morbidity Lung function Inadequate/insufficient evidence to infer the presence or absence of a likely causal relation for other endpoints 8

9 2007 American Housing Survey Description of Area within 300 Feet U.S. Census Bureau, National Data, December 2008 Year-round Occupied Characteristics Total housing units Seasonal Total Total Owner Renter Vacant New construction 4 years Manufactured/ mobile homes All Housing Unitss 128,203 4, , ,692 75,647 35,045 13,109 7,188 8,705 4-or-more-lane highway, railroad, or airport 20, ,751 17,864 9,361 8,503 1, ,220 % Near Mobile Sources 15.6% 6.0% 16.0% 16.1% 12.4% 24.3% 14.4% 10.6% 14.0% Suburbs 58,941 1,720 57,221 52,062 38,164 13,899 5, ,445 4-or-more-lane highway, railroad, or airport 9, ,068 8,305 4,660 3, % Near Mobile Sources 15.5% 5.2% 15.8% 16.0% 12.2% 26.2% 14.8% 5.5% 16.1% Central Cities or-more-lane highway, railroad, or airport % Near Mobile Sources 19.5% 13.5% 19.5% 19.7% 15.4% 24.6% 18.4% 20.0% 27.8% Outside MSAs 33,356 2,349 31,007 27,028 20,594 6,434 3,979 5,743 5,559 4-or-more-lane highway, railroad, or airport 3, ,742 3,346 2,106 1, % Near Mobile Sources 11.6% 5.6% 12.1% 12.4% 10.2% 19.3% 9.9% 9.5% 11.4% 9

10 Upcoming Model Applications Transportation conformity Modeling guidance for analysis of PM hot spot impacts from transportation projects National Environmental Policy Act Air toxics Criteria pollutants in areas meeting NAAQS 10

11 Transportation Conformity Guidance for Modeling Impacts of Transportation Projects 11

12 Transportation Conformity Section 176(c) of Clean Air Act Applies in nonattainment and maintenance areas for: Ozone Particulate matter: PM2.5 and PM10 Carbon monoxide (CO) Nitrogen dioxide (NO 2 ) Applies to: Long-term regional transportation plans Shorter-term transportation improvement programs Highway and transit projects funded or approved by Federal Highway Administration or Federal Transit Administration 12

13 Project-level Modeling Conformity requires that projects will not cause or contribute to a new violation of the NAAQS or worsen the frequency or severity of existing violations Historically, CO dispersion modeling for roadside receptors has been widespread Following 2006 rulemaking, PM modeling guidance for projects to be released to coincide with final release of EPA s new emission model, MOVES Scheduled for 12/

14 Issues to Address How to estimate emissions from a project MOVES (US) or EMFAC (California-specific) Developing local input data Focus on projects of air quality concern Use of dispersion models for projects Model recommendations Meteorological inputs Source characterization 14

15 National Environmental Policy Act 15

16 NEPA Requires that Federal agencies document and consider the environmental impacts of major projects Environmental Assessments Environmental Impact Statements Traditionally, has been a place where air issues are addressed for transportation projects generally 16

17 FHWA Interim Guidance on Air Toxics in NEPA FHWA issued interim guidance to division offices to its field in February 2006 Acknowledged that MSATs must be addressed 3-tiered approach based on size of project No analysis, qualitative analysis, or emissions-only for >140k-150k AADT Describes dispersion models as limited in applicability, performance, and utility for population exposure assessment FHWA suggests it may be revising interim guidance in coming months 17

18 NEPA EPA Regions have been commenting on air toxics and PM language in NEPA documents NEPA / Air Toxics workgroup meets bimonthly With increased attention to near-roadway exposure and health, public and NGOs expressing greater desire to understand impacts of transportation projects Highways Ports Airports Railroads EPA is working on recommendations for how to best model air toxics impacts 18

19 Implications for State, Local, and Regional Modelers Increased level of modeling activity related to transportation projects and roads in general Modelers may be asked to Review and comment on modeling protocols Provide information for analyses (e.g. background) In advance of increased activity, could be useful to Familiarize state air managers with near-road applications Establishing channels of communication in advance of increased activity may be useful EPA Regional mobile source staff State transportation and transit agencies Metropolitan planning organizations 19

20 Modeling Issues for Transportation Projects 20

21 Key Issues Traffic characterization Emission characterization Air quality model choice Meteorological data Land use / surface characteristics Variables most influential on modeled concentrations 21

22 Traffic Characterization Often, traffic data lack hourly detail Usually includes peak hour traffic flow and annual average daily traffic (AADT) Often includes 4 periods: AM peak/mid-day/pm peak/night Hourly emissions may require additional assumptions Focus generally on total traffic, not heavy-duty trucks Could be important for diesel-related pollutants Projected future travel demand can depend on land use changes in response to project May be outside the scope (and authority) of project sponsor Typically this is a metropolitan planning organization function, but affected by many factors 22

23 Emission Characterization Current emission factor model is MOBILE6.2 Pollutants: HC, CO, NOx, PM, Toxics, CO2 Emission factors (g/mi) depend on: Vehicle type (e.g., light-duty gas vehicle, heavy-duty diesel truck) Vehicle model year distribution Average speed of traffic / Roadway class Fuel type and characteristics Meteorology (i.e., temperature, humidity) Local emission inspection & maintenance programs EPA released a draft version of its new emission model, MOVES in April 2009, with final release planned by end of 2009 PM emissions higher Much greater flexibility in inputs, including driving patterns High degree of flexibility will call for greater attention to data quality 23

24 Air Quality Models for Transportation Projects 24

25 Air Quality Models Current guideline models Appendix W lists CALINE-3 as the preferred model for roadways CAL3QHC is specified for modeling CO from intersections Accept 1 hour of meteorological input Recent policy and health considerations require consideration of longer-term averages For instance, annual average exposure for air toxics or relevant design values for PM 2.5 or PM 10 NAAQS CAL3QHCR accepts one year s surface meteorology, and has been used in research publications, but employs model code from ISCST2 AERMOD can be used to model line sources, but treatment of traffic-induced turbulence is presently an off-model exercise 25

26 Common Model Applications for Mobile Sources CAL3QHC/R, CALINE3/4 Roadway and intersections AERMOD (or ISCST3 before it) Intermodal freight terminals Bus garages Rail terminals and rail lines Complex source mixtures Terminals, ports, and roadways together Large highway corridors Urban scale modeling 26

27 Meteorological Data Issues Representativeness of surface stations Large transportation projects can induce changes to land use and population maps Changes in surface characteristics? Changes in urban heat island? 27

28 AERMOD Sensitivity to Surface Characteristics Recent study by Brode et al. (2008) suggests that for non-buoyant, short stacks, AERMOD predictions at nearby receptors are sensitive to surface characteristics In particular, roughness length Lower sensitivity to Bowen Ratio and albedo 28

29 Road Network Influences on Surface Characteristics Satellite-based land cover information may not detect road network impacts on land RDU example, where road maps superimposed on NLCD 8.7% less forest area 11.4% more forest edge 42.3% more forest patches 35.9% reduction in average forest patch area How important is this? Riiters et al. (2004) 29

30 Transportation Project Impacts on Land Use Phenomenon not frequently included in urban or project planning, but increasing in frequency Example Application of UrbanSIM model in Salt Lake City, UT metropolitan area (Wasatch Front Regional Council) Model simulates changes in land prices, developer decisions, and residential and business location choices resulting from existing land use and travel time throughout a region 30

31 Impacts of Highway on Household Growth within Metropolitan Area Residential Units per Acre Waddell et al.,

32 Thoughts on Land Use Even in current years, roads influence interpretation of land cover information In future, transportation projects may exert significant impacts on land use Before and after changes on surface characteristics? Changes in population affect extent of urban heat island? Appreciate your thoughts Is tweaking land use data feasible and/or easy? Is prognostic meteorological modeling for individual transportation projects appropriate or overkill? Could AERSCREEN provide a first-order way to identify when land use impacts on dispersive properties of the atmosphere could be significant? 32

33 Source Characterization in Concentrations can depend on choice of area or volume source New York DEC (2007 workshop) Receptor location determine sensitivity of concentration to choice of volume/area source May be relevant in representation of roads, parking lots, freight terminals AERMOD 33

34 Source Characterization Accounting for traffic induced turbulence CAL3QHC: simple mixing zone algorithm AERMOD: off-model exercise with area or volume source specification GM sulfate experiment in 1975 shown on right 5462 cars per hour 80 km/h All light duty Chock,

35 As of Today For simpler, roadway-only sources, CALINE/CAL3QHCR series of models explicitly addresses traffic-induced turbulence For AERMOD applications, need to determine Source characterization that results in best model performance Recommended method for addressing vehicleinduced turbulence using current versions Thoughts and studies welcome! 35

36 Influential Inputs and Assumptions Overall, understanding inputs to which model results are most sensitive will help in understanding value of information from various inputs, increase model performance, and analyst efficiency Inputs in traffic characterization Inputs in emissions characterization Meteorological data Surface characteristics 36

37 Questions?