Are We Successful in Reducing Vehicle Miles

Transcription

1 TRB Environment and Energy Research Conference, Raleigh, NC June 7, 2010 Are We Successful in Reducing Vehicle Miles Traveled in Air Quality Nonattainment Areas? Statistical Evidence of the Impact of Air Quality Nonattainment Designation on Vehicle Miles Traveled in the Past Three Decades Presenting Author: Lei Zhang 1 Co-Authors: Xiang He 2, Yijing Lu 2, Nick Ferrari 2, Cory Krause 2 1. Assistant Professor, 2. Research Assistant Department of Civil & Environmental Engineering g University of Maryland College Park Phone: , lei@umd.edu 1

2 Background Federal involvement with air quality control 1955 APCA; 1969 NEPA; 1963~ CAA and CAAA; 1980 APA; 1993 Conformity Regulation; Etc. Reducing VMT is an official i goal of the U.S. government policy Stated in the CAA, the President s 1993 CCAP, CMAQ Program in ISTEA, TEA-2, and SAFETEA-LU Impact of nonattainment designation on VMT? Air quality conformity rule Congestion Management and Air Quality Improvement Program 2

3 Research Question Have air quality control, the associated funding preference, and state/local planning efforts to attain conformity indeed reduced VMT and VMT growth rates in air quality nonattainment areas? Nonattainment Designation Reduction in VMT? 3

4 Research Overview Data Collection and Integration HPMS, NHPN, and other national data sources Case Studies based on Hypothesis Testing 30 case studies representing urban/rural areas of various sizes Statistical Modeling based on SEM State-level analysis of short- and long-run effects 4

5 HPMS Data Processing and Integration Data Aggregation VMT totals for counties, states, and EPA non-attainment areas Data Geo-Coding Merging HPMS and NHPN into a GIS-based VMT database VMT by Vehicle Type Extrapolation from truck percentages on sample sections to all universe sections VMT share by vehicle type at the state level 5

6 Case Studies 30 case study areas representing all regions in the U.S. and representing large/medium/small urban areas and rural areas are selected based on CO, PM, and Ozone nonattainment designations since

7 Spatial Analysis for Case Studies Example: Atlanta a. Nonattainment status in Atlanta b. Nonattainment/attainment areas 7

8 Results based on 2000~2007 HPMS Data Difference in VMT/Person (Attainment Nonattainment)

9 Results based on 2000~2007 HPMS Data Difference in VMT/Person Growth Rate (Attainment Nonattainment)

10 T-Test Results VMT/Person Attainment Nonattainment = 6.79 miles/person Difference is statistically significant at level 0.03 VMT/Person Growth Rate Attainment Nonattainment = 0.52% Difference is statistically ti ti significant ifi at level l Both VMT/Person and VMT/person growth rate are lower in nonattainment areas 10

11 Results based on 1980~2008 HPMS VMT/Person Growth Rate Comparison by Year Nonattainment Attainment

12 State-Level Analysis with SEM Model Structural Equation Model Specification 1 / 1 / 1 With autoregressive errors: 1,,, Data Longitudinal panel data based on HPMS and other national data sources between 1978 and 2008

13 Results: VMT Equation Dependent Variable: vma Coefficient t P> t Description vma(t 1) ** Vehicle miles traveled per adult vehstock * Vehicle ownership per adult fuelcost/mile ** Fuel cost per mile at 1987 prices (fuelcost/mile)^ ** (fuelcost/mile)*income ** (fuelcost/mile)*urban income ** Personal income per capita at 1987 prices adults/road mile ** pop/adult urban ** Fraction of population living in urban areas employment/capita * Trend Used to capture changes in technology and consumer preferences %race_black ** %race_other %pop_ ** %pop_ ** %pop_ ** Median age GDP/capita Ozone_CO_PM ** constant ** Combined variable representing the nonattainment status of 1 hour ozone, CO and PM 10 (Fraction of population living in nonattainment areas) rho Coefficient of error autocorrelation No. of Observations 1887 R squared

14 Results: Vehicle Ownership Equation Dependent Variable: vehstock Coefficient t P> t Description vehstock(t 1) ** Vehicle miles traveled per adult vma ** Vehicle miles traveled per adult pv Price of new vehicles (index) fuelcost/mile Fuel cost per mile at 1987 prices income Personal income per capita at 1987 prices adults/road mile ** interest Interest rate for new car loans licenses/adult ** Trend Used to capture changes in technology and consumer preferences employment/capita Household size ** %race_black ** %race_ other ** Combined variable representing the nonattainment status of 1 hour ozone, CO and PM 10 (Fraction of population living in nonattainment counties) constant rho ** Coefficient of error autocorrelation Ozone_CO_PM No. of Observations 1887 R squared Adjusted R squared Notes: Italic type indicates the independent variable is logged. ** or * indicates the coefficient is statistically significant at the 5% or 10% level. Estimates of fixed effects coefficients are not shown.

15 Results: Vehicle Fuel Efficiency Equation Dependent Variable: fint Coefficient t P> t Description fint(t 1) ** Fuel intensity (Reciprocal of Fuel Efficiency) vma+pf ** Vehicle miles traveled per adult; fuel cost per gallon at 1987 prices cafe ** Variable measuring strength of CAFÉ regulation income Personalincome per capita at 1987 prices pop/adult urban Fraction of population living in urban areas employment/capita ** GDP/capita ** D ** Dummy variable for the years 1974 and 1979 Trend Trend before the OPEC embargo in 1973 Trend ** Trend between the embargo and the Iranian revolution in 1979 Trend ** Trend after the Iranian revolution constant ** rho ** Coefficient of error autocorrelation No. of Observations 1887 R squared Adjusted d R squared Notes: Italic type indicates the independent variable is logged. ** or * indicates the coefficient is statistically significant at the 5% or 10% level. Estimates of fixed effects coefficients are not shown.

16 Findings from State-Level Analysis Short-Run Impact of Nonattainment Designation 1.79% reduction in VMT 0.63% reduction in vehicle ownership Long-Run Impact of Nonattainment Designation 7.13% reduction in VMT 2.50% reduction in vehicle ownership Actual long-run impact will be smaller because an area may not be designated as nonattainment forever

17 Policy Analysis based on HPMS Data

18 Conclusions Statistically significant negative correlation between nonattainment designation and VMT 0.52% reduction in VMT growth rate. 1.79% (7.13%) reduction in short-run (long-run) VMT. Nonattainment t Designation Reduction in VMT? Causality? Maybe, but not proven. Proper control of confounding factors (urbanization, demographics, income, congestion, etc.). Hypothesized causal structure in the SEM cannot be rejected.

19 Policy Implications A bit premature to make policy recommendations based on these findings alone. Need additional analysis that attributes the impact of nonattainment designation on VMT to: Air quality conformity rule in transportation planning; CMAQ program; Other federal, state, and local efforts in reducing VMT in g air quality nonattainment areas.

20 Thank you! Additional Questions and Comments Lei Zhang Assistant Professor Department of Civil & Environmental Engineering g University of Maryland College Park lei@umd.edu, Acknowledgement This research is funded by the FHWA. Dr. Kenneth Small and Dr. Kurt Van Dender have provided d a dataset t for the statistical ti ti analysis. 20