CAN NEW LIGHT RAIL REDUCE PERSONAL VEHICLE CARBON EMISSIONS? A BEFORE‐AFTER, EXPERIMENTAL‐CONTROL EVALUATION IN LOS ANGELES

Marlon G. Boarnet, Xize Wang and Douglas Houston

Journal of Regional Science, 2017, vol. 57, issue 3, 523-539

Abstract: This paper uses a before‐after, experimental‐control group method to evaluate the impacts of the newly opened Expo light rail transit line in Los Angeles on personal vehicle greenhouse gas (GHG) emissions. We applied the California Air Resources Board's EMFAC 2011 emission model to estimate the amount of daily average CO2 emissions from personal vehicle travel for 160 households across two waves, before and after the light rail opened. The 160 households were part of an experimental–control group research design. Approximately half of the households live within a half‐mile of new Expo light rail stations (the experimental group) and the balance of the sampled households live beyond a half‐mile from Expo light rail stations (the control group). Households tracked odometer mileage for all household vehicles for seven days in two sample waves, before the Expo Line opened (fall, 2011) and after the Expo Line opened (fall, 2012). Our analysis indicates that opening the Expo Line had a statistically significant impact on average daily CO2 emissions from motor vehicles. We found that the CO2 emission of households who reside within a half‐mile of an Expo Line station was 27.17 percent smaller than those living more than a half‐mile from a station after the opening of the light rail, while no significant difference exists before the opening. A difference‐in‐difference model suggests that the opening of the Expo Line is associated with 3,145 g less of household vehicle CO2 emissions per day as a treatment effect. A sensitivity analysis indicates that the emission reduction effect is also present when the experimental group of households is redefined to be those living within a kilometer from the new light rail stations.

Date: 2017
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Journal of Regional Science is currently edited by Marlon G. Boarnet, Matthew Kahn and Mark D. Partridge

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