TY - JOUR
T1 - Evaluating vehicle inspection/maintenance programs using on-road emissions data
T2 - The Atlanta reference method
AU - DeHart-Davis, Leisha
AU - Corley, Elizabeth
AU - Rodgers, Michael O.
PY - 2002/4
Y1 - 2002/4
N2 - On-road remote sensing data is an increasingly popular source of evaluation information for vehicle inspection/maintenance (I/M) programs. This article conducts one such remote sensing data evaluation for the Atlanta, Georgia, I/M program. The reference method involves comparing emissions differences in I/M and non-I/M fleet vehicles with those predicted by a regulatory computer model. Assuming that on-road emissions differences represent observed effectiveness and model-predicted emissions differences represent effectiveness goals, the Atlanta enhanced I/M program appears to be achieving 83% of its targeted emissions reductions. The method compares favorably with other remote sensing evaluation methods in its ability to be applied over time and its relatively small sample size requirement. The chief limitation to the approach is its reliance on a representative non-I/M fleet, which may differ in characteristics for which controls are difficult to locate. Such potential confounding factors include discrepancies in maintenance trends, socioeconomic conditions, and vehicle quality.
AB - On-road remote sensing data is an increasingly popular source of evaluation information for vehicle inspection/maintenance (I/M) programs. This article conducts one such remote sensing data evaluation for the Atlanta, Georgia, I/M program. The reference method involves comparing emissions differences in I/M and non-I/M fleet vehicles with those predicted by a regulatory computer model. Assuming that on-road emissions differences represent observed effectiveness and model-predicted emissions differences represent effectiveness goals, the Atlanta enhanced I/M program appears to be achieving 83% of its targeted emissions reductions. The method compares favorably with other remote sensing evaluation methods in its ability to be applied over time and its relatively small sample size requirement. The chief limitation to the approach is its reliance on a representative non-I/M fleet, which may differ in characteristics for which controls are difficult to locate. Such potential confounding factors include discrepancies in maintenance trends, socioeconomic conditions, and vehicle quality.
UR - http://www.scopus.com/inward/record.url?scp=0036548792&partnerID=8YFLogxK
U2 - 10.1177/0193841X02026002001
DO - 10.1177/0193841X02026002001
M3 - Article
C2 - 11949536
AN - SCOPUS:0036548792
SN - 0193-841X
VL - 26
SP - 111
EP - 146
JO - Evaluation Review
JF - Evaluation Review
IS - 2
ER -
