Motor vehicle inspection and maintenance (I/M) programs are designed to identify high-emitting vehicles and mitigate their impacts on air quality and climate. I/M programs have been traditionally ranked superior among various vehicle emission control measures by the results of cost-benefit analysis, based on the assumption that these programs will achieve the targeted emission reduction outcomes. However, the actual effects of I/M programs may be greatly uncertain and when this uncertainty is taken into account, these programs may become suboptimal. This study develops a new a cost-benefit analysis framework that links various program design consideration, such as program participation rate, identification rate and effective repair rate, to the public health benefits as well as costs of the programs. This framework helps decision makers to investigate minimum implementation requirements that at least ensure the benefits are greater than the costs of implementing the programs in order to improve the overall effectiveness of the I/M programs. To illustrate the applications of the framework, it was applied to a particulate matter oriented I/M program targeting all diesel-fueled vehicles in the city of Bangkok, Thailand, a large metropolitan area that has been suffering from severe ambient PM pollution mainly attributable to its wide use of diesel-fueled vehicles and motorcycles. It was found that the health benefits achieved from the program are sensitive to several key program design elements, including participation rate and problem vehicle identification rate, fraction of effective repairs and illegal operation rate. Other variables, such as the testing cut-points and vehicle population growth rate, only have modest effects on the overall emission reduction and consequent health benefits. Overall, the performance of multiple variables associated with I/M program design needs to be improved simultaneous in order to achieve the targeted benefits of the program.
| Identifer | oai:union.ndltd.org:ETSU/oai:dc.etsu.edu:etsu-works-3715 |
| Date | 13 November 2017 |
| Creators | Li, Ying |
| Publisher | Digital Commons @ East Tennessee State University |
| Source Sets | East Tennessee State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | ETSU Faculty Works |
| Rights | http://creativecommons.org/licenses/by/4.0/ |
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