Abstract

On-road vehicle emissions are one of the major sources of transport emissions. As a key design factor, road grades (or road slopes) have significant effects on on-road vehicle emissions, particularly on Heavy-Duty Vehicles (HDVs). However, the research into the relationship between road grades and on-road vehicle emissions is very rare in China. Taking a road network in Taiyuan, China, as a study area, this paper explored the influences of road grades on carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NOx) emissions of HDVs. Combining emissions data collected by Portable Emission Measurement System (PEMS) with Vehicle Specific Power (VSP), we developed an emission rate model of HDVs. Then, we integrated it with the traffic simulation model VISSIM to attain the emissions of HDVs on nine scenarios differentiated by road grades. The results showed that the three emissions are found to be highly correlated to road grades, among which the CO emissions are most sensitive to the change of road grades and the HC emissions least. Compared to the emissions at 0% grade, the emissions at 4% grade will be boosted from 39.0% to 60.6%. The CO and NOx emissions increase with the road grades in all nine scenarios, while the variations of HC emissions in different scenarios were complicated. The findings of this research will provide insights for policy-makers, scholars, and practitioners into strategies for improving road design to reduce traffic emissions and develop sustainable transportation in China.

Document type: Article

Full document

The PDF file did not load properly or your web browser does not support viewing PDF files. Download directly to your device: Download PDF document

Original document

The different versions of the original document can be found in:

https://doaj.org/toc/2071-1050 under the license cc-by
http://dx.doi.org/10.3390/su70912644
https://www.mdpi.com/2071-1050/7/9/12644/pdf,
https://ideas.repec.org/a/gam/jsusta/v7y2015i9p12644-12671d55781.html,
https://core.ac.uk/display/90109404,
https://econpapers.repec.org/RePEc:gam:jsusta:v:7:y:2015:i:9:p:12644-12671:d:55781,
https://academic.microsoft.com/#/detail/1663599712 under the license https://creativecommons.org/licenses/by/4.0/
Back to Top

Document information

Published on 01/01/2015

Volume 2015, 2015
DOI: 10.3390/su70912644
Licence: Other

Document Score

0

Views 0
Recommendations 0

Share this document

claim authorship

Are you one of the authors of this document?