Transportation Research Procedia, 25, 3290–3302.īatterman, S., Ganguly, R., Isakov, V., Burke, J., Arunachalam, S., Snyder, M., Robins, T., & Lewis, T. Methodology for characterizing vehicle fleet composition and its territorial variability, needed for assessing low emission zones. This study provides a solid framework for developing high spatial–temporal resolution emission inventories for other densely populated cities of small area.Īndré, M., Carteret, M., Pasquier, A., & Liu, Y. Meanwhile, analysis of 3 scenarios on changes of road traffic emissions due to the operation of a light railway transit (LRT) system, variation on share of diesel, electric, and gasoline within the vehicle fleet, and replacement of vehicles with ones of Euro 5 and Euro 6 emission standards was carried out. The estimated fuel consumption agreed well also with the statistical fuel consumption in Macau. Results show that the total annual emissions of CO, CO 2, PM, NO X, and VOC in 2014 were 14,770, 413,099, 69, 1151, and 2945 tons, respectively. To improve the accuracy and temporal–spatial resolution for emission inventory, through a bottom-up approach, link-based road traffic emission inventory with a spatial resolution of 0.1 km ∗ 0.1 km and a temporal resolution of 1 h for Macau in 2014 was developed by using a traffic model (VISUM), a road traffic emission model (TREM), the Geographic Information System (GIS), and the most up-to-date information available. A high spatial–temporal resolution road traffic emission inventory is essential for assessment of environmental stresses imposed by local vehicle movements. This is an auxiliary step to prepareĪ good starting condition.With rapid economic growth, road transport is contributing substantial adverse effects on urban air quality, especially in densely populated cities with high growth rate of GDP per capita, such as Macau. (i.e., period-specific âreliability skimâ).Ī â A~ â A = links for which traffic counts are known Regional O-D matrix for a certain time of day period or hour Is designed to produce a distribution of travel times for a full The current memo explains generation of O-D timeĭistribution for model estimation for the base year. To explain travel choices along with the average travel timeĪnd cost. These reliability measures are used in travel demand models Which is needed for calculating travel time reliability measures. This method is suggested for the generation of originâĭestination (O-D) travel time distribution for the base year, Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages. Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book.
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