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Environmental Informatics Archives

ISSN 1811-0231 / ISEIS Publication Series Number P002

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  Paper EIA06-024, Volume 4 (2006), Pages 280-288 = complimentary

Evaluation of the International Vehicle Emission (IVE) Model with On-Road Remote Sensing Measurements

H. Guo, Q. Y. Zhang*, S. Yao, W. G. Xu and D. H. Wang

Department of Environmental Engineering, Zhejiang University, Hangzhou, China. *Corresponding author: qy_zhang@zju.edu.cn.

 

Abstract

International Vehicle Emissions (IVE) model funded by USEPA is designed to estimate emissions from motor vehicles in developing countries. In this study, the IVE model was evaluated by utilizing a dataset available from the remote sensing measurements on a large number of vehicles at five different sites in Hangzhou, China, in 2004 and 2005. For gasoline passenger cars, a total of approximately 27,000 records with valid CO and HC remote sensor readings, and 24,000 records with valid NO readings were available for the IVE model evaluation. For light duty gasoline trucks (LGDT) the remote sensing dataset contained 2,550 records with valid CO and HC readings and 2,000 records of valid NO readings. Average fuel-based emission factors derived from the remote sensing measurements were compared with corresponding emission factors derived from IVE calculations for urban, hot stabilized condition. The results show a good agreement between the two methods for gasoline passenger cars’ (PC) HC emission for all IVE subsectors and technology classes. In the case of CO emissions, the modeled results were relatively good, although systematically underestimate the emissions by almost 12~50% for different technology class. However, the model totally overestimated NOx emissions. The IVE NOx emission factors were 1.5~3.5 times of the remote sensing measured ones. The IVE model was also evaluated for LDGT, heavy duty gasoline vehicles (HDGV) and motor cycles (MC). A notable result was observed that the decrease in emissions from technology class Euro II to Euro I were overestimated by the IVE model compared to remote sensing measurements for all three pollutants.


Keywords: Remote sensing, IVE model, emission factor, evaluation

 

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