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Model Selection for Emission Models Based on Emission Factors


Affiliations
1 School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2 University of Eastern Finland, 80101 Joensuu, Finland
 

Transportation industry accounts for the majority of air pollutant emission, which is one of the leading factors of climate change. Many vehicle emission models have been proposed focusing on emission factors to study the pollutant emission issue. However, little research has been done in China on emission models, though China is a major air pollutant-emitting country. This paper first introduces two emission models- MOBILE model and MOVES model, then proposes model selection methods including AIC (Akaike information criterion) and BIC (Bayesian information criterion) to compare and select the better model which could be applied in China. Experimental results show that the value of AIC and BIC for MOVES model is significantly lower than MOBILE model, which implies that MOVES model has better performance on real data fitness and prediction. Our experimental findings may be useful for future research on air pollutant emission modelling in China.

Keywords

Emission Factor, On-Road Test, MOBILE Model, MOVES Model.
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  • Model Selection for Emission Models Based on Emission Factors

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Authors

M. A. Jing
School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Shuping Huang
School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Kasjewruy Pateuro
University of Eastern Finland, 80101 Joensuu, Finland

Abstract


Transportation industry accounts for the majority of air pollutant emission, which is one of the leading factors of climate change. Many vehicle emission models have been proposed focusing on emission factors to study the pollutant emission issue. However, little research has been done in China on emission models, though China is a major air pollutant-emitting country. This paper first introduces two emission models- MOBILE model and MOVES model, then proposes model selection methods including AIC (Akaike information criterion) and BIC (Bayesian information criterion) to compare and select the better model which could be applied in China. Experimental results show that the value of AIC and BIC for MOVES model is significantly lower than MOBILE model, which implies that MOVES model has better performance on real data fitness and prediction. Our experimental findings may be useful for future research on air pollutant emission modelling in China.

Keywords


Emission Factor, On-Road Test, MOBILE Model, MOVES Model.