Study on updated baseline emission factors and reduction rates for tunnel ventilation design based on prediction and measurement

Abstract Driven by technological innovation and emission standards, the actual emission level of road motor vehicles is far lower than the design value of the current standard, so it is necessary to update the outdated parameters in the standard for research. The estimated emission factors were obtained based on the updated statistical data of Chinese vehicle models and the comprehensive baseline emission factors, and the inter-annual variation was found to be far more than 2% of the standard setting, and a grey prediction model was established based on the deduced emission factor sequence. The predictive emission reduction rates of gasoline vehicle CO, diesel vehicle NO x and PM 2.5 are 14.5%, 4.7% and 10.1%, respectively. Field tests were carried out in the Yanglin extra-long tunnel. Through multiple regression analysis, the emission factors of gasoline vehicle CO, diesel vehicle NO x and diesel vehicle PM 2.5 are 0.79 g/ (km·veh), 5.64 g/ (km·veh) and 0.149 g/ (km·veh), respectively. The measured emission factor results are significantly lower than those in the China Guidelines 2014 , with a difference of more than 80%, much closer to the levels reported by PIARC. It is proved that the long base year and unreasonable reduction rate selection are the key reasons for the deviation from the actual standard emission factor. Combined with the measured data and predicted model data, this paper proposes to update the baseline emission factors and reduction rates of ventilation design, taking 2020 as the base year, the baseline emission factors for CO, NO x and PM 2.5 are 0.46 g/ (km·veh), 4.72 g/ (km·veh) and 0.027 g/ (km·veh), respectively, and the emission reduction rates are 12%, 4.7% and 10.1%, respectively. Through case calculation, the air demand after the parameter update was 70% lower than that before the update. The results can provide reference for tunnel ventilation design in China.