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1.
Chemosphere ; 297: 134171, 2022 Jun.
Article in English | MEDLINE | ID: mdl-35247447

ABSTRACT

Diesel vehicle emissions generally deteriorate with vehicle mileage due to the wear and deterioration of vehicle parts. Most of the experimental studies on vehicle emission durability were carried out based on the standard operation cycles of engine or vehicle, few research investigated vehicle emission deterioration characteristics under real driving conditions. In this research, the real driving emission (RDE) test method was used to investigate and evaluate the emission deterioration characteristics of two China-V diesel vehicles equipped with DOC and SCR systems. The experimental results show the emissions of CO and NOx from the N2 and N3 diesel vehicles increase with the vehicle mileage, showing the tendency of emission deterioration. The calculated deterioration factors of N2 and N3 diesel vehicle CO and NOx emissions are greater than the recommended values in China standard HJ 438-2008, which means experimental study on the vehicle emissions durability is necessary. The vehicle emissions deterioration depends on real driving conditions and the vehicle usage over vehicle lifetime.

2.
Sci Total Environ ; 739: 139688, 2020 Oct 15.
Article in English | MEDLINE | ID: mdl-32758932

ABSTRACT

Vehicle emission remote sensing has the potential to provide detailed emissions information at a highly disaggregated level owing to the ability to measure thousands of vehicles in a single day. Fundamentally, vehicle emission remote sensing provides a direct measure of the molar volume ratio of a pollutant to carbon dioxide, from which fuel-based emissions factors can readily be calculated. However, vehicle emissions are more commonly expressed in emission per unit distance travelled e.g. grams per km or mile. To express vehicle emission remote sensing data in this way requires an estimate of the fuel consumption at the time of the emission measurement. In this paper, an approach is developed based on vehicle specific power that uses commonly measured or easily obtainable vehicle information such as vehicle speed, acceleration and mass. We test the approach against 55 independent comprehensive PEMS measurements for Euro 5 and 6 gasoline and diesel vehicles over a wide range of driving conditions and find good agreement between the method and PEMS data. The method is applied to individual vehicle model types to quantify distance-based emission factors. The method will be appropriate for application to larger vehicle emission remote sensing databases, thus extending real-world distance-based vehicle emissions information.

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