Abstract
Modern gasoline and diesel vehicles are equipped with highly effective emission control systems that result in low emissions of pollutants such as nitrogen oxides (NOx) when new. However, with increasing age or mileage, the emissions performance of vehicles can deteriorate over time, leading to increased emissions. In this work we use comprehensive vehicle emission remote sensing measurements collected over a wide range of conditions, together with individual vehicle measured mileage to quantify vehicle emissions deterioration. A quantile regression modelling approach is used to provide a more complete understanding of the distribution of deterioration effects that is not captured by considering mean changes over time. The approach accounts for factors such as driving conditions and ambient temperature, as well as determining whether deterioration affects whole populations of vehicles or a smaller subset of them. Accounting for these factors, we find that for most pollutants the rate of deterioration of emissions from pre-Euro 5 gasoline passenger cars is highly skewed. Between 5% and 10% of pre-Euro 5 gasoline passenger cars have emissions similar to a Euro 5 diesel car, suggesting that policies should be developed to accelerate their removal from the fleet. Furthermore, we find evidence that there are differences between vehicle manufacturers in the way emissions of NOx deteriorate.
Original language | English |
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Article number | 100162 |
Number of pages | 9 |
Journal | Atmospheric Environment: X |
Volume | 14 |
DOIs | |
Publication status | Published - 2 Apr 2022 |
Bibliographical note
Funding Information:The authors thank Dr Gary Bishop from the University of Denver for access to and use of the FEAT instrument. Jack Davison was supported by NERC grant NE/S012044/1. We thank Drs Adam Vaughan, Stuart Young and Will Drysdale from the University of York for the collection of data using the FEAT instrument. Ricardo Energy & Environment's remote sensing field team, especially Ben Fowler, Tom Green and Les Phelps are thanked for collecting data using the Opus RSD 5000.
Funding Information:
The authors thank Dr Gary Bishop from the University of Denver for access to and use of the FEAT instrument. Jack Davison was supported by NERC grant NE/S012044/1 . We thank Drs Adam Vaughan, Stuart Young and Will Drysdale from the University of York for the collection of data using the FEAT instrument. Ricardo Energy & Environment's remote sensing field team, especially Ben Fowler, Tom Green and Les Phelps are thanked for collecting data using the Opus RSD 5000.
Publisher Copyright:
© 2022 The Author(s)
Keywords
- Emission deterioration
- Quantile regression
- Remote sensing
- Vehicle emissions