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| Titel |
Estimation of CO2 baseline level using a statistical approach for near-road vehicle emission measurements |
| VerfasserIn |
Ka Chun Wong, Zhi Ning, Ka Lok Chan |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250124730
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| Publikation (Nr.) |
 EGU/EGU2016-4209.pdf |
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| Zusammenfassung |
| Vehicle emission is widely accepted as one of the major air pollution problems in
metropolitan. Many different experimental setups have been designed to measure the
direct emission from vehicles in order to study their impact to local air quality.
Near-road/roadside in-situ measurement is one of the most common methods for vehicle
emission measurement, providing emission data of vehicle under real driving conditions. In
addition, the measurement system can be fully automatized and provides a better way to
collect vehicular emission data. Previous studies show that 5% of the total vehicles
contribute 50% of the total vehicle emission. In this study, we use the roadside
measurement data for the fuel-based emission factor calculation in order to identify
heavy emitters. The emission factor calculation uses CO2 as an indicator for the
fuel consumption rate. However, this measurement technique suffers from high
detection limit and large uncertainty of the CO2 measurement. As a result, heavy
emitters with low fuel consumption rate cannot be easily detected. A new data
analysis algorithm is developed to estimate the CO2 baseline for near-road/roadside
vehicle emission measurements. We investigated the error distribution of the CO2
measurement and use a statistical approach to identify the baseline levels. Our study
provides an alternative solution for the CO2 concentration baseline calculation. |
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