A simple semi-empirical technique for apportioning the impact of roadways on air quality in an urban neighbourhood

Abstract Air pollution from the transport sector has a marked effect on human health, so isolating the pollutant contribution from a roadway is important in understanding its impact on the local neighbourhood. This paper proposes a novel technique based on a semi-empirical air pollution model to quantify the impact from a roadway on the air quality of a local neighbourhood using ambient records of a single air pollution monitor. We demonstrate the proposed technique using a case study, in which we quantify the contribution from a major highway with respect to the local background concentration in Auckland, New Zealand. Comparing the diurnal variation of the model-separated background contribution with real measurements from a site upwind of the highway shows that the model estimates are reliable. Amongst all of the pollutants considered, the best estimations of the background were achieved for nitrogen oxides. Although the multi-pronged approach worked well for predominantly vehicle-related pollutants, it could not be used effectively to isolate emissions of PM 10 due to the complex and less predictable influence of natural sources (such as marine aerosols). The proposed approach is useful in situations where ambient records from an upwind background station are not available (as required by other techniques) and is potentially transferable to situations such as intersections and arterial roads. Applying this technique to longer time series could help to understand the changes in pollutant concentrations from the road and background sources for different emission scenarios, for different years or seasons. Modelling results also show the potential of such a hybrid semi-empirical models to contribute to our understanding of the physical parameters determining air quality and to validate emissions inventory data.