Correlating Traffic Data, Spectral Noise and Air Pollution Measurements: Retrospective Analysis of Simultaneous Measurements near a Highway in The Netherlands

Road traffic simultaneously emits noise and air pollution. This relation is primarily assessed by comparing A-weighted noise levels (L Aeq ) and various air pollutants. However, despite the common local traffic source, L Aeq and the various sets of air pollution show a lower correlation than expected. Prior work, using simultaneous mobile noise and air pollution measurements, shows that the spectral content of the noise explains the complex and highly nonlinear relation between noise and air pollution significantly better. The spectral content distinguishes between traffic volume and traffic d... Mehr ...

Verfasser: Luc Dekoninck
Marcel Severijnen
Dokumenttyp: Artikel
Erscheinungsdatum: 2022
Reihe/Periodikum: Atmosphere, Vol 13, Iss 740, p 740 (2022)
Verlag/Hrsg.: MDPI AG
Schlagwörter: noise / air pollution / ultrafine particles / proxy / low-frequency noise / road traffic / Meteorology. Climatology / QC851-999
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27192313
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://doi.org/10.3390/atmos13050740

Road traffic simultaneously emits noise and air pollution. This relation is primarily assessed by comparing A-weighted noise levels (L Aeq ) and various air pollutants. However, despite the common local traffic source, L Aeq and the various sets of air pollution show a lower correlation than expected. Prior work, using simultaneous mobile noise and air pollution measurements, shows that the spectral content of the noise explains the complex and highly nonlinear relation between noise and air pollution significantly better. The spectral content distinguishes between traffic volume and traffic dynamics, two relevant modifiers explaining both the variability in noise and air pollution emissions of the local traffic flow. In May 2011, the environmental agency in the Netherlands performed noise and air pollutant measurements near a major highway and included spectral noise. In the resulting report, the analysis of the traffic, the noise and a wide set of air pollutants only showed a strong correlation between noise and NO. In this work, this dataset is re-evaluated using the noise-related covariates, engine noise and cruising noise, defined in prior work. The modeling approach proves valid for most of the measured air pollutants except for the large PM fractions. Conclusion: the prior established methodology explains the complex interaction between traffic dynamics, noise emission and air pollution emissions for a wide variety of air pollutants. The applicability of the ‘noise-as-a-traffic-proxy’ approach is extended.