Improving traffic-related air pollution estimates by modelling minor road traffic volumes
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https://hdl.handle.net/10037/31917Date
2023-10-07Type
Journal articleTidsskriftartikkel
Peer reviewed
Author
Alvarado-Molina, Miguel; Curto, Ariadna; Wheeler, Amanda J.; Tham, Rachel; Cerin, Ester; Nieuwenhuijsen, Mark; Vermeulen, Roel; Donaire-Gonzalez, DavidAbstract
Accurately estimating annual average daily traffic (AADT) on minor roads is essential for assessing traffic-related
air pollution (TRAP) exposure, particularly in areas where most people live. Our study assessed the direct and
indirect external validity of three methods used to estimate AADT on minor roads in Melbourne, Australia.
We estimated the minor road AADT using a fixed-value approach (assuming 600 vehicles/day) and linear and
negative binomial (NB) models. The models were generated using road type, road importance index, AADT and
distance of the nearest major road, population density, workplace density, and weighted road density. External
measurements of traffic counts, as well as black carbon (BC) and ultrafine particles (UFP), were conducted at 201
sites for direct and indirect validation, respectively. Statistical tests included Akaike information criterion (AIC)
to compare models’ performance, the concordance correlation coefficient (CCC) for direct validation, and
Spearman’s correlation coefficient for indirect validation. Results show that 88.5% of the roads in Melbourne are
minor, yet only 18.9% have AADT. The performance assessment of minor road models indicated comparable
performance for both models (AIC of 1,023,686 vs. 1,058,502). In the direct validation with external traffic
measurements, there was no difference between the three methods for overall minor roads. However, for minor
roads within residential areas, CCC (95% confidence interval [CI]) values were − 0.001 (− 0.17; 0.18), 0.47 (0.32;
0.60), and 0.29 (0.18; 0.39) for the fixed-value approach, the linear model, and the NB model, respectively. In
the indirect validation, we found differences only on UFP where the Spearman’s correlation (95% CI) for both
models and fixed-value approach were 0.50 (0.37; 0.62) and 0.34 (0.19; 0.48), respectively. In conclusion, our
linear model outperformed the fixed-value approach when compared against traffic and TRAP measurements.
The methodology followed in this study is relevant to locations with incomplete minor road AADT data.
Publisher
ElsevierCitation
Alvarado-Molina, Curto, Wheeler, Tham, Cerin, Nieuwenhuijsen, Vermeulen, Donaire-Gonzalez. Improving traffic-related air pollution estimates by modelling minor road traffic volumes. Environmental Pollution (1987). 2023;338Metadata
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