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dc.contributor.authorAlvarado-Molina, Miguel
dc.contributor.authorCurto, Ariadna
dc.contributor.authorWheeler, Amanda J.
dc.contributor.authorTham, Rachel
dc.contributor.authorCerin, Ester
dc.contributor.authorNieuwenhuijsen, Mark
dc.contributor.authorVermeulen, Roel
dc.contributor.authorDonaire-Gonzalez, David
dc.date.accessioned2023-12-04T08:40:18Z
dc.date.available2023-12-04T08:40:18Z
dc.date.issued2023-10-07
dc.description.abstractAccurately 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.en_US
dc.identifier.citationAlvarado-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;338en_US
dc.identifier.cristinIDFRIDAID 2195084
dc.identifier.doi10.1016/j.envpol.2023.122657
dc.identifier.issn0269-7491
dc.identifier.issn1873-6424
dc.identifier.urihttps://hdl.handle.net/10037/31917
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalEnvironmental Pollution (1987)
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleImproving traffic-related air pollution estimates by modelling minor road traffic volumesen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Med mindre det står noe annet, er denne innførselens lisens beskrevet som Attribution 4.0 International (CC BY 4.0)