Improving traffic-related air pollution estimates by modelling minor road traffic volumes
Journal article
Alvarado-Molina, Miguel, Curto, Ariadna, Wheeler, Amanda J., Tham, Rachel, Cerin, Ester, Nieuwenhuijsen, Mark, Vermeulen, Roel and Donaire Gonzalez, David. (2023). Improving traffic-related air pollution estimates by modelling minor road traffic volumes. Environmental Pollution. 338, p. Article 122657. https://doi.org/10.1016/j.envpol.2023.122657
Authors | Alvarado-Molina, Miguel, Curto, Ariadna, Wheeler, Amanda J., Tham, Rachel, Cerin, Ester, Nieuwenhuijsen, Mark, Vermeulen, Roel and Donaire Gonzalez, David |
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Abstract | 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. |
Keywords | minor roads; air pollution; traffic volume; AADT; black carbon; ultrafine particles; external validation |
Year | 2023 |
Journal | Environmental Pollution |
Journal citation | 338, p. Article 122657 |
Publisher | Elsevier Ltd |
ISSN | 0269-7491 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.envpol.2023.122657 |
PubMed ID | 37813140 |
Scopus EID | 2-s2.0-85173821311 |
Open access | Published as ‘gold’ (paid) open access |
Page range | 1-10 |
Funder | Australian Catholic University (ACU) |
Instituto de Salud Global Barcelona (ISGLOBAL) | |
Agency for the Research Centres of Catalonia (CERCA) Programme, Generalitat de Catalunya | |
Publisher's version | License File Access Level Open |
Output status | Published |
Publication dates | |
Online | 07 Oct 2023 |
Publication process dates | |
Accepted | 28 Sep 2023 |
Deposited | 28 Nov 2023 |
Supplemental file | License File Access Level Open |
Grant ID | 903750–141 |
CEX 2018-000806-S | |
MCIN/AEI/10.13039/501100011033 |
https://acuresearchbank.acu.edu.au/item/8zzwq/improving-traffic-related-air-pollution-estimates-by-modelling-minor-road-traffic-volumes
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OA_Alvarado_2023_Improving_traffic_related_air_pollution_estimates.pdf | |
License: CC BY 4.0 | |
File access level: Open |
Supplemental file
OA_Alvarado_2023_Improving_traffic_related_air_pollution_estimates_[GRAPHICAL_ABSTRACT].jpg | |
License: CC BY 4.0 | |
File access level: Open |
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