Abstract
Local urban air quality models must be able to account for complex road geometries if they are to predict near-road concentrations accurately. This includes flyovers, which are often used to improve flow at busy junctions or to take traffic through urban greenspace. We present a new methodology for modelling elevated roads in which the plume is only allowed to grow downwards once it has left the downwind road edge, thus accounting for road shielding. This new approach has been implemented in the operational dispersion model ADMS-Urban. The updated model is validated against monitoring data from two sites located next to busy flyovers—one in London, UK, the other in Antwerp, Belgium. It is shown to perform very well compared with simulations in which the flyovers are modelled at ground level, and slightly better than simulations when the traditional approach to modelling elevated roads (no road shielding) is used. Near-ground concentrations are significantly reduced with road elevation due to (i) increased vertical source-receptor distance, (ii) greater dispersion from the source where wind speeds are higher, and (iii) reduced impact of ground-level plume reflections. Pollutant trapping in street canyons is also minimised in cases where a flyover is elevated above the local building level. A sensitivity analysis is also presented in which multiple road elevations are tested; these results can be used by urban planners when designing new flyovers or by modellers in deciding whether it is important to account for road elevation near sensitive receptors.
This is a preview of subscription content, log in via an institution to check access.
Source: ESRI et al. Right: Google Street View® images in the immediate vicinity of each air quality monitor
source apportionment results, using the new elevated road approach, for annual-average NOX for each 10° wind sector at the HS010 site (top) and HS5 site (bottom). Black dots and whiskers show corresponding annual-average monitored concentrations and their standard deviations. Green line in bottom panel shows total modelled concentrations when the A4 is modelled as an open road source rather than as an asymmetric canyon
Similar content being viewed by others
Data availability
The datasets associated with the London site evaluation are available from the corresponding author on reasonable request. The datasets associated with the Antwerp site evaluation may be available from Martine Van Poppel (VITO) but restrictions apply.
References
Baldwin N, Gilani O, Raja S, Batterman S, Ganguly R, Hopke P, Berrocal V, Robins T, Hoogterp S (2015) Factors affecting pollutant concentrations in the near-road environment. Atmos Environ 115:223–235. https://doi.org/10.1016/j.atmosenv.2015.05.024
Beckerman B, Jerrett M, Brook JR, Verma DK, Arian MM, Finkelstein MM (2008) Correlation of nitrogen dioxide with other traffic pollutants near a major expressway. Atmos Environ 42:275–290. https://doi.org/10.1016/j.atmosenv.2007.09.042
Cai M, Huang Y, Wang Z (2020) Dynamic three-dimensional distribution of traffic pollutant at urban viaduct with the governance strategy. Atmos Pollut Res 11:1418–1428. https://doi.org/10.1016/j.apr.2020.05.002
Carruthers DJ, Edmunds HA, Lester AE, McHugh CA, Singles RJ (2000) Use and validation of ADMS-Urban in contrasting urban and industrial locations. Int J Environ Pollut 14:364–374. https://doi.org/10.1504/IJEP.2000.000558
Caton F, Britter RE, Dalziel S (2003) Dispersion mechanisms in a street canyon. Atmos Environ 137:693–702. https://doi.org/10.1016/S1352-2310(02)00830-0
CERC (2021) ADMS Technical Specifications, available online at http://www.cerc.co.uk/TechSpec (accessed December 2021)
Cimorelli AJ, Perry SG, Venkatram A, Weil JC, Paine RJ, Wilson RB, Lee RF, Peters WD, Brode RW (2005) AERMOD: a dispersion model for industrial source applications. Part I: General Model Formulation and Boundary Layer Characterization. J Appl Meteorol Climatol 44:682–693. https://doi.org/10.1175/JAM2227.1
Defra (2019) Emissions Factors Toolkit v 9.0 User Guide, available at https://laqm.defra.gov.uk/documents/EFTv9-user-guide-v1.0.pdf (accessed December 2021)
Defra (2021) Automatic Urban and Rural Network (AURN), available at: https://uk-air.defra.gov.uk/networks/network-info?view=aurn (accessed December 2021)
Fenger J (1999) Urban air quality. Atmos Environ 33:4877–4900. https://doi.org/10.1016/S1352-2310(99)00290-3
Hang J, Luo Z, Wang X, He L, Wang B, Zhu W (2017) The influence of street layouts and viaduct settings on daily carbon monoxide exposure and intake fraction in idealized urban canyons. Environ Pollut 220:72–86. https://doi.org/10.1016/j.envpol.2016.09.024
Heist DK, Perry SG, Brixley LA (2009) A wind tunnel study of the effect of roadway configurations on the dispersion of traffic-related pollution. Atmos Environ 43:5101–5111. https://doi.org/10.1016/j.atmosenv.2009.06.034
Highways England (2021) WebTRIS, available at https://webtris.highwaysengland.co.uk (accessed December 2021)
Hitchins J, Morawska L, Wolff R, Gilbert D (2000) Concentrations of submicrometre particles from vehicle emissions near a major road. Atmos Environ 34:51–59. https://doi.org/10.1016/S1352-2310(99)00304-0
Hood C, MacKenzie I, Stocker J, Johnson K, Carruthers D, Vieno M, Doherty R (2018) Air quality simulations for London using a coupled regional-to-local modelling system. Atmos Chem Phys 18:11221–11245. https://doi.org/10.5194/acp-18-11221-2018
Hood C, Stocker J, Seaton M, Johnson K, O’Neill J, Thorne L, Carruthers D (2021) Comprehensive evaluation of an advanced street canyon air pollution model. J Air Waste Manag Assoc 71:247–262. https://doi.org/10.1080/10962247.2020.1803158
Joerger VM, Pryor SC (2018) Ultrafine particle number concentrations and size distributions around an elevated highway viaduct. Atmos Pollut Res 9:714–722. https://doi.org/10.1016/j.apr.2018.01.008
Kampa M, Castanas E (2008) Human health effects of air pollution. Environ Pollut 151:362–367. https://doi.org/10.1016/j.envpol.2007.06.012
Kumar A, Patil RS, Dikshit AK, Islam S, Kumar R (2015) Evaluation of control strategies for industrial air pollution sources using American Meteorological Society/Environmental Protection Agency Regulatory Model with simulated meteorology by Weather Research and Forecasting Model. J Clean Prod 116:110–117. https://doi.org/10.1016/j.jclepro.2015.12.079
Lu K-F, He H-D, Wang H-W, Li X-B, Peng Z-R (2020) Characterizing temporal and vertical distribution patterns of traffic-emitted pollutants near an elevated expressway in urban residential areas. Build Environ 172:106678. https://doi.org/10.1016/j.buildenv.2020.106678
Marner B (2016) Overview of changes introduced by EFT v7.0 and by CURED v2a. Air Quality Consultants, available online at https://www.aqconsultants.co.uk/CMSPages/GetFile.aspx?guid=dfba9f91-0351-4f8f-ab25-9d26f94bc8b3 (accessed December 2021)
Oke TR (1988) Street design and urban canopy layer climate. Energy Build 11:103–113. https://doi.org/10.1016/0378-7788(88)90026-6
Pasquill F (1961) The estimation of the dispersion of windborne material. Meteorol Mag 90:33–49
Sala A (2013) Assessment of traffic flow benefits of flyovers: a case study. J Traffic Transp Eng 4:1–9
Smith S, Stocker J, Seaton M, Carruthers D (2017) Model inter-comparison and validation of ADMS plume chemistry schemes. Int J Environ Pollut 62:395–406. https://doi.org/10.1504/IJEP.2017.089427
Snyder MG, Venkatram A, Heist DK, Perry SG, Petersen WB, Isakov V (2013) RLINE: A line source dispersion model for near-surface releases. Atmos Environ 77:748–756. https://doi.org/10.1016/j.atmosenv.2013.05.074
Tominaga Y, Stathopoulos T (2013) CFD simulation of near-field pollutant dispersion in the urban environment: a review of current modelling techniques. Atmos Environ 79:716–730. https://doi.org/10.1016/j.atmosenv.2013.07.028
Tsagatakis I, Richardson J, Evangelides C, Pizzolato M, Pearson B, Passant N, Pommier M, Otto A (2021) UK Spatial Emissions Methodology: a report of the National Atmospheric Emission Inventory 2019. Retrieved from: https://naei.beis.gov.uk/reports/reports?report_id=1024
Van Poppel M, Panis LI, Govarts E, Van Houtte J, Maenhaut W (2012) A comparative study of traffic related air pollution next to a motorway and a motorway flyover. Atmos Environ 60:132–141. https://doi.org/10.1016/j.atmosenv.2012.06.042
Vardoulakis S, Valiantis M, Milner J, ApSimon H (2007) Operational air pollution modelling in the UK – street canyon applications and challenges. Atmos Environ 41:4622–4637. https://doi.org/10.1016/j.atmosenv.2007.03.039
World Health Organization (WHO) (2021) WHO global air quality guidelines: particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide. World Health Organization. https://apps.who.int/iris/handle/10665/345329
Wu C-L, He H-D, Song R-F, Peng Z-R (2022) Prediction of air pollutants on roadside of the elevated roads with combination of pollutants periodicity and deep learning method. Build Environ 207:108436. https://doi.org/10.1016/j.buildenv.2021.108436
Zhi H, Qiu Z, Wang W, Wang G, Hao Y, Liu Y (2020) The influence of a viaduct on PM dispersion in a typical street: field experiment and numerical simulations. Atmos Pollut Res 11:815–824. https://doi.org/10.1016/j.apr.2020.01.009
Acknowledgements
We are grateful to Highways England for their input during the project.
Funding
This study was funded by Highways England under the Small Business Research Initiative (SBRI) Innovate UK competition ‘Developing digital roads and improving air quality’.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
O’Neill, J., Seaton, M., Johnson, K. et al. Modelling the influence of road elevation on pollutant dispersion. Air Qual Atmos Health (2022). https://doi.org/10.1007/s11869-022-01198-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11869-022-01198-9