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Street-scale air quality modelling for Beijing during a winter 2016 measurement campaign

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Street-scale air quality modelling for Beijing during a winter 2016 measurement campaign. / Biggart, Michael; Stocker, Jenny; Doherty, R. M. et al.
In: Atmospheric Chemistry and Physics , Vol. 20, 05.03.2020, p. 2755-2780.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Biggart, M, Stocker, J, Doherty, RM, Wild, O, Hollaway, M, Carruthers, D, Li, J, Zhang, Q, Wu, R, Kotthaus, S, Grimmond, S, Squires, FA, Lee, J & Shi, Z 2020, 'Street-scale air quality modelling for Beijing during a winter 2016 measurement campaign', Atmospheric Chemistry and Physics , vol. 20, pp. 2755-2780. https://doi.org/10.5194/acp-20-2755-2020

APA

Biggart, M., Stocker, J., Doherty, R. M., Wild, O., Hollaway, M., Carruthers, D., Li, J., Zhang, Q., Wu, R., Kotthaus, S., Grimmond, S., Squires, F. A., Lee, J., & Shi, Z. (2020). Street-scale air quality modelling for Beijing during a winter 2016 measurement campaign. Atmospheric Chemistry and Physics , 20, 2755-2780. https://doi.org/10.5194/acp-20-2755-2020

Vancouver

Biggart M, Stocker J, Doherty RM, Wild O, Hollaway M, Carruthers D et al. Street-scale air quality modelling for Beijing during a winter 2016 measurement campaign. Atmospheric Chemistry and Physics . 2020 Mar 5;20:2755-2780. doi: 10.5194/acp-20-2755-2020

Author

Biggart, Michael ; Stocker, Jenny ; Doherty, R. M. et al. / Street-scale air quality modelling for Beijing during a winter 2016 measurement campaign. In: Atmospheric Chemistry and Physics . 2020 ; Vol. 20. pp. 2755-2780.

Bibtex

@article{c122f5d478c64e6bac3cbf0e5cc15ae5,
title = "Street-scale air quality modelling for Beijing during a winter 2016 measurement campaign",
abstract = "We examine the street-scale variation of NOx, NO3, O3 and PM2.5 concentrations in Beijing during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) winter measurement campaign in November-December 2016. Simulations are performed using the urban air pollution dispersion and chemistry model ADMS-Urban and an explicit network of road source emissions. Two versions of the gridded Multi-resolution Emission Inventory for China (MEIC v1.3) are used: the standard MEIC v1.3 emissions and an optimised version, both at 3 km resolution. We construct a new traffic emissions inventory by apportioning the transport sector onto a detailed spatial road map. Agreement between mean simulated and measured pollutant concentrations from Beijing's air quality monitoring network and the Institute of Atmospheric Physics (IAP) field site is improved when using the optimised emissions inventory. The inclusion of fast NOx-O3 chemistry and explicit traffic emissions enables the sharp concentration gradients adjacent to major roads to be resolved with the model. However, NO2 concentrations are overestimated close to roads, likely due to the assumption of uniform traffic activity across the study domain. Differences between measured and simulated diurnal NO2 cycles suggest that an additional evening NOx emission source, likely related to heavy-duty diesel trucks, is not fully accounted for in the emissions inventory. Overestimates in simulated early evening NO2 are reduced by delaying the formation of stable boundary layer conditions in the model to replicate Beijing's urban heat island. The simulated campaign period mean PM2.5 concentration range across the monitoring network (∼15 µg m-3) is much lower than the measured range (∼40 µg m-3). This is likely a consequence of insufficient PM2.5 emissions and spatial variability, neglect of explicit point sources, and assumption of a homogeneous background PM2.5 level. Sensitivity studies highlight that the use of explicit road source emissions, modified diurnal emission profiles, and inclusion of urban heat island effects permit closer agreement between simulated and measured NO2 concentrations. This work lays the foundations for future studies of human exposure to ambient air pollution across complex urban areas, with the APHH-China campaign measurements providing a valuable means of evaluating the impact of key processes on street-scale air quality.",
keywords = "Air quality, Modelling, ADMS-Urban, Beijing, APHH-Beijing, PM2.5",
author = "Michael Biggart and Jenny Stocker and Doherty, {R. M.} and Oliver Wild and Michael Hollaway and David Carruthers and Jie Li and Qiang Zhang and Ruili Wu and Simone Kotthaus and Sue Grimmond and F.A. Squires and James Lee and Zongbo Shi",
year = "2020",
month = mar,
day = "5",
doi = "10.5194/acp-20-2755-2020",
language = "English",
volume = "20",
pages = "2755--2780",
journal = "Atmospheric Chemistry and Physics ",
issn = "1680-7316",
publisher = "Copernicus GmbH (Copernicus Publications) on behalf of the European Geosciences Union (EGU)",

}

RIS

TY - JOUR

T1 - Street-scale air quality modelling for Beijing during a winter 2016 measurement campaign

AU - Biggart, Michael

AU - Stocker, Jenny

AU - Doherty, R. M.

AU - Wild, Oliver

AU - Hollaway, Michael

AU - Carruthers, David

AU - Li, Jie

AU - Zhang, Qiang

AU - Wu, Ruili

AU - Kotthaus, Simone

AU - Grimmond, Sue

AU - Squires, F.A.

AU - Lee, James

AU - Shi, Zongbo

PY - 2020/3/5

Y1 - 2020/3/5

N2 - We examine the street-scale variation of NOx, NO3, O3 and PM2.5 concentrations in Beijing during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) winter measurement campaign in November-December 2016. Simulations are performed using the urban air pollution dispersion and chemistry model ADMS-Urban and an explicit network of road source emissions. Two versions of the gridded Multi-resolution Emission Inventory for China (MEIC v1.3) are used: the standard MEIC v1.3 emissions and an optimised version, both at 3 km resolution. We construct a new traffic emissions inventory by apportioning the transport sector onto a detailed spatial road map. Agreement between mean simulated and measured pollutant concentrations from Beijing's air quality monitoring network and the Institute of Atmospheric Physics (IAP) field site is improved when using the optimised emissions inventory. The inclusion of fast NOx-O3 chemistry and explicit traffic emissions enables the sharp concentration gradients adjacent to major roads to be resolved with the model. However, NO2 concentrations are overestimated close to roads, likely due to the assumption of uniform traffic activity across the study domain. Differences between measured and simulated diurnal NO2 cycles suggest that an additional evening NOx emission source, likely related to heavy-duty diesel trucks, is not fully accounted for in the emissions inventory. Overestimates in simulated early evening NO2 are reduced by delaying the formation of stable boundary layer conditions in the model to replicate Beijing's urban heat island. The simulated campaign period mean PM2.5 concentration range across the monitoring network (∼15 µg m-3) is much lower than the measured range (∼40 µg m-3). This is likely a consequence of insufficient PM2.5 emissions and spatial variability, neglect of explicit point sources, and assumption of a homogeneous background PM2.5 level. Sensitivity studies highlight that the use of explicit road source emissions, modified diurnal emission profiles, and inclusion of urban heat island effects permit closer agreement between simulated and measured NO2 concentrations. This work lays the foundations for future studies of human exposure to ambient air pollution across complex urban areas, with the APHH-China campaign measurements providing a valuable means of evaluating the impact of key processes on street-scale air quality.

AB - We examine the street-scale variation of NOx, NO3, O3 and PM2.5 concentrations in Beijing during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) winter measurement campaign in November-December 2016. Simulations are performed using the urban air pollution dispersion and chemistry model ADMS-Urban and an explicit network of road source emissions. Two versions of the gridded Multi-resolution Emission Inventory for China (MEIC v1.3) are used: the standard MEIC v1.3 emissions and an optimised version, both at 3 km resolution. We construct a new traffic emissions inventory by apportioning the transport sector onto a detailed spatial road map. Agreement between mean simulated and measured pollutant concentrations from Beijing's air quality monitoring network and the Institute of Atmospheric Physics (IAP) field site is improved when using the optimised emissions inventory. The inclusion of fast NOx-O3 chemistry and explicit traffic emissions enables the sharp concentration gradients adjacent to major roads to be resolved with the model. However, NO2 concentrations are overestimated close to roads, likely due to the assumption of uniform traffic activity across the study domain. Differences between measured and simulated diurnal NO2 cycles suggest that an additional evening NOx emission source, likely related to heavy-duty diesel trucks, is not fully accounted for in the emissions inventory. Overestimates in simulated early evening NO2 are reduced by delaying the formation of stable boundary layer conditions in the model to replicate Beijing's urban heat island. The simulated campaign period mean PM2.5 concentration range across the monitoring network (∼15 µg m-3) is much lower than the measured range (∼40 µg m-3). This is likely a consequence of insufficient PM2.5 emissions and spatial variability, neglect of explicit point sources, and assumption of a homogeneous background PM2.5 level. Sensitivity studies highlight that the use of explicit road source emissions, modified diurnal emission profiles, and inclusion of urban heat island effects permit closer agreement between simulated and measured NO2 concentrations. This work lays the foundations for future studies of human exposure to ambient air pollution across complex urban areas, with the APHH-China campaign measurements providing a valuable means of evaluating the impact of key processes on street-scale air quality.

KW - Air quality

KW - Modelling

KW - ADMS-Urban

KW - Beijing

KW - APHH-Beijing

KW - PM2.5

U2 - 10.5194/acp-20-2755-2020

DO - 10.5194/acp-20-2755-2020

M3 - Journal article

VL - 20

SP - 2755

EP - 2780

JO - Atmospheric Chemistry and Physics

JF - Atmospheric Chemistry and Physics

SN - 1680-7316

ER -