Articles | Volume 20, issue 5
https://doi.org/10.5194/acp-20-2755-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-2755-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Mar 2020
Research article |
| 05 Mar 2020
| 05 Mar 2020
Street-scale air quality modelling for Beijing during a winter 2016 measurement campaign
Michael Biggart
CORRESPONDING AUTHOR
School of Geosciences, University of Edinburgh, Edinburgh, UK
Jenny Stocker
Cambridge Environmental Research Consultants, Cambridge, UK
Ruth M. Doherty
School of Geosciences, University of Edinburgh, Edinburgh, UK
Oliver Wild
Lancaster Environment Centre, Lancaster University, Lancaster, UK
Michael Hollaway
Lancaster Environment Centre, Lancaster University, Lancaster, UK
now at: Centre for Ecology & Hydrology, Lancaster Environment
Centre, Bailrigg, Lancaster, UK
David Carruthers
Cambridge Environmental Research Consultants, Cambridge, UK
Jie Li
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing, China
Qiang Zhang
Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, China
Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, China
Simone Kotthaus
Department of Meteorology, University of Reading, Reading, UK
Institut Pierre Simon Laplace, École Polytechnique, Palaiseau,
France
Sue Grimmond
Department of Meteorology, University of Reading, Reading, UK
Freya A. Squires
Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry,
University of York, York, UK
James Lee
Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry,
University of York, York, UK
National Centre for Atmospheric Science, University of York, York, UK
Zongbo Shi
School of Geography Earth and Environmental Sciences, University of
Birmingham, Birmingham, UK
Institute of Surface-Earth System Science, Tianjin University,
Tianjin, China
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- Contrasting chemical environments in summertime for atmospheric ozone across major Chinese industrial regions: the effectiveness of emission control strategies Z. Liu et al. 10.5194/acp-21-10689-2021
- Measurements of traffic-dominated pollutant emissions in a Chinese megacity F. Squires et al. 10.5194/acp-20-8737-2020
- An integrated air quality modeling system coupling regional-urban and street models in Beijing T. Wang et al. 10.1016/j.uclim.2022.101143
- A method for estimating the ratio of aerosol mass concentration to the imaginary part of the atmospheric complex refractive index and its application R. Yuan et al. 10.1016/j.atmosres.2021.105848
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- Emission Rate Estimation of Industrial Air Pollutant Emissions Based on Mobile Observation X. Cui et al. 10.3390/atmos15080969
- Constraining emission estimates of carbon monoxide using a perturbed emissions ensemble with observations: a focus on Beijing L. Yuan et al. 10.1007/s11869-021-01041-7
- Integrated emission inventory and modelling to assess the distribution of particulate matters from rice straw open burning in Hanoi, Vietnam H. Le et al. 10.1016/j.apr.2022.101416
- Application of ADMS-Urban for an area with a high contribution of residential heating emissions - model verification and sensitivity study for PM2.5 P. Porwisiak et al. 10.1016/j.scitotenv.2023.168011
- Assessment of the Contribution of Different Particulate Matter Sources on Pollution in Sofia City R. Dimitrova & M. Velizarova 10.3390/atmos12040423
- Street-scale dispersion modelling framework of road-traffic derived air pollution in Hanoi, Vietnam K. Ngo et al. 10.1016/j.envres.2023.116497
- Predicting high-resolution air quality using machine learning: Integration of large eddy simulation and urban morphology data S. Wang et al. 10.1016/j.envpol.2024.123371
- Improving NOx emission estimates in Beijing using network observations and a perturbed emissions ensemble L. Yuan et al. 10.5194/acp-22-8617-2022
- Long-term characterization of roadside air pollutants in urban Beijing and associated public health implications X. Wu et al. 10.1016/j.envres.2022.113277
- Spatiotemporal estimation of satellite-borne and ground-level NO2 using full residual deep networks L. Li & J. Wu 10.1016/j.rse.2020.112257
- Implications of Mitigating Ozone and Fine Particulate Matter Pollution in the Guangdong‐Hong Kong‐Macau Greater Bay Area of China Using a Regional‐To‐Local Coupling Model X. Zhang et al. 10.1029/2021GH000506
- Evaluating traffic emission control policies based on large-scale and real-time data: A case study in central China C. Zou et al. 10.1016/j.scitotenv.2022.160435
- Large-eddy simulation of traffic-related air pollution at a very high resolution in a mega-city: evaluation against mobile sensors and insights for influencing factors Y. Zhang et al. 10.5194/acp-21-2917-2021
- Study on the Concentration of Top Air Pollutants in Xuzhou City in Winter 2020 Based on the WRF-Chem and ADMS-Urban Models W. Liu et al. 10.3390/atmos15010129
- The Impact of Anthropogenic VOC Emissions on Atmospheric Pollution: A Case Study of a Typical Industrialized Area in China X. Gao et al. 10.3390/atmos14101586
- A Multi-model Air Quality System for Health Research: Road model development and evaluation M. Seaton et al. 10.1016/j.envsoft.2022.105455
- Direct measurements of black carbon fluxes in central Beijing using the eddy covariance method R. Joshi et al. 10.5194/acp-21-147-2021
- Comparative assessment of ground-level air quality in the metropolitan area of Prague using local street canyon modelling V. Duong & O. Murana 10.1016/j.buildenv.2023.110293
- Estimating background concentrations of PM2.5 for urban air quality modelling in a data poor environment E. Draper et al. 10.1016/j.atmosenv.2023.120107
- On the suitability of dispersion models of varying degree of complexity for air quality assessment and urban planning W. Patiño et al. 10.1016/j.buildenv.2024.111892
- Using Task Farming to Optimise a Street-Scale Resolution Air Quality Model of the West Midlands (UK) J. Zhong et al. 10.3390/atmos12080983
- Modelling spatiotemporal variations of the canopy layer urban heat island in Beijing at the neighbourhood scale M. Biggart et al. 10.5194/acp-21-13687-2021
- Towards sustainable and net-zero cities: A review of environmental modelling and monitoring tools for optimizing emissions reduction strategies for improved air quality in urban areas A. O'Regan & M. Nyhan 10.1016/j.envres.2023.116242
- A two-way coupled regional urban–street network air quality model system for Beijing, China T. Wang et al. 10.5194/gmd-16-5585-2023
- “Forest fire emissions: A contribution to global climate change” S. Singh 10.3389/ffgc.2022.925480
- Using dispersion models at microscale to assess long-term air pollution in urban hot spots: A FAIRMODE joint intercomparison exercise for a case study in Antwerp F. Martín et al. 10.1016/j.scitotenv.2024.171761
Latest update: 20 Nov 2024
Short summary
Ambient air pollution is a major cause of premature death in China. We examine the street-scale variation of pollutant levels in Beijing using air pollution dispersion and chemistry model ADMS-Urban. Campaign measurements are compared with simulated pollutant levels, providing a valuable means of evaluating the impact of key processes on urban air quality. Air quality modelling at such fine scales is essential for human exposure studies and for informing choices on future emission controls.
Ambient air pollution is a major cause of premature death in China. We examine the street-scale...
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