Articles | Volume 21, issue 6
https://doi.org/10.5194/acp-21-5063-2021
https://doi.org/10.5194/acp-21-5063-2021
Research article
 | 
31 Mar 2021
Research article |  | 31 Mar 2021

Development and intercity transferability of land-use regression models for predicting ambient PM10, PM2.5, NO2 and O3 concentrations in northern Taiwan

Zhiyuan Li, Kin-Fai Ho, Hsiao-Chi Chuang, and Steve Hung Lam Yim

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Cited articles

Allen, R. W., Amram, O., Wheeler, A. J., and Brauer, M.: The transferability of NO and NO2 land use regression models between cities and pollutants, Atmos. Environ., 45, 369–378, 2011. 
Anand, J. S. and Monks, P. S.: Estimating daily surface NO2 concentrations from satellite data – a case study over Hong Kong using land use regression models, Atmos. Chem. Phys., 17, 8211–8230, https://doi.org/10.5194/acp-17-8211-2017, 2017. 
Bertazzon, S., Johnson, M., Eccles, K., and Kaplan, G. G.: Accounting for spatial effects in land use regression for urban air pollution modeling, Spatial and Spatiotemporal Epidemiology, 14, 9–21, 2015. 
Brokamp, C., Brandt, E. B., and Ryan, P. H.: Assessing exposure to outdoor air pollution for epidemiological studies: Model-based and personal sampling strategies, J. Allergy Clin. Immun., 143, 2002–2006, 2019. 
Cai, J., Ge, Y., Li, H., Yang, C., Liu, C., Meng, X., Wang, W., Niu, C., Kan, L., Schikowski, T., and Yan, B.: Application of land use regression to assess exposure and identify potential sources in PM2.5, BC, NO2 concentrations, Atmos. Environ., 223, 117267, https://doi.org/10.1016/j.atmosenv.2020.117267, 2020. 
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Short summary
This study established land-use regression (LUR) models using only routine air quality measurement data to support long-term health studies in an Asian metropolitan area. The established LUR models captured the spatial variability in exposure to air pollution with remarkable predictive accuracy. This is the first Asian study to evaluate intercity transferability of LUR models, and it highlights that there exist uncertainties when transferring LUR models between nearby cities.
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