Articles | Volume 18, issue 15
https://doi.org/10.5194/acp-18-10869-2018
https://doi.org/10.5194/acp-18-10869-2018
Research article
 | 
03 Aug 2018
Research article |  | 03 Aug 2018

Does afforestation deteriorate haze pollution in Beijing–Tianjin–Hebei (BTH), China?

Xin Long, Naifang Bei, Jiarui Wu, Xia Li, Tian Feng, Li Xing, Shuyu Zhao, Junji Cao, Xuexi Tie, Zhisheng An, and Guohui Li

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Cited articles

Bai, Y., Feng, M., Jiang, H., Wang, J., and Liu, Y.: Validation of land cover maps in China using a sampling-based labeling approach, Remote Sens.-Basel, 7, 10589–10606, 2015. 
Bei, N., Li, G., and Molina, L. T.: Uncertainties in SOA simulations due to meteorological uncertainties in Mexico City during MILAGRO-2006 field campaign, Atmos. Chem. Phys., 12, 11295–11308, https://doi.org/10.5194/acp-12-11295-2012, 2012. 
Bei, N., Wu, J., Elser, M., Feng, T., Cao, J., El-Haddad, I., Li, X., Huang, R., Li, Z., Long, X., Xing, L., Zhao, S., Tie, X., Prévôt, A. S. H., and Li, G.: Impacts of meteorological uncertainties on the haze formation in Beijing–Tianjin–Hebei (BTH) during wintertime: a case study, Atmos. Chem. Phys., 17, 14579–14591, https://doi.org/10.5194/acp-17-14579-2017, 2017. 
Bichet, A., Wild, M., Folini, D., and Schar, C.: Causes for decadal variations of wind speed over land: Sensitivity studies with a global climate model, Geophy. Res. Lett., 39, L11701, https://doi.org/10.1029/2012GL051685, 2012. 
Binkowski, F. S. and Roselle, S. J.: Models-3 Community Multiscale Air Quality (CMAQ) model aerosol component: 1. Model description, J. Geophys. Res., 108, 4183, https://doi.org/10.1029/2001JD001409, 2003. 
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