Although air quality in China has substantially improved since 2013 as a consequence of the clean air action, severe haze events still frequently strike megacities despite strict local emissions reduction efforts. Long-range transport and local accumulation as well as chemical transformation have been deemed as key factors of heavy haze pollution; however, the formation mechanisms of regional long-lasting haze and the physical and chemical connections between different megacities clusters are still poorly understood. Here we present that long-range transport and aerosol–boundary layer feedback may interact rather than act as two isolated processes as traditionally thought by investigating typical regional haze events in northern and eastern China. This interaction can then amplify transboundary air pollution transport over a distance of 1,000 km and boost long-lasting secondary haze from the North China Plain to the Yangtze River delta. Earlier emission reduction before the pollution episodes would provide better air pollution mitigation in both regions. Our results show an amplified transboundary transport of haze by aerosol–boundary layer interaction in China and suggest the importance of coordinated cross-regional emission reduction with a focus on radiatively active species like black carbon.
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The observation and simulation data that support the main findings of this study are available at figshare data publisher (https://doi.org/10.6084/m9.figshare.9963311.v6). The emission input used in this work is the mosaic Asian anthropogenic emission inventory (MIX), which is archived at http://www.meicmodel.org/dataset-mix.html. The radiosonde measurements in Integrated Global Radiosonde Archive Version 2 are openly accessible at https://www1.ncdc.noaa.gov/pub/data/igra. The original simulation data for multiple cross-regional pollution events used in this study are stored in a high-performance computing centre of Nanjing University due to large data storage and can be made available from the corresponding author upon request.
Data processing techniques are available on request from the corresponding author. The source code of the WRF-Chem model is archived on UCAR data repository (http://www2.mmm.ucar.edu/wrf/users/download). The LPDM model can be acquired from the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model (http://www.ready.noaa.gov). The ensemble empirical mode decomposition (EEMD) analysis code that is embedded in NCAR Command Language version 6.40 is available at https://www.earthsystemgrid.org/dataset/ncl.640.html.
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This work was funded by the Ministry of Science and Technology of the People’s Republic of China (2016YFC0200500), the National Natural Science Foundation of China (91544231, 41725020, 41922038 and 91744311), the National Research Program for Key Issues in Air Pollution Control in China (DQGG0107-03) and the Jiangsu Provincial Fund on PM2.5 and O3 pollution mitigation. We thank Q. Zhang and K. He at Tsinghua University for helpful suggestions and colleagues at Nanjing University and Environmental Monitoring Centers at Shijiazhuang, Zhengzhou, Tianjin and other cities in eastern and northern China for their contributions on the field measurements.
The authors declare no competing interests.
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Extended Data Fig. 1 Time series and transport patterns of PM2.5 in eastern China during the cross-year haze event.
a, PM2.5 concentrations measured from Shijiazhuang, Zhengzhou, Jinan, Xuzhou, Nanjing and Shanghai in late December 2017 and early January 2018. Shaded squares mark the main periods of haze pollution for each city. b, Time series for low-frequency and relative synoptic variations (2-7 days) of PM2.5 in Nanjing for 2013-2018. c-d, Average PM2.5 concentrations and wind flows simulated by WRF-Chem for 28-29 December 2017 and 30 December 2017 – 1 January 2018, respectively.
72-hour retroplume (“footprint” residence time) showing transport pathways at Nanjing, Zhengzhou and Tianjin during this cross-region haze pollution. a, Nanjing (NJ) on 27 December; b, Zhengzhou (ZZ) on 28 December; c, Tianjin (TJ) on 29 December; d, Nanjing (NJ) on 31 December, 2017.
Extended Data Fig. 3 Evidence of intense aerosol-PBL feedback by regional transport between NCP and YRD.
a, Temperature difference between the 24-hour forecast by Global Forecast System (GFS) and radiosonde observations at 20:00 LT on 28 December, 2017. Note that circles mark the temperature disparities near the surface and crosses display those at 850 hPa. b, Spatial patterns of simulated BC concentration and wind at the same time with a. c, Cross section of vertical distribution of BC along the blue line in b. Grey lines denote the relative contribution from the YRD region. d, Cross section of simulated temperature difference due to aerosols’ radiative effect (filled contour) and the relative contribution from YRD (isolines).
a, Temporal variation of Lidar measured normalized aerosol backscatter and modeled PM2.5 profiles at Shijiazhuang during 28-30 December 2017. Note that the dashed line marks the contribution from YRD emissions according to parallel simulations, and shadowed contour lines represent the temperature responses to ARI. b, Time series of difference between measured and simulated 2-meter air temperature without ARI, and time series of observed and simulated PM2.5 concentrations with/without considering aerosols’ radiative effect. c, Cross section of simulated difference in air temperature (filled contour) and relative humidity (isolines) due to ARI at 14:00 LT on 29 December, which was derived from the two simulation scenarios with and without ARI. d, Cross section of simulated difference in PM2.5 concentration (filled contour) and secondary sulfate formation rate due to ARI.
Extended Data Fig. 5 1-Dimensional modeling of cumulative impact of aerosol-PBL feedback along the transport pathway of pollution.
a-c, Diurnal variation of vertical air temperature difference (contour) due to ARI at Nanjing on 26 December, Jinan on 27 December, and Beijing on 28 December, simulated by WRF-Chem SCM. Note that the solid and dashed lines mark the PBL height with/without considering ARI, respectively.
a, Vertical distribution of the source appointment of PM2.5, BC and SN (sulfate and nitrate) for YRD at different altitudes on 31 December derived from WRF-Chem simulations. The sizes of the pies denote the concentrations of PM2.5, BC and SN, with numbers in a unit of µg m-3 under the pies for reference. Red, yellow, blue and grey areas display contributions from YRD, Shandong (SD), NCP and other regions. b, WRF-Chem simulated PM2.5 source appointment at the altitude of 700 m (upper panel) and at the ground surface (lower panel) of the YRD region.
Extended Data Fig. 7 A conceptual scheme for the amplified transboundary transport of fine particles through aerosol-PBL feedback between YRD and NCP in China.
The upper panel shows how aerosol-PBL feedback was enhanced with depressed PBL, dimmed and humidified lower PBL when the warm and humid air transport from the YRD to NCP in the upper PBL. The lower panel shows how intensified aged secondary pollution in the NCP was transported to the YRD by cold fronts.
Extended Data Fig. 8 Evolution of transboundary transport of PM2.5 for 18 pollution cases during 2013-2017.
WRF-Chem simulation of zonal averaged wind vector and PM2.5 concentrations over 115-120 °E during 18 transboundary haze pollution cases. The time series of hourly PM2.5 concentrations in NCP and YRD region in each case are presented in Supplementary Fig. 2. Note that the beginning date of each event is labelled above each subplot.
a, averaged spatial distribution of 2-meter temperature responses to aerosol-PBL interaction and mean wind vectors during Stage II of 18 cross-regional pollution events identified in Supplementary Fig. 2. b, Statistics of vertical profile of air temperature difference (Tdiff) and RH difference (RHdiff) between radiosonde observations and GFS 24-hour forecast at Beijing when haze pollution peaked in NCP. Lines and shaded areas mark the average and standard deviations, respectively.
Extended Data Fig. 10 Regional-scale PM2.5 mitigation due to in-advance and cross-regional coordinated emission control.
Zonal averaged PM2.5 reduction over 115-120 °E due to 2-day 50% emission cut in YRD before Stage I for 6 typical cross-regional cases during 2013-2017. Note that the beginning date of each event is labelled above each subplot.
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Huang, X., Ding, A., Wang, Z. et al. Amplified transboundary transport of haze by aerosol–boundary layer interaction in China. Nat. Geosci. 13, 428–434 (2020). https://doi.org/10.1038/s41561-020-0583-4
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