Abstract
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.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
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.
Code availability
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.
References
Huang, R. J. et al. High secondary aerosol contribution to particulate pollution during haze events in China. Nature 514, 218–222 (2014).
Ding, A. J. et al. Enhanced haze pollution by black carbon in megacities in China. Geophys. Res. Lett. 43, 2873–2879 (2016).
Guo, S. et al. Elucidating severe urban haze formation in China. Proc. Natl Acad. Sci. USA 111, 17373–17378 (2014).
Li, H. et al. Rapid transition in winter aerosol composition in Beijing from 2014 to 2017: response to clean air actions. Atmos. Chem. Phys. 19, 11485–11499 (2019).
Ding, A. et al. Significant reduction of PM2.5 in eastern China due to regional-scale emission control: evidences from the SORPES station, 2011–2018. Atmos. Chem. Phys. 19, 11791–11801 (2019).
Gao, M. et al. China’s Clean Air Action has suppressed unfavorable influences of climate on wintertime PM2.5 concentrations in Beijing since 2002. Atmos. Chem. Phys. 20, 1497–1505 (2020).
Wang, J. D. et al. Particulate matter pollution over China and the effects of control policies. Sci. Total Environ. 584, 426–447 (2017).
Sheehan, P., Cheng, E. J., English, A. & Sun, F. H. China’s response to the air pollution shock. Nat. Clim. Change 4, 306–309 (2014).
Huang, X., Wang, Z. L. & Ding, A. J. Impact of aerosol-PBL interaction on haze pollution: multiyear observational evidences in North China. Geophys. Res. Lett. 45, 8596–8603 (2018).
Zhang, R. Y. et al. Formation of urban fine particulate matter. Chem. Rev. 115, 3803–3855 (2015).
Zhang, Y. et al. Impact of synoptic weather patterns and inter-decadal climate variability on air quality in the North China Plain during 1980–2013. Atmos. Environ. 124, 119–128 (2016).
Cai, W. J., Li, K., Liao, H., Wang, H. J. & Wu, L. X. Weather conditions conducive to Beijing severe haze more frequent under climate change. Nat. Clim. Change 7, 257–262 (2017).
Callahan, C. W., Schnell, J. L. & Horton, D. E. Multi-index attribution of extreme winter air quality in Beijing, China. J. Geophys. Res. Atmos. 124, 4567–4583 (2019).
Zhang, G. et al. Seesaw haze pollution in North China modulated by the sub-seasonal variability of atmospheric circulation. Atmos. Chem. Phys. 19, 565–576 (2019).
Zhang, Q. et al. Transboundary health impacts of transported global air pollution and international trade. Nature 543, 705–709 (2017).
Li, K., Liao, H., Cai, W. J. & Yang, Y. Attribution of anthropogenic influence on atmospheric patterns conducive to recent most severe haze over Eastern China. Geophys. Res. Lett. 45, 2072–2081 (2018).
Ding, A. J. et al. Ozone and fine particle in the western Yangtze River Delta: an overview of 1 yr data at the SORPES station. Atmos. Chem. Phys. 13, 5813–5830 (2013).
Cheng, Y. F. et al. Reactive nitrogen chemistry in aerosol water as a source of sulfate during haze events in China. Sci. Adv. 2, e1601530 (2016).
Wang, G. H. et al. Persistent sulfate formation from London fog to Chinese haze. Proc. Natl Acad. Sci. USA 113, 13630–13635 (2016).
Xie, Y. N. et al. Enhanced sulfate formation by nitrogen dioxide: implications from in situ observations at the SORPES station. J. Geophys. Res. Atmos. 120, 12679–12694 (2015).
Zheng, G. J. et al. Exploring the severe winter haze in Beijing: the impact of synoptic weather, regional transport and heterogeneous reactions. Atmos. Chem. Phys. 15, 2969–2983 (2015).
Sun, Y. L. et al. Investigation of the sources and evolution processes of severe haze pollution in Beijing in January 2013. J. Geophys. Res. Atmos. 119, 4380–4398 (2014).
Moch, J. M. et al. Contribution of hydroxymethane sulfonate to ambient particulate matter: a potential explanation for high particulate sulfur during severe winter haze in Beijing. Geophys. Res. Lett. 45, 11969–11979 (2018).
Ding, A. J. et al. Intense atmospheric pollution modifies weather: a case of mixed biomass burning with fossil fuel combustion pollution in eastern China. Atmos. Chem. Phys. 13, 10545–10554 (2013).
Dong, Z. P. et al. Opposite long-term trends in aerosols between low and high altitudes: a testimony to the aerosol–PBL feedback. Atmos. Chem. Phys. 17, 7997–8009 (2017).
Li, Z. Q. et al. Aerosol and boundary-layer interactions and impact on air quality. Natl Sci. Rev. 4, 810–833 (2017).
Petäjä, T. et al. Enhanced air pollution via aerosol–boundary layer feedback in China. Sci. Rep. 6, 18998 (2016).
Wang, Z., Huang, X. & Ding, A. Dome effect of black carbon and its key influencing factors: a one-dimensional modelling study. Atmos. Chem. Phys. 18, 2821–2834 (2018).
Gao, M. et al. Modeling study of the 2010 regional haze event in the North China Plain. Atmos. Chem. Phys. 16, 1673–1691 (2016).
Yang, Y. Q. et al. PLAM—a meteorological pollution index for air quality and its applications in fog–haze forecasts in North China. Atmos. Chem. Phys. 16, 1353–1364 (2016).
Lou, S. J. et al. Black carbon amplifies haze over the North China Plain by weakening the East Asian winter monsoon. Geophys. Res. Lett. 46, 452–460 (2019).
Ramanathan, V. et al. Warming trends in Asia amplified by brown cloud solar absorption. Nature 448, 575–578 (2007).
Jacobson, M. Z. Strong radiative heating due to the mixing state of black carbon in atmospheric aerosols. Nature 409, 695–697 (2001).
Cappa, C. D. et al. Radiative absorption enhancements due to the mixing state of atmospheric black carbon. Science 337, 1078–1081 (2012).
Bond, T. C. et al. Bounding the role of black carbon in the climate system: a scientific assessment. J. Geophys. Res. Atmos. 118, 5380–5552 (2013).
Nair, V. S., Babu, S. S., Manoj, M. R., Moorthy, K. K. & Chin, M. Direct radiative effects of aerosols over South Asia from observations and modeling. Clim. Dynam. 49, 1411–1428 (2017).
Wilcox, E. M. et al. Black carbon solar absorption suppresses turbulence in the atmospheric boundary layer. Proc. Natl Acad. Sci. USA 113, 11794–11799 (2016).
Bharali, C., Nair, V. S., Chutia, L. & Babu, S. S. Modeling of the effects of wintertime aerosols on boundary layer properties over the Indo Gangetic Plain. J. Geophys. Res. Atmos. 124, 4141–4157 (2019).
Harris, E. et al. Enhanced role of transition metal ion catalysis during in-cloud oxidation of SO2. Science 340, 727–730 (2013).
Wang, C. Y., Li, P. G. & Liu, Y. Investigation of water-energy-emission nexus of air pollution control of the coal-fired power industry: a case study of Beijing-Tianjin-Hebei region, China. Energy Policy 115, 291–301 (2018).
Huang, N. E. et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc. R. Soc. Lond. A 454, 903–995 (1998).
Wu, Z. & Huang, N. E. Ensemble empirical mode decomposition: a noise-assisted data analysis method. Adv. Adapt. Data Anal. 1, 1–41 (2009).
Durre, I., Vose, R. S. & Wuertz, D. B. Overview of the Integrated Global Radiosonde Archive. J. Clim. 19, 53–68 (2006).
Stein, A. F. et al. NAAA’s HYSPLIT atmospheric transport and dispersion modeling system. Bull. Am. Meteorol. Soc. 96, 2059–2077 (2015).
Ding, A. J., Wang, T. & Fu, C. B. Transport characteristics and origins of carbon monoxide and ozone in Hong Kong, South China. J. Geophys. Res. Atmos. 118, 9475–9488 (2013).
Grell, G. A. et al. Fully coupled “online” chemistry within the WRF model. Atmos. Environ. 39, 6957–6975 (2005).
Huang, X. et al. Direct radiative effect by multicomponent aerosol over China. J. Clim. 28, 3472–3495 (2015).
Huang, X. et al. Pathways of sulfate enhancement by natural and anthropogenic mineral aerosols in China. J. Geophys. Res. Atmos. 119, 14165–14179 (2014).
Li, M. et al. MIX: a mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP. Atmos. Chem. Phys. 17, 935–963 (2017).
Huang, X. et al. Effects of aerosol–radiation interaction on precipitation during biomass-burning season in East China. Atmos. Chem. Phys. 16, 1–37 (2016).
Acknowledgements
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.
Author information
Authors and Affiliations
Contributions
A.D. and X.H. conceived the study and led the overall scientific questions. X.H., A.D., Z.W. and K.D. made the data analysis and modelling studies. J.G. and F.C. provided the measurement data for cities in northern China. X.H. and A.D. wrote the manuscript with contributions from all authors.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Peer review information Primary Handling Editors: Xujia Jiang; Heike Langenberg; Rebecca Neely.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
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.
Extended Data Fig. 2 Regional transport characteristics during the cross-year haze event.
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).
Extended Data Fig. 4 Vertical structure and evolution of aerosol-PBL feedback in North China.
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.
Extended Data Fig. 6 Enhanced haze pollution in YRD due to cross-regional transport.
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.
Extended Data Fig. 9 Air temperature response due to aerosol-PBL interaction.
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.
Supplementary information
Supplementary Information
Supplementary Figs. 1–8.
Rights and permissions
About this article
Cite this article
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
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41561-020-0583-4
This article is cited by
-
Vertical distribution characteristics and potential sources of atmospheric pollutants in the North China Plain basing on the MAX-DOAS measurement
Environmental Sciences Europe (2024)
-
Amplified positive effects on air quality, health, and renewable energy under China’s carbon neutral target
Nature Geoscience (2024)
-
Local surface cooling from afforestation amplified by lower aerosol pollution
Nature Geoscience (2023)
-
Health burden evaluation of industrial parks caused by PM2.5 pollution at city scale
Environmental Science and Pollution Research (2023)
-
Recent Progress in Atmospheric Chemistry Research in China: Establishing a Theoretical Framework for the “Air Pollution Complex”
Advances in Atmospheric Sciences (2023)