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Weakening aerosol direct radiative effects mitigate climate penalty on Chinese air quality

Nature Climate Change volume 10, pages 845–850 (2020)Cite this article

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Abstract

Future climate change may worsen air quality in many regions. However, evaluations of this ‘climate penalty’ on air quality have typically not assessed the radiative effects of changes in short-lived aerosols. Additionally, China’s clean air goals will decrease pollutant emissions and aerosol loadings, with concomitant weakening of aerosol feedbacks. Here we assess how such weakened aerosol direct effects alter the estimates of air pollution and premature mortality in China attributable to mid-century climate change under Representative Concentration Pathway 4.5. We found that weakening aerosol direct effects cause boundary layer changes that facilitate diffusion. This reduces air-pollution exposure (~4% in fine particulate matter) and deaths (13,800 people per year), which largely offset the additional deaths caused by greenhouse gas-dominated warming. These results highlight the benefits of reduced pollutant emissions through weakening aerosol direct effects and underline the potential of pollution control measures to mitigate climate penalties locked in by greenhouse gas emissions.

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Fig. 1: Comparison of regional climate change caused by air-pollutant-emission reduction and global-scale change.
Fig. 2: Population-weighted average changes in regional climate and air quality over China.
Fig. 3: Comparisons of changes in regional air quality attributable to two sources of climate change.
Fig. 4: Comparisons of changes in air-pollution and heat-related mortality attributable to two sources of climate change.
Fig. 5: Enhancement of surface PM2.5 concentrations due to ADEs in 2010 as a function of ambient PM2.5 concentrations.

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Data availability

The RCP4.5 emissions in 2010 and 2050 are available from http://tntcat.iiasa.ac.at:8787/RcpDb/dsd?Action=htmlpage&. The demographic and epidemiological data for mortality calculation is provided in Supplementary Dataset. Source data for the main figures are available at https://github.com/ChaopengHong/Hong_et_al_2020_Aerosol. The other data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

The two-way coupled WRF-CMAQ model is open source and publicly available. The WRF version 3.4 codes can be downloaded at http://www2.mmm.ucar.edu/wrf/users/download/get_source.html. The CMAQ version 5.0.2 codes and the WRF-CMAQ two-way package can be downloaded at https://www.cmascenter.org/download.cfm. The build instructions and run instructions for the two-way coupled WRF-CMAQ model are available at https://www.airqualitymodeling.org/index.php/CMAQv5.0.2_Two-way_model_release_notes. The code to generate the main figures is available at https://github.com/ChaopengHong/Hong_et_al_2020_Aerosol. Maps used in the spatial plots were created using the NCAR Command Language (v.6.4.0; https://doi.org/10.5065/D6WD3XH5). Maps of China were updated with a database provided by https://github.com/huangynj/NCL-Chinamap.

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Acknowledgements

This work was sponsored by the National Natural Science Foundation of China (41625020 and 41921005). The work by Y.Z’s group at North Carolina State University (NCSU) (now at Northeastern University) was supported by the National Science Foundation EaSM program (AGS-1049200) and the US Department of Energy Office of Science Biological and Environmental Research (DE-SC0006695). This work was funded in part by the US National Science Foundation (INFEWS grant EAR 1639318). The CESM simulations were conducted by T. Glotfelty at NCSU. We thank K. Yahya and T. Glotfelty at NCSU for their help during the generation of the initial and boundary conditions from CESM for WRF-CMAQ simulations. We thank R. Leung at PNNL for providing the script to generate meteorological initial and boundary conditions from CESM to WRF. The authors acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation and Information Systems Laboratory.

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Authors and Affiliations

  1. Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China

    Chaopeng Hong, Qiang Zhang, Steven J. Davis, Xin Zhang, Dan Tong, Dabo Guan, Zhu Liu & Kebin He

  2. Department of Earth System Science, University of California, Irvine, Irvine, CA, USA

    Chaopeng Hong & Steven J. Davis

  3. Department of Civil and Environmental Engineering, Northeastern University, Boston, MA, USA

    Yang Zhang

  4. Department of Marine, Earth and Atmospheric Sciences, North Carolina State University, Raleigh, NC, USA

    Yang Zhang

  5. Department of Civil and Environmental Engineering, University of California, Irvine, Irvine, CA, USA

    Steven J. Davis

  6. State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China

    Kebin He

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Contributions

Q.Z., Y.Z. and C.H. designed the research. C.H. performed the research. Y.Z. contributed CESM simulation results and new analytical approaches. C.H., Q.Z. and S.J.D. interpreted the data. C.H., Q.Z., S.J.D. and Y.Z. wrote the paper with input from all the co-authors.

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Correspondence to Qiang Zhang or Yang Zhang.

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Peer review information Nature Climate Change thanks Shuxiao Wang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Projected changes in regional air quality under RCP4.5.

Projected changes in annual mean PM2.5 concentrations a,c,e, and ozone season (April to September) average of daily 1-hour maximum ozone b,d,f, over East Asia from 2010 to 2050 under RCP4.5.

Extended Data Fig. 2 Changes in anthropogenic air pollutant emissions under RCP4.5.

Changes in anthropogenic emissions of SO2 a, NOx b, primary PM2.5 c, and VOCs d, over East Asia from 2010 to 2050 under RCP4.5.

Extended Data Fig. 3 Comparison of regional climate change caused by weakening ADEs and air pollutant emission reduction.

Projected annual mean changes in downward shortwave radiation at the surface a,b, near-surface air temperature at 2-m c,d, and planetary boundary layer height e,f, over East Asia, caused by changing/weakening ADEs (a,c,e, ∆WeakeningADE, from the feedback and no-feedback simulations) and regional air pollutant emission reduction (b,d,f, ∆RegEmisChg) from 2010 to 2050 under RCP4.5.

Extended Data Fig. 4 Distribution of surface PM2.5 concentration changes across grid cells grouped by populations.

Projected changes in annual mean PM2.5 concentrations over China due to weakening ADEs (a, ∆WeakeningADE) and global-scale climate change (b, ∆GlobalClimChg) from 2010 to 2050 under RCP4.5. Box plot elements: center line, median; box limits, upper (75th) and lower (25th) percentiles; whiskers, 1.5 times the interquartile range.

Supplementary information

Supplementary Information

Supplementary notes, references and Tables 1–3.

Supplementary Data

Supplementary Data 1 and 2.

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Hong, C., Zhang, Q., Zhang, Y. et al. Weakening aerosol direct radiative effects mitigate climate penalty on Chinese air quality. Nat. Clim. Chang. 10, 845–850 (2020). https://doi.org/10.1038/s41558-020-0840-y

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