The recovery of the stratospheric ozone layer relies on the continued decline in the atmospheric concentrations of ozone-depleting gases such as chlorofluorocarbons1. The atmospheric concentration of trichlorofluoromethane (CFC-11), the second-most abundant chlorofluorocarbon, has declined substantially since the mid-1990s2. A recently reported slowdown in the decline of the atmospheric concentration of CFC-11 after 2012, however, suggests that global emissions have increased3,4. A concurrent increase in CFC-11 emissions from eastern Asia contributes to the global emission increase, but the location and magnitude of this regional source are unknown3. Here, using high-frequency atmospheric observations from Gosan, South Korea, and Hateruma, Japan, together with global monitoring data and atmospheric chemical transport model simulations, we investigate regional CFC-11 emissions from eastern Asia. We show that emissions from eastern mainland China are 7.0 ± 3.0 (±1 standard deviation) gigagrams per year higher in 2014–2017 than in 2008–2012, and that the increase in emissions arises primarily around the northeastern provinces of Shandong and Hebei. This increase accounts for a substantial fraction (at least 40 to 60 per cent) of the global rise in CFC-11 emissions. We find no evidence for a significant increase in CFC-11 emissions from any other eastern Asian countries or other regions of the world where there are available data for the detection of regional emissions. The attribution of any remaining fraction of the global CFC-11 emission rise to other regions is limited by the sparsity of long-term measurements of sufficient frequency near potentially emissive regions. Several considerations suggest that the increase in CFC-11 emissions from eastern mainland China is likely to be the result of new production and use, which is inconsistent with the Montreal Protocol agreement to phase out global chlorofluorocarbon production by 2010.
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Data from remote AGAGE stations and Gosan data are available from the AGAGE website (agage.mit.edu). Hateruma data are available at World Data Centre for Greenhouse Gases (https://gaw.kishou.go.jp/). NOAA data are taken as the ‘combined set’ data record (a best-estimate record based on flask samples and in situ measurements), available from the NOAA Global Monitoring Division data server (https://www.esrl.noaa.gov/gmd/dv/ftpdata.html, or more specifically ftp://ftp.cmdl.noaa.gov/hats/cfcs/cfc11/combined/).
The inversion models of NAME-HB, NAME-InTEM, FLEXPART-MIT and FLEXPART-Empa are used to determine the regional CFC-11 emissions. Enquiries about the model codes should be directed to M.R., A.J.M., S.R. and R.G.P. Licences to use NAME and InTEM are available for research purposes via a request to the UK Met Office or on request from A.J.M. and A.L.R. The code for the NAME-based hierarchical Bayesian inversion (NAME-HB) is available on request from M.R. and L.M.W. The code of the dispersion model FLEXPART is available from www.flexpart.eu. The code for the FLEXPART-based Bayesian inversion (FLEXPART-MIT) is available on request from X.F. The inversion code used by Empa is available from https://doi.org/10.5281/zenodo.1194642 or on request from S.H.
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We are indebted to the site operators who oversee the day-to-day running of the AGAGE, NIES and NOAA stations. We particularly thank the NASA Upper Atmosphere Research Program for its continuing support of AGAGE, including providing modelling, field station and instrumentation support though grant NNX16AC98G to MIT, and supporting the overall experimental programme through grants NNX16AC96G and NNX16AC97G to SIO. Observations at Cape Grim are supported largely by the Australian Bureau of Meteorology, CSIRO, the Australian Department of the Environment and Energy (DoEE) and Refrigerant Reclaim Australia (RRA). Mace Head, Ireland, is supported by the Department for Business, Energy & Industrial Strategy (BEIS, UK, formerly the Department of Energy and Climate Change (DECC)) contract 1028/06/2015 to the University of Bristol and the UK Meteorological Office. Ragged Point, Barbados is supported by the National Oceanic and Atmospheric Administration (NOAA, USA), contract RA-133-R15-CN-0008 to the University of Bristol. M.R., L.M.W., M.F.L. and R.L.T. were supported by Natural Environment Research Council grants NE/I021365/1, NE/I027282/1, NE/M014851/1, NE/L013088/1 and NE/N016548/1. A.L.G. is supported by NERC Independent Research Fellowship NE/L010992/1. S.P., T.L., S.L., M.-K.P. and K.-R.K. were supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (no. NRF-2016R1A2B2010663). Observations at Hateruma were partly supported by the Ministry of the Environment of Japan. S.A.M., B.D.H. and G.S.D. are indebted to C. Siso, D. Mondeel, J. D. Nance, F. Moore, J.W. Elkins, B. Vasel, C. Schultz, R. Schnell and J. H. Butler for discussions and assistance with the NOAA measurements considered here, which were made possible in part with support from the NOAA Climate Program Office’s AC4 program.
Nature thanks Andreas Stohl, Guus Velders and the other anonymous reviewer(s) for their contribution to the peer review of this work.
The authors declare no competing interests.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
Extended Data Fig. 1 CFC-11 mole fractions measured at different sites in the AGAGE network and at affiliated sites.
Box plots indicate the 25th and 75th of the individual measurement data (approximately 2-hourly), with the median shown as a horizontal line within each box. The whiskers show the 10th and 90th percentiles. The lower percentiles are typically representative of baseline (‘unpolluted’) mole fractions, and the difference between the lower and higher percentiles indicates the magnitude of above-baseline events due to the interception of air masses containing recently emitted CFC-11.
Extended Data Fig. 2 NAME-derived mean sensitivities of atmospheric mole fractions at Gosan and Hateruma to potential emission.
This mean sensitivity map was derived for sampling events at these two sites during 2008 to 2017. Black triangle and circle indicate the Gosan and Hateruma stations, respectively. Thin grey lines show the boundaries of the provinces within the region we denote eastern mainland China. This region contains the provinces Anhui, Beijing, Hebei, Jiangsu, Liaoning, Shandong, Shanghai, Tianjin and Zhejiang. The west of the grey line transecting Japan, containing the regions Chūgoku, Kansai, Kyūshū & Okinawa, and Shikoku, is the region we denote western Japan.
Left, a comparison of the simulated CFC-11 mole fractions from the four different inversion analyses and those that were measured at Gosan and Hateruma. Right, residuals between the simulated and observed mole fractions (data minus model). Shading denotes 1 s.d. of the model-data mismatch uncertainties assumed in the inversions. Simulated mole fractions are derived from the a posteriori emissions. For the NAME-InTEM, FLEXPART-EMPA, NAME-HB and FLEXPART-MIT inversions, 2-hourly, 3-hourly, 24-hourly and 24-hourly averaging was applied to the model and data, respectively.
Extended Data Fig. 4 Derived emissions from different inverse models considering subsets of measurement data.
Shown are emission estimates derived using the Gosan CFC-11 measurements (green dashed line), the Hateruma CFC-11 measurements (red dotted line), or both records in the inversion analysis (pink solid line). a–d, Estimates shown use the NAME-HB (a), NAME-InTEM (b), FLEXPART-MIT (c) and FLEXPART-Empa (d) inversion techniques.
Extended Data Fig. 5 Derived emissions for eastern mainland China for different a priori emission magnitudes and different spatial distributions.
The inversions are as described in Methods (‘a priori’, pink solid line), with a priori emissions twice as high (‘2× a priori’, green dashed line), or the same magnitude but distributed in space according to population density (‘population weighted’, red dotted line). a–d, Estimates shown use the NAME-HB (a), NAME-InTEM (b), FLEXPART-MIT (c) and FLEXPART-Empa (d) inversion methods.
a–c, Emission estimates are shown for western Japan (a), South Korea (b) and North Korea (c) using the NAME-HB (yellow lines), NAME-InTEM (blue lines), FLEXPART-MIT (pink lines) and FLEXPART-Empa (grey lines) inverse frameworks described in the Methods. See Extended Data Fig. 2 for the definition of the western Japan region. All lines and symbols are the a posteriori mean, and shading denotes s.d. uncertainty.
Extended Data Fig. 7 Maps of mean CFC-11 emission fluxes from different models and time periods, and the differences between time periods.
a–i, CFC-11 emissions for NAME-InTEM (a–c), FLEXPART-MIT (d–f) and FLEXPART-Empa (g–i) using the inversion framework described in the Methods, and similar to Fig. 3. a, d, g, Average spatial emissions are shown for the period 2008–2012. b, e, h, Average spatial emissions are shown for the period 2014–2017. c, f, i, The difference in emissions from the 2008–2012 period to the 2013–2017 period, using NAME-InTEM, FLEXPART-MIT and FLEXPART-Empa, respectively.
The implied release fraction of banks of CFC-11 from the eastern mainland China region defined in Extended Data Fig. 2, assuming that there is no non-reported production after 2008. This calculation assumes that the 2008 emissions estimates are 5% of the bank size (estimated to be towards the upper limit of expected global bank fractional release rate3). The coloured lines show the implied bank release fraction for each year after 2008, required to sustain the mean a posteriori emissions from the NAME-HB (yellow), NAME-InTEM (blue), FLEXPART-MIT (pink) and FLEXPART-Empa (grey) inversions. The black line shows the bank release fraction from a bottom-up study for the whole of China7.
Measured mole fractions of CFC-12 at Gosan, South Korea, from 2008 to 2017. Box plots are as defined in Extended Data Fig. 1.
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Rigby, M., Park, S., Saito, T. et al. Increase in CFC-11 emissions from eastern China based on atmospheric observations. Nature 569, 546–550 (2019). https://doi.org/10.1038/s41586-019-1193-4
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