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Assessing progress towards sustainable development over space and time

An Author Correction to this article was published on 14 April 2021

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Abstract

To address global challenges1,2,3,4, 193 countries have committed to the 17 United Nations Sustainable Development Goals (SDGs)5. Quantifying progress towards achieving the SDGs is essential to track global efforts towards sustainable development and guide policy development and implementation. However, systematic methods for assessing spatio-temporal progress towards achieving the SDGs are lacking. Here we develop and test systematic methods to quantify progress towards the 17 SDGs at national and subnational levels in China. Our analyses indicate that China’s SDG Index score (an aggregate score representing the overall performance towards achieving all 17 SDGs) increased at the national level from 2000 to 2015. Every province also increased its SDG Index score over this period. There were large spatio-temporal variations across regions. For example, eastern China had a higher SDG Index score than western China in the 2000s, and southern China had a higher SDG Index score than northern China in 2015. At the national level, the scores of 13 of the 17 SDGs improved over time, but the scores of four SDGs declined. This study suggests the need to track the spatio-temporal dynamics of progress towards SDGs at the global level and in other nations.

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Fig. 1: Change in China’s SDG Index score and individual SDG scores.
Fig. 2: Spatial pattern of SDG Index scores in 2000, 2005, 2010 and 2015 for 31 Chinese provinces.
Fig. 3: Comparison of average SDG Index scores for different groups of provinces in China.
Fig. 4: Differences in SDG scores or SDG Index scores between 2015 and 2000.

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Data availability

All data are available from the corresponding authors upon reasonable request. Data that support the findings of this study are available within the paper and its Supplementary Information.

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References

  1. Liu, J. et al. Systems integration for global sustainability. Science 347, 1258832 (2015).

    Article  Google Scholar 

  2. Mekonnen, M. M. & Hoekstra, A. Y. Four billion people facing severe water scarcity. Sci. Adv. 2, e1500323 (2016).

    Article  ADS  Google Scholar 

  3. International Energy Agency. World Energy Outlook 2015 (IEA, 2015).

  4. Larivière, V., Ni, C., Gingras, Y., Cronin, B. & Sugimoto, C. R. Bibliometrics: global gender disparities in science. Nature 504, 211–213 (2013).

    Article  Google Scholar 

  5. United Nations. Sustainable Development Goals: 17 Goals to Transform Our World http://www.un.org/sustainabledevelopment/sustainable-development-goals/ (UN, 2015).

  6. Schmidt-Traub, G., Kroll, C., Teksoz, K., Durand-Delacre, D. & Sachs, J. D. National baselines for the Sustainable Development Goals assessed in the SDG Index and Dashboards. Nat. Geosci. 10, 547–555 (2017).

    Article  ADS  CAS  Google Scholar 

  7. Rodrik, D. The past, present, and future of economic growth. Challenge 57, 5–39 (2014).

    Article  Google Scholar 

  8. Xie, Y. & Zhou, X. Income inequality in today’s China. Proc. Natl Acad. Sci. USA 111, 6928–6933 (2014).

    Article  ADS  CAS  Google Scholar 

  9. Liu, J. G. et al. China’s environment on a metacoupled planet. Annu. Rev. Environ. Res. 43, 1–34 (2018).

    Article  CAS  Google Scholar 

  10. Liu, J. & Diamond, J. China’s environment in a globalizing world. Nature 435, 1179–1186 (2005).

    Article  ADS  CAS  Google Scholar 

  11. Ouyang, Z. et al. Improvements in ecosystem services from investments in natural capital. Science 352, 1455–1459 (2016).

    Article  ADS  CAS  Google Scholar 

  12. Bryan, B. A. et al. China’s response to a national land-system sustainability emergency. Nature 559, 193–204 (2018).

    Article  ADS  CAS  Google Scholar 

  13. Ortuño-Padilla, A., Espinosa-Flor, A. & Cerdán-Aznar, L. Development strategies at station areas in Southwestern China: the case of Mianyang city. Land Use Policy 68, 660–670 (2017).

    Article  Google Scholar 

  14. Sachs, J., Schmidt-Traub, G., Kroll, C., Lafortune, G. & Fuller, G. SDG Index and Dashboards Report 2018 https://www.sdgindex.org/reports/sdg-index-and-dashboards-2018 (Pica, 2018).

  15. Lu, Z. & Deng, X. Regional policy and regional development: a case study of China’s Western Development Strategy. Ann. Univ. Apulensis Ser. Oeconomica 15, 250–264 (2013).

    Google Scholar 

  16. Gai, K. Study on The Coordination between Ecological Environment and Economic Development in West China. [in Chinese] https://www.sdgindex.org/reports/sdg-index-and-dashboards-2018, PhD thesis, Southwestern University of Finance and Economics (2008).

  17. Yuan, N. Study on the Sustainable Development of West China Economy. [in Chinese] https://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CMFD&dbname=CMFD2008&filename=2008028325.nh&uid=WEEvREcwSlJHSldRa1FhdXNXaEhoOHRuWm1vU2REWU45b2ozL013SWRJTT0=$, Master’s thesis, Sichuan University (2006).

  18. Jayachandran, S. The roots of gender inequality in developing countries. Ann. Rev. Econ. 7, 63 (2015).

    Article  Google Scholar 

  19. Chen, Z. Launch of the health-care reform plan in China. Lancet 373, 1322–1324 (2009).

    Article  Google Scholar 

  20. Mok, K. H. & Wu, A. M. Higher education, changing labour market and social mobility in the era of massification in China. J. Educ. Work 29, 77–97 (2016).

    Article  Google Scholar 

  21. Wilkinson, R. G. & Pickett, K. E. Income inequality and social dysfunction. Annu. Rev. Sociol. 35, 493–511 (2009).

    Article  Google Scholar 

  22. Liu, J. An integrated framework for achieving Sustainable Development Goals around the world. Ecol. Econ. Soc. 1, 11–17 (2018).

    Article  Google Scholar 

  23. Nerini, F. F. et al. Mapping synergies and trade-offs between energy and the Sustainable Development Goals. Nat. Energy 3, 10–15 (2018).

    Article  ADS  Google Scholar 

  24. State Council of China. China Implements the 2030 Agenda for Sustainable Development Country Programme [in Chinese] https://www.fmprc.gov.cn/web/zyxw/t1405173.shtml (SSC, 2016).

  25. United Nations Statistics Division. SDG Indicators https://unstats.un.org/sdgs/indicators/indicators-list (UNSD, 2017).

  26. Schmidt-Traub, G., De la Mothe Karoubi, E. & Espey, J. Indicators and a Monitoring Framework for the Sustainable Development Goals: Launching a Data Revolution for the SDGs https://ec.europa.eu/knowledge4policy/publication/indicators-monitoring-framework-sustainable-development-goals-launching-data-revolution_en (Sustainable Development Solutions Network, 2015).

  27. Golding, N. et al. Mapping under-5 and neonatal mortality in Africa, 2000-15: a baseline analysis for the Sustainable Development Goals. Lancet 390, 2171–2182 (2017).

    Article  Google Scholar 

  28. Alia, D. Y. Progress toward the sustainable development goal on poverty: assessing the effect of income growth on the exit time from poverty in Benin. Sustain. Dev. 25, 495–503 (2017).

    Article  Google Scholar 

  29. National Bureau of Statistics of the People’s Republic of China. China Statistical Yearbook [in Chinese] http://www.stats.gov.cn/tjsj/ndsj/ (China Statistics Press, 2001–2016).

  30. Ministry of Finance of the People’s Republic of China. Finance Yearbook of China [in Chinese] http://tongji.cnki.net/kns55/navi/HomePage.aspx?id=N2014020005&name=YZGCZ (China Financial & Economic Publishing House, 2001–2016).

  31. National Bureau of Statistics & State Environmental Protection Administration of the People’s Republic of China. China Statistical Yearbook on Environment [in Chinese] http://www.shujuku.org/china-environmental-statistics-yearbook.html (China Statistics Press, 2001-2016).

  32. Ministry of Education of the People’s Republic of China. Educational Statistics Yearbook of China [in Chinese] http://tongji.cnki.net/kns55/Navi/HomePage.aspx?id=N2012010030&name=YZKRM&floor=1 (People’s Education Press, 2001-2016).

  33. Ministry of Health of the People’s Republic of China. China Health Statistical Yearbook [in Chinese] http://www.shujuku.org/china-health-statistical-yearbook.html (Peking Union Medical College Press, 2001-2016).

  34. National Bureau of Statistics of the People’s Republic of China. China Energy Statistical Yearbook [in Chinese] http://tongji.cnki.net/kns55/Navi/HomePage.aspx?id=N2016120537&name=YCXME&floor=1 (China Statistics Press, 2001–2016).

  35. National Bureau of Statistics of the People’s Republic of China. China Population Statistics Yearbook [in Chinese] http://tongji.cnki.net/kns55/navi/HomePage.aspx?id=N2007091124&name=YZGRL&floor=1 (China Statistics Press, 2001-2006).

  36. Costa, L., Rybski, D. & Kropp, J. P. A human development framework for CO2 reductions. Plos One 6, e29262 (2011).

    Article  ADS  CAS  Google Scholar 

  37. Turner, M. G., Wu, Y., Wallace, L. L., Romme, W. H. & Brenkert, A. Simulating winter interactions among ungulates, vegetation, and fire in northern Yellowstone Park. Ecol. Appl. 4, 472–496 (1994).

    Article  Google Scholar 

  38. Liu, J. & Ashton, P. S. FORMOSAIC: an individual-based spatially explicit model for simulating forest dynamics in landscape mosaics. Ecol. Modell. 106, 177–200 (1998).

    Article  Google Scholar 

  39. Institute of Geographic Sciences and Natural Resources Research of Chinese Academy of Sciences. Resource and Environment Data Cloud Platform [in Chinese] http://www.resdc.cn/data.aspx?DATAID=202 (2015).

  40. Frigge, M., Hoaglin, D. C. & Iglewicz, B. Some implementations of the boxplot. Am. Stat. 43, 50–54 (1989).

    Google Scholar 

  41. Krzywinski, M. & Altman, N. Visualizing samples with box plots. Nat. Methods 11, 119–120 (2014).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We acknowledge edits from S. Nichols and K. Kapsar, and data compilation from Y. Liu, Y. Wang, Z. Zhou and Y. Sun. We are grateful for financial support from the National Science Foundation, Michigan State University, Michigan AgBioResearch, the China Scholarship Council and the National Natural Science Foundation of China (grant numbers 51621061 and 51321001).

Author information

Authors and Affiliations

Authors

Contributions

Z.X. and J.L. designed the research. Yunkai Li and X.C. contributed and checked data. Z.X., S.N.C., J.L., T.D., Yunkai Li, Y.T., X.C., S.L., B.H., A.H., J.A.W. and D.H. provided comments on the manuscript. Z.X., J.Z., Yingjie Li and F.F. analysed the data. Yunkai Li and X.C. helped to analyse data related to SDGs 2 and 6. Z.X., S.N.C., J.Z., Yingjie Li and J.L. wrote the manuscript. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Yunkai Li or Jianguo Liu.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Brett Bryan, Xiangzheng Deng, Lei Gao and Jürgen Kropp for their contribution to the peer review of this work.

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 Change in China’ s individual SDG scores at the national level from 2000 to 2015.

For data sources, see Methods.

Extended Data Fig. 2 Uncertainty analysis for SDG scores (n = 281,287) at the national level in 2015 for different numbers of selected indicators.

1–17 indicates uncertainty analysis for SDG 1–17. Sample sizes are 63, 1,023, 262,143, 1,023, 63, 63, 7, 15, 16,383, 15, 63, 127, 31, 7, 127, 7 and 127 for box plots of SDG 1–17. In each box plot, the central rectangle spans the first quartile Q1 to the third quartile Q3, which is the interquartile range (IQR)40,41 (IQR = Q3 to Q1), while the line segment inside the rectangle shows the median. When the maximum observed SDG scores are greater than Q3 + 1.5 × IQR40,41, the upper whisker (red) is Q3 + 1.5 × IQR40,41. Otherwise, the upper whisker is the maximum observed SDG score. When the minimum observed SDG scores are less than Q1 − 1.5 × IQR40,41, the lower whisker (green) is Q1 − 1.5 × IQR. Otherwise, the lower whisker is the minimum observed SDG score40,41.

Extended Data Fig. 3 Sensitivity of SDG Index scores to changes in each indicator.

The sensitivity index Sx of SDG Index scores is shown when each SDG indicator’s original data value decreased by 10%, (1)–(16), or increased by 10%, (17)–(32), for China and for three example provinces (Beijing, Henan and Gansu) at three levels (high, middle and low) of the average SDG Index scores in 2000, 2005, 2010 and 2015. The sample size n for each figure is 119 indicators. The x axes display the SDG indicators arranged from 1 to 119. The y axis is the sensitivity index Sx of SDG Index scores due to the 10% decrease or increase in the original value of each indicator.

Extended Data Fig. 4 China’s SDG Index score compared with another 156 countries based on overlapping indicators.

The box plot depicts the distribution of SDG Index scores (n = 156) for 156 countries in one year. The central rectangle spans the first quartile Q1 to the third quartile Q3, which is the IQR40,41, while the line segment inside the rectangle shows the median. When the maximum observed SDG Index scores are greater than Q3 + 1.5 × IQR, the upper whisker is equal to Q3 + 1.5 × IQR40,41. Otherwise, the upper whisker is equal to the maximum observed SDG Index score. When the minimum observed SDG Index score is less than Q1 − 1.5 × IQR, the lower whisker is equal to Q1 − 1.5 × IQR40,41. Otherwise, the lower whisker is the minimum observed SDG Index score40,41. The green line segment within the box is the median value of SDG Index scores for the 156 countries.

Extended Data Fig. 5 Coefficient of variation for SDG scores.

a, Coefficient of variation (CV) for SDG scores of provinces in 2000, 2005, 2010 and 2015. b, Average value of the coefficient of variation for SDG scores at the provincial level in 2000, 2005, 2010 and 2015.

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Xu, Z., Chau, S.N., Chen, X. et al. Assessing progress towards sustainable development over space and time. Nature 577, 74–78 (2020). https://doi.org/10.1038/s41586-019-1846-3

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