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Assessment of the climate change adaptation capacity of urban agglomerations in China

  • Chunli Zhao
  • Jianguo ChenEmail author
  • Guofeng Su
  • Hongyong Yuan
Original Article

Abstract

Complex urban ecosystems are relatively fragile in the context of climate change. Given this fragility and the large numbers of urban inhabitants, it is important for researchers and government regulators to assess the adaptation capacity of urban areas with respect to climate change. Currently, there are few studies that have evaluated such adaptation capacity across different regions and periods. In this study, a framework and method are established to assess the adaptation capacity of Chinese cities and urban agglomerations (UAs) with respect to climate change by integrating an SPRR (Source, Pathway, Receptor, Response) model with the Intergovernmental Panel on Climate Change (IPCC) assessment framework. We develop an indicator system for exposure, sensitivity, and resilience and use the set pair analysis (SPA) method to evaluate the adaptation capacity of 12 typical UAs in China. Results show that (1) adaptation capacity levels show wide variation across China, with the majority of cities and UAs having either high or low levels of capacity and a minority having a moderate level of capacity; (2) inland UAs have low adaptation capacity because of low resilience and sensitivity, whereas eastern coastal UAs have high adaptation capacity, for their high resilience and sensitivity; and (3) higher climate change exposures are distributed predominantly in central China. A pronounced economic disparity exists between western inland regions and eastern regions, with the latter having higher levels of economic development and superior infrastructure. The regional economic inequalities and spatial variation in climate variability observed in China are also characteristics shared by many other countries and regions, suggesting that our results may be generalised to other countries and regions. We propose that underdeveloped regions should seek to improve infrastructure and funding directed towards improving adaptation capacity, whereas developed regions should improve their ability to monitor climate change and its impacts.

Keywords

Climate change Adaptation capacity Set pair analysis (SPA) Urban agglomeration (UA) 

Notes

Funding information

This research was supported by the National Key Research and Development Program of China (Grant No. 2018YFC0806900), the Major Program of the National Natural Science Foundation of China (Grant No.71790613), and the China Postdoctoral Science Foundation (Grant No. 2019M650631).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interests.

References

  1. Araos M, Berrang-Ford L, Ford JD, Austin SE, Biesbroek R, Lesnikowski A (2016) Climate change adaptation planning in large cities: a systematic global assessment. Environ Sci Pol 66:375–382CrossRefGoogle Scholar
  2. Asseng S, Ewert F, Martre P, Rötter RP, Lobell DB, Cammarano D (2015) Rising temperatures reduce global wheat production. Nat Clim Chang 5(2):143–147CrossRefGoogle Scholar
  3. Chen Z, She L (2009) Research on city vulnerability to safe development-based on an angle of underground space utilization. Huazhong Univ Sci Technol 23(1):109–112 (Chinese in English Abstract)Google Scholar
  4. Chen MX, Gong YH, Li Y, Lu DD, Zhang H (2016) Population distribution and urbanization on both sides of the Hu Huanyong Line: answering the Premier’s question. J Geogr Sci 26(11):1593–1610.  https://doi.org/10.1007/s11442-016-1346-4 CrossRefGoogle Scholar
  5. Chunli Z, Jianguo C, Peng D, Hongyong Y (2018) Characteristics of climate change and extreme weather from 1951 to 2011 in China. Int J Environ Res Public Health 15:2540.  https://doi.org/10.3390/ijerph15112540 CrossRefGoogle Scholar
  6. Cutter S, Boruff B, Shirley W (2003) Social vulnerability to environmental hazards. Soc Sci Q 84(2):242–261CrossRefGoogle Scholar
  7. Dell M, Jones B, Olken B (2012) Temperature shocks and economic growth: evidence from the last half century. Am Econ J Macroecon 4(3):66–95.  https://doi.org/10.3386/w14132 CrossRefGoogle Scholar
  8. Donat MG, Alexander LV, Yang H, Durre I, Vose R, Dunn RJH (2013) Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: the HadEX2 dataset. J Geophys Res Atmos 118(5):2098–2118CrossRefGoogle Scholar
  9. Eriyagama N, Smakhtin V, Chandrapala L, Fernando K (2014) Impacts of climate change on water resources and agriculture in Sri Lanka: a review and preliminary vulnerability mapping. Water Matters 5(5):6–7Google Scholar
  10. Fischer EM, Knutti R (2015) Anthropogenic contribution to global occurrence of heavy-precipitation and high-temperature extremes. Nat Clim Chang 5(6):560–564CrossRefGoogle Scholar
  11. Ford JD, Berrang FL (2016) The 4Cs of adaptation tracking: consistency, comparability, comprehensiveness, coherency. Mitig Adapt Strateg Glob Chang 21(6):839–859CrossRefGoogle Scholar
  12. Gao J, Sheng ZH (2002) Method and application of set pair analysis classified prediction. J Syst Eng:458–462 (Chinese in English Abstract)Google Scholar
  13. Holdgate MW (1979) A perspective of environmental pollution. Cambridge University Press Cambridge, UKGoogle Scholar
  14. IPCC (2001) Climate change 2001: impacts, adaptation, and vulnerability [M]. Cambridge University Press, Cambridge, pp 1–1032Google Scholar
  15. IPCC (2012) Managing the risks of extreme events and disasters to advance climate change adaptation. A special report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge 582 ppGoogle Scholar
  16. IPCC (2014) Climate change 2014: impact, adaptation, and vulnerability [M]. Cambridge University Press, CambridgeGoogle Scholar
  17. Jain M (2017) Economic development and climate change: an empirical study for developing nations. 4(01).  https://doi.org/10.17492/focus.v4i01.9541
  18. Jiang SM (2010) Applications of set pair analysis to uncertainty analysis of water resources. HeFei University of Technology, Hefei (Chinese in English Abstract)Google Scholar
  19. Kalafatis SE (2017) When do climate change, sustainability, and economic development considerations overlap in cities? Environ Polit 27:115–138.  https://doi.org/10.1080/09644016.2017.1373419 CrossRefGoogle Scholar
  20. Kintisch E (2015) Earth’s lakes are warming faster than its air. Science 350(6267):1449–1449CrossRefGoogle Scholar
  21. Li ZY, Wu M, Liu ZY, Li DP, Guo C (2009) A new approach to I in connection number and application in water quality assessment. J Sichuan Univ (Eng Sci Ed) 41(1):8–13 (Chinese in English Abstract)Google Scholar
  22. Liu XM, Zhao KQ (2009) Multiple attribute decision making and its applications with interval numbers based on D-U space of SPA. Fuzzy Syst Math 23(2):12–26 (Chinese in English Abstract)Google Scholar
  23. Liu B, Asseng S, Müller C, Ewert F, Elliott J, Lobell DB (2016) Similar estimates of temperature impacts on global wheat yield by three independent methods. Nat Clim Chang 6(12):1130–1136CrossRefGoogle Scholar
  24. Myers SS, Zanobetti A, Kloog I, Huybers P, Leakey ADB, Bloom AJ (2014) Increasing CO2 threatens human nutrition. Nature 510(7503):139–142CrossRefGoogle Scholar
  25. Narayan S, Hanson S, Nicholls RJ, Clarke D, Willems P, Ntegeka V (2012) A holistic model for coastal flooding using system diagrams and the source-pathway-receptor (SPR) concept. Nat Hazard Earth Syst 12(5):1431–1439CrossRefGoogle Scholar
  26. Nie L, Lindholm O, Lindholm G, Syversen E (2009) Impacts of climate change on urban drainage systems-a case study in Fredrikstad, Norway. Urban Water J 6(4):323–332CrossRefGoogle Scholar
  27. Peng SS (2014) Mine safety evaluation based on set pair analysis theory. Xi’an University of Science and Technology, Xian (Chinese in English Abstract)Google Scholar
  28. Revi A, Satterthwaite DE, Aragón-Durand F, Corfee-Morlot J, Kiunsi RBR, Pelling M, Roberts DC, Solecki W (2014) Urban areas. In: Climate change 2014: Impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 535–612Google Scholar
  29. Richardson M, Cowtan K, Hawkins E, Stolpe MB (2016) Reconciled climate response estimates from climate models and the energy budget of Earth. Nat Clim Change 6(10):39002-39003(2)CrossRefGoogle Scholar
  30. Rozas-Davila A, Valencia BG, Bush MB (2016) The functional extinction of Andean megafauna. Ecology 97(10):2533–2539CrossRefGoogle Scholar
  31. Scheffers BR, De Meester L, Bridge TCL, Hoffmann AA, Pandolfi JM, Corlett RT (2016) The broad footprint of climate change from genes to biomes to people. Science 354(6313):aaf7671CrossRefGoogle Scholar
  32. Shi L, Kloog I, Zanobetti A, Liu P, Schwartz JD (2015) Impacts of temperature and its variability on mortality in New England. Nat Clim Chang 5(11):988–991CrossRefGoogle Scholar
  33. Vezzulli L, Grande C, Reid PC, Hélaouët P, Edwards M, Höfle MG (2016) Climate influence on Vibrio and associated human diseases during the past half-century in the coastal North Atlantic. Proc Natl Acad Sci 113(34):E5062–E5071CrossRefGoogle Scholar
  34. Wang HF (2008) Research on set pair analysis in the hydrology and water resource fields. Sichuan University, Chengdu (Chinese in English Abstract)Google Scholar
  35. Wang WS, Jin J, Ding J, Liu YQ (2009) A new approach to water resources system assessment-set pair analysis method. Sci China Ser E-Tech Sci 39(9):1529–1534 (Chinese in English Abstract)Google Scholar
  36. Wang Y, Fang CL, Zhang Q (2013) Progress and prospect of urban vulnerability. Prog Geogr 05:755–768 (Chinese in English Abstract)Google Scholar
  37. Wang TF, Su BD, Jiang T (2014) Haze variation tendency and countermeasure analysis in haze under the climate change context. Environ Impact Assess (1):15–17 (Chinese in English Abstract)Google Scholar
  38. Webersik C (2010) Climate change and security: a gathering storm of global challenges: a gathering storm of global challenges [M]. Praeger Publishers, USGoogle Scholar
  39. Wieder WR, Cleveland CC, Smith WK, Todd-Brown K (2015) Future productivity and carbon storage limited by terrestrial nutrient availability. Nat Geosci 8(6):441–444CrossRefGoogle Scholar
  40. Wu J (1991) System dialectisc. People’s Publishing House, Beijing (Chinese in English Abstract)Google Scholar
  41. Wu T (2008) A value -fetching formula of nondeterministic coefficient in connection number and its applications. Bull Sci Technol 24(5):595–597 (Chinese in English Abstract)Google Scholar
  42. Wu M (2014) The empirical study of the economic development gap between east and west. Southwestern University of Finance and Economics, ChengduGoogle Scholar
  43. Wu RJ, Zhu BS (2016) Unbalanced distribution of the population of China and stability of ‘Hu Huanyong Line’. Chin J Population Sci 1:14–24Google Scholar
  44. Xie Q (2013) Urbanization issues and its solution analysis in China. Sci Technol Innov Herald (24):218–218 (Chinese in English Abstract)Google Scholar
  45. Yan BY (2016) Socio-economic vulnerability assessment on the influence of sea level rise and storm tide in Shanghai[D]. East China Normal University, ShanghaiGoogle Scholar
  46. Yusuf AA, Francisco H (2009) Climate change vulnerability mapping for Southeast Asia. Economy and Environment Program for Southeast Asia (EEPSEA), Singapore, pp 10–15Google Scholar
  47. Zhang B (1997) The fuzzy set pair analysis way of multiple objective system decision. Syst Eng Theory Pract 12:109 (Chinese in English Abstract)Google Scholar
  48. Zhao KQ (1997) Correlate and it’s uncertainty in set pairs analysis methods[J]. Explor Nat 16(2):91 (Chinese in English Abstract)Google Scholar
  49. Zhao KQ (2008) The theoretical basis and basic algorithm of binary connection A+Bi and its application in AI. CAAI Trans Intell Syst 3(6):476–486 (Chinese in English Abstract)Google Scholar
  50. Zhao KQ, Mi H (2010) Non-traditional security & SPA. Intellectual Property Publishing House, Beijing (Chinese)Google Scholar
  51. Zhao ZC, Luo Y, Huang JB (2012) Are there impacts of urban heat islands on future climate change? Progressus Inquisitiones de Mutatione Climatis 8(6):469–472 (Chinese in English Abstract)Google Scholar
  52. Zhou ZW (2010) Urbanization issues and urban governance in Brazil. China Finance (4):39–40 (Chinese in English Abstract)Google Scholar
  53. Zhu B, Wang WS, Wang HF, Li YQ (2008) Probe on variation uncertainty coefficient i in set pair analysis. J Sichuan Univ (Eng Sci Ed) 40(1):8–13 (Chinese in English Abstract)Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Engineering PhysicsTsinghua UniversityBeijingChina
  2. 2.Institute of Public Safety ResearchTsinghua UniversityBeijingChina
  3. 3.Beijing Key Laboratory of City Integrated Emergency Response ScienceBeijingChina

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