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Increased costs to US pavement infrastructure from future temperature rise

Abstract

Roadway design aims to maximize functionality, safety, and longevity1,2. The materials used for construction, however, are often selected on the assumption of a stationary climate1,3. Anthropogenic climate change may therefore result in rapid infrastructure failure and, consequently, increased maintenance costs, particularly for paved roads where temperature is a key determinant for material selection. Here, we examine the economic costs of projected temperature changes on asphalt roads across the contiguous United States using an ensemble of 19 global climate models forced with RCP 4.5 and 8.5 scenarios. Over the past 20 years, stationary assumptions have resulted in incorrect material selection for 35% of 799 observed locations. With warming temperatures, maintaining the standard practice for material selection is estimated to add approximately US$13.6, US$19.0 and US$21.8 billion to pavement costs by 2010, 2040 and 2070 under RCP4.5, respectively, increasing to US$14.5, US$26.3 and US$35.8 for RCP8.5. These costs will disproportionately affect local municipalities that have fewer resources to mitigate impacts. Failing to update engineering standards of practice in light of climate change therefore significantly threatens pavement infrastructure in the United States.

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Figure 1: Weather stations evaluated to compare 1966–1995 climate database and 1985–2014 climate databases.
Figure 2: Expected median increases in pavement temperature based on the RCP 8.5 ensemble.
Figure 3: National cost impact from failing to adapt asphalt grade.

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References

  1. Huang, Y. H. Pavement Analysis and Design (Prentice Hall, 1993).

    Google Scholar 

  2. Yoder, E. J. & Witczak, M. W. Principles of Pavement Design (John Wiley, 1975).

    Book  Google Scholar 

  3. Asphalt Institute Superpave Performance Graded Asphalt Binder Specifications and Testing Superpave Series No. 1 (SP-1) (Asphalt Institute, 2003).

  4. National Research Council Committee on Climate Change (NRC) Potential Impacts of Climate Change on US Transportation (National Research Council, 2008).

  5. Meyer, M. et al. Strategic Issues Facing Transportation, Volume 2: Climate Change, Extreme Weather Events, and the Highway System: Practioner’s Guide and Research Report NCHRP Report 750 (National Cooperative Highway Research Program, 2014).

    Google Scholar 

  6. Anderson, T., Beck, C., Gade, K. & Olmsted, S. Extreme Weather Vulnerability Assessment FHWA No. 0704-0188.FHWA (Arizona Department of Transportation, 2015).

    Google Scholar 

  7. Cambridge Systematics Central Texas Extreme Weather and Climate Change Vulnerability Assessment of Regional Transportation Infrastructure FHWA No. 0704-0188 (Capital Area Metropolitan Planning Organization, 2015).

  8. Koetse, M. J. & Rietveld, P. The impact of climate change and weather on transport: an overview of empirical findings. Transp. Res. 14, 205–221 (2009).

    Google Scholar 

  9. IPCC Climate Change and Cities: First Assessment Report of the Urban Climate Change Research Network (eds Rosenzweig, C., Solecki, W. D., Hammer, S. A.& Mehrotra, S.) (Cambridge Univ. Press, 2011).

  10. United States Department of Transportation (USDOT) Transportation in the United States (Bureau of Transportation Statistics, 2015).

  11. United States Department of Transportation (USDOT) US Beyond Traffic 2045: Trends and Choices (US Department of Transportation, 2015).

  12. American Society of Civil Engineers (ASCE) 2013 Report Card for Americas Infrastructure (2013); http://www.infrastructurereportcard.org

  13. IPCC Climate Change Impacts in the United States: The Third National Climate Assessment (eds Melillo, J. M., Terese, R. & Yohe, G. W.) 841 (US Global Change Research Program, 2014).

  14. Knutti, R. & Sedlacek, J. Robustness and uncertainties in the new CMIP5 climate model projections. Nat. Clim. Change 3, 369–373 (2013).

    Article  Google Scholar 

  15. Mearns, L. et al. The North American regional climate change assessment program: overview of phase I results. Bull. Am. Meteorol. Soc. 93, 1337–1362 (2012).

    Article  Google Scholar 

  16. Woldemeskel, F. M., Sharma, A., Sivakumar, B. & Mehrotra, R. Quantification of precipitation and temperature uncertainties simulated by CMIP3 and CMIP5 models. J. Geophys. Res. 121, 3–17 (2016).

    Article  Google Scholar 

  17. Wuebbles, D. et al. CMIP5 climate model analysis: climate extremes in the United States. Bull. Am. Meteorol. Soc. 95, 571–583 (2014).

    Article  Google Scholar 

  18. United States Department of Transportation (USDOT) National Transportation Statistics (Bureau of Transportation Statistics, accessed March 2016); https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transportation_statistics/index.html

  19. Chinowsky, P. & Arndt, C. Climate change and roads: a dynamic stressor-response model. Rev. Dev. Econ. 16, 448–462 (2012).

    Article  Google Scholar 

  20. Chinowsky, P. S., Price, J. C. & Neumann, J. E. Assessment of climate change adaptation costs for the US road network. Glob. Environ. Change 23, 764–773 (2013).

    Article  Google Scholar 

  21. Daniel, J. S., Jacobs, J. M., Douglas, E., Mallick, R. B. & Hayhoe, K. Impact of climate change on pavement performance: preliminary lessons learned through the infrastructure and climate network (ICNet). Int. Symp. Climatic Effects Pavement Geotechnical Infrastructure (Fairbanks AK, 2013).

    Google Scholar 

  22. Fletcher, C. G., Matthews, L., Andrey, J. & Saunders, A. Projected changes in mid-twenty-first-century extreme maximum pavement temperature in Canada. J. Appl. Meteorol. Climatol. 55, 961–974 (2016).

    Article  Google Scholar 

  23. Harvey, M. et al. Impact of Climate Change on Road Infrastructure Report No. AP-R243/04 (Austroads and the Bureau of Transport and Regional Economics, 2004).

    Google Scholar 

  24. Meagher, W., Daniel, J. S., Jacobs, J. & Linder, E. Method for evaluating implications of climate change for design and performance of flexible pavements. Trans. Res. Record J. Trans. Board 2305, 111–120 (2012).

    Article  Google Scholar 

  25. Mills, B. N., Tighe, S. L., Andrey, J., Smith, J. T. & Huen, K. Climate change implications for flexible pavement design and performance in Southern Canada. J. Trans. Eng. 135, 773–782 (2009).

    Article  Google Scholar 

  26. Mndawe, M. B., Ndambuki, J. & Kupolati, W. K. Revision of the macro climatic regions of Southern Africa. OIDA Int. J. Sustainable Dev. 6, 37–44 (2013).

    Google Scholar 

  27. Schweikert, A., Chinowsky, P., Espinet, S. & Tarbert, M. Climate change and infrastructure impacts: comparing the impact on roads in ten countries through 2100. Procedia Eng. 78, 306–316 (2014).

    Article  Google Scholar 

  28. Viola, F. & Celauro, C. Effect of climate change on asphalt binder selection for road construction in Italy. Transp. Res. 37, 40–47 (2015).

    Google Scholar 

  29. Kunkel, K. E., Liang, X. Z. & Zhu, J. Regional climate model projections and uncertainties of US summer heat waves. J. Clim. 23, 4447–4458 (2010).

    Article  Google Scholar 

  30. Maurer, E. P., Brekke, L., Pruitt, T. & Duffy, P. B. Fine-resolution climate projections enhance regional climate change impact studies. Eos Trans. Am. Geophys. Union 88, 504 (2007).

    Article  Google Scholar 

  31. Climate Analytics Group Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections (US Department of the Interior, Bureau of Reclamation, Technical Service Center, accessed September, 2015); ftp://gdo-dcp.ucllnl.org/pub/dcp/archive/cmip5/bcca

  32. Reclamation Downscaled CMIP3 and CMIP5 Climate Projections: Release of Downscaled CMIP5 Climate Projections, Comparison with Preceding Information, and Summary of User Needs 116 (US Department of the Interior, Bureau of Reclamation, Technical Service Center, 2013); http://gdo-dcp.ucllnl.org/downscaled_cmip_projections/techmemo/downscaled_climate.pdf

  33. Huber, G. A. Weather Database for the Superpave Mix Design System SHRP-A-648A (Strategic Highway Research Program, 1994).

    Google Scholar 

  34. Johnson, N. L. & Kotz, S. Continuous Univariate Distributions: Chapter 24 – Beta Distributions (Houghton Mifflin Company, 1970).

    Google Scholar 

  35. Zapata, C. E. & Cary, C. E. Integrating the National Database of Subgrade Soil-Water Characteristic Curves and Soil Index Properties With the MEPDG Final Report NCHRP 9-23b (National Cooperative Highway Research Program, 2012).

    Google Scholar 

  36. Applied Research Associates Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures Final Report NCHRP 1-37A (National Cooperative Highway Research Program, National Research Council, 2004).

  37. Darter, M. I., Glover, L. T., Von Quintus, H., Bhattacharya, B. B. & Mallela, J. Calibration and Implementation of the AASHTO Mechanistic-Empirical Pavement Design Guide in Arizona FHWA-AZ-14-606 FHWA (Arizona Department of Transportation, 2014).

    Google Scholar 

  38. Heitzman, M., Timm, D., Tackle, E. S., Herzmann, D. E. & Traux, D. D. Developing MEPDG Climate Data Input Files for Mississippi FHWA/MS-DOT-RD-11-232. FHWA (Mississippi Department of Transportation, 2011).

    Google Scholar 

  39. Pierce, L. M. & McGovern, G. Implementation of the AASHTO Mechanistic-Empirical Pavement Design Guide and Software Project 20-05, Topic 44-06 (National Cooperative Highway Research Program, 2014).

    Book  Google Scholar 

  40. Smith, B. & Nair, H. Development of Local Calibration Factors and Design Criteria Values for Mechanistic-Empirical Pavement Design FHWA/VCTIR 16-R1.FHWA (Virginia Center of Transportation, 2015).

    Google Scholar 

  41. VonQuintus, H. L. & Moulthrop, J. S. Mechanistic-Empirical Pavement Design Guide Flexible Pavement Performance Prediction Models for Montana, Volume III: Field Guide Calibration and Users Guide for the Mechanistic-Empirical Pavement Design Guide FHWA/MT-07-008/8158-3.FHWA (Montana Department of Transportation, 2007).

    Google Scholar 

  42. Witczak, M. W., Zapata, C. E. & Houston, W. N. Models Incorporated into the Current Enhanced Integrated Climatic Model, Final Report (National Cooperative Highway Research Program, 2006).

    Google Scholar 

  43. Fwa, T. F., Pasindu, H. R. & Ong, G. P. Critical rut depth for pavement maintenance based on vehicle skidding and hydroplaning consideration. J. Trans. Eng. 138, 423–429 (2011).

    Article  Google Scholar 

  44. Lamptey, G., Ahmad, M. Z., Labi, S. & Kumares, C. S. Life Cycle Cost Analysis for INDOT Pavement Design Procedures FHWA/IN/JTRP-2004/28 (Indiana Department of Transportation, 2005).

    Book  Google Scholar 

  45. New York Department of Transportation (NYDOT) Comprehensive Pavement Design Manual: Chapter 5 Rehabilitation (NYDOT Design Division and Technical Service Division, 2002).

  46. Santero, N. Life Cycle Assessment of Pavements: A Critical Review of Existing Literature and Research (Lawrence Berkeley National Laboratory, 2010); https://www.osti.gov/scitech/servlets/purl/985846

    Book  Google Scholar 

  47. Walls, J. & Smith, M. R. Life Cycle Cost Analysis in Pavement Design - Interim Technical Bulletin FHWA-SA98-079 (Federal Highway Administration, 1998).

    Google Scholar 

  48. National Highway Planning Network (NHPN) National Highway Planning Network - Tools - Processes - Planning (accessed March 2015); http://www.fhwa.dot.gov/planning/processes/tools/nhpn

  49. NIST/SEMATECH e-Handbook of Statistical Methods (National Institute of Standards and Technology, 2012); http://www.itl.nist.gov/div898/handbook

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Acknowledgements

We acknowledge the World Climate Research Program’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modelling groups (listed in Supplementary Table 1) for producing and making available their model output. For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We would also like to acknowledge the Climate Assessment for the Southwest (CLIMAS) at the University of Arizona for providing support to Z. Guido.

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Contributions

B.S.U. designed the study, identified the data sources, created the scripts to analyse the climate data, and developed the structure of the paper in collaboration with Z.G. and P.G.; Z.G. provided inputs on climate modelling and ensemble interpretation and review of the manuscript; P.G. reviewed the manuscript and discussed interpretation of the data at length; Y.F. assisted in downloading, cataloguing, and running the climate scripts. All authors contributed equally to developing the ideas in this paper.

Corresponding author

Correspondence to B. Shane Underwood.

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The authors declare no competing financial interests.

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Underwood, B., Guido, Z., Gudipudi, P. et al. Increased costs to US pavement infrastructure from future temperature rise. Nature Clim Change 7, 704–707 (2017). https://doi.org/10.1038/nclimate3390

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