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Abdel-Wahab, M and Vogl, B (2011) Trends of productivity growth in the construction industry across Europe, US and Japan. Construction Management and Economics, 29(06), 635–44.

Camilleri, M, Jaques, R and Isaacs, N (2001) Impacts of climate change on building performance in New Zealand. Building Research & Information, 29(06), 430–50.

Chi, C S F and Nicole Javernick‐Will, A (2011) Institutional effects on project arrangement: high‐speed rail projects in China and Taiwan. Construction Management and Economics, 29(06), 595–611.

Edwards, D J (2001) Predicting construction plant maintenance expenditure. Building Research & Information, 29(06), 417–27.

Gambatese, J A and Hallowell, M (2011) Enabling and measuring innovation in the construction industry. Construction Management and Economics, 29(06), 553–67.

Gundes, S (2011) Input structure of the construction industry: a cross‐country analysis, 1968–90. Construction Management and Economics, 29(06), 613–21.

Hartono, B and Yap, C M (2011) Understanding risky bidding: a prospect‐contingent perspective. Construction Management and Economics, 29(06), 579–93.

Murray, B and Smyth, H (2011) Franchising in the US remodelling market: growth opportunities and barriers faced by general contractors. Construction Management and Economics, 29(06), 623–34.

Scheublin, F J M (2001) Project alliance contract in The Netherlands. Building Research & Information, 29(06), 451–5.

Westberg, K, Noren, J and Kus, H (2001) On using available environmental data in service life estimates. Building Research & Information, 29(06), 428–39.

  • Type: Journal Article
  • Keywords: building components; building materials ; degradation; environmental characterization; micro climate; micro environment; service life estimation; weather data
  • ISBN/ISSN: 0961-3218
  • URL: http://journalsonline.tandf.co.uk/link.asp?id=78h0v7f4ttnfcbd5
  • Abstract:
    In the process of service life prediction or estimation of building and construction components and materials, data of the prevailing exposure environment, (the conditions at and around a building or construction) is required. However, most environmental data is measured by and available from meteorological and air quality research communities. This data is collected at macro and meso levels, some distance from the object studied, and raises the need to transform data in order to describe the specific, local conditions adjacent to that object. To estimate levels of degradation agents in the exposure environment, especially those close to the building or construction at local and micro levels have to be considered. This paper will show and discuss useful environmental data sources, and how to transform such data by means of available distribution models.

Zhang, H, Xing, F and Liu, J (2011) Rehabilitation decision-making for buildings in the Wenchuan area. Construction Management and Economics, 29(06), 569–78.