An Investigation of the Selection of LEED Version 4 Credits for Sustainable Building Projects

Abstract

The U.S. Green Building Council’s (USGBC) Leadership in Energy and Environmental Design (LEED) certification program supports sustainable construction as part of the effort to address climate change and resource depletion. It is the world’s most popular green building certification system, with more than 146,400 projects. Satisfying the LEED requirements brings many benefits to a project’s design performance and adds community value, but it does incur additional costs and challenges. This study examined the choices made by those working on the 222 LEED New Construction version 4 (LEED-NC-V4) projects that were certified between September 2014 and March 2020 to determine how the LEED project teams selected appropriate LEED goals. The results reveal interesting insights into the way project LEED goals and the credits corresponding to the target certification level were chosen, as well as the links and trade-offs between the various credit options. Based on these findings, useful suggestions are made for ways to help LEED project teams achieve their target certification levels and encourage authorities to continue to improve their local green regulations. The analysis of actual certified projects’ data makes it possible to re-evaluate the effects of newly updated requests in LEED v4 in the light of the stated goals of the USGBC.

Developing a Risk Management Process for General Contractors in the Bidding Stage for Design–Build Projects in Vietnam

“…Specifically, the factors will be in the high-risk group if the RL value of that factor is >0.8, the medium-risk level if the RL value is between 0.45 and 0.8, and the low-risk level if the RL value is <0.45 [10] (Figure 2). One important thing to note is that the mean value cannot accurately reflect the statistical results of the survey data, so further statistical techniques needed to be employed to evaluate the data from the survey [37]. In particular, the (1) mean value ranking, (2) Kolmogorov-Smirnov test, and (3) one-sample t-test techniques were used to identify the significant risk factors that influence GCs in developing an RMP for the bidding process.…”

“…In particular, the (1) mean value ranking, (2) Kolmogorov-Smirnov test, and (3) one-sample t-test techniques were used to identify the significant risk factors that influence GCs in developing an RMP for the bidding process. First, the mean value ranking technique was used to rank the risk factors based on their risk leveling value and the standard deviation [37]. Second, the Kolmogorov-Smirnov test (n > 50) [38] was used to test the normality of the collected data distribution for further statistical hypothesis testing [39].…”

“…After the bidding process was completed, members of the project team were interviewed to collect feedback on the application of the add-on process during the bidding process. [37]. Second, the Kolmogorov-Smirnov test (n > 50) [38] was used to test the normality of the collected data distribution for further statistical hypothesis testing [39].…”

LEED 2009 Recertification of Existing Buildings: Bonus Effect

“…Table 1 demonstrates that 15 of the 20 groups contained less than 8 primary sampling units. Therefore, we only used descriptive statistics, namely, the percentage of average score (PAS; the ratio of achieved points to maximal points, expressed as a percentage) to assess the performance of the LEED data [32].…”

Impact of the bonus approach on recertification strategies for LEED-EB v3 office projects in major US metropolitan areas: A case study

“…Table 1 illustrates that 6 of 12 groups contain less than 8 primary sampling units. Therefore, we only used descriptive statistics, namely, the percentage of average score (PAS)—the ratio of achieved points to maximal points (expressed as a percentage), to assess the performance of LEED data ( Pham et al., 2020 ).…”