Blog
About

0
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found

      PITTSBURGH 2030 DISTRICT ENERGY BASELINE: MOTIVATION, CREATION, AND IMPLICATIONS

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          INTRODUCTION

          Consider the task of tracking the energy use of an entire city while also working to reduce it by 50% in 17 years. How would you go about tracking and verifying such reductions? Further, how would this be accomplished in a city without a database of building-specific characteristics and no energy reporting law? To begin, let's consider what this task would look like for one building. Where to start? Let's try with a performance metric and point of comparison.

          Just as cars gauge performance by MPG, and pitchers by ERA, buildings can use Energy Use Intensity (EUI) as a performance metric. Measured in Energy / ft 2 / year, EUI standardizes energy use per square foot, allowing for comparison between many buildings. EUI is a snapshot of building performance over one year's time. It is relatively easy to calculate a building's EUI if their energy usage is known, but in order to gauge performance over a longer period, a constant comparison point must be established so that evaluation is consistent. Called the baseline, this comparison point can be established as a past year, a future goal, or the average performance of similar buildings.

          This paper covers the work of the Pittsburgh 2030 District team in formulating an energy performance baseline for each building in Downtown Pittsburgh for purposes of tracking energy use reduction towards the 50% reduction goals of The 2030 Challenge. Pittsburgh is a city with a large stock of aging buildings, without mandatory benchmarking laws, and no single publicly accessible real estate profile by property. Thus, the energy baseline methods included in this paper summarize efforts to create such an aggregated property characteristic database and associated energy baseline for Downtown Pittsburgh; it is the hope of the authors that these efforts will assist similar cities in mirroring 2030 District goal setting and achievement for building energy

          Related collections

          Author and article information

          Journal
          jgrb
          Journal of Green Building
          College Publishing
          1552-6100
          1943-4618
          1943-4618
          Fall 2014
          : 9
          : 4
          : 79-104
          Author notes

          1. LEED Green Associate. BuroHappold Engineering, 100 Broadway, New York, NY, 10005. matthew.huddleston@ 123456burohappold.com .

          2. PhD, LEED AP BD+C. Green Building Alliance, 33 Terminal Way, Suite 331, Pittsburgh, PA. auroras@ 123456gbapgh.org .

          3. LEED AP ND. Green Building Alliance, 33 Terminal Way, Suite 331, Pittsburgh, PA. seanl@ 123456gbapgh.org .

          4. 2030, Inc. / Architecture 2030. 936 N. 34th St. Ste 408, Seattle, WA 98103 and Sante Fe, NM. martinez@ 123456architecture2030.org .

          5. LEED Green Associate. Green Building Alliance, 33 Terminal Way, Suite 331, Pittsburgh, PA. isaacs@ 123456gbapgh.org .

          Article
          jgb.9.4.79
          10.3992/1943-4618-9.4.79
          ©2014 by College Publishing. All rights reserved.
          Page count
          Pages: 26
          Product
          Categories
          INDUSTRY CORNER

          Comments

          Comment on this article