Leveraging Energy Disclosure Data to Better Understand the Role of Building Ownership Type in Energy Consumption
*Names in bold indicate Presenter
Findings in New York City thus far have highlighted surprising inconsistencies in the energy performance of some buildings. For instance, some fairly new properties that achieved a high Leadership in Energy and Environmental Design (LEED) rating from the United States Green Building Council consumed more energy than mid-1920’s non-LEED properties. This and other similar findings highlight the need for much further analysis to understand some of the nuanced and contextual factors that contribute to building-wide energy consumption. It also sheds light on the immense opportunity for researchers, as the benchmarking data is rich with information.
Although a few researchers (Hsu, 2012, 2014a, 2014b; Kontakosta, 2012; Kontokosta, 2013, 2014) are making important quantitative and analytical advancements with the New York City data, the data is understudied from a social science perspective. There are unique opportunities to approach disclosure data with a blend of both qualitative and quantitative methods to better understand context-specific consumption patters in a given city, neighborhood, or building type.
To that end, this paper explores the hypothesis that ownership type plays a role in overall building energy consumption, and, more specifically, it argues that cooperative buildings – due to specific organizational characteristics that are unique to this type of ownership organization – are particularly low energy consumers relative to other types of multifamily properties in New York City. It relies on quantitative analysis of the NYC disclosure data, which is merged with New York City tax lot and property data (PLUTO data), and new ownership variables created for this work. In addition, it relies on qualitative fieldwork such as survey and interview data in a small New York City cooperative building.
This work contributes to policy knowledge about building energy consumption. If cities and jurisdictions have a better sense of what this new disclosure data is indicating about the building stock, they will be able to better leverage the findings to gain the support of property owners and key stakeholders, and better meet carbon reduction goals and targets. In addition, this work highlights opportunities to approach “big data” resources such as energy disclosure metrics with a social science and qualitative research lens to gain more contextual insights.