Month: May, 2017
HOW HAS CITYWIDE MULTIFAMILY ENERGY CONSUMPTION CHANGED?
In a recent blog post, we explored how energy consumption varies geographically across New York City using the publicly disclosed Local Law 84 data from 2015. In this follow-up, we look at how energy use has changed in the years that the benchmarking law has been in place. Using publicly disclosed data for the last four years and data provided by the NYC Office of Sustainability for the first two, we are able to assess how the law continues to shape New York City buildings for the better.
Data Cleaning Methodology
In this analysis, we use weather-normalized Source EUI1 as calculated by Energy Star’s Portfolio Manager software, which will just be referred to as “EUI” in the remainder of the blog. Given that the first year’s data (2010) reduces the overall dataset size by over half and is the most suspect in terms of data quality, we opt to instead include only the last five years of energy disclosure data. In addition, we require that buildings have a valid EUI for each of the last five years and remove buildings that vary in their reported square footage by more than 10% between any two years or in their EUI by more than 60%, either of which would indicate that a data entry error is likely. We also remove the top and bottom 1% of EUIs from all years pooled together. This leaves a total of 2,282 multifamily buildings in our dataset.
Change in Median Source EUI
After cleaning the data, we analyze the change in the median EUI over the last five years (see figure below), fitting it with an ordinary least squares regression. The best fit model implies a decrease in the median EUI of 1.3 kBTU/sqft/yr each year (or 1%/year), with a total decrease in EUI of 5.2 kBTU/sqft/yr over the full 5 years. This linear model has an adjusted r² value of 0.75, indicating a robust fit.
This change in the median EUI can be thought of as how much the average building population is changing its consumption overall. We can also look at the median change in EUI from 2011 to 2015 (6.0 kBTU/sqft/yr or 4.6% over the five-year span), which is more representative of how a typical building has changed over those five years.
Table 1 shows the median EUI for each year. It is important to note that these values vary somewhat from those published in NYC’s Benchmarking reports as the former are derived only from buildings with valid data in all five years.
Table 1. Median Source EUI from 2011-2015
Looking Across All Six Years
If we instead include all six years of data, the decrease in median EUI is a bit larger (1.7 kBTU/sqft/yr/yr), but as noted before, this reduces the overall dataset size by more than half to only 808 buildings. The histogram below shows the distribution of 2015 EUIs for three different data subsets, as well as the median for each subset (vertical dashed lines):
- Buildings with data in years 2012-2015
- Buildings with data in years 2011-2015 (the dataset used throughout this blog)
- Buildings with data in all 6 years
While there is not a large difference in the total number or distribution of EUIs for the first two groups, the subset including only buildings with data in all six years has a much higher median EUI for the overlapping five years (127.8 vs 124.4 for 2015), meaning that buildings that complied in the first year have on average higher EUIs than those that didn’t.
Comparing the Change for the Best and Worst Buildings
We can also see the shift in the EUI over the last five years by looking at the change in the normalized EUI distribution with time. The figure below displays the normalized EUI distribution (from a Kernel-density estimate) for each year, showing that the EUI distribution becomes narrower with a lower median EUI over time.
In order to confirm that this trend is not just year-to-year noise in building consumption, we want to see that the worst buildings are improving significantly and the best buildings are not getting worse. We can see this is the case in Table 2, which shows the median 2011 and 2015 EUIs of buildings in the 1st, 2nd, 3rd and 4th quartiles of buildings from the 2011 data.
Table 2. Change in Median Source EUI for 2011 Quartiles
|2011 Median Source EUI (kBTU/sqft/yr)||2015 Median Source EUI (kBTU/sqft/yr)||2011 to 2015 EUI % Difference|
While the buildings in the best quartile have increased their usage by 2%, the remaining 3/4 of buildings have improved, with the worst quartile of buildings decreasing their usage by 10% – suggesting that overall, buildings in NYC are improving.
This reduction in energy consumption can also be evaluated with a paired t-test, comparing the distributions of EUIs in 2011 and 2015, which returns a p-value of 6×10−28, indicating that the distributions of EUIs in those two years are statistically distinct.
Excluding the Impact of Hurricane Sandy
Thus far in this analysis, we have not compensated for the effects of Hurricane Sandy which cut out power to many areas in NYC for weeks in 2012. In the figure below, we remove areas with prolonged outages (Red Hook, The Rockaways and Lower Manhattan) from the dataset and compare the EUI trend between that set and our main dataset.
The ‘Sandy-corrected’ group, which omits heavily affected areas, shows the same trend of decreasing EUI over time, albeit with an even steeper slope (1.45 kBTU/sqft/yr vs 1.3 kBTU/sqft/yr). The median EUI for each year is also slightly lower for the Sandy-corrected group (see Table 3), likely because buildings in lower Manhattan have relatively high EUIs (see interactive map in the following section).
Table 3. Median Source EUI for Sandy-corrected Data
|Median Source EUI
|Median Source EUI
ARE ALL PARTS OF NYC IMPROVING?
We can also explore how this yearly change in EUI varies geographically. Are all boroughs and neighborhoods in NYC improving at the same pace? Are some still getting worse?
2011-2015 Median Source EUI by Community District
The maps below show the median EUI for each NYC community district for each year from 2011 to 2015 as well as the absolute and % difference from 2011 to 2015. You can click on the tabs at the top of the map to switch years, and hover over a community district to see the median EUI and number of buildings.
From these maps we can see that energy consumption has decreased in most regions, and in those districts for which it has increased, there are often less than 10 or 20 buildings included in the dataset, indicating those numbers are likely not as reliable. On average, however, Brooklyn and Queens have improved the most with a median 2011 to 2015 decrease in EUI of 6.6% and 7.1%, whereas Manhattan and the Bronx have only improved by 3.9% and 2.5%, respectively.
WHAT ABOUT THE IMPACT OF LOCAL LAW 87?
From these maps we can see that on average most areas of NYC are decreasing their energy consumption, but we expect to see an even larger decrease for properties that have had to comply with Local Law 87 (requires a building undergo an ASHRAE level II energy audit and subsequent implementation of recommended retro-commissioning measures every 10 years).
Comparison of Properties with and without LL87 Submission
In the figure below we compare NYC buildings that had to comply with Local Law 87 in 2013 and 2014 (based on the block number) with those that did not. While the Local Law 87 buildings have around the same median EUI in the first four years (prior to and during the audit and retro-commissioning period), there appears to be a larger decrease in consumption for those buildings in 2015. Presumably, as data from additional years comes in, these buildings should continue to show improved performance.
ARE BENCHMARKED BUILDINGS BECOMING MORE EFFICIENT?
Based on this analysis of Local Law 84 benchmarking disclosure data from the last five years, energy consumption is decreasing in large multifamily buildings across the city at a rate of 1% per year (or 4% over five years). This is an encouraging trend! Our analysis is similar to the finding from NYC’s most recent Energy and Water Use Report, which reported a 5% decrease in energy consumption for multifamily buildings from 2010 to 2013. While the results differ slightly, it is based on data from different years, and as seen in this blog, the data cleaning process can have a large impact on the overall result, as including or excluding a certain year’s data can significantly change the composition of the dataset.
To summarize, the analysis here suggests that the worst buildings are improving the most, and buildings in Brooklyn and Queens are improving more quickly than those in Manhattan and the Bronx. Data for the most recent year also indicates that buildings complying with Local Law 87 have an even larger decrease in EUI than the rest of the large multifamily building population. Stay tuned as data from subsequent years could strengthen this trend. It’s important to stress that although NYC’s multifamily buildings have been decreasing their energy consumption since the implementation of Local Law 84, there could be many reasons for this besides merely the effect of benchmarking. These may include the effects of Local Law 87, energy prices, building code changes, the phasing out of fuel oil, incentive programs and the cost of rent. On the other hand, a recent paper published by the National Electrical Manufacturers Association (NEMA), suggests that a majority of NYC large multifamily building managers are changing their operating practices and making capital investments in energy efficiency as a result of energy benchmarking. A more detailed analysis could explore the effects of these different factors on the energy consumption trend.
Whatever the myriad reasons for the decrease in energy consumption, this is an ongoing process, which the city needs to continue monitoring each year. Building owners can play their part by tracking their buildings’ consumption on a monthly basis. We all have a role to play and we cannot be passive (unless it’s passive house!) about our actions. Stay tuned for a more detailed analysis from the City, the Urban Green Council and CUSP. If this post has sparked any ideas, interest or questions, please reach out!
1 It is worth noting that in the previous blog post exploring Local Law 84 data, we chose to use Site EUI, since that metric is more representative of how energy is being used at a building, and the goal of that exploration was to compare trends in building characteristics and energy consumption. In this analysis, however, we are using Source EUI, since weather normalized Site EUI is not available in all six years of disclosure data.