Final Project: NYC Energy Star Scores
Motivation/Purpose
More and more people are migrating into cities and away from rural environments. This migration is likely to continue to increase as better technologies and economies develop. Pollution is a current and future issue, that needs to be accounted for when countries are developing cities. New York City is one of the most populated and advanced cities in the world. However, some of its building are old and consume massive amounts of energy and release enormous quantities of greenhouse gas emissions. Greenhouse gas emissions need to be monitored, as they destroy the Earth’s atmosphere, which increases global warming. The effects of global warming are both real and severe, which is why it is important for cities to develop in a way that reduces greenhouse gas emissions. Rating systems and certifications for buildings are becoming more abundant in today’s world. Energy Star is one rating system that is supposed to indicate the sustainability level/ environmentally friendliness of a building. This project will investigate the relationships between Energy Star ratings and greenhouse gas emissions in NYC. Other factors will also be looked at such as specific location, year constructed and specific energy usages.
Scientific Question
I will investigate the correlation between Energy Star ratings of buildings and the buildings’ reported greenhouse gas emissions in New York City. The goal is to discover if Energy Star ratings are a legitmate indication of the sustainability of a building.
Data Sources:
Data set content: List of Variables in the data set separated by semi-colons
Property Id; Property Name; Parent Property Name; BBL-10 digits; NYC Borough; Address 1; Address 2; Postal Code; Street Number; Street Name; Borough; DOF Gross Floor Area; Primary Property Type; List of All Property Use Types at Property; Largest Property Use Type; Second Larges Property Use Type; Third Largest Property Use Type; Year Build; Number of Buildings; Occupancy; Metered Areas (Energy); Metered Areas (Water); Energy Star Score; Site EUI; Weather Normalized Site EUI; Weather Normalized Site Electricity Intensity; Weather Normalized Site Nature Gas Intensity; Weather Normalized Source EUI; Fuel Oil 1 Use; Fuel Oil 2 Use; Fuel Oil 5 & 6 Use; Diesel 2 Use; District Steam Use; Natural Gas Use; Weather Normalized Site Natural Gas Use; Electricity Use – Grid Purchase; Weather Normalized Site Electricity; Total GHG Emissions; Direct GHG Emissions; Indirect GHG Emissions; Property GFA – Self Reported; Water Use; Source EUI; Release Date; Water Required?; Zip Code
Number of rows and columns:
There are 11,746 rows and 60 columns.
Units associated with values
Gross Floor Area – (ft^2) EUI – (kBtu/ft^2) Electricity Intensity – (kWh/ft^2) Natural Gas Intensity – (therms/ft^2) Oil Use – (kBtu) Natural Gas Use – (kBtu) Natural Gas Use – (Therms) Electricity Use – Grid Purchase – (kBtu) Site Electricity – (kWh) GHG Emissions – (Metric Tons CO2e) Water Use – (kgal)
Summary of Data
The summary table below shows the min, median and max of the variables used in the data set.
## Energy_STAR_Score Total_GHG_Emission Direct_GHG_Emission
## Min. : 1.00 Min. : 0 Min. : 0.0
## 1st Qu.: 36.00 1st Qu.: 338 1st Qu.: 161.9
## Median : 65.00 Median : 504 Median : 272.8
## Mean : 59.46 Mean : 2570 Mean : 759.3
## 3rd Qu.: 85.00 3rd Qu.: 912 3rd Qu.: 434.2
## Max. :100.00 Max. :4764456 Max. :2627015.0
## Indirect_GHG_Emission DOF_Gross_Floor_Area Parent_Property_Name
## Min. : -23134 Min. : 50028 Length:7770
## 1st Qu.: 96 1st Qu.: 64744 Class :character
## Median : 172 Median : 90174 Mode :character
## Mean : 1811 Mean : 168202
## 3rd Qu.: 445 3rd Qu.: 156270
## Max. :4764375 Max. :13540113
## Year_Built Borough Latitude Longitude
## Min. :1600 Length:7770 Min. :40.52 Min. :-74.23
## 1st Qu.:1926 Class :character 1st Qu.:40.70 1st Qu.:-73.98
## Median :1937 Mode :character Median :40.76 Median :-73.96
## Mean :1947 Mean :40.75 Mean :-73.96
## 3rd Qu.:1965 3rd Qu.:40.82 3rd Qu.:-73.93
## Max. :2019 Max. :40.91 Max. :-73.74Energy Star Score: Histogram
Interactive Map
#Total Green House Gas Emission vs. DOF Floor Area Hard to draw conclusions, likely need to rescale.
Total Green House Gas Emission vs. DOF Floor Area
Rescales with x log. From the graph below, it can be concluded that as the floor area of buildings increase, the amount of green house gas emissions produced increases. It can also be noted that the buildings with low Energy Star Scores (red) produce more GHG emission than buildings with higher Energy Star Scores.
Total Green House Gas Emission v.s. Borough with Average Indicated
From the graphs below it can be seen that Manhattan produces much more GHGs than the other boroughs, as the other boroughs are much farther below the average total GHG line. 
Total GHG Emissions vs. Year Built (Decade)
Normalized Total GHG Emmisions v.s. Decade
From the interactive boxplot below, it does not appear the amount of GHG emitted is not decreasing substantially. However, because it is a log scale this is hard to see visually. Therefore, although the Energy Star rating may accurately be rating the building it may not be encouraging building owners to release less GHGs.
Total average green house gas emission compared to 1950
By using 1950 as a baseline of the average total greenhouse gas emissions produced in 1950, we can begin to determine if total emissions have risen or fallen since then. As the graph below illustrates, emissions appear to peak around 1970 and have since decreased. However, emission levels are still above the 1950 base line.
Changes in Direct and Indirect Emmisions
The graphs below may indicate that the amount of direct GHG emissions is decreasing as time goes on. However, the trend line appears to fluctuate and does not decrease at a substantial slope.
Conclusion
Jason Barr did a similar analysis on New York City apartment buildings. He found that as the area of a building increases so does the amount of CO2 emissions. Specifically, he found that a 10% increase in building area results in an increase in emissions of about 7.1%. This corresponds to the analysis above; however, Barr also notes that on a person by person basis this increase in building size reduces the average carbon footprint of each occupant. Barr concludes that if you increase a building by one floor the average increase in CO2 emissions is 1.9%. He does note this is slightly misleading in the sense that building one more floor on a 10-floor building causes a greater increase in emissions than building one more floor on a 20-floor building. Furthermore, he states that to increase the height of building it must become skinnier which also varies the area. Barr’s analysis is interesting and should be reviewed as well as this analysis (link in sources).
One fact that Jason Barr mentions is that a Bank of America Tower in Midtown received Platinum LEED Certification (another sustainability certification, similar concept as Energy Star Ratings), the highest rating, but three years later it was found that the building was one of the highest emitters of CO2 in New York City. Therefore, it is important to analyze the data because ratings may be misleading. My analysis does suggest that Energy Star Ratings do rate more sustainable buildings higher for the most part. It is also important not only to rate the buildings, but to improve them after they are rated. Luckily, the NYC government is creating new regulations that should lower greenhouse gas emissions and improve the city’s sustainability.
New York City is home to almost one million buildings in an area of about 300 square miles. This is not a lot of space for a lot of building, which is a cause for concern if emissions are to rise. Buildings are responsible for about 70% of citywide greenhouse gas emissions. Therefore, improving the sustainability of buildings is crucial for the future environment of NYC. The City does have a plan in place with a goal to reduce GHG emissions by 35% by 2025 with a baseline from 2005. Systems like Energy Star may help reach this goal by informing building owners of their current emission levels and advising them on more sustainable practices.
As time progress more and more people will begin to live and work in cities. New York City is a hub for economic growth and technological advancements and is looked to for inspiration. This being the case, it is important for NYC to demonstrate that growth and development can occur while simultaneously acting in a sustainable way. Having a rating system like Energy Star is a good way to clearly show building owners the negative effects their buildings can have on the environment. From the analysis above, it appears that the Energy Star Score does accurately indicate how sustainable a building is in terms of its greenhouse gas emission. However, it does not appear that there has been a substantial decrease in the amount of greenhouse gasses that are being emitted from NYC buildings. This is a problem because if emissions do not decrease we will continue to see the negative effects of global warming. That damages all corners of the world and all plants, animals and humans.
Sources
The data set comes from NYC OpenData. Excel -> CSV
Data
The data set name is: “Energy and Water Data Disclosure for Local Law 84 2017 (Data for Calendar Year 2016)”
Calgary, Open. NYC Open Data, data.cityofnewyork.us/Environment/Energy-and-Water-Data-Disclosure-for-Local-Law-84-/8u86-bviy.
Literature
Barr, Jason. “Building Height and Greenhouse Gas Emissions in New York City.” Building the Skyline, 31 May 2018, buildingtheskyline.org/building-height-and-co2/.
“Figure 2f from: Irimia R, Gottschling M (2016) Taxonomic Revision of Rochefortia Sw. (Ehretiaceae, Boraginales). Biodiversity Data Journal 4: e7720. Https://Doi.org/10.3897/BDJ.4.e7720.” doi:10.3897/bdj.4.e7720.figure2f.