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Boston: College power plants that emit excessive carbon pollution¶

US EPA FLIGHT tool - Get Data¶

  • Browse to a State: Mass
  • Pick a Metro Area: Boston-Cambridge-Newton
  • Filter By: Emission Range (filtered): 25000 min
  • Sector: Filter Sectors (filtered): Other > Universities
  • List > Export Data
  • Excel: delete row 1-5 inclusive
  • Excel: delete row 6-7 inclusive
  • Excel: save as csv
In [129]:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
In [130]:
%config Completer.use_jedi = False
In [131]:
pd.options.display.max_columns = None
In [132]:
raw_data = pd.read_csv("flight.csv")
In [133]:
df_prep = raw_data.copy()
In [134]:
df_prep.head()
Out[134]:
FACILITY GHGRP ID REPORTED ADDRESS LATITUDE LONGITUDE CITY METRO AREA NAME STATE ZIP CODE PARENT COMPANIES SUBPARTS TOTAL REPORTED EMISSIONS, 2011 TOTAL REPORTED EMISSIONS, 2012 TOTAL REPORTED EMISSIONS, 2013 TOTAL REPORTED EMISSIONS, 2014 TOTAL REPORTED EMISSIONS, 2015 TOTAL REPORTED EMISSIONS, 2016 TOTAL REPORTED EMISSIONS, 2017 TOTAL REPORTED EMISSIONS, 2018 TOTAL REPORTED EMISSIONS, 2019 TOTAL REPORTED EMISSIONS, 2020 TOTAL REPORTED EMISSIONS, 2021 CHANGE IN EMISSIONS (2020 TO 2021) CHANGE IN EMISSIONS (2011 TO 2021) SECTORS
0 Boston University 1002274 120 Ashford Street 42.35395 -71.12204 Boston Boston-Cambridge-Newton, MA-NH MA 2134 TRUSTEES OF BOSTON UNIVERSITY (100%) C 53,903 44,367 44,797 49,319 50,937 51,247 43,986 50,356 43,827 37,558 47,622 10,064 -6,281 Other
1 MIT Central Utility Plant 1001289 59 VASSAR ST 42.36110 -71.09340 CAMBRIDGE Boston-Cambridge-Newton, MA-NH MA 2139 MASSACHUSETTS INSTITUTE OF TECHNOLOGY (100%) C 141,908 137,864 140,448 145,000 141,797 128,376 106,789 131,470 123,487 111,369 131,848 20,479 -10,060 Other
2 NORTHEASTERN UNIVERSITY 1005277 360 HUNTINGTON AVENUE 42.34012 -71.08933 BOSTON Boston-Cambridge-Newton, MA-NH MA 2115 NORTHEASTERN UNIVERSITY (100%) C 30,348 31,573 33,735 31,160 31,316 28,985 30,011 30,846 29,883 27,380 27,139 -241 -3,209 Other
3 The President and Fellows of Harvard Universit... 1000656 46 Blackstone Street 42.36360 -71.11610 Cambridge Boston-Cambridge-Newton, MA-NH MA 2139 PRESIDENT & FELLOWS OF HARVARD COLLEGE (100%) C 74,824 64,839 69,223 69,798 69,309 80,210 79,996 82,860 83,227 73,613 76,533 2,920 1,709 Other
In [135]:
df_prep.shape
Out[135]:
(4, 25)
In [136]:
list(enumerate(df_prep.columns))
Out[136]:
[(0, 'FACILITY'),
 (1, 'GHGRP ID'),
 (2, 'REPORTED ADDRESS'),
 (3, 'LATITUDE'),
 (4, 'LONGITUDE'),
 (5, 'CITY'),
 (6, 'METRO AREA NAME'),
 (7, 'STATE'),
 (8, 'ZIP CODE'),
 (9, 'PARENT COMPANIES'),
 (10, 'SUBPARTS'),
 (11, 'TOTAL REPORTED EMISSIONS, 2011'),
 (12, 'TOTAL REPORTED EMISSIONS, 2012'),
 (13, 'TOTAL REPORTED EMISSIONS, 2013'),
 (14, 'TOTAL REPORTED EMISSIONS, 2014'),
 (15, 'TOTAL REPORTED EMISSIONS, 2015'),
 (16, 'TOTAL REPORTED EMISSIONS, 2016'),
 (17, 'TOTAL REPORTED EMISSIONS, 2017'),
 (18, 'TOTAL REPORTED EMISSIONS, 2018'),
 (19, 'TOTAL REPORTED EMISSIONS, 2019'),
 (20, 'TOTAL REPORTED EMISSIONS, 2020'),
 (21, 'TOTAL REPORTED EMISSIONS, 2021'),
 (22, 'CHANGE IN EMISSIONS (2020 TO 2021)'),
 (23, 'CHANGE IN EMISSIONS (2011 TO 2021)'),
 (24, 'SECTORS')]
In [137]:
df_prep.drop(columns= df_prep.columns[[10,22,23,24]], inplace=True)
df_prep.head()
Out[137]:
FACILITY GHGRP ID REPORTED ADDRESS LATITUDE LONGITUDE CITY METRO AREA NAME STATE ZIP CODE PARENT COMPANIES TOTAL REPORTED EMISSIONS, 2011 TOTAL REPORTED EMISSIONS, 2012 TOTAL REPORTED EMISSIONS, 2013 TOTAL REPORTED EMISSIONS, 2014 TOTAL REPORTED EMISSIONS, 2015 TOTAL REPORTED EMISSIONS, 2016 TOTAL REPORTED EMISSIONS, 2017 TOTAL REPORTED EMISSIONS, 2018 TOTAL REPORTED EMISSIONS, 2019 TOTAL REPORTED EMISSIONS, 2020 TOTAL REPORTED EMISSIONS, 2021
0 Boston University 1002274 120 Ashford Street 42.35395 -71.12204 Boston Boston-Cambridge-Newton, MA-NH MA 2134 TRUSTEES OF BOSTON UNIVERSITY (100%) 53,903 44,367 44,797 49,319 50,937 51,247 43,986 50,356 43,827 37,558 47,622
1 MIT Central Utility Plant 1001289 59 VASSAR ST 42.36110 -71.09340 CAMBRIDGE Boston-Cambridge-Newton, MA-NH MA 2139 MASSACHUSETTS INSTITUTE OF TECHNOLOGY (100%) 141,908 137,864 140,448 145,000 141,797 128,376 106,789 131,470 123,487 111,369 131,848
2 NORTHEASTERN UNIVERSITY 1005277 360 HUNTINGTON AVENUE 42.34012 -71.08933 BOSTON Boston-Cambridge-Newton, MA-NH MA 2115 NORTHEASTERN UNIVERSITY (100%) 30,348 31,573 33,735 31,160 31,316 28,985 30,011 30,846 29,883 27,380 27,139
3 The President and Fellows of Harvard Universit... 1000656 46 Blackstone Street 42.36360 -71.11610 Cambridge Boston-Cambridge-Newton, MA-NH MA 2139 PRESIDENT & FELLOWS OF HARVARD COLLEGE (100%) 74,824 64,839 69,223 69,798 69,309 80,210 79,996 82,860 83,227 73,613 76,533
In [138]:
df_prep.dtypes
Out[138]:
FACILITY                           object
GHGRP ID                            int64
REPORTED ADDRESS                   object
LATITUDE                          float64
LONGITUDE                         float64
CITY                               object
METRO AREA NAME                    object
STATE                              object
ZIP CODE                            int64
PARENT COMPANIES                   object
TOTAL REPORTED EMISSIONS, 2011     object
TOTAL REPORTED EMISSIONS, 2012     object
TOTAL REPORTED EMISSIONS, 2013     object
TOTAL REPORTED EMISSIONS, 2014     object
TOTAL REPORTED EMISSIONS, 2015     object
TOTAL REPORTED EMISSIONS, 2016     object
TOTAL REPORTED EMISSIONS, 2017     object
TOTAL REPORTED EMISSIONS, 2018     object
TOTAL REPORTED EMISSIONS, 2019     object
TOTAL REPORTED EMISSIONS, 2020     object
TOTAL REPORTED EMISSIONS, 2021     object
dtype: object
In [139]:
df_prep.rename(columns = lambda x: x.replace("TOTAL REPORTED EMISSIONS, ", ""), inplace=True)
In [140]:
df_prep.head()
Out[140]:
FACILITY GHGRP ID REPORTED ADDRESS LATITUDE LONGITUDE CITY METRO AREA NAME STATE ZIP CODE PARENT COMPANIES 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
0 Boston University 1002274 120 Ashford Street 42.35395 -71.12204 Boston Boston-Cambridge-Newton, MA-NH MA 2134 TRUSTEES OF BOSTON UNIVERSITY (100%) 53,903 44,367 44,797 49,319 50,937 51,247 43,986 50,356 43,827 37,558 47,622
1 MIT Central Utility Plant 1001289 59 VASSAR ST 42.36110 -71.09340 CAMBRIDGE Boston-Cambridge-Newton, MA-NH MA 2139 MASSACHUSETTS INSTITUTE OF TECHNOLOGY (100%) 141,908 137,864 140,448 145,000 141,797 128,376 106,789 131,470 123,487 111,369 131,848
2 NORTHEASTERN UNIVERSITY 1005277 360 HUNTINGTON AVENUE 42.34012 -71.08933 BOSTON Boston-Cambridge-Newton, MA-NH MA 2115 NORTHEASTERN UNIVERSITY (100%) 30,348 31,573 33,735 31,160 31,316 28,985 30,011 30,846 29,883 27,380 27,139
3 The President and Fellows of Harvard Universit... 1000656 46 Blackstone Street 42.36360 -71.11610 Cambridge Boston-Cambridge-Newton, MA-NH MA 2139 PRESIDENT & FELLOWS OF HARVARD COLLEGE (100%) 74,824 64,839 69,223 69,798 69,309 80,210 79,996 82,860 83,227 73,613 76,533
In [141]:
df_prep.loc[:, "2011":] = df_prep.loc[:, "2011":].applymap(lambda x: x.replace(",", ""))
In [142]:
df_prep.head()
Out[142]:
FACILITY GHGRP ID REPORTED ADDRESS LATITUDE LONGITUDE CITY METRO AREA NAME STATE ZIP CODE PARENT COMPANIES 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
0 Boston University 1002274 120 Ashford Street 42.35395 -71.12204 Boston Boston-Cambridge-Newton, MA-NH MA 2134 TRUSTEES OF BOSTON UNIVERSITY (100%) 53903 44367 44797 49319 50937 51247 43986 50356 43827 37558 47622
1 MIT Central Utility Plant 1001289 59 VASSAR ST 42.36110 -71.09340 CAMBRIDGE Boston-Cambridge-Newton, MA-NH MA 2139 MASSACHUSETTS INSTITUTE OF TECHNOLOGY (100%) 141908 137864 140448 145000 141797 128376 106789 131470 123487 111369 131848
2 NORTHEASTERN UNIVERSITY 1005277 360 HUNTINGTON AVENUE 42.34012 -71.08933 BOSTON Boston-Cambridge-Newton, MA-NH MA 2115 NORTHEASTERN UNIVERSITY (100%) 30348 31573 33735 31160 31316 28985 30011 30846 29883 27380 27139
3 The President and Fellows of Harvard Universit... 1000656 46 Blackstone Street 42.36360 -71.11610 Cambridge Boston-Cambridge-Newton, MA-NH MA 2139 PRESIDENT & FELLOWS OF HARVARD COLLEGE (100%) 74824 64839 69223 69798 69309 80210 79996 82860 83227 73613 76533
In [143]:
df_prep.loc[:, "2011":] = df_prep.loc[:, "2011":].apply(pd.to_numeric)

/var/folders/d0/zf8g3jwx1r38bb54k6n7g8wr0000gn/T/ipykernel_24704/1148899735.py:1: FutureWarning: In a future version, `df.iloc[:, i] = newvals` will attempt to set the values inplace instead of always setting a new array. To retain the old behavior, use either `df[df.columns[i]] = newvals` or, if columns are non-unique, `df.isetitem(i, newvals)`
  df_prep.loc[:, "2011":] = df_prep.loc[:, "2011":].apply(pd.to_numeric)
In [144]:
df_prep.head()
Out[144]:
FACILITY GHGRP ID REPORTED ADDRESS LATITUDE LONGITUDE CITY METRO AREA NAME STATE ZIP CODE PARENT COMPANIES 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
0 Boston University 1002274 120 Ashford Street 42.35395 -71.12204 Boston Boston-Cambridge-Newton, MA-NH MA 2134 TRUSTEES OF BOSTON UNIVERSITY (100%) 53903 44367 44797 49319 50937 51247 43986 50356 43827 37558 47622
1 MIT Central Utility Plant 1001289 59 VASSAR ST 42.36110 -71.09340 CAMBRIDGE Boston-Cambridge-Newton, MA-NH MA 2139 MASSACHUSETTS INSTITUTE OF TECHNOLOGY (100%) 141908 137864 140448 145000 141797 128376 106789 131470 123487 111369 131848
2 NORTHEASTERN UNIVERSITY 1005277 360 HUNTINGTON AVENUE 42.34012 -71.08933 BOSTON Boston-Cambridge-Newton, MA-NH MA 2115 NORTHEASTERN UNIVERSITY (100%) 30348 31573 33735 31160 31316 28985 30011 30846 29883 27380 27139
3 The President and Fellows of Harvard Universit... 1000656 46 Blackstone Street 42.36360 -71.11610 Cambridge Boston-Cambridge-Newton, MA-NH MA 2139 PRESIDENT & FELLOWS OF HARVARD COLLEGE (100%) 74824 64839 69223 69798 69309 80210 79996 82860 83227 73613 76533
In [145]:
df_prep.dtypes
Out[145]:
FACILITY             object
GHGRP ID              int64
REPORTED ADDRESS     object
LATITUDE            float64
LONGITUDE           float64
CITY                 object
METRO AREA NAME      object
STATE                object
ZIP CODE              int64
PARENT COMPANIES     object
2011                  int64
2012                  int64
2013                  int64
2014                  int64
2015                  int64
2016                  int64
2017                  int64
2018                  int64
2019                  int64
2020                  int64
2021                  int64
dtype: object
In [146]:
df_prep.set_index(["FACILITY"])[df_prep.columns[-11:]].T.plot(figsize=(10,5))
Out[146]:
<AxesSubplot: >
In [147]:
df_prep["Cumulative"] = df_prep.loc[:, "2011":].sum(axis=1)
In [148]:
df_prep.head()
Out[148]:
FACILITY GHGRP ID REPORTED ADDRESS LATITUDE LONGITUDE CITY METRO AREA NAME STATE ZIP CODE PARENT COMPANIES 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Cumulative
0 Boston University 1002274 120 Ashford Street 42.35395 -71.12204 Boston Boston-Cambridge-Newton, MA-NH MA 2134 TRUSTEES OF BOSTON UNIVERSITY (100%) 53903 44367 44797 49319 50937 51247 43986 50356 43827 37558 47622 517919
1 MIT Central Utility Plant 1001289 59 VASSAR ST 42.36110 -71.09340 CAMBRIDGE Boston-Cambridge-Newton, MA-NH MA 2139 MASSACHUSETTS INSTITUTE OF TECHNOLOGY (100%) 141908 137864 140448 145000 141797 128376 106789 131470 123487 111369 131848 1440356
2 NORTHEASTERN UNIVERSITY 1005277 360 HUNTINGTON AVENUE 42.34012 -71.08933 BOSTON Boston-Cambridge-Newton, MA-NH MA 2115 NORTHEASTERN UNIVERSITY (100%) 30348 31573 33735 31160 31316 28985 30011 30846 29883 27380 27139 332376
3 The President and Fellows of Harvard Universit... 1000656 46 Blackstone Street 42.36360 -71.11610 Cambridge Boston-Cambridge-Newton, MA-NH MA 2139 PRESIDENT & FELLOWS OF HARVARD COLLEGE (100%) 74824 64839 69223 69798 69309 80210 79996 82860 83227 73613 76533 824432
In [149]:
import geopandas as gpd
In [150]:
geo_df = gpd.GeoDataFrame(df_prep, geometry=gpd.points_from_xy(df_prep["LONGITUDE"], df_prep["LATITUDE"]))
In [151]:
geo_df.head()
Out[151]:
FACILITY GHGRP ID REPORTED ADDRESS LATITUDE LONGITUDE CITY METRO AREA NAME STATE ZIP CODE PARENT COMPANIES 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Cumulative geometry
0 Boston University 1002274 120 Ashford Street 42.35395 -71.12204 Boston Boston-Cambridge-Newton, MA-NH MA 2134 TRUSTEES OF BOSTON UNIVERSITY (100%) 53903 44367 44797 49319 50937 51247 43986 50356 43827 37558 47622 517919 POINT (-71.12204 42.35395)
1 MIT Central Utility Plant 1001289 59 VASSAR ST 42.36110 -71.09340 CAMBRIDGE Boston-Cambridge-Newton, MA-NH MA 2139 MASSACHUSETTS INSTITUTE OF TECHNOLOGY (100%) 141908 137864 140448 145000 141797 128376 106789 131470 123487 111369 131848 1440356 POINT (-71.09340 42.36110)
2 NORTHEASTERN UNIVERSITY 1005277 360 HUNTINGTON AVENUE 42.34012 -71.08933 BOSTON Boston-Cambridge-Newton, MA-NH MA 2115 NORTHEASTERN UNIVERSITY (100%) 30348 31573 33735 31160 31316 28985 30011 30846 29883 27380 27139 332376 POINT (-71.08933 42.34012)
3 The President and Fellows of Harvard Universit... 1000656 46 Blackstone Street 42.36360 -71.11610 Cambridge Boston-Cambridge-Newton, MA-NH MA 2139 PRESIDENT & FELLOWS OF HARVARD COLLEGE (100%) 74824 64839 69223 69798 69309 80210 79996 82860 83227 73613 76533 824432 POINT (-71.11610 42.36360)
In [152]:
import folium
In [153]:
Boston_boundaries = gpd.read_file("cb_2022_25_sldl_500k/cb_2022_25_sldl_500k.shp")
In [154]:
Boston_boundaries.explore()
Out[154]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [155]:
base_layer = Boston_boundaries.explore(location=[42.35395, -71.12204], zoom_start=12, tooltip=False, width="60%", height="60%", style_kwds=dict(fillOpacity=0.1), highlight_kwds=dict(fillOpacity=0))

geo_df.explore(m=base_layer, column="Cumulative", marker_type="circle", marker_kwds=dict(radius=4828), cmap="autumn_r", popup=["FACILITY", "REPORTED ADDRESS", "Cumulative"], tooltip=False)
#base_layer.save("<SomeFilename>.html")

base_layer
Out[155]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [156]:
from folium.plugins import HeatMap

heatmap_points = [ [lat, long, weight] for lat, long, weight in zip(geo_df["LATITUDE"], geo_df["LONGITUDE"], geo_df["Cumulative"]) ]

map_layer = folium.Map(location=[42.35395, -71.12204], tiles="cartodbpositron", width="25%", height="25%", zoom_start=11)
HeatMap(heatmap_points, radius=15, blur=5).add_to(map_layer)
#map_layer.save("<SomeFilename>.html")

map_layer
Out[156]:
Make this Notebook Trusted to load map: File -> Trust Notebook