-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy path14-Conclusion.Rmd
109 lines (100 loc) · 9.73 KB
/
14-Conclusion.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
# Conclusion
This analysis evaluated alternative environmental justice community criteria, comparing them to the benchmark environmental justice criteria used by Massachusetts between 2010 - 2016. The evaluations considered increasing the Minority criterion from 25% to 30% and 50%, and also adding modifiers to the existing criteria, such that no community can be classified as an environmental justice community if its income exceeds 125% of the statewide median household income, or if the adult population with a college degree exceeds 50%. Geographically, adding more stringent criteria results in "lost" environmental justice classifications primarily in the eastern third of the state, and primarily within the I-495 belt. In order to compare these policy implications, the number and proportion of lost environmental justice classifications were considered with regard to whether or not they occurred within the wealthiest fifth of municipalities. These results are summarized in the table below.
```{r conclusion, echo=FALSE, message=FALSE, warning=FALSE, fig.cap="Table 1. Environmental Justice Policy Criteria Compared"}
library(kableExtra)
# Calculate summary vectors to put in summary table
# 2010 EJ Policy
EJ2010pct <- round(sum(blkgrp_shp_WGS84$CRITCNT2010 > 0) / nrow(blkgrp_shp_WGS84) * 100,1)
EJ2010insidePct <- round(sum(inside2010$inside)/sum(blkgrp_shp_WGS84$CRITCNT2010 > 0)*100,1)
# 2017 EJ Policy
EJ2017pct <- round(sum(blkgrp_shp_WGS84$CRITCNT > 0) / nrow(blkgrp_shp_WGS84) * 100,0)
EJ2017insidePct <- round(sum(inside2017$inside)/sum(blkgrp_shp_WGS84$CRITCNT > 0)*100,1)
# Alternative Policy A
EJAltAlost <- sum(blkgrp_shp_WGS84$LOSEJ_min30)
EJAltApct <- round(sum(blkgrp_shp_WGS84$CRITCNT_min30 > 0) / nrow(blkgrp_shp_WGS84) * 100,1)
# EJAltAlostW <- sum(lost30$lost)
# EJAltAinside <- sum(inside30$inside)
EJAltAinsidePct <- round(sum(inside30$inside)/sum(blkgrp_shp_WGS84$CRITCNT_min30 > 0)*100,1)
EJAltAlostWpct <- round(sum(lost30$lost) / sum(blkgrp_shp_WGS84$LOSEJ_min30) * 100,1)
# Alternative Policy B
EJAltBlost <- sum(blkgrp_shp_WGS84$LOSEJ_min50)
EJAltBpct <- round(sum(blkgrp_shp_WGS84$CRITCNT_min50 > 0) / nrow(blkgrp_shp_WGS84) * 100,1)
# EJAltBlostW <- sum(lost50$lost)
EJAltBinsidePct <- round(sum(inside50$inside)/sum(blkgrp_shp_WGS84$CRITCNT_min50 > 0) * 100,1)
EJAltBlostWpct <- round(sum(lost50$lost) / sum(blkgrp_shp_WGS84$LOSEJ_min50) * 100,1)
# Alternative Policy C
EJAltClost <- sum(blkgrp_shp_WGS84$LOSEJ_inc125)
EJAltCpct <- round(sum(blkgrp_shp_WGS84$CRITCNT_inc125 > 0) / nrow(blkgrp_shp_WGS84) * 100,1)
# EJAltClostW <- sum(lost125$lost)
EJAltCinsidePct <- round(sum(inside125$inside)/sum(blkgrp_shp_WGS84$CRITCNT_inc125 > 0) * 100,1)
EJAltClostWpct <- round(sum(lost125$lost) / sum(blkgrp_shp_WGS84$LOSEJ_inc125) * 100,1)
# Alternative Policy D
EJAltDlost <- sum(blkgrp_shp_WGS84$LOSEJ_inc125pctColl)
EJAltDpct <- round(sum(blkgrp_shp_WGS84$CRITCNT_inc125pctColl > 0) / nrow(blkgrp_shp_WGS84) * 100,1)
# EJAltDlostW <- sum(lost125_50$lost)
EJAltDinsidePct <- round(sum(inside125_50$inside)/sum(blkgrp_shp_WGS84$CRITCNT_inc125pctColl > 0) * 100,1)
EJAltDlostWpct <- round(sum(lost125_50$lost) / sum(blkgrp_shp_WGS84$LOSEJ_inc125pctColl) * 100,1)
# Alternative Policy E
EJAltElost <- sum(blkgrp_shp_WGS84$LOSEJ_m25inc125)
EJAltEpct <- round(sum(blkgrp_shp_WGS84$CRITCNT_m25inc125 > 0) / nrow(blkgrp_shp_WGS84) * 100,1)
# EJAltElostW <- sum(lostm25125$lost)
EJAltEinsidePct <- round(sum(insidem25125$inside)/sum(blkgrp_shp_WGS84$CRITCNT_m25inc125 > 0) * 100,1)
EJAltElostWpct <- round(sum(lostm25125$lost) / sum(blkgrp_shp_WGS84$LOSEJ_m25inc125) * 100,1)
# Alternative Policy F
EJAltFlost <- sum(blkgrp_shp_WGS84$LOSEJ_m30inc125)
EJAltFpct <- round(sum(blkgrp_shp_WGS84$CRITCNT_m30inc125 > 0) / nrow(blkgrp_shp_WGS84) * 100,1)
# EJAltFlostW <- sum(lostm30125$lost)
EJAltFinsidePct <- round(sum(insidem30125$inside)/sum(blkgrp_shp_WGS84$CRITCNT_m30inc125 > 0) * 100,1)
EJAltFlostWpct <- round(sum(lostm30125$lost) / sum(blkgrp_shp_WGS84$LOSEJ_m30inc125) * 100,1)
# Alternative Policy G
EJAltGlost <- sum(blkgrp_shp_WGS84$LOSEJ_m25inc150)
EJAltGpct <- round(sum(blkgrp_shp_WGS84$CRITCNT_m25inc150 > 0) / nrow(blkgrp_shp_WGS84) * 100,1)
# EJAltGlostW <- sum(lostm25150$lost)
EJAltGinsidePct <- round(sum(insidem25150$inside)/sum(blkgrp_shp_WGS84$CRITCNT_m25inc150 > 0) * 100,1)
EJAltGlostWpct <- round(sum(lostm25150$lost) / sum(blkgrp_shp_WGS84$LOSEJ_m25inc150) * 100,1)
# Alternative Policy H
EJAltHlost <- sum(blkgrp_shp_WGS84$LOSEJ_m30inc150)
EJAltHpct <- round(sum(blkgrp_shp_WGS84$CRITCNT_m30inc150 > 0) / nrow(blkgrp_shp_WGS84) * 100,1)
# EJAltHlostW <- sum(lostm30150$lost)
EJAltHinsidePct <- round(sum(insidem30150$inside)/sum(blkgrp_shp_WGS84$CRITCNT_m30inc150 > 0)*100,1)
EJAltHlostWpct <- round(sum(lostm30150$lost) / sum(blkgrp_shp_WGS84$LOSEJ_m30inc150) * 100,1)
# Alternative Policy I
EJAltIlost <- sum(blkgrp_shp_WGS84$LOSEJ_m40_m25inc150)
EJAltIpct <- round(sum(blkgrp_shp_WGS84$CRITCNT_m40_m25inc150 > 0) / nrow(blkgrp_shp_WGS84) * 100,1)
# EJAltIlostW <- sum(lostm40_m25inc150$lost)
EJAltIinsidePct <- round(sum(insidem40_m25inc150$inside)/sum(blkgrp_shp_WGS84$CRITCNT_m40_m25inc150 > 0) * 100,1)
EJAltIlostWpct <- round(sum(lostm40_m25inc150$lost) / sum(blkgrp_shp_WGS84$LOSEJ_m40_m25inc150) * 100,1)
# Alternative Policy J
EJAltJlost <- sum(blkgrp_shp_WGS84$LOSEJ_m40_m25Muninc150)
EJAltJpct <- round(sum(blkgrp_shp_WGS84$CRITCNT_m40_m25Muninc150 > 0) / nrow(blkgrp_shp_WGS84) * 100,1)
# EJAltJlostW <- sum(lostm40_m25Muninc150$lost)
EJAltJinsidePct <- round(sum(insidem40_m25Muninc150$inside)/sum(blkgrp_shp_WGS84$CRITCNT_m40_m25Muninc150 > 0) * 100,1)
EJAltJlostWpct <- round(sum(lostm40_m25Muninc150$lost) / sum(blkgrp_shp_WGS84$LOSEJ_m40_m25Muninc150) * 100,1)
# Create vectors for table variables and contents
Policy <- c("2010-16","2017","Alt A","Alt B","Alt C","Alt D", "Alt E", "Alt F", "Alt G", "Alt H", "Alt I", "Alt J")
Change <- c("None","None",
"Minority >= 30%",
"Minority >= 50%",
"Income <= 125%",
"Income <= 125% & College <= 50%",
"Minority >= 25% & Income <= 125%",
"Minority >= 30% & Income <= 125%",
"Minority >= 25% & Income <= 150",
"Minority >= 30% & Income <= 150",
"Minority >= 40% OR (Minority >= 25% & Income <= 150%)",
"Minority >= 40% OR (Minority >= 25% & MuniIncome <= 150%)")
PctEJPop <- c(EJ2010pct,EJ2017pct,EJAltApct,EJAltBpct,EJAltCpct,EJAltDpct,EJAltEpct,EJAltFpct,EJAltGpct,EJAltHpct,EJAltIpct,EJAltJpct)
LostEJ <- c(NA,NA,EJAltAlost,EJAltBlost,EJAltClost,EJAltDlost,EJAltElost,EJAltFlost,EJAltGlost,EJAltHlost,EJAltIlost,EJAltJlost)
# LostWealthy <- c(NA,NA,EJAltAlostW,EJAltBlostW,EJAltClostW,EJAltDlostW,EJAltElostW,EJAltFlostW,EJAltGlostW,EJAltHlostW,EJAltIlostW,EJAltJlostW)
LostWealthyPct <- c(NA,NA,EJAltAlostWpct,EJAltBlostWpct,EJAltClostWpct,EJAltDlostWpct,EJAltElostWpct,EJAltFlostWpct,EJAltGlostWpct,EJAltHlostWpct, EJAltIlostWpct,EJAltJlostWpct)
InWealthyPct <- c(EJ2010insidePct,EJ2017insidePct,EJAltAinsidePct,EJAltBinsidePct,EJAltCinsidePct,EJAltDinsidePct,EJAltEinsidePct,EJAltFinsidePct,EJAltGinsidePct,EJAltHinsidePct,EJAltIinsidePct,EJAltJinsidePct)
# Assemble the table
finalResults <- data.frame(Policy,Change,PctEJPop,LostEJ,LostWealthyPct,InWealthyPct)
# Display the table
kable(finalResults, col.names = c("Policy", "Change", "EJ Pop %", "EJ Lost", "Lost Wealthy %", "In Wealthy %")) %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive")) %>%
column_spec(2, width = "20em")
```
All of the policy alternatives considered in this analysis result in a reduction in the number and percentage of Census block groups in Massachusetts that are classified as environmental justice communities relative to the 2010-16 Environmental Justice policy (see "EJ Pop %" column in table above). Moreover, in all cases, at least one-fifth of the "lost" environmental justice classifications come from the wealthiest municipalities; those in the top quintile of median household income (see "Lost Wealthy %" column in table above), which results in a reduction in the percentage of environmental justice classified block groups that are within those wealthy communities (see "In Wealthy %" column in table above). The latter address the issue of environmental justice designations that occur in communities not typically associated with environmental injustices. However, there are significant differences in the impacts and efficiency of these alternatives.
Alternative Policy B results in the greatest reduction in the number of environmental justice classifications ("EJ Lost") relative to the 2010 base comparison policy, but Alternative Policy B is relatively inefficient because only a small percentage of these lost EJ classifications - 19.9% - come from the wealthiest communities. This means that 80% of the lost environmental justice classifications come from less wealthy municipalities, which carries the risk that some communities are likely inappropriately declassified. By contrast, Alternative Policy J results in the fewest number of total lost environmental justice classifications relative to the 2010 base comparison policy, and 100% of these lost environmental justice classifications come from the wealthiest communities; the most efficient alternative.
Policy J offers the most "efficient" implications, removing only those environmental justice designations which occur in wealthy communities where one would not expect to find environmental justice issues, while maintaining a relatively low residual percentage of environmental justice designations that continue to persist in those same communities. Overall, Environmental Justice Policy J achieves the objective of reducing inappropriately classified block groups as environmental justice communities while avoiding the inappropriate declassification of deserving environmental justice communities.