I chose to look at what locations in Maine had the highest median levels of arsenic and flouride in their private wells. I started by looking at the top 20 locations with the highest median levels of arsenic. We can see that the first three towns (Manchester, Gorham, and Manmouth) had median arsenic levels at or above 10ug/L, which is Maine’s Maximum Exposure Guideline for arsenic.
Then, I charted the top 20 locations in Maine that had the highest median levels of flouride. Maine’s Maximum Exposure Guideline for flouride is 2 mg/L and we can see from the chart that there were no locations with median flouride levels that were at or above that threshold. Finally, I combined the top 20 lists for both arsenic and flouride median levels and found three locations that ranked in the top 20 in each of those categories. The three locations are:
Surry
Rome
Millinocket
I am currently taking environmental health, so I was curious about the health effects of arsenic in particular. This report contains a lot of relevant information on arsenic in Maine. Maine’s bedrock structure, makes arsenic more prevalent in Maine than in other states without as much bedrock. This is because arsenic is a “naturally occuring metalloid released into the groundwater through the weathering of bedrock.” The report also talks about the issues and concerns of arsenic exposure including skin, bladder, and lung cancer.
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(tidyr)
library(rmarkdown)
arsenic_data <- read.csv("arsenic.csv", header = TRUE, stringsAsFactors = FALSE)
flouride_data <- read.csv("flouride.csv", header = TRUE, stringsAsFactors = FALSE)arsenic_median <-(arsenic_data) %>% select(location, median) %>% arrange(desc(median))%>% rename(arsenic_median =median) %>% head(20)
arsenic_median## location arsenic_median
## 1 Manchester 14.00
## 2 Gorham 10.50
## 3 Monmouth 10.00
## 4 Columbia 9.80
## 5 Eliot 9.70
## 6 Hallowell 8.60
## 7 Winthrop 8.20
## 8 Columbia Falls 8.10
## 9 Mariaville 7.20
## 10 Readfield 7.20
## 11 Blue Hill 7.00
## 12 Litchfield 7.00
## 13 Millinocket 6.80
## 14 Buxton 6.00
## 15 Surry 6.00
## 16 Rome 5.50
## 17 Orland 5.40
## 18 Hollis 5.25
## 19 Belgrade 5.25
## 20 Scarborough 5.20flouride_median <- (flouride_data) %>% select(location, median) %>% arrange(desc(median)) %>% rename (flouride_median=median) %>% head(20)
flouride_median## location flouride_median
## 1 Eastbrook 1.290
## 2 Otis 1.130
## 3 Marshfield 1.000
## 4 Dedham 0.940
## 5 Surry 0.800
## 6 Prospect 0.785
## 7 Fryeburg 0.760
## 8 Mercer 0.600
## 9 Stockton Springs 0.600
## 10 Rome 0.600
## 11 Ellsworth 0.500
## 12 Millinocket 0.495
## 13 Charlotte 0.490
## 14 Stoneham 0.490
## 15 Denmark 0.450
## 16 Smithfield 0.450
## 17 Casco 0.445
## 18 Chesterville 0.440
## 19 Otisfield 0.440
## 20 Lovell 0.435flouride_median %>% inner_join(arsenic_median) ## Joining, by = "location"## location flouride_median arsenic_median
## 1 Surry 0.800 6.0
## 2 Rome 0.600 5.5
## 3 Millinocket 0.495 6.8