by Rachel Kim and Liv Crowley
Last updated on 4/30/23
for Data Visualization for Allwith Prof. Jack DoughertyTrinity College, Hartford CT, USA
Hartford Area BIPOC and low-income residents have been facing environmental racism for decades. Landfills are located around census tracts that typically have lower median household income earnings and higher percentages of racial diversity. This led us to answering the question of proving whether race and median household income in specific Hartford county census tracts play a role in where trash facilities are located. We decided to find the percentage of people in each census tract that identified as white, in order to show the correlation between census tract demographics and where trash disposal is the most prevalent. To display the information, we designed choropleth maps to show how lower income and racially diverse neighborhoods are typically closer to waste facilities than white, upper class neighborhoods. Choropleth maps work well in displaying trends between census tracts.
When researching the connection between race and median household income, and where trash facilities are located, it is evident that lower-income and racially diverse census tracts typically surround trash faciltiies. Inequitable patterns regarding the location of trash facilities promote environmental racism. Therefore, it is critical to highlight these patterns in order to recognize racial and economic inequities, as well as to spread awareness as to where trash goes.
Environmental racism is still prevalent throughout Hartford county. Neighborhoods surrounding waste facilities generally have lower percentages of white people than census tracts located further away. Compared to the ‘Median Household Income of Each Census Tract in Hartford County,’ census tracts that are lower-income also typically tend to be more racially diverse. For example, census tracts surrounding MIRA have low percentages of white residents, one even as low as a whopping 7.13%. However, towns such as Granby, East Granby, Canton, Simsbury and Avon seem to have a population of over 90% white residents. The data shows how neighborhoods that are further away from the waste facilities are predominantly white, and areas close to the waste facilities have more racial diversity. The white suburban privilege is an ongoing example of environmental racism that so many Hartford county residents face.
Figure 1: Explores the percentage of individuals who identify as white in Hartford County Census Tracts.
Wealth disparities are accentuated through the locations of various trash facilities. The map claims that trash facilities are located in lower-income, racially diverse neighborhoods. The majority of the census tracts surrounding the Materials Innovation and Recycling Authority (MIRA) facility (which is no longer operating) have a median household income that ranges between around 20k-50k. Many of the census tracts surrounding the Newington landfill also fall below a 50k median household income. Wealthier, predominantly white towns such as Avon, Canton, and South Windsor are not located near a waste disposal center.
Figure 2: Shows the median household income of each census tract in Hartford County.
The race of Hartford county citizens is deeply correlated with the median household incomes. The trend line of the scatter plot chart shows that census tracts with a higher percentage of individuals who identify as white typically have more wealth than census tracts with more BIPOC citizens. Residents who live in both lower-income areas and identify as BIPOC are at an extremely high risk of facing environmental racism and other racial and economic inequities. Racism and wealth inequalities are related to the locations of trash faciltiies.
Figure 3: Shows the relationship between race and median household income of each Hartford county census tract.
The data used was the median household income and race data relative to Hartford county from Social Explorer. The data was based on the American Community Survey (ACS) 2017-2021 Estimates. Once downloaded, we created a Google Sheet of each data set, and cleaned up the census tract column. Next, we used Datawrapper to link the Google Sheet and began building the visual to display our data in a clear and concise way. We altered the format so that the map was more viewer-friendly, and added in several Map Labels and Text Annotations. The Map Labels we inserted were of each town in Hartford county, so that the viewer could have points of relativity when viewing the waste facilities and census tracts. The Text Annotations we added were of some of the waste facilities in Hartford county. We created a title that we believed accurately conveyed the data, and added in a description and data source.
Throughout creating the data story, we did face a few challenges. One of our most difficult challenges was forgetting to have the race/ethnicity data display percentages, instead of numbers. We had trouble figuring out how to display the data in percentages, and the map we had originally created was inaccurate. It displayed the total number of people in each census tract that identified as a particular race, rather than a percentage based on total population. In an effort to make our data story more accurate, we chose to re-download data from Social Explorer that displayed percentages, and only use the percentages of people who identify as white in our map. This way, the census tract data is clearer to the viewer, and does a better job at highlighting environmental racism and white privilege. Another challenge we faced was with correctly using the ‘index’ tab on Github to add in our findings, and working on the Github presentation jointly. At times, we would forget that one of us was working on it, and one of our changes would get deleted.
"American Community Survey (ACS) 2017--2021 (5-Year Estimates). Race" Social Explorer, https://www.socialexplorer.com/tables/ACS2021_5yr/R13357923. Accessed 17 April 2023.
“American Community Survey (ACS) 2017--2021 (5-Year Estimates). Median Household Income” Social Explorer, https://www.socialexplorer.com/reports/socialexplorer/en/report/dbd75914-dd80-11ed-a389-639962a7f178. Accessed 17 April 2023.
Dougherty, Jack, and Ilya Ilyankou. “On Data Visualization.” Hands, https://HandsOnDataViz.org/. Accessed 17 April 2023.