TITLE:
Diversifying Clean Water: An Examination of Drinking Water Quality and Social Disparities in Michigan
AUTHORS:
Tyra Blair, Ryan Beni, Sujata Guha
KEYWORDS:
Water Quality, Social Disparity, Michigan, Contaminants, Household Income, Income per Capita, Environmental Justice, Automobile Industry
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.10 No.5,
May
30,
2022
ABSTRACT: Water is one of the most essential resources
required to sustain life. However, it could be detrimental to the health of
those without access to water that is properly treated. Although the Safe
Drinking Water Act of 1974 set regulations to protect citizens from naturally
occurring and man-made contaminants, some people are still without clean and
safe water, which is speculated to be because of their race. This research
examines the disproportionality of available clean water provided by government
sources in Michigan and its correlation with race and household income. In the
study, it has been found that one of the leading causes of water contamination
is industrial activity, with the automobile industry being responsible for
approximately 300 million tons of lead contamination in water, and that the
manufacturing company’s locations mostly centered in minority and
low-income areas. Lower income cities, such as Hamtramck and Benton Harbor,
have an average of 14.8 drinking water standard violations with the highest
being 99 total violations, while higher income cities, like Novi and Bloomfield
hills, have an average of 4 violations. Cities, like Flint and Detroit, which
have a higher minority population, are 10 times more likely to have a water
standard violation, and the minority population is proportionally related to
the possibility of industrial manufacturing being located in those areas. These
communities also face a higher risk of birth defects, developmental issues in
children, and organ failure in adults, due to continuous exposure to water contaminants.
Race as a direct causation could not be proven, but there are links to direct
correlation through historical redlining and housing trends.