DOES “ONLY TRASH LITTER?” : REVISITED
Cory L. Rhodes,
Department of Earth Sciences,
Keyword: litter, socioeconomic factors, census data.
Litter has become a major environmental problem and, according to a Harris national poll, 94 percent of Americans believe that something should be done to curb pollution (Harper 2004). However, “according to the EPA, the average human has doubled his production of garbage since 1960, producing 4.5 pounds a day. So it is no surprise that we have serious littering and dumping problems” (Rea 2005). Over 80% of litter found in watersheds and surrounding creeks, rivers, and streams results from debris found on land (www.watershedwatch.net).
This raises questions about how litter enters into the watershed and, more importantly, who’s to blame. The primary result of litter entering the watershed is excessive rainfall resulting in runoff on land. According to the Merriam-Webster Collegiate Dictionary, runoff is defined as “the portion of precipitation on land that ultimately reaches streams often with dissolved or suspended material” (1993).
Social and demographic characteristics are other extremely important factors that come into play. Research assumes that less educated, predominantly older male adults living in areas not impacted by environmental hazards are the primary culprits for excessive littering (Harper 2004). However, this assumption is not a very powerful one. By utilizing census data, this paper will determine the socioeconomic factors that are the primary cause of litter and help educate the community on ways they can preserve the watershed. A good understanding of watersheds will develop participatory solutions in protecting the watershed (Randhir & Cole 2005).
One of the main questions
with the Dog River Watershed is “Who litters the most?”.
The hypothesis that I tested tries to answer this question based on
factors such as educational attainment, labor force status, income,
and sex of nine communities near
To go about testing this hypothesis, I gathered the tools I needed to begin the project: I acquired a map of Mobile County with the communities designated (2000 Census Tract Map) and also acquired statistical census tract data from the United States Census Bureau on basic socioeconomic factors in nine separate communities in Mobile County (2000 U.S. Census Bureau—General Housing, Social, and Economic Characteristics for Census Tracts and Block Numbering Area). A census tract is defined as “a small, relatively permanent statistical subdivision of a county” usually consisting of a few blocks (www.ffiec.gov). The nine communities I gathered my data in (Figure 1) include neighborhoods between: Knollwood Drive and University Boulevard South (census tract/ block numbering area 37.07), Airport Boulevard and Montlimar Street (33.01), Airport Boulevard and Downtowner Boulevard (32.04), Cottage Hill Road and Michael Boulevard (32.05), Government Street and Johnston Avenue (24), McVay Drive North and Interstate 10 (22), South Broad Street and St. Francis Street (2), Arlington Street and Virginia Street (13.02), and Bayfront Road and Hannon Road (18) (United States Census Bureau 2000).
I revisited these nine
from the original project to count, collect and tally the articles of
found along the street (away from commercial areas and main roads) for
of 100 feet. I returned to the sites a week later to repeat the process
noted any decreases or increases in amount. Similar to Pounds’ paper,
collected was then placed into an Excel
table and divided into three intervals based on educational attainment (Table
1). This factor was chosen as a comparison to litter due to the
people in different communities have various education levels when it
understanding about the environment. I
After I gathered the data
There is a slight indirect relationship between percent white and litter (-0.167) (Figure 5) and percent female and litter (-0.167) (Figure 6). However, there is a slight direct relationship between age and litter with a result of 0.090 (Figure 7).
Discussion and Conclusion:
includes age, race and sex. In other words, these socioeconomic factors
effect on littering amounts in a particular area. The
statistically significant factors include educational
attainment, labor force status and income. These factors do have an
effect on litter
in the environment. Therefore, the hypothesis can
claiming that there is a relationship between educational attainment,
force status, and socioeconomic status and the amount of litter
There are differences between a few of the socioeconomic factors and litter within the original and current projects. These include significance differences between race and labor force status and litter. Pounds’ project showed statistically significant data results between race and litter while the current study shows a statistically insignificant result between the two. Inversely, labor force is shown to be statistically insignificant within Pounds’ project while the current study shows this socioeconomic factor to be statistically significant with litter.
There are numerous
why there are significance differences within these two socioeconomic
One could be that more Caucasians (as opposed to African Americans)
the 2000 United States Census within a particular community or
opposed to the 1990 United States Census. This would result in a lower
probability (lower level of significance) within the
The current project shows statistically significant relationship between educational attainment and income and litter. A reason for this may be that some of the communities comprising low educational attainment cannot afford proper resources in order to clean litter and debris from neighborhood streets and walkways. As stated in Pounds’ discussion, those neighborhoods that contain higher amounts of educated peoples and incomes can afford maintenance crews for litter pickup and are aware of the consequences that litter has on the environment (2003). However, based on the data from the 2000 Census, the majority of persons who completed the form were of relatively low educational attainment and income therefore resulting in the insignificant statistical relationships.
The data and results
this project would allow Dog River Clearwater Revival to target all
tracts (not just the ones studied) in relation to the
Federal Financial Institutuion Examination Council (FFIEC). Home Mortgage Disclosure Act. HMDA Glossary. http://www.ffiec.gov/hmda/glossary.htm
Harper, Charles L. (2004). “Environment and Society: Human Perspectives on Environmental Issues”. Third Edition. Que Corporation, 391.
“Littering Is Throwing It All Away”. Watershed Watch. <http://www.watershedwatch.net>.
Merriam-Webster Collegiate Dictionary. 10th edition. (1993). Merriam-Webster, Incorporated.
“Mobile County, Alabama”. Reference Maps. United States Census Bureau. American Factfinder (2000). <http://factfinder.census.gov>.
Pounds, Tammy. (2003). Does “Only Trash Litter”? <http://www.usouthal.edu/geography/fearn/480page/03Pounds/03Pounds.htm>.
Randhir, Timothy & Genge, Cole. (2005, Apr. ). Watershed Based, Institutional Approach to Developing Clean Water Resources. Journal of the American Water Resources Association, 41, 2, 413-424.
Rea, Kimberly. (2005, Sept. ). “Trash nation: learn how to prevent your public lands from being trashed”. Parks and Recreation.