DOES “ONLY TRASH LITTER?” : REVISITED
Cory L. Rhodes,
Department of Earth Sciences,
Keyword: litter, socioeconomic factors, census data.
Introduction:
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).
Research Question:
One of the main questions
associated
with the Dog River Watershed is “Who litters the most?”.
The hypothesis that I tested tries to answer this question based on
socioeconomic
factors such as educational attainment, labor force status, income,
age, race
and sex of nine communities near
Methods:
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
communities
from the original project to count, collect and tally the articles of
trash I
found along the street (away from commercial areas and main roads) for
a length
of 100 feet. I returned to the sites a week later to repeat the process
and
noted any decreases or increases in amount. Similar to Pounds’ paper,
the data
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
fact that
people in different communities have various education levels when it
comes to
understanding about the environment. I
then
performed the
The
Results:
After I gathered the data
and
preformed the
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:
The statistically
insignificant data
includes age, race and sex. In other words, these socioeconomic factors
have no
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
be accepted,
claiming that there is a relationship between educational attainment,
labor
force status, and socioeconomic status and the amount of litter
entering the
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
plausible reasons
why there are significance differences within these two socioeconomic
factors.
One could be that more Caucasians (as opposed to African Americans)
completed
the 2000 United States Census within a particular community or
communities as
opposed to the 1990 United States Census. This would result in a lower
level of
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
gathered from
this project would allow Dog River Clearwater Revival to target all
census
tracts (not just the ones studied) in relation to the
References Cited:
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.