Household Waste Production and Categorization in Grahamstown, Eastern Cape Final Report Group 1 Authors: Bridget Nkoana (G12N1746) Francina Teffo (G11T2942) Luke Maingard (G12M0104) Slie Sithole (G11S1371) Stuart Biesheuvel (G11B2242) Tadiwanashe Dune (G12D2893) Tanya Kuhlmann (G12K0431) Environmental Science Department
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Household Waste Production and Categorization in Grahamstown, Eastern
CapeFinal Report
Group 1
Authors:
Bridget Nkoana (G12N1746)
Francina Teffo (G11T2942)
Luke Maingard (G12M0104)
Slie Sithole (G11S1371)
Stuart Biesheuvel (G11B2242)
Tadiwanashe Dune (G12D2893)
Tanya Kuhlmann (G12K0431)
Environmental Science Department3 rd October 2014
Word Count: 6,779
ABSTRACT 4
1) INTRODUCTION 4
1.1) Waste Generation of Households 5
1.2) Waste Composition of Households 5
2) KEY QUESTIONS, HYPOTHESES AND OBJECTIVES 6
2.1) Key Questions and Hypotheses 6
2.2) Objectives 7
3) STUDY AREA 7
4) METHODOLOGY 10
4.1) Data Collection and Analyses 10
4.2) Data Collection and Analyses 11
4.3) Assumptions and Pitfalls 13
5) RESULTS 14
5.1) Persons Per Household in Each of the Three Study Sites 14
5.2) Average Total Waste for a Household in Each Study Site 15
5.3) Waste Composition 16
5.4) Levels of Recycling and Sorting 17
5.5) Average Total Waste Per Household Size 18
5.6) Environmental Awareness 19
5.7) Education Level 20
6) DISCUSSION 21
6.1) The Influence of Social-Economic Factors on the Amount of Household Waste Being Produced 21
6.2) The Influence of Peoples Perceptions, Attitudes, and Practices on Waste Production 23
6.3 Conclusion and Recommendations 256.3.1 Concluding statement 256.3.2 Improvements and Suggestions For Future Research 26
6.4) Recommendations 26
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REFERENCE LIST: 29
PLAGIARISM STATEMENT 32
TURN-IT-IN REPORT 33
Abstract
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Municipal household solid waste production and categorisation has become a predominant
issue of public concern in both South Africa and at a global scale (Browne, 2001). Socio-
economic and demographic factors such as globalisation, population growth, unemployment
and rapid urbanisation have influenced the production of municipal solid waste (Browne,
2001; Bolaane and Ali, 2004). The study was conducted in Grahamstown, Eastern Cape.
Income, education, household size and environmental awareness were the variables used to
determine their influence on waste production and categorisation. A questionnaire survey and
a ‘sort’ and ‘weigh’ technique was used to acquire the data. Three socio-economic areas were
sampled resulting in a total of 96 houses. The five categories focused on were for sorting and
weighing were paper, glass, plastic, metal, and organic waste. Two statistical tests were used
to analyse the data; an ANOVA one-way analysis of variance test and multiple linear
regressions.
The results show that high-income areas produce the least waste (2.64 kg) compared to
medium-income (6.81 kg) and low-income (6.6 kg). The results between household size and
levels of waste produced showed there was no statistical difference. Also, there was no
statistical difference between the amount of waste a person produces, and their level of
environmental awareness. The results showed that a statistical difference was only found
between a person with primary education (2.24 kg) and a person with secondary education
(1.47 kg). Our hypothesis was that socio-economic factors, perceptions and practices do
influence waste production. However, many of the results deviated from the anticipated
expectations. It was found that an increased number of factors are needed in future research
to establish a sound, definitive conclusion of what exactly affects waste production.
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1) Introduction
Municipal solid waste production has become a predominant issue of public concern in South
Africa and at a global scale (Browne, 2001). Socio-economic and demographic factors such
as globalisation, population growth, unemployment, and rapid urbanisation contribute to the
excessive production of municipal solid waste (Browne, 2001; Bolaane and Ali, 2004). In
general, the higher the state of economic development and the rate of urbanisation the greater
the quantity of solid waste produced (World Bank, 2012). Moreover, with increasing
revenues the consumption of goods and services, living standards, and the amount of waste
produced increases (Van Beukering et al., 1999).
Waste production at a household scale is an important aspect to waste management and
categorisation. This project has focused on some of the key aspects that may influence waste
production and categorisation such as: location (socio-economic class), income, household
size, education levels, practices, attitudes, and perceptions.
1.1) Waste generation of households
The current waste production levels at a global scale amount to 1.3 billion tonnes per year
with 3 billion residents producing approximately 1.2 kg per person per day (World Bank,
2012). However with rapid urbanization urban populations are anticipated to increase further
by 1.3 billion to 4.3 billion residents by 2025. Consequently waste generation trends will also
increase from 1.2 to 1.42 kg per person per day by 2025 whilst annual waste generation levels
increase to 2.2 billion tonnes respectively (World Bank, 2012). With these increases, more
waste dumps will need to be created, resulting in more land being used and more pollution
will be produced and released.
In Africa, household waste generation is estimated to range between 0.4 to 1.1 kg per day,
spanning into 2.4 kg per day in urban areas and much lower in poorer residential areas
(World Bank, 2012). This can be attributed to various socio-economic statuses, such as
income status of different households as seen in a study that was done by the World Bank
(2012) and the Palmer Development Group (1996). In the Palmer Development Group study
(1996) it was found that there is a direct relationship between socio-economic groupings such
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as household income and waste production, hence waste generation was considered a
function of affluence.
1.2) Waste composition of households
Household waste composition in developing countries is mainly composed of 57% organic
material, paper 9%, plastic 13%, glass and metals 8%, and other elements of waste 13%
(World Bank, 2012). According to the Palmer Development Group (1996), waste production
from high-income and medium-income households reflect that of developed countries whilst
that from low-income households reflects that of developing countries. In this regard, high-
income earning households tend to produce more packaging waste such as paper and plastics.
This is due to the fact that high-income and medium-income households tend to buy more
pre-cooked foods which consequently have a relatively high disposable packaging content
than the low-income earning households and informal areas who often prepare every basic
meal at home (Bolaane and Ali, 2004).
The challenge regarding waste in South Africa is waste classification. One of South Africa’s
challenges is identifying and categorizing household waste (Karani and Jewasikiewitz, 2007).
There are laws and regulations implemented to address this challenge, however many of the
laws are not implemented because of the lack of knowledge of them. The South African
National Waste Management Strategy has been developed to address the gaps in general
waste classification and household waste generation (Karani, and Jewasikiewitz, 2007).
2) Key Questions, Hypotheses and Objectives
2.1) Key questions and hypotheses
The first key question was how social-economic factors influenced the composition and
amount of household waste being produced. We hypothesized that the type and amount of
waste produced is a function of socio-economic status. We hypothesized this according to
Slack et al. (2005). There is a strong correlation between income level and waste production:
as people earn more, their consumption of electricity and foodstuffs increase resulting in
increased waste (Slack et al., 2005).
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Another relation to socio-economic status of households was that households that have a
medium to high-income rate tend to manage their waste products more efficiently compared
to that of lower-income households. Lower-income households cannot afford large amounts
of these goods and therefore wasted produce will be less (Cossu, 2013).
The second key question asked was whether people’s perceptions, attitudes and practices
influenced the waste produced. We hypothesized that people’s perceptions, attitudes, and
practices will influence waste production and the type of waste produced. The reason for this
hypothesis was based on the level of education and environmental awareness that an
individual had (Etengeneng, 2012). According to Etengeneng (2012), people that tend to have
had higher levels of education tend to have a more positive attitude and practice towards
waste management because of their increased knowledge on waste issues.
Thus people with higher levels of education and environmental awareness have proven to
have a more positive influence in waste production, sorting, and recycling (Parfitt et al.,
1994). Conversely people with a lower standard of education tend to have an ignorant or
oblivious view towards waste production and its impact on the ecosystem around them
(Parfitt et al., 1994).
2.2) Objectives
There are three objectives to be determined in the course of the year project. The first
objective was to determine which socio-economic factors influence waste production and
categorisation? This is a necessary objective, as it will assist in accepting or rejecting the first
hypothesis.
The second objective was to determine whether people’s attitudes, perceptions, and practices
affect waste production and categorisation? This provided an insight concerning the second
hypothesis (Parfitt et al., 1994). According to Parfitt et al. (1994) peoples’ attitude towards
waste issues have a large influence on the amount of waste they produce as well as how the
household manages waste produce.
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The last objective was to determine whether waste categorisation is a function of knowledge.
This will determine environmental awareness of an individual and the ecosystem around
them (Etengeneng, 2012).
3) Study Area
The study was conducted in Grahamstown, Eastern Cape, which is under the Makana
Municipality. Established in 1812, Grahamstown now has a population of approximately
50 000 people of which 73% are black, 12% are white, 14% are colored and 1% are
Indian/Asian (Makana Municipality, 2013). These demographics are shown in Figure 1 (Fox,
2012; Google Earth V6.2.2.6613, 2013). According to Statistic South Africa (2013) the
population is made up of 6.2% elderly people, 69.4% working age (15-64) people and 24.4%
of population is young (0-14).
Eastern Cape is one of the poorest provinces in South Africa, with a very low employment
rate of 32. 5% (Statistics South Africa, 2013). Grahamstown has 29% employed people, 42%
unemployed and 29% people which are not economically active (Statistics South Africa,
2013). According to Irvine (2012), 93.7% of citizens of the town who are 20 years and older
have completed primary school, 35.6% have completed secondary education, 22.9% have
completed Matric and 12% have some form of higher education. Irvine (2012) states that
only 6.3% people who are 20 years and older have no form of schooling. Makana
Municipality has 85.4% formal dwellings with an average household size of 3.4 people and
44.5% of households are female headed (Statistics South Africa, 2013). Socio-economic
status is a factor that contributes to where people are spatially located in area. (Irvine, 2012).
The geography and historical events of Grahamstown have been highly influential in the race
distribution (Irvine, 2012). Policies applied during the apartheid era such as the Group Areas
Act 41 of 1950 enforced segregation of different racial ethnicity (Figure 1) and as a result this
has shaped the past and present landscape of South Africa (Irvine, 2012). Irvine (2012) stated
that although a lot has changed spatially and politically, radical distinct economic and social
differences within geographical boundaries still reflect the colonial and apartheid legacy as
seen in Figure 1 (Irvine, 2012). Residential areas and schools remain tied to the apartheid’s
divisions of race (Irvine, 2012). For the purpose of the study three spatial sites related to
former segregation boundaries were selected (Figure 2). The sampling sites included Fingo
Village for low-income households, Hillsview for medium-income households, and lastly
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Somerset heights to represent the high-income households (Figure 2).
Figure 1: Map representing the different socio-economic classes of Grahamstown, Eastern Cape
during the apartheid (Fox, 2012; Google Earth V6.2.2.6613, 2013).