Rate and Quantities of Household Solid Waste Generated in Kampala City, Uganda.

Abstract

³ Pwani University College, Kilifi, Kenya
⁴ Department of Environmental Management,
College of Agriculture and Environmental Management,
Makerere University,
P.O.Box 7062, Kampala, Uganda
Abstract
The study concentrated on solid waste (SW) generation at households to
establish rate of generation, quantities and overall composition. Kampala
divisions were purposively stratified according to existing parishes. Areas
of data collection were further stratified into three income-groups of low,
middle and high using the quality of housing. Descriptive statistics of
Statistical Package for Social Scientists (SPSS) was then used to analyze the
data. Findings revealed that 846,155 kg/day of household SW was being
generated in Kampala at the rate of 0.56 kg/person/day. However, rates
of SW generation for the three income groups were respectively 0.29, 0.75
and 1.34 kg/person/day. Post-hoc tests of multiple comparisons revealed
significant differences in the mean values of household SW generated
between divisions. The average composition of household SW were 83.6%
vegetable / organic matter; 10.9% waste paper; 1.2% waste plastics; 0.3%
waste metals ; 0.1% glass / cullet materials and 3.9% other materials.
Keyword:Generation, household solid waste, rate, composition,
quantities.

Full text

Science Journal of Environmental Engineering Research
ISSN:2276-7495
http://www.sjpub.org/ sjeer.html
Published By
Science Journal Publication
International Open Access Publisher
Research Article
Rate and Quantities of Household Solid Waste Generated in Kampala City, Uganda
J.Ojok¹,M.K.Koech²,M.Tole³,J.OkotOkumu⁴
¹ Department of Chemistry, Faculty of Science,
Kyambogo University, P.O.Box 1, Kyambogo,
Kampala, Uganda
² Department of Environmental Education,
School of Environmental Studies,
Kenyatta University,
P.O.Box 43844, Nairobi, Kenya
³ Pwani University College, Kilifi, Kenya
⁴DepartmentofEnvironmentalManagement,
College of Agriculture and Environmental Management,
Makerere University,
P.O.Box 7062, Kampala, Uganda
Abstract
The study concentrated on solid waste (SW) generation at households to
establish rate of generation, quantities and overall composition. Kampala
divisions were purposively stratified according to existing parishes. Areas
of data collection were further stratified into three income-groups of low,
middle and high using the quality of housing. Descriptive statistics of
Statistical Package for Social Scientists (SPSS) was then used to analyze the
data. Findings revealed that 846,155 kg/day of household SW was being
generated in Kampala at the rate of 0.56 kg/person/day. However, rates
of SW generation for the three income groups were respectively 0.29, 0.75
and 1.34 kg/person/day. Post-hoc tests of multiple comparisons revealed
significant differences in the mean values of household SW generated
between divisions. The average composition of household SW were 83.6%
vegetable / organic matter; 10.9% waste paper; 1.2% waste plastics; 0.3%
waste metals ; 0.1% glass / cullet materials and 3.9% other materials.
Keyword:Generation, household solid waste, rate, composition,
quantities.
Introduction
The rapid increase in volumes and types of MSW as a result
of continuous economic growth, urbanization and
industrialization, is becoming a burgeoning problem for
national and local governments to ensure effective and
sustainable management of waste (UNEP, 2009). It was
estimated that in 2006 the total amount of MSW generated
globally reached 2.02 billion tones, representing a 7%
annual increase since 2003 (UNEP, 2009). It was further
estimated that between 2007 and 2011, global generation
of municipal waste will rise by 37.3%, equivalent to roughly
8% increase per year (UNEP, 2009).
Generation rates for Africa continent's major cities are
estimated to range from 0.3-1.4 kg per capita per day
(Achankeng, 1995). This gives an average of 0.78 compared
to an average of 1.22 kg per capita for developed countries
(Beukering et al., 1999). In Egypt, studies indicate that the
amount of MSW generated in urban areas is in the order of
24,000 tons per day and in rural areas about 11,000 tons
per day, adding up to 35,000 tons per day nationwide
(Palczynski, 2002). The garbage generation rate in Cairo is
9000 tones per day (Palczynski, 2002). In Nairobi, Kenya,
the total SW generated at present is estimated at 1530 tons
per day (Palczynski, 2002) and the SW composition
(percentage by volume) estimated by Nairobi City Council
(NCC) Environment Department in the year 2000 were:
combustibles 51.5%, metals 2.6%, paper 17.3%, glass 2.3%,
plastics 11.8% and others 14.5%.
Little documentation was done in the 1970's and 1980's
regarding MSWM in Uganda. According to available data, it
is evident that in the 1970's and 1980's garbage pile-ups
were not such a big problem as in the 1990's. The National
Environment Management Authority (NEMA) of Uganda
reported that SW generation rates in Uganda today vary
from one urban area to another due to factors such as
economic status of the population, social habits, season of
the year as well as the extent of salvage and recycling
operations (NEMA, Uganda, 2001). Whereas much of the
food consumed in the urban center comprised mainly of
cereals with little residues in the 1970's and early 1980's,
in recent periods the trend has changed. In Kampala, for
example, it was estimated that banana peelings, leaves and
other forms of organic matter accounted for 70-80% of SW
generated (Ngategize et al., 2001).
The average SW generation rate for Kampala was estimated
to be about 0.6 kg per capita per day, averaging about 900
tones of wastes per day (KCC, 2000). In another survey
carried out in Kampala by Environmental Resources
Limited, it was revealed that vegetable matter constituted
73.8% of the total SW generated while non-biodegradable
materials accounted for 5.6% (Walyawula, 2004).
Unfortunately, there is no data on the composition of
household SW in rural areas - it probably consists of more
organic matter than that of urban areas (Walyawula, 2004).
This study particularly assesses the rates and quantities of
household SW generation in Kampala city as an urban area.
Methodology
Study areas
The study was carried out in Kampala and concentrated on
the five administrative divisions of the City, (Central,
Kawempe, Makindye, Nakawa and Rubaga) shown in figure
1.
Volume 2013, Article ID sjeer-237, 6 Pages, 2012. doi: 10.7237/sjeer/237
Accepted 23 August, 2012
Corresponding Author:J. Ojok
Department of Chemistry, Faculty of Science, Kyambogo University, P.O.Box 1, Kyambogo, Kampala, Uganda
Email:ojokjulius08@gmail.com

Page 2 Science Journal of Environmental Engineering Research (ISSN:2276-7495)
Figure 1: Map of Africa showing Uganda and Kampala district administrative divisions (Source: UBOS, 2007)
A two-stage sampling technique was employed. The first
stage involved the use of purposive sampling techniques
whereby the Divisions were stratified according to already
existing parishes. The five divisions of Kampala had a total
of ninety nine (99) parishes in 2008 when the study was
carried out. To ensure maximum coverage, the parishes
were numbered clockwise, starting from the top in each
divisional map and odd number parishes were taken as
sampling units. The second stage involved stratifying the
areas of data collection in each of the five divisions of
Kampala city into three income groups of low, middle and
high using the quality of housing in the absence of any other
formal way of stratification and acknowledging the
problems of using proxies and unpublished information.
This step was very important because WTP for improved
SWM involves demand estimation, and its main determinant
was expected to be income.
In order to produce both quantitative and qualitative data,
a range of research methods covering questionnaires,
interviews, observations and document reviews was used
in the study (Layder, 1993). During sample data collection,
which took place between August 2008 and July 2009, the
Research Assistants would toss a coin in each parish to
decide on the direction to take during the sampling exercise.
A systematic sampling technique was then used whereby
every 3rd building in the selected parishes was sampled.
However, data collection was characterized by non
responses to some questions from households, thus a total
of 4015 households were sampled from all the five divisions
as indicated in table 1. This fairly large number of samples
was to cover up for the non responses.
The SPSS linear regression analyses using descriptive
statistics were carried out in the data management.
How to Cite this Article: OJ. Ojok , M.K. Koech , M. Tole, J.Okot-Okumu “Rate and Quantities of Household Solid Waste Generated in Kampala City, Uganda”Science Journal of
Environmental Engineering Research, Volume 2013, Article ID sjeer-237, 6 Pages, 2012. doi: 10.7237/sjeer/237

Science Journal of Environmental Engineering Research (ISSN:2276-7495) Page 3
Results and Discussions
Rate and quantity of Household SW generated
Table 2 shows the mean quantities of SW generated per
person per day in the households of Kampala city as a whole
and in each of the Divisions.
Table 2 revealed that Kampala currently has a mean
household SW generation of 0.56 kg/person/day, with
Rubaga division having the highest (0.74 kg/person/day),
followed by Nakawa (0.58 kg/person/day) and Central
(0.55 kg/person/day). The table further revealed that
Kawempe and Makindye divisions had similar rates of
household SW generation per person per day (0.50
kg/person/day, each). Rubaga division had the highest
mean overall household SW generation rate of .74
kg/person/day due to high density solid waste generated
in households and some commercial undertakings within
the household premises. The Division had many cottage
industries such as markets, restaurants, metal workshops,
wood workshops, motor vehicle workshops and other small
scale industrial undertakings, which produced high density
SW. The average rate of SW generation for Kampala had
earlier been estimated at 0.6 kg/person/day (KCC, 2000).
Findings for Central and Nakawa divisions were in
agreement with the earlier estimate, while those of
Makindye and Kawempe divisions were below and that of
Rubaga, above the estimate. However, despite the
variations, there are similarities in the daily activities of the
households in these divisions, the major occupation being
business. Makindye division, having a population of
405,300, (refer to the table in Appendix I) is the most
populated of the five divisions. The relatively low rate of
household SW generation in the division was probably due
to high household populations, resulting into fairly lower
standards of living in the households.
When post-hoc tests were carried out, the results of
Turkey HSD tests of multiple comparisons, shown in table
3, revealed significant differences in the mean values of SW
generated per person per day in the divisions of Makindye
and Rubaga (p<0.001), Makindye and Nakawa (p=0.005)
and no significant difference in the mean values for
Makindye and Kawempe (p=1.000) and Makindye and
Central (p=0.114). The mean value for Central division was
only significantly different from those of Rubaga (p<0.001)
but not significantly different from those of the other three
divisions. However the mean value for Rubaga was
significantly different from the mean values of all the other
four divisions (p<0.001 in each case). The mean value for
Kawempe division was significantly different from that of
Rubaga (p<0.001) and Nakawa (p=0.003) but not
significantly different from those of Makindye (p=1.000)
and Central (p=0.085. On the other hand the mean values
for Nakawa division was significantly different from those
of Makindye (p=0.005), Rubaga (p<0.001) and Kawempe
(p=0.003) divisions but not significantly different from
those of Central (p=0.842) division. The significant
differences in the mean values of SW generation per person
per day between divisions was probably due to the various
average incomes of the households in the Divisions,
resulting in varying lifestyles and consumption patterns.
Division Total Number of
Parishes
Number of
Parishes Sampled
Samples at 95%
CL
Households
Sampled
Central 20 10 379 776
Kawempe 22 11 383 1019
Makindye 21 11 383 790
Nakawa 23 14 383 660
Rubaga 13 8 383 770
Total 99 54 1911 4015
Table 1: The total samples obtained from the parishes per division at 95% confidence level( CL)
Division N Mean SW generated at the different income levels (kg/person/day)
Low Income Middle Income High Income Overall Mean
Makindye 766 ·3262 ·7288 1·2866 ·4957
Central 536 ·3058 ·7655 1·3650 ·5526
Rubaga 770 ·2701 ·7926 1·4176 ·7366
Kawempe 957 ·2554 ·7505 1·2337 ·4967
Nakawa 489 ·2986 ·7291 1·3292 ·5790
Total 3518 ·2905 ·7548 1·3366 ·5624
Table 2: Mean quantities of household SW generated per person per day in the individual
Divisions and Kampala as a whole.
How to Cite this Article: OJ. Ojok , M.K. Koech , M. Tole, J.Okot-Okumu “Rate and Quantities of Household Solid Waste Generated in Kampala City, Uganda”Science Journal of
Environmental Engineering Research, Volume 2013, Article ID sjeer-237, 6 Pages, 2012. doi: 10.7237/sjeer/237

Page 4 Science Journal of Environmental Engineering Research (ISSN:2276-7495)
From the population data for each division of Kampala
presented in Appendix I and mean quantities of SW
generated per person per day data in table 2, a summary
of the total quantity of SW generated in each division and
Kampala city as a whole for the year 2008 was presented
in table 4.
Division Significance at 0.5 level (p values)
Makindye Central Rubaga Kawempe Nakawa
Makindye – 0.114b 0.000c 1.000a ·0.005c
Central 0.114b – 0.000c 0.085b 0.842a
Rubaga 0.000c 0.000c – 0.000c 0.000c
Kawempe 1.000a 0.085b 0.000c – 0.003c
Nakawa 0.005c 0.842a 0.000c 0.003c –
Table 3: Turkey HSD multiple comparisons of mean values of solid waste generated per person
per day. Letters a and b denote no significant difference while c denotes significant difference.
Same letters denote similarity in the results.
Division Pop. in
2008
Rate of SW generation at the different income
levels and the Overall Mean (kg/person/day)
Quantity of SW
generated
Low
Income
Middle
Income
High
Income
Overall
Mean kg/day
kg/month
Central 109500 ·3262 ·7288 1·2866 0·5526 60510 1815300
Kawempe 326400 ·3058 ·7655 1·3650 0·4967 162123 4863690
Makindye 405300 ·2701 ·7926 1·4176 0·4957 200907 6027210
Nakawa 299500 ·2554 ·7505 1·2337 0·5790 173411 5202330
Rubaga 367400 ·2986 ·7291 1·3292 0·7366 270627 8118810
Total 1508100 ·2905 ·7548 1·3366 0·5624 848155 25444650
Table 4: Quantities (kg) and rate of household SW generated in Kampala in 2008
A total of 848,155 kg/day of household SW were generated
in Kampala in 2008 when the research was conducted. Of
this total, Rubaga, the second highest populated division in
Kampala, generated the highest quantity of 270,627
kg/day, followed by Makindye, the highest populated
division, with 200,907 kg/day. Nakawa, fourth highest
populated division ranked third with 173,411 kg/day while
Kawempe, the third highest populated division was fourth
with 162,123 kg/day and Central, the least populated
division, was last with 60,510 kg/day of SW. The
corresponding monthly quantities of SW generated per
division is indicated in the last column of table 4. A total of
25,445 tons/month of SW were being generated in
Kampala in 2008. Rubaga division generated the highest
quantity of household SW amounting to 8,119 tons/month
as a result of the high population and per capita SW
generation capacity. Makindye division was second with
6,027 tons/month mainly due to its high population. The
quantities of SW generated by Nakawa and Kawempe
divisions were similar (5,202 tons/month and 4,864
tons/month respectively) as their populations and per
capita SW generation capacities were also similar. Central
division generated the least amount (1,815 tons/month)
as it had the smallest population.
In general, SW generation rates in developing or
'low-income' countries average only 0.4 to 0.6
kg/person/day, as opposed to 0.7 to 1.8 kg/person/day in
fully industrialized countries (Cointreau-Levin, 1982). It
was noted that SW generation rates vary between
countries, cities and parts of cities in Africa, depending on
the rate of economic developments (Achankeng, 1995).
Generation rates for the Africa continent' s major cities
were estimated to range from 0.3-1.4 kg per capita per day
with an average of 0.78 compared to an average of 1.22 kg
per capita for developed countries (Achankeng, 1995).
Extreme cases may exist in both situations. According to
the World Resource data of 1998 - 1999, the per capita SW
generation (kg/day) in some selected African cities were
estimated as follows: Porto Novo, Benin - 0.5;
Ouagadougou, Bukina Faso -0.7; Bujumbura, Burundi - 1.4;
Younde, Cameroon - 0.8; Ibadan, Nigeria - 1.1; Kinshasha,
Democratic Republic of Congo - 1.2; Brazzaville, Congo
Republic - 0.6; Abidjan, Cote d'Ivoire - 1.0; Cairo, Egypt -
0.5; Banjul, Gambia - 0.3; Accra, Ghana - 0.4; Conakry,
Guinea - 0.7; Nouakchott, Mauritania - 0.9; Rabat, Morocco
- 0.6; Windhoek, Namibia - 0.7; Niamey, Niger - 1.0; Dakar,
Senegal - 0.7; Dar es Salaam, Tanzania - 1.0; Lome, Togo -
1.9; Tunis, Tunisia - 0.5 and Harare, Zimbabwe - 0.7
(Achankeng, 1995). Although extreme cases exist for the
Africa continent's major cities, the figures compare well
with the case of Kampala where the per capita per day is
0.56.
Composition of SW generated
The average composition of household SW generated in
Kampala are summarized in the pie chart in figure 2.
How to Cite this Article: OJ. Ojok , M.K. Koech , M. Tole, J.Okot-Okumu “Rate and Quantities of Household Solid Waste Generated in Kampala City, Uganda”Science Journal of
Environmental Engineering Research, Volume 2013, Article ID sjeer-237, 6 Pages, 2012. doi: 10.7237/sjeer/237

Science Journal of Environmental Engineering Research (ISSN:2276-7495) Page 5
Vegetable / organic matter was high in average composition
(83.6%). This mainly consisted of domestic peelings,
cuttings and other vegetable remains of food items such as
bananas, cassava, potatoes, cereals, waste food, leaf and
grass remains. In most cases, these vegetable / organic
matter were found to be mixed up with other assortments
of household SW. Waste paper ranked second in average
composition (10.9%). These mainly originated from
household business premises and offices. Wastes plastics
(1.2%), waste metals (0.3%) and glass / cullet materials
(0.1%) were in relatively smaller quantities. Other materials
(3.9%) were broken pots, enamels, containers other than
plastics and metals. Findings from this study were
consistent with the situation in the rest of Africa and other
developing countries. In Sri Lanka, for example, MSW has a
high content of organic matter, moderate content of plastics
and paper and low content of metal and glass
(Vidanaarachchi et al., 2005). A typical SW composition in
Sri Lanka is 66% organic matter, 13% paper, 8% plastics,
3% metal, 2% glass and 8% others (DCS, Sri Lanka, 1998).
It is comparable with typical developing country values
(Rushbrook and Pugh, 1999). UNEP noted that the organic
content of MSW in typical African cities exceeded 70% on a
wet basis and that such an output offers opportunities for
centralized composting, anaerobic digestion, and gas
recovery (UNEP, 2000).
Conclusions
The composition of household SW generated in Kampala
city were mainly vegetable / organic matter (83.6)%,
consisting of domestic peelings, cuttings and other vegetable
remains of food items such as bananas, cassava, potatoes,
cereals, waste food, leaf and grass remains.
Kampala city had a mean solid waste generation of 0.56
kg/person/day, with Rubaga division having the highest
(0.7366 kg/person/day), followed by Nakawa (0.5790
kg/person/day), Central (0.5526 kg/person/day),
Kawempe (0.4967 kg/person/day) and Makindye (0.4957
kg/person/day).
A total of 848,155 kg/day (about 25,445 tons/month)
of SW are currently being generated in Kampala city. Of this
total, Rubaga division generates 270,627 kg/day (8,119
tons/month), followed by Makindye with 200,907 kg/day
(6,027 tons/month), Nakawa with 173,411 kg/day (5,202
tons/month), Kawempe with 162,123 kg/day (4,864
tons/month) and Central with 60,510 kg/day (1,815
tons/month) of SW.
References
1. Achankeng, E. 1995. Changing Urban Growth Trends in a Cameroon
Border Town: dependency or independence? Cameroon Geographical
Review. XII(1): 68.
2. Beukering, P. V., Sehker, M., Gerlagh, R. and Kumar, V., 1999. Analysing
Urban Solid waste in Developing Countries: a perspective on
Bangalore, India. Working Paper No. 24.
3. Cointreau-Levine, S., 1982. Environmental Management of Urban
Solid Waste in Developing Countries. The World Bank, Washington
DC.
4. DCS, 1998. Municipal Solid Waste Statistics. Department of Census
and Statistics, Colombo, Sri Lanka.
5. KCC (Kampala City Council), 2000. Waste Collection in Kampala City,
Jan-June, 2000. Kampala, Uganda.
Figure 2: The composition (%) of household SW generated in Kampala.
How to Cite this Article: OJ. Ojok , M.K. Koech , M. Tole, J.Okot-Okumu “Rate and Quantities of Household Solid Waste Generated in Kampala City, Uganda”Science Journal of
Environmental Engineering Research, Volume 2013, Article ID sjeer-237, 6 Pages, 2012. doi: 10.7237/sjeer/237

Page 4 Science Journal of Environmental Engineering Research (ISSN:2276-7495)
6. Layder, D., 1993. New Strategies in Social Research. An Introduction
and Guide. Polity Press, Blackwell Publishers, Cambridge, UK.
7. NEMA (National Environment Management Authority) Uganda, 2001.
State of the Environment Report for Uganda. Kampala, Uganda.
8. Ngategize, P., Moyini, Y., Aryagaruka, M., Mwigaga, M. and Kigonya, A.,
2001. Solid Waste Management Strategic Plan for Mpigi District Local
Government. Final Report. Mpigi District Local Government, July 2007.
9. Palczynski, R.J., 2002. Study of Solid Waste Management Options for
Africa. Project Report. Final Draft Version. Available at:
http://www.afdb.org/pls/portal/url/ITEM/F5F4CC9E2105E31EE0
30A8C0668C631A accessed, 02-08-2007.
10. Rushbrook, P., Pugh, M., 1999. Solid waste Landfills in Middle and
Lower-Income Countries. A Technical Guide to Planning, Design and
Operation. World Bank, Washington DC.
11. UBOS (Uganda Bureau of Statistics), 2007. Projection Population
Report, 2003 - 2017. Kampala.
12. UNEP (United Nations Environment Programmeme), 2000. Global
Environment Outlook 2000, UNEP millennium report on the
environment. Earth scan publication limited, London.
13. UNEP (United Nations Environment Programmeme), 2009.
Developing Integrated Solid Waste Management Plan Training
Manual, Volume 2. Assessment of Current Waste Management System
and Gaps therein. Available at:
http://www.unep.or.jp/ietc/Publications/spc/ISWMPlan_Vol2.pdf,
accessed, 23-07-2010.
14. Vidanaarachchi, C.K., Yuen, S.T.S. and Pilapitiya, S., 2005. Municipal
Solid waste Management in the Southern Province of Sri Lanka:
Problems, issues and challenges. Colombo, Srilanka. Available at:
www.sciencedirect.com , accessed 03-08-2008.
15. Walyawula F. 2004. Assessment of Challenges and Constraints of
Municipal Solid Waste Management. Makerere University Kampala,
Uganda.
Division
2008 Population and
Housing Projections
Total Land
Area (km²)
Total
Number
of Parishes
Number of
Parishes
Sampled
Required
Samples
at 95% CL
Number
Sampled
per division
Population
Housing
Central 109500 28313 14.6 20 10 379 776
Kawempe 326400 85651 31.5 22 11 383 1019
Makindye 405300 106494 40.6 21 11 383 790
Nakawa 299500 73795 42.5 23 14 383 660
Rubaga 367400 95756 33.8 13 8 383 770
Total 1508100 390009 163 99 54 1911 4015
APPENDIX I
The total projected population and housing in Kampala in 2008, the required number of samples at 95%
confidence level( CL) and number of samples obtained per division
How to Cite this Article: OJ. Ojok , M.K. Koech , M. Tole, J.Okot-Okumu “Rate and Quantities of Household Solid Waste Generated in Kampala City, Uganda”Science Journal of
Environmental Engineering Research, Volume 2013, Article ID sjeer-237, 6 Pages, 2012. doi: 10.7237/sjeer/237