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

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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.
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Science Journal of Environmental Engineering Research
ISSN:2276-7495
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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
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and Statistics, Colombo, Sri Lanka.
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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)
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Division
2008 Population and
Housing Projections
Total Land
Area (km²)
Total
Number
of Parishes
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
... Kampala City is one of the cities facing challenges of solid waste management. On an average, about 1500e2500 metric tons of waste is generated in the City per day (Ojok, Koech, Tole, & OkotOkumu, 2013). The city has a single recognized landfill known as Kiteezi (see Fig. 2). ...
... The waste generated was calculated with reference to (Kinobe et al., 2015;Ojok et al., 2013;Robinson, 1986) and data obtained at the landfill. The population of each parish was collected from (UBOS, 2012) and the total waste that is generated in each division was obtained from the landfill. ...
... One source of data was collected at the landfill and another was computational data calculated from waste generated per month per division, per parish and consequently per capita waste generation. According to Okot-Okumu and Nyenje, (2011), UBOS (2012) and Ojok et al., (2013), the per capita waste generation in Kampala is approximately 0.6 kg ca À1 d À1 . However, Nabembezi (2011) quotes a higher per capita waste generation at 1 kg ca À1 d À1 . ...
... All urban centers are also experiencing unprecedented population growth rates since 2002, the data on SWM at all levels from the household, up to the municipal level is scanty, or if available at all, it is generally unreliable, scattered, and poorly organized. The total amount of solid waste generated by urban centers varies according to the location and season; it has been estimated that the average solid waste generation rates are 0.55 kg/capita/day; low-income municipalities generate about 0.3 /kg/capita/day, compared to the higher-income municipality rate of 0.66 kg/capita/day (Ojok et al., 2013;Lwasa et al., 2007). Lira and Kampala are reported to have generate rates of 0.3 and 0.5 kg/capita/day, respectively, while the City of Hoima generates 0.2 kg/of waste per capita/day [Urban Research and Training Consultancy E.A Limited (URTC), 2012]. ...
... All urban centers are also experiencing unprecedented population growth rates since 2002, the data on SWM at all levels from the household, up to the municipal level is scanty, or if available at all, it is generally unreliable, scattered, and poorly organized. The total amount of solid waste generated by urban centers varies according to the location and season; it has been estimated that the average solid waste generation rates are 0.55 kg/capita/day; low-income municipalities generate about 0.3 /kg/capita/day, compared to the higher-income municipality rate of 0.66 kg/capita/day ( Ojok et al., 2013;Lwasa et al., 2007). Lira and Kampala are reported to have generate rates of 0.3 and 0.5 kg/capita/day, respectively, while the City of Hoima generates 0 ...
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... Hence, while rural areas comprise about 60 percent of the total population, they only dispose around 30 percent of the total amount of solid waste nationwide. According to Ojok et al. (2013), per capita waste generation in developing countries is about 0.3 to 0.6 kg/day. In 2012, 89.03 million tons of solid waste was generated in Egypt; the per capita solid waste generation in 2012 was 0.7-1.0 ...
Chapter
Waste generation in developing countries is highly increasing due to the accelerated economic growth. This raises many issues and concerns due to the high population and the improper waste management. For the Arab countries, the amount of municipal solid waste generated is about 81.3 million tons per year; less than 20% is adequately treated, and less than 5% is recycled. Another main issue is the transportation and logistics of waste. To address these issues, this chapter adopts ‘reverse logistics’ to explore how to manage waste and increase waste utilization efficiently. The scope of this chapter is Egypt and can be generalized to the Middle East and North Africa (MENA) region. The main interest of this chapter is to understand the role of reverse logistics in waste management and to determine the factors that influence logistics decisions and practices for waste management.
... Survey design and Data collection The application of CV survey is the most suitable method for collecting information on household preferences for providing an improvement in public good and services [18]. The various application such as [27] in Nigeria, [28] in India, [29] in Uganda; [30] in Cameroon; [18] in Ghana are the famous example of CV studies in developing countries. All of these studies provide evidence that household is provide a significant amount of improvement of solid waste improvement. ...
Article
The paper examines the current practices, concerns household willingness to pay (WTP) for Solid Waste Management (SWM) Services in urban areas of District Mardan, Pakistan. A sample size of 384 was allocated to 15 urban union councils proportionally. Contingent Valuation (CV) survey method was used for eliciting households' WTP for improved SWM services. The findings of the study show that household generates 53% biodegradable, 38% non-biodegradable, and 11% non-putrescible solid waste and majority households use Polythene bags for indoor SWM. The households mostly disposed the solid waste near to their resident at vehicle collection points, communal containers, canals/perennial nullahs and in many places, incineration was also practising. Most households (85%) are not satisfied with the existing SWM services and are WTP for improvement. Bid wise logistic regression analysis shows that majority of households' (280) are odd in favour of bid1 and mean WTP is PKR 125/month. This paper posits stress on the public utility company that for sustainable planning toward better services, CV survey is an appropriate tool for acquiring information on the existing practices and concerns for household WTP for proposed services. Service provider and practitioner should consider these traits of households before implementing waste collection charges in the locality.
... As observed in Fig. 4a-d, solid waste in the different LDCs regions consists mainly of organics which are predominantly attributed to food and yard wastes [27], with food wastes consisting mainly of food leftovers, fruits, and vegetable peelings [28,29]. The fraction 'others' is subdivided into textile, sand and other waste materials such as rubber and dust. ...
Article
Increasing solid waste generation is a major concern worldwide, with least developed countries (LDCs) particularly affected due to ineffective waste management systems. This article assessed the current status of solid waste management in LDCs from waste generation to disposal. Solid waste generation in LDCs averages 0.56 kg/capita/day while the solid waste stream consists mainly of organics (52%) followed by recyclables (26%). Waste collection is also low and due to irregular waste collection, many people in LDCs resort to illegal practices such as illegal dumping or open burning of wastes. Sanitary landfilling is almost non-existent in LDCs with some of the few landfills present severely lacking in effective leachate or gas collection systems. While recycling is carried out in some LDCs, the most common practice is to collect recyclables for exportation. Similarly, composting of solid waste exists mainly on small-scale while biogas plants present in LDCs are used mostly for treatment of animal manure. Some of the challenges faced by LDCs include lack of funding, infrastructure, legislations, knowledge, and awareness on solid waste issues. However, there is a huge potential for job creation in the solid waste management field including waste collection, recycling, composting and even sanitary landfilling.
... The amount of organic household waste generated (F5i1) is 0.4 AE 0.1 kg capita À1 day À1 wet weight (Lederer et al., 2012;Ojok et al., 2013), resulting in 41,055 AE 10,264 t yr À1 . 83% of this is generated in rural and 17% in urban areas. ...
Article
Human activities create wastes. Whether wastes would pose risks to the environment and to public health depend on how they are handled, stored, collected and disposed off. The research sought to identify the approaches adopted by households to dispose off wastes; the perception of households on public health in relation to nearness to dumpsites; health related activities organized and challenges of managing wastes. Duase, Ohwim and Oti-Dompoase, all in Kumasi metropolis were studied to understand these issues. A total of 256 households were systematically sampled from 3,364 households at a 95% confidence level. It was found that 44.9% of the household respondents disposed off their wastes at the dumpsites within their respective residential areas; 26.9% at the central collection skip containers provided by KMA; 17.2%, in pits at their backyards; and 10.9% by burning. ZoomLion Ghana Ltd, ABC Waste Group, Meskworld Co. Ltd and Kumasi Waste Management Limited were responsible for managing waste within the study areas. Their operations however seem not satisfactory by the respondents. About 41.4% of the household respondents complained of the stench of the dumpsites which some of them even attributed it to the cause of numerous diseases in the communities such as catarrh, cough and chest pains. Diarrhea, intestinal worms, typhoid fever and cancer were perceived as diseases resulting from the wastes at the dumpsites. About 41.4% cited stench of the dumpsites to justify this claim while others link the poor management of waste to the causes of numerous diseases (catarrh, cough and chest pains, diarrhea, intestinal worms, typhoid fever and cancer) prevalent in the communities. The operations of the waste management companies were however found to be challenged by inadequate trucks and equipment, high operating cost, limited land availability for sanitary landfill and inadequate funding. Community participation in sanitation improvement programmes, separation of solid wastes at collection points, recycling of solid wastes and sensitization on how to dispose off waste and how to prevent waste related diseases have been recommended.
Article
Population growth at an interminable rate is depleting resources uncontrollably. Researchers are concentrating on sustainable development mainly in urban areas where the growth rate is higher than any other regions. In addition to the development of new technologies for reducing the rate of natural resources usage, technologies are being developed to recover the resources from waste. In this perspective, solid waste management with proper collection and transportation techniques facilitates the waste managers to segregate and extract the required resources for recovery. GIS and remote sensing approaches come to the aid of managing this solid waste through its generation stage to the dumping stage. Using a proposed smart city, Vellore in India as a case study, this paper discusses possible collection methods for solid waste management in India, and presents methods for optimal collection and transportation of waste using GIS techniques through network analysis. The optimal waste collection and transportation routes derived from our analysis result in 59.12% reduction in travel distance along the routine collection road network followed. In addition, this study proposes possible transfer station locations based on various design factors like open land availability, ease of access from all the composting units/dustbin locations, transfer means by tractor trailers, and sanitation and environmental requirements. This study also reveals the vegetation cover changes at a depletion rate of 2100 square meters area in and around dumping sites.
Article
Full-text available
Human activities create wastes. Whether wastes would pose risks to the environment and to public health depend on how they are handled, stored, collected and disposed off. The research sought to identify the approaches adopted by households to dispose off wastes; the perception of households on public health in relation to nearness to dumpsites; health related activities organized and challenges of managing wastes. Duase, Ohwim and OtiDompoase, all in Kumasi metropolis were studied to understand these issues. A total of 256 households were systematically sampled from 3,364 households at a 95% confidence level. It was found that 44.9% of the household respondents disposed off their wastes at the dumpsites within their respective residential areas; 26.9% at the central collection skip containers provided by KMA; 17.2%, in pits at their backyards; and 10.9% by burning. ZoomLion Ghana Ltd, ABC Waste Group, Meskworld Co. Ltd and Kumasi Waste Management Limited were responsible for managing waste within the study areas. Their operations however seem not satisfactory by the respondents. About 41.4% of the household respondents complained of the stench of the dumpsites which some of them even attributed it to the cause of numerous diseases in the communities such as catarrh, cough and chest pains. Diarrhea, intestinal worms, typhoid fever and cancer were perceived as diseases resulting from the wastes at the dumpsites. About 41.4% cited stench of the dumpsites to justify this claim while others link the poor management of waste to the causes of numerous diseases (catarrh, cough and chest pains, diarrhea, intestinal worms, typhoid fever and cancer) prevalent in the communities. The operations of the waste management companies were however found to be challenged by inadequate trucks and equipment, high operating cost, limited land availability for sanitary landfill and inadequate funding. Community participation in sanitation improvement programmes, separation of solid wastes at collection points, recycling of solid wastes and sensitization on how to dispose off waste and how to prevent waste related diseases have been recommended.
Article
The disposal of residual wastes to land is the ultimate end-point for any waste management system. It is a delusion to believe that the health and social problems posed by wastes come only from waste storage or collection activities. Unfortunately, open dumping is currently the world's most common disposal method. No amount of careful waste collection or treatment will reduce the hazards to health or the environment from disposal if the final resting place for waste is an uncontrolled dump. Development of disposal sites away from open dumping is a necessity. To advance waste management systems in countries undergoing development, attention should also be paid to the improvement of waste landfills. Some aid assistance and loans for waste improvement schemes in the past have avoided doing this, perhaps in the belief that the prevailing disposal practices are too difficult to change. This Technical Guide seeks to demonstrate that, by encouraging small, continuous improvements in landfill siting, construction, and operation, the accumulative effect over time is the achievement of better operations. The Guide does not seek an immediate adoption of sanitary landfill practices. Instead, sanitary landfill is regarded as an eventual goal for which middle- and lower-income countries can plan during the course of several years. Most existing guides on sanitary landfill focus on technologies and practices most suited to the conditions and regulations found in higher-income countries. These are often based on attaining extremely high levels of protection for aquifers, incorporating aesthetic concerns, high levels of leachate treatment, and controls to assure low noise and low gaseous emissions. The immediate adoption of some of these technologies and practices are beyond the technical and financial resources available in many middle- and lower-income countries. The principle used in this Guide is 'keep it simple.' This axiom is considered at all stages in the development of a landfill (i.e., in its siting, design, operation, and aftercare). A common theme through the Guide is the emphasis on the practical ways landfills can evolve, as resources and confidence increase, from open dumps to 'controlled' dumps to 'engineered' landfills and perhaps, one day, to sanitary landfills. At each stage in this evolution, the level of environmental and health protection will also increase. The Guide is targeted at senior waste management staff in local authorities in middle- and lower-income countries. Of necessity, it is written in a generalized way, in recognition that there are wide differences in climatic, cultural and political regimes around the world. These will have varying influences on the appropriateness of some of the approaches and techniques described for the better siting, design, operation, and aftercare of landfills.
Article
The project guide provides information and procedures for planning and implementation of solid waste management improvements. It is designed to facilitate project preparation, appraisal and implementation of Bank financed solid waste projects in urban areas. Current Bank objectives, policies, and project requirements are summarized. It should also be of use to a wide audience involved in solid waste collection and disposal in developing countries. The project guide reflects the lessons and experience gained from World Bank solid waste projects. The text discusses establishment of an acceptable standard of collection and disposal service delivery, selection of appropriate technology, development of suitably phased action plans, arrangement of institutions for planning and management, arrangement of financial resources, development of regulatory and enforcement support services, provision of public education and participation programs, and incorporation of incentives and disincentives to facilitate project success.
Article
This paper describes the problems, issues and challenges faced by Sri Lanka based on the outcome of a recent study conducted in the country's Southern Province. The study consists of a public survey, discussions with local authority staff involved in waste management, discussions with Provincial Council and Government officials, dialogue with local politicians, review of documents and field observations. The study revealed that only 24% of the households have access to waste collection and that in rural areas it was less than 2%. A substantial number of households in areas without waste collection expect local authorities to collect their waste. The study also showed that most sites in the province are under capacity to handle any increased demand. Urgent and immediate improvement of the waste disposal sites is necessary to meet the current demand for improved waste collection. The study also revealed that there is a high willingness of people for home composting.
Changing Urban Growth Trends in a Cameroon Border Town: dependency or independence?
  • E Achankeng
Achankeng, E. 1995. Changing Urban Growth Trends in a Cameroon Border Town: dependency or independence? Cameroon Geographical Review. XII(1): 68.
Waste Collection in Kampala City Figure 2: The composition (%) of household SW generated in Kampala How to Cite this Article Rate and Quantities of Household Solid Waste Generated in Kampala City, Uganda
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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)
Solid Waste Management Strategic Plan for Mpigi District Local Government
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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.
Study of Solid Waste Management Options for Africa
  • R J Palczynski
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.
Assessment of Challenges and Constraints of Municipal Solid Waste Management
  • F Walyawula
Walyawula F. 2004. Assessment of Challenges and Constraints of Municipal Solid Waste Management. Makerere University Kampala, Uganda.