Municipal solid waste generation, composition, and management in the Douala municipality, Cameroon

Municipal Solid Waste Generation,Composition, and Management in the Douala Municipality, Cameroon
JEWM
Municipal solid waste generation, composition, and
management in the Douala municipality, Cameroon
1*
Innocent Ndoh Mbue, 1
Bitondo D, 2
Balgah Roland Azibo
1
The University of Douala, Faculty of Industrial Engineering, department of Hygiene, Safety and Industrial security, P.O.
Box 2071 Douala, Cameroon
2
Research Fellow/Lecturer, College of Technology, University of Bamenda, P.O. Box 39, Bambili
The study evaluates municipal solid waste generation, composition, and management in the
Douala municipality of Cameroon at landfill level. Load count analysis was used for the
systematic assessment of the flows and stocks of materials within the landfill in space and time.
Descriptive and inferential statistics methods were used to draw conclusions. The results show
that, on average, municipal solid waste composition in the municipality has been changing over
time. On average 490194580 Kg of wastes are generated per month, giving a per capita
generation rate of 0.54 ± 0.071 kg person
-1
month
-1
. While inert (7.4±0.8), metal (2.6 ± 0.8), glass
(3.5% ± 1.3), and paper (14.5% ± 0.9) wastes (2.0% ± 0.1) had higher proportions in the dry
season, plastic (16.1% ± 2.6), organic (49.8.3% ± 3.1) and special wastes (2.0% ± 0.1) had higher
proportions in the rainy season. However, at α = 0.05, all waste categories resulted in P > α, with
extreme critical values for the test statistic t, suggesting that waste composition do not
significantly differ from season to season. Similar results were observed for the mean
generation rates across the different districts 𝐱 𝟐
𝟒,𝟎.𝟎𝟓 = 𝟗. 𝟒𝟖𝟕𝟕; 𝐏 = 𝟎. 𝟏𝟓 .Forecasting
generation rates could be important for proper planning of operations related to solid waste
management.
Keywords: Municipal solid waste, Douala municipality, Cameroon, Material flow analysis, Load count analysis, Per
capita generation rate.
INTRODUCTION
Increasing population levels, booming economy, rapid
urbanization and the rise in community living standards
have greatly accelerated the municipal solid waste
(MSW) generation rate in developing countries (Minghua
et al., 2009).In African cities poor management of solid
waste is a common phenomenon due to budgetary
problems, mismatching plans and inadequate information
about the amount of solid waste generated by residents
(Simelane and Mohee, 2012). At the same time, improper
handling and disposal of solid waste constitutes a serious
problem: it results in deterioration of the urban
environment in the form of air, water, and land pollution
(Adekunle et al., 2011; Jalil, 2010) that pose risks to
human health, and cause serious environmental
problems (Khajuria et al., 2008). The environment has a
limited capacity for waste assimilation. If too much waste
enters the environment rather than being recycled or
reused, the assimilative capacity of the environment is
put under too much stress to be able to handle the total
quantity of waste generated.
*Corresponding author: Ndoh Mbue Innocent, The
University of Douala, Faculty of Industrial Engineering,
department of Hygiene, Safety and Industrial security,
P.O. Box 2071 Douala, Cameroon, Email:
dndoh2009@gmail.com
Journal of Environment and Waste Management
Vol. 2(4), pp. 091-101, October, 2015. © www.premierpublishers.org, ISSN: 1936-8798x
Review

Mbue et al. 091
The challenge, therefore, for the municipal environmental
engineers and planners is to employ green technology
approaches that are viable and sustainable. Solid waste
composition, generation and management seem to be
important to city authorities to help them in policy making
and proper planning of operations related to solid waste
management.
In the past decades, a large number of research studies
have been undertaken to determine influential factors
affecting waste management. A variety of approaches
have been adopted for assembling detailed quantitative
data on the amount, location, and characteristics of a
waste stream (Felder et al., 2001;Mason et al., 2003;
Dahlen et al., 2007). Several other studies have focused
on waste characterization at the household level (e.g.
Chang and Davila, 2008; Gomez et al., 2009). A few
other studies have attempted to develop either a
systematic approach for MSW at both the household and
non-household level (Zotos et al. 2009), or identified
factors influencing the elements of the waste
management systems (Akinci et al., 2012; Al-Jarallah and
Aleisa, 2013).Some researchers have documented how
an adequate legal framework contributes positively to the
development of an integrated solid waste management
system (Asase et al., 2009) while the absence of
satisfactory policies (Turan et al. 2009, Mrayyan and
Hamdi, 2006) and weak regulations (Seng et al., 2010)
are detrimental to it.
While numerous waste characterization studies have
been conducted at the household level (Chowdhury,
2009; Gomez et al., 2009) only a small number exist for
the municipal sector (Hristovski et al., 2007, Zhuang et
al., 2008). In the same way that municipal waste
characterization studies provide local decision makers
with a detailed understanding of a waste stream and
enable waste management programs to be tailored to
local needs (Chang and Davila, 2008), waste
characterization studies at municipal level identify urban
specific and regionally relevant opportunities for waste
reduction and recycling, representing an essential step
towards greening the community. Such data is key to
long term planning for the management of solid waste in
an efficient and economical manner (Gidarakos et al
2006), and for the identification of waste components to
target for source reduction, recycling, design of material
recovery facilities and waste-to-energy projects (del C
Espinosa Llorens et al., 2008; Qu et al., 2009).
The anthology of MSW study throughout the world is
scant. In developing economies the data on MSW
generation have a short history and insufficient national
data or data of a large urban or periurban population
center (Shekdar, 2009). In Africa, waste characterization
data specific to African cities is generally not available
(ADB, 2002), the composition of the waste varies
depending upon such diverse variables as urbanization,
commercial enterprises, manufacturing, and service
sector activities. In Cameroon, MSW management
including control, collection, processing, utilization, and
disposal, is the responsibility of the municipalities. Waste
management policy is based on a public-private
partnership which ensures regular collection and
processing service for domestic waste in the major cities.
However, data on MSW generation, composition and
management have insufficient national data or data of a
large urban or peri-urban population Centre. Policy
decisions that influence the components of MSW
systems are not possible until data of composition and
quantity of solid waste are available. This view is shared
by Acurio et al (1997) who contend that the type of
decision making that leads to adequate solid waste
management should be based on sound understanding
of composition. This study will attempt to fill this
knowledge gap in order to make theoretical and empirical
contribution in the field of waste management in the
country.
The purpose of this study is therefore to determine the
generation rate and composition of municipal solid waste
with the intention of providing base line data for
development of municipal solid waste management
system in the Douala municipality of Cameroon. Key
research questions are:
What is the generation rate and composition of
municipal solid waste in the Douala municipality?
How have MSW in the Douala Municipality varied in
generation and composition over the past decade
(2003 to 2013?)
What technically and administratively feasible waste
management improvements and strategies should be
adopted to advance the sustainability of the current
system?
The approach consists in manually segregating the
wastes on site. Load count analysis of all collected
samples was done on site. Mean values and standard
deviations were calculated for different components of
MSW.
MATERIALS AND METHODS
Study Area
The city of Douala (210 km
2
/80 sq mi) is the capital of
the Littoral region of Cameroon. It is Cameroon’s
economic capital, the richest city in the whole CEMAC
region of six countries, located on the banks of the Wouri
River, at 4°02′53″ N Latitude 9°42′15″E Longitude,
situated in the Wouri division at an average elevation of
13m above sea level. Five urban municipalities (also
known as districts) and one rural municipality form the
urban community of Douala: the town districts of Douala I
whose headquarters is at Bonanjo, Douala II whose

J. Environ. Waste Manag. 092
headquarters is New Bell, Douala III whose headquarters
is at Logbaba, Douala IV whose headquarters is at
Bonassama, Douala V whose headquarters is at Kotto,
and Douala VI whose headquarters is at Manoka (Fig.1).
Figure 1. Map of Africa and Cameroon showing the city of Douala with its
municipalities; “a-f”: CEMAC countries
Together, the six local governments are commonly
referred to as the Douala Urban Council (DUC). Douala is
also an industrial city and one of the fastest developing
urban areas in Africa and ranks first at national level.
Politically, the 2005 population censures estimate the
population to a controversial figure of 1.907 million
(UNdata, 2013). However, according to current estimates
from the Douala urban council, the population of the
municipality is estimated to at 5,000,000 people with an
average growth rate of 4.8%.
Research design and Data collection
Both exploratory and descriptive research designs were
employed to achieve the objectives of this study.
The following data-collection phases were employed:
Review of existing literature;
Quantifying the waste stream through vehicle
surveys; and
Determining the composition of the waste stream
through sampling and sorting.
Review of existing literature began with an evaluation of
internal policies and procedures related to municipal
sustainability and waste management, external
documents including government regulations and
guidelines and various municipal waste composition
studies. Through their annual solid waste reports,
HYSACAM office provided historic data on quantities of
waste generated daily, weekly, monthly and yearly.
Commercial recyclers and end-users provided
information on the types and estimated quantities of
wastes recycled in a voluntary survey.
Background research
Its aim was the identification of the functional elements
existing within the management of MSW in the
municipality, and of the most relevant stakeholders. It
included visits to the e landfill at PK 18 (landfill site).
Field research
Field work was conducted to identify the solid waste
sources, generation and composition. The aim of this
step was to improve the quality of the data gathered
during the background research. The samples were
collected from the landfill for both dry and rainy seasons.
The main tools used in data collection were interviews
sheets and scale balance. In order to obtain a higher
accuracy in the generation rates, historic data from the
facility and daily data on the waste load weights collected
by the trucks of the municipality were used.
Waste sampling
Sample collection and segregation was done monthly
from January 2013 to December 2013 to explore
seasonal variations and representative characteristics of
MSW. The sampling locations at the landfill site were
identified in consultation with HYSACAM authorities
responsible for the operation of the site to obtain a
representative sample (Fig. 2).
Figure 2. Sampling stations of MSW at PK10 landfill
Load count Analyses (Tchobanoglous et al., 1993b) was
used to estimate solid wastes quantities generated and
collected. Vehicles entering the landfill were surveyed
using survey forms. Loaded trucks carrying waste to the
landfill are first weighed, their size and destinations
identified before off-loading takes place. To choose the
waste collection trucks, several truck drivers were asked
from which route/district the waste was being collected.
Waste was sampled from numerous districts (strata):
Douala I, Douala II, Douala III, Douala IV and Douala V,
to develop a waste composition profile for each stratum.
The strata were then “added together” in a way that
reflects each stratum’s relative contribution to the overall
waste stream, thus producing overall waste composition
information. Samples were collected at 10 days of
intervals from 03 February to 31
st
of December 2013. The
apparatus used was a Single Pan, Physical

Mbue et al. 093
Table 1. Waste composition category
ID Waste composition category Waste components
1 Paper Packaging paper, cardboard, wrapper, newsprint, magazines, office paper
2 Plastic
PETE Containers, HDPE Containers, Miscellaneous Plastic Containers
Plastic Trash Bags, Plastic Grocery and other Merchandise Bags,
Durable Plastic Items, Remainder/Composite Plastic
3 Glass Clear, brown, green, other
4 Metal Ferrous, non-ferrous, tin cans, metal foils, Other Non-Ferrous and ferrous metals
3
Electronics
Computer-related Electronics, Other Small Consumer Electronics,
Video Display Devices, radio
4
Household Hazardous
Paint, Vehicle & Equipment Fluids , Used Oil, Batteries,
Remainder/Composite Household Hazardous
5 Other Organics
 Food wastes, Leaves and Grass, Prunings and Trimmings, Branches and
Stumps, Manures, Carpet, Textiles (rubber, clothes, synthetic, cables, leather),
Remainder/Composite Organic
6
Inerts& other
Concrete, Asphalt Paving, Lumber, Gypsum Board, Rock, Soil, and Fines,
Remainder/Composite
7 Special Waste Ash, Bulky Items, Tyres, Treated Medical Waste, Remainder/Composite Special Waste
balance. The Parameters studied are composition and
generation rate of municipal solid waste. Each load was
separated manually by component example - wood,
concrete, plastic, metal, etc. Each component is weighed
and weights recorded. Assessing waste quantity and
composition in this way has been shown to capture the
high spatial variation of waste (Felder et al., 2001),
thereby yielding more reliable and representative data.
Waste Sorting and Processing of Samples
A sorting & characterization form was used. Surveys
were conducted on the same days that waste was
sampled. Sorting and processing of waste samples were
manually done with the help of landfill workers into seven
categories, namely paper, plastic, electronic, household
hazardous wastes (HHW), other organics, inerts and
others, and special waste (Table 1).
Data Analyses
The analysis of the data was carried out qualitatively and
quantitatively. Flows were expressed in kg/year or in
kg/capita/year. Mean values and standard deviations
were calculated for different components of MSW. The
weight-based percentage composition for each
subcategory(primary and secondary) was calculated.
Estimating the composition of MSW
Composition estimates represent the ratio of the
components’ weight to the total waste for each noted
material component in a particular segment of the waste
stream. For a given material, j, in all of the relevant
samples, i, the ratio, rj, of the material weight, m, to the
total sample weight, w was estimated (Equation 1) from
each stratum or subdivision:
𝑟𝑗 =
𝑚 𝑖𝑗𝑖
𝑤 𝑖𝑖
(1)
for i = 1 to n, where n = number of selected
samples; and
for j = 1 to m, where m = number of components.
Estimating the Error Range
The confidence interval for this estimate was derived in
two steps. First, the variance around the estimate was
calculated, accounting for the fact that the ratio included
two random variables (the component and total sample
weights). The variance of the ratio estimator equation
follows (William, 77):
𝑉𝑟𝑗 ≈
1
𝑛
1
𝑤2
𝑐 𝑖𝑗 −𝑟 𝑗 𝑤 𝑖𝑖
𝑛−1
2
(2)
Where:
𝑤 =
𝑤 𝑖𝑖
𝑛
Second, precision levels at the 90percent confidence
level were calculated for a component’s mean as follows:
rj ± (z Var(rj) (3)
Where z = value from z-statistics (1.645) corresponding
to 90% confidence interval.

Table 2. Current Solid waste generation in the Douala Municipality
Municipality Amount Generated (Tonnes/day)
Amount Collected
(Tonnes/day) Collection rate (%)
Douala I 3,423 1845 54
Douala II 3,975 1984 50
Douala III 4,050 2104 52
Douala IV 4200 2245 53
Douala V 4150 2342 56
Total 19,798 10520 53
Calculating the Mean Estimate for Combining Waste
Sectors
Composition results for strata were then combined using
a weighted average method to estimate the composition
of larger portions of the waste stream. The relative
tonnage associated with each stratum served as the
weighting factors. The calculation was performed as
follows:
Oj = P1 ∗ rj1 + P2 ∗ rj2 + P2 ∗ rj3 + ⋯(4)
Where:
 P = the proportion of tonnage contributed by the
noted waste stratum (the weighting factor),where the
sum of all the values of p is 1
 r = the ratio of component weight to total waste
weight in the noted waste stratum (the composition
percent for the given material component), and
 For j = 1 to m, where m = the number of material
components
The variance of the weighted average by taking the
variance of equation (4):
V(Oj) =
p2
1
Var rj1 + p2
2
Var rj2 + p2
3
Var rj3 + ⋯ (5)
Estimating the quantities of MSW generated
Total waste generated on a daily base was estimated as:
Total waste generated = Disposed Waste + Recycled
Waste + Diverted Waste (6)
= Disposal + (Recycling + Reuse)
The proportion of waste diverted was obtained through
field interviews and field observations. The weight of
waste for each truck entering the landfill equals, the
weight of the truck when full of waste minus weight of the
truck when empty.
From [4], the per capita generation rate was calculated as
(equation 5):
Per capita generation =
Total waste generated
Population
Kg
day ∗person
(7)
Hence,
Generation recycled =
MSW Recycled
MSW disposed +MSW recycled
∗ 100%(8)
To keep the waste composition tables and figures
readable, estimated tonnages are rounded to the nearest
ton, and estimated percentages are rounded to the
nearest tenth of a percent. Due to this rounding, the
tonnages presented, when added together, may not
exactly match the subtotals and totals shown. Similarly,
the percentages, when added together, may not exactly
match the subtotals or totals shown. Percentages less
than 0.05% are shown as 0.0 percent. Hypothesis tests
were conducted to compare the municipal waste
composition among the districts and seasons.
RESULTS AND DISCUSSION
Generation of Municipal solid waste
On average, the municipality of Douala is generating
solid waste at a tune of 490194580 tonnes per day in
2013 giving a per capita generation rate 0.54 ± 0.071 kg
person
-1
month
-1
. Of these tonnes 53% is collected and
the remaining 47% are buried, burned, scavenged by
informal recyclers or dumped by the road side or into
drainage canals (Table 2).
These figures in the table shows that serious planning is
essential if the municipality will ever be clean and solid
waste characterisation and quantification are important
aspects of that planning process.
The average per capita generation rates were 0.46, 0.51,
0.56, 0.59 and 0.63 kg kg capita
_1
month
_1
for Douala I, II,
III, IV and V respectively. The results agree with the
range estimated by other recent research findings from
other similar cities of the developing countries (Table 3)
Though there is a strong positive correlation between
population of a district and per capita generation rates (r=
.78, p< .05), the variation across municipalities is not
significant;
𝑥2
4,0.05 = 9.4877; 𝑝 = 0.15 .

Mbue et al. 095
Table 3. MSW generation in selected major cities from Africa
City-Country Population
(Millions)
MSW generation rate
(Kg.capita
-1
.day
-1
)
Author (s) and year
Kumasi-Ghana 1.89 0.48 Asase et al (2009)
Abuja-Nigeria 2.5 0.44-0.66 Ogwueleka, 2009
Yaounde-Cameroon 1.72 0.52 Parrot et al (2009)
Bamako – Mali 1.5 0.43 Samake et al (2009)
Figure 3. Trend in MSW collection rate in Douala (2003-2012)
Trends in Solid Waste Generation
Waste products from the Douala municipality originate
from a variety of residential, commercial, institutional,
construction and demolition, municipal services,
treatment plant sites, industrial and agricultural activities.
Regular collection and processing is carried out by
HYSACAM. On average, between 50 - 60% of wastes
generated by the municipality are collected are collected
while about 47% remains uncollected (Fig. 3)
One of the reasons for HYSACAM’s success is its ability
to adapt to changing requirements. It has recruited
trained personnel and deployed modern, well-maintained
equipments– key requirements for managing waste in
towns and cities with as many as several million. To
reach harder-to-access neighbor hoods, HYSACAM has
developed pre-collection agreements with community
based organisations that gather the waste from the
inaccessible areas and transfer it to the company’s
collection bins. As a result, it is able to achieve collection
rates of over 50% (Parrot et al., 2009). Generally,
municipalities have failed to manage solid waste due to
financial factors. The huge expenditure needed to provide
the service, the absence of financial support, limited
resources, the unwillingness of the users to pay for the
service (Sujauddin et al., 2008) and lack of proper use of
economic instruments have hampered the delivery of
proper waste management services. Sharholy et al.
(2008) indicated that the involvement of the private sector
is a factor that could improve the efficiency of the system.
Composition and Trend in Per Capita Yearly
Generation of Solid Waste
The physical survey of the landfill site shows that the
organic fraction includes paper, cardboard,
rubber/leather/synthetics and compostable matter (Fig 4).
The average composition of MSW includes Paper and
cartons 19.4% ±(4.9), Plastic 15.4%±(1.1), Glass
2.2%±(0.3), Inert 9.4% ±(2.4), Metals 3.2%±(1.3), Other
organics (48.4%±(7.2), and Special wastes 2.0% ± (0.6)
(Table 4).
The generation of municipal solid waste is increasing in
the Douala municipality probably due to the increased
population density, consumption pattern, life style
behavior and economic development etc. Food waste
(mixed), paper and card board waste and plastic waste
are dominant in the waste stream. The waste stream has
higher percentage of organic waste compared to the
inorganic. The high amount of organic waste can be
effectively used as organic manure through composting
where as recycling and energy recovery would be an

Figure 4. An overview of waste composition: overall
municipal wide disposed waste
Table 4. Overview of the Douala municipality’s overall disposed waste stream
Material
Est.
percent + / -
Est.
tons Material
Est.
percent + / - Est. tons
Paper and Cartons : 19.4% 639646 Plastic 15.4% 441817
 PaperBags 1.2% 0.9% 39566
 PET
containers 5.2% 0.1% 171451
 Office Paper 5.2% 0.9% 171451
 HDPE
containers 2.4% 0.1% 79131
 Magazines/catalog
ue 1.9% 0.9% 62646
 Plastic trash
bag 0.7% 0.1% 23080
 Newspapers 4.3% 0.9% 141777
 Misc.
containers 4.3% 0.1% 141777
 White ledger
paper 0.3% 0.4% 9891
 Composite
Plastic 2.8% 0.7% 92320
 Mixed paper 6.5% 0.9% 214314 Other Organics 48.4% 1635382
Glass 2.2% 85726  Food wastes 24.3% 1.9% 807800
 Clear glass bottles 1.3% 0.1% 49457
 Leaves &
grass 3.8% 0.7% 125291
 Composite Glass 0.7% 0.1% 23080
 Composite
organic 3.3% 0.5% 141777
 Windows
breakings 0.2% 0.1% 13189
 Prunings/trimm
ing 2.7% 1.5% 89023
Inert and other 9.4% 0.1% 309931
 Branches &
stumps 0.6% 0.4% 19783
 Rock/soil/concrete
/fine 3.2% 0.1% 105509  Manures 0.1% 0.1% 3297
 Lumber/Wood 0.4% 2.2% 13189  Carpet 3.2% 2.0% 105509
 Composite 5.8% 0.1% 191234  Textiles 10.4% 0.2% 342903
Metals 3.2% 118697 Special wastes 2.0% 65943
 Tin/Steel cans 0.3% 0.1% 9891  Ash 0.2% 0.1% 6594
 Major Appliances 0.1% 0.1% 3297  Bulky Items 1.0% 0.1% 32971
 Used oil Filters 0.1% 0.1% 3297  Tyres/Rubber 0.2% 0.1% 6594
 Aluminiumcans 1.3% 0.4% 42863  Sewage Solids 0.4% 0.1% 13189
 Other Non-Ferrous 0.2% 0.1% 6594
 Industrial
Sludge 0.1% 0.1% 3297
 Composite metal 1.4% 0.5% 52754  Composite 0.1% 0.1% 3297
Confidence intervals calculated at the 90% confidence level. Percentages for material types may not total 100% due to rounding
appropriate option for the inorganic fraction of the waste
stream.
Variation of MSW Composition with Time
Non-recyclables (inerts, special wastes and others) have
increased from 15% in 2003 to about 40.60% in 2013 (an
increase of 25.6%). This could be attributed to the
practice of inclusion of the street sweepings, drain silt
and construction and demolition waste in MSW. On the
other hand, the decrease in recyclables can be attributed
to the increase in recycling enterprises in the city over

Mbue et al. 097
Figure 5. Monthly per capital generation of MSW
Table 5. Statistical comparison of the seasonal composition of MSW from 2003-2013
Waste category Mean (±SD) Hypothesis
t p
Confidence Interval
Dry Rainy Ho Ha Lower Upper
Glass 3.42 ±1.26 3.33±1.28 μ =3.4 μ ≠3.4 .027 0.735 -1.78 -1.78
Inerts& Others 2.72 ±.877 3.04±1.5 μ =2.72 μ ≠2.72 -.382 0.172 -2.20 1.56
Metal 2.90 ±.600 2.5±.945 μ =2.90 μ ≠2.90 .781 0.338 -.78 1.61
Paper 14.65 ±.98 14.47±.96 μ =14.65 μ ≠14.65 .294 0.730 -1.19 1.55
Putrescibles 45.0 ±4.0 47.0±1.41 μ =45.0 μ ≠45.0 -.651 0.404 -11.78 7.78
Plastic 16.42±3.1 16.15 ±2.6 μ =16.42 μ ≠16.42 .154 0.715 -3.67 4.20
Special 1.27 ±1.17 2.90 ±2.0 μ =1.27 μ ≠1.27 -1.465 0.287 -4.13 .880
At α = 0.05, the results indicated that all categories resulted in P >α, with extreme critical values for the test statistic t. We thus fail to reject the null
hypothesis and conclude that, waste composition do not significantly differ from season to season.
time, which has in turn given rise to the practice of
scavenging in the city in general, and at the landfill area
in particular, providing employment to hundreds of
unskilled workers. The result is a large proportion of
compostable and non-recyclable material content both at
collection and landfill sites. Thus, if a recycling program
for MSW is well conducted, it not only could potentially
recover, reuse, and/or regenerate useful resources, but
also could reduce the amount of waste to be disposed.
Solid waste treatment at source can help to divert over
60% of the total waste and could lead to enormous
savings in the cost of waste collection, transport and
disposal. To achieve sustainable municipal waste
management practices, the challenge will be to reduce
the amount of solid waste generated, while increasing the
amount of waste diverted from landfills through recycling
and other initiatives in an economically feasible way. It is
also necessary to realise that economic growth cannot
come at the expense of the environment. The importance
of understanding the implications for the diversion and
recycling of these materials merits an individual
discussion on waste treatment in the municipality.
Seasonal Variation in MSW
The monthly per capita variation of MSW in the
municipality showed small fluctuations throughout the
year. There is for example, a noticeable decrease from
January to February with a minimum in February, then a
sharp rise until the month of March (Fig. 5).
This corresponds to the peak of the dry season whereby,
putrescibles which constitute over 50% of the waste
streams limited in supply. The high generation rates from
February to April are related additional wastes resulting
from the consumption of drink products in plastic
containers (water, fruit juice, dairy products, artificially-
flavored drinks, etc.). From April to June, average per
capita generation was constant. This corresponds to the
rainy season when there is a general drop in food
supplies to the city as many food crops are not yet ready
for harvest. From July to August, food crops are ready,
their supply to the city increase leading to an increase in
putrescibles once more and the cycle continues,
beginning from October, the start of the next dry season.
The rise by year end could be explained by the numerous
feasts (Christmas, New Year, other cultural festivals)
which traditionally characterize this period each year. On
the whole, while inert, metal and glass had higher
proportions in the dry season, plastic, organic and special
wastes had a significantly higher proportion in rainy
season. There was no significant difference in the
quantity of wastes generated between the dry and rainy
seasons. Table 5 presents the hypothesis test results and
confidence intervals.

Figure 6. MSW Recycling Rates, 2003–2013
Municipal Solid Waste Management Practices
Solid waste management may be defined as the control
of generation, storage, collection, transfer and transport,
processing, and disposal of solid wastes in a manner that
is accord with the best principles of public health,
economics, engineering, conservation, aesthetics, and
other environmental considerations, and that is also
responsive to public attitudes. The first objective of solid
waste management is to remove discarded materials
from inhabited places in a timely manner to prevent the
spread of diseases, to minimize the likelihood of fires,
and to reduce aesthetic insults arising from putrefying
organic matter.
The Hygiene and Sanitation Company of Cameroon
(HYSACAM), established in 1969, is the country’s leading
private municipal solid waste management company.
Based in Douala and Yaoundé, HYSACAM operates
across the entire municipal solid waste management
chain, from collection through to processing. It has 5,000
employees and a fleet of 400 vehicles. HYSACAM
operates a landfill at PK10, located 10 km away from
Douala city center. The landfill is about 25 meters deep
and covers a 63 ha area, of which more than 10 ha has
been used already (Biotecnogas, 2009). Since 2003 it
has been used for disposal of domestic and commercial
waste collected in the city at an average rate of 287,000
tons per year.
Solid waste management practices in the Douala
municipality include: collection, recycling, solid waste
disposal on land, biological and other treatments as well
as incineration and open burning of waste. The recycling
of materials (paper, plastics, metals, and glass) in the
Douala municipality is practiced by several small and
medium size enterprises.
These include SOCAVER for glass; SIPLAST,
POLYPLAST, SOFAMAC and SICA for plastic waste,
African Recycling Industry, ICRAFON and BOCOM
Recycling. COMAGRI and SOCAVER are leaders of
glass recycling in the city with an estimated production of
110 tons of glass per day. Metals are sold to industry–
mainly in China and India. Hence, the recycling rate of
MSW has risen to about 28% over the past decade (Fig.
6).
In moving towards sustainable waste management, the
Douala municipality must adopt multiple strategies that
target a range of materials and follow the principle waste
management hierarchy: first reducing waste at the
source, re-using materials when possible and recycling
what remains. Should recycling matter go to the recycling
industries, this will reduce the burden on landfill and
environmental effects as landfill will also be minimized.
Although recycling is a definite step towards waste
reduction, processing materials for re-use still requires
the use of energy and resources (Finnveden and Ekvall,
1998) and recycling alone will not create an
environmentally sustainable waste management program
(Armijo de Vega et al., 2003). It seems that by targeting
specific material categories, the municipality could
achieve marked reductions in the amount of waste
generated and sent to landfill.
An examination of the paper recovered from the
municipality waste stream indicates the following
sequence of material prevalence: mixed paper → Office
papers → Newspapers → Magazines & catalogues.
Though targeting paper products in the order of their
occurrence could yield the highest rates of waste
diversion and reduction, a number of technical and
financial complexities may prevent the implementation of
this approach. For example, since office paper represents
5.2% of the recyclable material found in the waste stream
while magazines and catalogues characterizes only
1.9%, it would be logical to aim source reduction efforts
on office papers. Currently there is no alternative.
Determining the alternative that would be truly more
environmentally friendly choice would require a
comprehensive life cycle analysis, which may not be
achievable based on available data.
Composting is a waste management practice that allows
for the transformation of organic waste into a stabilized
product. Composting and anaerobic digestion of MSW

Mbue et al. 099
are strategies that are likely to be employed to reduce
waste generation and to recycle nutrients. Organic
wastes are typically the heaviest component of a waste
stream, thereby costing the most money to dispose of,
and have the highest potential to emit greenhouse gases,
once buried in a landfill (Diaz et al., 1993). The high
financial and environmental costs of improperly disposed
organic wastes make this component especially
important when considering opportunities for increased
waste reduction and diversion (Tammemagi, 1999).
Diverting organics from the waste stream has proven to
be difficult, not only for municipalities but also for the
regions in which they are located. Currently, Cameroon
lacks a nation-wide strategy for managing compostable
organics in the waste stream and as a result, policies for
dealing with this material vary significantly among
municipalities. For example, composting of green waste
is being experimented at the landfill site for the
production of organic fertilizers (compost).Unfortunately,
the market is dominated by competition from chemical
fertilizers. Furthermore, the city is not an agricultural area
it is extremely difficult to find individuals who practice
composting at home.
Incineration is one of the waste treatment technologies
that involve the combustion of organic materials and
other substances. Incinerator process converts the waste
into bottom ash, particulates and heat, which can be used
to generate the electric power. In recent years, the
concepts of protection and preservation of the
environment have gained a prominent place in modern
enterprises. Both BOCOM International (Waste
Treatment and Incineration Company) and BOCAM
(Industrial Waste Management Company) - an ISO
14001 certified companies are leading companies in
waste incineration in Cameroon. In partnership with Mobil
Oil Cameroon, BOCAM collects used oil from Project
work sites, processes the oil at a facility in Douala and
sells the treated oil to a nearby cement kiln for use as a
fuel. Companies interested in eco-responsible
management solutions are signing memoranda of
understandings with BOCAM for the treatment of their
waste products. If well managed, incineration can be a
renewable source of energy. However, the environmental
pollution resulting from incineration is a call for concern.
Again, incineration significantly reduces, but does not
eliminate, the volume of material to be disposed.
CONCLUSION AND RECOMMENDATIONS
The study was to analyses municipal solid waste
generation, composition, and management in the Douala
Municipality of Cameroon as a first step towards
enhancing the sustainability of the current waste
management system. The results presented in this paper
emphasize the potential for municipalities to achieve
higher rates of waste diversion as well as the challenges
that municipalities may face in the shift towards
sustainable MSW management. Paper and paper
products, disposable drink containers and compostable
organic material represented three of the most significant
material types for targeted waste reduction and recycling
efforts. Hypothesis tests were conducted to compare the
municipal waste composition among seasons and
districts and indicated that these had a significant effect
on composition. The rainy season had a higher
proportion of organic waste, whereas dry season
produced higher proportions of, wood, metal, concrete
and glass waste. A statistical comparison with a
previously published waste characterization data
obtained from HYSACAM indicated that the proportions
of all waste categories have not changed significantly.
These insignificant changes in waste composition
indicate that over the past decade, there has been no
new trend in population lifestyle, which must be
considered when planning future waste treatment
scenarios.
The following educational and policy techniques are
highly emphasized:
 promulgation of the waste management bill,
which will create an enabling environment for
enforcement and will provide a legal framework within
which environmental impact can be implemented; political
motivation (waste management must be seen as a
priority at all levels of government);
 education and awareness (waste management
must be taken as a priority among businesses and
communities, to encourage waste minimization and
recycling to enable acceptance of instruments);
development of capacity at all levels of government (for
administration, monitoring and enforcement of
instruments and of illegal dumping, billing for services to
enable cost recovery); increased access to resources for
waste management departments (to allow development
of capacity, recovery of costs, and improved waste
management services);
 Although the data collection samples in percentile
and tonnage are statistically reliable, the idea of
collecting data with a higher level of detail within
subcategories of dominant waste classes is inevitable. To
design an efficient management system, that
consider the appropriate final treatment of MSW based
on their physical and chemical characteristics, it is
important to consider not only information on the
generation and composition of MSW but also their
physical and chemical characteristics. Therefore, it
became necessary for future research to include the
physical (humidity, ashes, and specific heat) and
chemical characteristics (pH, organic matter and sulfur)
of MSW. This information could be very important when
considering the design of biogas and other energy plants
with wastes as primary products;

 Finally, further analysis on waste trends with
respect to household, commercial, and industrial sectors
is also necessary. Because organic waste treatment
options depend on waste origin, it is important to
determine whether the organic waste is pre- or post-
consumed and its moisture content. Such information will
allow for comparisons between various options, such as
composting, biogas production, or utilization as animal
feed. However, whether the quantities produced are
sufficient for a large-scale waste management system
requires further analyses in terms of economies of scale,
operating capacities, and break-even analysis. The data
presented here will facilitate a thorough compilation and
evaluation of the inputs and outputs of such analyses.
ACKNOWLEDGMENTS
The authors would like to acknowledge the authorities of
the Douala municipality and management of the PK10
landfill for their in-kind support. We are also very grateful
to the Cameroon government for assisting research in
higher education through the modernisation allowance.
We show our appreciation to colleagues, friends,
municipalities’members and workers that have
contributed with valuable information. The authors
acknowledged the contributions of Dr. Essam Gooda, Dr.
Brahima Kone, Dr. Lorena De Medina Salas, Dr. Ali
Hammoud and Dr Mohamed Ben Oumarou for donating
their time, critical evaluation, constructive comments, and
invaluable assistance toward the improvement of this
very manuscript.
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Citation: Mbue NI, Bitondo D, Balgah RA (2015).
Municipal Solid Waste Generation, Composition, and
Management in the Douala Municipality, Cameroon.
Journal of Environment and Waste Management 2(3):
091-101.
Copyright: © 2015 Mbue et al. This is an open-access
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