Introduction to Maseru (Lesotho) - UNEP System in Maseru City” Maseru City, the capital city of Lesotho, had as of 2005, an estimated population of 300 000, and it grows at a rate

Waste Quantification and Characterization – Maseru (2008)

Extracted from the reports “Final Baseline Report on Waste Management in Maseru City” and “Weak

Spots and Gap Analysis of the Baseline Assessment for the Development of an Integrated Solid Waste

Management System in Maseru City”

Maseru City, the capital city of Lesotho, had as of 2005, an estimated population of 300 000, and it grows at a rate of 7% per annum (MCC, 2005); a rapid growth mainly linked to industrialisation, urbanisation, rural to urban migration and the retrenchment of mine workers.

In 2006 Maseru accounted with:

• Residential 44,300 & 157 villages

• Industrial 29 Textile Industries & 7 other industries

• Commercial 608

• Institutional (schools) 81

• Administrative (offices) 17 Ministries and many private offices

Residential

There are 300,000 people living in Maseru City (Lesotho Review Report, 2006) and 44,300 households (Bureau of Statistics, 2001a) and 157 villages (MCC IEC 2005), which are further divided into low, middle and high-income areas. According to this information, the average household size for Maseru city is supposed to be 6.8 and the average village size be 1,910. However, the results obtained from the current survey show that the average household size for Maseru City is 4.2 while Bureau of Statistics (2001b) shows that the average household size for Maseru district is 4.6. For the purposes of this study, the figures that have been used throughout the report are the ones found by this study but a comparison will be made with other figures.

Industrial Establishments

The city of Maseru is not highly industrialised, both in terms of the size and complexity of industrial activities. There are two small industrial estates, i.e. Thetsane Industrial Estate (shown on Map 5.2) and Maseru Industrial Area (shown on Map 5.3). The industries produce mainly textiles (mostly jeans and t -shirts and, to a limited extent, pants, sweaters, skirts, embroidery and denim fabric). Other industries produce TVs, plastics, paper cartons and soap. There is also a flourmill and a brewery, both of which are located in the Maseru Industrial Area. A brick-making factory is located at Thetsane Industrial Estate.

Introduction to Maseru (Lesotho)





Commercial Establishments

The main shopping complexes, which house most of the shops comprise Sefika Shopping Complex, LNDC, Metcash Building, Carlton Centre, Fairways Centre, Tradorette Mall, Speedy Complex, 60 Minutes Building, Thanda Bantu, Kolo House, and P.L.M. Shopping Complex (Ha Mabote). All of these shopping facilities, shown on Map 5.4, fall within the Maseru Central Business District (CBD).

More than half of the shops in Maseru City are located within the bus stop area. The other busy shopping areas are BEDCO, Borokhoaneng, Thabong, Ha Motšoeneng, Ha Tlelai (Cathedral,Lithabaneng and Ha Hoohlo), Sea Point (along Airport Road), Nutri Foods and Khubetsoana Market (Khubetsoana), and Ha Matala (Hillside).

According to the Department of Trade and based on the licenses there are close to 600 existing commercials with different types identified in Maseru City and 35 registered mechanical workshops. These are mainly located at Maseru Industrial Area, along Main South I Road, Main North I Road, and along the road connecting Main South 1 Road and Lakeside.

Educational Institutions

There are 48 primary schools with 31,030 pupils, 20 high schools with 12,487 pupils and 11 tertiary/vocational/technical institutions with 7,035 Students. The overall number of schools is 81, with 50,552 pupils.

Health Centres

There are five hospitals, two filter clinics and eight clinics in Maseru City;

Administrative Establishments

There are 17 ministries with several offices and many private offices within Maseru City. Forthcoming buildings are the Parliament, Ministry of Health and Social Welfare, and the proposed MCC Building.





Methodology

The baseline data was undertaken by a combination of both desktop study (literature review from previous studies, published and unpublished documents as well as internet to explore international and regional scenarios) and detailed surveys (questionnaires, interviews and field work) on the types and characteristics of wastes generated in Maseru by volume, properties and sources, comprising households, industries, administrative and commercial establishments, and evaluated existing waste management infrastructure. Even where data already existed, a consultative approach was used in order to validate such data. Regular contacts were maintained with key stakeholders.

Projections of domestic waste were based on population growth rate (i.e. 7%) and different types of income levels. In determining future waste generation by commercial establishments, the necessary information such as growth patterns was provided by the Department of Trade. This assessment of projections is further discussed within the report. The projections of future trends of waste production in the industrial sector were based on three (3) scenarios i)‘worst case’ scenario or no/low growth; ii) ‘middle case’ scenario or medium growth; iii) ‘best case’ scenario or high growth.

Relevant government departments were visited where interviews were conducted with key officials and information and data were acquired. Sample surveys of dumpsites and waste infrastructure / facilities were conducted and questionnaires administered to samples of residences, schools, commercial establishments and industries.

Sampling Procedure

Questionnaires were distributed to determine amounts and characteristics of waste generated by households, schools, commercial and administrative establishments as well as industries.

� Residential Areas

Forty-two (42) residential areas were identified within the City. 220 households were selected as samples within these areas and according to different income levels (High-income households ( 25 samples) were those in well-planned areas and villas, with servants’ quarters, while middle-income households (85 samples) were those in semi-planned areas; and low-income households (110 samples) were those in low-cost, unplanned areas) and taking into consideration a fact of density per area (areas with households numbering less than 1000, a sample size of 2.5% was taken, while in areas with more than 1000 households, a sample size of 5% was taken.

To supplement the information obtained through the questionnaires, another sample of

1 Baseline Data (2006)





residential areas was taken in the same categories of high- (50 samples), middle- (20 samples) and low-income (50 samples) where the actual weight of waste produced was weighed. A five-litre bucket was used to estimate the amount waste type a household produced per week. The results of this sampling procedure are likely to be inaccurate as they were dependent on how good each respondent could estimate his or her waste.

� Educational Institutions

In terms of educational institutions (schools), 4 primary schools, 4 high schools and 1 tertiary school were sampled to administer questionnaires. Two primary schools were randomly selected from within town, while 2 were outside town. Similarly, 2 high schools were selected within town, while 2 were selected outside town, the reasoning being that schools from the same locality would be likely to have similar waste types. To supplement the information obtained in questionnaires another sample of 2 high schools (Lesotho High and Thetsane High Schools and 1 primary school (Seventh Day Adventist Primary School) were taken, and their wastes were measured using a weighbridge.

Figure 3.2: Institutions sampled (Survey data 2006)

� Commercial Establishments

A list of commercial establishments was obtained from the Department of Trade. The aim was to sample 100 businesses out of the whole range of existing commercial types, covering major sources of waste. Therefore, the technicians were assigned to specific businesses, of which each covered a minimum of 20% of the identified types. Tables 3.4 below shows the commercial establishments: both the sampled and overall number of existing types.





Table 3.4: Number of commercial establishments sampled

Hotels, guesthouses, Bed and Breakfasts and Shebeens were not sampled because of limited funds and because most of the waste generated is recycled and re- used. The leftovers are given to people to feed animals, cans and bottles are taken by Welcome Transport.

With the exception of bars/off-sales and restaurants, the numbers of the various types of business in Table 3.4 above may not be a true reflection of what is on the ground, as these data, derived from the Department of Trade, do not enable one to know whether the businesses are still operating, given that some businesses do not go back to the Department for license renewal even though still operational and also that many of those closed do not make the Department aware of their closure. There are however many that are operating illegally without licenses.

� Industrial areas

Table 3.5 below shows industries that were sampled. The Consultants undertook a purposive sampling, targeting textile factories and other types of industries.

The respondents were requested to provide information on raw materials and chemicals used, how much waste was produced and how it was disposed of.





Table 3.5: Sampled industries

Questionnaire Administration

The questionnaires administered to households, businesses, schools, industries and waste service providers were structured to include a wide range of both closed and open-ended questions covering issues such as demographics, socio-economic status, key problems in the area, service provision and facilities, waste volumes and waste management practices (questionnaires are attached as Annexes 2, 3, 4 and 5). The questionnaires were tested on a sample of 17 respondents, comprising 10 households, 5 commercial outlets, 1 primary school and 1 high school to ensure their efficiency and effectiveness in providing the required information.

Data Analysis and Presentation

The data generated was captured using Microsoft Excel. Statistical analysis methods were employed to determine the socio-economic status and profiling of the population within Maseru City, the types and characteristics of wastes by volume and properties, as well as their sources and existing waste management practices.

Waste quantities given by respondents were compared to those found by other previous studies conducted within Maseru City. A further comparison was made with situations in other Southern African cities. The samples were also compared to waste collected by MCC trucks from the same residential areas and weighed on a weighbridge to calculate mass. All these steps were taken to get as accurate a representation of the actual figures as possible.





Limitations of the Study

1. The data that came from the Department of Trade, specifically the statistics and information on numbers of commercial establishments operating in Maseru, were found to be unreliable since there were no clear records of such businesses. These records were presented haphazardly and are likely to be distorting the actual scenario/or representation of the commercial sector in the city.

2. Significant delays were encountered in terms of acquiring a weighbridge for the measurement of waste generated by different sources. The weighbridge accessible for the Consultants to use was broken for about 2 months. The second weighbridge considered was later accessed at Lesotho Flour Mills Pty (Ltd). By that time, this component within the waste assessment process had suffered a delay of more than 2 months.

3. MCC vehicles were often out of order and could not be used for weighing. NES was approached to assist with a departmental vehicle (a 3-ton truck). Although this was helpful in determining the tonnages of waste from samples of residences and schools, insufficient time prohibited adequate coverage of all sectors or sources of waste, especially commercial outlets, which are diverse and complex in size and nature of operations.

Weak Spot and Gap Analysis of the Baseline Assessment

A review of the baseline study was undertaken as to identify the information available by the study, the quality of the data and the existing gaps in the current data basis.





Waste Quantities for Residential Areas According to the surveys responses the waste generation in the residential areas of different income level is as presented in the table below.

Table 5.12: Waste generation in different income residential areas in litres per week

Waste generation at different income levels was determined. Table 5.12 shows that middle-income residential areas produced more waste than both low- and high-income areas. Middle-income areas produced almost twice as much as low-income and six times more than high-income areas. The findings of Mvuma (2002) and Seholoholo (1998) show that waste generation is directly relational on the level of income have been corroborated only in low- and middle-income areas. Their findings were that the wealthier one is, the more waste one generates. However, this was not the case with the results of the present study in the high-income areas, mainly because:

• fewer households were sampled at the high-income level compared to other income levels.

• the error margin for these results is high as the study relied on the accuracy of the answers given by interviewees.

• people in high-income areas are more elite and their answers are likely to be different from the ones in the low-income. The results are likely to be more accurate.

Figure 5.1 shows waste generation in low-income residential area. According to this figure, garden refuse is the most generated waste, while ‘other wastes’ are the least

1 Waste Quantification and Characterisation





generated. Almost the same amounts of paper and kitchen leftovers are produced. Figure 5.2 shows waste generation in middle-income area. It also indicates that garden refuse is the most generated and ‘other wastes’ are least generated. Unlike in the low -income, here almost the same amounts of cans and plastic are produced. Figure 5.3 shows waste generation in the high-income residential area. This also follows the same pattern that garden waste is the most generated, while ‘other wastes’ are the least. In the same figure, exactly the same amounts of plastic and ‘other wastes’ are produced.

Figure 5.1: Low Income Level Figure 5.2: Middle-Income Level

Figure 5.3: High-Income Level

Table 5.13 shows types and quantities of waste generated weekly and annually by households. The total volume of waste generated by households was about 10,970 litres per week or 570,490 litres per annum. Garden waste was the most generated waste, constituting 37% of the total waste, followed by paper with 16%, while the least produced was “other waste” with 7%. “Other waste” included batteries and old clothes.





Waste differs depending on the seasons of the year. In this case, garden refuse quantities was high because the study was conducted in autumn when trees shed their leaves and grass dries up and dies back.

Table 5.13: Waste generation for residential establishments

The figures obtained on Table 5.13 above are further demonstrated on the Figure 5.4 below:

Figure 5.4: Types and amount of waste generated by residential establishments





Table 5.14: Household size and total number of people in low-income sample areas

Using the total number of households surveyed in the low income (110) and household size of 4.3, per capita waste generation for low income residential areas was calculated and the answer is 0.2kg/day

Table 5.15: Calculated waste generation by type in kg per annum for low income area





Table 5.16: Household size and total number of people in middle-income sample areas

Using the total number of households surveyed in the middle income (85) and household size of 4.5, per capita waste generation for middle income residential areas was calculated and the answer is 0.3kg/day.

Table 5.17: Calculated waste generation by type in kg per annum for middle income area





Table 5.18: Household size and total number of people in high-income sample areas

Using the total number of households surveyed in the high income (25) and household size of 3.8, per capita waste generation for high income residential areas was calculated and the answer is 0.4kg/day. Therefore, the total waste generated by sampled residential areas is 27,375 + 41,975 + 14,710 = 84,060 kg per annum.

Table 5.19: Calculated waste generation by type in kg per annum for high income area





According to the results in Tables 5.16, 5.17 and 5.18, the average household size within the sampled residential areas in Maseru is 4.2. This is slightly lower than the figure given by Lesotho Demographic Survey, 2001: Vol.1 report, which was 4.6. It has previously been indicated that there are about 300,000 people living in Maseru. If each person in Maseru generates 0.3 kg per day it can be calculated that 300,000 people generate 90,000 kg per day or 32,850,000 kg per annum, which is equivalent to 32,900 tons per annum. Each household in a low-income residential area generates 0.68 kg per day, each household in the middle income residential area generates 1.35 kg day and each household in high income residential area generates 1.6 kg per day. Therefore the average household generation is 1 kg per day.

Each person in the low-income residential area generates 0.2 kg per day, each person in the middle income generates 0.3 kg per day and each person in the high income generates 0.4 kg per day. Therefore, the average waste generation per person per day is 0.3 kg.

Table 5.20: Waste generation by wards in kg/annum

The total waste generated by wards in Maseru is 17,786,453 kg per annum or 17,786 tons per annum. The figure is different from the actual calculated results as average household waste generation was used instead of household generation for each income level. Average was preferred because some wards have a mixture of low, middle and high income.





Figure: Waste generation by MCC Ward





Table 5.21: Waste generated by different income levels

The total mass of waste generated by the residential areas sampled (220) in Maseru city is 84,060 kg per annum, which is equivalent to 84 tons per annum. To validate the information collected through the survey, the actual measurements of waste generated were obtained by weighing truckloads collected from a sample of 120 households, comprising high, middle and low-income residential areas. The results indicate that a total of 950 kg of waste was generated by 120 households per week, meaning that each household generated 8 kg per week and each person generated 0.6 kg per day. The results follow in Table 5.22.

Table 5.22: Empirical measurement of waste generated in kg





To find the total waste generated by the sampled residential area, the empirical results were multiplied by per capita waste generation for each income level i.e. 0.2 kg/ day for low income residential areas, 0.4 kg/day for middle income residential areas and 0.3 kg/day for high income residential areas. Therefore the total waste generated by each income level from the study area was found to be 100,886 kg/annum. This was the most reliable way to get the most accurate results possible. Table 5.23 below shows total waste generation and per capita waste by income level.

Table 5.23: Waste generation using empirical results

According to Table 5.23 above, a sample of 220 households generated 100,886 kg per annum, which is about 101 tons per annum. This is lower than the survey results, which were 32,850,000 kg per annum or 32,900 tons per annum, mainly because smaller samples were used for weighing compared to the larger samples in the survey. These results differ from what the literature says, i.e. the high-income residents generate more waste than the middle-income and low-income categories. A number of reasons are possible;

i. settlements sampled in these study may have mixed classes,

ii. after two weeks of MCC collection vehicles not arriving in the villages, most of the high-income residents would have emptied their bins themselves, as their bins tend to fill up more quickly than those of the low- and middle-income residents,

iii. most of the middle-income residents reported keeping their waste for the whole two weeks they waited for the MCC vehicles to come.

Weak Spot and Gap Analysis:

The domestic sector accounts for the second highest share of waste generated with an estimated 33,000 t/a (see Figure 1). Data collected for the household sector are based on estimates of the generated waste volume by the head of the household, and only a limited number of households have been interviewed (220 households of a total of 44,300; 0.5





%). As the interviewees gave estimates on volumes, results are highly subjective, and the error margin important.

Figure 1: Waste Generation by Sector – Maseru 2006

In the baseline study, the obtained survey results are validated against a set of empirical samples (weighting truckloads from a sample of 120 households). The conclusions drawn from this validation are dubious, as it is stated that the result of 101t/a obtained from the empirical samples of 120 households is lower than the survey results of 32,900 t/a for 44,300 households. By dividing the 101t/a calculated for the empirical sampling by the number of households samples (120), and multiplying the results by the number of total households (44,300), the total amount of generated household waste is 37,500 t/a, which is higher than the 32,900 t/a obtained from the survey, although being of the same order of magnitude. In contrast to what is stated in the baseline report, the empirical samples seem to validate the survey results.

At the breakdown calculation by income level the extrapolation for the total household waste generated in Maseru uses an average value per household waste generation instead of using the calculated figures per income level. It is argued in the baseline study that the average value was preferred, because some wards have a mixture of low, middle and high income. This however defeats the purpose of calculating waste generation figure per income level. It is therefore suggested to use the waste generation figures per income level, and multiply them with the accurate number of households per income level respectively, in order to obtain a more reliable figure regarding the total waste generation in the household sector. For that purpose, necessary data must be sourced from the Bureau of Statistics.

The numbers provided for the different methods used to dispose of waste are interesting. In a next step, it should be established what the waste quantities are that are being disposed of in different ways.

Industrial; 17,900 t/a; 19%

Commercial; 38,900 t/a; 40%

Residential; 32,900 t/a; 34%

Educational; 900 t/a; 1%

Hospitals; 100 t/a; 0%

Administrative; 5,300 t/a; 6%





As biodegradable waste plays an important role on the household level (ca. 40% of total household waste), and that ca. 30% of the surveyed households use composting as one means amongst others for waste disposal (Table 5.24), it is suggested to further investigate the matter in terms of composting approaches used by the households.

Waste Quantities for Industries Several studies have been conducted to determine industrial production and waste generation in Lesotho. These include the study which was conducted by LNDC in 2005 on “The Feasibility Study on Waste Management in Lesotho with respect to the Textile Industries in the Thetsane Industrial Estate” and another which was also conducted by LNDC in 2004 on “Determining Lesotho’s Knitted Fabric Requirements Preparing for the Post September 2007 AGOA rules of Origin”.

The objectives of the former were as follows:

• To identify the feasibility of exporting industrial sludge to South Africa as an option for final treatment and its disposal as temporary measure to alleviate the current problem of lack of appropriate facilities.

• To collect data for the development of a hazardous waste treatment facility in Lesotho as a second option.

• To investigate economical and technical implications of industrial sludge disposal locally, that should be translated into monetary terms.

According to this study, the primary residual wastes produced by the textile industry are non-hazardous, and include fabric and yarn scrap, off-spec yarn and fabric and packaging waste. The fabric off-cuts are used to fire boilers for steam generation. The other waste including packaging material is stored in MCC skips to be collected later and be disposed of at Tšosane dumpsite.

Garments are blasted with aluminium oxide to get a specific colour effect and produce sand blast as waste. The denim product is washed with pumice stone, and this also becomes a waste product. Table 5.29 summarises the results obtained by the study.

Table 5.29: Waste Generation by Woven Garments Industries in tons per annum





Table 5.29 shows that 2,073 tons of sludge, 3,000 tons of blasting sand and 6,600 tons of pumice stone were generated per annum and that the total waste generated by Woven Garments industries is 11,673tons per annum. This does not include waste generated by knit garments industries i.e.-shirt industries. An investigation was made to get the information that was missing on Table 5.29 and the results are shown in Table 5.29. According to the interviews held with CGM representative, it was indicated that the CGM group i.e. United Clothing, CGM and Presitex generate a total of 2 tons of sludge per day making 60 tons per month i.e. 720 tons/year. This means that the average sludge generation per each firm is 240 tons. This would change the total waste generation by woven garment industries to 11,925 tons per annum.

The other group of jeans known as Nien Hsing international comprises of Nien Hsing, Global, C&Y and Formosa denim mill reported to produce a total of 8 tons of sludge per day which is equivalent to 240 tons per month thus, 2,880 tons per year. That means the four firms produce 720 tons each per year. The results for blasting sand and pumice stone did not change as the two groups claimed to give the away ash to people who make bricks and no quantities were given.





Table 5.30: Waste Generation by Woven Garments Industries (Tons/annum)

Table 5.30 shows combined information from LNDC (2005) with the findings of the current study and the total waste produced is 13,200 tons making a difference of 1,527 which could be the information missing for Formosa, CGM and United.

The conclusions made by the study were as follows:

• Hazardous waste is disposed indiscriminately within and outside the industry.

• There is a need in Maseru to develop hazardous landfill.

• For management process of industrial wastes both in Lesotho and South Africa it would be useful for industrialists to delist the waste stream from hazardous waste to general waste.

• There is a need for management of industrial sludge locally as its transportation to the nearest landfill which is in South Africa is too far and costly as well.

• Before the development of proper landfill in Lesotho all sludge and sand will have to be disposed of at an approved landfill in South Africa.

The other study that was conducted by LNDC in 2004 was determining the volume of knitted fabric being consumed by Lesotho manufacturers of knitted garments. It was estimated that Lesotho consumes between 22,000 and 26,000 metric tons of knitted fabric per year and about 220 tons of knitted trims and accessories such as collars and ribbed cuffs and hems. The knitted apparel includes sweater, women’s and men’s trousers and shorts, T-shirts and shirts/blouses. The findings of this study were as follows:





Table 5.31: Total USA imports of Knitted Apparel from Lesotho

Table 5.32: Total Canada and European Union

The study concluded that:

• Based on the information given above it was estimated that Lesotho exported 21,100 tons per annum (based on the average lighter weight knit fabric of 250 g/garment) of knitted garments to USA, Canada and some member states of the EU and 25,400 tons per annum (based on an average slightly heavier weight fabric of 300 g/garment).

Using the information given by this study it was possible to calculate the waste generated by knitted garments manufacturers in Lesotho. It was indicated the following:

� To make 90,000,000 units of garments weighing 250g/garment needs 22 500 tons

� To make 90,000,000 units of garments weighing 300g/garment needs 27 000 tons

� 21,100 tons are exported using 250g/garment that means 22,500 – 21,100 = 1,400

� 25,400 tons are exported using 300g/garment this means 27,000 – 25,400 = 1,600.

Therefore, the total waste generated by knitting garments is 3,000 tons per annum making 6% of the total material used. The total amount waste generated by industries is 13,200 tons of sludge + 3,000 knitted garments + 1,678 tons by brewing company = 16,351 tons per annum





Table 5.33: Summary Profile of Maseru’ Textile & Apparel Industries





The study decided to use the two studies mentioned above as the data seems reliable and not outdated. Moreover, the factories have not changed their ways of operation or increased in number to justify a significant difference. The only addition was made regarding other industries that are not textile.

Another waste from textile factories is plastic that is used to cover fabric rolls, which is taken away and recycled by the plastic bag making factory. The quantity of this plastic is not known.Table 5.34 shows waste produced by the brewing and soft-drinks making company.

Table 5.34: Waste produced by the brewing and soft-drinks making

Ash from the boiler, which makes the largest volume of waste, is sold to a customer who makes bricks with the material. Spent grain, which makes the second largest volume of waste, is given to customers who use it for animal feeds.





Labels are taken to Tšosane dumpsite. Cullet bottles are taken back to Consol in South Africa for recycling. Cans are recycled via Welcome Transport.

The bulk chemicals comprise sodium hydroxide and chlorine. The former is stored in large tanks. The flour milling company reported that it produces waste paper and plastic from packaging material, scrap metal from machinery, wood from broken pallets and waste oil. However, the company did not provide the quantities for these.

The TV assembler produces about 300 – 400 pallets and 400 – 500 boxes per week. The other troublesome waste is polystyrene/polyform, which its quantity was not known by the factory. However, Welcome Transport, as a collector of such polystyrene, could estimate 100m3 per month.

In terms of waste management practices, the brewing company reported to sort waste at source, collect and compact cans and crush light tubes. The flourmill reported that it empties its dustbins and skips on daily basis. Textile factories burn off-cuts to produce steam.

Concerning problems that industries encounter in managing waste, the brewing company reported the limited capacity of their service provider to handle all types of waste. The flourmill stated lack of recycling facilities. Textile factories that take waste to Tšosane themselves also stated that this is time consuming. They all wanted a waste disposal service from the MCC.

In terms of contribution to help the MCC to reduce and recycle waste in the city, brewing company expressed the need to strengthen sorting of waste at source.

Regarding their expectations of the MCC, the brewing company cited allocation of an appropriate site for dumping waste as essential. The flourmill stated that the MCC should have recycling places for waste oil, plastics and paper.

Weak Spot and Gap Analysis:

The industrial sector accounts for the third highest share of waste generated in Maseru with 17,900 t/a (see Figure 1). The main difference of the industrial sector to the other considered sectors is the amount of hazardous wastes generated.

The knitted textile industry produces 3,000 t/a of textile off-cuts that are non-hazardous and are mainly being burned. Due to US trade related issues, it is not possible to release these off-cuts into the local markets for re-use or recycling purposes.

Although figures are given for the textile industries, source documents prepared by the LNDC dealing with the issue had to be consulted in order to clarify hazardous waste classifications1 It is state by the LNDC with regards to hazardous waste that “the waste

1 LNDC, 2005: "Feasibility Study on Waste Management in Lesotho with respect to the Textile Industry in

the Thsesane Industrial Estate"





that remains on site and which is not collected by MCC, generally classified as hazardous waste and generated at the garment factories and mill consists primarily of sludge, blasting sand and pumice stones”. In Appendix E of the LNDC study submitted in February 2005, a total amount of 11,700 t/a of hazardous waste is given; the baseline study gives a slightly higher number – 13,300 t/a – for 2006, which will be used as a basis for further calculations in the gap analysis and ultimately the ISWMP. However the statement that “most of the primary residual wastes generated in the textile industry are non-hazardous” as given by the baseline study is not correct, as 75% of the total industrial waste stream is classified as hazardous.

Data for the brewery industry are good, whereas no or little data was provided for the flour milling company as well as the TV assembler.

Waste Quantities for Commercial Establishments To determine the quantities of waste produced by commercial establishments, questionnaires were administered to different businesses. The sample sizes are shown in Tables 5.35 .and Map 5.5 shows the distribution of commercial establishments within the CBD and at the old bus stop area (Pitso Ground area).

Table 5.35: Existing commercial by type and sample size

LNDC, 2004: "Determining Lesotho's knitted fabric requirements preparing for the post September 2007 AGOA rules of origin"





The volume of waste generated by the sampled commercial establishments (101) is about 11,903 litres per day or 83,314 litres per week. Table 35 shows the amounts of waste generated by waste type, while Table 5.36 shows waste quantities by the different categories of commercial establishments.

Table 5.36: Waste generated by types for sampled commercial in litres day

Table 5.37 below shows daily and annual waste generation by commercial establishments. Using waste produced and sample size, per capita waste generation per litre per day was calculated. In order to get the total amount of waste generated by commercials in Maseru per capita was multiplied by number of existing commercial establishments in Maseru. The result was 179,266,190 litres per annum.

Table5.37: Waste generation by commercial and per capita waste generation





To convert volume (litres) to mass (kilograms/tons), the density of each waste type was multiplied by waste generated in litres. The densities were derived from a similar survey which was conducted in Kwazulu Natal in South Africa since there was no study conducted in Lesotho that established densities. Table 5.11 shows the total waste generated by 101 sampled commercial establishments in kilograms per annum. Therefore, the total amount of waste generated by the commercial establishments in Maseru is 17,376,555kg/annum which is equivalent to 17,377 tons per annum.

Table 5.38: Waste generation by type for sampled commercial in kg

To get the total waste generated for commercial establishments in Maseru in kilograms, the following formula was used.

The results shows that 101 commercials generated 17,376,555kg/annum that means 1,091 commercials will generate (17,376,555kg kg/annum x 1,091commercials)/101 commercials = 187,701,203 kg / annum. Thus the total waste generated by commercial establishments is 187,701,203 kg/ annum which is equivalent to 187,701tons/ annum

To supplement the information collected the actual measurement of waste generated was done by weighing a truckload of waste from two big shopping complexes namely Sefika and LNDC. The waste from Sefika complex was found to be 460 kg per day while that of LNDC was found to be 520 kg per day. That means Sefika alone generates 154,560kg per annum and LNDC generates 174,720kg per annum. The two add up to 329,280kg per annum or 330tons per annum. The result is slightly lower than the extrapolated result mainly because some shopping complex did not have the opportunity of their waste being weighed.

It must be noted that not all waste produced from commercial establishments is properly disposed of at the existing dumpsite (at Tšosane dumpsite). While all the furniture stores, retailers, butcheries, fruits and vegetables stores indicated that they dispose of their waste





at Tšosane dumpsite, 13% supermarkets, 50% wholesalers, 75% hardwares, 25% liquor stores and 55% cafes indicated that they also burn their waste as a means of waste reduction. In very few instances they also give their waste to recycling centres. It is worth noting that the respondents who mentioned that they dump in nearby dongas came from the peripheries of the urban areas or the outskirts of the town, for example Ha Tsolo, which is notorious for illegal dumpsites.

The analysis indicates that the top ten problems experienced by commercial establishments in Maseru in terms of waste management are as follows:

The respondents who indicated that they do not experience any problems were predominantly those who do not derive their waste services from MCC but from individual transport owners as well as established waste removal service providers such as Lefielo Cleaning Services and P&L Cleaners. Other than that, they indicated that they dispose of waste themselves.

The waste from mechanical shops was also not added to the total waste, as the wastes were not given in litres per waste type nor in kilograms (their summary follows in the next section).

Weak Spot and Gap Analysis of the baseline:

Based on the figures given by the baseline study, the commercial sector would account for the highest share of generated waste with 187,701 t/a.

However, major calculation errors were detected in the baseline study. In table 5.37, the total extrapolated waste volume generated by supermarkets is not 147,752,090 l/a, but 14,775,209 l/a. The total volume of waste generated would therefore change from 179,266,190 l/a to 46,289,309 l/a.

Furthermore, in table 5.28, the mass of waste in kg/d has not been calculated properly. The daily volume of waste given in the second column should have been multiplied by the waste density in kg/l as given in the third column, which has not happened. Therefore, all figures in the fourth and fifth column are erroneous. By correcting these figures, the





total quantity of waste generated for the commercial sector in Maseru changes from 187,701 t/a to 38,900 t/a.

The latter error has repercussions on the total waste amount generated for Maseru. The total waste generated from commercial outlets must be changed from 187,701 t/a to 39,000 t/a, the total amount of waste generated in Maseru being 96,000 t/a2 instead of 255,832 t/a as given by the study. By readjusting these numbers, the commercial sector still accounts for the highest share of generated wastes, but falls from the perspective of an order of magnitude into the same category as household waste.

It has been identified that from a waste handling perspective, a bailing machine exists at the Shoprite shopping centre.

An important aspect missing in the baseline study is that the commercial sector consists of two distinct types of activities. On the one hand, large commercial activities such as shopping malls and formal shops generate specific types of waste (e.g. paper, cardboard, LDPE plastics) usually collected in formal skips/containers. On the other hand, small commercial activities such as street vendors and vendors at the open fruit and vegetable markets generate waste with a high share of biodegradables, which are collected/dumped in rather informal ways (small containers, burning, spillage, food waste recovered to feed animals).

Waste generation by types

Based on the assumptions and calculations described for the different sectors as presented here fore, the quantity of wastes generated by waste types has been extrapolated. The assumptions made might not represent the ideal figures, but they provide at least an idea on the order of magnitude regarding the different waste types.

Figure 2: Generated Waste Quantities by Type – Maseru 2006

2 The total amount of waste generated is 105,000 t/a taking into account assumptions for the sectors not covered by the baseline study.

Glass; 9,1%Cans; 3,4%

Scrap Metal ; 3,6%

Biodegradables; 23,9%

Paper; 22,5%

Plastics; 14,5%

Other; 10,6%

Hazardous; 12,5%





As can be seen in Figure 2, the waste types paper and biodegradable wastes (kitchen leftovers and garden refuse) represent the highest shares of the wastes types generated with 24% and 22% respectively of the total generated waste volume of approx. 105,000 t/a. Plastics represent 15% of the total generated waste types, and a breakdown of generated amounts by type of plastic (PE, PET, LD PE, PS, PVC, etc.) would be helpful for the investigation of future treatment alternatives. Hazardous wastes account for 12.5%, letting appear the importance of this type of waste in Maseru, requiring immediate action, as it is not handled properly at the moment of writing. Glass and other wastes account for only 9% and 10.5% respectively.

Based by number of Collect-a-Can South Africa, it has been calculated that the amount of waste cans generated in Maseru should be approx. 800 t/a, five times smaller than the figure given by the baseline study (ca. 3,600 t/a).3 Furthermore, the amount of scrap metal is estimated at around 3,800 t/a; this is however the amount of scrap metal being recovered by the recycling companies (see Section 2.2.8). Therefore, it is suggested that these figures need refining and should therefore be recalculated.

By trying to establish the figures for waste quantities generated by type, it became apparent that some important numbers are missing in the baseline study. These gaps have been identified for each waste generation sector separately, and have been summarised in the Table 2.

Waste Quantities for Mechanical Workshops A special category of commercial establishments is motor or mechanical workshops. Waste produced here that is of interest comprises brake pads, brake linings, clutch plates and tyres.

From the sample of 6 workshops, the 2 large-scale workshops, i.e. Lesotho Nissan and Imperial Fleet Services, replace about 10-15 pads a day, which make 60 – 90 pairs per week. At Imperial, which is a company that leases vehicles to the Government of Lesotho, about 15 cars change sets of tyres per day, which is about 90 sets of tyres per week. Other waste such as cans, cardboard and glass make about 2 x 85 litres per day, which add up to 1 020 litres per week. About 80% of this is oil cans.

Three out of 4 small-scale workshops change an average of 3 brake pads, 2 linings and 3 clutch plates per week. Per capita waste generation for large-scale mechanical workshops is 80 brake pads, linings and clutch plates, and 800 litres oil cans and 1000 litres other waste per week. There are about 31 small-scale and 4 large-scale workshops within Maseru City. This means the numbers of brake pads, brake linings and clutch plates replaced is over 300 pairs per week or all of them.

3 Approx. 3 billion cans are consumed in South Africa each year. Based on a total population of South Africa of 47 million, the weight of an empty can of 40g, and a population of Maseru of 300,000, the total amount of generated empty cans would be approx. 800 t/a.





Weak Spots and Gap analysis

Mechanical workshops have been listed as a special category of commercial establishments. The waste amounts generated have not been included to the total waste volumes for the commercial sector, i.a. because conversion factors for the break-pads, tyres, etc. are not given.

Waste Quantities for Schools The information for waste quantities for schools was first collected through questionnaires, and this was later supplemented with actual measurement of waste generated from schools. As explained in chapter three, four primaries, four high and one tertiary school were sampled. The results are shown in Table 5.39.

Table 5.39: Waste generation for schools in volume (litre) week

According to Table 5.39, the total amount of waste collected in primary schools was 5,555 litres per week while high schools generated 3,610 litres per week and tertiary school generated 2,845 litres per week.





In primary schools, the largest volume of waste came from paper, followed by plastic and then garden refuse. In high schools, the largest amounts ware made up of garden refuse, followed by paper and then kitchen leftovers. Thus, paper and kitchen leftovers were the first 3 largest quantities. In primary and high schools, glass was the least generated waste. In the category of ‘other waste’ is ash.

Table 5.40: Waste types by schools in litres per week

Table 5.41: Number of pupils per sampled schools





To get the amount of waste produced by sampled primary schools, density of each waste type was multiplied by volume of each waste type. The answer was 151 kg/day, this was multiplied by 180 school days to get annual waste and the answer was 27,180 kg per annum. The total daily production was further divided by number of students in the sampled primary schools (4397) to get per capita waste and the answer was 0.03 kg/day. This is illustrated in Table 5.43 below. If there are 31,030 pupils in primary schools, and if each pupil produces 0.03 kg of waste per day, 31,030 pupils will produce (31,030 x 0.03 x 180) =167,562 kg per annum.

Table 5.42: Waste generation by sampled primary schools (4) in kg





To get the amount of waste produced by sampled high schools, density of each waste type was multiplied by volume of each waste type. The answer was 621kg/day, this was multiplied by 180 days to get annual waste and the answer was 111,780kg per annum. The total daily production was further divided by number of students in the sampled high schools (2,501) to get per capita waste and the answer was 0.2kg/day. This is illustrated in Table 5.44 below. If there are 12,487 pupils in high schools, and if each pupil produces 0.2 kg of waste per day, then 12,487 pupils will produce (12,487x 0.2 x 180) = 449,532 kg per annum

Table 5.43: Waste generation by sampled high schools (4) in kg

To get the amount of waste produced by sampled tertiary school, density of each waste type was multiplied by volume of each waste type. The answer was 526kg/day, this was multiplied by 180 days to get annual waste and the answer was 94,680kg per annum. The total daily production was further divided by number of students in the sampled tertiary school (2525) to get per capita waste and the answer was 0.2kg/day. Practically senior students have more buying power than junior students and therefore per capita waste for tertiary was expected to be higher than that of high school. The reason may be that the sample for tertiary was too small at least if two or three tertiaries were sampled the results would have been different. This is illustrated in Table 5.44 below. If there are 7,035 pupils in tertiary schools in Maseru, and if each student in tertiary school produces 0.2 kg of waste per day, that means 7,605 students will produce (7,605 x 0.2 x 180) =273,780kg per annum.





Table 5.44: Waste generation by sampled tertiary school (1) in kg. Per capita/ pupil/day 526/2501=0.2

Table 5.45: Total number of pupils and waste generation in kg

Table 5.46: Daily and weekly waste generation for schools in kilograms (kg)





Table 5.46 shows empirical measurements of waste generation for a sample of two high schools and one primary school in kilograms (kg). The number of schools selected for

weighing may not be representative because schools were closed and these were the only ones opened. All the tertiary institutions were closed so no weights were measured for them. To find the amount of waste generated by schools in Maseru, the total number of pupils and per capita waste generation were used (Table 4.5).

Using the empirical measurements, the total number of primary student is found to be 31,030; multiplying this by per capita of 0.02kg/day and by 180 days the answer is 11,708 kg per annum. The total number for high school students is found to be 12,487; multiplying this by per capita of 0.07kg/day and by 180 days the answer is 157,336 kg per annum. The empirical measurements are different from the survey results mainly because few schools were selected for weighing.

Regarding the different means of waste disposal that schools practise, 3 high schools and 2 primary schools reported to burn their waste. Two (2) high schools and 2 primary schools also take their waste to Tšosane dumpsite. Lesotho College of Education (LCE) reported to only dispose all its waste at Tšosane dumpsite. Only one primary school reported to bury waste and make compost with some.

In terms of key problems that they encounter in waste management, 3 out of 4 primary schools complained of students and passers-by throwing waste all over. The same attitude of pupils throwing litter all over the place was also reported in 2 high schools. This shows that most of the schools do not have waste management systems in place or where such system exists; pupils do not yet see the need to follow it.

When asked to mention a few ways they believe they can help the MCC to reduce and recycle waste, more than 50% of both primary and high schools indicated that they could educate their pupils to clean up and keep the waste separated according to different types. This shows that teachers understand that waste could be sorted at source and perhaps recycled.

Regarding the expectations about the MCC in terms of its contribution to help them better manage their waste, the sampled schools mentioned the need for more bins to enable them to store waste in separate bins. They needed free extra bins to add to the ones already in use. They also expressed the need for more frequent disposal of bins, e.g. 2 - 3 times a week, as against once a week.

The tertiary institution serviced by the MCC was not satisfied by the irregularity of the MCC service. Just as was the case with the lower level schools, this institution also requested the MCC to empty the bins at least twice a week.

Weak Spots and Gap Analysis

The educational sector accounts for 1% of the total waste generated in Maseru (see Figure 1). The numbers provided are reliable, and split according to primary, secondary and tertiary institutions.





Source separation of wastes is not practiced at schools in Maseru, although one school runs a composting project for garden waste. It would be useful to investigate the role that schools could play regarding awareness creation and implementation of pilot projects within the framework of an ISWMP.

Waste Quantities for Clinics and Hospitals The Ministry of Health and Social Welfare (MOHSW) conducted a study on Health Care Waste (HCW) and developed a National Health Care Waste Management Plan (NHCMP) in 2005. Since the study was still new the consultants used the findings of this study. As a result, a survey was not conducted for medical waste. The aim of the MOHSW study was to identify the level of HCWM that will be relevant to help implement and enforce environmentally sound, technically feasible, economically viable and socially acceptable systems for management of HCW in Lesotho.

The findings were as follows:

• HCWM is not assigned any specific authority

• Segregation of HCW is not observed by the medical staff

• Staff engaged in HCW handling is not provided with appropriate protective equipment

• All staff is not trained in HCWM

• HCW is not accorded effective treatment

• There is rampant theft of plastic bucket type medical bins

• Hospitals grounds are not maintained in a manner deserving of a health care institution\

• There is general poor maintenance of equipment from the incinerator to the sewerage network.

The HCWM plan requires that HCW be separated into three categories mainly; potentially infectious waste, used sharps and general waste through the use of three different coloured bin or bags. Again it requires an establishment of basic system for collection and disposal of HCW.

The implementation of the HCWM plan is in advanced but has not yet started. In order to assess the HCW generation a survey was conducted at Queen Elizabeth II hospital for a period of a month and the results are as follows:





Table 5.47: Health Care Waste weights at Queen Elizabeth II Hospital in kg/month





Table 5.47 shows Health Care Waste (HCW) generation by Queen Elizabeth II (Queen II) hospital. The study was carried during December month. According to the study, 4,278.3 kg of general waste and 4,457.3 kg of HCW were generated respectively per month making a total of 8,735.6 kg per month. This is equivalent to 104,827.2 kg per annum or 105 tons per annum. There are 450 beds at Queen II, meaning that daily waste generation per bed per day is 0.64 kg.

Table 5.48: HCW generated by hospitals in Maseru in kg (extrapolated estimates)

NOTE: 80% was calculated from the Health Statistics Tables (2004)

Table 5.48 shows HCW generated from all hospitals in Maseru city. The total waste generated by Queen II hospital is 83,950 kg per annum or 84 tons per annum. The results are slightly lower than that calculated from the survey results because the extrapolated results did not include the waste generated by outpatients while the Queen II study looked at all the waste generated by the hospital except pharmaceutical wastes which are returned to the storeroom and can only be destroyed after consultation and in the presence of relevant stakeholders which include Department of Finance and Treasury. Another reason can be that the study was conducted in one month which can result in waste being different in other months. The table further shows that the total amount of waste generated by hospitals in Maseru is 129,210 kg per annum or 130 tons per annum. The waste generation figures given in Table 5.49 include for both in-patients and out-patients whereas the one on Table 5.47 is for in-patients only.





Figure 5.6: Waste generations for Hospitals in Maseru

According to WHO (1998) in the Ministry of Health and Social Welfare (2004), types of waste produced in health care institutions are classified into anatomical, infectious, sharps, pharmaceutical, radioactive, chemical wastes and their definitions are as follows:

1. Anatomical wastes are human tissues, body parts, foetuses, placentas, and other similar wastes from surgeries, biopsies. This also includes organs and tissues infected with human pathogens.

2. Infectious wastes are blood and blood products and other body fluids, items contaminated with blood, serum or plasma, cultures and stocks of infectious agents from diagnostic and research laboratories and items contaminated with such agents, isolation wastes from highly infectious patients (including food residues), discarded life and attenuated vaccines, waste, bedding, bandages, surgical dressing, and other contaminated material infected with human pathogens.

3. Sharps are needles, syringes, scalpel blades, suture, razors, infusion sets, contaminated broken glass, specimen tubes, and other similar material.

4. Pharmaceutical wastes are outdated medications and residuals of drugs used in chemotherapy, as well as items contaminated by or containing pharmaceutical bottles or boxes.

5. Radioactive wastes are any solid, liquid, or pathological waste contaminated with radioactive isotopes of any kind.

6. Chemical wastes are solid, liquid, or gaseous chemicals such as solvents, reagents, film developer, ethylene oxide, and other chemicals that may be toxic, corrosive, flammable, explosive, or carcinogenic.

*Waste from the clinics is taken to the hospitals to be incinerated






The hospital sector accounts for less than 1% of the total waste generated in Maseru (see Figure 1). One particularity is however the amounts of hazardous waste generated. The figures provided by the baseline study are sufficient and reliable, and have been sourced from a study undertaken by the Ministry of Health and Social Welfare (MoHSW).

An ambiguity remains regarding general waste generated by hospitals. The baseline study doesn’t clarify whether general waste is collected separately, or is mixed with the health care waste. In case of the latter, source separation would definitely have to be considered. The constitution of the general waste is also missing. For the purpose of calculating generated waste types, it has been assumed that the constitution of general waste from hospitals is similar to the constitution of residential waste. See Appendix E or the detailed breakdown of generated wastes by type.

Moreover, the baseline study does not clarify which amounts of health care wastes are disposed of via which means (dumping, incineration, pit burning).

Waste Quantities for Administrative Establishments Another questionnaire was administered to service providers. These are companies that provide cleaning services in administrative establishments (offices). Seventeen (17) service providers were identified (Annex 5). Of these, only four (4) clean and collect wastes, the rest provide cleaning only. The former are as follows:

a) Lefielo Cleaning Services

b) Scichem Cleaning Services

c) Aero Tech Cleaning Services

d) Lesotho Golden Associates (LESGA) Pty Ltd

LESGA and Lihlabo Cleaning collect “she bins” (Sanitary Hygiene Equipment) and burns the waste at Tšosane dumpsite.

Questionnaires were meant to collect information regarding waste generated by the offices, how much is collected and how much is disposed of. The data collected were not representative enough as a lot of waste from the offices goes into the MCC’s fleet and quantities could not be determined because it is mixed with waste from other waste sources. The waste collected by the four companies coming from administrative establishments amounted to 40,930kg per week or 5,322,640kg per annum or 5,323tons per annum.

It was not easy to get information for waste generated by administrative establishments since most offices are rented out and waste management is the responsibility of the landlord. Some landlords hired private companies to clean their buildings and put waste in the bins to be collected by the MCC. Some however contracted the same cleaning company to collect waste and disposed it of while some contracted a different company





to collect their waste and dispose it. For this category, the results are shown in Table 5.49. Due to financial constraints mentioned earlier, the consultants were not able to collect and separate the administrative waste and weigh it. It was also not clear who to give the questionnaire to (landlord, tenant or service provider). The information collected came from four service providers who collect waste. They did not know how much they were collecting, so the estimations were made using the size of the vehicles used and number of loads made. The cleaners could not estimate how much was collected from each office as different sizes of containers were used.

Table 5.49: Waste quantities for administrative establishments in kg

To validate the waste from administrative establishments, a truckload was taken from two office complexes (Telecommunication training school and headquarters) and weighed on the weighbridge. The weight recorded was 1,540 kg/day.


As already mentioned in the baseline study, the data provided for the administrative sector are scarce, and no breakdown according to waste types is available. It is however assumed to be of a minor issue, as the administrative sector accounts for only 6% of the total waste generated in Maseru (see Figure 1). In order to estimate the waste types generated by the administrative sector, it has been assumed that its constitution is identical to the constitution of the waste generated in the residential sector.

It has been observed that a current practice is to burn paper wastes from offices. It might be a way of discarding of confidential data, but should be investigated further.

A figure lacking from the baseline study is the amount of green wastes generated from inner-city forests and parks, which would fall under the responsibility of the administrative sector.





Total Waste Generation in Maseru City Table 5.50 below shows that the calculated total amount of waste generated in Maseru City is 141,280. Most of the commercial waste is taken by waste collectors for recycling e.g. cardboard and packaging plastics from shops and wholesalers. Kitchen leftovers from the hotels, bed & break fasts and restaurants is taken by people to feed animals. Cans from the hotels and most fast food cafes is taken by can collectors hence the reason why commercial waste has gone down plus the other reasons given earlier.

Table 5.50: Total waste generation in Maseru City compared with Mvuma’s (2002)

The total waste generated in Maseru according to the study is a bit higher than that found by Mvuma (2002) because he did not include hospitals and administrative establishments and because of growth that has taken place in four years. The school waste seems to be lower in our study maybe the samples taken were not representative enough. Mvuma’s industrial waste seems to be far lower than what the study found maybe he did not include waste from the Brewing Company and the Knit Garments.

Another type of solid waste identified and observed is construction debris. This seems to be growing at an alarming rate. After 1998 political unrest in Lesotho, a lot of buildings were burnt. The reconstruction process resulted in a lot of buildings being demolished. There was no specific area designated for rubble coming from the demolition of buildings. These were then dumped anywhere along the roads, in dongas, etc. Since then, a lot of people have been dumping rubble rampantly. There are many waste heaps identified all over the place. This waste could be hazardous as some have cement, asbestos, etc. Plate 5 shows one of the construction debris dumped at the football pitch. Although rubble has been identified as a problem, the proper investigation on volume and composition was not determined due to lack of weighing instruments.

Another solid waste type that has been observed as a problem is used car tyres. There is no collection of tyres for recycling or a safe place for disposal. As a result, they end up at Tšosane dumpsite. During burning, these cause dioxins that are carcinogenic. However, this study did not devote sufficient time to tyres due to financial constraints.





Further investigation is needed here. However, investigation was made into how many tyres are imported into the country as there are no tyre manufacturing companies in Lesotho.

Table 5.51: Number of imported tyres


It has been roughly estimated that the waste types which have not been covered by the baseline study, i.e. e-waste, used tyres, builder’s rubble, sewage sludge and car batteries, account for a total waste amount of 10,300 t/a.4 The breakdown for the different waste types is as follows:

Types of waste 2006

e-Waste 1,0% 100,00

Used Tyres 1,0% 100,00

Builder's Rubble 48,5% 5000,00

Sewage Sludge 48,5% 5000,00

Car Batteries 1,0% 100,00

Documents

Introduction to Maseru (Lesotho) - UNEP System in Maseru City” Maseru City, the capital city of Lesotho, had as of 2005, an estimated population of 300 000, and it grows at a rate