Sampling Household Waste at Source: Lessons Learnt in Gaborone

Abstract

Municipal solid waste (MSW) quantity and composition analysis is fundamental for the planning of municipal waste management services. The purpose of this paper is to report the results and experiences of sampling household waste at the source of generation in Gaborone, Botswana. The average generation rate, in kg capita(-1) day(-1), and percentages of various components of waste in Gaborone were determined using a statistically designed household sampling survey. The survey covered 47 households with different socio-economic characteristics over 21 days with 893 samples obtained. The results showed that the average waste generation rate for Gaborone was 0.33 kg capita(-1) day(-1). Contrary to common belief, the waste generation rate measured as in weight units was found not be directly related to household income. However, the packaging fractions of plastic and paper measured as volume had a direct relationship with household income. Across all income groups, the putrescible waste fraction constituted the highest proportion of the waste stream at approximately 68%. The main general conclusion is on the importance of practical considerations. As much as statistically designed sampling procedures provide a useful means of estimating the quantity and composition of household waste at source of generation, there are some practical issues that should be carefully considered during sampling to improve the accuracy and relevance of the results.

MUNICIPAL WASTE GENERATION AND COMPOSITION IN A TOURIST CITY — HOI AN, VIETNAM

“…The ST3's distribution peaked because the coefficient of kurtosis was higher than the coefficient of kurtosis of the normal distribution, which was equal to 3 14), 16), 22) . Previous studies used mean estimates and standard deviation (SD) 16), 23)- 26) to describe the confidence interval of waste generation rate by tolerating the small amount of skewness to have Normal distribution 22) . However, in this study we used geometric mean and standard deviation for statistical estimates of waste generation rate 14) .…”

“…For stratified random sampling, population mean of waste generation and composition was unbiasedly estimated by a weighted average of means of strata 15), 16) , described by the following equation:…”

Waste Characterization as an Element of Household Waste Management Operations: A Case Study in Limbe, Cameroon

“…As the number of household occupant's increases, waste generation has been found to decrease per person, mainly because of economies of scale in the consumption of goods and packaging in developing countries [21]. Nevertheless, "Abu-qdais et al [21] found" a statistically significant but weak negative relationship between waste generation and household size in Abu Dhabi (R 2 = 0.11), while "Bolaane et al [22] found" a similar weak negative relationship in Gabarone, Botswana (R 2 = 0.34). However, "Parizeau et al [18] found" a weak (R 2 = 0.35), but significant (p = 0.000) negative relationship between waste generation and household size.…”

Análise global das características de frações de resíduos urbanos residenciais

“…Já Bolaane & Ali (2004) apontam uma média de 68%; sendo assim, quando esses resultados são comparados com os do presente estudo, que compreende uma faixa de 40,2 a 68,4%, nota-se que a geração mínima é compatível com a do Banco Mundial, mas a máxima difere deste. Mas, por outro lado, adere-se à média de Bolaane & Ali (2004), o que pode ser explicado em função da quantidade de estudos em países desenvolvidos, em desenvolvimento e subdesenvolvidos utilizados, pois há uma variação de geração de resíduos dependendo da classificação do país. A fração de geração de resíduos orgânicos em todos os grupos de rendas (países desenvolvidos, em desenvolvimento ou subdesenvolvimento) (Tabela 3) corresponde a maior representação; assim, esse resultado adere-se às afirmações de Bolaane & Ali (2004).…”

“…Mas, por outro lado, adere-se à média de Bolaane & Ali (2004), o que pode ser explicado em função da quantidade de estudos em países desenvolvidos, em desenvolvimento e subdesenvolvidos utilizados, pois há uma variação de geração de resíduos dependendo da classificação do país. A fração de geração de resíduos orgânicos em todos os grupos de rendas (países desenvolvidos, em desenvolvimento ou subdesenvolvimento) (Tabela 3) corresponde a maior representação; assim, esse resultado adere-se às afirmações de Bolaane & Ali (2004). …”