sustainable waste management in Bangladesh. For this ... Urban solid waste management is considered to be one of the most serious environmental problems.
Selected Socio-economic Factors Affecting the Willingness to Minimize Solid Waste in Dhaka City, Bangladesh Rafia Afroz1 Rabaah Tudin2 Keisuke Hanaki3 Muhammad Mehedi Masud1 1
Department of Economics Faculty of Economics and Management Science International Islamic University Malaysia 2 Department of Economics Faculty of Economics and Business University Malaysia Sarawak 3
Department of Urban Engineering Faculty of Engineering The University of Tokyo Japan
Abstract This paper examines the factors that influence the waste generation and willingness to minimize solid waste in Dhaka city, Bangladesh. Information on waste generation, willingness to minimize, socioeconomic characteristics, and behavior of the households towards solid waste management were obtained from interviews with 402 households in Dhaka city. Of the 402, 103 households regularly practiced recycling activities. Ordinary least square (OLS) regression and logistic regression analysis were used to determine the dominant factors that might influence the waste generation and households’ willingness to minimize solid waste, respectively. The results found that the waste generation of the households in Dhaka city was significantly affected by environmental consciousness, income groups specifically the middle income earners and willingness to separate. The significant factors for willingness to minimize solid waste were environmental consciousness, income groups particularly the middle income earners, young adults mainly those aged between 25 to 35 years and storage facility. Establishment of solid waste management program could be an effective strategy for implementing sustainable waste management in Bangladesh. For this strategy to succeed, however, active partnership between the respondents and waste management service department is required. The respondents’ behavior toward solid waste management practices should be taken into consideration as should the results of this study, which are important indicators of respondents’ positive attitudes toward sustainable waste management in Dhaka city. Key words: : waste minimization, waste generation, recycling, logistic regression model, Perception and attitude,
1. Introduction Urban solid waste management is considered to be one of the most serious environmental problems confronting urban areas in developing countries (Pfammatter and Schertenleib, 1996; Sinha and Enayetullah, 2000; WRI et al., 1996) and Bangladesh is no exception. Bangladesh has the highest density of population among all countries of the world. It has very little open physical space and empty terrain to
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cushion the country against environmental shocks. Therefore, any environmental contagion in Bangladesh is sure to spread very fast and affect millions of people. (Salequzzaman and Stocker, 2001). If the population increase, resource consumption also increases as the side effect (Haden et al.,2009) and highest population has the highest generation of waste (Ayotamuno and Gobo, 2004). Urbanization in Bangladesh is no stranger than what happen in China’s urban migration that has become a burden to economic development and a problem for the environment (Ling & Isaac, 1996). Bangladesh’s population density is already 50 times higher than that of the USA, six times higher than that of China, and is the worst victim of environmental degradation therefore, protection of the environment is therefore necessary even from the view of social justice (Salequzzaman and Stocker, 2001). Dhaka, the capital city of Bangladesh, with more than 10 million inhabitants, is one of the fastest growing mega cities in the world. In the period of 1991 to 2004, Dhaka’s population had an average of more than 4 percent annual growth rate ( DOE, 2004). Dhaka metropolitan area occupies an area of about 1353 sq kms ( Enayetullah and Sinha 1999). About 6 million residents live under the management of Dhaka city corporation (DCC) in an area of 344 sq km (Enayetullah and Sinha, 1999). In Dhaka, solid waste generation amounts to 3500 ton/day, of which 1800 tons are collected and dumped by the Dhaka city corporation (DCC), 900 tons end up in backyards and informal landfills, 400 tons end up on roadsides or open space, 300 tons are recycled by the Tokais (destitute slum children acting as scavengers), and 100 tons go through informal recycling at the point of generation (DCC, 2005). Irrespective of the municipal authorities’ ability to collect it, both collected and uncollected waste creates problems for the city residents. One household awareness survey was conducted by DCC in 2004 in Dhaka city which has found that 88 percent of upper income group, 95 percent of middle income group and 100 percent of lower income group are not willing to participate in recycling activities. Unfortunately, public participation in waste management (including waste minimization) in developing countries, including Dhaka, is very low. The general situation of poverty and illiteracy of the masses makes Bangladesh very vulnerable to environmental damage and the general populace of Bangladesh is busy trying to meet their basic material needs therefore, have little scope to be concerned about environmental amenities (Salequzzaman and Stocker, 2001). The Summary Report (BBS, 1995) shows that 46.7 per cent of the urban population (14.5 million) lives in absolute poverty and in Dhaka, some 40 to 45 percent of the people live in slums and slum like areas (Zuberi, 1998). Number of homeless individuals who make road their home or those who use boxes as their shelter they call home, in which some people considered these ‘boxes’ as waste. Alternatively, households with low income have too little to recycle, and households with middle income might have no space at home to keep recycle materials and they see little incentives to manage waste. In addition there is no structured recycling mechanism being implemented to households at this moment in Dhaka. Many people do not know the location of the nearest collection point. Location of collection points is poor or too far away and so it easier to throw the recyclables into the street than to bring them to a collection point (Sujauddin et al., 2008).Finding adequate waste disposal sites for the future is also very difficult at this moment with the increased in population and horizontal expansion of the city. Overall the city corporations have failed to manage the solid waste of this increasing population, mainly because of lack of financial support and willingness to pay (WTP) and low participation of the households for overall sustainable solid waste management policies. So, there is a dire need to increase the public awareness of the waste minimization problem and to estimate the factors which are responsible for increasing waste generation. If the influential factors of increasing waste generation can be identified, it will be helpful for the environmental and waste management planners in their decision making for managing waste and environmental pollution. A considerable amount of research work on solid waste management has already been conducted in Bangladesh (Salequzzaman et al., 1998, 2001; Salequzzaman, 2000; Ahmed and Rahman, 2000; Alam et al., 2002; Hasan and Chowdhury, 2005; Enayetullah et al., 2005; Rahman et al., 2006; Sinha, 2006). However, no study to investigate the effect of the socioeconomic level of householders on solid waste generation and minimization has yet been undertaken. The objectives of the
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study were, therefore, to contribute to a better understanding of household waste management behavior by examining waste management practices and behaviors of the residents of Dhaka city, Bangladesh. More specifically, it analyzes the factors that promote household’s waste generation and their willingness to minimize the household waste. The results of the study will provide inputs into the formulation of local waste minimization plans and programs, particularly on waste segregation and recycling activities of the residents of Dhaka city, Bangladesh.
2. Methodology 2.1 Theoretical Framework for Waste Generation of the Households In developing an effective waste minimization strategy for a given region, it is important to know the amount of waste generated and the composition of the waste stream and this has direct effect on the socioeconomic factors. Early on, economists discussed the socio-economic factors influencing household waste generation. Viewed from an economic perspective, Wertz (1976) analyzed the household behavior on waste generation in terms of changes in income, price of refuse service, frequency of service, site of refuse collection and packaging. Households size, cultural patterns, education and personal attitudes (AlMomani 1994; Grossmann et al., 1974) are said to influence solid waste generation as well. Economists also compared the composition and quantity of waste in terms of income level, household size and age structure of the household as these affect the quantity and composition of solid waste. For instance, Richardson et al. (1978) study shows that grass, yard wastes and newspaper were positively correlated with the level of income. Hence this project consider age, education, knowledge, income, household size and extra land as important components that affect the solid waste generation. Maturity of the respondents might affect their attitude towards environmental issues. In a poor country, if tenants of the household are made of teenagers, they might not consider environmental issues as their priority in life compared to the retirees generation that spend many hours taking care of their home. Similarly, level of education affects the way people lead their lives. A person with higher level of education will most likely be having more articulate and analytical reasoning. Ling and Isaac, 1996 conducted a research in China and they claimed that a national awareness relating to environmental protection needs to be stimulated by education. Ignorance and poverty were recognized as being responsible for acceptance of toxic/hazardous wastes from industrialized countries (Sangodoyin and Ipadeola, 2000). An informed population will mean that measures of environmental protection can be easily implemented (Ling & Isaac, 1996). Education, training and research in the field of environment management is a need (Zuberi, 1998). Environmental education and care is not new in Bangladesh however, the large majority of people in Bangladesh have had no chance to go through formal education; they have been using their own devices to cope with the environmental problems (Salequzzaman and Stocker, 2001). The illiteracy only aggravates Bangladesh’s environmental problem, because it acts as a barrier for them even to understand the damaging impact on their own physical and mental health of the environmental degradation that is occurring right around them (Salequzzaman and Stocker, 2001). Thus, inclusion and dissemination of environmental knowledge and information in the formal and non-formal systems of education and the media should be ensured (Salequzzaman and Stocker, 2001). Information and facts about the past, present and possible future scenario should be presented to the public. Barr et al.’s 2001 research indicated that recycling behavior is influenced by convenience, knowledge and access to a curbside scheme, whereas waste minimization behavior is driven more by a concern about environmental issues. For many people, income will determine what they buy, when the buy, where they buy and how frequent they buy the products. If income is low, most items purchase will likely be necessity items but those belonging to the high income bracket will buy luxury and unnecessary items. Thus, there is a positive relation between income and waste generation (Nilanthi et al.,2006). Sangodoyin and Ipadeola, 2000
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investigated environmental issues in Nigeria and the waste produced differs according to the household level of income. Size of the household is associated to the population of a country. When the size of household increase, the country’s population will directly increases. The quickening pace of development, industrialization, urbanization and population growth in Bangladesh increase the environmental challenges (Salequzzaman and Stocker, 2001). Various authors have shown that the amount of waste generated by a country is proportional to its population and the mean living standards of the people (Wertz, 1976; Grossmann et al., 1974; Medina, 1997) relate to income levels of people hence individual household’s waste generation are correlated. For instance, the average rate of waste generation in Port Harourt is about 1.25 kg/persons/household (Ayotamuno and Gobo, 2004). As a city grows in population and physical size, so does its land use become more complex (Ayotamuno, and Gobo, 2004). Such as, with the cultivation of land came the negative effects of extensive deforestation (Haden et al.,2009). And as the land use becomes more complex, so does the solid waste generated increase in volume and variety (Ayotamuno and Gobo, 2004). Extra land can also be used as storage or warehouse to store unused or unwanted products. This study examines the household’s waste generation using a multiple regression model considering the studies discussed above. 2.2 Theoretical Framework for Waste Minimization Willingness to pay for waste management services or facilities is very important to the success of the private sectors’ participation in solid waste management program. The willingness to pay or not to pay could have direct impact ( positive or negative) on the reliability and success of any solid waste management strategy ( Epp and Mauger, 1989; Rahman et al., 2005). The question therefore has to do with the demand or economics of household waste management especially in developing country like Bangladesh. Household demand for solid waste services is a function of the unit price of solid waste services and other determining factors such as wage, non-wage income, prices of consumption goods, prices received for recyclables, waste components of market goods and quantity of wastes generated by non-market goods (Jenkins 1993). Other socio-economic characteristics are included in models such as household size, age and education. The variables, income and household size, are surrogates for the unobserved household production activities which generate waste as a by-product (Hong et al. 1993). Some researchers have used this demand for solid waste services framework to model the determinants of household waste recycling (Hong et al. 1993; Jenkins et al. 2000; Reschovsky and Stone 1994). Jenkins et al., 2000 examined the intensity of recycling different waste materials using an ordered probit model where the dependent variable, i.e., intensity of recycling each material (categorized in 3 levels), is a function of unit price of waste disposal, some characteristics of the local waste management system, and socio-economic factors like household income, age and home ownership. Using the same model, Hong et al. 1993 modeled household recycling participation or the number of times it recycles over a period of time (categorized in 5 levels) as a function of disposal price and socio-economic variables. Lastly, using a simple probit model, Reschovsky and Stone (1994) examined the probability of recycling a specific material and included socio-economic variables and characteristics of recycling programs as independent variables. The first two models examined mainly the influence of waste disposal price on household recycling behavior, while the third model examined the differential effects of recycling systems when combined with unit pricing. Research on waste recycling in the developing world places less emphasis on understanding the indirect motives of one’s behaviour( i.e., recycling research focus in developed countries), but more heavily on the practical, direct factors influencing the institutions and elements associated with waste management. The studies conducted in developing country like Malaysia, China, Mexico have found that recycling activities are further influenced by the availability of storage space in the home, the presence of recycling agents and the proximity of collection centre to households. They have also observed that competencies were the best predictors of actual behaviour, whereas beliefs were more indicative of perceptions of behaviour or desired behaviour. In the case of recycling, one was more likely to recycle waste when fully understanding the proper way and the reasons to do it as opposed to
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one simply desiring to recycle (Corral-Verdugo, 1997 Harvie and Jaques, 2003). This study examines household waste minimization behavior using binary choice modeling following the studies discussed above. Waste minimization is an activity undertaken to facilitate recycling and disposal and thus entails household resources such as time, space and effort in the same manner as waste recycling. This household activity consists basically of the separation or sorting of wastes into recyclables and non-recyclables, and storing these wastes in separate containers to facilitate recycling and disposal. It is therefore reasonable to assume that the household’s decision to engage in waste minimization will be determined by the same factors that influence its decision to engage in recycling activities. However, since the amount or level of effort of waste segregation done by the household is also not observable, the study adopted a dichotomous or binary choice model. 2.3 Econometric Model of Waste Generation of the Households To determine the factors that affect waste generation of the households selected, this study followed a multiple regression model. In this regression analysis, the total solid waste generation of the households per month is regressed due to its quantitative nature by several independent variables. The model is:
Y 1 2 X 2 3 X 3 .............. k X k Y 1 2 Gender 3 householdsize 4 Age1 5 Age2 6 income1 7 Income2 8 EnvConcern 9 willingtoseparate 10 Extraland
Where, Y = Total waste generation by the households per month Xk = Independent variables 1 = Constant term
i = Coefficient of independent variables e = The error or disturbance term
In this model the household is viewed as a production unit producing solid wastes. Hypotheses about the nature of the waste production relationship can be stated as hypotheses about coefficient signs of the variables included in the model. Gender was entered as a dummy (Male) that was assigned a value of 1 for males and 0 otherwise. Household size refers to the number of family members living in the same household. Monthly income was measured by two dummies- lower income (Income 1) representing the TK 3000 group and Middle income (Income 2) representing the TK 3000 to TK 15000 group; and the high income (> TK15000) category was omitted. Multicollinearity between income and education forced us to drop the latter from the estimated equation. Keeping income ( rather than education) yielded better log likelihood ratio and McFadden R2 statistics. Age was entered as two dummies, Age1 and Age2 representing the sixteen to twenty-four and twenty-five to thirty-five age categories, respectively; the above thirty-five age group was the omitted category. Concern for the environment was a dummy (Environ cons) assigned a value of 1 if the individual was concerned and 0 otherwise. Extra land within the compound assigned a value of 1 if the household had extra land within their compound and 0 otherwise. Willingness to separate the waste assigned a value of 1 if the individual was willing to separate the waste and 0 otherwise. 2.4 Econometric Model of Willingness to Minimize Solid Waste This study examines household solid waste minimization behavior using binary choice modeling ( Logit model) following the studies discussed above. The Maximum Likelihood (ML) method was employed to estimate the parameters in logistic regression model. The likelihood ratio index has been measured as an
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indicator of goodness of fit for the logistic regression model. As such, the model assesses the relationship between various factors and the respondents’ willingness to minimization solid waste. The dependent variable is designed as a dichotomous dummy because of assuming whether the household is willing to minimization solid waste or not. The data collected via the survey were used to run a logit regression model of the form: Log P /(1 P) 1 2 X 2 3 X 3 .............. k X k
Log P /(1 P) 1 2 Gender 3 Age1 4 Age2 5 Income1 6 Income2 7 EnvConcern 8 storage
Where, Pi = 1 if the household is willing to minimize solid waste Pi = 0 for otherwise Xi = Independent variables 1 = Constant term
i = Coefficient of independent variables e = The error or disturbance term i = 1,2,3,…..n
So, in this study p /(1 p) may be interpreted as the ratio of the probability that the respondent will minimize the waste to the probability that he/she will not. Alternatively, it is the odds of the respondent participating in waste minimization. Gender was entered as a dummy (Male) that was assigned a value of 1 for males and 0 otherwise. Monthly income was measured by two dummies- lower income (Income 1) representing the TK 3000 group and Middle income (Income 2) representing the TK 3000 to TK 15000 group; the high income (> TK15000) category was omitted. Multicollinearity between income and education forced us to drop the latter from the estimated equation. Keeping income ( rather than education) yielded better log likelihood ratio and McFadden R2 statistics. Age was entered as two dummies, Age1 and Age2 representing the sixteen to twenty-four and twenty-five to thirty-five age categories, respectively; the above thirty-five age group was the omitted category. Concern for the environment was a dummy (Environ cons) assigned a value of 1 if the household was concerned and 0 otherwise. The storage facility was a dummy (storage) assigned a value of 1 if the household had storage facility in house and 0 otherwise. Most of the variables are derived from the interview, in which it is considered relevant from theoretical point of view and included as independent variables. 2.5 Survey Design and Sampling Method Dhaka is chosen as the location of this study. Residents in Dhaka are the immediate beneficiaries of door to door waste collection systems which have been introduced by Dhaka city corporation (DCC). The unit of analysis is household – either in an independent house, an apartment, a flat or a shanty and a residencecum office/business. Those staying in barracks or orphanages and homeless individuals were excluded from the target population as they do not form a household for tax purposes. The reason for choosing ‘household’ as the unit of analysis is linked with the cultural practice in Bangladesh. In most cases jointfamily structure still exists and incomes are combined for the purpose of any expenditure decision. Hence, ‘income’ in this study refers to household income. Dhaka comprises of 10 zones and within these zones there are 90 wards (subdivision) (BBS, 2001). Each ward is composed of one or more mohallas (blocks), each of which contains one or few streets and a varying number of households. In total, there are 659 mohallas and the number of households in Dhaka city is 643,016 (BBS, 1999). This project utilizes stratification process and random sampling on the number of household. First, from each zone, we selected one ward with the highest level of waste
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generation. Then, two mohallas from each ward was chosen. This resulted in a total of 20 mohallas from the 10 wards. Next, from these 20 mohallas, 413 households were randomly chosen in proportion to each zone’s population. Face to face interview was employed in this study because in Bangladesh literacy rate (47.9%) is low (CIA, 2010). After censoring for missing information and inconsistent answer, 402 (97%) were valid for further investigation. According to Sekaran (2003), sample sizes larger than 30 and less than 500 are appropriate for most research. Leedy and Ormrod (2005) also believe that a sample size of 400 will be adequate if the target population size is beyond 5000. All the respondents are above 17 years old. Before the final data gathering, two pretests were conducted in April 2006. The first pretest involved 10 participants, to test on their understanding and clarity of the questions. One week later, 50 individuals were interviewed based on the modified questions from the first pretest. In August, 2006 the final data gathering was conducted in Dhaka city. The questions in the interview have three sections. In Section A respondents were asked on who normally collect and place solid waste generated in their households, how many container of waste each household produced in 3 to 4 days, weight of each container, whether they receive door-to-door collection service and what happen if they failing to get the door-to-door collection, and their knowledge and concern on environment. “Knowledge” here refers to respondent’s awareness on waste minimization and recycling issues, information on what are recyclable and non-recyclable wastes, who can collect wastes and where solid waste can be disposed (as advertised by Bangladesh Government in the mass media). It is emphasized that the government of Bangladesh frequently advertises to explain waste minimization on television, newspaper and radio. Among others, the messages on these advertisements are: what is waste, how individuals can recycle, recyclable and non-recyclable items, benefits of waste minimization and the impact of minimization of waste. A respondent’s concern on the environment was evaluated based on responses to a set of five questions in the questionnaire. The respondent was only classified as being environmentally conscious if, in response to these questions, he/she satisfied all the following criteria: perceived a clean environment as a personal responsibility, not the responsibility of other parties; participated in any clean environment campaign or project; disposed of waste responsibly during outings when no waste bins were available; was involved in some environmental protection activity; and rated him/herself as being environmentally conscious. The second section asked the respondents about their recycling activity, waste disposal practices and whether they were willing to minimize their household waste or not. Section B asked the respondents about their sources of knowledge, recycling activity, waste disposal practices and whether they were willing to minimize their household waste. Here, waste minimization refers to separating the solid waste from recyclable materials, compost the organic materials, give the solid waste to waste collectors and sell the recyclable materials. Next respondents were asked how often they recycle their solid waste. Section C covered socio-economic characteristics (education level, employment, household monthly income, age and no. of family members) and miscellaneous issues (extra land and any others comments that respondents wish to express).
3. Results 3.1 Socio-economic Characteristics of the Respondents Table 1 & Table 2 show the socio-economic characteristics of the respondents. Table 1 shows the gender, education and employment characteristics. The study found that 67.1 percent of the respondents are male and 32.9 percent female. Dhaka’s population (2001 Census) growth is at 56.5% and sex ratio is 1.26 male to 1 female (Hossain, 2008). In this survey, 80.2 percent of the respondents follow Islam religion, 16.4 percent Hindu, 3.0 percent Christian and 0.4 percent Buddhist. A figure of 83% Bangladeshis (CIA, 2010) are muslim and Islam is the dominant religion in Dhaka city. The highest percentage of the respondents have university degree (61%) followed by diploma (13.4%), higher secondary certificate (11.8%), secondary school certificate (5.7%), primary level (4.8%) and 3.3 percent have no formal
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education. It seems that most of the respondents have tertiary education. Bangladesh’s literacy population is 47.9% while 62.3% in Dhaka (Wikipedia). The proportion of respondents with a university degree was quite high for a developing country like Bangladesh. It could be that many of those who have tertiary education decide to reside in Dhaka city. Most of the respondents (53.7%) were service provider (paid employment), 22.4 percent were business man, 19.5 percent house wives and 4.4 percent retirees. Bangladesh unemployment rate is at 2.5%, labor force is in agriculture (45%), industry (30%) and services (25%). While, in Dhaka unemployment remains high at 23%, half the workforce is employed in household and unorganised labour, while about 800,000 work in the textile industry (Wikipedia, 2010). Table 2 shows respondents’ socio-economic background in terms of household income, age, number of family members and extra land in the compound. On average the monthly household income of the respondents was USD176.1 (1 US Dollar = 70.1 BD Taka). Despite many having tertiary education, the respondents earned way below the target population. It was reported that Bangladesh’s GDP per capita (purchasing power parity) is $1600 (CIA, 2010) per month while the annual per capita income of Dhaka is estimated at $500, with 48% of households living below the poverty line, including a large segment of the population coming from the villages in search of employment, with many surviving on less than $10 a day (Wikipedia, 2010). Based on household income amount, the respondents were divided into three groups: below TK3000 (lower group), TK 3000 to TK 15000 (middle group) and above TK15000 (higher group). A total of 56% of the households are from higher group, 23% from middle group and 11% are from lower group. Contrary to this division, Dhaka city has a growing middle class population (Wikipedia, 2010). The average age was just under 39, with the lowest being 32 and the highest 65 years old. The average household size is 4, maximum is 10 and minimum number is 2. Average of extra land in the compound is 0.5 acre. 3.2 Waste Generation in the Households The respondents were asked on who normally collect and place solid waste generated in the households. Servants/maids are in charge of waste discharge among 89 % of higher group and 79 % of middle group, while members of the households, mostly wives and daughters, are in charge among 94 % of lower group. Attitudes towards waste disposal (as a menial task) or the social status of such a job imply that even within a household, this task is likely to be done by the weaker members, for instance, children or dependent women such as a widow or a daughter-in-law or house maid. The respondents were asked on how many container of waste each household produced in 3 to 4 days. Most respondents (56.4%) produced 3 to 4 waste containers (Figure 1). A typical waste container contained around 1 kg of waste. Waste generation in the study area averaged 38kg/month for each household. As the household average number is 4, the waste generation averaged is 0.3kg/day per capita, which is similar to the findings of DCC (2005). Door-to-door collection service was received by 82 % of upper group households, 75 % of middle group and 30 % of lower group. This shows that the door-to-door collection services are not consistent to all the households and those belonging to the upper group households are more fortunate. Failing to get the door-to-door collection services, 51 % of lower group households dump their waste in vacant lands/river/marsh, while 5% of upper group and 4% of middle group behave in similar manner. 3.3 Knowledge about Solid Waste Minimizationment The respondents were asked about their knowledge of solid waste minimization. A majority of the respondents (61.94 %) stated that they have knowledge about solid waste minimization. Figure 2 show that the majority obtained their source of knowledge from newspaper (50.2%), television (20.9%) and radio (4%). In this case, newspaper and television have been most influential in promoting environmental issues. 3.4 Waste Recycling Practices In solid waste minimization aspect, the respondents were asked how often they recycle their solid waste. For recycling practice, only 25.6% regularly recycled (Table 3), 18.2% seldom recycle and 56.2% never practiced recycling. It must be pointed out that most people in Dhaka were not and still are not served by any convenient recycling network. This high figure of those who seldom and never recycle (74.4%)
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agrees with the study conducted by DCC showing a high level of solid waste in Dhaka city. Of those who regularly recycled (25.6%), a majority separate recyclable materials from solid waste and sell them (74.4%), followed by those separate the waste and give them to waste collectors (20.9%) and separate the waste, sell recyclable materials and compost the organic materials (4.7%) (Table 4). The reasons given (Table 4) by those who practiced waste separation at the source were: good for the environment (68.0%), earn extra income (21.4%) and allows for waste composting (10.7%). On why respondents seldom and never recycled their wastes (74.4%), reasons given were (Table 5): lack of time (38.49%), no space at home (37.2%), recycling is expensive (12.0%), no economic incentives (3.9%), no recycling facilities (3.09%) and no reason (5.4%). These group of households (seldom and never practice recycling) were also presented with another scenario in which the government will provide them with a container to keep and separate their household waste. Interestingly, 30.1 percent of the respondents were willing to minimize their waste if facilities are provided. 3.5 Perception and Attitude of the Respondents about Solid Waste Management Table 6 show the questions related to the perception, willingness to pay and attitude of the households. Question 1 to 4 is related to the perception; question 5 to 7 is related to the willingness to pay of the households and question 8 to 10 is related to the attitude of the households. All data collected was then analyzed using statistical tools for simple percentages, frequency analysis and severity index calculations. The answers to questions were displayed on a 0 to 4 points Likert Scale while the severity index (SI) was calculated using the following equation developed by Al-Hammed and Assaff (1966):
Where, = the index of a class; constant expressing the weight given to the class = the frequency of response i =0, 1, 2, 3, 4 and described as below. Where X0, X1, X3, X4 are the frequencies of response corresponding to a0,=0, a1,= 1, a3,= 3 and a4=4 respectively. The rating classification was adapted developed by Majid and Mc Caffer ,1997. a0 = Strongly disagree a1= Disagree a2= Neutral a3= Agree a4= strongly agree On the point scale, the ratings given to the households are as follows: strongly disagree (0), disagree (1), neutral (2), agree (3), and strongly agree (4). For the ease of interpretation, each rating is given the following denotation: Strongly disagree (SD) Disagree (D) Neutral (N) Agree (A) Strongly Agree (SA) Only the responses to the questionnaires directly related to the scope of the present study have been analyzed and discussed. The results on the assessment of the general perception, willingness to pay and attitude of households to waste management are presented in Table 6. Table 6 presents calculated values of severity indices related to the perception of the households about waste management. The values ranged between 46.9 % and 60.1%. The values are found within the neutral opinion range of
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( Majid and McCaffer, 1997; Isa et al., 2005). With this opinion range the households affirm the existence of an organized solid waste management system in Dhaka. The survey results indicate that the rate of willingness to pay is relatively high across the study area. The values are found within the agreed opinion range of ( Majid and McCaffer, 1997; Isa et al., 2005). The study has also found that the values of severity index related to the attitude of the households ranged between 45.3% and 68.3%. The values are found within the neutral opinion range of ( Majid and McCaffer, 1997; Isa et al., 2005). The values indicate that the households are willing to implement and participate in waste management program and encourage the community to practice waste management at source. 3.6 Estimation Results of Waste Generation and Socio-economic Model All estimation analysis used in this study was undertaken by using the Econometric package Limdep Nlogit 8.0 (Greene, 2006). The estimation result of waste generation and socio-economic model is shown in Table 7. It is evident that environmental consciousness and middle income group (Income 2) are significant positive predictors of waste generation (at the 1 per cent level). Another variable willing to separate is also positively correlated with waste generation (at the 5 per cent level). As might be expected, the coefficient for the attitudinal variable for concern about Environment is positive and statistically significant which supports the hypothesis that the respondents who are more concerned about the Environment in Dhaka would have generated less waste and willing to have improved solid waste management program. The positive coefficient on middle income group (income 2) variable indicates that holding all other variables constant, middle income earners are generating more waste than the lower and higher income people. The positive relationship between these two variables is generally supported by the previous literature (Jenkins, 1993; Hong et al.,1993). The positive sign for concern about Environment is supported by the results of the study conducted by Jin et al. (2006). The positive coefficient for willingness to separate wastes means that the respondents who agree to separate the waste at their house are willing to recycle more and generate less waste. Overall, the model depicts a satisfactory goodness of fit with Mc-Fadden R2 value of 0.36. The goodness of fit of the model is evaluated using the McFadden R2 or the likelihood-ratio (LR) index, which compares the likelihood for the intercept only model to the likelihood for the model with the predictors. The value of the LR statistic (P < 0.00001) shows that all the variables have a significant effect on the waste generation of the households. 3.7 Estimation Results of Willingness to Minimize Solid Waste and Socio-economic Model Table 8 shows the estimation results of willingness to minimize solid waste and socio-economic model. It is evident that environmental consciousness is significant positive predictors of waste minimization (at 1 percent level). Middle income group (Income 2) is also positively correlated with waste minimization (at the 5 per cent level). Another two variables age (twenty-five to thirty five) and storage are also significant ( at 5 percent level) but age has a negative relationship with waste minimization. The results in Table 8 confirm that environmentally conscious individuals are more likely to minimize the waste although this is not consistent with some studies (Carrus et al. 2008, Oom et al., 2005, Knussen et al. 2004). According to Mohai (1985), decisions and attitudes towards the environmental protection effort depend on degrees of personal efficacy and resource availability. Concerning the predictive effect of family income on participation in environmental development programs, several studies have shown that households with higher income levels are more propitious to engage in environmental development programs ( Berger, 1997; Jacobs et al., 1984; McGuire, 1984; Owens et al., 2000; Vining & Ebreo, 1992). Likewise, this present study also shows a positive relationship between income and willingness to minimization solid waste. More interestingly, the middle-age group respondents (25–35 years) are significantly more likely to willingness to minimize than those in the young and oldest age group. These results may be interpreted as follows: the youngest respondents have not yet accepted the need to minimize the waste, while the oldest respondents belong to a generation that never saw the need to minimize the waste. Waste minimization and concern for the environment is a relatively recent
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phenomenon; in time, it is likely that the positive correlation between the likelihood of waste minimization and age will become more apparent in Dhaka, Bangladesh. Demographic variables like gender and age have not shown consistently significant correlation with recycling behaviour. Studies in Holland, Germany and Norway suggest that older respondents are more devoted to recycling (cited in Fenech 2002, Martin et al. 2006). This concern was hypothesized to reflect the frugality of the older generation. Several authors (Barr & Gilg 2005, Barr et al. 2001, Guerin et al. 2001, Jenkins et al.2000) have reported similar findings. Blaine et al. (2001) and Fenech (2002), on the other hand, suggest that older people recycle simply because they have more time on their hands; after all, recycling is a timeintensive activity (Martin et al. 2006, Bruvoll et al. 2002). Overall, the model depicts a satisfactory goodness of fit with Mc-Fadden R2 value of 0.41. The value of the LR statistic (P < 0.00001) shows that all the variables have a significant effect on the waste minimization of the households.
4. Conclusion and Policy Implication The willingness to minimize household waste is an important component for the sustainable development of waste minimization projects in Bangladesh. As the residents of Dhaka city are the main group of contributors to the waste minimization program, the success of this program depends on their willingness to implement it. This study investigated factors that affect waste generation and respondents’ willingness to minimize solid waste. Important determinants of the waste generation are environmental consciousness, middle income group (Tk 3000 up TK 15000) and willingness to separate. Environmental consciousness, middle income group (Tk 3000 up TK 15000), young adults (25 to 35 years) and storage facility are most important factors for respondents’ willingness to minimize solid waste in Dhaka city. In recent years reducing and recycling of households waste has become increasingly imperative because waste generation has been increasing with increase in population and economic development and resources has been becoming scarce, making recycling not only sensible practice but essential. Although there is widespread public support for reducing and recycling of households waste, this is not reflected in participation levels in Bangladesh. In reducing solid waste issues, findings of this study are helpful to the environmental and waste minimization planners as well as to policy makers. First, through this study, there are important indicators of positive attitudes of residents toward solid waste minimization. For instance, 30.1 percent of the households are willing to minimize their household waste. The study has also found that only 25.6 percent of the households are doing recycling regularly. Using the severity index analysis this study has found that the households are agreeing to implement and participate in waste management improvement program. Now the question is if they are agree to separate the waste and agree to implement and participate the waste management program, why the participation in waste minimization is low? It is suggested in this study that we should investigate what discourages them from participating. In order for the waste minimization program to be successful, the behavior of the households in Dhaka city toward solid waste minimization should be taken into consideration. Second, another way to reduce solid waste is by encouraging the residents of Dhaka to recycle and separate the waste at source, as do many developed countries. It is evident that concerted efforts to raise environmental consciousness through education and more publicity regarding waste separating, reducing and recycling could affect the households waste generation. Third, door-to-door waste collection service is not available to all households in Dhaka. The DCC should monitor this service, observe the satisfaction of the households on the service and ensure all the households get the same treatment from the solid waste collectors. For instant, Afroz et al., 2009 found in their study that 54.6 percent of the households in door to door waste collection receiving areas are not satisfied with the waste collectors in Dhaka. They suggested that waste collectors can motivate the households to minimize the solid waste. Fourth, findings in this study show that households that are environmental conscious are more willing to minimize the waste. As such, policies should be formulated to focus on raising awareness, promoting knowledge and motivating households with regard to environment, waste generation and waste minimization practices. Fifth, since in Dhaka the recycling centres are not near to the households and the dustbins are far from the households, the DCC should look into this matter carefully. Sixth, findings in
11
this study show that middle-aged people are willing to minimize waste more than the young or old. Old people are more resistant to new ideas because they do not want to change their beliefs and lifestyle. However, young people could be encouraged at school or college by introducing the topic on different environmental problems including waste management in their syllabus. If they learn it from at school or college, it would be easy for them to adopt waste minimization practices in later life. On the other hand, parents can also play their role in waste minimization. Setthasakko, 2009 conducted a qualitative approach research in Thailand and the findings show that culture in waste management especially recycling should be embedded to children from the very young age. The parents must be committed to implement waste management system in their household and if this system is not followed the parents can form a penalty that relate to environmental friendly activities such as cleaning the drain, mowing the lawn, or planting flowers. Finally, recycling should be encouraged by legal and business policy mandates, as well as by increasing taxes on virgin resources (Tiemstra, 2002). In this project, compliance suffers when individual households cannot be held accountable for their behavior (Gandy, 1993).
5. Limitation of Study & Future Research There are a few limitations to this study. Firstly, the sample in this study is not representative of Dhaka as a whole thus the findings cannot be generalized. The findings of this study are applicable and limited to the area under investigation. Second, the population sample for those who practice recycling regularly are low (103 respondents, 25.6%) thus the findings should be used with caution. Third, number of respondents that have extra land was extremely limited that the researcher was not able to analyze from this perspective. Therefore, future researchers should consider all these limitations when they plan their research relating to solid waste management. Conducting research targeting specifically on those sample who participate on solid waste management might give a different output to the study. Moreover, researching on target sample that have extra land in their compound might show another view of solid waste management. References Afroz, R., Keisuke, H. 2009 A Survey of Recycling Behaviour of the Households in Dhaka City Bangladesh. In press. Journal of Waste Management and Research,2009. Ahmed, M.F., Rahman, M.M., 2000. Solid Waste Management: Water Supply & Sanitation – Rural and Low Income Urban Communities. ITN – Bangladesh, Center for Water Supply and Waste Management, BUET, Dhaka, Bangladesh with contribution from IRC, International Water and sanitation Center, Delft, The Netherlands. Ayotamuno, J. M. & Gobo, A. E. (2004). Municipal solid waste management in Port Harcourt, Nigeria: Obstacles and prospects. Management of Environmental Quality: An International Journal, 15 (4), 389398. Alam, A.K.M.M., Saha, S.K., Rahman, M.M.S., 2002. Aspects of solid waste management – A case study at Nirala Residential Area, Khulna. In: Ahmed, M.F., Tanveer, S.A., Badruzzaman, A.B.M. (Eds.), Bangladesh Environment. Bangladesh Poribesh Andolon (BAPA), Dhaka-1207, Bangladesh, pp. 698– 711. Al-Momani, A. H. (1994). Solid waste management: Sampling, analysis and assessment of household waste in the city of Amman. International Journal of Environmental Health Research, 4, 208–222. Al-Hammad, A and ., Assaf, S., 1996 Assessment of the work performance contractors in Saudi Arabia. J. of Managt. in Engn. ASCE, 12, 44-49.
12
Bangladesh Bureau of Statistics (BBS). 1999. Population Census 1991. Bangladesh Bureau of Statistics (BBS).2001. Population Census 2001. Blaine, W., D. Mascarella and N. Davis (2001) ‘An Examination of Rural Recycling Drop-Off Participation’, Journal of Extension 39(5) (Online journal). Available online: http://www.joe.org/joe/2001October/rbl.html Bruvoll, A., B. Halvorsen and K. Nyborg (2002) ‘Households’ Recycling Efforts’, Resources, Conservation and Recycling 36(4): 337–54. Berger, I. (1997). The demographics of recycling and the structure of environmental behavior. Environment and Behavior, 29, 515-531. Barr, S. and Gilg, A. W. (2005) Conceptualizing and analyzing household attitudes and actions to a growing environmental problem - development and application of a framework to guide local waste policy. Applied geography. 25, 226-247. Barr S, Gilg AW, Ford NJ. 2001. A conceptual framework for understanding and analysing attitudes towards household-waste management. Environ Plan A 2001;33(11):2025–48. Central Intelligence Agency( CIA). The World Factbook. Cited https://www.cia.gov/library/publications/the-world-factbook/geos/BG.html
on
8th
July
2010.
Carrus, G., Passafaro, C. & Bonnes, M.(2008) Emotions, habits and rational choices in ecological behaviours: the case of recycling and use of public transportation. Journal of Environmental Psychology, 28, 51–62. Corral-Verdugo V. (1997) Dual ‘realities’ of conservation behavior: selfreports vs observations of re-use and recycling behavior. Journal of Environmental Psychology, 17, 135–145. Dhaka City Corporation(DCC).2005. Clean Dhaka Master Plan: The Study on the Solid Waste Management in Dhaka City, Final Report. DOE (Department of Environment). (2004) SAARC Workshop on Solid Waste Management – Country Paper Bangladesh, Dhaka Enayetullah, I and Sinha, A.H.M.M. 1999. Community based Composting-Experience of Waste Concern in Dhaka-Case Study no. 3, Urban Management Program for Asia and the Pacific. Enayetullah, I., Sinha, A.H.M.M., Khan, S.S.A., 2005. Urban Solid Waste Management Scenario of Bangladesh: Problems and Prospects. Waste Concern Technical Documentation, Dhaka, Bangladesh, 18p. Epp, D.J., Mauger, P.C., 1989. Attitudes and household characteristics influencing solid waste generation: A household garbage analysis. Northeastern Journal. of Agricultural. and Resource. Economics., 18, 4651.
13
Fenech, M. (2002) Understanding Public Participation in Source Separation of Waste. MSc Thesis, Institute for Industrial Environmental Economics, Lund, Sweden.
Gandy, M., 1993. Recycling and Waste. In: , Avebury, Aldershot, p. 55. Greene, W.H., 2002. LIMDEP Version 8.0, Econometric Modeling Guide. Econometric Software Inc., NY. Guerin,D., J. Crete and J. Mercie (2001) ‘A Multilevel Analysis of the Determinants of Recycling Behaviour in the European Countries’, Social Science Research 30(2): 195–218. . Grossmann, D., Hudson, J. F., & Marks, D. H. (1974). Waste generation models for solid waste collection. Journal of the Environmental Engineering Division, 100, 1219–1230. Grossmann, D., Hudson, J. F., & Marks, D. H. 1974. Waste generation models for solid waste collection. Journal of the Environmental Engineering Division, 100, 1219–1230. Harvie, M. & Jaque, P. (2003) Public awareness and the environment: ‘how do we encourage environmentally responsible behavior?’Water Supply, 3, 247–254. Haden, S. S. P. & Oyler, J. D., & Humphreys, J. H. (2009). Historical, practical, and theoretical perspectives on green management: An exploratory analysis. Management Decision, 47 (7), 1041-1055. Hasan, G.M.J., Chowdhury, M.A.I., 2005. Municipal waste management and environmental hazards in Bangladesh. Pakistan Journal of Biological Science 8 (6), 921–928. Hassan, S. 2008 .Rapid Urban Growth and Poverty in Dhaka City. Bangladesh e-journal of Sociology. 5(1), 1-24. Hong, S., R.M. Adams., and H. Alan Love. 1993. An Economic Analysis of Household Recycling of Solid Wastes: The Case of Portland, Oregon. Journal of Environmental Economics and Management. 25,136-146. Isa, M.H., Asaari, F.A.H., Ramli, N.A., Ahamad, S. and Siew, T.S., 2005. Solid waste collection and recycling in Nibong, Tebal, Penang, Malaysia: a case study. Waste Management and Research., 23, 565570. Jacobs, H., Bailey, J., & Crews, J. (1984). Development and analysis of a community-based recourse recovery program. Journal of Applied Behavior Analysis, 17, 127-145. Jekins, R.B. 1993. The Economics of Solid Waste Reduction. The Impacts of User Fees. Edward Elgar. Jenkins. R.B.; S.A. Martinez; K. Palmer; and M.J. Podolsky. 2000. The Determinants of Household Recycling: A Material Specific Analysis of Recycling Program Features and Unit Pricing. Discussion Paper 99-41-REV. Resources for the Future. Washington, D.C. Jin, J., Wang, Z.,and Ran, S., 2006. Estimating the public preferences for solid waste management programs using choice experiments in Macao. Waste Management Research 24, 301-309.
14
Knussen, C., Yule, F., Mackenzie, J. & Wells, M. (2004) An analysis of intentions to recycle household waste: the roles of past behaviour, perceived habit and perceived lack of facilities. Journal of Environmental Psychology, 23, 237–246. Leedy, P. D. & Ormrod, J. E. 2005. Pratical Research: planning and design. 8th ed.Upper Saddle River, NJ: Merrill Prentice Hall. Ling, L. & Isaac, D. (1996). Environmental management issues in China: problems and strategies. Property Management, 14 (3), 17-26. Majid, M.Z.A and McCaffer, R., 1997. Discussion of Assessment of Work Performance of Maintenance Contractors in Saudi Arabia. J. of Managt. in Eng., ASCE, 13, 91. Martin, M., Williams, I. & Clark, M. (2006) Social, cultural and structural influences on household waste recycling: a case study. Resources, Conservation and Recycling, 48, 357–395. Medina, M. 1997. The effect of income on municipal solid waste generation rates for countries of varying levels of economic development: A model. Journal of Resource Management and Technology, 24, 149– 155. McGuire, R. 1984. Recycling: Great expectations and garbage outcomes. American Behavioral Scientist, 18, 93-114. Mohai, P.. 1985. Public concern and elite involvement in environmental conservation issues. Social .Science. 66, 820–838. Nilanthi, J.G.J.B., Patrick, J.A., Hettiaratchi, S.C., Pilapiiya, S., 2007. =Relation of waste generation and composition to socio-economic factors: a case study. Journal of Environmental Monitoring Assessment 135, 31-39.
Oom, D.V.P., Rebelo, E., Reis, E. & Menezes, J. (2005) Combining behavioural theories to predict recycling involvement. Environment and Behaviour, 37, 364–396. Owens, J., Dickerson, S., & Macintosh, D. 2000. Demographic covariates of residential recycling efficiency. Environment and Behavior, 32, 637-650. Pfammatter R, Schertenleib R. 1996. Non-governmental refuse collection in low-income urban areas. Lessons learned from selected schemes in Asia, Africa and Latin America. SANDEC Report No. 1/96. Water and Sanitation in Developing Countries EAWAG/SANDEC, Duebendorf, Switzerland; 1996. Rahman, M.M., Hossain, M.D., Badruzzaman, A.B.M., Ali, M.A., Rahman, M.M., 1999. Characterization of municipal solid waste and preliminary environment impact assessment of collection and disposal wastes in Dhaka City. Bureau of Research, Testing and Consultation (BRTC), BUET, Dhaka. Reschovsky, J.D.and S.E. Stone. 1994. Market Incentives to Encourage Household Waste Recycling: Paying for What You Throw Away. Journal of Policy Analysis and Management. 13,120-139. Richardson,R.A and Havlicek,J.Jr. 1978. Economic Analysis of Composition of Household Solid Wastes. Journal of Environmental Economics and Management. 5,103-111.
15
Richardson,R.A and Havlicek,J.Jr. 1974. An Analysis of Seasonal Household Waste Generation. Southern Journal of Agricultural Economics. 6, 143-155. Salequzzaman, M. & Stocker, L. (2001). The context and prospects for environmental education and environmental careers in Bangladesh. International Journal of Sustainability in Higher Education, 2 (2), 104-127. Sujauddin, M; Huda, M S.M.S. and Rafiqul , A.T.M. 2008. Household solid waste characteristics and management in Chittagong, Bangladesh. Journal of Waste Management, 28, 1688-1695. Salequzzaman, M., Murtaza, M.G., Saroar, M., 1998. Evaluation Study on Municipal Solid Waste Management Project in Khulna City, PRODIPAN, Shaheb Bari Road, Khulna 9203, Bangladesh. Salequzzaman, M., 2000. Perceptions of vehicle air pollution in Khulna,Bangladesh. In: Proceedings of the Habitus 2000, Conference in Perth,Western Australia, September 05–09. Salequzzaman, M., Awal, M., Alam, M., 2001. Willingness to pay: community based solid waste management and its sustainability in Bangladesh. In: Proceedings of the International Conference ‘The Future is Here’, RMIT, Melbourne, Victoria, January 15–19. Sinha, A.H.M.M., 2006. Community Based Solid Waste Management Through Public-Private Community Partnerships: Experience of Waste Concern in Bangladesh. Paper presented in 3R South Asia Expert Workshop, Katmandu, Nepal. Sangodoyin, A. Y. & Ipadeola, S. F. (2000). Hazardous wastes Assessing the efficacy of structures and approaches to management in Nigeria. Environmental Management and Health, 11(1), 39-46. Sekaran, U. 2003. Research methods for business: A skill – building Approach. 4th ed. New York: John Willey & Son, Inc Setthasakko, W. (2009). Barriers to implementing corporate environmental responsibility in Thailand: A qualitative approach. International Journal of Organizational Analysis, 17 (3), 169-183. Sinha AHMd, Enayetullah MI. 2000. Community based solid waste management: the Asian experience. Dhaka, Bangladesh: Waste Concern & USAID; 2000. Tiemstra, J. P. (2002). Wasting time and wasting the earth. International Journal of Social Economics, 29 (4), 260-270 Vining, J. and Ebreo, A.. 1992. Predicting recycling behavior from global and specific environmental attitudes and changes in recycling opportunities. Journal of Applied Social. Psychology. 22, 1580–1607. World Resources Institute, United Nations Environment Programme(WRI). 1996. , United Nation Development Programme, World Bank. World Resources—a guide to the global environment,1996–97. The Urban Environment. Oxford University Press, Oxford, UK; 1996. Wertz L. Kenneth; 1976 Economic Factors Influencing Household’s Production of Refuse’ Journal of Environmental Management and Economics. 2, 263-272 .
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Zuberi, M. I. (1998). Environmental, socio-cultural and developmental linkages in a South Asian set-up. International Journal of Social Economics, 25 (6/7/8), 1112-1127.
Figure 1: Packages of Wastes in 3-4 Days (n=402)
Percentage of Respondents
60
55.2
50 40 30.3 30 20 10
8.1
4.2
2.2
0 1-2 Packages
3-4 Packages
5-6 Packages
7-9 Packages
More than 10 Pakages
Generation of w aste on average 3-4 days
Key: 1 Package = 11” x 15” plastic shopping bag, contained about 1 kg of waste.
Table 1: Gender, Education and Employment of Respondents Item Number of Respondents Gender Male 270 Female 132 Religion Islam 322 Hindu 66 Christian 12 Buddhist 2 Education No formal education 13 Primary education 19 Secondary school certificate(S.S.C) 23 Higher school certificate(H.S.C) 47 Diploma 54
17
Percentage 67.1 32.9 80.2 16.4 3.0 0.4 3.3 4.8 5.7 11.8 13.4
University Employment Service holder Business man House wife Retired
246
61.0
216 90 78 18
53.7 22.4 19.5 4.4 N= 402
Table 2: Respondents’ Household Income, Age, Number of family members and Extra land available Item Number of Average Respondents Household monthly Income Taka(USD) 12000(172) Age in years 402 39 Family members (number of persons) 402 4 Extra Land with the compound 402 0.5 acre
Percentage of Respondents
Figure 2: Sources of Knowledge about Recycling (n=402) 60
50.2
50 40 30
24.9
20.88
20 10
4.02
0 Information from Information from Information from Information from newspaper Radio TV all above the sources Sources of know ledge
Table 3: Practice of Recycling Answer Never practiced recycling Seldom did Regularly practiced it Total
Number Respondents 226 73 103 402
of Percentage 56.2 18.2 25.6 100
18
Table 4: Regularly Practice Recycling Regularly Practice Recycling Way of Recycling Separate the recyclable materials from the waste and sell them Separate the waste and give them to waste collectors Separate the waste , sell the recyclable materials and compost the organic materials Reasons for Regular Practice of Recycling Good for Environment Allows for Composting Earn for Extra Income
Number of Respondents
Percentage
77
74.4
22 4
20.9 4.7
70 11 22
68.0 10.7 21.4 (N=103)
Table 5: Reasons for Seldom and Never Practice Recycling Reasons
Number of Respondents
Percentage
There was no facility for recycling Lack of time No economic incentive No space at home No reason Expensive to recycle
9 115 12 111 16 36
3.1 38.5 3.9 37.2 5.4 12.0
Total
226
100
19
Questions
1. There is an organised waste disposal program in my
SD(0) NR PR 28 7
D(1) NR PR 57 14.2
20
Frequency N(2) A(3) NR PR NR PR 124 30.8 165 42
SA(4) NR PR 28 7
(SI) % 56.7
area 2. I am satisfied with the services of the service provider in my 3. Separate plastic bags for waste collection should be provided by the waste collector 4. Waste management improvement is not important 5. I am ready to pay for the disposal of waste I generate
61
15.2
13 3
33.2
59
14.8
92
23
57
14
46.9
57
14.3
43
10.6
49
12.1
192
47.8
62
15.2
60.1
101
25.3
90
22.4
18
4.5
96
24
97
23.8
54.9
77
19.2
91
22.7
23
5.9
92
22.8
118
29.4
55.0
6. I am not ready to pay for the disposal of waste I generate 7. Earning more income will encourage payment for waste disposal services 8. I am willing to implement and participate waste management program 9. Practice waste segregation regularly 10. Encourage community to practice waste management at source
5
1.2
5
1.2
9
2.3
154
38.3
229
57
87.1
82
20.3
62
15.3
36
9
90
22.5
132
32.9
57.9
49
12.1
53
13.2
28
7
94
23.6
177
44.1
68.3
116
29.1
84
21.0
13
3.2
129
32.2
58
14.5
45.3
72
17.9
81
20.2
20
4.9
125
31.2
104
25.8
56.7
Table 6. Perception, Wiliness to Pay and Attitude of the Respondents about Solid Waste Management
Table 7: Factors Affecting Waste Generation Variables
Estimation.
Standard error
Constant Male
-.12 -0.12
0.32 0.20
21
t-statistics -0.37 -0.6
16 – 24 years (Age 1) 25 – 35 years (Age 2) House size Lower income (Income1) Middle Income (Income 2) Household size Willing to separate the waste Extra Land Environmental conscious LR statistics Mc-Fadden R2 Probability Total observation
-0.11 0.11 0.31 0.04 0.76 0.45 0.56 0.08 0.52 -121.24 0 .36 0.00000 402
0.09 0.15 0.20 0.21 0.12 0.36 0.12 1.58 0.13
-1.22 0.73 1.55 0.19 6.33*** 1.25 2.33* 0.05 4.00***
*Significant at p ≤ 0.05.***Significant at p ≤ 0.01.
Table 8. Factors Affecting Willingness to Minimize the Solid Waste Variables Constant Male 16 – 24 years (Age 1) 25 – 35 years (Age 2) Lower income (Income1) Middle Income (Income 2) Storage Environmental conscious LR statistics Mc-Fadden R2 Probability Total observation
Estimation.
Standard error
-1.12 -0.28 -0.03 0.54 0.02 0.54 0.92 0.52 -112.3 0 .41 0.00000 402
0.32 0.20 0.14 0.21 0.41 0.26 0.45 0.13
*Significant at p ≤ 0.05.***Significant at p ≤ 0.01.
22
t-statistics -3.5 -1.41 -0.21 2.57* 0.04 2.07* 2.04* 4.56***
