Influence of socio-economic factors on household solid waste (HSW) generation of the city of Guayaquil, Ecuador.

Rivas, Jorge Luis Amaya; Hidalgo-Crespo, J.; Jervis, Freddy X.; Moreira, César M.

doi:10.18687/laccei2019.1.1.24

Cited by 7 publications

(9 citation statements)

References 8 publications

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“…After in-depth review of online literature, little information showed to be available relating social factors with the generation of waste cooking oil. However, experience in previous research [1] mention that household size and social status always influence household waste. Other findings closely related to ours revealed: the necessity for rigorous public awareness campaign in order to encourage households to properly manage their WCO through recycling for biodiesel production [12] also, access to recycling facilities evidently has most impact on recycling behavior.…”

Section: Literature Reviewmentioning

confidence: 96%

“…In previous research, the authors identified how domestic solid waste generation varies according to certain socioeconomic factors [1] and determined the energy potential of such waste by theoretically characterizing the residues with the help of literature [2]. However, to our knowledge no research exists for liquid domestic waste produced in the city.…”

Section: Introductionmentioning

confidence: 99%

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Domestic waste cooking oil generation in the city of Guayaquil and its relationship with social indicators.

Borja¹,

Pisco²,

Vaca³

et al. 2020

Proceedings of the 18th LACCEI International Multi-Conference for Engineering, Education, and Technology: Engineering, Integrat

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This paper estimated the domestic waste cooking oil (DWCO) generation for the city of Guayaquil, Ecuador. The study also determined how social indicators influence the quantity of waste produced domestically by using Ordinary Least Square (OLS) regression. For this effect, a stratified random sampling methodology was used, resulting in the selection of 441 sample households for this study. Results show that the city produces 5.11 grams of DWCO per capita every day also, households with higher number of youngsters between 12 and 18 years old produce more DWCO and social status plays a crucial role in liquid waste generation, giving a negative coefficient for the OLS regression, meaning that households with higher social status produce less of this waste. Finally, this study suggests new insights concerning the generation of domestic waste cooking oil and sets a milestone for future research in the reuse and recycle of this liquid residue.

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Section: Literature Reviewmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Domestic waste cooking oil generation in the city of Guayaquil and its relationship with social indicators.

Borja¹,

Pisco²,

Vaca³

et al. 2020

Proceedings of the 18th LACCEI International Multi-Conference for Engineering, Education, and Technology: Engineering, Integrat

View full text Add to dashboard Cite

show abstract

“…In the year 2016, Kolekar [9] reviewed these techniques and concluded that correlation and regression analysis is the commonly used approach for forecasting the SWGR. Moreover, Lakioti et al, Suthar et al, Trang et al and Hidalgo et al [10][11][12][13][14] proved that socio-demographic and economic parameters are the most influential parameters affecting the amount of solid waste generation amount.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Solid Waste Generation Rates in Urban Region of Laos Using Socio-Demographic and Economic Parameters with a Multi Linear Regression Approach

et al. 2021

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This paper aims to develop a predictive model for Laos to generate reliable statistics for urban solid waste from 1995 to 2050. The multi-linear regression (MLR) approach is used with six different socio-demographic and economic parameters, i.e., urban population, gross domestic product (GDP) per capita, urban literacy rate, urban poverty incidence, urban household size and urban unemployment rate. Different reliable models are generated under four different scenarios. The value of R2 (a relative measure of fit) and value of performance indicators (an absolute measure of fit) such as mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) are calculated to assure the validity and accuracy of the results. Model 2 of Scenario 4 is estimated as the best model, where population and GDP per capita show statistical significance for estimating urban solid waste generation rate in Laos. The amount of municipal solid waste is estimated to be 0.98 million tons (MT) in the year 2030, 1.26 MT in the year 2040 and 1.52 MT in the year 2050, assuming that the present waste generation trends will be followed in the future. Moreover, the study provides an easy and detailed explanation of the work which will increase the interest of researchers, allow them to understand the MLR approach clearly and inspire them to use it for other developing countries where the scarcity of data is a major obstacle in the field of solid waste management. The drawback of the study is the limited availability of historical official and reliable data statistics in Laos for the dependent and independent variables.

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“…Many reasons such as rapid population growth, urbanization, development of the economy, developments in science and technology, improvement in the living standards of society and people's lifestyles, and development of the mode of consumerism have led to a significant increase in the production of the municipal solid waste (MSW) and the diversity of its composition (Astane & Hajilo, 2017; Liu et al., 2019). Lately, solid waste management (SWM) has become a serious issue and major concern for many countries, especially for developing countries, and is now one of the urban environmental subjects discussed by the planners and policymakers (Ali & Siong, 2016; Hidalgo et al., 2019).…”

Section: Introductionmentioning

confidence: 99%

“…To plan a MSWM strategy for a specific city, it is substantial to know the amount and composition of the waste produced (Bandara et al., 2007; Hidalgo et al., 2019). The knowledge of the amount and composition of the solid waste produced is gained based on studies of classification of solid waste at the level of complexes or populated areas.…”

Section: Introductionmentioning

confidence: 99%

The urban household solid waste generating factors and composition study—A case study: Irbid City – Jordan

Alwedyan

2021

Environmental Quality Mgmt

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The household solid waste (HSW) constitutes a main segment of municipal solid waste (MSW). Therefore, effective management of HSW has become an imperative issue to solve the problems caused by massive generation of HSW, the protection and sustainability of the environment, as well as the protection of public health in Jordan. The present study was conducted to assess the amount and components of urban HSW generated and to determine the influencing factors in the urban areas of Irbid city, Jordan. The study was conducted on 383 households. The driving forces behind Irbid household waste generation were analyzed using a multiple linear regression model.The outcomes of this study indicated that the average waste produced by households was 0.90 kg/cap/day. Also, the data analysis displayed that organic waste represents more than half of the total composition of waste 58.56% followed by plastic 14.59%, paper and paper products 9.61%, glass 7.49%, metal 4.19%, rubber and leather, others, and textile had the lowest concentrations, being less than 2% wt. The multiple linear regression outcomes displayed that the value of R 2 was found to be 0.614 for the household waste generation per capita. Also, according to Pearson's coefficient and Point-Biserial correlation values, a positive correlation was found between HSW generation and gender of household head r = 0.256, household size r = 0.629, and monthly household income r = 0.529, while a negative correlation was found between household waste generation and age of the household head r = -0.329, and education level of the household head r = -0.303.The study findings serve to provide crucial inputs to the policymakers and planners concerned with environmental issues in making their decisions toward a more effective and sustainable solid waste management (SWM) system, which helps to protect the environment and the maintain natural resources.

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Influence of socio-economic factors on household solid waste (HSW) generation of the city of Guayaquil, Ecuador.

Cited by 7 publications

References 8 publications

Domestic waste cooking oil generation in the city of Guayaquil and its relationship with social indicators.

Domestic waste cooking oil generation in the city of Guayaquil and its relationship with social indicators.

Prediction of Solid Waste Generation Rates in Urban Region of Laos Using Socio-Demographic and Economic Parameters with a Multi Linear Regression Approach

The urban household solid waste generating factors and composition study—A case study: Irbid City – Jordan

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