Submitted:
25 January 2024
Posted:
26 January 2024
Read the latest preprint version here
Abstract
Keywords:
1. Introduction
1.1. General Background of the Study
1.3. Objective of the Study
- To evaluate existing landfill suitability of practicing proper solid waste management.
- To assess well known solid waste types which are taken for final disposal by households to landfill site.
- To investigate the current status and practice of solid waste management.
1.4. Research Questions
1.5. Significance of the Study
1.6. Scope of the Study
2. Review of Literature
2.1. Theoretical and conceptual definition of solid waste Management
2.2. Theoretical Review
2.2.1. Significance of definition of Evolving Theory
2.2.2. Moving toward the waste management Theory
- ➢
- Giving conceptual responses by describing waste and concepts.
- ➢
- Providing guidance for selecting garbage disposal choices.
- ➢
- Providing a foundation for selecting and integrating waste management strategies.
- ➢
- Forecasting the results of waste management actions.
- ➢
- Aiding legislation in prescribing waste-related action.
2.3. Approaches of Solid Waste Management
2.3.1. Convectional Approaches to Planning for Solid Waste Management of Urban Environment
2.3.2. Alternative Approaches to Planning of SWM of the Urban Environment
2.4. Empirical Review
2.4.1. The Global Solid Waste Management Perspective
2.4.2. Status of Solid Waste Management in Ethiopia
2.5. Summary Implication of Reviews
2.6. Conceptual Framework of the Study
3. Research Methodology
3.1. Study Area Description

3.2. Research Design
3.3. Research Approach
3.4. Population of the Study Area
3.5. Sampling Methods and Sampling Frame Work

- Where N =population size

3.6. Sources of Data and data collection method
3.6.1. Sources of Data
3.6.2. Data Collection Methods
3.7. Methods of Data Analysis
3.7.1. Landfills Suitability Analysis by Using GIS
3.7.2. Model Specification
- Where, for i=n observations:
- Where y-hat, or is the total of the regression terms. The linear predictor, or xb, is the sum of the regression terms. Each x is a word that represents the value of a predictor, x, and its coefficient, . is the predicted value of the regression model as well as the linear predictor in linear regression, which is based in matrix form on the Gaussian or normal probability distribution? The number i denote the number of predictors in a model. The anticipated or fitted values of the model have a linear connection with the terms on the right-hand side of Equation 2 — the linear predictor = xb. In the case of logistic regression, this is not the case[14].
3.8. Variable Description
3.9. Validity and Reliability
3.10. Ethical Consideration
4. Results and Discussion
4.1. Response Rate
4.2. Demographic Information of Respondents

4.2.1. Respondents Family Size

4.2.2. Respondents Response on HHs Solid Waste Service Payment Has Relation with Income

4.2.3. Status of Solid Waste Management and Housing Ownership

4.2.4. Respondent’s Response on Landfills Site Suitability

4.2.5. Respondents Response on Status of Solid Waste Management

4.2.6. Respondents Response on Household’s Income and Determinant Factors

4.2.7. Respondents Response on Types of Solid Waste and Solid Waste Storage Material




4.2.8. Respondents Response on Why Households Are Practicing Improper Solid Waste Management

4.3. Qualitative Data Analysis
4.3.1. Respondent’s Response on Attitude of Communities towards on Proper Solid Waste Management Practice
4.3.2. Respondent’s Response on Existing Landfill Suitability for Collection of Solid Waste

4.3.3. Respondent’s Response on Types of Waste Particle That Most of the Time Used to Landfill Site
4.3.4. Respondents response on whether urban community has their own solid waste container or bin around their home
4.3.5. Respondents Response on Household’s Method of Solid Waste Management Practice
4.3.6. GIS Arc Map Generated Study Are Watershed and Soil Type.

4.3.7. Soil Type of Study Area by Arc Map GIS

4.4. LUCC of Study Area
| No | Land use type | Areal coverage sq. mile |
| 1 | Agricultural Land | 0.503516 |
| 2 | Degraded Land | 0.200503 |
| 3 | Settlement | 0.960468 |

5. Conclusion and Recommendation
5.1. Conclusion
5.2. Recommendation Based on Research Findings
List of Abbreviations
- ATLAS.ti.: Computer Based Qualitative Data Analysis Software
- BMP: Business Process Management
- EPM: Environmental Planning Management
- GIS: Geographic Information System
- Hhs: House Holds (residents of municipality)
- IF: Institutional Factors
- ISWM: Improper Solid Waste Management
- OECD: Organization for Economic Co-operation and Development
- SAS: Analytics, Artificial Intelligence and Data Management
- SLM: Solid Waste Management
- SPSS: statistical Package for Social Science
- STATA: Statistical Software
Acknowledgments
Conflicts of Interest
References
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