The Waste Flow Diagram (WFD) estimates the amount of solid waste entering nature and the oceans from various sources. A scenario function is used to simulate how improved waste management could reduce pollution and prevent marine litter.
The Waste Flow Diagram has been developed to provide a rapid assessment method for low and middle income communities or cities to understand their waste management systems.
Therefore, material flow analysis is used to assess and map waste flows throughout the waste management system.
Flows represent possible material pathways, quantified in tonnes per year.
Important aspects such as contributions from the informal waste sector are also quantified.
A unique observational approach provides a quick estimate of plastic leakage and identification of problem areas. This is achieved using decision trees and descriptive tables for each part of the waste management system, which incorporate waste management infrastructure and practices into the calculation of leakage potential. The total plastic leakage from the waste management system is calculated as the sum of plastic leakage from each stage by multiplying the leakage percentages by the total amount of plastic flowing through the system at each specific MSWM stage.
The results of the Waste Flow Diagram are presented in either a material flow diagram for in-depth analysis or simpler Sankey diagrams for communication and dissemination. In addition, the plastic pollution results are converted into easily understood values such as “PET bottles per person per year” or “number of waste trucks per year” to enable all stakeholders to understand the significance of the results.
Built-in scenario capabilities allow the user to understand the potential impact of applying interventions within the waste management system. For example, the user can simulate how increasing collection coverage by a certain amount would affect the rest of the waste management system, including the amount of plastic leaking into water. Transparent and clear results also provide benchmarking opportunities for cities to track their progress.
The WFD is specifically created to integrate with the SDG 11.6.1 methodology, users of the Waste Flow Diagram will be guided through the process of data collection in area lacking such information. Results will further inform the SDG 11.6.1 sub-indicators, providing benchmarking capabilities and visualisation of results.
SDG 11.6.1 – Proportion of municipal solid waste collected and managed in controlled facilities out of total municipal solid waste generated by cities
The WFD (Waste Flow Diagram) provides a preliminary estimation of waste characteristics and management, aiming for a balance of speed and accuracy. It serves as an initial step in assessing waste management systems. For more detailed analysis, tools like the ISWA (International Solid Waste Association) Plastic Pollution Calculator offer deeper insights. Additionally, the GIZ study “Benchmark of Plastic Hotspotting Methodologies” supplements this with further information on plastic pollution assessment methods.
The accuracy and reliability of a WFD assessment are influenced by several factors:
The WFD incorporates expert-derived factors to estimate plastic leakage and environmental impact. Nonetheless, it’s important to acknowledge that plastic pollution modeling is a developing field, and the science behind it is still evolving.
The Waste Flow Diagram (WFD) tool is developed to complement the UN-Habitat Waste Wise Cities Tool (WaCT), aligning with the Sustainable Development Goal (SDG) indicator 11.6.1, which focuses on the proportion of municipal solid waste (MSW) that is collected and adequately disposed of. The WaCT’s methodology incorporates the WFD as part of its seventh step, designed through a collaborative effort between UN-Habitat and GIZ, with contributions from Wasteaware, the University of Leeds, and Eawag. The WFD tool specifically helps in calculating three sub-indicators related to SDG 11.6.1, enabling users to input primary data obtained during a WaCT assessment. These key data points include:
The WFD tool provides a more detailed focus compared to the broader SDG 11.6.1 approach, especially regarding the final stage of waste processing within the study’s boundaries. While the SDG methodology emphasizes recovery facilities as end points, the WFD tool can function independently of a WaCT or SDG 11.6.1 assessment, though it requires relevant data from alternative sources for accuracy.
Beyond SDG 11.6.1, the WFD connects to SDG 12.5.1, concerning the national recycling rate, and SDG 14.1, aimed at reducing marine pollution. However, in the context of SDG 12.5.1, the WFD only accounts for the initial sorting stages and not the full scope of municipal waste recovery, which limits its ability to fully align with the national recycling rate measured by SDG 12.5.1. Moreover, the WFD’s focus is more localized, targeting city or local authority levels, unlike SDG 12.5.1’s national perspective.
In terms of addressing plastic leakage (related to SDG 14.1), the WFD assesses the sources of leakage within the municipal solid waste management (MSWM) system, identifying areas for intervention. In contrast, SDG 14.1 evaluates the presence of plastics in the marine environment, potentially tracing back to the type of plastic, its manufacturer, and country of origin. Both the WFD and SDG assessments offer valuable insights that complement each other, focusing on both the source and impact of plastic pollution.
For more information, please refer to the relevant chapter in the WFD compendium. Please click here to be redirected.
The WFD stands out in the landscape of plastic pollution assessment tools, which have evolved significantly over recent years. Tools vary in their methodologies, including transfer coefficients, material flow analysis (MFA), statistical trends, and hydrological modeling. Here’s how the WFD compares and contrasts with other notable tools employing MFA:
Waste Flow Diagram (WFD): Ideal for quick, city-level assessments. It’s designed for low data input, annual updates, and covers all material types. The WFD is the most efficient in terms of speed and cost, targeting municipal solid waste management systems.
ISWA Plastic Pollution Calculator (PPC): Offers a detailed look at a municipality’s plastic flow, requiring daily data inputs for a detailed baseline and action planning. Its thoroughness comes at a high resource cost.
IUCN Hotspotting Tool: Identifies plastic pollution hotspots by examining the entire plastic value chain, from production to disposal. It assesses both micro and macroplastics’ impacts, supporting regional action plans and enabling benchmarking across different scales.
SPOT Model: Utilizes machine learning for an in-depth analysis of plastic leakage on land and in rivers, demanding extensive data. It’s unique for its global assessment capability, making it suited for large-scale hotspotting.
The WFD offers a streamlined, efficient option for experts needing rapid assessments at the city level. Meanwhile, other tools provide more detailed analyses, address specific aspects of plastic pollution, or cover larger geographical areas. This diversity ensures experts can choose the tool that best fits their specific needs and available resources.
Table 1
Similarities and Differences between the MFA-based Plastic Pollution Estimation Tools
For more information, please refer to the relevant chapter in the compendium. Please click here to be redirected.
The reliability of a Waste Flow Diagram (WFD) assessment is determined by a comprehensive quality assessment framework, which builds upon the foundational work of Laner et al. (2016). This framework identifies five critical indicators essential for evaluating the uncertainty in Material Flow Analysis (MFA) input data:
The quality assessment framework for the WFD not only incorporates these indicators but also expands them into sub-indicators, tailored to address the unique aspects of the WFD. This expansion is designed to make the evaluation process more granular, enabling easier and more consistent scoring. Each sub-indicator is scored on a scale from 1 (indicating the highest reliability) to 4 (indicating the lowest reliability), based on detailed criteria provided in the framework. The average score derived from these sub-indicators is then used to determine the overall reliability of the WFD assessment, offering a structured approach to assessing the quality and reliability of the data underpinning a WFD analysis.
The Waste Flow Diagram (WFD) estimates the amount of solid waste entering nature and the oceans from various sources. A scenario function is used to simulate how improved waste management could reduce pollution and prevent marine litter.