Crosscutting Methodologies for Generating Data

4.1 Crosscutting Methodologies for Generating Data

1This section provides additional detail on methodologies that have been previously referenced and are relevant to data collection for several data types.

4.1.1 Collection records from municipal and private sector groups

1Collection records maintained by municipalities and private waste operators provide the foundation for reliable waste collection data. These records capture operational information about waste quantities, collection coverage, and service frequency, making them essential for understanding the formal waste management system’s performance. When properly maintained and aggregated, these records offer the most direct measurement of collected waste within a jurisdiction.

Municipal Departments (including Local Authorities and/or Local Government)

1Implementation steps

1. 2Identify all collection entities
   1. 3Create a comprehensive registry of all municipal departments and private companies involved in waste collection
   2. 4Document contact information, service areas, and types of waste collected
   3. 5Update this registry annually to account for new operators or changes in service provision
2. 6Develop standardised reporting templates
   1. 7Create forms for reporting collected waste quantities including fields for date, collection route/area, waste type, weight/volume, and vehicle information
3. 8Establish weighing infrastructure
   1. 9Install weighbridges at key points in the waste collection system
   2. 10If weighbridges are not feasible, develop alternative measurement approaches:
      1. 11Volume to weight using standard densities
      2. 12Vehicle load counting with estimated capacity
4. 13Implement data collection protocol
   1. 14Train collection staff on record-keeping procedures
   2. 15Establish recording timelines of data collection
   3. 16Create verification procedures to ensure accuracy
5. 17Develop data management systems
   1. 18Establish a central database for collection records
   2. 19Design simple data entry procedures for staff
   3. 20Monitor and verify the data through audits, comparisons and spot checks.

Licensed Recycling Facilities

1In the formal recycling sector, regulatory authorities should require record-keeping from licensed recycling facilities. These records should track volumes of plastic received, processed, and sold to end markets as well as the plastic types and quality levels.

2Implementation Steps

1. 3Create a registry of licensed recycling facilities
2. 4Develop a standardised reporting method focusing on the following metrics
   1. 5Tonnage of plastics collected for recycling (tons/year)
   2. 6Percentage of collected waste diverted to recycling
   3. 7Types of plastics recovered and their percentage distribution
   4. 8End markets for recycled materials
3. 9Establish a reporting schedule and submission process
4. 10Implement verification procedures including:
   1. 11Site visits
   2. 12Cross-checking data
5. 13Provide feedback and incentives to reporting facilities

Informal sector

1The informal collectors/ recyclers often play a significant role in material recovery, particularly in developing countries. Conducting surveys with waste pickers and informal collectors provides valuable data on materials that bypass formal collection systems. Periodic spot checks and interviews can help estimate volumes handled by the informal sector when direct measurement is not feasible.

2Implementation Steps

1. 3Identify key informants or organisations who understand the informal recycling networks
2. 4Design sampling approaches and survey instruments
   1. 5Identify a representative sample of socio-economic status, geography, urban versus rural contexts, types of informal collectors.
3. 6Collect field-data on informal waste collectors for recycling
   1. 7Conduct interviews with waste collectors
   2. 8Implement waste accumulation studies at aggregation points
   3. 9Record a sample of materials at various points in the value chain for:
      1. 10Tonnage of plastics collected for recycling
      2. 11Price
      3. 12End markets for recycled materials
      4. 13Temporal/spatial variations
4. 14Ensure appropriate compensation mechanisms for the participants’ time
5. 15Establish trust through transparency about study objectives, results and long-term engagement

4.1.2 Surveys

Social science surveys

1Social science surveys are structured data collection instruments used to gather valuable insights into human practices, behaviours, consumption patterns, and waste generation practices that may not be directly observable through other methods.

2Types:

• 3Household surveys: Collect data on residential consumption and/or waste generation, and disposal practices.
• 4Businesses/industry surveys: Gather information on commercial and industrial production and waste streams.
• 5Institutional surveys: Target educational institutions, hospitals and government facilities for plastics consumption and waste arising.

6Steps:

1. 7Co-design the work with relevant end-users, agreeing on shared objectives, key research questions, geographic coverage, and the team’s capacity and skills.
2. 8Establish the survey design, including whether it will be quantitative, qualitative, or both, and which variables need to be collected.
3. 9Define a sampling approach that ensures representative coverage across factors such as socio-economic status, institution or household type, and geographic distribution.
4. 10Assess the team’s capacity and skills, then recruit and train staff for the work ahead (e.g. interviewing).
5. 11Pilot the survey through pre-testing.
6. 12Implement the survey.
7. 13Collect data through questionnaires.
8. 14Analyse and interpret the results and communicate them to end-users and then to wider audiences.
9. 15Extrapolate the findings to the wider area using appropriate statistical methods.
10. 16Compare the results against other data sources.
11. 17Report and disseminate the findings.

Environmental surveys

1Environmental surveys are systematic data collection methods used to assess environmental conditions, impacts, and natural resources through direct field measurements and observations. They assess environmental conditions, impacts, and resources through ecological assessments, water and soil sampling, habitat mapping, pollution monitoring, and biodiversity inventories to inform conservation efforts, development planning, regulatory compliance, and environmental management decisions.

2Steps:

1. 3Design the sampling strategy and protocol
   • 4Define the study’s objectives and scope.
   • 5Define target environments using the IUCN Global Ecosystem Typology.
   • 6Design the sampling method. Ecosystems, realms, and biomes vary widely, so different methods are needed for each; choose standards that are nationally or internationally agreed to ensure comparability. Suggested methods for each ecosystem type are set out in Annex D, “Techniques for Scientific Sampling for Plastics in the Environment.”
   • 7Select study sites, informed by factors such as social, economic, or environmental significance, accessibility, or institutional capacity.
   • 8Set out clear team roles and responsibilities.
   • 9Establish monitoring protocols and safety procedures for fieldwork.
2. 10Categorise the debris
   • 11Separate plastic from natural (e.g. sand, soil, sticks), metallic, or ceramic materials.
   • 12Categorise plastic according to agreed groups, such as material, polymer, or use.
   • 13Where possible or necessary, verify identified groups using scientific techniques such as Fourier-Transform Infrared (FTIR) or Raman spectroscopy; this step can be skipped where resources are not available.
   • 14Record information on the isolated plastics, including total weight or quantity by plastic type, polymer, or use.
3. 15Analyse and report on the data
   • 16Engage research institutions or academic partners to carry out statistical analysis of the results. Examples include density metrics (items/m², g/m², particles/kg), maps of debris’ spatial distribution, analysis of composition and likely sources, and assessment of temporal trends.
   • 17Apply the findings to broader environmental management contexts, using appropriate statistical and spatial methods.
   • 18Compare the results against baseline data and regulatory standards.
4. 19Report and disseminate the findings.

4.1.3 Material Flow Analysis

1Material flow analysis (MFA) is a systematic assessment methodology that quantifies the flows and stocks of materials within a defined system boundary over a specified time period.

2Types:

• 3Substance Flow Analysis: Focuses on specific compounds within plastic materials
• 4Economy-wide MFA: Examines all material flows across an entire economic system or region.

5Steps

1. 6Define the system
   1. 7Define clear geographical and temporal boundaries for the analysis
   2. 8Identify key processes and stakeholders within the plastic value chain
2. 9Collect data
   1. 10Gather quantitative data on plastic production, import/export, consumption, and waste (where possible)
   2. 11Collect information on waste management routes and treatment efficiencies
3. 12Quantify the flows
   1. 13Calculate material transfers between system components
   2. 14Identify and quantify stock accumulations within the system
4. 15Verify the mass balance
   1. 16Apply mass balance principles to verify data consistency
   2. 17Identify data gaps and uncertainties in the analysis
   3. 18Where a specific flow or stock cannot be measured directly, it can instead be estimated as the residual needed to balance the system.
5. 19Visualise and interpret the results
   1. 20Create Sankey diagrams or flow charts to visualise material pathways
   2. 21Identify hotspots, inefficiencies, and intervention opportunities

22Modelling tools: Where system-level MFA data is available, dedicated modelling tools can translate it into policy-relevant scenarios. The Breaking the Plastic Wave Pathways Tool, developed by The Pew Charitable Trusts with the University of Oxford, is a free, open-access model that projects plastic flows through the value chain under different policy and intervention scenarios at city, national, or regional scale, together with the associated costs, jobs, and greenhouse gas emissions.

4.1.4 Remote Sensing Approaches

1Remote sensing refers to the collection and analysis of data about objects or areas from a distance, typically using satellite-based sensor technologies or private aerial technologies. In plastic management, these approaches enable the detection, monitoring and quantification of waste sites across large geographical areas without requiring extensive ground-level fieldwork. Remote sensing approaches offer significant advantages including their cost effectiveness, high-precision, and openly available data.

2Types:

• 3Satellite Imagery: Uses Earth observation satellites to identify and monitor larger waste areas.
• 4Drone surveys: Employs unmanned aerial vehicles for high-resolution imaging of specific waste areas of interest.
• 5Thermal imaging: Detects heat signatures from active burning sites using infrared sensors.
• 6Multispectral analysis: Utilises different spectral bands to identify waste material signatures.
• 7LiDAR (Light Detection and Ranging): Measures distances using laser light to create detailed topographical models for volume estimation.
• 8Fixed monitoring cameras: Provides continuous observation of specific waste accumulation hotspots.

9Steps:

• 10Site selection
  • 11Prioritise target areas based on existing information or preliminary assessments
  • 12Identify areas with limited accessibility or monitoring coverage
• 13Platform selection
  • 14Determine appropriate technology based on location, required resolution, and project scope
  • 15Select suitable software platforms (Google Earth Engine, ArcGIS, QGIS) for analysis
  • 16Consider cost-effectiveness and technical requirements
• 17Image acquisition
  • 18Select optimal imagery sources (open-source, commercial, or locally deployed)
  • 19Establish regular imaging schedule to track changes over time
  • 20Account for environmental conditions (cloud cover, lighting, seasonality)
  • 21Maintain consistent methodology for longitudinal monitoring
  • 22Document environmental conditions during each acquisition period
• 23Image processing and analysis
  • 24Apply specialised algorithms to detect waste accumulation
  • 25Utilise machine learning or artificial intelligence for automated identification
  • 26Calculate surface areas and estimate volumes of identified waste sites
  • 27Validate results through ground-truthing at selected locations
• 28Data integration and visualisation
  • 29Convert identified waste sites to quantity estimates using validated models
  • 30Integrate findings with GIS systems for spatial analysis
  • 31Combine with complementary environmental and socioeconomic datasets
  • 32Develop visualisation tools for decision-makers and stakeholders

4.1.5 Waste Composition Estimates

1Plastic waste composition studies involve systematic sampling and manual sorting of incoming waste streams to determine plastic percentages by weight and polymer type. These studies provide detailed breakdowns of various plastics present - from PET and HDPE to PVC, LDPE, PP, and PS - establishing critical baseline data that enables tracking of plastic pollution trends and identification of targeted plastic recycling opportunities.

2The methodology employs statistical sampling techniques that allow for extrapolation to total plastic waste volumes. When properly conducted, these studies capture seasonal variations in plastic disposal patterns and provide precise data on plastic contamination across different sources and geographical areas.

3Despite their analytical value, plastic waste composition studies present several operational challenges. They are notably resource-intensive, requiring specialised polymer identification equipment and personnel trained in plastic categorisation. The process of sorting and identifying different plastic types is labor-intensive and potentially costly, limiting the frequency of plastic data collection to typically quarterly or annual intervals rather than continuous monitoring.

4The representativeness of results can be compromised by plastic sample selection methods, as chosen samples may not accurately reflect all plastic waste streams. Additionally, these studies provide only point-in-time measurements of plastic composition, necessitating repeated analyses to maintain current plastic pollution data.

5Types:

• 6Physical sorting analysis: Direct manual separation and weighing of waste samples
• 7Visual characterisation: Observers estimate the composition through visual inspection and separating into waste fractions

8Steps:

• 9Study design and planning
  • 10Define clear objectives and determine appropriate sample size
  • 11Select representative sampling locations and establish material categories
• 12Sample collection
  • 13Collect representative waste samples from predetermined sources
  • 14Ensure adequate sample size (typically 100-200 kg per sampling event)
• 15Physical sorting and analysis
  • 16Sort waste into predetermined material categories
  • 17Weigh each fraction and calculate percentage by weight
• 18Data analysis and interpretation
  • 19Calculate composition percentages by weight for each material category
  • 20Compare results across different sources or time periods
• 21Reporting and application
  • 22Document methodology, assumptions, and limitations
  • 23Establish baseline for monitoring composition changes over time

4.1.6 IPCC 2006 Guideline for National Greenhouse Gas Inventories

1This subsection draws on two elements of the IPCC 2006 Guidelines for National Greenhouse Gas Inventories that can be adapted to estimate plastic waste quantities: standardised data on waste composition, used to estimate the plastics share of the waste stream, and a standardised equation for solid waste that is openly burned, used to estimate the quantity of plastic lost to uncontrolled burning.

Waste composition

1Many countries collect detailed waste composition data through their National Atmospheric Emissions Inventory (NAEI) reporting, mainly to estimate landfill emissions; this is the same data used to compile the reports submitted to the UNFCCC.

2Where countries do not have accurate waste composition data of their own, they can instead use the IPCC fixed assumptions for Municipal Solid Waste (MSW) composition set out in Table 4.1, below.

3Table 4.1. IPCC standardised assumptions on the plastics proportion of municipal solid waste in each region

Region	Plastic Percentage of MSW (%)
Asia
Central Asia	8.4
Eastern Asia	6.5
South-Eastern Asia	10.2
Southern Asia	7.0
Western Asia	17.2
Africa
Northern Africa	13.8
Eastern Africa	8.0
Middle Africa	7.1
Southern Africa	26.5
Western Africa	6.4
Europe
Eastern Europe	4.6
Northern Europe	4.9
Southern Europe	11.8
Western Europe	20.5
America
Central America	10.3
South America	13.7
Northern America	15.8
Oceania
Australia and New Zealand	8.3

Solid waste openly burned

1Although designed for greenhouse gas inventories, the IPCC 2006 Guidelines for National Greenhouse Gas Inventories set out a standardised equation for solid waste that is openly burned, which can be adapted to estimate plastic waste quantities.

2Chapter 5 of the IPCC Guidelines, “Incineration and Open Burning of Waste,” sets out this equation. Applying a plastics fraction drawn from waste composition data (see Waste composition, above) to the equation’s output isolates the plastic-specific component of openly burned waste.

3The equation below is Equation 5.7 of Chapter 5: Incineration and Open Burning of Waste of the IPCC Guidelines, with variable names aligned to this Handbook’s existing convention.

$$\mathrm{MSWB} = P \times \mathrm{Pfrac} \times \mathrm{SWc} \times \mathrm{Bfrac} \times 365 \times 10^{-6}$$

4Where:

• 5SW = Total municipal solid waste open-burned (gigagrams/year)
• 6P = Total population (persons)
• 7Pfrac = Fraction of population burning waste
• 8MSWP = municipal solid waste generation rate per capita (kg/person/day)
• 9Bfrac = Fraction of waste that is burned relative to total waste treated
• 10365 = Days per year
• 1110⁻⁶ = Conversion from kg to gigagrams

12Some of this openly burned waste will come from uncollected sources, and some will come from collected sources. The 2019 Refinement to the 2006 IPCC Guidelines (Volume 5, Chapter 5) updates the default data and methods underlying this equation and should be consulted alongside it. The worked example below illustrates how the equation can be applied, using hypothetical figures.

Worked example (illustrative figures only)

Suppose a population of 5,000,000 people, of whom 15% burn their waste (Pfrac = 0.15), generates 0.6 kg of solid waste per person per day (SWc), with 40% of that waste burned relative to total waste treated (Bfrac = 0.40).

SW = 5,000,000 × 0.15 × 0.6 × 0.40 × 365 × 10⁻⁶ ≈ 65.7 Gg/year of solid waste openly burned.

If waste composition data indicate that plastics make up 10% of the waste stream (see Table 4.1, above, for regional assumptions), the plastic-specific estimate is 65.7 × 0.10 ≈ 6.6 Gg/year.