Return to Metabolism of Cities

“How to” with Metabolism of Cities

Your Circularity journey on Metabolism of Cities

The CityLoops Data Hub

How to add data to the CityLoops Data Hub

Collecting geospatial information

How to process data

Aggregation and disaggregation

Data Hub processing: geospatial data

Geospatial spreadsheets

Data Hub processing: spreadsheet data

Flow data processing

Stock data processing

Population data processing

Data gap analysis

How to analyse data

How to benchmark indicators

How to interpret the circularity dashboards

Flow Diagram Builder

Eurostat Library and Grid

Existing reports

Urban Circularity Assessment – Handbook

Why should cities carry out the UCA?

What is the UCA?

What are the UCA materials?

What are the outputs?

What are the steps of the UCA?

Part 1a: Material Flow Accounting

Defining urban context

Data collection

Step 1: Select if materials are extracted, imported and/or exported

Step 2: Determine if data from the SCA can be reused

Step 3: Find local data to satisfy your data needs

Step 4a: If you don’t have or can’t find local data, try to use provided data sources

Step 7: Determine which waste treatment methods exist within your municipal boundaries

Step 8: Determine if you have data for the waste categories and fill in the amounts

Data processing

Step 4b: Downscale the data from Step 4a with the correct proxies

Step 5: Fill in your final values in tonnes for two years

Step 6: Note meta information of the data

Part 1b: Material Stock Accounting

Step 1: Find locations, land use and floor areas of buildings

Step 2: Gather building typologies

Step 3: Determine building typology’s material composition

Step 4: Calculate material stock and spatialise it

Part 2: Measuring indicators

Part 3: Assessing Circularity

Step 1: Data gap and quality analysis

Step 2: Interpretation of indicators

Step 3: Assessing the circularity of the city

Sector-Wide Circularity Assessment – Handbook

Why should cities carry out the SCA?

What is the SCA?

What are the sectors and materials?

What are the outputs?

What are the steps of the SCA?

Step 1: Data collection

Layer 1: Urban context

Economic activities in the city

Policy documents

Layer 2: Sector economic activities

GDP and/or GVA per NACE code

Employees per material

Geo-localisation of infrastructure

Layer 3: Material flows and stocks

Extraction / harvesting

Construction manufacturing

Biomass manufacturing

Construction waste

Imports and Exports

Step 2: Data processing

Step 3: Data analysis

Generation of Sankey diagram

Selection and calculation of indicators

Background and glossary of indicators

Generation of insights

Insights from Sankey diagram

Insights from single datasets

Insights from data quality assessment

Insights from indicators

Step 2: Data processing

Data processing is the second step of the SCA.

Goal: Process the collected data to:

bring the data into the right format (annual weight unit)
determine which data is still missing and needs to be collected
create individual dataset visualisations (on the Data Hub), to better understand the data
fill in Table 1 and 2, in order to build the basis for the analysis through indicators and the Sankey diagram

Approach

Step 2 is about data processing and continues the work of the SCA by following Step 1: data collection. The documents that were uploaded in its various data formats, such as Excel, PDF, shapefiles, CSV are taken and converted to a standardised format for a reference year.

Three general substeps have to be carried out in the data processing step. Since their nature is the same for the SCA and the UCA (Urban Circularity Assessment), they are therefore explained in the overarching section of “How to process data”.