Dataset in municipal biowaste collection strategies in Portugal

Published: 8 August 2025| Version 2 | DOI: 10.17632/tt6j24z8g2.2
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Description

The dataset provides an updated overview of the separate collection of organic kitchen waste (mostly food waste) across Portugal’s 308 municipalities. Data was collected through a structured questionnaire distributed to all municipalities and a systematic search of secondary official sources, mostly municipal websites and reports. Collected data comprises (i) waste collection approaches followed by the municipalities, (ii) activity sectors targeted by the separate collection, (iii) Type of collection in single-family, multi-family, or mixed areas, including access to the waste container - free or controlled, (iv) date when separate collection was implemented, (v) changes made to the regular collection as a result of separate collection, (vi) capture rates and (vii) operational and investment costs, (viii) Whether economic incentive mechanisms are present and (ix) number of inhabitants and establishments covered by the separate collection.

Files

Steps to reproduce

1. Questionnaire Design: Create a structured questionnaire using Microsoft Forms. The questions were designed to capture the characteristics of the different municipal biowaste collection models (nearby bring points, door-to-door, and co-collection), focusing on specifics such as service coverage area/inhabitants, collected quantities, and financial aspects. 2. Distribution to Municipalities: Addressing the waste treatment municipal services by email. 3. Primary Data Compilation: Collect the survey responses. For this dataset, 93 responses were received and compiled. 4. Secondary Data Sourcing: Conduct a systematic search of publicly available official sources for complementary data to address those municipalities without answers or to complement the answers received. These sources include, among others, official municipal websites, local or national news, and waste management reports. 5. Data Integration and Validation: Cross-reference, validate, and supplement the data obtained from the questionnaires with the information gathered from secondary sources to produce a final, refined dataset.

Institutions

Universidade Aberta Departamento de Ciencias e Tecnologia

Categories

Municipal Waste, Waste Collection, Recycling Performance Indicator, Food Waste, Kitchen Waste

Funding

CENTRO DE COMPETÊNCIAS DE PLANEAMENTO, DE POLÍTICAS E DE PROSPETIVA DA ADMINISTRAÇÃO (PLANAPP)

C19-i07.04

Fundação para a Ciência e Tecnologia

C19-i07.04

Licence