Waste separation behavior: A field study on information interventions and underlying mechanisms

Municipal waste generation exceeds 2 billion tons annually and is projected to rise 56% by 2050, intensifying environmental and resource recovery challenges. Even in countries with an advanced infrastructure like Germany, household waste sorting errors persist, undermining recycling efficiency. This study applies the Motivation-Opportunity-Ability (MOA) framework to examine behavioral drivers of sorting accuracy and to assess the effect of an information intervention. In a mixed-design field experiment with 102 households across socioeconomically diverse districts in Stuttgart, waste composition was measured before and after distributing an environmental flyer to the intervention group. Regression analyses revealed that structural factors-particularly limited access to collection points, system-inherent barriers, and knowledge-related barriers-significantly predicted sorting errors, while motivational variables had surprisingly no effect on sorting accuracy. The flyer intervention reduced errors across both socioeconomic groups, with flyer households showing a 69.7% reduction compared to 28.8% in the control group. Findings underscore the importance of addressing infrastructural and cognitive constraints alongside informational tools to improve waste separation systems. Well-designed flyers offer a cost-effective, scalable strategy to promote sustainable behavior, enhance recycling quality, and advance circular economy goals.

Authors

Institutions

Publication Details

Journal
Journal of Environmental Management
Published
2026-02-26
DOI
https://doi.org/10.1016/j.jenvman.2026.129111
Citations
1
Primary Topic
Municipal Solid Waste Management
Type
article
Field-Weighted Citation Impact
35.31
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Waste separation behavior: A field study on information interventions and underlying mechanisms

Ramona Weinrich, Ellen Mielinger, Eva Pawelczyk
1 citations
Journal of Environmental Management
Municipal Solid Waste Management
35.31
article

Waste separation behavior: A field study on information interventions and underlying mechanisms

Ramona Weinrich, Ellen Mielinger, Eva Pawelczyk
article en
1 citations

Abstract

Municipal waste generation exceeds 2 billion tons annually and is projected to rise 56% by 2050, intensifying environmental and resource recovery challenges. Even in countries with an advanced infrastructure like Germany, household waste sorting errors persist, undermining recycling efficiency. This study applies the Motivation-Opportunity-Ability (MOA) framework to examine behavioral drivers of sorting accuracy and to assess the effect of an information intervention. In a mixed-design field experiment with 102 households across socioeconomically diverse districts in Stuttgart, waste composition was measured before and after distributing an environmental flyer to the intervention group. Regression analyses revealed that structural factors-particularly limited access to collection points, system-inherent barriers, and knowledge-related barriers-significantly predicted sorting errors, while motivational variables had surprisingly no effect on sorting accuracy. The flyer intervention reduced errors across both socioeconomic groups, with flyer households showing a 69.7% reduction compared to 28.8% in the control group. Findings underscore the importance of addressing infrastructural and cognitive constraints alongside informational tools to improve waste separation systems. Well-designed flyers offer a cost-effective, scalable strategy to promote sustainable behavior, enhance recycling quality, and advance circular economy goals.

Journal of Environmental ManagementVol. 402
University of Hohenheim (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 0%
Municipal Solid Waste Management
35.31
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.