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Related Experiment Video

Updated: Jun 28, 2026

Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger

Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger

Published on: January 16, 2020

Using SFA indicators to support environmental policy.

E van der Voet¹, L van Oers, J B Guinée

¹Centre of Environmental Science, Leiden University, P.O. Box 9518, NL-2300, RA Leiden, The Netherlands. voet@rulcml.leidenuniv.nl

Environmental Science and Pollution Research International

|November 14, 2008

Summary

This summary is machine-generated.

This study translates Substance Flow Analysis (SFA) into key indicators for evaluating regional environmental quality and sustainable development. It helps link SFA data to environmental policy, addressing issues across time and space.

Related Experiment Videos

Last Updated: Jun 28, 2026

Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger

Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger

Published on: January 16, 2020

Area of Science:

Environmental Science
Sustainability Science
Policy Analysis

Background:

Substance Flow Analysis (SFA) provides a comprehensive overview of material flows and stocks.
There is a need to bridge the gap between SFA data and practical environmental policy-making.
Existing SFA approaches may not directly translate into actionable policy insights.

Purpose of the Study:

To develop a method for translating SFA data into a concise set of indicators.
To enhance the linkage between SFA studies and environmental policy development.
To create tools for evaluating a region's substance management in the context of environmental quality and sustainable development.

Main Methods:

Development of a translation framework from SFA flows and stocks to indicators.
Selection of a limited, policy-relevant set of indicators.
Analysis of substance regimes considering environmental quality and sustainable development.

Main Results:

A defined set of indicators derived from SFA data.
The indicators facilitate the evaluation of regional substance management.
The framework accounts for problem shifting in both temporal and spatial dimensions.

Conclusions:

The proposed translation enhances the policy relevance of SFA.
The indicator set provides a valuable tool for assessing environmental quality and sustainable development.
This approach supports more informed and effective environmental policy decisions.