NORSUS and Leiden University are leading a UNEP-supported survey for weighting environmental impacts in LCA

Ugandan Research Team

Hoima District: Timothy Galabuzi, Bena Nansubuga, Emmanuel Kaduku, Joan Businge, Denis Twinomujuni are participating in the survey.

NORSUS participates in the important international standardisation work that takes place in the GLAM expert group of the UN Life Cycle Initiative. GLAM is an abbreviation for Global Guidance for Life Cycle Impact Assessment Indicators and Methodswhich was initiated in 2013 in order to generate tangible and practical recommendations for different environmental indicators and characterization factors used in Life Cycle Impact Assessments (LCIA).

A subgroup of GLAM, co-chaired by NORSUS senior researcher Cecilia Askham and assistant professor Marco Cinelli from the University of Leiden, aims to develop a global model for weighting of issues that are important for our environment, human health and natural resources. This model is needed in order to help decision-makers prioritise when analyses of the complex world we live in provide answers that point in different directions. Decision-makers sometimes have to rank these important matters (environment, human health and natural resources) in order to make decisions. The nature of this work is subjective and value based, so the sub-group developed a survey to learn what preferences people around the world have on these matters.


Interviewer: Oumarou OUATTARA
Interviewer: Oumarou OUATTARA
Interviewer : Abdoul Aziz Adama BANDE
Interviewer: Abdoul Aziz Adama BANDE
Dr. Christine Nagawa (Makarere University) og Dr. Christine Kyarimpa (Kyambogo University)
Dr Christine Nagawa (Makarere University) and Dr Christine Kyarimpa (Kyambogo University)
Interviewer: Styve Cédric SANON
Interviewer: Styve Cédric SANON

NORSUS has contributed to funding and coordinating information gathering in Uganda and Burkina Faso. The interviews have recently been completed, and now researchers in several countries are working hard on the analysis of the data to calculate the weighting factors that will be part of the GLAM recommendations.