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Project title

A Data Driven Circular Economy National Platform

Primary Funding Agency

Environmental Protection Agency

Co-Funding Organisation(s)

n/a

Lead Organisation

University of Limerick (UL)

Lead Applicant

Colin Fitzpatrick

Project Abstract

A vast range of data is collected and curated on every aspect of the economy, society and environment by a host of different government agencies and private organisations. Meanwhile, machine learning is the most popular branch of artificial intelligence that has driven the use of data in the creation of evidence-based models and objective and verifiable insights over the last two decades. The underlying concept of this project is to employ machine learning to develop algorithms to understand the relationships between these datasets, and ultimately predict material flows and outcomes. This project will create a tool that will be useable by policy makes and will have two obvious uses and impacts in policy impact assessment. A policy impact assessment is aimed at bringing scientific evidence to the attention of decision makers using evaluation and prediction of potential impacts of different policy options . It is an approach to support the development of evidence-based policies and monitor their implementation. The first impact is in ex-post Policy Impact Assessment where we can use this model to estimate what waste would have been generated in the absence of a given policy and how it would have been treated without any further policies or initiatives in place. This model can therefore be used as a counterfactual comparison to quantify the impact of circular policies and other initiatives post implementation. The second impact is in Ex-Ante Policy Impact Assessment as it will deliver a virtual sandpit to simulate and test the potential impacts of new proposed policies or initiatives. Having a model such as this would allow policy makers to simulate the effects of the introduction of a new policy on customer and company behaviours and, eventually, waste creation patterns. Hence, policy makers will be able to run ‘what if’ analyses to select and fine tune policies. Moreover, the model will be able to indicate how contributors to waste streams are expected to be effected by the proposed policy, thus providing early insights in the implications any proposed policy may have. It responds directly to the OECD report "The Circular Economy in Ireland" to create a National Circular Economy Information System.

Grant Approved

�596,276.23

Research Hub

Green and Circular Economy

Research Theme

Harnessing Data and Digitalisation for the Environment

Start Date

29/03/2024

Initial Projected Completion Date

28/03/2028