A Geographically-based modelling tool to promote Circular Economy decision making and identification of climate and environmental impacts of sectoral activities: Orkney Islands Case Study.

Overview

What?
The aim of this project is to develop a geographically-based decision-making tool, which will enable early identification of the environmental impacts of sectoral activities to ensure that Circular Economy design is central to planning processes. The tool takes into account the uncertainty in the process of decision making process and provides flexibility while answering specific sustainable development questions relevant to Orkney in the next decade.

Why?
Ambitious targets have been set for the delivery of Net Zero Carbon in the Orkney islands by 2030. Sectors with big footprints in Orkney include Transport, Housing, Agriculture, Fisheries and Tourism. In order to reach these targets significant behavioural changes must be made by Orkney residents and visitors regarding their use of resources and services. Development of tools which can visualise the changes and communicate the process in a transparent way are needed. This tool will be used to educate, interact, and modified by the society through visualisation and public engagement. This is a key element to the decarbonisation process.

Where?
Orkney is the choice for this case study approach to design of the tool because it represents a discrete geographical region, with substantial datasets available across some of the sectors already. This makes it a tractable proposition for building the tool and testing it out. The project would also sit alongside other major projects in decarbonisation including the UKRI ReFLEX project (http://www.emec.org.uk/ukri-gives-green-light-to-reflex-orkney-project-2/). Funded by UKRI through the Industrial Strategy Challenge Fund, ReFLEX Orkney is aiming to integrate electricity, transport and heat networks in Orkney using advanced software to balance demand and supply. The pioneering project is helping Orkney maximise the potential of its renewable production capabilities and reduce the county’s carbon footprint by decreasing reliance on imported carbon-intensive grid electricity from the UK mainland.

How?
The tool will be developed from the RADDMAP Geospatial Information System (GIS) database system of Aquatera Ltd, with significant developments by the student to incorporate a dashboard for promoting interaction with stakeholders and for supporting members of the public wishing to change their behaviour to promote reduction of emissions across the sectors. While receiving input and modification through mutual interactions with stakeholders may add to the bias of the results of the tool, the tool can consider and act to debias data, and deal with uncertainty of the inputs.

Impact
The tool will be designed and piloted for the Orkney region. If successful it can be replicated via linkage with the Net Zero Carbon Centre based at Orkney Research and Innovation Campus in Stromness, which forms part of the UK and Scottish Government funded Islands Growth Deal funding (https://www.gov.scot/news/gbp-50-million-for-islands/). Opportunities for replication for the tool would exist across to the Western Isles and to Shetland through the collaboration of the stakeholders engaged in the consortium. Ultimately the tool could be implemented beyond the Islands at a national and international level.

Research questions
1. What is the geospatial distribution of cumulative carbon emissions across sectors in the Orkney region?
2. What is the geospatial distribution of carbon sinks across the Orkney region from terrestrial and marine biospheres? In this context, the project will consider carbon sources as well as carbon sinks in order to evaluate correctly net fluxes.
3. How effective are the geovisualisations in supporting decision making to promote Circular Economy across the regional sectoral interests?
4. How effective are the geovisualisations in supporting decision making to reduce carbon emissions and promote carbon sequestration and storage across the regional terrestrial and marine biospheres?
5. how geospatial uncertainties (including positional and thematic inaccuracies) and biases will change the results?
6. How effective are the quality assurance measures for the SDSS (Spatial Decision Support System) tool?

Methodology

1. Collation of regional based sectoral datasets, data cleaning and importing into RADD MAP databasing system. This process will involve critical review of strengths/weaknesses of the available datasets, quality assessment, missing data imputation and debiasing processes and prioritisation of gathering and merging essential data.
2. Visualisation of the data using the RADDMAP system and development of how the outputs could be used to develop live dashboard style approach for interaction with stakeholders.
3. Piloting of the dashboard with stakeholders to promote decision making on Circular Economy and carbon emissions reductions at the regional level.
4. Revision of the dashboard taking into consideration the feedback from the stakeholders.
5. Critical evaluation of the tool with a view to replication out to other regions.

Project Timeline

Year 1

Months 1-6: Objective 1. Engage with Case partner and relevant stakholders. Plans scientific manuscripts.
Months 7-12: Start work on Objective 2.

Year 2

Months 13-18: Continue and complete work on Objective 2. Engage with CASE partner and with relevant stakeholders
Months 19-24: Objective 3, Pilot the tool with stakeholders across different sectors.

Year 3

Months 25-30: Continue and complete Objective 3. Engage with CASE partner and with relevant stakeholders
Months 31-36: Completion of Objectives 4 and 5. Complete draft of scientific manuscripts.

Year 3.5

Final 6 months: Writing up and submission of the PhD thesis, finalising scientific manuscripts, reporting back to stakeholders.

Training
& Skills

The student will be embedded through a placement into Aquatera Ltd particularly during the first year and final year of the project. The student will obtain advanced skills in handling and analysis of large datasets, Geospatial databasing and visualisation, networking and engagement with stakeholders and presentation skills relating to the visualisation aspects of the tool.

References & further reading

Nowacka, Anna & Remondino, Fabio. (2018). Geospatial data for energy efficiency and low carbon cities: overview, experiences and new perspectives. ISPRS – International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XLII-4. 467-474. 10.5194/isprs-archives-XLII-4-467-2018. https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4/467/2018.

Further Information

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