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A review of the criteria that influence choices concerning the location of onshore wind energy projects in Iceland
(University of Iceland, Department of Environment and Natural Resources, 2025-04-30) Cook, David; Pétursson, Jón Geir; Umhverfis- og auðlindadeild (HÍ); Department of Environment and Natural Resources (UI)
WIND ENERGY – BACKGROUND Over the course of the 20th Century, the global use of onshore and offshore wind energy has continued to expand, especially in response to environmental, availability and price concerns about electricity generation derived from fossil fuel combustion (Kiunke et al., 2022; Msigwa et al., 2022). Today, wind energy constitutes the fastest growing technology in the renewable power industry, with almost 1,870 TWh produced in 2021, up 17% on 2020 generation (IEA, 2022). Total installed capacity from onshore and offshore sources in 2020 was 837 MW, more than half of which is sourced from China (GWEC, 2022). Approximately 6.7% of global electricity production was from wind energy in 2021 (BP, 2022). In the light of various nations’ net zero greenhouse gas emissions commitments, the GWEC (2022) project rapid further expansion, anticipating an additional 557 GW of combined offshore and onshore capacity by the end of 2026. Despite the various uses of wind power, its growing significance as a share of global electricity production, and environmental advantages in comparison to fossil fuel powered alternatives, the negative consequences of wind turbine installations and wind farms have often been to the fore in the public and planning discourse about the merits of the technology (Brannstrom et al., 2022; Graham et al., 2009; Langer et al., 2018). Hastik et al. (2015) provided a comprehensive analysis of the environmental and ecosystem service impacts of several renewable energy technologies. In the case of impacts located close to the site of onshore wind farms, the most often cited issues are negative effects on birds and bats (Husby and Pearson, 2022; Lintott et al., 2016; Wang et al., 2015), altered landscape aesthetics (Vlami et al., 2016), shadow flickering and safety risks (Karanikas et al., 2021), and health impacts from noise (Nazir et al., 2020). Offsite issues, such as the construction of access roads and power line infrastructure, often constitute additional concerns (Hastik et al., 2015). Connected to these various issues, several studies have also focused on the themes of social acceptance and how best to cultivate a social license to operate (Colvin et al., 2019; Frate et al., 2019; Walker and Baxter, 2019). GIS MAPPING FOR LOCATING RENEWABLE ENERGY PROJECTS The various environmental, social, and economic implications of renewable energy projects frequently demand advanced decision support platforms to determine the optimality of proposals. In recent years, an increasing number of studies have utilised Geographic Information System (GIS) mapping in tandem with MCDA to enrich the data pool available to decision-makers. The aim of GIS mapping is to store, retrieve, manipulate, analyse, and map geographical data (Church, 2002). The recent study by Cook and Pétursson (2023) appraised the increasingly significant role of GIS-based analysis, specifically connected to its use within MCDA. Although focused only on geothermal power, hydropower, and onshore wind energy, the study nevertheless revealed the breadth of focus of GIS-MCDA in the academic literature, particularly in relation to issues such as economic prospectivity, land-use trade-offs, visual impacts of erected infrastructure, and the social acceptability of proposals. A total of 41 articles were analysed, based on the most relevant publications in the period January 2017 to May 2023. These were split as follows: n = 13 for geothermal power, n = 9 for hydropower, and n = 19 for wind power. As per the detailed Appendix C in the Cook and Pétursson (2023) study, the criteria evaluated in the GIS-MCDA literature on onshore wind energy projects includes the following: • Environmental impacts (e.g., visual, noise, birds, bats, shadow flicker, soil texture, presence of geological formations, etc.). • Location specifics (e.g., predicted productive capacity; relief and topography; other land uses; and distance to electricity sub-stations, powerlines, telecommunications, roads, tourist sights, cities, towns, railways, etc.). • Land use and legal restrictions (e.g., protected areas, airports, military zones, forests, sand dunes, farms, vegetated areas, wetlands and rivers, urban locations, etc.). • Socio-demographics (e.g., population density) and social acceptability of proposals. ONSHORE WIND ENERGY DEVELOPMENT IN ICELAND Onshore wind energy is a relatively new technology in Iceland, currently comprising a few off-grid turbines and contributing a token 0.03% of national electricity generation (NEA, 2023). However, given the strong productive potential of onshore wind power (Archer and Jacobson, 2005; Nawri et al., 2014) there are plans for expansion (Sæþórsdóttir et al., 2021). A 120 MW wind farm at Búrfellslundur in South Iceland, where two 0.9 MW test turbines have operated for a decade, will be the first major wind power project in Iceland, commencing operations within the next few years. Another project of ca. 100 MW at Blöndulundur in North Iceland is also planned and classed in the utilisation category by Iceland’s Master Plan for Nature Protection and Energy Utilization (ramma.is, n.d.). In early 2025, 39 wind energy projects had been submitted for assessment in the Master Plan, a clear indication of the interest in wind energy development in the country. AIMS AND STRUCTURE This report has the following aims: 1) To consider how the various GIS-MCDA criteria for onshore wind energy projects, as identified by Cook and Pétursson (2023), could apply to the Icelandic context. 2) To evaluate the extent to which GIS-based analysis is already utilised in Iceland and what additional aspects could be considered, providing potentially useful information to aid Iceland’s Master Plan for Nature Protection and Energy Utilization, and its Steering Committee and four Expert Groups. Section 2 of this report provides a summary overview on how MCDA studies are typically structured and operate in a renewable energy project context. Sections 3 to 5 of this report consider the GIS-MCDA evaluative criteria identified in Cook and Pétursson (2023) with respect to onshore wind energy projects, outlining how these are likely to apply to the Icelandic case. Much of this content constitutes a synthesis of other work recently published in support of the Master Ploan’s evidence base. Section 6 then provides a discussion, first reflecting on the extent to which such GIS-MCDA based evaluations are already undertaken in Iceland and then considering the main practical and policy-making implications of this study. Section 7 provides a short conclusion regarding the main findings.
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Application of Multi-Criteria Decision Analysis (MCDA) for assessing the location of energy options: A literature review on the use of GIS-MCDA to inform the Master Plan
(University of Iceland, Department of Environment and Natural Resources, 2025-09-30) Cook, David; Pétursson, Jón Geir; Department of Environment and Natural Resources (UI); Umhverfis- og auðlindadeild (HÍ)
BACKGROUND Information gathering about likely environmental and social impacts can play a major role in assuaging public concerns about the location of energy infrastructure, particularly when such data is used to enlighten developers about the optimal location of onsite infrastructure (Kazak et al., 2017; Sliz-Szkliniarz et al., 2019). As such a determination depends on many factors, the use of Multi-Criteria Decision Analysis (MCDA) has become increasingly popular in energy planning (Kazak et al., 2017). MCDA constitutes a type of Multi-Criteria Decision-Making (MCDM) support system, which can model social, economic and environmental factors, helping to provide a broad perspective on the overall merits of energy projects and diminishing the risk that interests specific to one or two social groups could carry overwhelming weight in decision-making (Harper et al., 2019; McKenna et al., 2022). A broad variety of criteria can be incorporated into MCDA methods for comparing the characteristics of energy projects, including but not limited to land uses, distances to ports, urban areas and distribution and transmission systems, wind speed, slope, air density, and ecological impacts (Tahri, et al., 2015; Villacreses et al., 2017). The quality of environmental information provided to inform MCDAs is a significant issue. In recent years, an increasing number of studies have utilised Geographic Information System (GIS) mapping in tandem with MCDA to enrich the data pool available to decision-makers. The aim of GIS mapping is to store, retrieve, manipulate, analyse and map geographical data (Church, 2002). The application range of GIS mapping is considerable, including but not limited to the mapping of landslide hazards (Carrara et al., 1995), health impacts (Brewer, 2006), ecosystem services (Troy and Wilson, 2006), place values (Brown et al., 2020), mineral prospectivity (Zuo et al., 2021), and solar radiation (Choi et al., 2019). MCDA operates via several approaches, which are commonly divided into two categories (i) multi-objective decision-making (MODM), and (ii) multi-attribute decision-making (MADM) (Ho, 2008; Pohekar and Ramachandran, 2004). MODM is a systematic process that aims to identify conflicts and trade-offs, reconciling these in a transparent manner through compromise and incorporating indicators of the strength of various preferences for specific objectives (Roijers, 2017). MADM involves the undertaking of preference decisions (including evaluation, prioritisation, and selection) concerning the available project alternatives that are typically characterized by multiple, conflicting attributes (Xu, 2015). The Analytic Hierarchy Process (AHP) has become one of the most applied approaches within MCDA. It compares multiple alternatives, each with several criteria to help identify the best option via pairwise comparisons (Vaidya and Kumar, 2006). This contrasts with approaches that utilise numerical values directly. OBJECTIVES AND METHODS Despite the increasing deployment of GIS approaches to inform MCDA in the context of various energy projects, the literature is scattered and, thus far, devoid of a review and synthesis of the main analytical approaches. Scrutinising the literature will help to identify the criteria in MCDA that are currently being informed by GIS mapping and the different types of MCDA platforms that are being used by decision-makers specific to energy projects. This information will be particularly useful for decision-makers who are considering the breadth of criteria that could make use of GIS-based information within MCDA, especially when such platforms are already applied and continuing to evolve. This is the case with respect to Iceland’s Master Plan for Nature Protection and Energy Utilisation (hereafter referred to simply as the ‘Master Plan’), which is a complex decision-support tool with a national scope and based on MCDA principles. It endeavours to reconcile the frequently competing interests of nature conservation and energy utilisation during the earliest planning stages. First commenced in 1999, the Master Plan became enshrined in Icelandic law in 2013 and is shortly entering its fifth evaluative phase. The first two evaluative phases of the Master Plan only evaluated the merits of potential geothermal and hydropower projects in Iceland, however, the third phase also encompassed wind farms. All energy projects subject to the Master Plan’s assessment are evaluated following consideration of multiple different interests, many of which are allocated weightings in the assessment process. This leads to an eventual ranking and the classification of all power plant options into one of three categories: utilisation, on hold, or protection. This report conducts a Systematic Literature Review (SLR) to fulfil its objectives. A combination of the Search, Appraisal, Synthesis and Analysis (SALSA), together with the snowballing method, is used in this SLR. These methods have been widely adopted in SLRs in a broad variety of decision-making contexts, including in Arctic ecosystem services (Malinauskaite et al., 2019), MCDA studies on geothermal power projects (Cook et al., 2019), sustainable energy development (Gunnarsdóttir et al., 2020), and the systemic risk issues pertaining to the COVID-19 pandemic (Cook and Jóhannsdóttir, 2021). STRUCTURE This report commences in Section 2, where further background material is provided concerning how MCDA studies are typically structured and operate in a renewable energy project context. Section 3 articulates the history of the Master Plan in Iceland and its structure, including its overarching Steering Committee and four Working Groups, is set out. The remit of each Working Group is described, together with the main criteria under evaluation. Section 4 outlines the SALSA method used to conduct the systematic literature review and provides the main results specific to each of the energy generating technologies under study – geothermal power, hydropower, and onshore wind. Section 5 discusses the relevance of the outcomes for the Master Plan, and the main practical and decision-making implications of the GIS-MCDA studies reported in the examined literature. Section 6 provides a brief conclusion and outlines potential areas for future research.
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Maternal Smoking during Pregnancy and Academic Achievement of Offspring over Time: A Registry Data-Based Cohort Study : A registry data-based cohort study
(2018-08) Kristjansson, AL.; Thomas, S.; Lilly, CL.; Thorisdottir, IE.; Allegrante, JP.; Sigfusdottir, ID.; Department of Psychology
Few studies have assessed the cumulative impact of maternal smoking during pregnancy (MSDP) on scholastic outcomes over time. We examined the relations between MSDP and academic achievement in the 4th, 7th and 10th grades using registry data collected at birth, during the neonatal period, and at each grade level from the 2000, LIFECOURSE study birth cohort in Reykjavik, Iceland (N = 1151, girls = 49.3%). Latent growth modeling showed that MSDP influenced Icelandic achievement scores, standardized to a range from 0 to 60, at baseline (β = −0.04), and over time (β = −0.05). Likewise, MSDP was negatively associated with standardized mathematics scores at baseline (ß = −0.09) and continued to exert a negative impact on mathematics scores over time (ß = −0.08) after controlling for gender, income, cohabitation, and baseline mathematics and Icelandic achievement scores. Results provide evidence of the persistent negative impact of MSDP on academic achievement in offspring. Findings support the proposition that children whose mothers smoke during the first trimester of pregnancy are, on average, at greater risk for poor scholastic outcomes over time than children whose mothers do not smoke during their first trimester. To our knowledge, this is the first study using a longitudinal cohort design to assess whether the impacts of maternal smoking during pregnancy may persist over time. This study contributes to the current state of knowledge by providing an assessment that focuses on the impact of smoking during pregnancy on academic achievement from childhood into early adolescence.
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The Impact of Choice on Exercise Motivation and Physical Activity in College Students
(2017) Tracy, JF.; Taliaferro, A.; Kristjansson, AL; Department of Psychology
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Negative Life events, Identity, and Life Satisfaction in Adolescents : International Society for Research on Identity
(2017) Balducci, K.; Davison, K.; Smith, M. L.; Mann, M. J.; Kristjansson, A. L.; Department of Psychology

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