Mainstreaming Biodiversity into Renewable Power Infrastructure

4. Mainstreaming biodiversity into low-emissions pathways and power sector planning

Abstract

This chapter examines opportunities, good practices and tools for mainstreaming biodiversity into low-emissions pathways and power system planning. It discusses the importance of low-energy demand pathways, accounting for biodiversity in decisions on electricity generation portfolios and strategically siting renewable power infrastructure. The chapter also discusses the role of institutional and cross-border co-ordination in safeguarding biodiversity while scaling up renewable power.

Since the adoption of the Paris Agreement, national governments have set emission reduction targets in their Nationally Determined Contributions (NDCs). Increasingly, countries are also developing long-term low greenhouse gas emission development strategies (LT-LEDS). Decarbonising energy use through electrification and the expansion of low-emissions electricity generation (particularly from renewable sources) is an important part of governments’ NDCs and LT-LEDS. In parallel, governments are pursuing the objective of affordable and reliable energy provision for all, which is the focus of Sustainable Development Goal 7.

Planning for the transition to low-emissions electricity involves setting targets, developing strategies and adopting policies that guide investment in the energy sector. It is often informed by analysis of modelling-based energy scenarios, which illustrate potential pathways for meeting future energy demand and achieving emission reduction targets. Long-term planning is necessary to ensure investments are consistent with the Paris Agreement temperature goals and other long-term policy objectives. As infrastructure is long-lived, decisions made today on energy infrastructure investment have implications for future decades. Long-term plans, such as LT-LEDS, help to orientate mid-term planning (e.g., multi-annual energy programmes, ten-year electricity network plans; ten-year integrated national energy and climate plans; spatial plans), and short-term planning (i.e., decisions dealing with immediate priorities and actions, such as project siting).

As governments plan the low emissions transition, they have an opportunity to design power systems that deliver better outcomes for both climate and biodiversity. Capitalising on this opportunity requires a systemic and integrated approach to electricity planning in which climate, energy and biodiversity (and other societal goals) are considered together from the earliest stages of planning. Such an approach is vital if governments are to achieve their national biodiversity objectives and international commitments, for example, under the Convention on Biological Diversity’s Kunming-Montreal Global Biodiversity Framework and the Convention on Migratory Species, as well as the goals of the Paris Agreement and the 2030 Agenda for Sustainable Development (Annex A).

Three key questions confront governments as they plan the transition to low-emissions electricity systems: How much electricity generation capacity is required over time (i.e., electricity demand)? What is the appropriate technology mix to meet this demand? Where should this infrastructure be sited? The response to each of these questions has implications for biodiversity. Yet, the extent to which biodiversity is considered when addressing these questions remains limited. Failure to account for biodiversity in the design and appraisal of energy policies, plans and programmes could lead to governments pursuing unsustainable pathways.

This chapter examines each of these questions in turn, discussing their implications for biodiversity. While the three questions are discussed individually, they are interdependent. For example, changes to energy demand or siting constraints can alter the optimum balance of different renewable power technologies (Wu et al., 2019[1]). The chapter then presents decision support tools that planners and policy makers can use to strengthen biodiversity considerations in decision making. Finally, it discusses the role of institutional co-ordination and cross-border collaboration in delivering a biodiversity-aligned transition to low-emissions electricity systems.

4.1. Biodiversity and energy demand

Electrification coupled with expansion in renewable power is necessary to transition away from fossil fuel-based economies (see Chapter 2). Electricity demand will and must increase. However, the extent of electricity demand growth will depend in part on overall energy demand, which in turn, depends on societal choices and how end-use sectors are designed. How much energy is required will influence the spatial footprint of power systems in the coming decades, thereby determining the extent of competition for land and the risks to biodiversity. A study of France’s potential low-carbon energy pathways for 2050, for example, found that mineral resource requirements would be reduced by approximately 20% in a sufficiency (low-demand) scenario1 compared to a reference scenario,2 including a 30 million tonne decline for the electrical system and 10 million tonne decline in material for batteries, which could reduce mining pressure on biodiversity (RTE, 2022[2]).

The value of adopting low-emission development pathways based on low-energy (and material) demand is clear. Low-energy demand scenarios can benefit multiple SDGs, including those on biodiversity (SDGs 14 and 15) (Grubler et al., 2018[3]), while pathways that do not have an absolute reduction in energy consumption are likely to make sustainable land management impossible (Tran and Egermann, 2022[4]). The sixth assessment report (AR6) of the Intergovernmental Panel on Climate Change (IPCC, 2022[5]) examines mitigation pathways and land-use implications (Box 4.1). It states that “many challenges, such as dependence on CDR [carbon dioxide removal], pressure on land and biodiversity (e.g., bioenergy) […] are significantly reduced in modelled pathways that assume using resources more efficiently (e.g., IMP-LD) or that shift global development towards sustainability (e.g., IMP-SP) (high confidence)”. Further, the report underscores that “[d]ecent living standards, which encompasses many SDG dimensions, are achievable at lower energy use than previously thought (high confidence).”

Box 4.1. IPCC’s sixth assessment report (AR6), mitigation pathways and land-use implications

The AR6 presents five Illustrative Mitigation Pathways (IPCC, 2022[6]). Three of these have >50% likelihood of limiting warming to 1.5°C with no or limited overshoot: IMP-REN, which places greater emphasis on renewables, IMP-LD, which emphasises efficient resource use and shifts in consumption patterns leading to low resource demand, and IMP-SP, which emphasises shifting global pathways to sustainable development, including by reducing inequality. All three of these pathways are characterised by steep early reductions in emissions and a relatively small contribution of net negative emissions, thereby reducing reliance on bioenergy with carbon capture and storage (BECCs), which is land-use intensive and associated with high risks to biodiversity. An emphasis on demand reduction, as illustrated in IM-LD could reduce the need for renewable power infrastructure compared to IMP-REN, while still achieving the 1.5°C goal.

Source: (IPCC, 2022[5]), Climate Change 2022: Mitigation of Climate Change. Working Group III contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; (Hof et al., 2018[6]), Bioenergy cropland expansion may offset positive effects of climate change mitigation for global vertebrate diversity, 10.1073/pnas.1807745115; (Smith et al., 2019[7]), Land-Management Options for Greenhouse Gas Removal and Their Impacts on Ecosystem Services and the Sustainable Development Goals 10.1146/annurev-environ-101718-033129; (Creutzig et al., 2021[8]), Considering sustainability thresholds for BECCS in IPCC and biodiversity assessments, 10.1111/gcbb.12798.

Pursuing pathways with low energy and material demand will require countries to fully leverage a range of demand-side mitigation measures to improve energy efficiency and change consumer behaviour (IEA, 2021[9]; Creutzig et al., 2021[10]). Technological strategies and innovations are critical but may be insufficient; accompanying social innovations and strategies that address cultures, institutions and practices of energy use and supply are also needed (Tran and Egermann, 2022[4]). Adopting a systems approach (Box 4.2) to development planning could help countries reduce energy demand in end-use systems (e.g. transport and agriculture), thereby delivering climate and other well-being outcomes such as biodiversity (OECD, 2019[11]; OECD, 2021[12]).

Box 4.2. Systems innovation for net zero

Systems innovation for net-zero is a process which allows governments to think innovatively and design climate strategies with the potential to accelerate climate change mitigation while improving wider well-being outcomes. Building on systems thinking, the process unleashes emission reduction opportunities through policies targeted at redesigning systems, often absent or at the margin of current climate strategies. By defining outcomes in terms of well-being (e.g., biodiversity, health, affordability, equity) and making these outcomes central criteria guiding systems’ redesign, it mainstreams well-being considerations into the decision-making process of climate strategies from the onset.

Climate action could be more efficient and effective if focused on systems as a whole, so that – by design – end-use systems require less energy and materials, and emit less greenhouse gases, while achieving wider well-being outcomes, such as improving our health and safety, and subsequently better lives. OECD work on the transport sector, for example, identified three vicious cycles in the transport system design that fostered growing car use, and thus led to an energy-intensive transport system. These cycles (induced car demand, urban sprawl and the sustainable modes low-quality trap) are key drivers of car dependency, high energy demand and emissions, as well as other undesirable results (e.g., unequal access to opportunities, poor air quality and limited physical activity). Examples of policies and actions that can reverse these dynamics and reduce the demand of energy-intensive transport modes include wide-scale reallocation and redesign of streets, such as in the case of superblocks; rethinking urban regeneration and new development through the 15' city framework; and mainstreaming on-demand shared services to complement public transport.

Current climate strategies for the transport sector place today an overriding focus on vehicle electrification, leaving car dependency and high energy demand unaddressed. From a well-being lens, electrification of vehicles will be key, but its potential to achieve net-zero goals and contribute to wider well-being objectives will only be fulfilled if vehicle technology improvements are embedded in a wider process of systemic redesign that addresses issues such as car-dependency.

Source: (OECD, 2021[12]), Transport Strategies for Net-Zero Systems by Design, OECD Publishing, Paris, https://doi.org/10.1787/0a20f779-en.

4.2. Biodiversity and electricity generation portfolios

Different combinations of renewable power and flexibility technologies (e.g., batteries) may be consistent with the low-emissions electricity transition. However, the choice of technologies will partly determine the biodiversity footprint of transitioning to low-emissions electricity (Luderer et al., 2019[13]). Land and sea-use demands from renewables vary due to the distribution of energy resources, differing power densities of energy technologies and grid infrastructure requirements, among other things. For example, bioenergy is the most land-use intensive of all electricity sources requiring more space per megawatt/hour (MWh) than solar or wind (Lovering et al., 2022[14]). Wind and solar power are more land-use efficient but scaling up these technologies may demand more electricity transmission and energy storage infrastructure. Additionally, some technologies more profoundly impact the species and ecosystems where they are deployed. For example, traditional hydropower schemes tend to be relatively destructive to both terrestrial and freshwater ecosystems (Nilsson et al., 2005[15]; Pörtner et al., 2021[16]). The impact of a given technology mix will differ across countries, according to various factors such as the overlap between energy resources and ecologically important or sensitive areas.

A key challenge for electricity planners and regulators is to identify and deliver the optimal capacity expansion of different electricity generation technologies. Decisions on which electricity generation technologies to invest in, and when, are informed by energy models (e.g., capacity expansion models). These models are developed based on assumptions of demand, technology costs and performance, resource availability and climate regulations (van Ouwerkerk et al., 2022[17]; Wu et al., 2019[1]). The risks to nature and associated costs to society (other than through a climate lens) tend not to be considered.

A major limitation of most capacity expansion modelling is that they are spatially coarse (or aspatial). They therefore do not provide the necessary level of detail to account for potential conflicts between renewable power projects and biodiversity or other environmental, cultural and social constraints. This can create a disconnect between long-term planning and the deployment of renewable power projects (Wu et al., 2019[1]). Long-term planning that does not account for biodiversity impacts and spatial constraints could increase the risk of land-use conflicts, undermining renewable power projects and threatening biodiversity.

To better account for biodiversity in long-term planning, power sector modally could integrate spatially explicit data on biodiversity. For example, scenarios for electricity expansion could be developed that vary constraints on land/sea availability for electricity infrastructure based on the location of areas important for biodiversity protection. This would enable planners to identify power or broader energy sector scenarios that best minimise costs while reducing emissions and protecting biodiversity (Box 4.3). While progress has been made in power sector modelling to better reflect siting constraints and provide more spatially specific outputs (Mai et al., 2021[18]), most studies are limited in scope (geography and/or technologies considered) or do not consider habitat loss.

Another key entry point for biodiversity is the appraisal of different technology options or scenarios for capacity expansion. Decision makers could apply strategic environmental assessments (see SEA section, Chapter 5) to evaluate the cumulative environmental effects of different scenarios. They could also integrate biodiversity criteria and proxies such as land-use intensity of energy (Lovering et al., 2022[14]) into cost-benefit analysis and multi-criteria analyses to identify optimal portfolios (see 4.2).

What constitutes an optimal portfolio depends on a variety of environmental, geographic, social and economic factors. Some jurisdictions may have greater opportunities for siting low-risk renewable power infrastructure. For example, in a scenario with high rooftop solar (an additional 9GW compared to the baseline 2050 forecast), utility-scale capacity build-out to meet California’s energy demand could be reduced by 3-6%, which is the equivalent of 200 – 445 km² (see 4.4). However, the potential role for rooftop solar varies depending on rooftop availability (e.g., heritage regulations have prevented rooftop solar expansion in some areas), geographical or climatic factors and overall consumption. Estimates indicate that as little as 0.3-1% of Finland’s total electricity demand could be met by rooftop PV compared to 5.2-17.4% in Australia and 27.8-92.7% in Indonesia (Capellán-Pérez, de Castro and Arto, 2017[19]).

The potential for conflict across renewable energy and biodiversity targets will be more pronounced in some countries or regions, due to their greater biodiversity and the overlap of areas of high energy resource potential with biodiversity. For example, Central America has a relatively higher overlap of renewable power resources with biodiversity compared to other regions: an estimated 77% of wind energy potential and 75% of solar energy potential is concentrated within the most biodiversity areas, many of which are unprotected (Santangeli et al., 2015[20]). While conflicts can be reduced by integrating biodiversity into capacity expansion scenarios, significant trade-offs may persist. These trade-offs could be partly addressed in later stages of planning and project development, for example by avoiding impacts through project (micro-)siting decisions, minimising impacts through physical controls, restoring project sites and offsetting residual impacts.

Box 4.3. Assessing the biodiversity impact of energy portfolios

Power of Place: Land Conservation and Clean Energy Pathways for California

The Power of Place study developed a planning framework integrating spatially-explicit biodiversity data with an electricity sector capacity expansion model to assess how siting constraints to avoid impacts on natural and working lands in the Western United States could affect technology choices, generation and transmission capacity, system costs, and environmental impacts of pathways that achieve climate targets. The study developed sixty-one scenarios consistent with an 80% reduction in greenhouse gas (GHG) emissions in 2050 compared to 1990. From the scenarios it was concluded that the balance between wind, solar PV, and storage capacity – and the resultant costs – are sensitive to land protections and whether California has access to renewable power from other western states. Applying land protections effectively avoid environmental impacts while achieving GHG targets but can increase system costs (this does not account for avoided costs of cancelled/delayed projects resulting from conflict with biodiversity in scenarios without land protections). The higher costs can be more than offset by allowing access to out-of-state wind and solar resources. In other words, California can reduce costs and improve conservation outcomes by pursuing regional renewable resource development and trade. However, this approach requires significantly more transmission infrastructure and can have greater land use impacts under scenarios with lower levels of environmental protection.

Low to medium ecological risk energy portfolios in the UK

An analysis of potential UK energy portfolios using the DECC 2050 Calculator3 demonstrated how climate targets could be met with low to medium ecological risk, by excluding high-ecological-risk technologies and carefully siting medium-ecological-risk technologies. The study excluded energy technologies judged to have high risk (e.g., new large-scale hydropower schemes and certain tidal range technologies) and focused instead on what the authors considered to be medium-risk technologies (onshore wind, bioenergy, solar PV, offshore wind, wave power and tidal stream). The analysis evaluated the technical opportunity for each medium-risk technologies, and the physical, policy and ecological constraints limiting their deployment. Technology-specific ecological sensitivity maps were developed based on available information and inferences about the impacts of each technology. This allowed a comparison of the overlap of potential areas for the deployment of specific renewable energy technologies with species or habitats that they may negatively impact. The study identified a low ecological risk scenario for the medium-risk technologies that excludes areas of both high and medium ecological sensitivity from the areas remaining after the various constraints had been applied. The study also identified a medium ecological risk scenario that excludes only areas of high ecological sensitivity from the remaining eligible areas.

Source: (Gove et al., 2016[21]), Reconciling Biodiversity Conservation and Widespread Deployment of Renewable Energy Technologies in the UK, 10.1371/journal.pone.0150956; (Wu et al., 2019[1]), Power of Place Land Conservation and Clean Energy Pathways for California,

As renewable power generation and storage technologies with relatively lower ecological risk become increasingly cost-competitive, countries can reduce their dependence on more harmful forms of electricity generation – fossil fuels but also more harmful forms of low-emission electricity generation. For example, investment in wind, solar and batteries is reducing the need for new hydropower schemes, thereby avoiding negative impacts on rivers4 and the fragmentation of tens to hundreds of thousands of kilometres of free-flowing rivers globally (Opperman et al., 2019[22]). Hydropower will continue to play an important role in low-emissions electricity pathways for some countries. However, due to wind and solar energy expansion, the focus can shift from traditional dams with significant biodiversity impacts to lower impact schemes that provide storage capability and flexibility to facilitate the integration of variable renewable energies (e.g. strategically-sited off-channel pumped storage) (Opperman et al., 2019[22]; Moran et al., 2018[23]).

Supporting new electricity generation and storage technologies through to full commercialisation may facilitate low-ecological-impact expansion of the electricity system. Increasing the diversity of technologies available for generating low-emissions electricity could provide greater siting flexibility, allowing for areas of low ecological sensitivity to be exploited, while also helping to address concerns with energy variability (McManamay, Vernon and Jager, 2021[24]). For example, the recent development of large offshore floating wind turbines may reduce pressure on terrestrial and coastal ecosystems and provide an opportunity to harness substantial energy resources in areas of low ecological risk. Wave power and tidal stream technologies have not yet been fully commercialised but could also offer an opportunity for low-ecological risk electricity generation (although their ecological impacts will require careful assessment and monitoring, and siting will remain critical).

Additionally, continued investment to refine existing technologies is important for reducing the impact of the power sector on biodiversity. For example, technological developments that improve the power density or efficiency of commercialised technologies such as solar and wind may help reduce their overall spatial requirements. Changes to their design could reduce impacts associated with their construction and operation (e.g., bird-safe power lines designs to reduce electrocution risk, see Chapter 3), or reduce upstream impacts associated with mining for construction materials by improving material efficiency or finding alternative materials (see also Box 5.1, Chapter 5).

Technology development makes it possible to repower old existing solar and wind power facilities to increase their efficiency and capacity. Repowering can increase electricity generation without the downstream5 land-use/sea-use change associated with new projects. Additionally, it may provide an opportunity to redesign facilities so that they are more biodiversity-friendly (e.g., by removing or re-siting wind turbines if they pose a relatively high collision risk for birds and bats, creating ecological corridors throughout solar farms).

4.3. Biodiversity and the location of electricity infrastructure

Various factors inform siting decisions, such as energy resource availability, technical feasibility for construction, connection to electricity grids, distance from settlements and environmental issues. As the potential impacts of renewable power on biodiversity are largely location-specific (see Chapter 3), decisions on where to deploy renewable power infrastructure are a critical entry point for mainstreaming biodiversity into energy planning. Explicit integration of biodiversity into siting decisions is fundamental for avoiding impacts on biodiversity, which is the first step of the mitigation hierarchy – an important tool to guide planning and projects (Box 4.4).

Key biodiversity factors to consider regarding the location of renewable power infrastructure include the location of areas legally established as sites of international, national, regional or local priority for biodiversity (e.g. Protected Areas; Natura 2000 sites in Europe; World Heritage sites); other areas identified as important for biodiversity through conservation planning prioritisation tools (e.g. Key Biodiversity Areas, Important Marine Mammal Areas, Wilderness Areas), the distribution of rare or threatened species and habitats, and migratory routes of birds, bats and other mammals.

Box 4.4. The Mitigation Hierarchy

The mitigation hierarchy provides a structured approach to development planning and the implementation of infrastructure projects with the aim of limiting the negative impacts on biodiversity. Implementation of the hierarchy is vital for achieving goals of no net loss of biodiversity or net biodiversity gain. The mitigation hierarchy involves four sequential and iterative steps. These are outlined below together with examples specific to renewable power:

1. Avoidance: Avoidance tends to be the most effective and least expensive way of reducing potential negative impacts on biodiversity. It requires biodiversity to be considered in the earliest stages of planning. Avoidance measures include, for example, careful siting of renewable power infrastructure to avoid important areas for biodiversity such as key biodiversity areas and migratory routes; or constructing infrastructure outside breeding seasons to avoid disturbance.

2. Minimisation: Minimisation measures reduce the duration, intensity and extent of impacts that cannot be completely avoided. It includes physical controls (e.g., bird flight diverters on power lines), operational (e.g., shut-down of wind turbines during migration) and abatement controls (e.g., technologies to reduce pile-driving noise for offshore wind).

3. Onsite rehabilitation/restoration: Impacts that cannot be completely avoided or minimised can be partly addressed through rehabilitation or restoration. Rehabilitation aims to return basic ecological functions and ecosystem services. Restoration aims to return an area to its original state.

4. Offset: Residual impacts may occur even after full implementation of the previous three steps. Offsetting aims to compensate for any residual adverse impacts through actions taken elsewhere to achieve positive biodiversity outcomes for the species or habitats affected by the development project. Through effectively designed offsets, developers could deliver no net loss or net gains in biodiversity.

Figure 4.1. Mitigation hierarchy

Source: Text based on (OECD, 2016[25]), Biodiversity Offsets: Effective Design and Implementation and (Bennun et al., 2021[26]), Mitigating biodiversity impacts associated with solar and wind energy development: guidelines for project developers. Figure adapted from (Rio Tinto, 2012[27]), “Rio Tinto and biodiversity: Working towards net positive impact”, www.riotinto.com/documents/Rio_Tinto_and_biodiversity.pdf.

While some overlap between renewable power and areas of conservation importance is likely in the future, significant opportunities exist to deploy renewable power in areas of low-ecological risk (Dunnett et al., 2022[28]). Low-risk siting strategies include integrating electricity generation technologies and power lines with existing infrastructure (e.g. solar rooftops; for further discussion see 4.3.1) and deploying ground-mounted facilities in converted lands, as these tend to be lower in biodiversity than unconverted lands (Newbold et al., 2015[29]). Globally, sufficient converted land with renewable energy resource potential exists to deliver 17 times the required renewable energy to meet the combined emission reduction targets of the NDCs submitted by May 2016 (Baruch-Mordo et al., 2019[30]). In addition to avoiding and minimising biodiversity impacts, deploying renewable power infrastructure on converted lands may provide opportunities to deliver net gains for biodiversity if renewable power companies restore biodiversity on their facilities.

Brownfield sites are an example of converted land that may hold promise for low-impact siting. For example, a study of renewable power potential in West Virginia found more than 100 000 acres (>4 000 hectares) of former mine lands and other brownfields that were suitable for solar energy development. Many of these sites have existing infrastructure (e.g. road and power lines) and are close to energy markets, reducing the need for additional infrastructure expansion (James and Hansen, 2017[31]). A study of energy potential in low-ecological risk areas in Nevada concluded that developing solar on former minefields and brownfields could power 3.8 million homes (TNC, 2020[32]).

While targeting converted, unproductive land for renewable power development can reduce trade-offs between renewable power and biodiversity objectives, such areas may still have important biodiversity values that could be threatened by renewable power development. For example, in parts of Europe marginal agricultural lands provide critical habitats (Halada et al., 2011[33]). Deploying solar panels could negatively impact these habitats if it entails vegetation clearance or changes to the low-intensity agricultural practices shaping these habitats. Co-location of low-intensity agriculture with renewables could be one potential strategy for managing such cases (see 4.3.1). Similarly, some brownfield sites (e.g., old land-fill sites) support unique, relatively undisturbed ecological communities and contribute to landscape-level biodiversity (Macgregor et al., 2022[34]). Site evaluation and careful construction and operation therefore remains important for anticipating and addressing biodiversity impacts and other challenges (e.g. release of landfill gases if solar is developed on old landfill sites (AXA XL, 2022[35])).

Harnessing opportunities to develop renewable power on converted lands could require changes to land-use planning regulations and spatial plans. For example, to facilitate deployment of solar energy on former mine lands, the Administrative Code of Nevada was updated to explicitly list “renewable energy development and storage” as an acceptable post-production use for shuttered mining operations (Bream, 2018[36]). Deployment in degraded lands can also be encouraged through incentives (e.g., integration of biodiversity criteria into power procurement – see Chapter 5).

4.3.1. Multi-use spaces: co-locating renewable power with other activities

Opportunities exist to develop multi-use spaces or co-locate renewable power infrastructure. For example, renewable power infrastructure can be co-located with other power infrastructure (e.g., wind and solar; wind and storage), with other complementary infrastructure (e.g., roads, carparks, buildings) and economic activities (e.g., agriculture, aquaculture, forestry), and with biodiversity protection and restoration activities. Co-location can be an effective strategy for minimising land-use change (and therefore biodiversity risks) associated with renewable power expansion, while also harnessing synergies across different social, economic and environmental objectives.

Co-location of power infrastructure (e.g., wind turbines, solar PV/CSP, storage) is increasing across the globe, and considerable scope exists for further expansion. For example, the technical capacity of wind energy facilities in place in Australia to accommodate co-located solar farms was over 1 gigawatt (GW) in 2016, and further opportunities are emerging as renewable power expands (AECOM, 2016[37]). In India, at least 110 GW of wind and 360 GW of solar PV could be co-located, meeting 35% of India’s electricity demand in 2030 (Deshmukh et al., 2019[38]). In addition to reducing land-use pressure, co-locating solar and wind power (or storage) can help smooth electricity generation (European Commission, 2020[39]). It can also provide private benefits. For example, it is estimated that co-location of solar and wind power in Australia could drive cost efficiencies of 3%-13% for capital expenditure and 3%-16% for operating expenditure, by amalgamating grid connections, development costs (e.g. ecological assessments) and equipment installation, among other things (AECOM, 2016[37]).

A second form of co-location is siting renewable power infrastructure with other infrastructure or economic activities. As mentioned above, one of the most effective approaches for avoiding biodiversity impacts from renewable power expansion is to integrate solar panels into the built environment. Rooftop solar is a well-known example, but solar panels are also starting to be integrated into other infrastructure such as parking lots and noise barriers along motorways (Rijkswaterstaat, 2020[40]). Such integrated approaches with solar panels deployed close to their end-use can also help reduce power losses associated with electricity transmission and distribution (van de Ven et al., 2021[41]).

For ground-mounted solar energy facilities, co-location depends on utilising the space below solar arrays or separating a plot of land into different uses (e.g. solar arrays could be deployed in the non-irrigated corners of centre-pivot irrigation plots) (Hassanpour Adeh, Selker and Higgins, 2018[42]). Co-location of solar energy and agriculture (agrivoltaics) is gaining increasing interest. Solar energy has been co-located with crops, small fruit trees, and small to medium-sized livestock.

Agrivoltaics have the potential to provide multiple additive and synergistic benefits. The main benefit for biodiversity arises from reduced land-use pressure (Amaducci, Yin and Colauzzi, 2018[43]). Other benefits include a diversified income stream for landowners, reduced plant drought stress, greater food production, increased PV panel efficiency due to cooling effect of vegetation under solar panels and reduced mowing requirements (Barron-Gafford et al., 2019[44]; Adeh et al., 2019[45]; Hassanpour Adeh, Selker and Higgins, 2018[42]). Locating solar on existing agricultural land may also increase community support, thereby facilitating permitting of renewable power projects (Pascaris et al., 2022[46]). Opportunities also exist to co-locate floating solar PV with aquaculture (Pringle, Handler and Pearce, 2017[47]).

Wind energy facilities often extend over large areas, due to the spacing requirements of turbines (see Chapter 3). However, only a small fraction of this area is occupied by infrastructure (turbine foundations, substation, access roads etc). The remaining space can be used for other activities. Onshore wind energy facilities, for example, are often combined with agriculture (crop and livestock systems) and increasingly forestry6 (European Commission, 2020[39]). They may also be compatible with transport networks, industrial activities and public utility networks (RTE, 2022[2]).

A third form of co-location is combining biodiversity protection or restoration with renewable power. The deployment of renewable power infrastructure, whilst itself having potentially negative impacts on biodiversity, may reduce other pressures at the site. This could provide opportunities to combine energy generation with targeted restoration or protection measures. For example, recent studies demonstrate that through careful design, combining restoration activities and transmission infrastructure can increase biodiversity and provide a corridor for species to move across the landscape (e.g. to different foraging or breeding sites) (Ferrer et al., 2020[48]). Through strategic planting, restoration and maintenance, land-based solar PV facilities on degraded land could support pollinators, with potential spillover benefits for wild plants off-site and for agricultural crops (Hoffacker, Allen and Hernandez, 2017[49]; Randle-Boggis et al., 2020[50]; Blaydes et al., 2021[51]; Semeraro et al., 2018[52]; Sinha et al., 2018[53]; Dolezal, Torres and O’Neal, 2021[54]). Floating PVs could be designed to benefit aquatic plants and the fish that depend on them for shelter and food (de Rijk et al., 2021[55]).

In Europe, initiatives are underway to pilot artificial reefs at offshore wind farms, which are designed to support blue mussels, cephalopods, and flat oyster restoration (WaterProof Marine Consultancy and Services, 2020[56]; Didderen, Bergsma and Kamermans, n.d.[57]). To promote and guide efforts to co-locate wind energy, biodiversity restoration and food production, the Dutch Ministry of Agriculture, Nature and Food Quality commissioned guidelines on “Nature-Inclusive Design: A catalogue for offshore wind infrastructure” (Prusina et al., 2020[58]). The Nature and Environment Foundation (Stichting Natuur & Milieu) and North Sea Foundation (Stichting De Noordzee) commissioned a report on “Options for biodiversity enhancement in offshore wind farms Knowledge base for the implementation of the Rich North Sea Programme” (Waardenburg, 2020[59]).

Box 4.5. Co-locating solar and agriculture

Innovative Solar Practices Integrated with Rural Economies and Ecosystems (InSPIRE)

The U.S. Department of Energy’s InSPIRE project brings together industry, academia and national laboratories to examine solar energy and environmental synergies across four core research areas: 1) Low-impact site preparation practices for ground mounted solar projects; 2) Improved compensatory mitigation planning; 3) Siting solar projects on contaminated and marginal lands; 4) Co-locating solar projects on agricultural lands for mutual benefits. The InSPIRE project combines innovative computational studies with field-based research to provide data to landowners, the solar industry and state decision-makers. It analyses native vegetation growth underneath and around ground-mounted solar installations; agricultural crop performance under innovative solar configurations; impacts of low-impact solar development approaches on soil quality, carbon storage, storm water management, microclimate conditions, and solar efficiencies; and benefits of pollinator-friendly solar on local agricultural yields.

Source: (Dreves, 2019[60]), Beneath Solar Panels, the Seeds of Opportunity Sprout; (DOE, 2022[61]), InSPIRE.

The viability and sustainability of co-location is context-specific (Ravi et al., 2016[62]). For example, establishing artificial reefs may be appropriate in locations where similar habitats once existed but have since been lost or degraded (e.g., from dredging), but inappropriate in areas where seagrass is the natural habitat. Furthermore, co-location can entail risks and trade-offs (AECOM, 2016[37]; Blyth-Skyrme, 2011[63]; Macknick, Beatty and Hill, 2013[64]), which will be important to understand and consider. For example, one risk of establishing artificial reefs at turbine foundations of offshore wind facilities is that invasive alien species benefit at the expense of local species (Degraer et al., 2020[65]). Combining renewable power generation and agriculture could in theory reduce the productivity of one or both activities relative to a single use siting approach, leading to partial displacement of these activities with potential biodiversity impacts (see indirect impacts in Chapter 3). Ongoing efforts to build the scientific and economic case for co-location, including through laboratory studies, pilot tests and monitoring, will be valuable for deepening the understanding of potential benefits and trade-offs of co-location in different contexts.

To capitalise on the potential benefits of co-locating activities, it may be necessary to adapt spatial planning, sectoral policy and infrastructure design. For example, the co-location of passive gear fishing with offshore wind farms may require, among other things, a definition of the legal basis, implementation of safety regulations and delineation of minimum requirements for fishing vessels (Stelzenmüller et al., 2016[66]). Co-locating solar energy in agricultural land may require designing elevated solar modules to optimise space for grazing or crop growing (RTE, 2022[2]). Effective implementation of co-location approaches will also benefit from the active engagement of local communities, economic interests and environmental experts (Schupp et al., 2021[67]), for example, by establishing communities of practice (Steins et al., 2021[68]).

4.3.2. Spatial planning and renewable energy zones

Well-designed and implemented spatial planning can facilitate a biodiversity-aligned transition to low emissions electricity systems. The importance of spatial planning in reconciling various demands on land and sea resources, including renewable power and biodiversity protection, is widely accepted. However, the extent and effectiveness to which spatial plans have been applied varies considerably across countries. Not all countries explicitly address biodiversity in their plans (Tucker, Quétier and Wende, 2020[69]). Good practice for spatial planning calls for an ecosystem approach7 and a multi-sector strategy that balances and achieves environmental, economic and social objectives.

Governments can develop or adapt spatial plans to identify and prescribe appropriate locations for the development of renewable power infrastructure. Integrating biodiversity considerations into the spatial planning process could help avoid some of the significant adverse impacts of renewable power projects on biodiversity. For example, spatial planning could identify areas as low ecological risk, medium ecological risk or high ecological risk for renewable power development (European Commission, 2020[39]), drawing on tools such as sensitivity maps (see 4.4.1). This could then inform whether or under what conditions renewable power development should take place. Governments could exclude renewable power infrastructure from areas identified as critical for biodiversity or particularly vulnerable to renewable power developments. Alternatively, they could require projects in these areas to undertake more rigorous environmental assessments, mitigation measures and monitoring. Conversely, environmental permitting requirements could be less onerous at low-ecological risk sites.

In addition to steering development away from high-ecological-risk areas to low-ecological risk areas, renewable energy zones could deliver climate, energy and economic benefits. This is because the identification of low-risk areas for development may enable faster expansion of renewable energy with reduced project approval times and costs (see 5.1.1), while offering increased certainty and a level playing field for developers. For example, the U.S. Bureau of Land Management pre-approved low-ecological-risk renewable energy zones for solar energy development as part of the Department of the Interior’s Western Solar Plan. Several large-scale solar projects were subsequently approved at these sites within 10 months, which is less than half the time that was usually required (US DOI, 2015[70]).

Spatial plans for renewable energy development can be developed at national, subnational and landscape level (see Box 4.6), and are applied in developed and developing countries (McKenney, 2020[71]). For example, EU Member States are required by EU Article 15(7) of the revised Renewable Energy Directive (2018/2001) to carry out an assessment of potential renewable energy sources and “where appropriate, include spatial analysis of areas suitable for low-ecological-risk deployment”. In France, the national government asked regions to map areas favourable to wind energy development to help reach the objectives of the national multiannual energy programme, whilst accounting for biodiversity, landscape and human activity considerations. More than 35 biodiversity issues were considered in the mapping, which was carried out by elected representatives in the Regions, municipalities and the inter-municipalities and key stakeholders, such as environmental organisations. The regional mapping exercise is helping to inform a national map of appropriate sites (France, 2022[72]).

In the US, a process has been established for proactively identifying renewable energy zones (REZ) and planning the expansion of transmission infrastructure to connect these areas to the power grid. A REZ is defined in the US as an area that has high-quality renewable energy resources, suitable topography and land-use designations, and demonstrated interest from developers (Lee, Flores-Espino and Hurlbut, 2017[73]). Data on species, habitats, migratory routes and protected areas can be factored in when identifying a REZ (McKenney, 2020[71]). An Energy Zones Mapping Tool funded by the U.S. Department of Energy enables users to select from over 300 Geographic Information System data layers, including many related to biodiversity, to inform the REZ planning process. Several other countries, including India and 21 African nations have adopted similar approaches, many with the support of the United States Agency for International Development (USAID) (McKenney, 2020[71]).

Box 4.6. Planning for renewables and biodiversity at a landscape level: The Desert Conservation Plan

The Desert Renewable Energy Conservation Plan (DRECP) is a landscape-level plan for the development of utility-scale renewable power generation and transmission infrastructure in the deserts of Southern California. The plan covers 22.5 million acres (c. 9 million hectares) across seven counties. Its three objectives are to: i) advance federal and state national resource conservation goals and other management goals; ii) meet federal Endangered Species Act (ESA) and Federal Land Policy and Management Act (FLPMA) requirements; and iii) facilitate the timely and streamlined permitting of renewable power projects.

The plan was developed through a cross-sectoral collaboration of both federal and state agencies, together referred to as the Renewable Energy Action Team Agencies (REAT). REAT includes the Bureau of Land Management (BLM), U.S. Fish and Wildlife Service (USFWS), California Energy Commission (CEC), and California Department of Fish and Wildlife (CDFW). The planning process also involved consultation with other federal and state agencies, local agencies, tribal governments, private utilities and renewable energy proponents, and the public (citizens and not-for-profits). Furthermore, the DRECP was subject to a Programmatic Environmental Impact Assessment.

The DRCEP has three core components: i) a federal “general conservation plan” under the ESA, ii) a California “natural communities conservation plan”, under California’s Natural Communities Conservation Plan Act, and iii) a “Bureau of Land Management Land Use Plan Amendment (LUPA)”, under the FLPMA. Central to this process, was the identification of locations most compatible with renewable energy development, understood to be areas with high renewable energy resource potential, close to existing or planned transmission and with relatively low biodiversity value.

The LUPA allows more than 800 000 acres (c. 324 000 ha) of land to be developed for renewable energy. Of this, 388 000 acres (157 000 ha) are designated as Development Focus Areas (DFAs), which are areas with substantial energy generation potential, access to existing or planned transmission, and low resource conflicts. Conservation and Management Actions were developed to provide certainty to help streamline and incentivise utility-scale renewable energy generation in DFAs. Approximately 40 000 acres (c. 16 000 ha) have been designated as Variance Process Lands (VPLs), where renewable energy development could be considered and approved without a plan amendment. Additionally, renewable energy could be developed in the 419 000 acres (c. 170 000 ha) of General Public Lands and 35 000 acres (c. 14 000 ha) of Extensive Recreation Management Areas (ERMAs) (not overlaid by a conservation allocation), but a plan amendment would be necessary as part of project review and approval. The LUPA identifies approximately 3 956 000 acres (c. 1 600 000 ha) of California Desert National Conservation Lands and allocates 6 527 000 acres (c. 2 641 000 ha) of total conservation designations for biological, cultural, and other natural resource protection and outlines managements actions for these areas.

Source: (US Bureau of Land Management, 2015[74]), Desert Renewable Energy Conservation Plan: Proposed Land Use Plan Amendment and Final Environmental Impacts Assessment. (US Bureau of Land Management, 2016[75]), Executive Summary for the Record Decision for the Land Use Plan Amendment to the California Desert Conservation Plan, Bishop Resource Management Plan, and Bakersfield Resource Management Plan.

Given the multiple economic pressures on marine resources and the rapid increase of offshore renewable energies, it is becoming increasingly important for spatial plans to cover not only terrestrial but also marine areas (OECD, 2017[76]). Responding to this need, the EU adopted a Maritime Spatial Planning (MSP) Directive 2014/89/EU that helps guide the sustainable development of marine-based energy technologies. The aim of the MSP Directive is to create a common framework for reducing conflicts and harnessing synergies across sectors such as maritime transport, fisheries and energy, to encourage cooperation and investment and preserve the environment (European Commission, 2020[39]). Members States were required to develop maritime spatial plans by 31 March 2021. An example of marine spatial planning for renewable energy in Germany is outlined in Box 4.7.

Box 4.7. Marine spatial planning in Germany

The marine spatial plan developed for Germany’s exclusive economic zone (EEZ) in the North Sea aims to coordinate the growing conflict of maritime uses between space-intensive offshore wind farms and marine environmental protection goals, as well as traditional maritime uses such as shipping and fisheries. The Spatial Plan formulates guidelines for spatial development and sets targets and principles for the various maritime functions and uses. For the German EEZ in the North Sea the Spatial Plan contains provisions aimed at coordinating the individual uses and functions of shipping, the exploitation of resources, laying of pipelines and submarine cables, scientific marine research, wind power production, fisheries and mariculture, as well as protection of the marine environment. The spatial plan was subject to a strategic environmental assessment (SEA), in accordance with the SEA Directive 2001/42/EC. Broad public participation was secured through consultations with stakeholders from agencies and non-governmental organisations covering the following issues: marine environment and nature conservation, fisheries, energy, sand and gravel, shipping, military, tourism, leisure boating, research.

Source: (EC, 2022[77]), Maritime Spatial Plan for German EEZ in the North Sea.

It is good practice for planners to apply strategic environmental assessment (SEA) to the development of spatial plans (see Chapter 5). These should include an assessment of cumulative impacts on biodiversity, which are more easily assessed and addressed at a strategic planning level than at a project level. While spatial plans subject to an SEA may help avoid the worst of environmental impacts, they do not remove the need for environmental screening at the project level or even an environmental impact assessment. Rather, they provide a framework and initial siting prescriptions. Local specificities may not be fully captured in coarse grain spatial plans, and further opportunities for avoiding or minimising biodiversity impacts could arise through strategic micro-siting within renewable energy zones and other mitigation measures.

Spatial plans and land/sea-use restrictions may need to be periodically revised to reflect improvements in data and knowledge, evolution of renewable power technology and other social, economic and environmental factors. The Netherlands, for example, applies adaptive management to marine spatial planning (Vrees, 2021[78]). While adaptive management is a good practice, continuity and predictability are also important for businesses and investors. Adaptive management therefore ideally takes place within a broader framework shaped by a long-term vision (Vrees, 2021[78]). Ongoing monitoring and evaluation are fundamental to inform adaptive spatial planning (see 5.1.4).

4.4. Decision-support and planning tools

Planning for the low-emissions transition requires making informed decisions on what is best for society. This includes deciding on which technologies to adopt and where to locate electricity generation and transmission infrastructure. These are complex choices owing to the range of policy priorities (e.g., biodiversity protection, food provision, energy access), inevitable trade-offs and uncertainties that planners must deal with. Various tools exist to support these decisions, such as strategic environmental assessment (SEA), environmental (wildlife) sensitivity mapping, cost-benefit analysis (CBA) and multi-criteria decisions analysis (MCDA). Environmental sensitivity mapping and SEA are environmental assessment tools, while CBA and MCDA are standard economic appraisal tools, which can be tailored to account for biodiversity. These decision-support tools are complementary, not mutually exclusive. This chapter discusses environmental sensitivity mapping and biodiversity-inclusive CBA and MCDA. SEA is discussed together with EIA in Chapter 5 in the section on regulatory policy instruments.

4.4.1. Environmental sensitivity mapping

Environmental sensitivity mapping (or wildlife sensitivity mapping) can guide the deployment of renewable power infrastructure to help ensure it does not compromise biodiversity goals. It is a tool for identifying and communicating the location of biodiversity features (e.g. plant or animal species, habitats, ecosystems) that are vulnerable to renewable power developments because of their conservation status and their susceptibility to impacts (Bennun et al., 2021[26]). While different approaches exist, sensitivity maps typically draw on geographic information systems (GIS) and spatial data on species and habitats. Most approaches also assign sensitivity values to biodiversity components (Allinson et al., 2020[79]).

By predicting potential conflicts between renewable power development and vulnerable biodiversity features, sensitivity maps can be an important input for developing spatial plans during strategic planning and in initial project siting decisions. They can also be used as a due diligence and risk assessment tool for power purchasers and financial institutions investing in renewable power projects (Allinson et al., 2020[79]).

Various sensitivity mapping approaches have been developed, primarily by civil society or academic institutions, with varying degrees of government involvement. The maps typically operate at a landscape level, with regional, national or international coverage. Most approaches have been applied to onshore and offshore wind energy. For example, a 2020 review of sensitivity mapping identified 24 approaches or tools,8 of which all but one had been developed primarily for wind power (Allinson et al., 2020[79]). Despite the focus on wind, sensitivity mapping can also be applied to other electricity generation infrastructure (see e.g. (Gove et al., 2016[21]) and transmission infrastructure (see e.g. (Gauld et al., 2022[80])).

Most sensitivity mapping approaches focus on birds, with only a handful covering bats or other mammals (Allinson et al., 2020[79]). Integrating other taxa and habitats into sensitivity maps could increase their value and uptake by decision makers. The focus on avian sensitivity has likely emerged for two reasons. First, birds are one of the most impacted groups by wind energy. Second, information and data on avian species distribution, abundance and risk factors are relatively advanced. Improving the underlying data on other taxa and the risks posed to them by renewable power infrastructure, will be fundamental for expanding the scope and use of sensitivity maps (see also 5.1.4).

Sensitivity mapping has been used to inform renewable power siting in several countries (Box 4.8). However, application of sensitivity mapping tends to be ad hoc rather than formalised in energy planning processes. Scope exists for governments to better integrate sensitivity mapping into their planning processes. This could involve developing guidance on sensitivity mapping (e.g. the EU commissioned a Wildlife Sensitivity Mapping Manual (Allinson et al., 2020[79])), leading the development of sensitivity maps (e.g. the Environmental Zoning Tool developed by the Spanish government Box 4.8), or establishing regulatory requirements to consider sensitivity maps as part of the planning and appraisal process. Ensuring the compatibility of sensitivity mapping with planning and consenting procedures is also important, which underscores the value of government engagement in tool development. For example, as biodiversity impacts are just one constraint to consider when siting infrastructure, governments could find value in wildlife sensitivity maps that can be integrated with information on other relevant constraints or criteria, such as resource potential, land-uses, legal restrictions and distance from the transmission grid. Finally, ongoing efforts to improve the coverage of species and habitats of concern will help to increase sensitivity mapping’s utility.

Box 4.8. Sensitivity mapping examples

Environmental Zoning for Implementing Renewable Energy: Wind and Solar – Spain

Spain’s Ministry for the Ecological Transition and Demographic Challenge developed a sensitivity mapping tool to guide the development of onshore wind and solar PV. The tool is intended to be indicative, providing strategic guidance for project siting. It complements regulatory requirements. The tool assesses sites against 18 categories of indicators covering e.g., ecological corridors, Important Bird and Biodiversity Areas, Natura 2000 sites, Ramsar wetlands of international importance, UNESCO sites, visual impacts etc. Some indicators are exclusionary (i.e., development is not advised if a certain feature is present). The other indicator scores are weighted to produce an overall environmental sensitivity score for the area in question. The zoning tool, available on the Ministry’s website, consists of two layers of information (one for energy and one for wind), with colours indicating the sensitivity score of any point on the map of Spain.

Sensitivity Mapping for Mammalian Carnivores – Croatia

Disturbance and habitat fragmentation are key threats to Croatia’s carnivores. Therefore, poorly planned wind energy developments could threaten their survival in the region. The University of Zagreb and the Croatian Ministry for Environment and Nature created a sensitivity map in 2016 based on data on large carnivore occurrence and related habitat characteristics. The sensitivity map defines nine classes of habitat sensitivity, which are grouped into four categories of suitability for large mammal presence. Individual sensitivity maps were developed for bears, wolves and lynx. Two additional maps were produced for bear and wolf reproduction sites. Finally, one combined sensitivity map was created for all three species together. The sensitivity mapping is accompanied with guidelines and information on the habitat use of carnivores. The analysis and guidelines can be used to evaluate and inform all environmental assessment procedures, such as SEAs and EIAs. The analysis and guidelines include advice about which areas to prioritise for avoidance and estimations of the permissible losses of each habitat class where some loss is unavoidable.

Soaring Bird Sensitivity Mapping Tool – Southern Europe, Middle East and North Africa

BirdLife International’s Soaring Bird Sensitivity Mapping Tool provides public access to extensive spatial datasets relating to soaring birds. A formula assigns sensitivity categories to allow an objective assessment and comparison of prospective locations based on available data. The aim of the tool is to provide planning authorities, developers and other stakeholders with an authoritative, transparent and accurate assessment of the soaring bird sensitivity of onshore wind energy and transmission infrastructure. The tool is based on data for 89 species, primarily from BirdLife’s Important Bird and Biodiversity Areas (IBA) dataset. Supplementary information, including soaring bird satellite tracking data and species’ range maps, as well as spatial data on protected areas and relevant topography, are also included to provide additional context and insight.

Site Renewables Right – United States

The Nature Conservancy’s Site Renewables Right tool was designed to inform the siting of wind and solar energy projects in the Central United States (17 states) where approximately 75% of US onshore renewable energy is likely to be located by 2050. Site Renewables Right is a sensitivity map for buyers, developers, planners and policy makers to identify areas where renewable energy development is unlikely to lead to wildlife conflicts, project delays or related cost overruns. It comprises two distinct layers, one for wind and one for solar energy. The maps are suited to landscape-level site evaluations and site characterization analyses. They are not intended for use as “go/no-go” maps, nor as a substitute for robust assessment of anticipated impacts to species and habitat. Sensitive areas covered in the maps include: whooping crane stopover sites with 400m buffer (wind and solar); big game habitats (wind); eagle and other raptor nesting areas (wind); water, wetlands, and riparian corridors (wind and solar); breeding waterfowl habitats (wind); protected and managed lands (wind and solar); important bird areas (wind); intact natural habitats (wind and solar); bat roosts (wind); other areas of biodiversity significance (wind and solar); threatened and endangered species (wind and solar); climate-resilient lands (wind and solar).

Source: (Passoni et al., 2017[81]), Framework for strategic wind farm site prioritisation based on modelled wolf reproduction habitat in Croatia, 10.1007/s10344-017-1092-7; (Allinson et al., 2020[79]), The Wildlife Sensitivity Mapping Manual: Practical guidance for planning in the European Union. Final report for the European Commission (DG ENV), https://ec.europa.eu/environment/nature/natura2000/management/nat; (Spain, 2020[82]), Environmental zoning for : Wind and solar PV www.miteco.gob.es/es/calidad-y-evaluacion-ambiental/temas/evaluacion-ambiental/zonificacion_ambiental_energias_renovables.aspx; (TNC, 2022[83]), Site Renewables Right: Accelerating a Clean and Green Buildout in the Central United States; www.nature.org/content/dam/tnc/nature/en/documents/SRR_Methods_20220202_LR.pdf.

4.4.2. Cost-benefit analysis and multi-criteria decision analysis

Cost-benefit analysis (CBA) and multi-criteria decision analysis (MCDA) are two related decision-support tools that are sometimes used to inform decisions on electricity generation portfolios and power sector policies and projects. These tools can be used individually, in parallel (as two separate sources of information), or in an integrated manner where monetised and non-monetised values are considered together (e.g., CBA results can be one criterion in the MCDA). Both tools are increasingly combined with GIS to inform spatially explicit decisions, such as infrastructure siting.

Effective integration of biodiversity into CBA and MCDA, when appraising power sector policies, plans, programmes (hereafter “policies”) and projects, can help ensure that choices made in power-sector planning optimally balance trade-offs across biodiversity and other environmental and social objectives. This requires thorough accounting of the impacts on ecosystem services in CBA and inclusion of explicit and appropriately weighted biodiversity criteria in MCDA. As illustrated in the examples below, investment options could be pre-screened with exclusionary criteria for those that may reduce the viability of species or ecosystems of conservation concern.

This section provides a brief overview of CBA and MCDA and explores how biodiversity has been integrated into these tools in theory and practice, with a particular focus on renewable power development.

Cost-benefit analysis

CBA is a widely used economic appraisal tool that compares the social costs (reductions in human well-being) and benefits (increases in human well-being) of plans, policies or projects (Beria, Maltese and Mariotti, 2012[84]; OECD, 2018[85]). The benefits and costs are aggregated and monetised, accounting for different points in time. The result of a cost-benefit analysis is generally represented in a Benefit-Cost Ratio (BCR) or Net Present Value (NPV). For a policy or project to qualify on cost-benefit grounds, its social benefits (represented in monetary terms) must exceed its social costs (OECD, 2018[85]). Environmental cost-benefit analysis is the use of CBA to evaluate an environmental project or a project that will have a non-negligible impact on the environment.

Generally, CBA analyses in the context of renewable power did not account for the social costs and benefits associated with biodiversity and ecosystem services (but have rather focused on greenhouse gas emissions or air pollution). (OECD, 2018[85]). However, valuing ecosystem services – and incorporating ecosystem service values into CBA – is an important component of robust decision making. While challenges remain in valuing ecosystem services, a range of valuation approaches have emerged and substantial progress has been made in assigning increasingly robust values to ecosystem services even where these are not explicit in market prices (see section 13 of (OECD, 2018[85]) for an overview). These advances enable many ecosystem service values to be explicitly integrated into CBA. National appraisal frameworks in various countries, such as Australia (Infrastructure Australia, 2021[86]) and the UK (HM Treasury, 2022[87]) explicitly promote or facilitate inclusion of monetised ecosystem service values when conducting CBA. Other appraisal frameworks promote the integration of biodiversity (and other difficult-to-monetise impacts) in CBA using non-monetised values (e.g., through plus-minus methods (Norway Directorate for Financial Management, 2018[88]) – see discussion below on MCDA and integrated approaches).

Where decision makers choose to use CBA to inform electricity system design and technology choices or appraise renewable energy infrastructure projects,9 integrating ecosystem service values in CBA provides an entry point for mainstreaming biodiversity in power sector planning. Take the example of transmission planning in the US. A key step in the transmission planning process outlined by USAID and the National Renewable Energy Laboratory guidelines (Lee, Flores-Espino and Hurlbut, 2017[73]), is to compare transmission options to understand the social costs, benefits and trade-offs of each option. For example, planners may need to choose between developing renewable power facilities at less productive sites that are close to existing transmission infrastructure or at more productive sites that require significant expansion of transmission infrastructure. The guidelines suggest CBA be used to compare these options and determine which approach has the greatest societal benefit. Ideally, such an analysis would account for the biodiversity impacts of each of these options, and how these translate to a change in welfare.

Examples of where biodiversity has been integrated into CBA for renewable power planning and project appraisal are not common in the literature and are mainly theoretical rather than applied. While various examples exist in academic literature of environmental CBA or economic valuation for evaluating renewable energy portfolios, policies or projects (Rhodes et al., 2017[89]; Pojadas and Abundo, 2022[90]; Rouhani et al., 2016[91]), these tend to focus on greenhouse gas emissions and air pollution rather than biodiversity. Those CBA studies that do consider biodiversity often do so by excluding ecologically important areas before or after CBA is applied, rather than attempting to value changes in ecosystem services (Deshmukh et al., 2019[38]; Sun et al., 2013[92]; Kim, Jang and Kim, 2018[93]).

One example of where CBA approaches have been applied to biodiversity and renewable power is an analysis of external costs and benefits of electricity generation options (hydropower, offshore and onshore wind, biomass) in Scotland (Bergmann, Hanley and Wright, 2006[94]). Using choice experiments the analysis showed that projects can have varying costs in terms of landscape, wildlife and air pollution impacts. They concluded that wildlife was highly valued by the population and that projects potentially harming wildlife would therefore require large offsetting benefits. A separate study (Álvarez-Farizo and Hanley, 2002[95]) used contingent rating and choice experiments to identify the social costs of environmental impacts of a wind farm in Spain. The analysis concluded that flora and fauna impacts were valued more highly than impacts on landscape and geologically rare cliff sites, but all three variables were significant determinants of preferences for wind power investments. The authors propose that such methodologies would facilitate wind farm development that minimises total social costs and maximises net benefits. A third study, in the US, applies CBA to compare costs and benefits of pollinator-friendly solar PV, standard solar PV and agriculture land, and provides policy recommendations based on their findings (Box 4.9).

Environmental CBA has well-known limitations and challenges (Beria, Maltese and Mariotti, 2012[84]; OECD, 2018[85]). These include its data and resource intensiveness, difficulties in accurately capturing all values and the uncertainty of ecosystem thresholds or tipping points. Nonetheless, it can play an important role as part of a broader policy or project appraisal process (Beria, Maltese and Mariotti, 2012[84]; OECD, 2018[85]). It is likely most useful when it is used as a decision-support tool, rather than as a prescriptive tool (Turner, 2007[96]). While it is unrealistic to include all ecosystem service values in CBA, ongoing improvements in ecosystem service valuation facilitate increasing integration of biodiversity considerations into CBA to ensure it is not ignored. Evaluating non-monetary criterion next to monetary criteria – including through integrated CBA-MCDA (discussed below) – can enable a more comprehensive and transparent assessment of positive and negative impacts in policy and project appraisal.

Box 4.9. Policy interventions for pollinator-friendly solar

Researchers at Yale University conducted a CBA to compare private and social returns from three types of land use: conventional solar, pollinator-friendly solar and pre-existing agricultural land uses. The analysis monetised positive and negative environmental externalities related to carbon emissions, soil erosion, groundwater recharge and pollination. It calculated the private and social rents from each land use, discounting values to their net present value for a 30-year project lifetime using a social discount rate of 3%. Total welfare gains and losses were calculated by comparing net gain in private, social and tax benefits across all land uses. The analysis revealed significantly higher private and social net benefits for conventional solar than farmland, and even higher net benefits for pollinator-friendly solar. Private benefits from pollinator-friendly solar projects were higher than from conventional solar because of the assumed efficiency gains for pollinator-friendly solar panels due to ambient microclimate conditions created by native plantings, and from lower operations and maintenance costs owing to reduced mowing for native plants compared to turfgrass. The relatively high social benefits associated with pollinator-friendly solar arose from greater groundwater recharge, reduced soil erosion and increased crop yields resulting from pollination (when projects are sited near pollinator-dependent farmland). The report outlined the following policy implications:

1. Private benefits: If investment does not increase in pollinator-friendly solar despite the assumed private benefits, information or behavioural market failures may be present. To address information gaps, research and development funding could focus on the relationship between native plantings, microclimates and solar panel output. If ongoing research confirms efficiency gains but investment does not increase, a behavioural failure may persist. Addressing behavioural barriers requires other measures, such as webinars or local permitting requirements that familiarise developers with pollinator-friendly practices. Additionally, stakeholder engagement across potential collaborating organisations can cultivate consensus and awareness.

2. Social benefits: The additional social (environmental) benefits of pollinator-friendly solar compared to conventional solar and agriculture warrant policy intervention. These benefits could best be captured by providing developers with a power purchase agreement “adder” that represents the per-kWh social benefits of pollinator-friendly solar. Second-best policy measures include a pollinator-friendly solar mandate, or tax credits to subsidise the practice. Research and development funding could improve ecosystem valuation and inform the appropriate incentive amount to efficiently internalise the ecosystem service benefits.

3. Location-specific benefits: Ecosystem service benefits are spatially specific. Values for soil carbon sequestration and groundwater recharge are highly dependent on topographies and soil types. Pollinator-friendly solar benefits depend greatly on the surrounding crop types. Policies need to be designed to direct and reward the siting of pollinator-friendly solar projects on lands where they will realise maximum social benefit. For example, policies could encourage project development near crops that depend on pollinators. The analysis modelled a 6.3% crop yield increase for a moderately pollinator-dependent crop (soy) from pollinator-friendly solar installations, but the yield increase for specialty crops could be much greater. Site-specific policy examples include property tax abatement, streamlined permitting processes and a tiered subsidy system where the subsidy is scaled up or down based on the value of ecosystem benefits that a project helps realise in the area where it is developed.

Source: (Siegner et al., 2019[97]), Maximizing land-use benefits from utility scale solar: A cost-benefit analysis of pollinator-friendly solar in Minnesota, https://cbey.yale.edu/sites/default/files/2019-12/MaximizingLandUseBenefitsFromUtility-ScaleSolar_0.pdf.

Multi-criteria decision analysis

Multi-criteria decision analysis (MCDA) is an approach for ranking or selecting alternative policies or projects. An advantage of this approach is its ability to account for a diverse range of social, economic and environmental dimensions – including those not easily monetised – in a single framework (Beria, Maltese and Mariotti, 2012[84]; OECD, 2018[85]). It also tends to be more “transparent” than CBA, since the objectives and criteria are usually clearly stated, rather than assumed (OECD, 2018[85]). On the other hand, unlike CBA, MCDA only provides a relative ranking of options; it does not determine whether it is appropriate to adopt a policy or project. Additionally, it is often unclear how MCDA deals with time discounting, which is a key part of CBA. Furthermore, as MCDA proceeds by adopting scores and weights chosen by experts, it tends not to be as “accountable” as CBA where the money units reflect individuals’ preferences rather than expert preferences (OECD, 2018[85]). The capacity of MCDA to articulate ecosystem service values, its transparency and accountability, depend in part on the methods applied and how the process is organised and facilitated (Saarikoski et al., 2016[98]).

Typical steps for MCDA include establishing the goals or objectives of the policy or project, selecting criteria or attributes to achieve the objectives (measured in monetary or non-monetary terms), and then scoring and weighting the options for achieving the objectives. The outcome, in the simplest form of MCDA, is a weighted average of the scores with the option with the highest weighted score being the best (OECD, 2018[85]).

MCDA can help decision makers to select among electricity generation portfolios based on a range of criteria. It allows biodiversity impacts to be considered alongside other environmental, social and economic criteria such as greenhouse gas emissions and levelised-cost. For example, (Nock and Baker, 2019[99]) applied MCDA to evaluate the sustainability of electric generation portfolios in New England against seven sustainability criteria, one of which was land-use. A similar approach was taken to compare the sustainability of 13 individual electricity generation technologies in the US (Klein and Whalley, 2015[100]). However, the authors note that their land use results underscore the need for more research to harmonise land use estimates across energy options and reduce uncertainty, especially for life cycle estimates.

MCDA integrated with global information system (GIS) has been applied in studies to inform the siting of solar and wind energy facilities in various geographies (Shorabeh et al., 2019[101]). Biodiversity considerations have been addressed in GIS-MCDA in two ways: as a constraint and as criteria. Several studies on renewable energy siting apply biodiversity constraints, but then do not explicitly include biodiversity as criteria (Shorabeh et al., 2019[101]; Sánchez-Lozano, García-Cascales and Lamata, 2016[102]). For example, (Shorabeh et al., 2019[101]) applied several biodiversity constraints, including “must not be in a conservation area” and “must not be in wetlands, forests, agricultural areas”, before applying ten criteria related to cost (e.g. distance from road, slope) and benefit (e.g. solar radiation, land surface temperature).

Other GIS-MCDA studies explicitly incorporate biodiversity as a criterium or both as a constraint and a criterium. For example, a GIS-MCDA for Gwadar, Pakistan, examined seven evaluation criteria, including two focused on biodiversity – avian hotspots and location of wetlands and forests (Zahid et al., 2021[103]). In their analysis of suitable locations for wind and solar developments in southern England, (Watson and Hudson, 2015[104]) created a binary constraint layer identifying entirely unsuitable locations, including “wildlife designations”.10 Seven criteria were then considered covering technical (wind speed, solar radiation), visual (distance from historically important sites, distance from residential areas), ecological (distance from wildlife designations), and economic (distance from transport links, distance from network connection) factors. Based on these criteria, locations were scored as not suitable, least suitable, moderately suitable and most suitable. Similarly, an assessment of potential wind energy locations in the Städteregion Aachen in Germany (Höfer et al., 2014[105]) first excluded natural resources areas, national parks, important habitat areas, bird reserves and protected biotopes. It also excluded a 300m buffer zone around these areas. After the exclusions zones had been removed, the criteria used to select sites included “distance from natural environments” and “land cover type”.

Owing to the challenges of fully accounting for biodiversity and other complex societal values in CBA, it is increasingly common to complement CBA with MCDA. Integrated CBA-MCDA methodologies are also emerging (e.g. balance sheet approach; plus-minus methods) (Saarikoski et al., 2016[98]; Turner, 2016[106]; Norway Directorate for Financial Management, 2018[88]). ENTSO-E’s Draft Cost Benefit Analysis of Grid Development Projects Guideline11 (ENTSO-E, 2019[107]), for example, combines qualitative, quantitative non-monetised and monetised assessments, recognising that a fully monetised approach is not practically feasible. When impacts on biodiversity are predicted, the estimated impact mitigation costs (i.e., private costs to business) are captured in the CAPEX. Residual impacts on biodiversity (i.e., costs to society or externalities) are assessed through a quantitative but non-monetary indicator: the number of kilometres of overhead line or underground/submarine cable passing through sensitive areas.12 A similar approach using kilometres of submarine cable as a proxy for biodiversity impacts was taken to communicate the importance of planning offshore transmission in the US (Pfeifenberger et al., 2023[108]).

4.5. Institutional co-ordination

Through its demand for land, renewable power expansion has implications for various policy areas, including biodiversity, climate change and production sectors (e.g., agriculture and fisheries). Effective co-ordination across the institutions that are responsible for these policy areas and house relevant expertise (i.e., horizontal co-ordination) is therefore critical for policy alignment.

The appropriate structure for facilitating horizontal co-ordination is likely to be country- and context-specific, but could involve e.g., inter-ministerial or inter-agency committees and working groups, taskforces or consultation processes that promote multi-stakeholder dialogue and inclusive decision-making processes. Coordination may be ad hoc or institutionalised. Examples are highlighted below:

• In Egypt, to help minimise conflicts between wind power development and migratory bird conservation, the Egyptian Environmental Affairs Agency (EEAA) and the New and Renewable Energy Authority (NREA) signed a Memorandum of Understanding (MoU), in 2012. The MoU provided a framework for co-operation on the sustainable deployment of renewable energy. In 2015, the Regional Center for Renewable Energy and Energy Efficiency initiated an Active Turbine Management Project (ATMP) based on a protocol signed with the EEAA, the NREA and the Egyptian Electricity Transmission Company. The ATMP is divided into 3 main sub-programmes: i) a bird monitoring programme; ii) a shutdown on demand programme; and iii) a fatality monitoring programme. These programmes are pertinent to all wind facilities in the Gulf of Suez region (RCREEE, 2015[109]).

• In France, until 2022, the responsibility for biodiversity, climate and energy policy was under the same ministry – the Ministry for Ecological Transition. Within the Ministry, a staff member in the directorate for water and biodiversity was responsible for following offshore wind development, while within the energy directorate some staff focused on biodiversity. A working group established in 2018 to examine cumulative effects of offshore wind was co-chaired by staff from each of these two directorates. The working group consisted of 25 central and local administrative representatives, academic experts and environmental protection agencies (France, 2022[72]).

• The Norwegian Water Resources and Energy Directorate (NVE) collaborated with the Norwegian Environment Agency, and another ten institutions to develop a knowledge base presenting positive and negative effects of wind power and information about regulatory responsibilities and procedures (NVE, 2022[110]).

Previous OECD work on biodiversity mainstreaming and policy alignment (OECD, 2018[111]; OECD, 2020[112]) and country responses to OECD’s questionnaire on biodiversity and renewable energy highlight key lessons for institutional coordination. These include the importance of setting clear goals for coordinating bodies, establishing roles and responsibilities, and ensuring continuity of effort to facilitate progress towards the set goals. Ensuring sufficient financial, technical and time resources is fundamental.

In addition to horizontal coordination, delivering on renewable energy and biodiversity objectives requires vertical coordination to align national and subnational policy, and ensure national plans reflect local interests and issues. The energy transition is planned and delivered across multiple tiers of government (international, regional, national and local) (Goldthau, 2014[113]). While the share of decision-making power and responsibility across national and subnational institutions differs from one country to another, subnational governments are playing an increasingly important role in the energy transition. Generally, renewable power objectives are established at a national and international level, while subnational governments hold responsibility for land-use decisions and the implementation of renewable energy policies (Koelman, Hartmann and Spit, 2021[114]). As renewable power constraints and biodiversity impacts are highly location-specific, subnational institutions and stakeholders are well-positioned to inform national planning and ensure that the implementation of energy plans is biodiversity-aligned.

Disconnects or tensions between international, national, regional and local levels in renewable power planning can undermine efforts to sustainably scale up renewable energy (Michalena and Hills, 2012[115]). For example, a study of case studies on wind power development in the Netherlands found conflicting differences between local interests (liveability), regional interests (landscape protection) and national tier interests (renewable energy objectives) (Koelman, Hartmann and Spit, 2021[114]). Indeed, it is often subnational government institutions implementing national climate-energy policy that are confronted by resistance from individual landowners or communities, owing to the perceived impacts of renewable energy developments on ecosystem services (e.g. cultural services [aesthetic values]) (Zoellner, Schweizer-Ries and Wemheuer, 2008[116]; Larsson and Emmelin, 2015[117]).

Establishing processes or structures for vertical coordination can help to align interests across the different tiers of government and ensure policy coherence. As with horizontal coordination, it is important to clearly define the responsibilities of institutions across the different tiers of government, and to ensure that each institution has the capacity to carry out its responsibility (Goldthau, 2014[113]).

4.6. Cross-border collaboration

Collaboration across national borders or subnational borders can help to ensure the global transition to low-emissions electricity systems does not compromise efforts to halt and reverse biodiversity loss. First, the ranges of species and ecosystems affected by renewable energy development – particularly migratory birds, bats and marine species – extend beyond subnational and national borders. The biodiversity impacts of renewable energy projects in multiple jurisdictions can therefore accumulate, potentially leading to population or ecosystem declines (see Chapter 3). Collective ambition by sub-national and national governments to mainstream biodiversity into renewable energy development is necessary to ensure a species or ecosystem is protected across its entire lifecycle and range. It can also help avoid leakage where renewable energy projects shift towards jurisdictions with fewer regulatory requirements.13

Cross-border spatial planning (e.g., at a landscape or seascape level), coordinated monitoring of affected populations and data-sharing can also play an important role in managing cumulative impacts. The EU, for example, encourages and provides guidance for its member states on cross-border co-operation in marine spatial planning. At the global level, the Convention on Migratory Species provides a framework for co-operation to address negative impacts on migratory species, including those arising from renewable power infrastructure.

Second, cross-border trade in electricity presents both an opportunity and risk to biodiversity. Well-planned interconnection of grids across country (or state) borders can reduce system costs, balance supply and demand and increase energy access (European Commission, 2020[39]). Furthermore, by offering greater flexibility for siting, cross-border grid expansion could in some contexts increase opportunities for siting infrastructure in areas of low ecological risk and reduce overall need for electricity generating assets. The Californian study highlighted in Box 4.3, for example, concluded that if California were to access renewable resources from Western states, both biodiversity impacts and portfolio costs would decrease compared to a business-as-usual scenario for expansion (Wu et al., 2019[1]).

The risk of electricity trade is that it drives land-use pressure and biodiversity loss far from where the electricity is consumed (Holland et al., 2019[118]). Negative impacts could arise from the construction and operation of utility-scale wind and solar facilities (in the absence of robust planning and policy), or from the unsustainable harvest and export of biomass to fuel power plants. Furthermore, interconnecting grids entails greater extensions of electricity transmission infrastructure, which could negatively impact biodiversity for example through habitat fragmentation and by posing collision risk for volant species. This further emphasises the importance of ensuring all jurisdictions have effective policies and planning processes in place to safeguard biodiversity, and the need to ensure that cross-border energy trade is governed by good practice principles for safeguarding biodiversity. The Green Grids Initiative – One Sun One World One Grid, launched at the COP26 World leaders Summit by the UK and Indian Prime Ministers and backed by over 80 countries, could play a role in promoting grid interconnections that protect nature. In addition to harnessing synergies and reducing trade-offs across climate, energy and biodiversity goals in electricity trade, it will be important to address trade-related risks associated with sourcing of critical minerals (Box 4.10).

Box 4.10. Trade-related risks to biodiversity from critical minerals in renewable energy

Trade-related risks to biodiversity arise from the sourcing of critical minerals upon which renewable energy infrastructure depends. These minerals are globally unevenly spread (see Chapter 3), and in most cases will be sourced through international supply chains. International co-operation is fundamental to ensure that the extraction and trade of minerals is conducted sustainably, for example through application of appropriate standards and due diligence guidelines and increased supply chain transparency. The OECD, for example, has established Due Diligence Guidance for Responsible Supply Chain of Minerals from Conflict-Affected and High-Risk Areas and a Practical Tool on Environmental Due Diligence in Mineral Supply Chains.

Notes: OECD’s Due Diligence Guidance is available here: (OECD, 2023[119]), OECD Practical Tool on Environmental Due Diligence In Mineral Supply Chains,

www.umweltbundesamt.de/sites/default/files/medien/6232/dokumente/211102_factsheet_practicaltoolenvddmineralsc.pdf.

Source: Author.

Third, development co-operation plays an important role in mainstreaming biodiversity (OECD, 2018[111]; Drutschinin et al., 2015[120]). Through technical and financial support, official development finance could support partner countries to deliver a biodiversity-aligned transition to low-emissions electricity systems. For example, Official Development Assistance (ODA) could be used to strengthen the evidence and knowledge base on renewable energy impacts on biodiversity given this is relatively poor in many developing countries (see Chapter 3), develop individual, institutional and systemic capacities to mainstream biodiversity into climate and energy planning and policy, support the development of sensitivity mapping tools or biodiversity-explicit spatial plans for renewable power, enhance monitoring frameworks and data management systems, and develop guidelines on biodiversity-inclusive SEA and environmental impact assessment (EIA), including cumulative impact assessments.

ODA from members of the OECD Development Assistance Committee has been promoting such biodiversity-related capacity development type of activities in the energy sector, to the tune of USD 2.4 million on average per year over 2011-20. This represents 1% of what these donors spent on biodiversity-related energy ODA over that period. Although overall biodiversity-related criteria in ODA funded energy activities have increased over this period, the share of commitments for biodiversity-related capacity development in the energy sector is still low, thus indicating the need for donors to continue integrating biodiversity considerations through their technical and knowledge transfer support.

Fourth, as knowledge of impacts and mitigation measures is rapidly evolving but incomplete, value lies in international exchange of knowledge, insights and experience. This could involve, for example, sharing information and evidence on species risk and effective mitigation measures, and exchanging good practices and tools for assessing species risk and environmental impacts. Multi-country initiatives have been established to this end (Box 4.11). Donors are also actively engaging in such exchanges through the promotion of triangular co-operation, although this is a development co-operation modality that has scope to grow in the area of biodiversity (OECD, 2019[121]), especially beyond Latin America and the Caribbean (OECD, 2023[122]).

Box 4.11. International initiatives to share knowledge on renewable energy and biodiversity impacts

The Convention on Migratory Species’ Energy Task Force

The CMS Energy Task Force brings together governments, multilateral environmental agreements, investors, the private sector and non-governmental organisations with an aim of avoiding and minimising negative impacts of energy developments on migratory species. It was established in 2015 in accordance with  Resolution 11.27 (Rev. COP13) Renewable Energy and Migratory Species. It was established in 2015 in accordance with  Resolution 11.27 (Rev. COP13) Renewable Energy and Migratory Species to support the implementation of these resolutions and the use of relevant guidelines. The Task Force works to:

• Promote and develop guidance and tools for the sustainable deployment or retrofitting of renewable energy technologies and power lines.

• Exchange and disseminate good practices for deploying energy infrastructure.

• Provide recommendations on how best to respond to specific problems.

• Deliver research to address knowledge gaps. 

WREN (Working Together to Resolve Environmental Effects of Wind Energy)

WREN, also known as Task 34, was established by the International Energy Agency (IEA) Wind Committee in October 2012 to address environmental issues associated with commercial development of land based and offshore wind energy projects. As the operating agent for WREN, the United States (US) leads this effort with support from the National Renewable Energy Laboratory (NREL), the Pacific Northwest National Laboratory (PNNL), and the US Department of Energy's (DOE) Wind Energy Technologies Office (WETO). The primary objective of WREN is to facilitate international collaboration and advance global understanding of potential environmental effects of wind energy. As the operating agent for WREN, the United States (US) leads this effort with support from the National Renewable Energy Laboratory (NREL), the Pacific Northwest National Laboratory (PNNL), and the US Department of Energy's (DOE) Wind Energy Technologies Office (WETO). To support this effort, Tethys (a US initiative developed in 2009) was expanded to serve as a collaborative outreach and engagement space, and to disseminate knowledge and information. Through WREN and Tethys, interested stakeholders can locate the latest scientific publications and briefings on the environmental effects of wind, and how to assess and mitigate them.

Source: (CMS, 2022[123]), CMS Energy Task Force, www.cms.int/en/taskforce/energy-task-force; (Hein, Whiting and Page, 2022[124]), About WREN, https://tethys.pnnl.gov/about-wren.

References

[45] Adeh, E. et al. (2019), “Solar PV Power Potential is Greatest Over Croplands”, Scientific Reports, Vol. 9/1, https://doi.org/10.1038/s41598-019-47803-3.

[37] AECOM (2016), Infrastructure Interdependencies and climate risks report, https://arena.gov.au/assets/2016/01/AECOM-Wind-solar-Co-location-Study-1.pdf (accessed on 10 March 2018).

[79] Allinson, T. et al. (2020), The Wildlife Sensitivity Mapping Manual: Practical guidance for rewnewable energy planning in the European Union. Final report for the European Commission (DG ENV), https://ec.europa.eu/environment/nature/natura2000/management/nat.

[95] Álvarez-Farizo, B. and N. Hanley (2002), “Using conjoint analysis to quantify public preferences over the environmental impacts of wind farms. An example from Spain”, Energy Policy, Vol. 30/2, pp. 107-116, https://doi.org/10.1016/s0301-4215(01)00063-5.

[43] Amaducci, S., X. Yin and M. Colauzzi (2018), “Agrivoltaic systems to optimise land use for electric energy production”, Applied Energy, Vol. 220, pp. 545-561, https://doi.org/10.1016/j.apenergy.2018.03.081.

[35] AXA XL (2022), Solar and wind power: Renewable Energy Environmental Exposures, AXA, https://axaxl.com/-/media/axaxl/files/pdfs/fff/2022/6874_env_solar-wind-energy-exposures_whitepaper.pdf (accessed on 25 July 2022).

[44] Barron-Gafford, G. et al. (2019), “Agrivoltaics provide mutual benefits across the food–energy–water nexus in drylands”, Nature Sustainability, Vol. 2/9, pp. 848-855, https://doi.org/10.1038/s41893-019-0364-5.

[30] Baruch-Mordo, S. et al. (2019), “From Paris to practice: sustainable implementation of renewable energy goals”, Environmental Research Letters, Vol. 14/2, p. 024013, https://doi.org/10.1088/1748-9326/aaf6e0.

[26] Bennun, L. et al. (2021), Mitigating biodiversity impacts associated with solar and wind energy development: guidelines for project developers, IUCN, International Union for Conservation of Nature, https://doi.org/10.2305/iucn.ch.2021.04.en.

[94] Bergmann, A., N. Hanley and R. Wright (2006), “Valuing the attributes of renewable energy investments”, Energy Policy, Vol. 34/9, pp. 1004-1014, https://doi.org/10.1016/j.enpol.2004.08.035.

[84] Beria, P., I. Maltese and I. Mariotti (2012), “Multicriteria versus Cost Benefit Analysis: a comparative perspective in the assessment of sustainable mobility”, European Transport Research Review, Vol. 4/3, pp. 137-152, https://doi.org/10.1007/s12544-012-0074-9.

[51] Blaydes, H. et al. (2021), “Opportunities to enhance pollinator biodiversity in solar parks”, Renewable and Sustainable Energy Reviews, Vol. 145, p. 111065, https://doi.org/10.1016/j.rser.2021.111065.

[63] Blyth-Skyrme, R. (2011), Benefits and disadvantages of co-locating windfarms and marine conservation zones, with a focus on commercial fishing, http://www.offshorewind.co.uk (accessed on 29 June 2022).

[36] Bream, H. (2018), Nevada’s Mines Could Hold Key to Question 6 Energy Standard, Las Vegas Review-Journal, https://www.reviewjournal.com/business/energy/nevadas-mines-could-hold-key-to-question-6-energy-standard1524958/.

[128] Buhl-Mortensen, L. et al. (2017), “Maritime ecosystem-based management in practice: Lessons learned from the application of a generic spatial planning framework in Europe”, Marine Policy, Vol. 75, pp. 174-186, https://doi.org/10.1016/j.marpol.2016.01.024.

[19] Capellán-Pérez, I., C. de Castro and I. Arto (2017), “Assessing vulnerabilities and limits in the transition to renewable energies: Land requirements under 100% solar energy scenarios”, Renewable and Sustainable Energy Reviews, Vol. 77, pp. 760-782, https://doi.org/10.1016/j.rser.2017.03.137.

[130] CBD (2004), CBD Guidelines for the Ecosystem Approach, https://www.cbd.int/doc/publications/ea-text-en.pdf.

[123] CMS (2022), Energy Task Force | CMS, https://www.cms.int/en/taskforce/energy-task-force (accessed on 27 July 2022).

[8] Creutzig, F. et al. (2021), “Considering sustainability thresholds for BECCS in IPCC and biodiversity assessments”, GCB Bioenergy, Vol. 13/4, pp. 510-515, https://doi.org/10.1111/gcbb.12798.

[10] Creutzig, F. et al. (2021), “Demand-side solutions to climate change mitigation consistent with high levels of well-being”, Nature Climate Change, Vol. 12/1, pp. 36-46, https://doi.org/10.1038/s41558-021-01219-y.

[55] de Rijk, S. et al. (2021), Potential synergy between solar energy and biodiversity, Copernicus GmbH, https://doi.org/10.5194/egusphere-egu21-7040.

[65] Degraer, S. et al. (2020), “Offshore Wind Farm Artificial Reefs Affect Ecosystem Structure and Functioning: A Synthesis”, Oceanography, Vol. 33/4, pp. 48-57, https://doi.org/10.5670/oceanog.2020.405.

[38] Deshmukh, R. et al. (2019), “Geospatial and techno-economic analysis of wind and solar resources in India”, Renewable Energy, Vol. 134, pp. 947-960, https://doi.org/10.1016/j.renene.2018.11.073.

[57] Didderen, K., J. Bergsma and P. Kamermans (n.d.), “Offshore flat oyster pilot Luchterduinen wind farm Results campaign 2 (July 2019) and lessons learned Status: draft”, 2019, http://www.buwa.nl (accessed on 18 July 2022).

[61] DOE (2022), InSPIRE - US Department of Energy, https://openei.org/wiki/InSPIRE (accessed on 11 July 2022).

[127] Domínguez-Tejo, E. et al. (2016), “Marine Spatial Planning advancing the Ecosystem-Based Approach to coastal zone management: A review”, Marine Policy, Vol. 72, pp. 115-130, https://doi.org/10.1016/j.marpol.2016.06.023.

[60] Dreves, H. (2019), Beneath Solar Panels, the Seeds of Opportunity Sprout | News | NREL, NREL, https://www.nrel.gov/news/features/2019/beneath-solar-panels-the-seeds-of-opportunity-sprout.html (accessed on 11 July 2022).

[120] Drutschinin, A. et al. (2015), “Biodiversity and Development Co-operation”, OECD Development Co-operation Working Papers, No. 21, OECD Publishing, Paris, https://doi.org/10.1787/5js1sqkvts0v-en.

[28] Dunnett, S. et al. (2022), “Predicted wind and solar energy expansion has minimal overlap with multiple conservation priorities across global regions”, Proceedings of the National Academy of Sciences, Vol. 119/6, https://doi.org/10.1073/pnas.2104764119.

[77] EC (2022), Maritime Spatial Plan for the German EEZ in the North Sea | The European Maritime Spatial Planning Platform, https://maritime-spatial-planning.ec.europa.eu/practices/maritime-spatial-plan-german-eez-north-sea (accessed on 18 July 2022).

[107] ENTSO-E (2019), 3 rd ENTSO-E Guideline for Cost Benefit Analysis of Grid Development Projects Draft version, https://eepublicdownloads.entsoe.eu/clean-documents/tyndp-documents/Cost%20Benefit%20Analysis/191023_CBA3_Draft%20for%20consultation.pdf (accessed on 13 July 2022).

[39] European Commission (2020), Commission notice Guidance document on wind energy developments and EU nature legislation Commission notice Guidance document on wind energy developments and EU nature legislation Guidance document on wind energy developments and EU Nature Legislation, European Commission (C2020) 7730 final, Brussels, https://ec.europa.eu/environment/nature/natura2000/management/docs/wind_farms_en.pdf (accessed on 3 May 2022).

[48] Ferrer, M. et al. (2020), “Transporting Biodiversity Using Transmission Power Lines as Stepping-Stones?”, Diversity, Vol. 12/11, p. 439, https://doi.org/10.3390/d12110439.

[72] France (2022), Country response to OECD questionnaire on mainstreaming biodiversity into renewable energy.

[80] Gauld, J. et al. (2022), “Hotspots in the grid: Avian sensitivity and vulnerability to collision risk from energy infrastructure interactions in Europe and North Africa”, Journal of Applied Ecology, Vol. 59/6, pp. 1496-1512, https://doi.org/10.1111/1365-2664.14160.

[113] Goldthau, A. (2014), “Rethinking the governance of energy infrastructure: Scale, decentralization and polycentrism”, Energy Research & Social Science, Vol. 1, pp. 134-140, https://doi.org/10.1016/j.erss.2014.02.009.

[3] Grubler, A. et al. (2018), “A low energy demand scenario for meeting the 1.5 °C target and sustainable development goals without negative emission technologies”, Nature Energy, Vol. 3/6, pp. 515-527, https://doi.org/10.1038/s41560-018-0172-6.

[33] Halada, L. et al. (2011), “Which habitats of European importance depend on agricultural practices?”, Biodiversity and Conservation, Vol. 20/11, pp. 2365-2378, https://doi.org/10.1007/s10531-011-9989-z.

[124] Hein, C., J. Whiting and J. Page (2022), About WREN | Tethys, https://tethys.pnnl.gov/about-wren (accessed on 27 July 2022).

[87] HM Treasury (2022), Guidance The Green Book, https://www.gov.uk/government/publications/the-green-book-appraisal-and-evaluation-in-central-governent/the-green-book-2020#a1-non-market-valuation-and-unmonetisable-values.

[6] Hof, C. et al. (2018), “Bioenergy cropland expansion may offset positive effects of climate change mitigation for global vertebrate diversity”, Proceedings of the National Academy of Sciences, Vol. 115/52, pp. 13294-13299, https://doi.org/10.1073/pnas.1807745115.

[105] Höfer, T. et al. (2014), “Wind Farm Siting Using a Spatial Analytic Hierarchy Process Approach: A Case Study of the Sttdteregion Aachen”, SSRN Electronic Journal, https://doi.org/10.2139/ssrn.2548520.

[49] Hoffacker, M., M. Allen and R. Hernandez (2017), “Land-Sparing Opportunities for Solar Energy Development in Agricultural Landscapes: A Case Study of the Great Central Valley, CA, United States”, Environmental Science & Technology, Vol. 51/24, pp. 14472-14482, https://doi.org/10.1021/acs.est.7b05110.

[118] Holland, R. et al. (2019), “The influence of the global electric power system on terrestrial biodiversity”, Proceedings of the National Academy of Sciences, Vol. 116/51, pp. 26078-26084, https://doi.org/10.1073/PNAS.1909269116.

[9] IEA (2021), Do we need to change our behaviour to reach net zero by 2050? – Analysis - IEA, https://www.iea.org/articles/do-we-need-to-change-our-behaviour-to-reach-net-zero-by-2050 (accessed on 24 June 2022).

[86] Infrastructure Australia (2021), Guide to economic appraisal Technical guide of the Assessment Framework, Australian Government, https://www.infrastructureaustralia.gov.au/sites/default/files/2021-07/Assessment%20Framework%202021%20Guide%20to%20economic%20appraisal.pdf (accessed on 4 August 2022).

[5] IPCC (2022), Climate Change 2022: Mitigation of Climate Change. Working Group III contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change.

[31] James, J. and E. Hansen (2017), Prospects for Large-scale Solar on Degraded Land in West Virginia, Appalachian Stewardship Foundation and Downstream Strategies, http://www.downstreamstrategies.com/documents/reports_publication/utility-scale-solar-report_2-21-17.pdf (accessed on 4 March 2022).

[93] Kim, C., S. Jang and T. Kim (2018), “Site selection for offshore wind farms in the southwest coast of South Korea”, Renewable Energy, Vol. 120, pp. 151-162, https://doi.org/10.1016/j.renene.2017.12.081.

[100] Klein, S. and S. Whalley (2015), “Comparing the sustainability of U.S. electricity options through multi-criteria decision analysis”, Energy Policy, Vol. 79, pp. 127-149, https://doi.org/10.1016/j.enpol.2015.01.007.

[114] Koelman, M., T. Hartmann and T. Spit (2021), “When tensions become conflicts: wind turbine policy implementation and development in the Netherlands”, Journal of Environmental Planning and Management, Vol. 65/3, pp. 375-397, https://doi.org/10.1080/09640568.2021.1885018.

[117] Larsson, S. and L. Emmelin (2015), “Objectively best or most acceptable? Expert and lay knowledge in Swedish wind power permit processes”, Journal of Environmental Planning and Management, Vol. 59/8, pp. 1360-1376, https://doi.org/10.1080/09640568.2015.1076383.

[73] Lee, N., F. Flores-Espino and D. Hurlbut (2017), Renewable Energy Zone (REZ) Transmission Planning Process: A Guidebook for Practitioners, USAID; NREL.

[13] Luderer, G. et al. (2019), “Environmental co-benefits and adverse side-effects of alternative power sector decarbonization strategies”, Nature Communications 2019 10:1, Vol. 10/1, pp. 1-13, https://doi.org/10.1038/s41467-019-13067-8.

[34] Macgregor, C. et al. (2022), “Brownfield sites promote biodiversity at a landscape scale”, Science of The Total Environment, Vol. 804, p. 150162, https://doi.org/10.1016/j.scitotenv.2021.150162.

[64] Macknick, J., B. Beatty and G. Hill (2013), “Overview of Opportunities for Co-Location of Solar Energy Technologies and Vegetation”, http://www.nrel.gov/publications. (accessed on 29 June 2022).

[21] Magar, V. (ed.) (2016), “Reconciling Biodiversity Conservation and Widespread Deployment of Renewable Energy Technologies in the UK”, PLOS ONE, Vol. 11/5, p. e0150956, https://doi.org/10.1371/journal.pone.0150956.

[18] Mai, T. et al. (2021), “Interactions of wind energy project siting, wind resource potential, and the evolution of the U.S. power system”, Energy, Vol. 223, p. 119998, https://doi.org/10.1016/j.energy.2021.119998.

[71] McKenney, B. (2020), Clean and Green Pathways for the Global Renewable Energy Buildout.

[24] McManamay, R., C. Vernon and H. Jager (2021), “Global Biodiversity Implications of Alternative Electrification Strategies Under the Shared Socioeconomic Pathways”, Biological Conservation, Vol. 260, p. 109234, https://doi.org/10.1016/J.BIOCON.2021.109234.

[115] Michalena, E. and J. Hills (2012), “Renewable energy issues and implementation of European energy policy: The missing generation?”, Energy Policy, Vol. 45, pp. 201-216, https://doi.org/10.1016/j.enpol.2012.02.021.

[23] Moran, E. et al. (2018), “Sustainable hydropower in the 21st century”, Proceedings of the National Academy of Sciences, Vol. 115/47, pp. 11891-11898, https://doi.org/10.1073/pnas.1809426115.

[29] Newbold, T. et al. (2015), “Global effects of land use on local terrestrial biodiversity”, Nature, Vol. 520/7545, pp. 45-50, https://doi.org/10.1038/nature14324.

[15] Nilsson, C. et al. (2005), “Fragmentation and Flow Regulation of the World’s Large River Systems”, Science, Vol. 308/5720, pp. 405-408, https://doi.org/10.1126/science.1107887.

[99] Nock, D. and E. Baker (2019), “Holistic multi-criteria decision analysis evaluation of sustainable electric generation portfolios: New England case study”, Applied Energy, Vol. 242, pp. 655-673, https://doi.org/10.1016/j.apenergy.2019.03.019.

[88] Norway Directorate for Financial Management (2018), Veileder i samfunnsøkonomiske, https://dfo.no/sites/default/files/fagomr%C3%A5der/Utredninger/Veileder-i-samfunnsokonomiske-analyser.pdf#page=24&zoom=100,0,0.

[110] NVE (2022), Knowledge base on the effects of wind power on land, https://www.nve.no/energi/energisystem/vindkraft/kunnskapsgrunnlag-om-virkninger-av-vindkraft-paa-land/.

[122] OECD (2023), A Decade of Development Finance for Biodiversity, OECD Publishing, Paris, https://doi.org/10.1787/e6c182aa-en.

[119] OECD (2023), OECD Practical Tool on Environmental Due Diligence In Mineral Supply Chains, https://www.umweltbundesamt.de/sites/default/files/medien/6232/dokumente/211102_factsheet_practicaltoolenvddmineralsc.pdf.

[12] OECD (2021), Transport Strategies for Net-Zero Systems by Design, OECD Publishing, Paris, https://doi.org/10.1787/0a20f779-en.

[112] OECD (2020), Towards Sustainable Land Use: Aligning Biodiversity, Climate and Food Policies, OECD Publishing, Paris, https://doi.org/10.1787/3809b6a1-en.

[11] OECD (2019), Accelerating Climate Action: Refocusing Policies through a Well-being Lens, OECD Publishing, Paris, https://doi.org/10.1787/2f4c8c9a-en.

[121] OECD (2019), “Green triangular co-operation: An accelerator to sustainable development”, OECD Development Policy Papers, No. 21, OECD Publishing, Paris, https://doi.org/10.1787/d81d884a-en.

[85] OECD (2018), Cost-Benefit Analysis and the Environment: Further Developments and Policy Use, OECD Publishing, Paris, https://doi.org/10.1787/9789264085169-en.

[111] OECD (2018), Mainstreaming Biodiversity for Sustainable Development, OECD Publishing, Paris, https://doi.org/10.1787/9789264303201-en.

[76] OECD (2017), Marine Spatial Planning Assessing net benefits and improving effectiveness, https://www.oecd.org/greengrowth/GGSD_2017_Issue%20Paper_Marine%20Spatial%20Planning.pdf (accessed on 25 July 2022).

[25] OECD (2016), Biodiversity Offsets: Effective Design and Implementation, OECD Publishing, Paris, https://doi.org/10.1787/9789264222519-en.

[22] Opperman, J. et al. (2019), Connected and Flowing: A renewable future for rivers, climate and people, WWF and TNC, Washington D.C.

[46] Pascaris, A. et al. (2022), “Do agrivoltaics improve public support for solar? A survey on perceptions, preferences, and priorities”, Green Technology, Resilience, and Sustainability, Vol. 2/1, https://doi.org/10.1007/s44173-022-00007-x.

[81] Passoni, G. et al. (2017), “Framework for strategic wind farm site prioritisation based on modelled wolf reproduction habitat in Croatia”, European Journal of Wildlife Research, Vol. 63/2, https://doi.org/10.1007/s10344-017-1092-7.

[108] Pfeifenberger et al. (2023), The Benefit and Urgency of Planned Offshore Transmission: Reducing the Costs of and Barriers to Achieving U.S. Clean Energy Goals, https://www.brattle.com/wp-content/uploads/2023/01/Brattle-OSW-Transmission-Report_Jan-24-2023.pdf (accessed on 28 February 2023).

[54] Pitts-Singer, T. (ed.) (2021), “Can Solar Energy Fuel Pollinator Conservation?”, Environmental Entomology, Vol. 50/4, pp. 757-761, https://doi.org/10.1093/ee/nvab041.

[90] Pojadas, D. and M. Abundo (2022), “A spatial cost-benefit-externality modelling framework for siting of variable renewable energy farms: A case in Bohol, Philippines”, Renewable Energy, Vol. 181, pp. 1177-1187, https://doi.org/10.1016/j.renene.2021.09.114.

[16] Pörtner et al. (2021), Scientific outcome of the IPBES-IPCC co-sponsored workshop on biodiversity and climate change, IPBES Secretariat, https://doi.org/10.5281/zeonodo.4659158.

[47] Pringle, A., R. Handler and J. Pearce (2017), “Aquavoltaics: Synergies for dual use of water area for solar photovoltaic electricity generation and aquaculture”, Renewable and Sustainable Energy Reviews, Vol. 80, pp. 572-584, https://doi.org/10.1016/j.rser.2017.05.191.

[58] Prusina, I. et al. (2020), Nature-Inclusive Design: a catalogue for offshore wind infrastructure The Ministry of Agriculture, Nature and Food Quality Final version, http://www.witteveenbos.com (accessed on 18 July 2022).

[50] Randle-Boggis, R. et al. (2020), “Realising co-benefits for natural capital and ecosystem services from solar parks: A co-developed, evidence-based approach”, Renewable and Sustainable Energy Reviews, Vol. 125, p. 109775, https://doi.org/10.1016/j.rser.2020.109775.

[62] Ravi, S. et al. (2016), “Colocation opportunities for large solar infrastructures and agriculture in drylands”, Applied Energy, Vol. 165, pp. 383-392, https://doi.org/10.1016/j.apenergy.2015.12.078.

[109] RCREEE (2015), Active Turbine Management Program, https://www.rcreee.org/project/active-turbine-management-program-atmp/4300 (accessed on 27 June 2022).

[89] Rhodes, J. et al. (2017), “A geographically resolved method to estimate levelized power plant costs with environmental externalities”, Energy Policy, Vol. 102, pp. 491-499, https://doi.org/10.1016/j.enpol.2016.12.025.

[40] Rijkswaterstaat (2020), LIFE13ENV/NL/000971 FINAL Report Solar Highways Project Data Beneficiary Data, http://solarhighways.eu (accessed on 18 April 2023).

[27] Rio Tinto (2012), Rio Tinto and biodiversity: Working towards net positive impa.

[91] Rouhani, O. et al. (2016), “Cost-benefit analysis of various California renewable portfolio standard targets: Is a 33% RPS optimal?”, Renewable and Sustainable Energy Reviews, Vol. 62, pp. 1122-1132, https://doi.org/10.1016/j.rser.2016.05.049.

[2] RTE (2022), Futurs énergétiques 2050 : les scénarios de mix de production à l’étude permettant d’atteindre la neutralité carbone à l’horizon 2050. Chapitre 12: L’analyse environnementale.

[98] Saarikoski, H. et al. (2016), “Multi-Criteria Decision Analysis and Cost-Benefit Analysis: Comparing alternative frameworks for integrated valuation of ecosystem services”, Ecosystem Services, Vol. 22, pp. 238-249, https://doi.org/10.1016/j.ecoser.2016.10.014.

[14] Saikia, L. (ed.) (2022), “Land-use intensity of electricity production and tomorrow’s energy landscape”, PLOS ONE, Vol. 17/7, p. e0270155, https://doi.org/10.1371/journal.pone.0270155.

[102] Sánchez-Lozano, J., M. García-Cascales and M. Lamata (2016), “Comparative TOPSIS-ELECTRE TRI methods for optimal sites for photovoltaic solar farms. Case study in Spain”, Journal of Cleaner Production, Vol. 127, pp. 387-398, https://doi.org/10.1016/j.jclepro.2016.04.005.

[20] Santangeli, A. et al. (2015), “Global change synergies and trade‐offs between renewable energy and biodiversity”, GCB Bioenergy, Vol. 8/5, pp. 941-951, https://doi.org/10.1111/gcbb.12299.

[67] Schupp, M. et al. (2021), “Fishing within offshore wind farms in the North Sea: Stakeholder perspectives for multi-use from Scotland and Germany”, Journal of Environmental Management, Vol. 279, p. 111762, https://doi.org/10.1016/j.jenvman.2020.111762.

[52] Semeraro, T. et al. (2018), “Planning ground based utility scale solar energy as green infrastructure to enhance ecosystem services”, Energy Policy, Vol. 117, pp. 218-227, https://doi.org/10.1016/j.enpol.2018.01.050.

[101] Shorabeh, S. et al. (2019), “A risk-based multi-criteria spatial decision analysis for solar power plant site selection in different climates: A case study in Iran”, Renewable Energy, Vol. 143, pp. 958-973, https://doi.org/10.1016/j.renene.2019.05.063.

[97] Siegner, K. et al. (2019), Maximizing land-use benefits from utility scale solar: A cost-benefit analysis of pollinator-friendly solar in Minnesota, Yale Center for Business and the Environment, https://cbey.yale.edu/sites/default/files/2019-12/MaximizingLandUseBenefitsFromUtility-ScaleSolar_0.pdf (accessed on 6 October 2021).

[53] Sinha, P. et al. (2018), “Best Practices in Responsible Land Use for Improving Biodiversity at a Utility-Scale Solar Facility”, Case Studies in the Environment, Vol. 2/1, pp. 1-12, https://doi.org/10.1525/cse.2018.001123.

[7] Smith, P. et al. (2019), “Land-Management Options for Greenhouse Gas Removal and Their Impacts on Ecosystem Services and the Sustainable Development Goals”, Annual Review of Environment and Resources, Vol. 44/1, pp. 255-286, https://doi.org/10.1146/annurev-environ-101718-033129.

[82] Spain (2020), Environmental Zoning for Implementing Renewable Energy: Wind and Solar, https://www.miteco.gob.es/es/calidad-y-evaluacion-ambiental/temas/evaluacion-ambiental/zonificacion_ambiental_energias_renovables.aspx (accessed on 17 April 2023).

[68] Steins, N. et al. (2021), “Combining offshore wind farms, nature conservation and seafood: Lessons from a Dutch community of practice”, Marine Policy, Vol. 126, p. 104371, https://doi.org/10.1016/j.marpol.2020.104371.

[66] Stelzenmüller, V. et al. (2016), “Co-location of passive gear fisheries in offshore wind farms in the German EEZ of the North Sea: A first socio-economic scoping”, Journal of Environmental Management, Vol. 183, pp. 794-805, https://doi.org/10.1016/j.jenvman.2016.08.027.

[92] Sun, Y. et al. (2013), “GIS-based approach for potential analysis of solar PV generation at the regional scale: A case study of Fujian Province”, Energy Policy, Vol. 58, pp. 248-259, https://doi.org/10.1016/j.enpol.2013.03.002.

[83] TNC (2022), Site Renewables Right: Accelerating a Clean and Green Renewable Energy Buildout in the Central United States, https://www.nature.org/content/dam/tnc/nature/en/documents/SRR_Methods_20220202_LR.pdf.

[32] TNC (2020), Mining the Sun: How Nevada and West Virginia are Reclaiming Former Mine Lands with Solar Panels, https://www.nature.org/en-us/what-we-do/our-priorities/tackle-climate-change/climate-change-stories/nevada-west-virginia-solar-energy-former-mines/.

[4] Tran, T. and M. Egermann (2022), “Land-use implications of energy transition pathways towards decarbonisation – Comparing the footprints of Vietnam, New Zealand and Finland”, Energy Policy, Vol. 166, p. 112951, https://doi.org/10.1016/j.enpol.2022.112951.

[69] Tucker, G., F. Quétier and W. Wende (2020), uidance on achieving no net loss or net gain of biodiversity and ecosystem services. Report to the European Commission, DG Environment on Contract ENV.B.2/SER/2016/0018, Institute for European Environmental Policy, Brussels.

[106] Turner, R. (2016), “The ‘Balance Sheet’ Approach Within Adaptive Management for Ecosystem Services”, in Routledge Handbook of Ecosystem Services, Routledge, https://doi.org/10.4324/9781315775302-25.

[96] Turner, R. (2007), “Limits to CBA in UK and European environmental policy: retrospects and future prospects”, Environmental and Resource Economics, Vol. 37/1, pp. 253-269, https://doi.org/10.1007/s10640-007-9119-2.

[129] U.S. (2022), United States Response to OECD Working Party on Biodiversity Water and Ecosystems Questionnaire.

[75] US Bureau of Land Management (2016), “Executive Summary for the Record of Decision for the Land Use Plan Amendment to the California Desert Conservation Plan, Bishop Resource Management Plan, and Bakersfield Resource Management Plan”, https://eplanning.blm.gov/public_projects/lup/66459/133459/163123/DRECP_BLM_ROD_Executive_Summary.pdf (accessed on 3 March 2022).

[74] US Bureau of Land Management (2015), Desert Renewable Energy Conservation Plan: Proposed Land Use Plan Amendment and Final Environmental Impacts Statement.

[70] US DOI (2015), Interior Department Approves First Solar Energy Zone Projects, https://www.doi.gov/pressreleases/interior-department-approves-first-solar-energy-zone-projects (accessed on 15 July 2022).

[41] van de Ven, D. et al. (2021), “The potential land requirements and related land use change emissions of solar energy”, Scientific Reports, Vol. 11/1, https://doi.org/10.1038/s41598-021-82042-5.

[17] van Ouwerkerk, J. et al. (2022), “Impacts of power sector model features on optimal capacity expansion: A comparative study”, Renewable and Sustainable Energy Reviews, Vol. 157, p. 112004, https://doi.org/10.1016/j.rser.2021.112004.

[42] Villarini, M. (ed.) (2018), “Remarkable agrivoltaic influence on soil moisture, micrometeorology and water-use efficiency”, PLOS ONE, Vol. 13/11, p. e0203256, https://doi.org/10.1371/journal.pone.0203256.

[78] Vrees, L. (2021), “Adaptive marine spatial planning in the Netherlands sector of the North Sea”, Marine Policy, Vol. 132, p. 103418, https://doi.org/10.1016/j.marpol.2019.01.007.

[59] Waardenburg, B. (2020), Biodiversity enhancement in offshore wind farms Options for biodiversity enhancement in offshore wind farms Knowledge base for the implementation of the Rich North Sea Programme, https://www.buwa.nl/fileadmin/buwa_upload/Bureau_Waardenburg_rapporten/2020/18-0660_The_Rich_North_Sea-_options_for_biodiversity_enhancement_in_OWFs_07022020-reduced.pdf (accessed on 18 July 2022).

[56] WaterProof Marine Consultancy and Services (2020), Artificial reef structures North Sea: Structure stability analyses in Borssele OWF and NSIL, https://de-rijke-noordzee-production.s3-eu-west-1.amazonaws.com/Website/WP2020_1218_R1r2_Stability_eco_structures_Northsea_final.pdf (accessed on 18 July 2022).

[104] Watson, J. and M. Hudson (2015), “Regional Scale wind farm and solar farm suitability assessment using GIS-assisted multi-criteria evaluation”, Landscape and Urban Planning, Vol. 138, pp. 20-31, https://doi.org/10.1016/j.landurbplan.2015.02.001.

[126] Winemiller, K. et al. (2016), “Balancing hydropower and biodiversity in the Amazon, Congo, and Mekong”, Science, Vol. 351/6269, pp. 128-129, https://doi.org/10.1126/science.aac7082.

[1] Wu, G. et al. (2019), “Power of Place Land Conservation and Clean Energy Pathways for California”, https://www.scienceforconservation.org/assets/downloads/Technical_Report_Power_of_Place.pdf (accessed on 30 March 2022).

[103] Zahid, F. et al. (2021), “Wind farms selection using geospatial technologies and energy generation capacity in Gwadar”, Energy Reports, Vol. 7, pp. 5857-5870, https://doi.org/10.1016/j.egyr.2021.08.165.

[125] Zarfl, C. et al. (2019), “Future large hydropower dams impact global freshwater megafauna”, Scientific Reports, Vol. 9/1, https://doi.org/10.1038/s41598-019-54980-8.

[116] Zoellner, J., P. Schweizer-Ries and C. Wemheuer (2008), “Public acceptance of renewable energies: Results from case studies in Germany”, Energy Policy, Vol. 36/11, pp. 4136-4141, https://doi.org/10.1016/j.enpol.2008.06.026.

Notes

← 1.  Lifestyles change to increase energy sufficiency in terms of end-uses and consumption (less individual travel, favouring soft mobility and mass transport, less consumption of manufactured goods, sharing economy, lower set point temperatures for heating, increase in remote working, digital sustainability, etc.), resulting in an overall reduction in energy needs, and thus electricity needs.

← 2.  Gradual electrification (substitution for fossil fuels) and ambitious targets for energy efficiency (NLCS assumption). Assumes continued economic growth (+1.3% per year from 2030) and demographic growth (INSEE’s low fertility scenario). The baseline trajectory assumes a high degree of efficacy of public policies and plans (stimulus, hydrogen, industry). The manufacturing industry expands, and its share of GDP ceases to decrease. Building renovation is factored in but so is the related rebound effect.

← 3.  The predecessor of the MacKay Carbon Calculator.

← 4.  Not only does hydropower tend to be more harmful than solar and wind, much of the untapped potential for hydropower is found in river basins with exceptionally high biodiversity (Zarfl et al., 2019[125]; Winemiller et al., 2016[126]).

← 5.  Upstream impacts from mining for minerals used in the component parts may still occur.

← 6.  Increasing turbine and hub height has facilitated this (see Chapter 3).

← 7.  The ecosystem approach is an interdisciplinary management approach that recognises the complexity of ecological systems and integrates social, ecological, and governance principles to achieve equitable and sustainable natural resource use (Domínguez-Tejo et al., 2016[127]; Buhl-Mortensen et al., 2017[128]). For guidelines on the Ecosystem Approach see CBD Secretariat (2004[130]), CBD Guidelines for the Ecosystem Approach, Montreal.

← 8.  Not all of these approaches have been operationalised, some were developed as academic demonstrations.

← 9.  CBA for renewable energy is not standard practice globally. It can also be challenging owing to the significant and rapid fluctuations and uncertainties in energy prices.

← 10.  Wildlife designations included: UK Sites of Special Scientific Interest, National and Local Nature Reserves; European Special Protection Areas and Special Areas of Conservation; and international Ramsar site and “landscape designations”, comprising National Parks and Areas of Outstanding Natural Beauty. Other constraint areas included, historically important sites, residential area, agricultural land classification and aspect (direction of slope) and slope (gradient of land).

← 11.  The guideline was developed in compliance with the requirements of the EU Regulation (EU) 347/2013, which aims to ensure a common framework for multi-criteria cost-benefit analysis (CBA) for ENTSO-E Ten Year Network Development Plan (TYNDP) project.

← 12.  Sensitive areas are considered to be land protected under the following Directives or International Laws: Habitats Directive (92/43/EEC); Birds Directive (2009/147/EC); RAMSAR site; IUCN key biodiversity areas; Marine Strategy Framework Directive (2008/56/EC); Other nature protection areas under national law.

← 13.  In the US, for example, regulations differ from one state to another, affecting the location and practices of renewable power projects (U.S., 2022[129]). Most projects are in states and on lands that have fewer regulatory requirements for renewable power companies to build and operate.