Accounting and allocation of avoided environmental impact—Integrating scope 4 in sustainability reporting and investment analysis

Capital allocation toward renewable technologies is a prerequisite for the energy transition. Current reporting standards cover greenhouse gas emissions from companies' own operations, purchased energy, and increasingly upstream and downstream activities, while avoided emissions (scope 4) and other generated or avoided environmental impacts are normally not included. This paper presents a methodology for integrating scope 4 and a broader set of environmental indicators into investment analysis and discusses how this can assist investors in capital allocation toward renewable technologies. Taking wind and solar power as examples, environmental impact is quantified from a life cycle perspective in five different geographical settings: Brazil, China, Germany, India, and the USA. The environmental impact in scope 1-3 as well as the potential avoided impact in scope 4 was calculated through life cycle assessment. Three different allocation methods were applied to demonstrate how avoided impact can be divided between system components: economic allocation, mass allocation and allocation according to scope 1-3 impact. For both wind and solar power, the scope 4 avoided impact can exceed the scope 1-3 environmental impact in several impact categories, including climate impact, particularly in regions with fossil-based electricity production. A gradual transition to more renewable electricity production is shown to reduce the scope 4 impact over time, but even with "net zero emissions" electricity by 2050 the avoided impact exceeds scope 1-3 for both wind and solar. Finally, this paper addresses the challenge of allocating avoided impact between components of renewable energy systems, where there is no physical relationship between the components and their scope 4 contributions, giving reporting companies and investors a view on how each component contributes to avoided impact. The study shows that avoided environmental impact, which is not covered in current accounting standards, can be of great importance when assessing renewable energy technologies. The presented methodology could be applied to other systems where avoided impact is created, such as waste-based bioenergy. Allocating avoided impact between components would allow companies behind each of them to claim a share of the positive sustainability effects and make them more attractive to investors.

To address the risks of the climate crisis, the International Energy Agency (IEA) forecasts that 50% of global electricity will have to come from renewable energy sources by 2030 (Cozzi and Gould, 2025). Despite efforts to divert funding from fossil fuel-reliant companies (Boermans and Galema, 2019), power generation remains the primary contributor to global greenhouse gas (GHG) emissions (Çam et al., 2025), with fossil fuels accounting for around 80% of total primary energy supplied in the global energy mix (Energy Institute, 2025). Concurrently, the accelerating global electrification is forecast to create a surge in demand for all major energy sources. Looking back at four consecutive years of record fossil fuel demand and CO 2 emissions (Çam et al., 2025), there are undoubtedly structural challenges ahead in aligning global energy demand with climate goals.

Turning the current development towards a more sustainable path with more renewable energy will require efficient reallocation of capital from the financial sector (cf. Ghanem, 2026; Munonye and Munonye, 2025; Popescu et al., 2024). This in turn is strongly related to sustainable corporate management (Perera et al., 2026), contingent on transparent accounting and reporting to reduce information asymmetry and enable informed decisions (Healy and Palepu, 2001). In 2000, the Carbon Disclosure Project emerged as an investor initiative to encourage companies to report GHG emissions from their operations (scope 1) and purchased energy (scope 2) (Carbon Disclosure Project, 2024). They also developed a broader view—radical at the time—on disclosing upstream and downstream GHG emissions along the value chains (scope 3) from the reporting organization. Although scope 3 emissions occur outside a company's organizational and judicial boundaries, they serve as a critical indicator of investment risk (Blanco, 2021). However, reporting scope 3 emissions is not yet mandatory, and various approaches exist among different firms (Hettler and Graf-Vlachy, 2024). Meanwhile, investment strategies among financial industry actors have evolved to increasingly prioritize and capitalize companies that demonstrate low GHG emissions, while investment practices have expanded to actively engaging with high emitters to improve their performance (Calvin et al., 2023; GSIA, 2025; PRI, 2025).

Policies in both the EU and the US, like the EU's REPowerEU plan (European Commission, 2022) and the US Inflation Reduction Act (Podesta, 2023), promote clean energy by incentivizing investments in renewable energy technologies, particularly solar and wind power. The legal institutions and standards of particularly the European Union have, in turn, been found to exert pressure on policy development globally, a phenomenon known as ‘The Brussels Effect' (Bradford, 2012). Some of the key European regulatory initiatives for mitigating GHG emissions and reaching carbon neutrality by 2050 can be structured as:

Targets, Governance, and Framework: The European Green Deal (EGD) encompasses a strategy to achieve climate-neutrality by 2050 and the 2030 milestone goal Fit for 55 (55% GHG emission reductions by 2030), aiming to establish legal commitment and binding reduction pathways for the entire bloc. Core instruments of the EGD and Fit for 55 are the EU Emissions Trading Scheme and its expansion into global value-chains entering Europe, the Carbon Border Adjustment Mechanism.

Energy System Transformation: These policies, like the REPowerEU Plan and the directives for renewable energy and energy efficiency, aim to reshape the production, distribution, and consumption of energy, which is the largest source of GHG emissions.

Financial Mobilization and Transparency: Policies like EU Sustainable Finance Action Plan, which encompasses the Sustainable Finance Disclosure Regulation, the EU Taxonomy and the Corporate Sustainability Reporting Directive, aim to ensure that private finance flows towards genuinely sustainable activities, mitigating the risk of greenwashing and increasing market accountability.

Furthermore, the European Parliament has recognized the need for private investment to complement public efforts in reducing environmental impact (European Parliament European Council, 2020). Given the right conditions and guidelines, the financial sector could thus act as a catalyst for sustainability by facilitating this process.

An increasing number of companies are required to report their emissions according to the GHG protocol, as well as impact and financial materiality (according to the Corporate Sustainability Reporting Directive), providing a foundation for investors to assess the companies' risks. However, positive externalities in the form of potential environmental benefits created by companies' products and activities do not fit into the established reporting framework and are normally not considered. Such contributions, commonly denoted “scope 4” or “avoided emissions,” could be seen as a separate extension of the upstream and downstream (scope 3) activities (WRI and WBCSD, 2011) (Figure 1). Scope 4 includes impact avoided through, for example, the use or recycling of a company's products, compared to an alternative scenario where these products are not used or recycled (Valeri et al., 2023). Adding this scope thus provides a more complete life cycle perspective on a company's products and activities. Considering such holistic approaches to a company's value chains, avoided emissions could for example be generated by promoting more circular resource use and investments in disruptive technologies that replace traditional systems with large environmental impact, such as fossil fuels (Howard et al., 2021). Moreover, it could help steer investments to the geographical regions where they have the most impact. For instance, the impact of investing in solar power will vary depending on the local solar irradiation and the impact of averted energy production, whether based on fossil or renewable resources (cf. Grant and Hicks, 2020). While the interest in creating avoided emissions by implementing new technology is now budding, there is no standardized method for accounting and reporting them (Russell, 2018; Young-Ferris et al., 2025) and many different approaches are being used by different companies (O'Keeffe and Brander, 2025). This makes it difficult to make comparisons of avoided emissions, as well as assessing the contributions of individual components in, for example, renewable energy installations. Furthermore, there is a need to investigate the relationship between scope 4 emissions and green financing (Khanchel et al., 2024).

Although climate change is indeed a major global concern, neglecting other environmental aspects through a sole focus on GHG emissions is problematic. Assessing multiple environmental factors enables more holistic decision-making, reducing the risks of suboptimal environmental outcomes. The Carbon Disclosure Project, working globally on companies' environmental performance reporting, recently included other environmental impacts (Carbon Disclosure Project, 2024), but they are not yet integrated in the GHG protocol reporting standard. Meanwhile, environmental product declarations have been used optionally since the 1990s to report the broad environmental performance of individual products according to life cycle assessment (LCA) methodology (EPD International, 2025). A full LCA covers all life cycle stages, from resource extraction to product use and disposal, as well as a wide range of impact categories, empowering informed decisions based on environmental consequences (Curran, 2006; European Commission, 2010). The life cycle perspective is also integrated in several European policy initiatives, such as the Sustainable Finance Action Plan and the Taxonomy for sustainable investments. The taxonomy defines six environmental objective areas, encompassing aspects beyond climate change, requiring investments to contribute positively to at least one objective without significantly harming others (European Parliament European Council, 2020). Consequently, when taking climate change aspects into account—one objective area of the taxonomy—investors must also address if any of the other five objective areas within the taxonomy will be affected, to avoid problem shifting. The EU has, hence, created a tool for increasing the materiality of other environmental aspects than GHG emissions.

In the context of LCA and finances, Ritchie and Dowlatabadi (2014) highlighted the climate impact of financial investments through an economic LCA framework. Similarly, Popescu et al. (2023) applied LCA to include scope 3 GHG emissions of investment funds, and recent attempts to assess scope 4 focus on climate impact (De Giovanni, 2025; Liu and Wang, 2025). The climate aspect is also prevalent in research on sustainable finance (Kumar et al., 2025; Singhania et al., 2024), although efforts have been made to include local socio-economic aspects (Räikkönen et al., 2016). However, to the best of the authors' knowledge, there is a lack of studies applying LCA for a broad environmental assessment of financial investments, as well as LCA studies including the positive environmental externalities (scope 4 impact) of investments.

This paper demonstrates how avoided environmental impact (scope 4) can be calculated, presented and integrated into investment analysis for renewable energy systems. By establishing clear, investment-relevant metrics, this work seeks to enable investors to better assess, make informed decisions and support companies' contributions to energy transition and efforts towards a carbon-neutral economy. Life cycle assessments of solar and wind power are used as examples to evaluate both generated and avoided environmental impacts of a renewable energy power plant in different geographical contexts. Finally, the paper demonstrates how avoided environmental impact can be allocated between the components of such systems, providing a foundation for dividing positive environmental effects between different actors.

The principle of adding scope 4 emissions to the GHG protocol framework and integrating them in an investment analysis is demonstrated by using two renewable electricity systems as examples: solar photovoltaic (PV) power and wind power. The environmental impact in scope 1–3 as well as the potential avoided impact in scope 4 was calculated through LCA, in accordance with ISO 14040 and ISO 14044, and allocated between the components and processes of the studied systems. Figure 2 illustrates the system model used in the LCA. The inputs consist of energy and material consumption while the outputs are emissions and produced energy. System boundaries cover the whole life cycle (cradle to grave), including raw material acquisition, manufacturing, use and end-of-life, where energy produced in the use phase is considered to replace other electricity production (scope 4). In the end-of-life phase, material recycling contributes to scope 4 by replacing the production of virgin raw materials. The following subsections provide more detailed descriptions of the LCA methodology (2.1), data collection (2.2) and allocation methods used (2.3).

Life cycle assessment

Modelling and calculations were done using the LCA software SimaPro v 9.6 (PRé Sustainability, 2023), with data from the ecoinvent v 3.10 database (Moreno Ruiz et al., 2018). These are both among the most widely used and acknowledged tools for LCA. Environmental impact assessment was conducted by applying the ReCiPe midpoint method with a heuristic perspective (Huijbregts et al., 2016), in order to produce results for a wide array of indicators and not limit the analysis to climate impact. Processes from the database were selected to represent a global average, meaning that they include background data from a mix of different geographical settings. As the aim was to compare the environmental performance of potential changes in the electricity generation system, a consequential approach was taken in the modelling (Plevin et al., 2014; Russell, 2018), using marginal data as far as possible.

The environmental impact of the studied systems is set in relation to the amount of electricity they produce during their lifetime and expressed per 1 kWh electricity. In scope 4 calculations, a counterfactual scenario of alternatively produced electricity is used, assuming 1 kWh from solar or wind power replaces 0.5 kWh electricity from the grid, in accordance with the principle of avoided burden/substitution often implemented in consequential LCA (Schaubroeck et al., 2021). Although the rate of electricity production replacement is sometimes assumed to be 1:1 (Chen et al., 2023; Valencia et al., 2026), a lower number was selected in this case since both PV and wind generate electricity intermittently and the analysis did not include batteries or other technologies for storing or utilizing surplus electricity. To show how the scope 4 impact could vary depending on where the renewable electricity systems are installed, five different geographical settings are considered: Brazil, China, Germany, India and the USA. The selection of countries was based on the rate of additional wind and solar power capacity installed during 2022–2023, where these five countries are in the top six for both wind (Statista, 2024a) and solar power (Statista, 2024b). For the scope 1–3 impacts of PV plants, the electricity production potential was set to vary depending on the location (Table 1). The electricity production potential for wind power plants was assumed to be the same for all locations, as local variations can be more important than differences between countries.

The robustness of the results was assessed through Monte Carlo analysis with 1,000 iterations, using probability calculations to account for uncertainty of input parameters. Parameters were set to a mean value with a lognormal distribution, i.e. a normal distribution of the natural logarithm of parameter values. For a lognormal distribution, the 95% confidence interval is found by varying parameter values between the geometric mean value divided by the square of the standard deviation (variance, σ 2) and the mean value multiplied by σ 2 (Weidema et al., 2013). Considering quality indicators of data (reliability, completeness, temporal correlation, geographical correlation and further technical correlation), σ 2 was set conservatively to 1.2. The uncertainty analysis included material inputs, capacity factors, recycling replacement rate and avoided electricity production from the grid. In addition, a sensitivity analysis was done to assess the influence of specific input parameters on the results, including rate of replaced alternative electricity, system lifetime, capacity factor, capacity decline, and recycling replacement rate.

As the electricity system can be expected to develop and change over time, a set of three future scenarios for the electricity system was added to the analysis, based on the International Energy Agency's World Energy Outlook 2025 (Cozzi and Gould, 2025): “Current policies,” “Stated policies” and “Net zero emissions by 2050” (NZE). The “Current policies” scenario represents an energy system development under policies that are already in place, “Stated policies” considers strategies and planned policies, and “NZE” represents what would be required to keep global warming below 1.5 °C above pre-industrial levels by year 2100. The environmental impact of the three scenarios was calculated by modelling the electricity production mixes in SimaPro, as shown in Table 2. For scope 1–3 calculations, the electricity production potential of an average PV plant was in this case assumed to be equal to a plant located in the USA. The data used to model the three scenarios can be found in the Supplementary Table S1.

Data collection

Life cycle inventory (LCI) data for wind power plants was based on an LCA from the Danish manufacturer Vestas Wind System A/S (Table 3), one of the largest wind turbine suppliers worldwide (Bloomberg, 2020). The type of wind turbine assessed in their LCA is Vestas model “V150-4.2 MW Wind Plant onshore.” The material and process data was quantified per 1 kWh electricity produced using the inventory data presented in the report by Mali and Garrett (2022) and matched with similar processes in the ecoinvent library for modelling in SimaPro (see Supplementary Table S2). For a land-based wind power plant comprising 24 turbines with a capacity rating per turbine of 4.2 MW, they estimated the annual electricity production to be 14,692 MWh, taking into account wake losses of 6% and electricity transmission losses of 2.5% (Mali and Garrett, 2022). The technical lifetime of the wind power plant was set to 20 years, which according to Schön et al. (2016) is the lower limit for a wind turbine's durability. At the end of the wind turbines' service life, 92% of all metals were assumed to be recycled, while the remaining share as well as other materials were assumed to be landfilled or, if combustible, incinerated (Mali and Garrett, 2022). Recycled materials were assumed to replace primary materials at a rate of 80%, considering that an increasing demand for materials could imply that not all recycling leads to replacement. The recycling processes were assumed to require 85% less energy than primary production for copper, 95% less for aluminum and 72% less for steel (cf. Metal Recycling Factsheet, 2019). Data on end-of-life treatment processes for the wind power plant can be found in the Supplementary Table S4. The capacity factor of the wind power plant was initially set to 28%, with an annual decline of 0.6%/year (Do et al., 2022; Germer and Kleidon, 2019; Hamilton et al., 2020).

For the solar PV plant, LCI data was provided by the Swedish municipal utility company Tekniska verken i Linköping AB, based on their open ground 4.9 MW p plant constructed in 2020 (Table 4). The technical lifetime of the PV plant was assumed to be 30 years, in accordance with the International Energy Agency's guidelines on LCA of PV electricity (Frischknecht et al., 2016). The capacity factor was set to 15%−25%, depending on where the PV plant is installed (Table 2), with an annual decline of 0.65%/year (Annigoni et al., 2019; Da Fonseca et al., 2020). Material data used to model the PV plant and its end-of-life treatment in SimaPro are found in the Supplementary Table S3, S5, respectively. As the electricity production varies depending on location, material quantities in Supplementary Table S3 are presented for the whole plant rather than per produced kWh.

Allocation

In the LCA, components were modelled as individual unit processes, enabling a direct division of scope 1–3 environmental impact as well as avoided impact from recycling (scope 4) between the components. For avoided impact due to replaced electricity production (also scope 4), there is no physical relationship between components and their influence on the total avoided impact. Thus, this was allocated using three different parameters as proxy: economic value, mass, and share of scope 1–3 impact (Figure 3). The component costs used for allocation of scope 4 impact were based on data from Stehly et al. (2023) for wind power plants and (Ramasamy et al. 2023) for solar PV plants, respectively (Table 5). The “auxiliary” category includes costs not directly linked to a physical process or component. For PV plants, Ramasamy et al. (2023) summarize these costs as “office work” and “other,” whereas for wind power plants the auxiliary costs comprise “engineering and development,” “project management,” “construction finance,” “contingency,” “warranty” and “OPEX” (Stehly et al., 2023). In the case of mass allocation, no avoided impact is allocated to non-physical processes, while the allocation based on scope 1–3 impact follows the distribution calculated for scope 1–3.

Environmental impact in scope 1–3 and scope 4

For the wind power plant, the scope 4 avoided climate impact from replacing alternative electricity production (negative numbers due to avoided impact) can exceed the climate impact in scope 1–3 in all studied geographical locations (Figure 4). Within 1–7 years, the avoided impact of replaced electricity production balances out the initial climate impact of the wind power plant, after which it can be considered to have a positive effect on the climate. The avoided impact is largest in India and China, where the existing electricity generation systems have a high share of fossil energy sources. The lowest avoided impact is seen in Brazil, where the electricity mix is largely based on hydropower, resulting in a low carbon intensity. Material recycling contributes only marginally to avoided climate impact.

For the PV plant, the scope 4 avoided impact from replaced electricity is larger than the scope 1–3 impact in all locations except Brazil (Figure 5). Like the wind power plant, the avoided impact is largest in India and China. Apart from Brazil, a climate impact “break-even” occurs within 2–17 years for the studied countries. The contribution of material recycling to scope 4 is very small, as most of the materials are assumed to be landfilled.

Figure 6 summarizes LCA results for the impact categories terrestrial acidification, ozone formation, mineral resource scarcity and water consumption, considering a global average electricity system. A full overview of the LCA results, including different geographical locations, can be found in the Supplementary Table S6. The avoided environmental impact of wind and solar power is, in most cases, larger than the scope 1–3 impact in these categories as well. Exceptions can be noted for mineral resource scarcity (wind power) and terrestrial ecotoxicity (solar power), as well as a few other indicators for the PV system in geographical contexts with a relatively low carbon intensity. Overall, it can be stated that both wind power and solar power can contribute to larger avoided impact than the impact they create in production and installation, although there can be tradeoffs and the positive impact is larger in areas with high carbon intensity electricity grids.

Varying the rate of replaced alternative electricity production per kWh has a large influence on the scope 4 avoided climate impact (Figure 7). Decreasing or increasing this rate by 0.20 kWh/kWh increases or reduces the scope 4 climate impact by 40%, respectively. A 30% replacement rate brings the “break-even” between scope 1–3 and scope 4 to 1–12 years for the wind power system and within 2–29 years for the PV system—except for Brazil, where the avoided climate impact of the PV system is less than the scope 1–3 climate impact. With 0.7 kWh replaced per 1 kWh produced, the “break-even” is reached within 1–5 years for the wind power system and 3–25 years for PV, including Brazil.

Figure 8 shows how the climate impact of wind power systems in scope 1–3 and scope 4 recycling is influenced by varying the lifetime, capacity factor and yearly capacity decline. Increasing the lifetime from 20 to 25 years can reduce the climate impact by 20% by reducing the need for material input per delivered kWh, while reducing the lifetime by 5 years increases the impact by 33%. Varying the capacity factor by ±10% and the yearly decline between 0.20 and 1% affects the electricity output of the plant and changes the climate impact by ±2% and ±1%, respectively. The assumption on how much virgin material production can be replaced by recycling materials from the plant at the end of the life cycle can change the results by ±12% when varied between 60% and 100% of the recycled materials.

For the solar PV plant, a similar sensitivity analysis was done for each of the studied countries, since the capacity factor varies depending on location (Figure 9). The recycling rate was omitted, as most of the materials are assumed to be landfilled in this case, making this parameter less influential than for the wind power plant. Increasing the lifetime from 30 to 35 years reduces the climate impact proportionally by 14%, while decreasing it from 30 to 25 years yields a 20% increase. Varying the capacity factor by ±10% changes the scope 1–3 climate impact by around ±5% for all locations. A lower capacity decline changes the results from −3% to −5%, and a higher decline increases the climate impact by +2% to +4%. The influence of the capacity factor and capacity decline is the largest in China and Germany, where the capacity factor for PV systems is the lowest (Table 1).

Environmental impact abatement costs under future scenarios

Figure 10 shows the life cycle climate impact of wind and solar power plants per invested million US dollar (USD), under three future scenarios for the global electricity system development. The smallest avoided impact occurs in the net zero electricity scenario, where there will be gradually less fossil energy sources to replace in the electricity system. In this scenario, the avoided climate impact (scope 4) is around 3–4,000 ton CO 2 eq per invested million USD for wind power and solar power, respectively. In the “Current policies” scenario, the benefit of investing in renewable electricity production is significantly larger, reaching an avoided climate impact of 5,000–6,500 ton CO 2 eq per million USD for the wind power plant, including the margin of uncertainty, and 6,500–8,000 ton CO 2 eq for the solar PV power plant. The “Stated policies” scenario renders scope 4 impacts of 4–6,000 ton CO 2 eq per million USD and 6–7,000 ton CO 2 eq per million USD for wind and PV, respectively. Taking into account the scope 1–3 impact, wind and PV have very similar net results for the global electricity system.

The trends for acidification and photochemical ozone formation are very similar to that of climate impact, showing less avoided impact per invested million USD the less fossil energy that is replaced (Figure 11). Meanwhile, the water consumption and mineral resource scarcity impact are less dependent on the type of energy replaced, giving almost identical results for all three electricity system scenarios.

Allocation of climate impact

Figure 12 shows how avoided climate impact can be allocated between the components and processes in a wind power system, using three different allocation methods for the scope 4 impact of replaced electricity: economic, mass and share of scope 1–3 impact. For scope 1–3, the turbine stands for 62% of the climate impact, followed by transports (22%), foundation (13%) and electrical infrastructure (4%), following the results of the LCA calculations. Allocating the scope 4 impact of avoided electricity production according to system costs, the largest contributors are on the one hand the turbine, on the other hand the “auxiliary” category, including project development and management, contingency, and operation and maintenance. These two each constitute 40% of the total system costs. Operation and maintenance constitute 2/3 of the costs and in the “auxiliary” category and therefore contribute to just over 25% of the total scope 4 electricity impact. Transports, foundation and electrical infrastructure are allocated 13%, 4% and 3% of the scope 4 impact, respectively. With mass allocation, the foundation gets 75% of the credit for avoided climate impact, while 24% is allocated to the turbine and less than 1% to the electrical infrastructure. Transports and auxiliary processes, which are not quantifiable in terms of mass, are not credited with this allocation method. Finally, the avoided impact is allocated according to the distribution calculated for the scope 1–3 impact. The avoided impact of each system component can be considered to be larger than the scope 1–3 impact in all cases except mass allocation, where transport and installation are not allocated any avoided impact.

For the solar PV power plant, the component with the largest scope 1–3 impact is the inverter (51%), followed by the PV panels (42%) and the electrical infrastructure (8%), while other processes contribute less than 1% (Figure 13). With economic allocation, the PV panels are attributed the largest share of the avoided impact (32%). The second largest share of the scope 4 impact (20%) goes to transport and installation, followed by auxiliary processes (planning, management and other related costs) at 17% and electrical infrastructure at 15%. Applying mass allocation, the PV panels get 96% of the avoided impact, electrical infrastructure 4% and other components less than 1%. In most cases, the avoided impact of each system component is larger than the scope 1–3 impact. One exception is the inverter, which only accounts for 4% of the costs and less than 1% of the mass and is thus allocated an equally small share of the scope 4 impact with economic or mass allocation. Allocating the scope 4 impact according to the scope 1–3 distribution solves this, as long as the scope 4 impact exceeds the scope 1–3 impact.

Scope 4 environmental impact assessment

The results of this study demonstrate that avoided environmental impact, which is not covered in the current accounting standard by GHG Protocol and in applications like the Science Based Targets initiative, can be of great importance when assessing renewable energy technologies. Moreover, the results show that it is vital to make accurate assumptions about the alternative scenario, i.e., what is avoided, as pointed out by the World Resources Institute (Russell, 2018) as well as Jabot et al. (2025). In the case of renewable energy generation, the avoided environmental impact is generally larger the more fossil energy sources are replaced. This suggests, as confirmed by the results of this study, that investments in renewable energy should be prioritized in regions with a large share of fossil energy. With regards to sustainable investments, accuracy in reporting is crucial for fulfilling the primary goal of directing capital towards investments with the largest impact (Browder et al., 2023). A consistent and transparent methodology is, furthermore, key to making fair assessments and enabling comparisons between different companies (Young-Ferris et al., 2025). Adequately allocating the contributions to avoided impact is a key part of this, distributing credit between relevant processes and actors. For scope 1–3, and even the recycling part of scope 4, it is usually possible to identify a physical bond between components and emissions, which is not the case with all scope 4 impact, imposing a risk of double-counting. In addition, the linkage to management control of the accounting organization, the manufacturer or the operator may be weaker the further away processes are from the physical bond to the equipment. A transparent and standardized system for allocating and reporting scope 4 could prevent a situation where different actors make claims on the same avoided impact, leading to an overestimation.

In LCA, environmental impact is normally valued equally whether it occurs today or several years from now, to prevent pushing environmental problems onto future generations (Hellweg et al., 2003). When it comes to scope 4 and avoided impact, it could be argued that the sooner emissions and resource use are reduced, the better, with regards to the risks of crossing planetary boundaries and reaching ecological tipping points (Rockström et al., 2009). In contrast to many other sectors, renewable energy production can compensate its scope 1–3 emissions rather quickly by replacing fossil-based energy production. Thus, directing investments to this sector today creates positive effects within the near future. In a longer time perspective, it is more difficult to estimate the impact of investments and activities. When it comes to wind and solar power systems, their efficiency declines over time, while the scope 4 impact can be considered to be reduced as a consequence of the long-term energy transition, with an increasingly lower share of fossil-based electricity to replace. At the same time, as the demand for electricity is increasing in different areas, it could be argued that new electricity production will not replace existing production at a 1:1 ratio and lead to avoided emissions at the same rate. Meeting the increasing electricity demand with fossil fuels would, however, result in a larger impact on the environment. It could also be considered that new electricity production may fill other functions than the current system, such as producing electricity-based renewable fuels (so called e-fuels), thus replacing fossil fuels in other areas. For intermittent energy sources like wind and solar, it could be relevant to add batteries or other forms of energy storage to the analysis, to better utilize the capacity of the power plants and replace more fossil energy.

A broad environmental impact assessment, including a wide array of indicators, reduces the risk for suboptimization and problem shifting. The results of the present study suggest that both wind and solar power can lead to more avoided impact than the impact caused by scope 1–3 activities in many environmental impact categories and geographical contexts. It should be noted that some of the indicators deviating from this, like ecotoxicity, are not as well-documented as, e.g., climate impact, making them more difficult to analyze with certainty (cf. Arvesen and Hertwich, 2012; Pizzol et al., 2017). Overall, the scope 4 impact is often many times larger than the scope 1–3 impact, giving a very short “payback time” of environmental impact over the systems' life cycle.

The presented methodology for calculation and allocation of scope 4 environmental impact could be applied to other systems where avoided impact is created. For example, waste-based bioenergy such as biogas systems have often been shown to give avoided impact by replacing alternative scenarios (cf. Gustafsson et al., 2021; Prussi et al., 2020; Vaneeckhaute et al., 2018). Similar to material recycling (WRI and WBCSD, 2011), other scope 4 impact should be reported side by side with scope 1–3, and not only as a net negative impact (Russell, 2018).

Integration in investment analysis

Broadening the perspective beyond today's business revenue delimitations to cover the activities that cause the most significant environmental impacts, new solutions to business problems could be found (Cerin, 2006). To direct capital towards investments that give the most impact at the lowest risk, accuracy and transparency in reporting are crucial (Browder et al., 2023). Investment analysis can require quite complex decision frameworks and models, weighing in a large number of economic, technical, environmental and social factors to achieve the best and most sustainable outcome and minimize the financial risks (Deng et al., 2021; Ozorhon et al., 2018). In the same way that scope 3 impact indicates the risks associated with investing in a company (Blanco, 2021), scope 4 reveals the opportunities of avoided impact. Currently, none of these are mandatory to report, resulting in varying approaches and quality of reporting. The lack of a consistent methodology to account for scope 4 impact risks diverting capital from systems generating avoided impact, as it makes it difficult to assess and compare (Young-Ferris et al., 2025). In the studied cases of wind and solar power, scope 4 activities, located outside the legal borders of the manufacturing company, represent the most significant environmental impact. Yet this part is not accounted for in the current GHG accounting standard. Thus, today's practices of sustainability investments are insufficient, calling for further development and discussion.

Integrating a larger part of the products' life cycle in reporting should increase companies' awareness and sense of ownership of their impact. Gebhardt et al. (2024) found institutional ownership to be positively related to the quality of climate-related risk disclosure (i.e., scope 3), and possibly also to the quality of opportunity reporting (scope 4). From an investor perspective, Benz et al. (2021) concluded that particularly private investors tend to avoid buying into firms with high climate-related risks. As noted by Cerin and Dobers (2008), investors sometimes lack understanding of what they invest in due to difficulties in assessing the performance—in this case in particular environmental performance along value chains. Increasing the scope and transparency in environmental impact reporting—including allocation of avoided impact among relevant actors—can contribute to reduced information asymmetries (Akerlof, 1970), thus enhancing informed investment decisions and more efficient markets. Enabling and gradually making it mandatory for companies to report scope 3 and scope 4 alongside their scope 1 and 2 impact would make it possible for investors to consider these factors in their decision frameworks.

The allocation methods demonstrated in this paper can be one way of distributing avoided impact between system components, allowing companies behind each of them to claim a share of the positive sustainability effects and making them more attractive to investors. LCA standards prescribe avoidance of allocation or allocation based on physical properties such as mass (International Organization for Standardization, 2006). For scope 4 impact, however, none of these methods would generally be applicable. Firstly, there is no obvious physical link between each part of the system and its contribution to avoided impact, and secondly, processes like transport and installation cannot be weighted based on mass like physical components. Economic allocation is often more suitable and pragmatic, assigning each component and process credit for avoided emissions proportional to their value and attracting investments to all parts of the system. The drawback with economic allocation can be discerned in Figure 13, where the inverter, despite being a key component in a PV system, is only allocated a small share of the avoided impact because it constitutes 4% of the total system costs. The alternative to use the same distribution for scope 4 as calculated for scope 1–3 means that if the avoided impact of the system is larger than the scope 1–3 impact, this applies to all components and processes. On the downside, it means that a larger scope 1–3 impact merits a larger share of the avoided impact, counteracting the incentive to reduce the scope 1–3 impact of those components. A better basis for allocation between components would perhaps be their functional contributions to the system, although this is more complex to determine than the parameters used as examples in this study.

For the energy sector in particular, integrating scope 4 is relevant to support a transition from the traditional, fossil-based systems to more renewable energy generation, enabling societal shifts towards carbon neutral and resource efficient economies. Indeed, this is an example of creative destruction (Schumpeter, 1942), phasing out old technologies in favor of new technologies with less environmental impact. The urgency of the energy transition is clearly showcased not only in recent reports on climate change (Calvin et al., 2023), but also in the broader framework of planetary boundaries developed by Rockström et al. (2009). Mavi (2024) concluded that crossing such thresholds should increase the rate of creative destruction, freeing up resources like competences and materials for the technological and economic transitions. Still, steering investments to more sustainable sectors requires increasing knowledge among investors about what constitutes a sustainable investment (European Commission European Council, 2018; European Parliament European Council, 2020). Integrating scope 4 reporting and a wider environmental impact assessment—e.g. in energy technologies—could be a step towards a transparent and consistent framework for sustainable investment support.

Limitations and future research

This study exemplifies how scope 4 can be calculated for two renewable energy technologies: wind power and solar PV. Material and process data for these systems were based on one manufacturer for each system, which may not be representative for all technology providers and settings. Likewise, the geographical locations used in this study are not representative for all contexts, but are meant to demonstrate a range of conditions. Conclusions about exact scope 4 results should be made with great care, considering parameter and model uncertainties (Heijungs and Huijbregts, 2004) as well as the definition of counterfactual scenarios. Furthermore, the scope 4 calculations are simplified by taking the lifetime electricity production and assuming it replaces average grid electricity at a 1:0.5 ratio. Calculating the electricity production and replacement with a higher resolution, e.g. per hour, can make a substantial difference (Valencia et al., 2026) and should be further investigated for more accurate scope 4 estimates. Future studies should also include battery storage, to assess how that affects the replacement of alternative electricity and how it could be included in the allocation of scope 4 impact.

The midpoint approach of environmental impact assessment provides a broad range of impact categories, including climate impact and other categories commonly used in, e.g., environmental product declarations. However, it does not perfectly reflect all aspects brought up in the Planetary boundaries framework or all the objectives in the EU taxonomy for sustainable investments. Reporting scope 4 according to these would require modifications of the calculation methodology, linking midpoint categories to, e.g., biodiversity.

While this study focused on wind and solar power plants, the methodology could be used to assess other technologies, also in other sectors, that enable environmental impact abatement as well. Further research could investigate the scope 4 impact of biobased energies, information and communication technologies (ICT) and circular technologies, for example biogas systems and material recycling. Efforts could also be directed towards implementing this methodology into real cases, to demonstrate how it would work in practice.

This paper has presented a methodology for calculating avoided (scope 4) emissions, which could be integrated into environmental impact reporting, investment analysis and decision-making processes. By considering not only the direct environmental impact of renewable energy systems, but also the avoided impact they indirectly create, the total impacts and benefits of the systems are clearer and the incentives for investing in them stronger. Then, the potential for the investor shifts from merely avoiding risky assets to reaping the benefits of investing in the technologies and companies that form the backbone of industrial and energy transitions as economies pursue the goals of the Paris Agreement and climate neutrality. Extending the impact assessment from scope 1–3 to scope 4 and from a single-issue climate impact assessment to a holistic environmental impact assessment reduces information asymmetries and provides a better ground for making informed decisions and effectively prioritize environmentally sustainable investments. This approach should encourage capital allocation to investments that deliver actual environmental benefits, rather than just supporting companies with low scope 1–3 climate impact, and enable shared value. Importantly, impact reporting should clearly display both of these parts, as showing only a net negative impact could provide an erroneous and imbalanced view. Moreover, assumptions such as system boundaries, counterfactual scenarios and as well as uncertainties must be transparently disclosed to support sustainable decisions.

Investing in wind and solar power plants can create avoided impact in almost all established environmental impact categories, by replacing alternative electricity generation. The benefit of investing in renewable electricity is particularly great in countries with a large share of fossil energy sources in their electricity mix, suggesting that this is where such efforts should be concentrated to have the most impact. Considering the time perspective, the efficiency of both wind and solar power plants will gradually decrease, while the overall environmental impact of the electricity to be replaced is likely to be reduced over time. This means that the benefits of investing in renewable energy are larger at the beginning of the systems' lifetime. These factors are, however, marginal in relation to the overweight of avoided environmental impacts. In general, scope 4 reporting could be said to be especially relevant for disruptive technologies, where the alternative scenario is far inferior, leaving room for great improvement through avoided impact.

In the absence of a physical connection between avoided impact and system components, data on economic value is often available and can serve as a suitable proxy for dividing scope 4 impact. This type of allocation is crucial to prevent a single actor from shouldering the entire responsibility for avoided emissions or multiple actors claiming the same avoided emissions, but rather to give credit where credit is due. Transparency and standardization are key to reduce the risk of double-counting and overestimation of avoided impact.