The motivation is stark. Biodiversity loss is driven by land and sea use change, direct exploitation of nature, climate change, pollution and invasive alien species, all of which stem from deeper root causes such as consumption patterns, trade and governance. Organizations sit at the heart of that system: direct emissions from roughly 9,000 companies accounted for more than 38 percent of global greenhouse gas emissions in 2021, and the environmental impacts of nearly any organization ripple through international supply chains to every corner of the planet. Yet while carbon footprinting has matured into a routine corporate practice, biodiversity footprinting remains fragmented, with a patchwork of methods that are difficult to compare across regions and value chains.

The core problem the researchers set out to solve is one of perspective. Existing biodiversity indicators are typically regional, meaning they weigh a hectare of degraded land in Finland the same as a hectare in Brazil. The team illustrates the trap with a simple example. Suppose an organization converts 200 hectares in Finland where 25 percent of species abundance remains, and 100 hectares in Brazil where 50 percent remains. A regional metric based on Mean Species Abundance would score both impacts identically at 50 MSA-hectares. But when the same impacts are evaluated with a global metric, the Potentially Disappeared Fraction of Species from the LC-IMPACT database, the Brazilian footprint comes out roughly 42 times larger than the Finnish one, because Brazil hosts far more species found nowhere else on Earth.

That difference matters for decision-making. Regional indicators ignore the global distribution and vulnerability of species, so two organizations with identical regional footprints may have radically different true impacts on global species richness. For a multinational with supply chains spanning dozens of countries, regional metrics make it nearly impossible to prioritize where action would deliver the greatest benefit for global biodiversity. The researchers argue that because trade flows distribute biodiversity impacts worldwide, organizations need indicators that can identify, report and compare impacts across global value chains in a unified way.

The biodiversity equivalent builds on the global Potentially Disappeared Fraction of Species indicator by weighting ecosystem-specific footprints with the estimated number of plant and animal species in each realm. The formula multiplies the terrestrial footprint by 0.801, the freshwater footprint by 0.096 and the marine footprint by 0.102, reflecting the estimated share of the world’s species living in each ecosystem type. The result is a single number that estimates what fraction of the planet’s species are at risk of global extinction from a given activity. Because the values are tiny, they are reported with metric prefixes such as nano, pico or femto biodiversity equivalents, mirroring the way kilograms of carbon dioxide equivalents become tonnes. Crucially, the metric captures the intuition that the same pressure causes less global harm in species-poor regions than in species-rich ones, while equal biodiversity equivalent values mean equal fractions of global species potentially lost, wherever they occur.

Turning the metric into a practical tool required a six-step methodology. First, an organization selects the activities to assess, with system boundaries essentially set by its financial accounts. Second, it quantifies the drivers of biodiversity loss, such as land use or greenhouse gas emissions, caused per unit of each activity, drawing on life cycle assessment and environmentally extended input-output analysis. Third, the location of each driver is traced using regionalized databases like ecoinvent and EXIOBASE, and spatially explicit biodiversity impact factors are calculated by combining the location matrix with LC-IMPACT data. Fourth, the organization’s activity data are harmonized with the LCA and input-output classifications. Fifth, ecosystem-specific footprints are calculated and merged into the biodiversity equivalent. The resulting global impact factors have been released as an open database so that other organizations, experts and researchers can apply the method without rebuilding it from scratch.

The sixth step is the most provocative: assembling a value-transforming financial-environmental impact statement. The researchers argue that environmental accounting today remains superficially integrated with financial reporting and is routinely ignored in management decisions, even though organizational decision-making is ultimately guided by financial accounts. Their solution is to give footprints a monetary cost that becomes visible in the income statement, for instance by financing offsets that match the calculated carbon and biodiversity footprints. Once footprints carry a price, they alter the financial value of the organization itself, forcing senior executives and investors to confront environmental damage in the same ledger where profits and losses live.

To test the framework, the team used the University of Jyväskylä as a living lab. The institution, with 14,600 degree students, 2,800 staff members and an annual turnover of 230 million euros, is comparable in scale to a large corporation. The results were revealing. The university’s carbon footprint fell 15 percent between 2019 and 2023, from 22,723 to 19,405 tonnes of carbon dioxide equivalents, as heat and electricity emissions declined. Yet its biodiversity footprint stayed essentially flat at 58 nano biodiversity equivalents, because a shift to biomass in energy production and rising purchases of items like IT equipment and food offset the gains. The finding underscores how carbon reductions alone can mask persistent biodiversity harm, and how a unified metric exposes trade-offs that separate reporting would hide.

The offsetting demonstration produced the study’s most striking numbers. Using the World Bank’s carbon price for the European Union, about 96 US dollars per tonne of carbon dioxide equivalent in 2023, and a purpose-built biodiversity offsetting cost, the researchers calculated what it would cost the university to offset its 2023 footprint. If the cost were spread over 30 years like the depreciation of a large investment, offsetting in Finland would cost roughly 435.78 million euros annually, while the same global biodiversity offset completed in Brazil would cost around 0.60 million euros. The biodiversity equivalent, being location-independent in the way the carbon dioxide equivalent measures global warming potential, allows impacts distributed across the world to be offset anywhere, and the team is candid that this global offsetting idea is controversial and deliberately simplified for illustration.

The authors acknowledge the risks. Monetizing nature could legitimize further destruction, and carbon offsetting schemes have repeatedly failed to achieve additionality, a problem that plagues biodiversity offsetting as well. Offsetting in species-rich countries more cheaply than in species-poor ones raises uncomfortable questions about equity between the Global South and Global North, even as the researchers argue the method could help expose and mitigate the unsustainable appropriation of resources from the South. The biodiversity equivalent also cannot capture genetic, functional and ecosystem diversity, and it merges drivers that behave differently over time, since land use impacts do not accumulate the way greenhouse gas concentrations do. Still, the team believes the metric could let organizations benchmark themselves against global goals such as the Kunming-Montreal target of reducing extinction rates tenfold by 2050, and that value-transforming accounting, backed by regulation, taxation and mandatory offsetting, is essential to drive the transformative changes in production and consumption needed to halt biodiversity loss.

Subject of Research: Integrated carbon and biodiversity footprint accounting with a unified biodiversity equivalent metric

Article Title: Value-transforming financial, carbon and biodiversity footprint accounting

Article References: El Geneidy, S., Peura, M., Aumanen, V.-M., Baumeister, S., Helimo, U., Vainio, V., & Kotiaho, J. S. (2026). Value-transforming financial, carbon and biodiversity footprint accounting. Journal of Industrial Ecology. https://doi.org/10.1007/s44498-026-00151-8

Image Credits: AI Generated

DOI: 10.1007/s44498-026-00151-8

Keywords: biodiversity footprint, biodiversity equivalent, carbon footprint, financial accounting, environmental accounting, life cycle assessment, EXIOBASE, LC-IMPACT, biodiversity offsetting, species extinction, corporate sustainability, industrial ecology

The study’s authors, led by Lorenzo Rinaldi of the Department of Energy at Politecnico di Milano, built what they call a hybrid life-cycle assessment framework, embedding a detailed process-based model of the crystalline-silicon photovoltaic supply chain into the multi-regional input–output structure of the EXIOBASE database. The distinction matters because the two dominant tools for assessing the environmental footprint of technologies each fail in opposite ways. Process-based life-cycle assessment captures the fine technical detail of manufacturing but truncates the wider economy-wide ripples of production decisions. Top-down input–output models, by contrast, capture the whole economy but are too aggregated to distinguish polysilicon refining from wafer slicing or cell fabrication. The hybrid approach stitches the two together, resolving 18 new photovoltaic activities and 16 new commodities within a model spanning 22 regions, 205 activities and 220 commodities.

The supply chain the researchers resolved is one of the most geographically concentrated in the world. China accounts for more than 80 percent of global cell and module manufacturing capacity and more than 95 percent of the capacity for polysilicon, ingots and wafers, the electricity-hungry upstream stages where raw silicon is purified and sliced into the building blocks of solar cells. The model represents the full chain for monocrystalline silicon technology, which made up more than 98 percent of global production in 2024, from metallurgical-grade silicon through solar-grade silicon, ingots, wafers, cells and modules, along with balance-of-system components, installation and end-of-life treatment. Each stage is parameterised with bottom-up life-cycle inventory data drawn primarily from the IEA PVPS Task 12 database, complemented by NREL inventories and IRENA cost data, and harmonised to a functional unit of one square metre of module with a representative efficiency of 19.5 percent.

Before applying the model to policy, the team verified it against the literature. The carbon footprints of solar electricity produced by the hybrid model fall between 22 and 65 grams of CO2-equivalent per kilowatt-hour across regions, squarely within the ranges reported by harmonised life-cycle assessments and recent assessments by the IPCC, IRENA and NREL. The conventional top-down representation, by contrast, produced irregular and dispersed regional patterns, and in some cases implausible results, because without explicit manufacturing stages it assigned embodied emissions to generic domestic sectors such as electricity generation and construction. The hybrid model also reproduced producer prices of solar electricity more consistently against IRENA levelized-cost benchmarks. A key methodological finding is that conventional input–output models systematically underestimate the footprint of capital-intensive technologies like photovoltaics because the embodied impacts of productive capital, including the modules themselves, do not propagate into per-unit footprints unless capital is explicitly endogenised.

The decomposition of the footprint reveals where the carbon actually lives in a solar panel’s life. Electricity is the single largest contributor, reflecting the carbon-intensive grids powering upstream stages such as polysilicon, ingot and wafer production. Coal-fired power alone accounts for roughly 38 percent of the EU’s photovoltaic electricity footprint, rising to nearly 45 percent when coal extraction is included, and about 58 percent of the EU footprint originates in China. Each stage of the chain inherits most of its footprint from the stage immediately upstream — between 60 and 95 percent in both the EU and China — so delivered solar electricity is dominated by inherited manufacturing impacts: about 74 percent of the 51 grams per kilowatt-hour in the EU27 and 62 percent of the 65 grams in China. This cascading structure is precisely why relocating downstream assembly changes so little of the total footprint as long as upstream stages stay abroad.

When the researchers ran the Net Zero Industry Act scenario, comparing a 2030 baseline against a 2030 configuration in which 40 percent of module and upstream demand is met domestically, the reconfiguration proved strikingly uneven. EU module output rises from below 1 percent to about 10 percent of global production, but the EU share of cells, wafers, ingots and polysilicon remains at only a few per cent or less. European module factories would continue to rely heavily on imported intermediate inputs from Asia–Pacific regions, and the share of the EU’s photovoltaic electricity footprint originating within the EU climbs only from about 16 percent to 22 percent — meaning nearly 80 percent of embodied emissions remain tied to imported upstream stages even under the policy.

The economic picture is similarly asymmetric. EU value added increases by approximately €4 billion, with roughly half arriving as employee compensation, indicating that expanded module manufacturing, installation and downstream activities are relatively labour-intensive. China experiences the largest absolute loss, about €3.5 billion or 0.06 percent of its GDP, while South Korea, India and other suppliers of intermediate components benefit indirectly. Employment tells a similar story with a sharp asymmetry: the EU gains about 65,000 jobs while China loses about 229,000, a gap reflecting the fact that the Chinese industry spans an integrated set of upstream and downstream stages whereas the reshoring scenario expands mainly downstream activities in Europe. A substantial share of the additional European activity still leaks abroad through continued imports of cells, wafers, polysilicon and key materials such as glass, aluminium and precious metals.

The sensitivity analysis tested whether these findings were artefacts of scenario design. Sweeping the EU domestic share of upstream photovoltaic stages from 0 to 100 percent showed both the footprint and the recovered value responding smoothly, with no threshold at which leakage stops. Even full upstream reshoring would lower the EU footprint only from 42.8 to 39.9 grams of CO2-equivalent per kilowatt-hour, and the 40 percent target captures about €2 billion of the roughly €7 billion of value added recoverable under complete upstream reshoring. Physical parameters mattered too: for the EU, module efficiency is the dominant uncertainty, cutting the footprint by up to 14 percent at 24 percent efficiency, while for China the capacity factor dominates, with a 19 percent swing reflecting divergent yield estimates for Chinese sites.

The authors conclude that the Net Zero Industry Act should be understood primarily as an industrial capacity and supply-chain resilience policy rather than a climate instrument or a macroeconomic stimulus. The roughly 0.6 megatonnes of CO2-equivalent saved — about 5 percent of EU photovoltaic-related emissions and 0.02 percent of total EU greenhouse-gas emissions — largely reflect a geographic redistribution of manufacturing emissions rather than net global abatement, especially since photovoltaic electricity is already low-carbon and the environmental advantage of European manufacturing is likely to narrow as China’s grid decarbonises. If domestic value creation is the goal, the researchers argue, policy support should extend selectively to the electricity-intensive polysilicon, ingot and wafer stages that currently remain offshore, and the industrial strategy should be aligned with climate instruments such as the EU Emissions Trading System and the Carbon Border Adjustment Mechanism.

Beyond the specific policy verdict, the study carries a broader methodological message for anyone assessing clean-energy industrial strategy. Reshoring’s downstream concentration, persistent upstream import dependence, and the redistribution of emissions and value added across regions would be poorly captured by conventional models in which photovoltaic electricity generation is decoupled from its manufacturing chain. By resolving every stage from sand to silicon to module, the hybrid framework traces policy shocks along the global chain and exposes spillovers, bottlenecks and trade dependencies that aggregated models miss entirely. As the United States and India pursue parallel re-regionalisation of clean-energy supply chains, the finding that resilience comes at the price of modest climate and economic returns is likely to resonate far beyond Brussels.

Subject of Research: Environmental and socio-economic assessment of solar photovoltaic manufacturing reshoring in the EU under the Net Zero Industry Act using a hybrid input–output life-cycle model.

Article Title: Environmental and socio-economic implications of solar photovoltaic reshoring under the EU Net Zero Industry Act: a hybrid input–output assessment

Article References: Rinaldi, L., Merletti, R., Citterio, C., Golinucci, N., & Rocco, M. V. (2026). Environmental and socio-economic implications of solar photovoltaic reshoring under the EU Net Zero Industry Act: a hybrid input–output assessment. Journal of Industrial Ecology. https://doi.org/10.1007/s44498-026-00175-0

Image Credits: AI Generated

DOI: 10.1007/s44498-026-00175-0

Keywords: solar photovoltaics, Net Zero Industry Act, reshoring, hybrid life-cycle assessment, EXIOBASE, input–output model, carbon footprint, supply chain, value added, employment, EU industrial policy, photovoltaic manufacturing