Minviro helps global manufacturers and resource companies measure, verify, and reduce environmental impact across complex supply chains using primary and secondary data. Their XYCLE platform delivers auditable life cycle insights that stand up to regulatory and investor scrutiny.

With deep expertise in batteries, mining, automotive, and electronics, Minviro supports some of the world’s largest enterprises in turning sustainability into a competitive advantage.

In this interview, Robert Pell shares his vision to scale high-quality sustainability analysis to drive measurable impact reduction, the limitations of black box data, and how life cycle assessment (LCA) delivery has changed.

Read on to discover where Minviro meets ecoinvent.

Introducing Robert Pell, Founder and CEO of Minviro

Robert Pell founded Minviro during his PhD to ensure that the energy transition doesn’t simply shift impacts upstream, but is instead grounded in transparent, data-driven decision-making from materials to market.

As CEO, Robert’s role is to ensure the product is scientifically rigorous and commercially relevant. He safeguards that XYCLE is built on robust LCA methodology, while also functioning inside real businesses, supporting decision-making, enabling ecodesign, strengthening governance, and meeting tightening regulatory requirements.

He leads the product vision and long-term direction of the company, defining how life cycle intelligence becomes core infrastructure for global supply chains. To achieve this, he works closely with product, engineering, and modeling teams to ensure methodological integrity. He also communicates with clients, regulators, and industry stakeholders to anticipate where market and policy pressures are heading.

1. Please describe Minviro’s core activities and offerings, including your LCA tool “XYCLE”.

Minviro provides the scientific and digital infrastructure required to operationalize LCA across complex industrial supply chains. We deliver this through three integrated solutions: consultancy, software, and data.

We started as an LCA consultancy focused on complex industrial supply chains, particularly in sectors such as battery materials, mining, chemicals, and advanced manufacturing. Through this work, we developed deep expertise in modeling raw materials and industrial production routes. That hands-on experience with enterprise clients exposed the limitations of traditional LCA tools and directly shaped the development of our software.

XYCLE is our LCA software, built by practitioners to embed LCA across organizations. It enables companies to build transparent, ISO-aligned, and regulatory-ready LCA models at scale by combining primary supplier data with high-quality secondary databases such as ecoinvent. ecoinvent data forms a structured backbone of our background modelling environment, ensuring consistency, methodological integrity, and global comparability across complex supply chains.

XYCLE is designed to support ISO-compliant modeling, product carbon footprint requirements, and evolving regulations like the EU Battery Regulation, while remaining practical for enterprise use.

2. What makes LCA such a powerful tool for understanding environmental impacts, and how have you seen the field evolve during your career?

At a high level, LCA is a structured approach to better decision-making across complex systems. It helps businesses understand the environmental consequences of choices that span multiple processes, suppliers, and regions. That ability to make informed decisions is what industry and policymakers increasingly need.

What has changed significantly is how LCA is delivered. It used to be largely one-off, static studies conducted in isolation. Today, it is moving toward live, connected ecosystems where suppliers are integrated, primary data flows directly into models, and results update dynamically. That shift enables faster, more consistent decision-making and embeds LCA in operations rather than treating it as a standalone report.

We are entering a phase where environmental impact data becomes a dynamic operating layer within organizations, shaping strategy and supply chain choices rather than merely recording them.

3. The LCA data landscape ranges from simple emission factor databases to full unit process inventories. How do you see these different sources serving different purposes? Where does ecoinvent fit in that ecosystem?

Different data sources serve different levels of decision-making.

Simple emission factor databases are useful for rapid screening, early-stage estimates, or high-level reporting. They provide speed and simplicity, which can be appropriate when the goal is directional insight.

Full unit process inventories serve a different purpose. They provide transparency, technological detail, and geographic specificity. That level of granularity is essential when modeling complex supply chains, conducting scenario analysis, or meeting regulatory requirements that demand traceability.

Within XYCLE, this is combined with proprietary datasets and primary supplier data to improve representativeness and decision relevance.

4. When your clients need to make high-stakes decisions or defend their environmental impact assessments to investors and regulators, what role does data quality play?

As sustainability claims move from voluntary reporting into regulated disclosure, the cost of weak data increases dramatically. Data quality directly affects strategy, capital allocation, and the ability to defend results to investors and regulators.

Many companies set decarbonization targets based on the data available at the time. As modeling improves—becomes more dynamic and more representative—LCA is moving from one-off reports to live, connected systems embedded in operations, and results can change accordingly. In many cases, that fluctuation reflects better science and a more accurate understanding of impacts. However, organizations often see these changes as a risk because they may affect when targets are achieved or how past decisions are perceived.

Without a clear understanding of data quality, representativeness, and methodological assumptions, decisions can be misinformed. High-quality, transparent data allows companies to explain why numbers evolve over time and ensures that strategy is based on robust evidence rather than unstable assumptions.

5. Transparency and traceability are often cited as critical in LCA. How do your clients benefit from being able to trace results back to underlying process data?

Being able to trace impacts back to the underlying process or inventory is fundamental. It allows companies to see exactly where impacts arise at a specific production step, technology, region, or supplier rather than relying on a single aggregated result.

When traceability is combined with scenario analysis and deeper interpretation, it becomes a powerful decision tool. Clients can test alternative sourcing routes, production technologies, or energy mixes and understand how those changes influence the overall footprint. That moves LCA from static reporting to informed strategy.

Black box solutions do not provide that level of insight. If you cannot see how a result was built, you cannot properly audit it, and trust is reduced. As automation increases, maintaining methodological transparency becomes even more critical. For regulatory reporting and investor scrutiny, organizations need to demonstrate how results were constructed.

In XYCLE, traceability is embedded in the architecture rather than added as a reporting feature. Every process link, background dataset, and primary supplier input remains visible and traceable within the modeling environment. Users can follow data flows through the system, review assumptions and data quality indicators, and export structured outputs that retain this traceability.

Importantly, this transparency is paired with structured access controls. Different user roles, such as model owners, contributors, and viewers, allow organizations to involve suppliers, internal teams, and stakeholders in a controlled way. Contributors can upload and verify primary data without altering model structure, while decision makers can review validated results with full traceability. This ensures both collaboration and governance.

6. XYCLE works with full unit process and LCI data rather than aggregated emission factors. What does that unlock for your users that simpler tools can’t deliver?

Working with full unit process and LCI data removes the black box element. Instead of relying on a single aggregated emission factor, users can review the underlying inventory, understand how each process contributes to impact, and customize datasets to reflect specific suppliers, technologies, geographies, or forward-looking assumptions. That level of methodological visibility is not possible with simplified, factor-based tools.

What this unlocks is increased control and stronger auditability. Companies can clearly demonstrate how results were built, document assumptions, and justify changes over time. It also allows them to plan with confidence, including testing alternative sourcing routes, energy mixes, or production pathways while maintaining a clear, defensible link between data, methodology, and outcome.

For enterprise users, this means moving from estimated averages to a supplier-specific strategy. Environmental performance becomes something they can engineer and optimize rather than approximate.

7. Many companies start with simple carbon calculators that give them a number but not much else. Can you share an example where a client needed to go deeper to trace impacts through their supply chain, and what that enabled?

Most companies start with a simple carbon calculator because it’s quick. You get a number, you can report it, and you can say you’ve measured your footprint. The problem is that the number doesn’t tell you much about what the confidence is, whether it reflects reality, or where to act.

We worked with a large original equipment manufacturer (OEM) whose footprint was dominated by supply chain impacts. On paper, they had the data covered. In reality, most of it was based on spend averages and generic emission factors. That was fine for disclosure. It wasn’t useful for decision-making.

They had hundreds of tier 1 suppliers, and the real impact wasn’t neatly confined to that level. The hotspots were further upstream, in specific metal refining routes, precursor chemistries, and energy mixes tied to certain regions. “Purchased goods and services” as a line item told them nothing about which material, which process, or which supplier relationship actually mattered.

We rebuilt the model properly. That meant disaggregating components to the process level using established LCA methodology and good background data, then prioritizing where primary supplier data would genuinely change the result. Instead of asking 500 suppliers for everything, we identified the 20–30 suppliers that were driving most of the impact.

That changed the conversation internally. Procurement could identify which suppliers were structurally higher carbon. Engineering could see where design changes would reduce impact. Sustainability could move from broad Scope 3 targets to specific reduction pathways grounded in actual production routes.

It wasn’t about producing a more sophisticated footprint for the sake of it. It was about operationalizing supplier data. Once you can trace impact through the value chain with sufficient scientific depth, you can prioritize properly and engage suppliers on concrete targets rather than abstract ones.

8. Looking at how your most sophisticated clients use XYCLE, what becomes possible when teams move beyond surface-level sustainability metrics?

When teams move beyond headline metrics, sustainability stops being retrospective and becomes strategic. The most advanced organizations use XYCLE to model entire product portfolios at once, running mass bill of materials (BOM) LCAs in seconds to see where real risks and opportunities lie. They connect suppliers directly into the ecosystem, extending traceability beyond tier 1 and addressing hotspots that may sit two or three tiers upstream.

Most importantly, they use LCA before decisions are locked in. Procurement, engineering, and sustainability teams test sourcing routes, production pathways, and future scenarios dynamically, understanding trade-offs before capital is committed or contracts are signed. At that point, environmental impact becomes something you design for and not something you report on after the fact.

Environmental performance will increasingly be treated with the same rigor as cost, quality, and engineering specifications. Organizations that embed it into decision systems now are not only improving compliance, but they are building a structural competitive advantage.

Interested in becoming an ecoinvent partner? Contact us.

Introducing Johnson Gui

Johnson’s sustainability background includes experiences from around the world, which helped to build his wide-reaching perspective on LCA.

His career has been a single, unbroken thread: making environmental assessment work inside real industry. From studying environmental engineering in China and industrial ecology in Sweden, to working at ArcelorMittal in France and Baosteel in China—the world’s two largest steelmakers—he has stayed at the exact point where LCA meets the factory floor.

Johnson has explored how digital and information technologies could be combined with traditional LCA and consulting approaches. He seeks to support small and medium-sized enterprises in managing their carbon footprints and broader sustainability issues through technology.

This motivation led Johnson to found E-C Digital and HiQLCD. Their vision is to apply digital and AI technologies to make LCA easier to use, more accessible, and more affordable.

Introducing Ondrej Szabo

Ondrej has a professional background in managing and leading go-to-market motions for data businesses. Before joining ecoinvent in 2024, he was a newcomer to the sustainability sector.

His core experiences are at the helm of translating, transforming, and future-proofing legacy data businesses into Data as a Service (DaaS). Today, his work is focused on running data businesses successfully in the age of AI.

Johnson, your product, Jimu, has an interesting translation in English. Can you tell us the story behind it?

Our company has a clear vision: we use digital and AI technologies to translate professional sustainability and LCA knowledge into tools that are practical and easy for non-specialists to use.

We initially focused on the steel sector, where we developed a sector-specific LCA tool called Jimu Life Cycle Assessment. “Jimu” means Lego in English, and the idea is similar: each “block” represents the smallest unit process, such as a specific piece of equipment. We standardize industrial equipment and processes into these digital blocks, which are already linked to LCA data, product category rules (PCRs), and allocation methodologies.

This block-based approach allows engineers inside a company—such as EHS or ESG engineers who are not LCA specialists—to complete highly professional LCA calculations. At the same time, it significantly reduces costs, as traditional LCA software can be prohibitively expensive for small and medium-sized enterprises in China.

This solution was quickly adopted by the market after our 2017 launch, and we now serve roughly two-thirds of the steel sector. We then realized that the Jimu “block” concept could be applied to other industries as well. From there, we expanded into the power sector and now cover a wide range of manufacturing industries, including batteries, electric vehicles, and solar panels. This marked the first phase of our company’s development.

As we continued to grow, we recognized another major challenge: for most companies, 70–80% of emissions come from Scope 3 sources. While our tools are strong in on-site data collection and modeling, accurate Scope 3 assessments also require high-quality background databases. Despite China being a global manufacturing hub, there is still a lack of reliable and localized life cycle data.

Our long-term goal is to build a Chinese-specific life cycle inventory (LCI) database that meets the same principles of transparency, quality, and continuous improvement that organizations like ecoinvent have upheld for decades.  In many ways, ecoinvent has served as a benchmark and a teacher for us in how high-quality databases should be developed and maintained.

Ondrej, from your perspective, what are the key advantages of the collaboration between ecoinvent and HiQLCD?

China is fueling the global economy as the center of production. Therefore, to achieve a more sustainable planet, enabling users and businesses of all sizes in China to access science-backed environmental data is paramount.

China is a challenging market for Swiss and European enterprises to enter, which is why finding valuable partnerships is so important. Johnson and I have known each other for over a year now, and I’m grateful for the several roundtables in Shanghai he has hosted with stakeholders from the industry, government, and sustainability sphere, because it all informs ecoinvent’s strategy.

As Johnson has previously stated, we need to ensure that we’re not just delivering factors or numbers that somebody can use to create a report. We want to provide the market with actionable, high-quality data that can be used to decarbonize the industry.

Johnson, what is the main challenge in the Chinese market that you are working to address?

One of the biggest challenges in China today is that sustainability has become very popular very quickly. There is a strong commitment and clear direction from the Chinese government to make the economy more sustainable—but turning that ambition into real, credible action at the company and factory level is not easy.

In the early stages, many organizations claimed they could provide carbon footprint or sustainability solutions, but the underlying methodologies varied widely. Some companies calculated emissions using only organizational Scope 1 and 2 data, while others relied on emission factors collected from websites, articles, or secondary sources without proper validation. As a result, companies were producing numbers—but the key question was whether those numbers were trustworthy and usable.

Building accurate models takes time, deep industry understanding, and close cooperation with companies across different sectors. Fortunately, China’s manufacturing ecosystem is also our strength. China has one of the most complete industrial supply chains in the world—producing more than half of global steel, a significant share of aluminum, and dominating key areas including batteries and rare earth materials. This gives us the opportunity to build high-quality, sector-specific data blocks—but it still requires time and sustained effort.

Another major challenge is the expectation around speed. There is a strong cultural drive in China to move fast and deliver results quickly. However, when building a high-quality life cycle database, speed cannot come at the expense of quality.

ecoinvent and other European pioneers have spent decades building, refining, and continuously updating their databases. High-quality data is not created overnight. Together with partners like ecoinvent, we believe there is still important education work to be done—across government, industry, and the broader stakeholder community—to align expectations around what “quality” really means in sustainability data.

Ondrej, looking ahead, what further developments do you envision to strengthen and expand the collaboration?

Powering the Jimu LCA tool with ecoinvent data is already a major step forward, but we need to think bigger. China’s carbon-intensive industries are represented by huge, partially state-owned enterprises. We need to find new, innovative licensing models. Think bigger, better. This will ultimately support Johnson in selling enterprise cloud applications to these critical players.

Finally, the next step is to sit together and think more broadly about combining data assets across geographies, and then to ensure a productive and forward-looking approach regarding AI applications.

Johnson, what qualities are your customers looking for when it comes to their data?

Customer expectations around data quality have evolved significantly. In the past, many companies simply wanted a carbon footprint value. As long as they had a number expressed in CO₂ equivalent, that was considered sufficient.

Today, that mindset has changed. More and more clients care deeply about the quality of the underlying data—not just the final value, but what sits behind it. They want to understand the data sources, the assumptions, the modeling approach, and whether the results are credible and defensible.

As a result, transparency, full documentation, and consistent methodology have become key requirements. Clients increasingly recognize the importance of high-quality databases, such as ecoinvent, precisely because of their rigorous documentation, transparent processes, and well-established modeling standards.

This shift is also shaping our own work. We are focused on providing high-quality, well-documented data to the market, aligned with the same principles of consistency and transparency. In this context, ecoinvent is widely regarded as the leading reference, and its acceptance in the Chinese market continues to grow.

At the same time, data quality alone is not enough. Proper use of high-quality databases requires education and clear guidance. In many cases, Chinese clients are willing to use these databases correctly, but they need better explanations, training, and support. As adoption increases, providing education and sharing best practices across the community becomes just as important as the data itself.

Johnson, can you provide some examples of how your customers leverage your technology to meet their sustainability goals?

Today, most of our enterprise customers require private cloud or on-premise deployments. This is a distinctive feature of the Chinese market—large companies need their LCA and carbon management systems to be fully integrated into their internal IT infrastructure, with ecoinvent data securely embedded within their own environments. Working closely with ecoinvent, we have developed a private cloud solution that meets these requirements while maintaining full data integrity and licensing compliance.

A good example is our work with Baosteel. Together, we developed what we believe is the first real-time carbon labeling system in the steel industry. Before this system was implemented, Baosteel had a dedicated LCA team of five people who could calculate the carbon footprint of about nine complex steel products per year. Annual updates were already difficult, as the calculations were done using traditional LCA software.

After implementing the real-time carbon labeling system, Baosteel can now calculate the carbon footprint of approximately 330,000 steel products per month at just one factory—the Baoshan facility. This factory alone produces close to 10 million tons of steel per year. Compared to fewer than ten products annually, this represents a dramatic improvement in both scale and efficiency.

The system has been verified by TÜV and integrates data from more than twenty internal systems, including financial systems, energy and environmental systems, manufacturing execution systems (MES), and supply chain systems. These data are collected, cleaned, preprocessed and then fed directly into the LCA models, enabling near real-time results. This will also be very valuable for regulators and local governments. More granular and up-to-date data support better decision-making, more accurate management, and more effective progress toward sustainability goals.

We see a clear trend: industry leaders are moving toward real-time, high-resolution carbon labeling systems. These systems go beyond traditional LCA software by providing faster, more granular results and enabling batch- or contract-based carbon footprint calculations.

Looking ahead, we believe real-time carbon labeling will become a standard requirement for new factories and production systems. From around 2027, local governments in China are also expected to introduce clearer requirements related to carbon emissions and carbon intensity at the regional level. These requirements will be passed down to individual companies and even reflected in management KPIs.

Johnson, tell us about your latest package for corporate businesses, how ecoinvent data is involved, and the benefits for your users.

ecoinvent is widely recognized as one of the most reputable and high-quality life cycle databases in the world, and we consider ourselves very fortunate to work closely with ecoinvent to bring this level of data quality to the Chinese market.

As ecoinvent’s authorized partner in China, we are currently the only company that offers ecoinvent data through fully compliant licensing structures with transparent pricing and clear policies tailored to local market requirements. Together with ecoinvent, we have also innovated a private cloud deployment model that allows large enterprises to integrate ecoinvent data securely within their own IT infrastructure—a critical requirement for corporate clients that place a strong emphasis on intellectual property protection, data security, and regulatory compliance. For these companies, using high-quality and well-documented data through authorized channels is not optional—it is essential.

For that reason, we prioritize ecoinvent data across our corporate packages, alongside our own high-accuracy datasets where appropriate. Our approach is to maintain quality step by step, rather than relying on generic emission factors or low-transparency databases. For us, ecoinvent represents quality, credibility, and long-term trust.

Beyond large enterprises, we are also focused on accessibility. Last year in Shanghai, we worked to integrate ecoinvent data into a local public service platform, allowing more small and medium-sized enterprises to access professional LCA calculations. While industry leaders often have dedicated LCA teams and already understand the value of ecoinvent, smaller companies typically lack these resources—even though medium-sized private enterprises account for around 70% of employment and a significant share of real economic activity.

Ultimately, we believe ecoinvent is the reference choice for high-quality, general-purpose LCA databases. As ecoinvent’s authorized partner in China, we are committed to helping companies of all sizes access, subscribe to, and properly use ecoinvent data. Looking ahead, we hope to deepen our collaboration further—expanding both the reach and the depth of ecoinvent’s presence in the Chinese market, and ensuring that sustainability data of the highest quality is available to every company that needs it.

Johnson, what is your team looking forward to in the next year or two?

Over the next year or two, our focus is on two main priorities.

First, we want to continue educating the market and expanding access to professional LCA methodologies and high-quality databases. Many of these companies do not have in-house LCA expertise or the resources to build dedicated sustainability teams. Helping them adopt credible, professional approaches to sustainability remains a key goal for us.

Natcap plans to integrate ecoinvent’s industry–leading Life Cycle Inventory (LCI) database into its methodology, enhancing the scalability, credibility, and coverage of its nature-related impact assessments.  

This will enhance Natcap’s ability to model impact intensity and magnitude scores across commodities and supply chains with greater precision. 

Quotes on the Partnership

Read Natcap’s press release to learn more about…

– Solving the Coverage and Scalability Challenge 

– The benefits of embedding ecoinvent’s LCI data into a data platform 

– How Natcap’s platform supports organizations towards sustainability 

Thomas is one of ecoinvent’s Database Content Leads. He works on the implementation of life cycle impact assessment (LCIA) methods in the database and corresponding inventory modeling developments. Previously, he led ecoinvent’s participation in the ORIENTING project and supported the nomenclature group of the GLAD project of the Life Cycle Initiative.

In this post, Thomas shares his insights from his five years of working with ecoinvent.

If Thomas’ ecoinvent story inspires you, check out our careers page for more information about our current job openings. 

ecoQuery now features semantic search, a smarter way to find life cycle inventory data that understands what you mean, not just what you type. Users no longer need to recall precise search terms to retrieve the information they need quickly.

Why Easier Search Matters for LCA Practitioners

Time spent hunting for the right dataset can slow down or impact the precision of your assessments. Semantic search lowers the barrier to finding exactly what you need, whether you are a seasoned ecoinvent user or exploring the database for the first time. It’s especially useful when working across sectors or in unfamiliar territory.

Try Our New ecoQuery Search Feature

Semantic search is now live. Log into ecoQuery and search for previously hard-to-locate datasets—like “aluminum recycling” or “biofuel production”—and see how semantic search surfaces relevant datasets instantly.

As always, we would love to hear your feedback. Let us know how semantic search works for you.

Metal production has been found to contribute approximately 10% of global climate impacts and 12% of particulate matter-related health effects. To better understand the environmental contributions of metal production and processing, rigorous life cycle assessment (LCA) evaluations are vital.

The ecoinvent database provides life cycle inventory data that enables researchers and product designers to understand the environmental impacts of a product or process. The first steps towards creating a more sustainable product or workflow begin with knowledge about where the greatest impacts in the supply chain reside.

In our latest video, Valeria Superti (Project Manager) and Antonella Polimeno Camastra (Data Analyst) describe the data we have available for the metals sector in ecoinvent version 3.11, alongside their support for the operational processes and strategy of the database.

Our database supports environmental assessments in the metals sector with over 400 datasets across twenty geographic regions, documenting processes from the mining and beneficiation of natural resources to the production of metal and mineral commodities, including recycling.

Watch the video now to learn more about our metals sector.

Interested in the future of the ecoinvent metals sector? Our latest release, version 3.12, is now available with new and updated information.

Creating regionalized data is essential to improving the accuracy and relevance of life cycle assessment (LCA) studies. Regionalization captures site-specific variations in the geology, technology, energy mix, transport, and regulatory context, and it enables the use of location-specific characterization factors.

The report investigates the continuing role (and limits) of global averages for mining, refining, and smelting, identifying sources and approaches, benefits of regionalized life cycle inventories (LCIs), how processing steps vary by ore and region, and challenges to compiling regional LCIs. It also explores how to compile more geographically representative LCIs, best practices for integrating granular data, and where models could help.

The work screens more than 100 published sources and complements them with fourteen expert interviews to add practical and implementation-focused perspectives.

Regional LCI vs Global Average Datasets

When considering global trends or evaluating a singular operation compared to the average, global average datasets have value when a commodity’s processing is relatively standardized across sites.

However, reliance on global average datasets can lead to significant under- or over-estimation of environmental impacts. For some materials, the process sequence is uniform enough that a global dataset can be serviceable, but where routes and site conditions vary widely, averages quickly become misleading. For example, in the case of lithium, inventories should be built at the process- and site-level to reflect local geology, brine chemistry, energy systems, and operating conditions. This is specifically important for metals used in batteries in light of the EU battery passport, which will become a legal requirement for some battery technologies in 2027.

To create assessments that drive meaningful and sustainable action, greater transparency and accuracy are required. In this report, regionalized data for metals and mining are highlighted as vital for competitive business intelligence and regulatory compliance.

Overall, the study suggests a great need for the regionalization and validation of data, but it also shares the obstacles to overcome before the goals can be achieved, including thoughts on the industry-academia disconnect and regulatory fragmentation.

Read the report now to better understand why regionalized data is essential, alongside key findings that will develop the future life cycle inventory data for metals.

ecoinvent and the Future of Environmental Data

At ecoinvent, we believe that sustainability decisions are only as strong as the data behind them, and that accuracy, transparency, and scientific rigor are mission-critical. Future ecoinvent data releases will bring increased granularity across global value chains by advancing in three key areas:

• Better regionalized precision
• Significant scale of high-quality data
• Greater flexibility and adaptability

To learn more about how ecoinvent will support the future of LCI data across the many sectors of our database, discover the ecoinvent vision with our downloadable whitepaper and webinar recording.

Agricultural, fisheries, and livestock systems play a vital role in biodiversity conservation, biogenic carbon balance and sequestration, and generate value across local and global economies. However, according to IPCC’s Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas Fluxes in Terrestrial Ecosystems, agriculture is responsible for approximately 23% of all human-induced greenhouse gas emissions.

Understanding the many impacts of the processes involved in this sector, of which greenhouse gas emissions are included, can help organizations choose more sustainable outcomes in their value chains.

To achieve a better understanding, ecoinvent data is used by industries, researchers, and policymakers to form a robust foundation for environmental assessments, innovation, and evidence-based decision-making.

In our latest video, which you can watch below, our agriculture, fisheries, and animal husbandry sector experts at ecoinvent, Francesco Cirone and Andreas Giakoumatos, provide an overview of the ecoinvent database and its developments.

Our database contains over two thousand datasets for agriculture, fisheries, and animal husbandry, covering over four thousand unit processes. This sector plays a central role in ensuring food security, nutrition, and human health, and includes more than 1,200 datasets for crops, more than 900 datasets for fertilizers, pesticides, machinery related to agriculture and irrigation, and almost 200 datasets for animal husbandry and fisheries. This data supports life cycle assessments for various products and services, enabling sustainable decision-making in the value chain.

Within the sector, and of great importance to scientific impact assessments, are several main challenges, such as improving pesticide emission models or balancing biogenic carbon. Our agriculture sector experts are contributing to the discussion through their work on several methodological advancements to improve the data modeling on this topic. They aim to support users in managing the accountability of emissions more precisely.

Our mission is to promote and support the availability of high-quality environmental data worldwide to support informed sustainability decisions.

Discover the agriculture, fisheries, and animal husbandry sector of the ecoinvent database to learn about how our data supports sustainable decision-making for a greener future.

Persefoni is a leading Sustainability Management SaaS and AI platform, designed to meet escalating regulatory and stakeholder expectations around sustainability. They help companies and financial institutions to measure and manage carbon emissions with precision, to generate trustworthy and audit-ready sustainability reports, and to engage supply chains for decarbonization strategies.

In this interview, Caroline explains the benefits for clients when integrating ecoinvent’s detailed life cycle data into Persefoni software to enhance supply chain assessments. Her experience in guiding clients through their carbon accounting journeys shines through in her responses, which always keep the client in mind.

Read on to discover where Persefoni meets ecoinvent.

1. Caroline Bartlett, please tell us a bit about your background and what led you to the sustainability sector.

My path into sustainability began with a love for ecology and conservation biology, which shaped my academic focus. However, I quickly realised that achieving real, wide-reaching impact required working with businesses to help transform their practices. Nearly two decades ago, I transitioned into environmental consulting before recognising that scalable impact would come through technology—making high-quality emissions data accessible to every organisation.

2. What does your role at Persefoni entail?

The climate reporting landscape is constantly evolving, and staying aligned with the latest science and standards is critical. In my role, I guide clients along their carbon accounting journeys—whether they’re just getting started and need foundational support, or are more advanced and seeking to refine complex, detailed analyses.

Equally important is ensuring our software evolves in step with regulatory changes. Together with our team of climate experts, I help feed market insights and client needs back into our Product team, ensuring Persefoni remains ahead of the curve.

3. What makes Persefoni AI such a powerful tool for understanding environmental impacts?

Our platform simplifies carbon accounting by streamlining data ingestion and delivering fast, accurate GHG calculations using globally recognised methodologies like the GHG Protocol and PCAF. Built-in artificial intelligence (AI) automatically flags anomalies and processes thousands of transactions in seconds, removing the need for manual interventions behind the scenes.

Insights are presented through intuitive dashboards and automated reports aligned with leading frameworks and standards such as the CSRD, CDP, and SECR, enabling clients to move from data to disclosure with confidence.

4. How was the partnership with ecoinvent established? How do Persefoni’s customers use ecoinvent data through your solutions?

ecoinvent is widely regarded as one of the most robust and trusted sources of life cycle GHG emissions data (amongst other data!). It was important to Persefoni to ensure our customers could access this level of granularity and transparency.

Persefoni clients typically use ecoinvent to enhance supply chain assessments, enabling them to identify emissions from specific purchases (across thousands of products, components, or raw materials, to name a few). This allows for a more refined, process-specific view of emissions.

5. From your experience, what are the biggest challenges companies face when trying to account for their emissions? How does Persefoni help to address these challenges?

Data is the most common challenge. Knowing where to source it, how to process it, and which emissions factors to apply. Persefoni addresses these challenges in several ways:

– Accessibility: We offer Persefoni Pro, a free, self-guided carbon accounting tool available to any organisation. It runs on the same calculation engine as our enterprise platform, democratising access to high-quality emissions measurement. It also enables supplier and portfolio engagement to enhance Scope 3 data quality.

– Breadth of data: Our platform includes over 150,000 emission factors, from global spend-based models to regional databases and granular LCA datasets like ecoinvent, ensuring organisations can use the most appropriate data for their needs.

– Expert support: Our climate experts and Customer Success teams are always available to assist clients in improving data quality, methodologies, and output accuracy.

6. Your platform uses a variety of emissions data sources—what role does a premium dataset provider like ecoinvent play in this mix?

It’s essential that customers have access to a broad range of emissions data to meet them where they are on their climate journey. For those just starting out, who may not yet have access to detailed or granular data, broad datasets help them understand the materiality of their impacts and identify where to focus their efforts.

However, that’s only the first step for many organisations. For companies looking to truly decarbonise or set and achieve science-based targets, it becomes critical to go beyond averages and access datasets that distinguish between different technologies and processes.

This is where premium datasets like ecoinvent add significant value. Many of our clients operate in complex sectors such as manufacturing or chemicals, where even small variations in ingredients or production methods can result in substantial differences in emissions. Having access to detailed, process-specific data enables these organisations to pinpoint those differences and make more informed, impactful decisions.

7. Data transparency is very important to ecoinvent. Please could you share some insights on the importance of data transparency on your platforms, and Persefoni’s thoughts on how data transparency builds trust and creates value for clients?

Data transparency is no longer a ‘nice to have’ in carbon accounting. Many Persefoni clients use our platform to meet regulatory reporting obligations, and data audits are becoming standard practice. That means the emission factors used, as well as the methodologies applied, are often checked and challenged.

Transparency is embedded in the foundation of Persefoni’s platform. Clients maintain full ownership of their data, including every decision around methodology and emission factor selection. All transactions are captured within our Carbon Ledger—a fully downloadable, audit-ready record of every data point uploaded. This includes details such as original inputs, applied conversions, selected emission factors, and a complete audit trail showing user IDs, timestamps, and any edits made.

This level of transparency not only supports compliance—it also builds trust, improves data quality, and ultimately enables organisations to take credible climate action with confidence.

8. Many emissions calculations rely on spend-based data. Can you walk us through the key differences between spend-based and unit-based accounting, and what advantages you see when clients transition to unit-based approaches using datasets like ecoinvent’s?

Spend-based analysis is often a useful starting point for estimating emissions, particularly for companies early in their carbon accounting journey. It works by multiplying the amount a company spends on a good or service by a relevant spend-based emissions factor, often derived from environmentally extended input-output models. This approach offers a high-level view of emissions, particularly across the supply chain, but it comes with limitations. Critically, it assumes that all suppliers and products within a given sub-sector have similar carbon intensities, which is rarely the case in reality.

Unit-based accounting, on the other hand, uses actual quantities, such as kilograms of material or litres of ingredient, to estimate emissions. Because it’s based on physical activity rather than financial spend, it is not distorted by price fluctuations, inflation, or procurement dynamics. When paired with high-quality life cycle assessment (LCA) data, like that provided by ecoinvent, unit-based analysis enables far greater precision, offering emissions factors that are specific to particular technologies, production methods, and geographies.

To illustrate the difference: imagine purchasing one tonne of fabric. A spend-based approach might apply the same emissions factor per euro or pound spent, regardless of whether the fabric is cotton or silk, whether it was purchased at a premium due to demand spikes, or secured earlier at a discount. A unit-based approach, however, takes into account the specific material, production region, recycled content, and even the weave or knit, providing a much more accurate reflection of its true carbon footprint.

9. In what ways does having access to unit-based emission factors influence the kinds of strategic decisions your clients can make?

Most of our clients are aiming for more than just compliance-driven carbon reporting—they’re committed to actually reducing their emissions. Whether this is motivated by internal leadership, investor scrutiny, or evolving regulatory and public disclosure requirements, there’s a growing expectation for accountability and measurable progress.

For many companies, the bulk of emissions sit outside their direct operations, typically within the supply chain (though this varies by sector). This makes access to accurate, unit-based emissions data critical. It provides the level of specificity needed to set credible targets, identify material emissions hotspots, and take meaningful, data-informed steps towards decarbonisation.

At Persefoni, we’ve seen clients use granular unit-based emission factors to inform a wide range of strategic decisions, from product redesign and material selection to manufacturing process improvements and increased use of recycled inputs. By moving beyond estimates to precise, activity-based data, organisations can align carbon reduction strategies with their operational realities and drive tangible climate impact.

10. How do you help clients balance the trade-off between completeness and accuracy in their emissions inventories?

The GHG Protocol, widely regarded as the world’s leading greenhouse gas accounting framework, is built on five key principles: Relevance, Completeness, Consistency, Transparency, and Accuracy. Striking the right balance between completeness and accuracy is essential but can be challenging, particularly when navigating fragmented data or Scope 3 emissions.

At Persefoni, we support clients in managing this trade-off by providing access to a wide range of emissions factors and multiple methodological approaches. Many organisations begin with spend-based data to gain a comprehensive, top-down view of their emissions. This offers a high level of completeness, even if the initial accuracy is limited.

From there, clients can identify material emissions sources and begin refining their estimates using more precise, unit-based emission factors. To take it a step further, our Data Exchange module and Persefoni Pro enable companies to directly engage their suppliers and portfolio companies, unlocking supplier-specific data where available and appropriate, and further improving accuracy.

As we often say in this space, nothing is ever black and white. The most accurate and complete inventories typically blend multiple approaches. Managing that complexity manually can be resource-intensive, which is why technology is so important. Persefoni’s platform automates best practices, streamlines data management, and helps clients build GHG inventories that are not only robust and credible but also time- and cost-efficient.

11. How do you see the field of emissions accounting evolving over the next few years, whether in response to regulations, stakeholder pressure, or corporate ambition? What shifts do you think will define the next wave of best practices?

Emissions accounting has advanced rapidly in recent years, and that momentum shows no sign of slowing. Amid ongoing regulatory shifts across Europe, North America, and beyond, companies that embed best practices, such as prioritising primary data and adopting precise, unit-based methodologies, are emerging as the most resilient and future-ready.

Looking ahead, we expect to see increased scrutiny and a clear move away from basic disclosure towards high-integrity climate data as a core business asset. There’s a growing convergence around international standards like those set by the ISSB, which are significantly raising expectations for transparency, traceability, and auditability.

In this next phase, organisations will need to go beyond estimates. They’ll be expected to justify methodologies, provide robust data trails, and demonstrate the use of verifiable, activity-level data. This evolution will not only enhance the credibility of climate reporting but also sharpen its strategic value, enabling more informed, accountable decision-making.

12. With the launch of Persefoni Pro as a free, self-guided platform, how do you see its role in shaping the sustainability reporting market?

Persefoni Pro is designed to lower the barriers to entry for carbon accounting, making it possible for any organisation, regardless of size, expertise, or budget, to begin measuring and understanding their emissions. By offering a free, self-guided platform powered by the same calculation engine used by global enterprises, Persefoni Pro helps democratise access to high-quality emissions data and GHG reporting capabilities.

Its impact extends beyond individual users. Large organisations can now more easily engage their suppliers and portfolio companies in climate disclosure efforts, improving the quality and completeness of Scope 3 data across their value chains. This kind of scalable, bottom-up engagement is essential for credible decarbonisation planning.

In shaping the market, Persefoni Pro is redefining what’s expected from sustainability tools: transparency, accessibility, and alignment with global standards, all without requiring a team of experts or expensive consulting support. As reporting requirements become more widespread and stringent, tools like Persefoni Pro will play a vital role in enabling more organisations to participate meaningfully and confidently in the climate disclosure ecosystem.

13. How can readers engage with Persefoni to deepen their understanding of carbon accounting and sustainability reporting?

One of the most accessible ways to engage with us is through Persefoni Academy, our free, on-demand learning platform designed to help organisations globally to build confidence in carbon accounting, climate disclosure, and sustainability strategy.

The Academy offers a range of expert-led courses that walk users through the fundamentals of emissions measurement, carbon accounting standards like the GHG Protocol and PCAF, and practical application of climate data in business decision-making. Whether you’re just getting started or looking to strengthen your existing knowledge, the content is structured to meet learners where they are.

It’s not just for Persefoni users; Persefoni Academy is open to anyone looking to better understand the carbon accounting landscape. It’s part of our broader mission to empower more people with the skills and knowledge needed to take credible climate action. And for those who complete the courses, certificates of completion are available to demonstrate growing expertise in this evolving field.