Lifecycle Analysis for Sustainability

♻️ What exactly is a Life Cycle Assessment (LCA) — and why should your business care? As a sustainability consultant, I often meet companies that want to reduce their impact but aren’t sure where to start.One of the most powerful yet underused tools is LCA (or ACV in French). 🌍 A Life Cycle Assessment measures the environmental footprint of a product, service, or process — from raw materials to end-of-life. It gives a full picture: carbon emissions, water use, resource depletion, toxicity, and more. 🔍 It helps you: - Spot hidden hotspots in your supply chain - Compare design or material options with real data - Structure eco-design strategies with credibility - Align with regulations like RE2020, CSRD, EU Taxonomy, HQE, and more 🧱 And when formalized through tools like: => FDES (for construction products) => PEP ecopassport® (for electrical/electronic equipment) These assessments become valuable assets for tenders, certifications, and client trust. 📘 Some key methodologies: - ISO 14040 / 14044 (global standards) - EN 15804 (Europe, construction sector) - Product Environmental Footprint (PEF) – EU-wide approach 🧠 As a consultant, I see LCA as an essential tool — not just for compliance, but for informed, credible, and future-ready sustainability strategies. 💬 Are LCA, FDES or PEP already part of your sustainability approach? If not yet — what’s holding it back? #Sustainability #LCA #ACV #EcoDesign #CircularEconomy #CSRD #GreenBuilding #FDES #PEP #Consulting #ClimateStrategy

LCA can significantly weaken your carbon claims. Biochar projects are often framed around a simple idea: carbon is stored, therefore carbon is removed. But carbon removal is defined by net impact, not intention. Life Cycle Assessment forces a project to account for everything from feedstock logistics to energy inputs and auxiliary systems. And when you look at the full system, the picture can change. 📌 Transport distance matters. Biomass is bulky, and long logistics chains increase fuel use and associated emissions. A project that looks strong at the reactor level can weaken at the geography level. 📌 Energy design matters even more. Pyrolysis requires heat, and drying often consumes substantial energy. If fossil sources support these steps, net removals shrink. Internal energy recovery can improve the balance — but only if properly integrated. 📌 Startup fuel is rarely highlighted. After shutdowns, reactors require reheating. If this relies on fossil inputs and occurs frequently, cumulative emissions are not negligible. 📌 Moisture content shapes everything. High-moisture feedstock increases drying demand, which directly affects both cost and lifecycle emissions. 📌 Compliance systems and auxiliary equipment also contribute. Individually small, collectively relevant. An LCA does not focus on the reactor alone. It actually measures the whole system. In carbon removal infrastructure, system design determines whether the climate story holds under scrutiny. And keep in mind that investors increasingly look at that layer! What do you think is the LCA variable most biochar projects underestimate?

How to map the environmental footprint of 70,000 organic chemicals? 🧪🌍 Current LCA databases cover too few chemicals, leaving much of the industry to operate in a "data desert." Today, I am happy to share our preprint introducing CRYSTAL: a framework designed to shift chemical LCA from a reliance on "unknown unknowns" to a collaboratively improvable mapping of "known unknowns." Why a preprint? We believe that achieving a sustainable chemical industry requires an open, community-oriented approach. By sharing our methodology now, we hope to start a conversation on how we can collectively refine and improve LCI data at scale. What is CRYSTAL? Short for “Chemical RetrosYnthesiS for Transparent Assessment of Life-cycles,” this framework uses retrosynthesis and machine learning to predict inventories based solely on molecular structure. We’ve used it to generate over 110,000 datasets—a 40-fold increase in coverage compared to existing databases. Key themes we explore in the paper: ➡️ Transparency as a Priority: Every inventory is based on full, visible reaction pathways. If an expert has better real-world data for a specific yield or solvent, the modular nature of CRYSTAL allows those components to be replaced and updated. ➡️ Identifying "Divergent Hotspots": Our analysis pinpoints chemicals where impacts do not correlate with climate change. These are critical environmental "blind spots" where carbon-reduction alone isn't enough to improve sustainability. ➡️ Accelerating R&D: By providing a predictive foundation, CRYSTAL enables chemists and engineers to evaluate the sustainability of emerging pathways at the very earliest stages of research. We are currently busy finalizing the user interfaces and refining the database for its full release. In the meantime, we welcome your feedback on our framework and methodology. You can read the preprint here: https://lnkd.in/eGWVu9iU A huge thank you to our leads Shaohan Chen and Johannes Schilling, and the entire team at ETH Zürich: Tim Langhorst, Julian Nöhl, Christopher Oberschelp, and Martin Pillich. Let’s move toward a more transparent, data-driven future for chemical sustainability. 🚀 #Sustainability #LCA #GreenChemistry #MachineLearning #Preprint #ETHZurich #CRYSTAL Energy and Process Systems Engineering Group, ETH Zurich & Chair of Ecological Systems Design (ESD), ETH Zürich

As CCS technologies continue to scale up, it's critical to accurately quantify the carbon footprint and emissions reduction potential of these projects. A new report from IOGP provides an overview of the methodologies, tools, and best practices for conducting lifecycle assessments (LCAs) of CCS projects. Key takeaways: 📢 1. LCAs for CCS projects should follow established ISO standards like ISO 14040, 14044, and 14064 to ensure a robust, consistent approach. 📢 2. Defining the appropriate system boundaries is crucial - this includes accounting for emissions from capture, transport, and storage operations. 📢 3. Establishing a baseline scenario is important to demonstrate the "CO2 avoided" through the CCS project. 📢 4. Shared CO2 transport and storage networks between multiple emitters add complexity to the LCA - allocation approaches like proportional or Scope 3 accounting should be considered. 📢 5. LCAs should be conducted throughout the lifecycle of a CCS project - from planning and development to operations and decommissioning. 📢 6. Various software tools and emissions factor databases are available to support the LCA quantification process. Careful LCA accounting is essential for demonstrating the true emissions reduction benefits of CCS technologies. This report provides a helpful overview for CCS project developers, policymakers, and other stakeholders. #CCS #CCUS #LCA #CarbonBaseline #CO2 #Scope3 #IOGP #Decarbonization

💡Proud to share the outstanding masters thesis work of my student Xingci (Chichi) Chen at University of Pennsylvania), developed during a 6-month full-time internship at CELINE (LVMH Group, Paris HQ). 🎯In 2022, CELINE’s reached its highest total carbon footprint in recent years. Nearly all emissions were driven by 𝐒𝐜𝐨𝐩𝐞 3 sources. Capital goods accounted for a notable share of the overall carbon footprint. Construction of new stores was the major driver. Xingci's thesis replaced traditional expenditure-based estimation with carbon footprint based on 𝐋𝐢𝐟𝐞 𝐂𝐲𝐜𝐥𝐞 𝐀𝐬𝐬𝐞𝐬𝐬𝐦𝐞𝐧𝐭 (LCA) 𝐦𝐞𝐭𝐡𝐨𝐝𝐨𝐥𝐨𝐠𝐲.  Using SketchUp (3D) design files & detailed plans, each architectural element was broken down into raw materials and processed through a newly designed carbon calculation template. Instead of estimating spend, the model calculated:  • Material quantities • Emission factors • Transportation impact 🌍 Some material-level insights: ⚠️ Carbon analysis revealed that marble wall panels backed with aluminum honeycomb were among the most carbon-intensive elements. ♻️ Through supplier collaboration, this particular backing was gradually replaced with rPET foam (recycled plastic) — maintaining durability while dividing by half the carbon footprint of this particular element with a potential impact of approximately 10% of stores’ carbon footprint. 🎯A single, data-driven material substitution — aligned with procurement — delivered measurable carbon reduction without compromising luxury standards.    🎯This work directly supports LVMH’s LIFE 360 roadmap, built around ♻️Circular Design, Biodiversity ,Climate and Transparency. By embedding carbon calculation into architecture and procurement processes, sustainability became operational, not rhetorical.    ⚠️ Despite the success there is more work to be done:  • The current focus is limited to CO₂ (excluding water, toxicity, land impact). • There is limited visibility on last-mile transport 🚛. • Existing stores that require retrofits require separate emission calculations. • Custom elements (stairs, unique features) require manual calculation. • Transport of art & vintage furniture not fully captured Some of these gaps have already been tackled by new versions of the tool. In summary, in luxury retail:  📊Data precision drives innovation 🤝 Supplier collaboration enables real reduction 🌍 Design decisions shape Scope 3 impact 🎯 Sustainability strengthens brand differentiation  ✨The future of sustainable luxury is analytical, collaborative, and measurable! Cathy Large (Mines Paris) was the primary reader. I was the secondary. Jessica Caron (Noblis), Siobhan Whadcoat (University of Pennsylvania), Eric Baratta(University of Pennsylvania), Sam Chandan, PhD (NYU Stern School of Business Chen Real Estate Center), Fritz Troller (Therm), Luis Vassy (Sciences Po po), Ariane Joab-Cornu (Sciences Po)  PC: Hiedi FIn

🌿 Can AI Be More Sustainable? Google's TPU Study Says Yes! 🌿 As AI continues to revolutionize industries, one critical question looms large:-What is the environmental cost of AI compute? 📚 A new study by Google researchers presents the first comprehensive life-cycle assessment (LCA) of AI accelerators. It examines the 'cradle-to-grave emissions' of Tensor Processing Units (TPUs) and quantifies greenhouse gas (GHG) emissions across raw material extraction, manufacturing, energy consumption, and retirement. 🔹 Key Findings:- ✅ AI hardware’s 'Compute Carbon Intensity (CCI)' has improved 3x from TPU v4i to TPU v6e, reducing emissions per computation unit. ✅ Operational emissions dominate total lifecycle emissions (~70-90%), highlighting the importance of clean energy adoption in AI data centers. ✅ Manufacturing emissions are now quantifiable, with TPU production accounting for a significant share of AI’s environmental footprint. ✅ Software optimizations amplify hardware gains, further reducing emissions for AI workloads. Why does this matter? 🌍 With AI models growing exponentially in size, understanding and optimizing their carbon footprint is crucial for sustainable AI adoption. This research provides a standardized metric (CCI) that can guide future AI hardware and software innovations. 📢 Call to Action:- ➡️ Should AI vendors disclose carbon metrics for model training and inference? ➡️ How can enterprises prioritize sustainable AI adoption? ➡️ What policy measures should support greener AI computing? 📖 Read the paper - https://lnkd.in/gjuQXPdp Let’s discuss in the comments! 👇 #AI #Sustainability #CarbonFootprint #GoogleCloud #AIAccelerators #MachineLearning #GreenTech

Product design is becoming a more important exercise for companies to reduce tariff impacts and costs, drive down emissions, and capture revenue upside. A key first step is evaluating the bill of materials and conducting a lifecycle assessment to pinpoint where both tariffs and emissions are highest—from materials to manufacturing, usage, and disposal—allowing for targeted, high-impact changes. Switching to low-carbon or recycled materials, simplifying designs, and sourcing locally can significantly reduce costs and environmental impact. Modular, durable products also support circular economy goals by enabling easier repair, reuse, or recycling. Improving energy efficiency—both in production and during product use—can lower emissions and operating costs, making products more attractive to customers. Technologies like digital modeling and just-in-time production also help reduce waste. To fully realize the commercial potential, companies must clearly communicate sustainability attributes through credible claims, transparent labeling, third-party certifications, and marketing that highlights both environmental and performance benefits. Our research shows that appropriate claims can drive 6 to 25%+ revenue uplift.

Let's learn together :-) Understanding Product Life Cycle Assessment (LCA): A Key to Reducing Carbon Footprint Why Conduct a Product LCA? A Product LCA provides a science-based assessment of environmental impacts, helping companies: - Measure GHG emissions at every stage of a product’s life cycle. - Determine the most emission-intensive phases and materials. - Support corporate sustainability goals and #ESGreporting. - Align with sustainability policies - Foster eco-friendly product design and material selection. - Engage suppliers in carbon reduction initiatives. Step-by-Step Process of Product LCA Conducting a Product LCA involves four key phases as defined by ISO 14040 and ISO 14044 standards: 1. Goal and Scope Definition - Define the objective (e.g., carbon footprint calculation) - Set system boundaries: Cradle-to-Grave, Cradle-to-Gate, or Gate-to-Gate. - Establish functional unit (e.g., 1 kg of product, 1 unit of service). 2. Life Cycle Inventory Analysis - Collect data on raw materials, energy use, water consumption, and emissions. - Identify direct and indirect emissions associated with manufacturing, transport, use, and disposal. - Engage supply chain partners for data on upstream emissions. 3. Life Cycle Impact Assessment (LCIA) - Convert inventory data into environmental impacts using impact assessment methods like: - Global Warming Potential (CO₂e emissions) - Acidification Potential (SO₂ emissions) - Eutrophication Potential (water pollution) - Resource Depletion (raw material consumption) 4. Interpretation and Decision-Making - Analyze results to identify emission hotspots. - Compare different materials, processes, or suppliers for sustainability improvements. - Develop carbon reduction strategies, such as material substitution, energy efficiency, or circular economy initiatives. Tools for Conducting Product LCA - SimaPro - GaBi - OpenLCA - One Click LCA - Ecoinvent databases Relationship between LCA and Scope 3 Emissions Scope 3 emissions are those indirect emissions occurring in a company’s value chain. They often represent the largest share of total emissions but are the hardest to measure. Product LCA helps in the following way: - Quantify Scope 3 Emissions: Identify embedded carbon in purchased goods, raw materials, and transportation. - Optimize Supply Chain Choices: Select low-carbon suppliers and transportation modes. - Improve Circular Economy Strategies: - Support Carbon Reduction Targets: Align SBTi and Net-Zero commitments. Conclusion Product LCA is a powerful tool for businesses aiming to achieve sustainability goals, reduce carbon footprints, and make data-driven decisions. By integrating LCA insights into product design, supply chain management, and #SustainabilityStrategy, companies can mitigate Scope 3 emissions and strengthen their competitive edge in a low-carbon economy. #LCA #Sustainability #CarbonFootprint #Scope3 #ESG #ClimateAction

One small paper for GPUs. One giant LEAP for sustainability. 🦘 This paper from Falk et al. delivers the first cradle-to-grave life cycle assessment of training AI models on Nvidia’s A100 GPUs. Here are some cool highlights 😎 : 1️⃣ This study looked at 16 environmental categories to provide a comprehensive cradle-to-grave picture of impacts across the entire lifecycle. 2️⃣ GPT-4 (1.8T parameters, Iowa, 2023) training consumed 57 million GPU hours with the carbon-intensive US grid making its footprint vastly larger. 3️⃣ The GPU chip itself is the single biggest contributor, responsible for approximately 81% of climate change impacts and 80% of fossil resource use. 4️⃣ Communities near extraction and manufacturing sites bear localized health and ecological risks, while AI benefits are concentrated elsewhere AI's environmental footprint is not just about energy, water, or carbon. It includes the unforeseen impacts as well including metals, water, toxicity, waste, and justice issues. Time for a wake-up call. Paper link: https://lnkd.in/eYaYDnu8 #SustainableAI #LifeCycleAssessment #AIandEnvironment #CarbonTunnelVision #AIethics #AIgovernance #EnvironmentalJustice --- AI & Environment Resource Hub: https://lnkd.in/dCuj6hnM Book a meeting: https://lnkd.in/eWKT_4Xj The Climate Code: https://lnkd.in/eurNtuKT