Sustainable Product Development

STUDY FINDS COST PER WEAR INFORMATION SHIFTS SHOPPERS TO QUALITY: A new study published in Psychology & Marketing offers a fascinating look at what fashion drives fashion purchasing decisions. Researchers from the University of Bath and Cambridge University found that simply showing consumers the cost per wear (CPW) of garments (price divided by the number of times an item can be worn) can shift preferences away from cheap, low-quality clothing toward higher-priced, longer-lasting options. The findings draw on behavioural psychology to reveal that people respond more to perceived 'economic value' than to abstract sustainability messages. When shoppers could compare CPW between garments, and especially when figures were backed by trusted certification, they were far more likely to choose quality over quantity. The authors suggest CPW could be a powerful tool for brands and policymakers seeking to reframe sustainability as smart spending. Full story in comments.

#Technology is increasingly pivotal in driving sustainability goals, offering innovative solutions to address some of the world's most pressing challenges. Two recent breakthroughs showcase the transformative potential for sustainable energy systems: 1. Sodium-Ion Batteries A game-changing development in sodium-ion batteries using sodium vanadium phosphate presents a promising alternative to lithium-based energy storage. Unlike lithium, sodium is abundant, cost-effective, and can even be harvested from #seawater. This offers a circular economy solution, reducing reliance on scarce resources while addressing the environmental toll of lithium mining and limited recycling capabilities. 2. Photochemical Water Oxidation for Hydrogen Fuel Advances in photochemical water oxidation are optimizing hydrogen production through water splitting—a key step toward realizing #hydrogen’s potential as a sustainable fossil fuel replacement. Efficient processes like this pave the way for cleaner energy systems and a hydrogen-driven future. While both technologies are in early stages, they point to where sustainability funding and innovation should focus. #Startups, in particular, have a unique role in bridging the gap between lab research and real-world applications, turning potential into scalable solutions. The future of sustainability lies in harnessing such breakthroughs to redefine energy, #circularity, and resilience. With the right investment and collaboration, we can unlock a cleaner, more sustainable future. #Sustainability #Innovation #CleanEnergy #TechnologyForGood #FutureOfEnergy

🌿 As software practitioners, how can we adopt green software practices? Here are the key steps: 1. Awareness: Start by becoming aware of the environmental impact of your software. Understand that your application's overall design and efficiency contribute to its energy consumption. 2. Understanding: Gain a deeper understanding of your code's impact using tools and frameworks. The Software Carbon Intensity (SCI) specification and the Impact Framework from our Green Software Foundation are open-source and provide valuable insights into your software's carbon footprint. Leverage these resources to measure and understand the energy consumption of your applications. 3. Opportunity to Apply: Once you are aware and understand your impact, look for opportunities to apply green software practices. There are two main approaches: -- Optimizing Existing Code/Infrastructure/Architecture: Start with small, impactful changes. For example, improve the efficiency of your current codebase and infrastructure. -- Strategic Replacement: When possible, replace parts of your code with more efficient alternatives. For example, A sidecar implementation in Kubernetes transitioned a portion of code from JavaScript to Rust, achieving a 75% reduction in CPU usage and a 95% reduction in memory usage. This shows how strategic replacements can lead to substantial energy savings. (Link to the use case in comments section) 4. Spread the Word: You have the power to make a difference. Share your knowledge and experiences with your peers. Encourage others to adopt green software practices and raise awareness about the importance of sustainability in software development. By taking these steps, we, as a community of software practitioners, can make a significant impact on reducing the environmental footprint of our software. Let’s inspire each other to adopt green software practices. 🌱💡 #Sustainability #GreenSoftware #EnergyEfficiency #TechInnovation #SCI #OpenSource

# HPE Chief Technologist's Five-Point Plan to Cut AI Infrastructure Emissions TLDR; Sustainability for AI needs to be planned from the outset and consider the full stack, not bolted on later. Great to see our own John Frey, Senior Director and Chief Technologist for Sustainable Transformation at HPE, interviewed in this article for Capacity Media - a techoraco brand this week. John runs through the five levers of efficiency, and here's my take on them: 1. Equipment efficiency: We typically overprovision and underutilise IT equipment, so consider how to maximise utilisation of the assets you have before adding more capacity 2. Energy efficiency: Maximise performance per Watt of energy consumed, and make use of low power states when resources are idle 3. Resource efficiency: Advanced cooling options like DTC and fanless liquid cooling are more energy efficient than air cooling for power dense workloads. Consider heat recovery to convert waste heat into an asset that can decarbonise other forms of heating 4. Software efficiency: In AI, Python is popular for notebooks and experimentation but as a high-level interpreted language it's also the least energy efficient. Particularly when deploying to production, consider compiled alternatives like Rust or C++ to minimise processor cycles. The Green Software Foundation's Software Carbon Index (SCI) is a useful tool for calculating the carbon impact of software in meaningful terms like number of concurrent users, prompts or tokens 5. Data efficiency: Data exists everywhere and it is inherently messy, it resists our attempts to constrain it into neat boxes. Data strategies need to consider the energy cost of data movement - embracing a hybrid, distributed approach to data management and bringing the AI to the data can significantly reduce unnecessary data movement, loading and duplication. Check out the full interview with John here: https://lnkd.in/eimVfv9d HPE has a long history of building some of the world's most energy efficient AI computers, making use of technical and energy innovations to optimise performance per watt. Now that AI is becoming part of everyone's IT portfolio, efficiency is more important than ever. #sustainableIT #livingprogress #fiveleversofefficiency #ITefficiency

𝐀𝐫𝐞 𝐲𝐨𝐮𝐫 𝐝𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝𝐬 𝐜𝐚𝐫𝐛𝐨𝐧-𝐧𝐞𝐮𝐭𝐫𝐚𝐥? Creating carbon-neutral dashboards involves minimizing and offsetting the carbon emissions associated with their development, hosting, and usage. Here are some strategies to achieve carbon neutrality in dashboard development: 1) 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭 𝐃𝐞𝐬𝐢𝐠𝐧 𝐚𝐧𝐝 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: - Optimize code and design to reduce resource usage. - Use lightweight libraries and frameworks. - Minimize unnecessary features and elements in the dashboard. 2) 𝐆𝐫𝐞𝐞𝐧 𝐇𝐨𝐬𝐭𝐢𝐧𝐠: - Choose data centres powered by renewable energy sources. - Consider cloud providers with a commitment to sustainability. - Optimize server infrastructure for energy efficiency. 3) 𝐄𝐧𝐞𝐫𝐠𝐲-𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭 𝐇𝐚𝐫𝐝𝐰𝐚𝐫𝐞: - Use energy-efficient servers and hardware. - Consider serverless architectures that automatically scale based on demand, optimizing resource usage. 4) 𝐂𝐨𝐧𝐭𝐞𝐧𝐭 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬 (𝐂𝐃𝐍𝐬): - Utilize CDNs to reduce the physical distance between the user and the server, minimizing data transfer and energy consumption. 5) 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 𝐚𝐧𝐝 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: - Implement monitoring tools to identify performance bottlenecks and optimize resource usage. - Regularly review and update the dashboard to incorporate efficiency improvements. 6) 𝐑𝐞𝐧𝐞𝐰𝐚𝐛𝐥𝐞 𝐄𝐧𝐞𝐫𝐠𝐲 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐞𝐬 (𝐑𝐄𝐂𝐬): - Purchase Renewable Energy Certificates to offset the carbon footprint associated with the energy consumption of servers and infrastructure. 7) 𝐂𝐚𝐫𝐛𝐨𝐧 𝐎𝐟𝐟𝐬𝐞𝐭𝐭𝐢𝐧𝐠: - Invest in carbon offset projects to compensate for any remaining carbon emissions that cannot be eliminated. - Support projects such as reforestation, renewable energy, or methane capture. 8) 𝐔𝐬𝐞𝐫 𝐀𝐰𝐚𝐫𝐞𝐧𝐞𝐬𝐬: - Educate users about the carbon impact of digital services. - Encourage users to use energy-efficient devices and practices. 9) 𝐃𝐚𝐭𝐚 𝐂𝐨𝐦𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧: - Compress data to reduce the amount of data transferred between servers and users, minimizing energy consumption during data transmission. 10) 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐞𝐝 𝐃𝐚𝐭𝐚 𝐒𝐭𝐨𝐫𝐚𝐠𝐞: - Use efficient data storage methods to reduce the energy required for storing and retrieving data. - - - - - - - - - + By combining these strategies, dashboard developers and organizations can work towards minimizing the environmental impact of their digital services and contribute to a more sustainable future. + Just to let you know, achieving carbon neutrality is an ongoing process that requires continuous improvement and adaptation to emerging technologies and best practices. #dataanalytics #sustainability #carbonneutrality #datavisualization #dashboard

Addressing the Carbon Footprint of Foundation Models Training LLMs is extremely energy-intensive, with a single session capable of emitting up to 626,000 pounds of carbon dioxide equivalent. The energy demands extend beyond training. As AI becomes integrated into everyday applications like web search, energy consumption can skyrocket, sometimes increasing usage by more than tenfold. Creating a more sustainable AI future is not just necessary; it’s imperative. Companies are increasingly acknowledging the environmental impact of foundation models and are actively working to reduce their carbon footprint. Key strategies include: 1️⃣ Optimize AI Software and Hardware Efficiency - Fine-tune AI algorithms for maximum efficiency to reduce computing power needs. - Use approaches like Quantization and Speculative Decoding - Deploy AI on energy-efficient hardware. - Foster collaboration between sustainability and IT teams for AI deployment. 2️⃣ Use Renewable Energy for AI Computing - Power AI operations with renewable sources like solar and wind. - Place AI data centers in regions rich in renewable energy. 3️⃣ Carefully Select and Manage AI Training Data - Choose high-quality, relevant data for training AI models. - Avoid unnecessary data that increases computational demands. 4️⃣ Integrate AI into Existing Decarbonization Efforts - Use AI to optimize and automate sustainability initiatives. - Employ AI for real-time monitoring and optimization of energy use, emissions, and resource consumption. - Redesign business models and production systems with AI to minimize environmental impact. 5️⃣ Prioritize AI Use Cases with High Emissions Reduction Potential - Focus AI efforts on areas with the highest potential for emissions reduction. - Enhance logistics, supply chains, and transportation with AI. - Utilize AI for climate modeling, prediction, and decision support. Together, let's drive a greener future with AI! 🌍💡 #IBM #IBMiX #AI #genAI #generativeAI

Electrons to Molecules (E2M) technologies 🟦 1) Hydrogen - Today, most hydrogen is produced by steam methane reforming of natural gas, which offers an economical means of large-scale production. - Molecular hydrogen is an energy carrier and can be generated from renewable energy via water electrolysis. H₂O → (1/2)O₂ + H₂ 🟦 2) Ammonia (NH₃) - Ammonia is composed of nitrogen (N₂) and hydrogen. It is used in various industries, from fertilizer production to chemical production, explosives, and plastics. - Traditionally, Ammonia is produced through the Haber-Bosch process using hydrogen and nitrogen as reactants in the presence of a metal catalyst at high pressure and temp. N₂ + 3H₂ → 2NH₃ 🟦 3) Carbon Monoxide - CO can be used in its pure form or as part of syngas, a mixture of CO and H₂. - Conventionally, CO is produced by coal gasification, steam reforming of natural gas, or partial oxidation of hydrocarbons.  - Electrochemical carbon dioxide reduction (CO₂R) reactors can also produce carbon monoxide, which operates similarly to water electrolyzers.  CO₂ + H₂O + 2e−→ CO + 2OH− 🟦 4) Ethylene - Ethylene (C₂H₄) is a key component in the production of plastic, often derived from ethane. - Ethylene can be produced electrochemically through CO₂ reduction, presenting a long-term opportunity for low-cost solar energy. 2CO₂ + 8H₂O+12e−→C₂H₄+12OH− 🟦 5) Ethanol - Ethanol (C₂H₅OH) is a liquid fuel from various biomass feedstocks through fermentation. - CO₂R can also produce ethanol via a 12-electron transfer reaction, but the process can suffer from lower selectivity. - Recent experimental work establishes the selectivity of CO₂ to ethanol at about 25%. 2CO₂ + 9H₂O +12e−→ C₂H₅OH +12OH− 🟦 6) Methanol (CH₃OH)  - Conventional methanol pathways rely on natural gas as a chemical reactant and a source of high-grade heat for the synthesis process. CH₄ + H₂O → CO+3H₂ CO + H₂O → CO₂ + H₂ 🟦 7) Formic Acid - Formic acid (HCOOH) is a common chemical intermediate conventionally produced from hydrolysis of methyl formate.  CH₃OH+CO→HCOOCH₃ HCOOCH₃+H₂O↔CH₃OH+HCOOH 🟦 8) Methane (CH₄) - Methane can be formed thermochemically by converting hydrogen and carbon dioxide in a catalyst (typically nickel-based).   CO₂+4H₂→CH₄+2H₂O CO+3H₂→CH₄+H₂O CO₂+H₂→CO+H₂O 2CO→C(s)+CO₂ 🟦 9) Potential future hydrogen demand [Direct Electrochemical Product Synthesis]: - U.S. Market Size [million t/yr] Hydrogen = 58 Ammonia = 16 Carbon Monoxide = 2.1 Ethylene = 37 Ethanol = 70 Methanol = 6 Formate = 0.07 Methane = 604 - Desired Electrical Production Efficiency [ kWh/kg] Hydrogen = 41 Ammonia = 22 Carbon Monoxide = 5 Ethylene = 21 Ethanol = 13 Methanol = 9 Formate = 3 Methane = 17 - Electricity Demand to Meet 100% of Market [TWh/y] Hydrogen = 2,367 Ammonia = 343 Carbon Monoxide = 11 Ethylene = 777 Ethanol = 880 Methanol = 60 Formate = 0.2 Methane = 10,350 Source: see post image. This post is based on my knowledge and is only for educational purposes.

The US government has published the Voluntary Carbon Markets Joint Policy Statement and Principles. After going through it, it is amazing that this is what we are talking about in 2024. These are just basic common-sense principles that should already be in practice in all organizations within the VCM ecosystem from the developers to the funders to the buyers and etc. We cannot continue talking about high-integrity carbon credits without dealing with the elephant in the room, when credits are traded at USD 1 or less per ton, in many situations. The buzzwords such as high integrity and high quality means little when people do not understand what the underlying asset is and how it is created, this leads to large scale projects that are unmanageable and unsustainable that actually have negative environmental, ecological and social impacts, just look at the NBS failures over the last few years. Here are 5 things we can do right now to build actual integrity into the VCM ecosystem... 1.      Projects should be smaller in scale and measured and monitored more accurately 2.      Credits must have an expiry date 3.      A large portion of the funds from the sale of carbon credits must flow to the people on the ground and this too needs to be measured, monitored and verified 4.      Developers should be mandated to employ members of the local community to manage and monitor ongoing offset projects. 5.      There needs to a framework in place to ensure accountability when a project fails from misuse and unethical actions by developers such as financial penalties. Climate action is a collective effort, let's do it from the ground up and bring sustainability to the community. #KarbonHero #GenesysReserve #QAVF #carboncredits #carbonmarket #SDG #sustainabledevelopmentgoals #sustainability #ESG #voluntarycarbonmarket #VCM #NBS

On October 10, 2024, the Supervisory Body of the Paris Agreement’s Article 6.4 mechanism adopted the Sustainable Development Tool (SD Tool) during its 14th meeting. This tool represents a significant step in aligning international carbon markets with sustainable development priorities. The SD Tool, will be mandatory for projects under Article 6.4, aims to ensure that efforts to reduce greenhouse gas emissions are coupled with positive contributions toward the 17 Sustainable Development Goals (SDGs) while adhering to the 'do-no-harm' principle. Key aspects of the SD Tool include: 1. Environmental and Social Safeguards Projects are required to identify and mitigate any potential adverse impacts on the environment and communities. 2. Impact on Sustainable Development The tool provides a framework to measure how projects contribute to equitable and sustainable development. 3. Validation and Verification A rigorous process ensures ongoing accountability through stakeholder engagement and monitoring. The adoption of the SD Tool signals a convergence between voluntary and compliance carbon markets. The tool will be critical for enhancing the quality of carbon markets by incorporating comprehensive environmental and social safeguards. The tool will be piloted in selected countries to refine its application and enhance its effectiveness across carbon market projects. #CarbonMarkets #ClimateAction #ParisAgreement #ESG #Sustainability #SDGs

Monitoring and optimizing the performance of solar energy systems requires careful tracking of various parameters. Here are some key parameters to evaluate: 1. Energy Production (kWh) - What to check: Total energy generated by the solar panels. - Why: This helps assess if the system is generating the expected amount of energy. 2. Performance Ratio (PR) - What to check: Ratio of actual energy produced to the theoretical maximum energy. -Why: A key metric to understand how efficiently the solar system is operating. 3. Capacity Factor - What to check: The ratio of the actual output over a period to the maximum possible output. - Why: This provides insight into the utilization of the system's installed capacity. 4. Irradiance (W/m²) - What to check: Solar irradiance at the site. -Why: This shows the amount of sunlight available for conversion into electricity and helps identify inefficiencies. 5. System Availability - What to check: The amount of time the system is operational. - Why: Downtime due to maintenance or failures affects overall performance, so this metric helps in minimizing losses. 6. Temperature of Modules - What to check: Module temperature during operation. - Why: Higher temperatures can reduce the efficiency of solar panels, so it's crucial to monitor. 7. Inverter Efficiency - What to check: How well the inverter is converting DC to AC electricity. - Why: Inverter losses can lead to performance degradation; maintaining high efficiency is critical. 8. Degradation Rate - What to check: Annual rate of performance loss in solar modules. - Why: Understanding how much performance decreases over time ensures accurate long-term planning. 9. Shading Loss - What to check: Losses due to shading from trees, buildings, or other objects. - Why: Shading can significantly reduce performance and must be minimized or mitigated. 10. Soiling Loss - What to check: Energy losses due to dirt, dust, or debris on the panels. - Why: Regular cleaning schedules can be optimized based on the soiling losses. 11. Grid Outages - What to check: Instances when the grid is down, affecting the solar system's ability to export energy. - Why: Frequent outages impact overall energy delivery and system profitability. 12. Module Mismatch - What to check: Variations in performance between different panels in the same array. - Why: Mismatches can lead to power loss and underperformance of the overall system. 13. Fault Detection - What to check: Occurrence of issues such as string faults, inverter malfunctions, or grounding problems. - Why: Early detection of faults helps maintain high system performance and reduce downtime. By closely monitoring these parameters, you can optimize the system's efficiency, reduce losses, and ensure the highest possible energy yield.