As artificial intelligence (AI) continues to transform industries and unlock new opportunities, its environmental impact is also a matter of concern. While AI holds immense potential to combat climate change, it paradoxically contributes to the problem it aims to solve. The computational intensity of AI training and deployment leaves a significant carbon footprint. So, what’s the responsible way to savor the benefits of AI without worsening the climate crisis? The answer is Green AI.
So, What Is Green AI?
Green AI is a movement and an innovation that seeks to balance technological advancement with environmental sustainability. Green AI, also referred to as Sustainable AI or Net Zero AI, encompasses practices to reduce the carbon footprint of artificial intelligence technologies. Unlike traditional approaches, Green AI integrates sustainability into every stage of the AI lifecycle, from research and development to deployment and maintenance.
Furthermore, understanding the differences between conventional AI and Green AI is key to addressing this growing challenge.
Traditional AI vs. Green AI: A World of Difference
Traditional AI focuses on achieving unmatched accuracy in tasks like language translation, image recognition, and autonomous driving. While its applications are groundbreaking, this accuracy comes at a cost. Training large-scale AI models often require enormous computational resources, consuming vast amounts of energy.
For example, a nature.com study revealed the carbon footprint of training a single big language model is equal to around 300,000 kg of carbon dioxide emissions. This could be quantified as equivalent to 125 round-trip flights between New York and Beijing, a quantification that laypersons can visualize.
Thus, conventional AI overlooks energy efficiency. It also increases costs for businesses and excludes smaller players from entering the AI landscape. The worst outcome is the damage done to the environment from its carbon footprint, suppressing its potential to mitigate climate change.
In contrast, Green AI prioritizes energy-efficient practices. By focusing on sustainable development and deployment of AI systems, it seeks to minimize environmental harm without compromising innovation. Green AI introduces efficiency as a key metric alongside accuracy. It also advocates solutions that deliver high performance while conserving resources.
AI Powering Innovation but at What Cost?
We projected this study from ScienceDirect to understand the energy appetite of AI solutions. AI is growing rapidly, with bigger data needs and more complex models. However, this doesn’t always lead to equally big improvements in accuracy. While large language models (LLMs) like ChatGPT drive innovation, they come with significant environmental costs. Let’s dig deeper…
AI’s Growing Energy Appetite
The same report explains training GPT-3, for instance, consumed 1287 MWh of electricity and emitted 550 tons of carbon dioxide—comparable to flying 33 times between Australia and the UK.
The energy required for AI isn’t just during training. Using systems like GPT-3 also carries a hefty price. In January 2023 alone, GPT-3 processed 590 million queries, consuming energy equivalent to that of 175,000 people. On a smaller scale, each ChatGPT query uses as much power as running a 5W LED bulb for over an hour.
Fig: CO2 equivalent emissions for training ML models (blue) and of real-life cases (violet). In brackets, the billions of parameters adjusted for each model.
Source: ScienceDirect
Deloitte’s recent report, “Powering Artificial Intelligence: A study of AI’s environmental footprint”, revealed the following findings:
- Between 2021 and 2022, data centers accounted for 98% of Meta’s additional electricity use and 72% of Apple’s between 2022 and 2023.
- AI adoption will fuel data center power demand, likely reaching 1,000 terawatt-hours (TWh) by 2030, and potentially climbing to 2,000 TWh by 2050.
- This will account for 3% of global electricity consumption, indicating faster growth than in other uses like electric cars and green hydrogen production.
AI Data Centers: Energy Efficient or Energy Waste?
Data centers are the backbone of AI training and deployment, often referred to as the “cloud.” However, they rely on physical infrastructure for computing, processing, storing, and exchanging data. They require massive power and contribute heavily to the energy consumption of tech companies.
Different types of data centers have unique energy demands. Basic computer rooms handle simple tasks, while mid-size and large-scale enterprise data centers manage more complex operations. Hyperscale data centers, owned by tech giants have maximum hardware density and handle massive computational workloads, consuming the most energy.
Within this category, AI hyperscale data centers are emerging as a distinct segment. These centers are specifically built for generative AI and machine learning tasks, requiring high-performance GPUs for model training and inference.
This results in higher server power usage and the need for advanced cooling systems, further increasing energy consumption. Smaller data centers often lack the capacity for these high-demand workloads, driving the growth of AI-focused hyperscale facilities.
Fig: Data centers’ electricity consumption by server type and scenarios
But as they expand, a critical question remains: How sustainable are AI hyperscale data centers in the fight against climate change?
Well, this is where the demand for Green AI garners importance.
Why Green AI Matters?
The environmental cost of AI is no longer a hypothesis, it is palpable all around. Even blockchain technologies like cryptocurrency mining have demonstrated how unchecked digital innovation can lead to unsustainable energy consumption.
Coming straight to the topic, Green AI holds the promise of reversing this trend. For example, AI-powered tools can optimize supply chains, reduce waste, and improve energy grid efficiency. If developed responsibly, AI could become the key driving force behind the global effort to achieve carbon neutrality.
Thus, by combining innovation with sustainability, Green AI can meet the growing demand for computational power while reducing its impact on the environment.
Core Principles of Green AI
This means leveraging AI solutions that are not only effective in optimizing energy use in applications but are also inherently low-energy consumers. It’s crucial to balance AI’s benefits with its environmental impact. It means AI should support sustainability goals and not worsen the problems that it aims to solve.
Energy Efficiency
Green AI encourages the design of algorithms and models that consume less energy. Researchers can achieve this by developing lightweight models or installing techniques like pruning, quantization, and model distillation, which reduce computational requirements.
Hardware Optimization
Using energy-efficient hardware, such as GPUs with higher FLOPS per watt or specialized Tensor Processing Units (TPUs), can significantly cut AI’s energy consumption. Parallelizing tasks across multiple cores also helps reduce training times and emissions, though excessive cores may increase energy use disproportionately.
Another technique is edge computing which means processing data locally to avoid energy-intensive transmissions to cloud or data centers and optimizing resources for IoT (The Internet of Things) devices. Together, these strategies enable powerful AI performance with a smaller environmental footprint.
Data Center Optimization
Adopting renewable energy sources for powering data centers and AI operations is a significant milestone of Green AI. Companies like Google and Microsoft are already leading the charge by transitioning their cloud services to run on clean energy.
To make data centers more energy-efficient, researchers have created algorithms and frameworks that balance server loads, optimize cooling systems, and allocate resources more effectively. All these processes are included in data center optimization that cuts down energy use and emissions.
Transparency and Accessibility
Green AI promotes transparency in reporting the environmental costs of AI projects. Standardized metrics for energy consumption and emissions can help developers and organizations make informed decisions about their AI strategies.
Some of the tools that are used to estimate the carbon footprint of AI technologies are CarbonTracker, CodeCarbon, Green algorithms, and PowerTop.
Additionally, by lowering computational barriers, Green AI fosters inclusivity. Smaller organizations and researchers gain access to advanced tools without burdening themselves with high environmental and financial costs.
Fig: Achievable electricity demand reduction through energy savings, “High adoption” scenario
Policies Driving Green AI
The United Nations’ Sustainable Development Goals (SDGs) highlight the need for a sustainable future. Goals like Affordable and Clean Energy and Industry, Innovation, and Infrastructure are driving the rise of Green AI. Industry leaders are rethinking data center designs and operations to lower energy consumption and environmental impacts. This shows their eagerness to demonstrate proactive efforts toward sustainability.
While Green AI initiatives are mostly industry-led, some regions are implementing supportive policies. These range from monitoring low-impact data centers to stricter regulations for areas where grid stability is at risk. Thus, balancing these policies can encourage sustainable practices without moving operations to less regulated regions.
Notable policies include:
- European Code of Conduct for Data Centers (EU DC CoC)
- Energy Efficiency Directive (EED)
- Singapore Green Data Centre Roadmap
China has also introduced measures like the Three-Year Action Plan on New Data Centres, while the U.S. lacks federal-level regulations specific to data centers.
Policymakers can amplify these efforts by co-developing standards with industry leaders. Collaborative strategies ensure data centers meet climate goals without compromising growth or grid stability.
Green AI demonstrates that with the right policies and innovations, the tech industry can lead the way to a more sustainable future.
Green AI Takes the Spotlight at COP29
As world leaders convened in Baku, Azerbaijan, for COP29, discussions pointed to the role of AI in promoting environmental sustainability. A Deloitte-hosted panel brought together experts from NVIDIA, Crusoe Energy Systems, EON, and the International Energy Agency (IEA) to explore strategies for reducing AI’s environmental footprint.
Josh Parker, senior director of legal–corporate sustainability at NVIDIA, said,
“We see a very rapid trend toward direct-to-chip liquid cooling, which means water demands in data centers are dropping dramatically right now.”
According to NVIDIA, designing data centers while keeping energy efficiency at the highest priority right from the beginning is very much essential. As AI demands grow, sustainable infrastructure will be critical. Parker highlighted that current data centers are becoming outdated and inefficient.
He added, accelerated computing platforms are 10X more efficient than traditional systems for running workloads. This creates a significant opportunity to cut energy consumption in existing infrastructures.
Accelerated Computing: A Path to Green AI
Parker once again emphasized that accelerated computing represents the most energy-efficient platform for AI and many other applications. Over the past few years, energy efficiency for accelerated computing has improved dramatically, with a 100,000x reduction in energy consumption.
- In just the last two years, energy use for AI inference tasks dropped by 96%, with systems becoming 25x more efficient for the same workload.
Accelerated computing uses GPUs to process tasks faster and more efficiently than traditional CPUs. By handling multiple tasks simultaneously, GPUs reduce the energy required for AI workloads. It’s one of the techniques that come under hardware efficiency and data center optimization.
Furthermore, NVIDIA emphasized the need for energy-efficient infrastructure in data centers. Innovations like liquid-cooled GPUs are transforming cooling methods. Unlike traditional air conditioning, direct-to-chip liquid cooling consumes less power and water while maintaining effective temperature control.
The Bottom Line
Deloitte’s findings have adeptly showcased AI’s potential in driving climate-neutral economies. Green AI strategies focus on minimizing environmental impact by improving hardware design and increasing the use of renewable energy.
Industry leaders are spearheading these efforts, highlighting the effectiveness of sustainable computing practices. The shift toward accelerated computing and energy-efficient design is paving the way for AI to support global climate goals.
As we face a climate crisis, the integration of Green AI principles is no longer optional—it is essential. By redefining how AI solutions are developed, we can harness their power for good while minimizing their environmental toll. The road ahead demands collective effort, innovation, and accountability. Last but not least, Green AI is not just a technological imperative but a moral responsibility to ensure a greener future.
Key Sources:
- A review of green artificial intelligence: Towards a more sustainable future – ScienceDirect
- AI at COP29: Balancing Innovation and Sustainability | NVIDIA Blog
The post Green AI Explained: Fueling Innovation with a Smaller Carbon Footprint appeared first on Carbon Credits.
Carbon Footprint
SBTi Net-Zero Standard V2: What the Revision Means for Every Business
Key takeaways
- SBTi is the default reference point for corporate climate action: 51% of Fortune Global 500 companies now hold net-zero targets, up from 8% in 2020, and over 11,000 organizations worldwide have SBTi-validated targets.
- Net Zero Standard V2 redefines climate leadership as reducing emissions and mitigating ongoing emissions, not reduction alone.
- The new standard adds flexibility through five-year cycles, a “best efforts” standard, and an Asset Transition Method for companies whose path to net-zero doesn’t fit a straight-line trajectory.
- Voluntary carbon credits are formally recognized for the first time, with reduction and removal credits accepted from 2027, and removals required from 2035.
- Companies with 2030 targets keep using V1 for their current cycle and move to V2 in 2028; companies without targets can start using V2 on February 1, 2027.
Why every business needs to understand the SBTi Net-Zero Standard revision
The Science Based Targets initiative (SBTi) has become the default reference point for credible corporate climate action. Net-zero targets are now held by 51% of Fortune Global 500 (FG500) companies, up dramatically from just 8% in 2020, and more than 11,000 organizations worldwide have set SBTi-validated targets.
However, SBTi’s influence extends well beyond the companies formally participating in the program. Every business in the value chain of an SBTi participant will have to reduce its own carbon emissions, and businesses that aren’t SBTi participants themselves still look to the program for guidance on climate action.
In short, SBTi gives every business a credible blueprint for climate action, and companies that follow its principles can pursue climate action with confidence, whether or not they’re formally part of the program.
How will the Net Zero Standard revision affect business climate action?
SBTi participation is expected to grow. Despite strong target-setting participation among the F500, only 17% of companies use the SBTi Net Zero Standard V1 beyond target setting, largely because its rules have been seen as too rigid to apply in practice. Much of the Net Zero Standard revision has focused on creating more flexibility to enable higher participation. Medium and small businesses will also increasingly feel pressure for climate action, since SBTi mandates that its participants reduce carbon emissions across their value chains.
Net Zero Standard V2 also redefines climate leadership: leading climate action now means reducing emissions and mitigating ongoing emissions. Reducing your own emissions while ignoring the emissions you continue to release along the way is no longer considered leadership. Supporting voluntary carbon projects with high-integrity carbon credits is now backed by the leading authority on corporate climate action.
What lessons shaped the Net Zero Standard V2 revision?
The revision reflects a few learnings about what actually drives climate progress, and how SBTi built those lessons into the new standard.
| Net Zero Standard V1 Learnings | Net Zero Standard V2 Implementation |
|---|---|
| Making real short-term progress is more important and more difficult than making big long-term promises | Focus on short-term climate progress |
| Every company has a different path to net zero that doesn’t always fit generalized net-zero rules | Create asset transition plans based on each company’s unique asset lifecycles and capital planning |
| We need to mitigate our ongoing emissions to keep global carbon emissions in check | Reduce global carbon emissions by financing voluntary carbon projects with high-integrity carbon credits |
What are the key changes between the old and new Net Zero Standard?
Both versions of the standard are grounded in net-zero by 2050. However, the old standard treated climate leadership as simply reducing emissions, expected a long-term commitment to net zero, based emission reduction targets on generalized net-zero goals, revoked status from companies that fell behind on targets, and ignored voluntary carbon projects entirely.
The new standard treats climate leadership as reducing emissions and mitigating ongoing emissions. It shifts the focus to short-term progress through five-year cycles, and it bases emission reduction targets on both the net-zero goal and a company’s own asset decarbonization plan. A new Asset Transition Method lets companies set decarbonization targets through asset plans with committed, verifiable steps; an ambitious but achievable path based on a company’s starting point, financial resources, and technology, with multiple pathways to reflect the unique opportunities and constraints of different industries and companies.
Crucially, the new standard moves to a “best efforts” basis that creates real flexibility on progress against targets. Businesses that miss their targets can keep their status if they’ve used “every lever” within their control, and minimum progress rules will be set out in the SBTi Assurance Manual.
Finally, the new standard formally uses voluntary carbon projects to mitigate ongoing emissions. From 2027 through 2034, this mitigation is recognized, and both carbon reduction and removal credits are accepted. From 2035 forward, mitigation with carbon removal credits becomes required, with durability matching between the removal and the emission it offsets.
| Old Net Zero Standard | New Net Zero Standard |
|---|---|
| Grounded in net-zero by 2050 | Grounded in net-zero by 2050 |
| Climate leadership is reducing emissions | Climate leadership is reducing emissions and mitigating ongoing emissions |
| Make a long-term commitment to net-zero | Focus on short-term progress in 5-year cycles |
| Emission reduction targets are based on net-zero goal |
|
| Businesses who fall behind targets lose status |
|
| Ignores voluntary carbon projects |
|
When does the new Net Zero Standard take effect?
Companies with existing 2030 targets should continue using the old Net Zero Standard for their current cycle, and start using the new Net Zero Standard in 2028 to set targets for the next cycle (2030–2035).
Companies that don’t yet have targets can use the new Net Zero Standard starting February 1, 2027.
What are SBTi’s Category A and Category B companies?
The new Net Zero Standard splits companies into two categories, with different requirements attached to each.
Category A covers large companies from all countries and medium-sized companies from high-income countries. A company from any country qualifies if it meets at least one of: net turnover of €450 million or more, or 1,000 or more full-time employees. A company from a high-income country qualifies if its Scope 1 and 2 emissions are 10,000 tCO2e or more, or if it meets at least two of: balance sheet of €25 million or more, net turnover of €50 million or more, or 250 or more full-time employees.
Category B covers small companies from all countries and medium-sized companies from lower-income countries.
How do Scope 1 targets work under Net Zero Standard V2?
Scope 1 targets aim to transition companies to net-zero direct emissions by 2050 or sooner, and companies can choose from three approaches.
- Absolute emissions reduction follows a straight-line emissions trajectory from the target base year to the net-zero year.
- Emissions intensity reduction lets companies follow sector-specific pathways designed to reflect the reduction opportunities available in sectors like steel, cement, or chemicals.
- Asset transition is designed for companies whose capital stock turnover doesn’t follow a linear or sector pathway. These companies design a transition plan to operate existing assets efficiently and replace them with low-carbon assets, using predetermined milestones.
How do Scope 2 targets work under Net Zero Standard V2?
Scope 2 targets address emissions from purchased electricity through three pathways:
- Reducing electricity consumption,
- Reducing grid consumption by installing onsite or direct-line offsite clean energy generation, and
- Cleaning up the regional grid using market-based tools like PPAs, RECs, and GOs that drive clean energy development.
V2 introduces a dual Scope 2 framework requiring two separate targets, with an overall goal of 100% low-carbon electricity by 2040.
The location-based target addresses the carbon intensity of a company’s physical power use, and requires companies to show that their grid consumption is falling and/or that their physical grid use is getting cleaner; in other words, that their market-based solutions are actually making the grid cleaner.
The market-based (or zero-carbon electricity) target tracks a company’s use of low-carbon power generation contracts and Energy Attribute Certificates. It requires geographical matching of these certificates with electricity consumption based on deliverability regions (grid regions); annual matching is allowed, though hourly matching is encouraged. Category A companies with large electricity loads must report the percentage of their Scope 2 electricity consumption matched with low-carbon attributes on an hourly basis, and there’s an optional recognition framework for companies that meet hourly matching thresholds.
How do Scope 3 targets work under Net Zero Standard V2?
Scope 3 targets share the same 2050-or-sooner net-zero goal, but companies set near-term targets only for material emissions sources in their value chain and areas where they have real influence. Long-term Scope 3 targets are generally not required.
Limited, justified exclusions are allowed for near-term targets, including categories that individually account for less than 5% of total Scope 3 emissions, and activities where a company lacks practical influence, like leased assets it doesn’t operationally control, or the processing of sold products. Optional exclusions are also available in specific categories.
Companies can choose from three approaches to near-term Scope 3 targets:
- An overarching emissions reduction target, which follows a linear contraction of emissions from the base year to residual emissions of 10% or less by 2050 or sooner;
- An overarching supplier/customer alignment target, benchmarked against a growing share of tier 1 suppliers and customers reaching net-zero by 2050 or sooner; or
- A category- or activity-specific target, tailored for companies with concentrated emissions in particular Scope 3 categories or high-emitting activities.
What is “ongoing emissions mitigation” under the new SBTi standard?
This is one of the most significant additions in Net Zero Standard V2. Accelerated climate contributions are needed to help the world achieve climate objectives, limit temperature overshoot, mitigate transition risks, and support the scale-up of climate solutions, and V2 formally recognizes that. Ongoing emissions mitigation runs as a parallel track to companies also reducing their own emissions.
The framework is initially voluntary, with recognition available at three contribution levels to encourage early action.
- Engaged companies address more than 1% of total Scope 1, 2, and 3 emissions.
- Advanced companies address more than 10% of total Scope 1, 2, and 3 emissions, including 100% of Scope 1 and 2 emissions.
- Leadership companies address 100% of total Scope 1, 2, and 3 emissions with a contribution budget of $80/tCO2e.
Carbon credits used for this purpose have to meet certain quality standards. They must be ex-post (issued after the mitigation has actually occurred), independently third-party-assured, emissions reductions or removals, measured in tCO2e, that occur within five years prior to the reporting year. They must be sourced from outside the company’s own value chain. Further minimum criteria will be set to align with high-integrity frameworks, with additional details on the recognition program expected in the second half of 2026.
Starting in 2035, carbon removals become mandatory for Category A companies. From that point, the carbon removal coverage requirement rises linearly from 1% of Scope 1–3 emissions to 100% by a company’s net-zero year. Within that, 10% of long-lived GHG emissions must specifically be covered by durable removals, also rising linearly to 100% by the net-zero year.
How must companies neutralize residual emissions?
At a company’s net-zero target year and thereafter, it must reduce its Scope 1, 2, and 3 emissions to zero or to residual levels, and neutralize all residual emissions using eligible carbon removals. Those removals have to meet two conditions: they must occur within the same reporting period as the residual emissions they’re neutralizing, and long-lived GHGs must be neutralized with long-lived removals, matching the durability of the removal to the atmospheric lifetime of the emission being addressed.
What is the SBTi implementation hierarchy?
Net Zero Standard V2 also lays out how companies should prioritize their actions for credible target delivery, in three tiers.
- Direct actions, at the activity level, are actions that reduce emissions at the source within a company’s own operations and value chain; things like efficiency improvements, fuel switching, and engaging suppliers and customers to reduce their emissions.
- Actions within shared systems, or activity pools that reduce the emissions of shared systems like electricity or gas grids. This includes market instruments that convey low-carbon attributes, such as PPAs, RECs, and GOs, all of which must meet minimum integrity criteria that SBTi will elaborate on in future guidance.
- Sector-level actions relate to the same type of activity occurring in a relevant geography or system, in a way that meaningfully reduces the emissions a company is responsible for.
How Terrapass helps businesses meet the new SBTi standard
As the rules around carbon credits become more rigorous, the quality of the credits behind them matters more than ever. Terrapass has expanded our global network of carbon projects: more project types, locations, prices, ICVCM CCPs, and UN SDGs, spanning super-pollutant destruction, nature-based solutions, and durable removals. We offer Green-e® Climate Certification and we only source from third-party-verified projects on ICVCM-Eligible registries.
We also help clients with impact beyond carbon: EACs, RECs, and GOs including Green-e® Certified credits that support leading renewable energy projects; water credits that support water restoration projects; and custom environmental product needs like RNG and SAF. Wherever your organization is on its sustainability journey, we help clients around the world address climate risk, advance their environmental and social goals, and get the most out of their sustainability budgets.
FAQ: SBTi Net-Zero Standard revision
What is the SBTi Net-Zero Standard?
It’s the framework the Science Based Targets initiative publishes for companies that want validated, credible net-zero targets tied to limiting global warming.
What is changing in the SBTi Net Zero Standard V2 revision?
The biggest changes are more flexibility (five-year cycles and a “best efforts” standard), a new Asset Transition Method for companies whose emissions don’t follow a straight-line path, and formal recognition of voluntary carbon credits for mitigating ongoing emissions.
When do companies need to switch to the new SBTi standard?
If your company already has 2030 targets, you keep using V1 for your current cycle and move to V2 in 2028. If you don’t have targets yet, you can start using V2 as of February 1, 2027.
Can companies use carbon credits to meet SBTi targets?
They can. Under V2, high-integrity carbon reduction and removal credits count toward mitigating ongoing emissions from 2027 through 2034. Starting in 2035, only removal credits count, and they need to be durability-matched to the emissions they offset.
What’s the difference between Category A and Category B companies under SBTi?
Category A is large companies everywhere plus medium-sized companies in high-income countries, based on thresholds like revenue, headcount, or emissions. Category B is small companies everywhere and medium-sized companies in lower-income countries.
What happens if a company misses its SBTi target?
Under the old standard, falling behind could cost a company its SBTi status. Under V2’s “best efforts” approach, a company can hold onto its status as long as it’s used every lever within its control, with minimum progress rules coming in the SBTi Assurance Manual.
Sources: This post is based on Terrapass’s internal analysis of the SBTi Corporate Net-Zero Standard V2.0. Facts and figures were checked against SBTi’s official V2.0 announcement, SBTi’s Corporate Net-Zero Standard V2.0 — Chapter 6: Ongoing Emissions Responsibility, Trellis’s coverage of the standard, Trellis’s reporting on Ongoing Emissions Recognition costs, Sylvera’s analysis of what comes next, Anthesis Group’s Fortune 500 net-zero commitments research, and Climate Impact Partners’ seventh annual FG500 analysis, as reported by CarbonUnits.com.
The post SBTi Net-Zero Standard V2: What the Revision Means for Every Business appeared first on Terrapass.
Carbon Footprint
How to improve Scope 3 data accuracy for CSRD
For most businesses, the emissions that matter most sit outside their own walls. Scope 3 emissions, everything generated across your value chain, from the suppliers who make your inputs to the customers who use your products, typically make up the majority of a company’s total carbon footprint. Under the Corporate Sustainability Reporting Directive (CSRD), those value-chain emissions now have to be measured and disclosed with a rigour that spend-based estimates alone struggle to satisfy. This guide sets out how to improve Scope 3 data accuracy for CSRD: the calculation methods open to you, how to move from estimates to verified supplier data, and how to govern that data so it holds up to audit.
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Carbon Footprint
How community stewardship makes carbon credits durable
A carbon credit is a commitment that extends well into the future. The tonne of CO₂ compensated for today from a nature-based carbon project must remain out of the atmosphere for good, which means the forest behind the credit has to remain standing long after the transaction is complete. For any buyer, this raises a defining question: What ensures that the forest endures?
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