This document lists additional resources that reinforce the guidelines and success criteria within the Web Sustainability Guidelines (WSG) specification.
Resources may include academic and/or government sources, works from standards bodies, research papers, case studies, relevant content showcasing implementation or use cases, tools (free or open source); or other materials that are relevant to understanding, implementing, or reinforcing the sustainability principles.
Resources are for information purposes only, no endorsement is implied. Neither the W3C nor the Sustainable Web Interest Group can guarantee the sustainability of these external resources.
Help improve this page by sharing your ideas, suggestions, or comments via GitHub issues.
Additional Resources
User Experience Design
Identify, assess, disclose, review, and mitigate sustainability impacts:
Impact analysis
External impact
Understand user requirements or constraints, resolving barriers to access:
Audience evaluation
Barriers and access
Barrier removal
Integrate sustainability into every stage of the ideation process:
Sustainable brand development
Wireframes and prototypes
Participation and testing
Environmental ideation
Minimize non-essential content, interactivity, or journeys:
Efficient paths
Patterns for efficiency
Distraction-free design
Eliminate the non-essential
User-initiated actionable content
Decorative design
Ensure that navigation and wayfinding are well-structured:
Navigation and search
Human-readable sitemaps
New content
Design to assist and not to distract:
Respect user attention
Minimize distraction
Reduce engagement traps
Avoid being manipulative or deceptive:
Deceptive design patterns
Advertisements
Analytics and tracking
Search Engine Optimization
Make deliverables understandable and reusable:
Deliverables reusability
Deliverables documentation
Deliverables readability
Use a design system for interface consistency:
Provide clear, inclusive content with purpose:
Clear content
Content formatting
Optimize media to reduce resource use:
Need for media
Optimized media
Lazy loading
User-controlled media
Media management and use
Ensure animation is proportionate and easy to control:
Need for animation
Avoiding overburdening
Control animation
Use optimized and appropriate web typography:
Pre-installed typefaces
Web font optimization
Web font subsetting
Offer suitable alternatives for every format used:
Open formats
Font stack fallbacks
Alternative text
Transcripts and text
Video alternatives
Provide accessible, usable, minimal web forms:
Simple forms
Functional forms
Avoid unwanted notifications:
Need for notification
Notification settings
Reduce the impact of downloadable and physical documents:
Printed documents
Optimized documents
Optimized delivery
Labels and choice
Involve users early in the project:
Audit and test for bugs or issues requiring resolution:
Ongoing evaluation
Non-regression tests
Regression tests
Performance testing
Compliant measurement
Verify that real-world users can successfully use your work upon and after release:
Usage changes
Usability testing
Regularly test and maintain compatibility:
Compatibility policy
Maintaining compatibility
User constraints
Progressive web applications (PWAs)
- Assessing the Impact of Service Workers on the Energy Efficiency of Progressive Web Apps [[SWPWA]]
- Evaluating the Impact of Caching on the Energy Consumption and Performance of Progressive Web Apps [[MPWA]]
- GreenIT
- 0019 - Prefer PWA over native mobile applications that are similar to the website
- Investigating the correlation between performance scores and energy consumption of mobile web apps [[PSEC]]
- PWA Builder
- Starbucks Ordering and Store Locator PWA
- The Carbon Impact of Web Standards [[CIWS]]
- Web Almanac: Sustainability [[ALMANAC]]
Business Strategy and Product Management
Have an ethical and sustainable product strategy:
Public documents
Achievements and compliance
Governance over time
Technology legislation
Assign a sustainability advocate:
Advocate for sustainability
Inform, raise awareness, and train for sustainability:
Inform and aware
Routine training
Active participation
Training materials
Incentivize progress
Communicate the environmental impact of user choices:
Calculate the environmental impact:
Life-cycle assessment
Competitor impact
Tooling impact
Define clear organizational sustainability goals and metrics:
Validate efforts using established third-party certifications:
Obtaining certifications
Maintaining certifications
Support mandatory disclosures and reporting:
Policies and practices
Impact reports
Standards and policies
Impact reduction
Create one or more impact business models:
Follow a product management and maintenance strategy:
Management and maintenance
Planning strategy
Resourcing products
Resource measurement
Failure indicators
Implement continuous improvement procedures:
Continuous improvement
Retrospectives conducted
Iterative consideration
Functionality decisions
Security updates
Skills and maintenance
Document future updates and evolutions:
Establish if a digital product or service is necessary:
Sustainable Development Goals
Creation evaluation
Obstacle consideration
Provide a supplier standards of practice document:
Vetting potential partners
Collaborative measurement
Informative partner promotion
Share economic benefits:
Living wage
Incentivisation
Employee benefits
Share decision-making power with affected parties:
Use Justice, Equity, Diversity, Inclusion (JEDI) practices:
JEDI practices
Accessibility policy
JEDI training
JEDI improvements
Promote responsible data practices:
Data practices
Data ownership
Implement appropriate data management procedures:
Outdated content
Data controllers
Establish responsible practices around AI and emerging or disruptive technologies:
AI and data collection
Business adaptation
Environmental responsibilities
- 3rd Global CryptoAsset Benchmarking Study [[CRYPTOBENCH]]
- A Computer Scientist Breaks Down Generative AI's Hefty Carbon Footprint
- A sustainable internet: Missing pieces to a healthy future
- AI and crypto mining are driving up data centers' energy use
- AI could account for nearly half of datacentre power usage 'by end of year'
- AI, data centers, and water
- AI emissions: What we know so far - and more importantly, what we don't know
- AI Energy Score
- AI Environmental Equity
- AI has an environmental problem
- AI Is Fueling a Data-Center Energy Crisis. A New Architecture Can Ease the Pressure.
- AI is set to drive surging electricity demand from data centres while offering the potential to transform how the energy sector works
- AI power demand rapidly escalating
- AI Will Spew Gas Fumes for Years Before the Nuclear Revolution Takes Off
- AI's Climate Impact Goes beyond Its Emissions
- AI's Environmental Impact: Making an Informed Choice
- Are harvest now, decrypt later cyberattacks actually happening?
- Beyond Counting Carbon [[BEYONDCARBON]]
- Big tech's selective disclosure masks AI's real climate impact
- Bitcoin Energy Consumption Index
- Carbon Emissions from AI and Crypto Are Surging and Tax Policy Can Help
- Carbon in Motion: Characterizing Open-Sora on the Sustainability of Generative AI for Video Generation [[CIM]]
- Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models [[CTML]]
- ChatGPT energy usage is 0.34 Wh per query
- Crypto and blockchain must accept they have a problem, then lead in sustainability
- Cryptocurrency's Dirty Secret: Energy Consumption [[CRYPTO]]
- Data center energy and AI in 2025
- Datacenters to emit 3x more carbon dioxide because of generative AI
- Designing sustainable AI
- Digital aspects and the environment
- Dismantling the Quantum Threat [[QUANTUM]]
- Ecological Awareness for the Decentralized Web
- EMLIO: Minimizing I/O Latency and Energy Consumption for Large-Scale AI Training [[EMLIO]] (PDF)
- Energy and AI [[ENERGYAI]]
- The Energy and Environmental Footprint of AI [[FOOTPRINT-AI]] (PDF)
- Evaluating the Energy-Efficiency of the Code Generated by LLMs [[CODE-AI]] (PDF)
- Environmental impact and net-zero pathways for sustainable artificial intelligence servers in the USA [[AI-SERVERS]]
- From Efficiency Gains to Rebound Effects [[EFF-REBOUND]]
- Generating AI Images Uses as Much Energy as Charging Your Phone, Study Finds
- Generative AI is a climate disaster
- Generative AI's environmental costs are soaring — and mostly secret
- Google's still not giving us the full picture on AI energy use
- The GPT-OSS models are here… and they're energy-efficient!
- How AI and automation make data centers greener and more sustainable
- How Much Energy Does AI Use? The People Who Know Aren't Saying
- How much energy does Google's AI use? We did the math
- How off-grid solar microgrids can power the AI race
- How useful is GPU manufacturer TDP for estimating AI workload energy?
- Hype, Sustainability, and the Price of the Bigger-is-Better Paradigm in AI [[HYPE-AI]]
- Improving Carbon Emissions of Federated Large Language Model Inference through Classification of Task-Specificity [[CELLMTS]]
- In battle against climate crisis, don't overlook the blockchain
- Introducing a new AI metric to drive sustainability
- Jevons' Paradox is good sometimes
- Learning a Data Center Model for Efficient Demand Response [[DC-EDR]]
- Ledger of Harms
- Let's talk about AI and end-to-end encryption
- Measure environmental Impact of your AI Implementations
- Measuring the environmental impact of delivering AI at Google Scale [[AIG-IMPACT]] (PDF)
- More than Carbon: Cradle-to-Grave environmental impacts of GenAI training on the Nvidia A100 GPU [[C2G]] (PDF)
- New Method Forecasts Computation, Energy Costs for Sustainable AI Models
- Offline Energy-Optimal LLM Serving [[OFF-LLM]]
- Optimize AI Model Training and Inference
- Overestimating AI's water footprint
- Prioritize Sustainable AI Design
- Refine Architecture and Assess Latest Trend Impacts
- Sustainable Ux in VR (PPT)
- Sustainability of Bitcoin and its Impact on the Environment [[BITCOIN]]
- The carbon emissions of writing and illustrating are lower for AI than for humans
- The cyber-consciousness of environmental assessment [[CYBER]]
- The Environmental Impacts of AI
- The Environmental Impact of ChatGPT
- The growing energy footprint of artificial intelligence [[EFAI]]
- The Real Story on AI's Water Use-and How to Tackle It
- The role of artificial intelligence in achieving the Sustainable Development Goals [[AISDG]]
- Too Hot to Compute: The Water Crisis Behind Southeast Asia's Data Centre Boom
- Towards Carbon-efficient LLM Life Cycle [[CELLM]]
- Towards Sustainable Large Language Model Serving [[SLLM]]
- Turning AI Data Centers into Grid-Interactive Assets [[AI-GRID]]
- UK Government urged to promote, prioritise and invest in sustainable AI to become global leader in AI frugality and efficiency
- Ultra-efficient AI won't solve data centers' climate problem. This might
- Understanding the environmental impact of generative AI services [[GENAI]]
- United Nations [[SDGS]]
- Unveiling Environmental Impacts of Large Language Model Serving [[UELLM]]
- Water use in AI and Data Centres (PDF)
- Watts That Matter [[WATTS]]
- We did the math on AI's energy footprint. Here's the story you haven't heard
- We need to talk more about AI's environmental impact
- Web3 and Sustainability
- Web3 and sustainability: Benefits and risks
- What is the environmental impact of LLM use on the customer's side?
- Why Blockchain, NFTs, And Web3 Have A Sustainability Problem
Automated tooling
Quantum resilience
Include responsible financial policies:
Fuel divestment
Responsible finance
Include organizational philanthropy policies:
Philanthropy policy
Voluntary work
Plan for a digital product or service's care and end-of-life:
Include e-waste, right to repair, and recycling policies:
E-waste management
E-waste policy
Recycling and repairing
Refurbishment strategy
Right to repair
Define performance and environmental budgets:
Environmental budget
Performance budget
Human budget
Measurable improvements
Use open source where possible:
Open source policy
Collaboration
Contribution
Create a business continuity and disaster recovery plan:
Plan of action
Audience awareness
Acknowledgments
Additional information about participation in the Sustainable Web Interest Group can be found within the GitHub repository of the Interest Group.
Participants active in the development of this document
Alexander Dawson, Andrea Davanzo, Anne Faubry, Antoine Abélard, Arnaud Levy, Berwyn Powell, Brett Tackaberry, Dennis Lemm, Diogo Abrantes Da Silva, François Burra, Iain McClenaghan, Ines Akrap, Iulia Raluca Ionita, Ivano Malavolta, Jennifer Strickland, Jens Oliver Meiert, Josh Kim, Laurent Devernay Satyagraha, Mike Gifford, Morgan Murrah, Owen Rogers, Richard Ishida, Romuald Priol, Rose Newell, Siddhesh Wagle, Thibaud Colas, Tim Frick, Tzviya Siegman