Dry Labs / Computer Labs

Dry labs and computer labs play a crucial role in modern research, supporting computational and data-driven experiments across scientific disciplines. While they don't produce physical waste like wet labs, their environmental impact is significant due to high energy consumption, driven by servers, data centers, and computing devices. Below are sustainable practices to reduce energy use and minimize the environmental footprint of dry labs.

Sustainable Practices for Dry Labs 

• Hardware Inventory and Efficiency

  • Keep a detailed list of all devices (servers, workstations, etc.) to ensure efficient resource allocation.
  • Regularly assess energy consumption during simulations and idle periods to identify inefficiencies.
  • Prioritize upgrading to newer, energy-efficient systems and optimize power settings.
  • Enable automatic power-saving modes and implement overnight shutdowns for unused devices.

• Data Management

  • Catalog large datasets to assess storage needs and ensure compliance with policies.
  • Implement backup workflows for critical datasets and store only data necessary for regeneration.
  • Avoid storing interim results and delete unnecessary data after mandated retention periods.
  • Consider energy-efficient storage solutions, such as cloud services with renewable energy commitments.

• Energy Reduction Strategies

  • Turn off hardware and lights when not in use and use reminder stickers near workstations to encourage energy-saving habits.
  • Implement checkpointing to reduce repeated simulations, saving both energy and time.
  • Deduplicate large datasets to minimize storage needs and reduce energy consumption.

• Policy and Training Improvements

  • Develop clear guidelines on energy use, hardware upgrades, and data storage to standardize sustainable practices.
  • Offer regular training on power management, efficient hardware use, and data management.
  • Encourage collaboration to share resources like computational time and storage space, reducing redundancy.

• Open Science and Resource Sharing

  • Share datasets and computational tools openly to reduce duplicated efforts.
  • Partner with other labs or institutions to share high-performance computing resources and avoid redundant infrastructure.

Additional Tips for Reducing Digital Carbon Footprint 

• Optimize Data Management

  • Store files in the cloud and share links instead of email attachments to save energy.
  • Regularly clean up duplicates or archive data to cold storage to minimize digital waste.
  • Organize data efficiently to apply FAIR data principles and optimize resource use.

• Energy-Efficient Algorithms

  • Use energy-efficient algorithms and adopt power-saving practices like reducing screen brightness and using power-saving modes.

• Support Sustainable Production

  • Purchase equipment from companies that prioritize sustainability in their production processes.

By adopting these practices, dry labs can significantly reduce their digital carbon footprint, improve resource efficiency, and contribute to global sustainability efforts.

Useful Links:

The Carbon Footprint of Bioinformatics

PRACTICAL GUIDE TO SUSTAINABLE RESEARCH DATA

Green Algorithms: Quantifying the Carbon Footprint of Computation

Digital Cleanup Day