Pushing boundaries: Yale-affiliated projects are winners in climate solutions/AI challenge – Yale News

Yale Research Initiatives Advance Sustainable Development Goals through Climate Innovation

Yale University’s Planetary Solutions (YPS) initiative, with critical support from the Bezos Earth Fund, is advancing interdisciplinary research projects designed to address global environmental challenges. These projects are directly aligned with the United Nations Sustainable Development Goals (SDGs), focusing on climate action, marine ecosystem management, and technological innovation.

Project Overview and Alignment with Global Goals

Two key projects have been funded to advance climate mitigation strategies. Their objectives contribute significantly to the following SDGs:

• SDG 13 (Climate Action): Both projects develop innovative solutions to mitigate climate change by targeting the primary greenhouse gases: carbon dioxide and methane.
• SDG 14 (Life Below Water): The marine carbon removal project engages directly with ocean systems, aiming to utilize their vast capacity for carbon storage while ensuring the protection of marine biodiversity.
• SDG 9 (Industry, Innovation, and Infrastructure): The development of advanced computational tools represents a significant technological innovation, building a resilient infrastructure for climate science and sustainable development.
• SDG 17 (Partnerships for the Goals): The initiatives are founded on multi-stakeholder collaborations between academia, philanthropic organizations, and the technology industry, exemplifying the partnership model essential for achieving the SDGs.

Detailed Project Analysis

1. The Marine Carbon Dioxide Removal (mCDR) Forecasting ‘Stack’

This project enhances the monitoring, reporting, and verification (MRV) framework for technologies that remove atmospheric carbon dioxide and store it as stable bicarbonate in the ocean. The ‘Stack’ integrates machine learning with advanced climate simulations to quantify the efficiency and durability of carbon removal.

Core Objectives and Technological Innovation

1. Strengthen MRV Processes: To deliver a scientifically robust, rapid, and intuitive forecasting tool for a broad range of users engaged in carbon dioxide removal (CDR).
2. Utilize Advanced Technology: The system combines a new GPU-optimized ocean model, a biogeochemistry model, and AI-derived atmospheric forecasts developed with technology partners like NVIDIA.
3. Overcome Scalability Challenges: It addresses the inefficiencies and turbulence that complicate geochemical interventions, providing precise and rapid modeling to enable large-scale climate mitigation.

Contribution to Sustainable Development Goals

• SDG 13 (Climate Action): By enabling high-fidelity MRV, the ‘Stack’ directly supports global climate mitigation efforts. Its unprecedented forecasting speed—delivering decadal-scale forecasts in hours—allows for better planning of interventions and provides a basis for durable carbon crediting.
• SDG 14 (Life Below Water): The project advances the scientific understanding of marine carbon cycles. Accurate forecasting is crucial for ensuring that mCDR interventions are effective and can be managed to avoid negative impacts on marine ecosystems.
• SDG 9 (Industry, Innovation, and Infrastructure): The ‘Stack’ is a landmark innovation, creating a new technological infrastructure for climate research and the verification of carbon markets, thereby fostering sustainable industrial practices.

2. The Rumen Digital Twin

This project is a collaborative effort between Yale Engineering, the Alliance of Biodiversity International and the International Center for Tropical Agriculture (CIAT), and BiomEdit. It is focused on mitigating livestock methane emissions, a significant contributor to global warming.

Contribution to Sustainable Development Goals

• SDG 13 (Climate Action): The project’s central aim is to reduce methane emissions from the agricultural sector, directly addressing a potent greenhouse gas and contributing to climate change mitigation.
• SDG 2 (Zero Hunger): By tackling the environmental footprint of livestock, this research supports the transition to more sustainable agricultural systems, a key target for ensuring long-term global food security.
• SDG 17 (Partnerships for the Goals): The collaboration between academic, international research, and private sector entities demonstrates a powerful partnership model for developing solutions to complex global challenges.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 13: Climate Action
  • The article’s central theme is climate change mitigation. It discusses two specific projects aimed at reducing greenhouse gases: one focused on marine carbon dioxide removal (mCDR) and another on livestock methane emissions. These efforts directly contribute to taking urgent action to combat climate change and its impacts.
• SDG 14: Life Below Water
  • The mCDR forecasting “Stack” project is explicitly focused on the ocean. It aims to use the ocean to store atmospheric carbon dioxide as dissolved bicarbonate. This directly relates to the sustainable use of oceans and marine resources, particularly concerning the ocean’s role in the global carbon cycle and addressing issues like ocean acidification.
• SDG 9: Industry, Innovation, and Infrastructure
  • The projects described are heavily reliant on scientific research and technological innovation. The article highlights the use of machine learning, AI, graphics processing units (GPUs), and advanced physics models to create new tools for climate mitigation. This fosters innovation and upgrades technological capabilities, which is a core component of SDG 9.
• SDG 17: Partnerships for the Goals
  • The article emphasizes the collaborative nature of these projects. It mentions partnerships between Yale University, the Bezos Earth Fund, technology companies like NVIDIA, and international agricultural research centers (CIAT). This multi-stakeholder approach, mobilizing financial resources, technology, and expertise, is the essence of SDG 17.

2. What specific targets under those SDGs can be identified based on the article’s content?

1. Target 13.3 (under SDG 13): Improve education, awareness-raising and human and institutional capacity on climate change mitigation, adaptation, impact reduction and early warning.
   • The development of the mCDR “Stack” is a direct effort to improve institutional and scientific capacity for climate change mitigation. By creating a tool for “monitoring, reporting, and verification (MRV),” it enhances the ability of researchers and organizations to accurately track and plan carbon removal interventions.
2. Target 14.3 (under SDG 14): Minimize and address the impacts of ocean acidification, including through enhanced scientific cooperation at all levels.
   • The mCDR project involves adding alkalinity to the ocean surface to help it absorb atmospheric CO2 and store it as bicarbonate. This process directly addresses ocean chemistry and is a potential method to counteract ocean acidification. The project itself is an example of “enhanced scientific cooperation.”
3. Target 9.5 (under SDG 9): Enhance scientific research, upgrade the technological capabilities of industrial sectors in all countries… and public and private research and development spending.
   • The article details the enhancement of scientific research through the creation of new AI and physics models. It also highlights private R&D investment from the “Bezos Earth Fund” to support these “bold, interdisciplinary” research projects that upgrade technological capabilities for climate action.
4. Target 17.16 (under SDG 17): Enhance the global partnership for sustainable development, complemented by multi-stakeholder partnerships that mobilize and share knowledge, expertise, technology and financial resources…
   • The initiatives are described as collaborations involving a university (Yale), a private foundation (Bezos Earth Fund), a technology company (NVIDIA), and an international research center (CIAT). This is a clear example of a multi-stakeholder partnership mobilizing financial resources, knowledge (AI, oceanography), and technology to achieve a sustainable development goal.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

• Monitoring, Reporting, and Verification (MRV) Process: The article explicitly states that the mCDR “Stack” supports the “monitoring, reporting, and verification (MRV), a process used in tracking climate change mitigation.” The successful implementation and use of this MRV process is a direct indicator of progress.
• Net Carbon Dioxide Removed: The “Stack” tool is designed to provide a “day-by-day forecast of net carbon dioxide removed.” This provides a specific, quantifiable metric to measure the effectiveness of carbon removal interventions.
• Durability of Carbon Removal: The tool will also measure the “durability of that removal over a user-specified amount of time.” This is a crucial indicator for assessing the long-term impact and stability of carbon storage in the ocean.
• Forecasting Speed and Efficiency: The article mentions that the “Stack” can provide “decadal-scale forecasts in hours and millennia-scale forecasts in days.” This processing speed is an indicator of the technological advancement and improved capacity achieved by the project.
• Livestock Methane Emissions: Although fewer details are provided, the second project focuses on “livestock methane emissions.” The reduction in the volume of these emissions would be the primary indicator of this project’s success.

4. Table of SDGs, Targets, and Indicators

Source: news.yale.edu