Tackling the climate crisis is going to require a combined scientific, industrial, public and governmental effort on a scale that has never been seen before. It’s little wonder, then, that the eyes of the world will be on Glasgow this weekend as COP26 gets underway.
The goals of this UN climate change conference include reducing greenhouse gas emissions (with a target of global net zero by 2050), and protecting communities and natural habitats by making infrastructure and agriculture more resilient to future climate changes. Data science and artificial intelligence (AI) will have a crucial role to play in achieving these aims, allowing us to fully exploit the rapid growth in environmental data from sensors, remote sensing satellites and increasingly powerful numerical weather and climate models, to transform our understanding of the complex interactions between the environment, climate, ecosystems, and human social and economic systems.
The sheer volume of data that needs to be assessed for developing sustainable pathways to net zero means that human decision-making needs to be augmented with AI. By combining human and machine intelligence, we can capitalise on the power of algorithms, machine learning, data science and high performance computing to deliver the information necessary for evidence-based decision-making. These technologies will also be essential in monitoring environmental changes and tracking progress towards the aims of the Paris Agreement and the United Nations Sustainable Development Goals (SDGs).
Beyond the ability to quantify the need for action and tracking developments, data science and AI have arguably an even more important role to play in facilitating direct change through the integration of cutting-edge data science and AI technologies in energy, water, transport, agricultural and other environmentally related systems, and by empowering individuals, organisations and businesses through the provision of targeted information that will support the changes required for the delivery of net zero. The development of environmental digital twins, which integrate computational models of the environment with real-time data input, as well as digital twins of social and economic systems, will allow us to quantify the benefits and risks associated with environmental decisions, investments and policies.
The Alan Turing Institute, the UK’s national centre for data science and AI, has an extensive portfolio of work in environment and sustainability, with a large number of projects that are directly aligned with the aims of COP26. These include using machine learning to better understand the complex interactions between climate and Arctic sea ice, assessing and managing the risk of abrupt greenhouse gas emissions from peatlands, and analysing sensor information to better understand urban air quality. In the drive to achieve net zero, our research on using modern AI tools to develop electricity control room algorithms for a decarbonised system, and to provide decision support under climate uncertainty to ensure energy security, will help the energy sector to mitigate and adapt to climate change. The Turing is also working with partners to integrate crop and disease models with remote sensing and climate projections to understand future threats to agriculture, and develop next-generation models to support resilient agricultural policy for future food security.
Advances in data science and AI provide an enormous range of opportunities to drive technological innovation to help us achieve the goals of COP26. Let’s use this time of international focus to fully exploit that potential and push towards the goals that the future of our planet depends on.
Top image: Fredrika Carlsson / Unsplash
