In the shift towards decentralized and renewable dominated energy grids, residential buildings play a crucial role. Their flexible demand is key to integrating renewables like solar and wind, which are crucial for a sustainable low-carbon future. Building energy management relies on energy forecasting, improving flexible demand, and scheduling charging/discharging of batteries and EVs, all areas that can leverage artificial intelligence and machine learning in the short and medium term. Energy flexibility1 relies on energy users modulating or adapting their energy demand when needed, typically ..read more

Climate Change AI is excited to announce the awardees of our 2023 Innovation Grants Program. This program, now in its second cycle, supports impactful projects leveraging AI and machine learning to address problems in climate change mitigation, adaptation, and climate science, as well as the creation of publicly-available datasets/simulators to catalyze further work in this area. To select our 2023 cohort, submissions from 47 countries were peer-reviewed by an international committee of experts in AI and climate change-relevant fields. The awardees include nine outstanding projects spanning 30 ..read more

In December 2023, CCAI hosted a workshop at NeurIPS for the fifth consecutive year since 2019. NeurIPS is the largest conference in the AI field, today attracting thousands of participants across academia, industry, and government. The workshop brings together some of the latest research in AI that has potential to address the climate crisis. The 2023 iteration of the workshop focused on blending new and existing knowledge systems to inspire work that considers how novel machine learning research can build upon layers of institutional wisdom. This year, 118 papers were accepted to the CCAI wor ..read more

Intro Climate change has enormous implications for extreme events and hazardous weather. ML offers unprecedented potential to predict such events and thus adapt to and mitigate their effects. Our three forecasting tutorials illustrate end-to-end pipelines that use ML tools to predict extremes and climate variability. As I flew across the eastern coast of Canada in mid-June 2023, it was impossible to overlook the hazy smoke clouds caused by the ongoing wildfires. As a climate scientist, it’s hard to ignore the link between these fires and the massive carbon emissions we humans release into th ..read more

Fashion shapes the way we express ourselves and reflects personal values. However, from haute couture (handmade) to fast fashion, the cost of fashion extends beyond the price tag. This article delves into the far-reaching consequences of fashion products and how overlooked factors such as quality can be combined to significantly reduce their impact on the planet. A product that breaks quickly or fails to meet consumer expectations has a staggering impact. Durability issues give rise to short lifecycles, resource squandering, and increased landfill waste. Poor designs create unwanted products ..read more

In the realm of environmental science, accurate data is not just a luxury; it’s a necessity. This is particularly true when it comes to understanding the carbon content stored in the world’s forests—a critical factor in the global fight against climate change. Forests are the lungs of the Earth, absorbing carbon dioxide and releasing oxygen, thereby playing a pivotal role in climate regulation. However, existing data sets for estimating forest carbon content have been largely skewed towards the Global North. This bias leaves a glaring gap in our understanding of forests in the Global South, wh ..read more

Separations are foundational processes in the chemical industry, accounting for about half of US industrial energy use and more than 10% of the world’s total energy consumption. An analysis of the largest energy consuming industries indicate that replacing traditional separation processes with more efficient alternatives could potentially eliminate 100 million tonnes of carbon emissions and save billions of dollars in energy costs annually. Separation also serves as a cornerstone of carbon capture and storage, enabling the selective removal of carbon dioxide from pre- and post-combustion gas a ..read more

The users of community science platforms such as iNaturalist (www.inaturalist.org) generate millions of photographic observations each month documenting where different plant and animal species can be found. In the last few years, advances in AI in the form of automated image classifiers allow non-experts to identify the different species that are present in these images. However, automatic species identification in images remains a challenging problem, as community science platforms can potentially contain images from hundreds of thousands of different species. One of the major sources of dif ..read more

Contributors: JC Nacpil, JT Miclat, Oshean Garonita, Anica Araneta, Joseph Schmidt, Rod Braun, Jack Kittinger, Pia Faustino, and Dane Klinger Shrimp aquaculture has grown 100-fold over the last 40 years, from an estimated 74,000 metric tons in 1980 to 7.4 million metric tons in 2020. This rapid growth has come at the cost of critical coastal ecosystems, especially mangroves. While deforestation rates have decreased from 0.21% (1996-2010) to 0.04% (2010 to 2020), at least 35% of global mangroves were deforested in the late twentieth century, and the ecosystem services they provided remain lost ..read more

Buildings consume a significant amount of global energy and contribute to greenhouse gas emissions (around 19% in 2010), but also have the potential to reduce their carbon footprint by 50-90%. Optimal building decarbonization requires electrification of end-uses and integration of renewable energy systems. This integration requires aligning availability of renewable energy with the energy demand, and must be carefully managed during operation to ensure reliability and stability of the grid. Demand response (DR) is an energy-management strategy that allows consumers and prosumers to provide gri ..read more