NeurIPS 2023 Workshop: Blending new and existing knowledge systems
Climate Change AI Blog
by Ashwin Bhanot
1M ago
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
Visit website
Using Machine Learning to Forecast the Weather and Climate
Climate Change AI Blog
by Ioana Colfescu
3M ago
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
Visit website
Using Machine Learning to Increase Durability and Reduce Returns for Sports and Fashion Goods
Climate Change AI Blog
by Multiple authors
4M ago
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
Visit website
Introducing The ForestBench Project
Climate Change AI Blog
by Multiple authors
6M ago
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
Visit website
Deep learning of nanoporous materials for chemical separations
Climate Change AI Blog
by Gustavo Perez
8M ago
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
Visit website
Mapping Species From Crowdsourced Data Using Machine Learning
Climate Change AI Blog
by Multiple authors
9M ago
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
Visit website
Using Machine Learning to Integrate Mangrove Restoration with Sustainable Aquaculture Intensification
Climate Change AI Blog
by Multiple authors
10M ago
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
Visit website
Using Reinforcement Learning to Improve Energy Management for Grid-Interactive Buildings
Climate Change AI Blog
by Multiple authors
1y ago
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
Visit website
Using AI-driven Yield Estimation to Improve Resilience of Malian Cotton Farmers
Climate Change AI Blog
by Multiple authors
1y ago
Climate Change Risks to Agri-Business Sector 15 million Malians rely on agriculture for food and income, much of which is small-scale agriculture. Among agricultural crops, cotton is one of the most important economic crops in Mali. Cotton contributes 15% of GDP and 11% of total value of exports (second only to gold), with cotton production supporting close to a quarter of Mali’s population, 4 million. Cotton is also highly sensitive to climate change, as yields are closely linked to rainfall. Mali’s cotton production is at high risk due to the expected shorter growing periods, increasing dura ..read more
Visit website
Circularity in Fashion, powered by AI
Climate Change AI Blog
by Alan Fortuny Sicart
1y ago
We are regularly reminded of the impact of our food, transport, and energy systems on our biodiversity and climate. However, fashion has enormous environmental impacts which must be addressed to mitigate climate change. The United Nations Environmental Programme and the Ellen Macarthur Foundation show that: 10% of annual global carbon emissions come from the fashion industry 87% of the total fiber input is incinerated or disposed of in a landfill 20% of wastewater worldwide comes from fabric dyeing and treatment 93 billion cubic meters of water are used yearly 50 billion plastic bottles equiv ..read more
Visit website

Follow Climate Change AI Blog on FeedSpot

Continue with Google
Continue with Apple
OR