Tackling Climate Change with Machine Learning

arXiv.org Artificial Intelligence

Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change.


What would it take for renewably powered electrosynthesis to displace petrochemical processes?

Science

Plants that grow in the ground make all their carbon-based infrastructure from carbon dioxide (CO2). By contrast, plants built by chemists use petroleum and natural gas as their carbon feedstock. In a review, De Luna et al. explore the prospective challenges and opportunities for manufacturing commodity chemicals such as ethylene and alcohols by direct electrochemical reduction of CO2. They estimate that production costs would be competitive with fossil technologies if renewable electricity costs drop below 4 cents per kilowatt-hour and electrical-to-chemical conversion efficiencies reach 60%. As the world continues to transition toward carbon emissions–free energy technologies, there remains a need to also reduce the carbon emissions of the chemical production industry. Today many of the world's chemicals are produced from fossil fuel–derived feedstocks. Electrochemical conversion of carbon dioxide (CO2) into chemical feedstocks offers a way to turn waste emissions into valuable products, closing the carbon loop. When coupled to renewable sources of electricity, these products can be made with a net negative carbon emissions footprint, helping to sequester CO2 into usable goods. Research and development into electrocatalytic materials for CO2 reduction has intensified in recent years, with advances in selectivity, efficiency, and reaction rate progressing toward practical implementation. A variety of chemical products can be made from CO2, such as alcohols, oxygenates, synthesis gas (syngas), and olefins--staples in the global chemical industry. Because these products are produced at substantial scale, a switch to renewably powered production could result in a substantial carbon emissions reduction impact. The advancement of electrochemical technology to convert electrons generated from renewable power into stable chemical form also represents one avenue to long-term (e.g., seasonal) storage of energy. The science of electrocatalytic CO2 reduction continues to progress, with priority given to the need to pinpoint more accurately the targets for practical application, the economics of chemical products, and barriers to market entry.


Internet of Things: Energy boon or bane?

Science

Since the dawn of the internet, a digital revolution has transformed life for millions of people. Digital files have replaced paper, email has replaced letters, and cell phones provide access to many services that facilitate daily life. This digital revolution is not over, and there is now a growing deployment of technologies grouped under the term "Internet of Things" (IoT)--a worldwide network of interconnected objects that are uniquely addressable via standard communication protocols (1). By 2020, there may be as many as 30 billion objects connected to the internet (2), all of which require energy. These devices may yield direct energy savings (3, 4), but it is much less clear what their net effect on the broader energy system will be.


Using artificial intelligence and machine learning to manage the electricity grids of the future - Watt-Logic

@machinelearnbot

Existing power grids were designed to transmit electricity over relatively short distances, however, increasingly grids are required to supply major cities from remote offshore wind farms at the same time as integrating local generation. With generators feeding variable amounts of energy from renewable sources into the grid at all voltage levels, it is more difficult to balance supply and demand, and the risks of overloads and fluctuations increase.


How Microsoft Is Using Artificial Intelligence To Fight Climate Change

#artificialintelligence

With each industrial revolution mankind, has progressed by leaps and bounds. But that progress has also damaged our environment. Today, climate change, loss of biodiversity, water woes, and food sustainability are among the most pressing global issues. However, the advent of the Fourth Industrial Revolution is set to fundamentally change such trends. Characterized by advanced technologies such as Artificial Intelligence (AI), big data, automation, and quantum computing, the Fourth Industrial Revolution has the potential to heal the past and ensure a better future.