Rolnick, David, Donti, Priya L., Kaack, Lynn H., Kochanski, Kelly, Lacoste, Alexandre, Sankaran, Kris, Ross, Andrew Slavin, Milojevic-Dupont, Nikola, Jaques, Natasha, Waldman-Brown, Anna, Luccioni, Alexandra, Maharaj, Tegan, Sherwin, Evan D., Mukkavilli, S. Karthik, Kording, Konrad P., Gomes, Carla, Ng, Andrew Y., Hassabis, Demis, Platt, John C., Creutzig, Felix, Chayes, Jennifer, Bengio, Yoshua
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.
President Donald Trump withdrew the United States from the Paris Climate Agreement on June 1, 2017, and exactly a year later, also directed his administration to take steps that would prevent the closure of coal and nuclear power plants in the country. Meanwhile, the production of U.S. shale is at record highs (the price of gasoline in the domestic market is also at its highest in several years) and crude oil production heavyweights, like Russia and the Saudi Arabia-led Organization of the Petroleum Exporting Countries (OPEC), are also mulling increasing their output. Despite the virtual stranglehold on global production of crude oil by OPEC and Russia, and the pursuit of environmentally-unfriendly policies by the Trump administration, a new study found there is an economic "carbon bubble" forming, one that could lead to the sudden loss of up to $4 trillion in the global economy by 2035, mostly accounted for by "stranded" fossil fuel stockpiles. Economists and policy experts from Cambridge and the Open universities in the United Kingdom, Radboud University in the Netherlands, Macau University, and Cambridge Econometrics ran detailed simulations that showed technological changes in the energy and transport industries would lead to a significant decline in the global demand for fossil fuels in the coming years. This change in the near future would occur even if major nations did not adopt climate-friendly energy policies, leading to a slump in fossil fuel prices and stocks of associated companies.
General views of the INEOS plant in Grangemouth as the first shipment of shale gas from the United States arrived in Britain on September 27, 2016. A £2 billion (2.3 billion euros, $2.6 billion) investment by Ineos, the world's third largest chemical company, will create a'virtual pipeline' with eight tankers transporting regular shipments across the Atlantic to Britain and Norway. A fierce competitor of both coal and renewables, shale gas has done at least one favor for solar and wind, according to a Harvard economist: it has demonstrated that the American energy system can accommodate sudden and massive influxes of supply. Last year, energy-policy expert William Hogan penned a cautionary paper on the Clean Power Plan, arguing that its celebrated flexibility could disrupt energy markets. But he never worried, as others have, that the disruption would come from too much unreliable power.
Today's announcement by New York State's Governor Cuomo that the Indian Point nuclear power plant will shut down by 2021 – 14 years early - was accompanied by commitments to replace the facility's electrical generation capacity with carbon-free sources in a way that won't spike utility bills. This is a tall order. The power plant – located about 30 miles north of New York City - has been plagued by safety concerns for decades and Governor Cuomo, along with several environmental groups and other stakeholders, have led efforts to shut the facility on safety and environmental grounds for years. However, the nuclear power plant has over 2,000 megawatts of carbon-free electricity generation capacity, which accounts for roughly 25% of New York City and Westchester County's load. For comparison, the capacity of an average coal plant is between 500 to 600 MW.