carbon storage
AI technology will be critical in the race to a cleaner future
The past three months alone has seen the UK announce three major milestones โ covering carbon storage, offshore wind and hybrid energy projects โ to propel it further down the road towards net zero. But that journey is no longer only about creating a sustainable, green future. World events have brought security of supply sharply into focus, placing new impetus on governments to accelerate alternative energy projects. While moving at pace is critical for the planet, the old proverb of more haste, less speed โ warning against making errors by acting too quickly and without due diligence โ should be weighing on the minds of developers. Nicola Blanshard, CEO of Geoteric, a world-leading AI-driven seismic interpretation software provider, believes the balance of speed and success can be achieved through appropriate application of technology. She explained: "The need for alternative energy sources beyond hydrocarbons is well understood, and a massive expansion of carbon storage and offshore wind projects will be required to meet the Paris Agreement targets.
AI technology will be critical in the race to a cleaner future - TechNative
The past three months alone has seen the UK announce three major milestones โ covering carbon storage, offshore wind and hybrid energy projects โ to propel it further down the road towards net zero. But that journey is no longer only about creating a sustainable, green future. World events have brought security of supply sharply into focus, placing new impetus on governments to accelerate alternative energy projects. While moving at pace is critical for the planet, the old proverb of more haste, less speed โ warning against making errors by acting too quickly and without due diligence โ should be weighing on the minds of developers. Nicola Blanshard, CEO of Geoteric, a world-leading AI-driven seismic interpretation software provider, believes the balance of speed and success can be achieved through appropriate application of technology.
Accelerating Climate Change Mitigation with Machine Learning: The Case of Carbon Storage
Climate change mitigation is about reducing greenhouse gas (GHG) emissions. The worldwide goal is to reach net zero, which means balancing the amount of GHG emissions produced and the amount removed from the atmosphere. On the one hand, this implies reducing emissions by using low-carbon technologies and energy efficiency. On the other hand, it implies deploying negative emission technologies such as carbon storage, which is the subject of this post. Carbon capture and storage (CCS) refers to a group of technologies that contribute to directly reducing emissions at their source in key power sectors such as coal and gas power plants and industrial plants.
Big data, machine learning shed light on Asian reforestation successes
Since carbon sequestration is such an important factor for mitigating climate change, it's critical to understand the efficacy of reforestation efforts and develop solid estimates of forest carbon storage capacity. However, measuring forest properties can be difficult, especially in places that aren't easily reachable. Purdue University's Jingjing Liang, an assistant professor of quantitative forest ecology and co-chair of the Forest Advanced Computing and Artificial Intelligence (FACAI) Laboratory in the Department of Forestry and Natural Resources, led an international team to measure forest carbon capacity in northeast Asia. Their research, which blends remote sensing, field work and machine learning, offers the most up-to-date estimates of carbon capture potential in reclusive North Korea and details the benefits of reforestation efforts over the last two decades in China and South Korea. "Because there is historically scant data from North Korea, people know little about how much carbon is stored in this region," said Liang, whose findings were published in the journal Global Change Biology.