Overabundance of dissolved carbon dioxide poses a threat to marine life. A new system detects elevated levels of the greenhouse gases and mitigates them on the spot.
A defunct drydock basin arched by a rusting 19th century steel bridge seems an incongruous place to conduct state-of-the-art climate science. But this placid and protected sliver of water connecting Brooklyn’s Navy Yard to the East River was just right for Garrett Boudinot to float a small dock topped with water carbon-sensing gear. And while his system right now looks like a trio of plastic boxes wired up together, it aims to mediate the growing ocean acidification problem, caused by overabundance of dissolved carbon dioxide.
Boudinot, a biogeochemist and founder of a carbon-management startup called Vycarb, is honing his method for measuring CO2 levels in water, as well as (at least temporarily) correcting their negative effects. It’s a challenge that’s been occupying numerous climate scientists as the ocean heats up, and as states like New York recognize that reducing emissions won’t be enough to reach their climate goals; they’ll have to figure out how to remove carbon, too.
To date, though, methods for measuring CO2 in water at scale have been either intensely expensive, requiring fancy sensors that pump CO2 through membranes; or prohibitively complicated, involving a series of lab-based analyses. And that’s led to a bottleneck in efforts to remove carbon as well.
But recently, Boudinot cracked part of the code for measurement and mitigation, at least on a small scale. While the rest of the industry sorts out larger intricacies like getting ocean carbon markets up and running and driving carbon removal at billion-ton scale in centralized infrastructure, his decentralized method could have important, more immediate implications.
Specifically, for shellfish hatcheries, which grow seafood for human consumption and for coastal restoration projects. Some of these incubators for oysters and clams and scallops are already feeling the negative effects of excess carbon in water, and Vycarb’s tech could improve outcomes for the larval- and juvenile-stage mollusks they’re raising. “We’re learning from these folks about what their needs are, so that we’re developing our system as a solution that’s relevant,” Boudinot says.
Ocean acidification can wreak havoc on developing shellfish, inhibiting their shells from growing and leading to mass die-offs.
Ocean waters naturally absorb CO2 gas from the atmosphere. When CO2 accumulates faster than nature can dissipate it, it reacts with H2O molecules, forming carbonic acid, H2CO3, which makes the water column more acidic. On the West Coast, acidification occurs when deep, carbon dioxide-rich waters upwell onto the coast. This can wreak havoc on developing shellfish, inhibiting their shells from growing and leading to mass die-offs; this happened, disastrously, at Pacific Northwest oyster hatcheries in 2007.
This type of acidification will eventually come for the East Coast, too, says Ryan Wallace, assistant professor and graduate director of environmental studies and sciences at Long Island’s Adelphi University, who studies acidification. But at the moment, East Coast acidification has other sources: agricultural runoff, usually in the form of nitrogen, and human and animal waste entering coastal areas. These excess nutrient loads cause algae to grow, which isn’t a problem in and of itself, Wallace says; but when algae die, they’re consumed by bacteria, whose respiration in turn bumps up CO2 levels in water.
“Unfortunately, this is occurring at the bottom [of the water column], where shellfish organisms live and grow,” Wallace says. Acidification on the East Coast is minutely localized, occurring closest to where nutrients are being released, as well as seasonally; at least one local shellfish farm, on Fishers Island in the Long Island Sound, has contended with its effects.
The second Vycarb pilot, ready to be installed at the East Hampton shellfish hatchery.
Courtesy of Vycarb
Besides CO2, ocean water contains two other forms of dissolved carbon — carbonate (CO3-) and bicarbonate (HCO3) — at all times, at differing levels. At low pH (acidic), CO2 prevails; at medium pH, HCO3 is the dominant form; at higher pH, CO3 dominates. Boudinot’s invention is the first real-time measurement for all three, he says. From the dock at the Navy Yard, his pilot system uses carefully calibrated but low-cost sensors to gauge the water’s pH and its corresponding levels of CO2. When it detects elevated levels of the greenhouse gas, the system mitigates it on the spot. It does this by adding a bicarbonate powder that’s a byproduct of agricultural limestone mining in nearby Pennsylvania. Because the bicarbonate powder is alkaline, it increases the water pH and reduces the acidity. “We drive a chemical reaction to increase the pH to convert greenhouse gas- and acid-causing CO2 into bicarbonate, which is HCO3,” Boudinot says. “And HCO3 is what shellfish and fish and lots of marine life prefers over CO2.”
This de-acidifying “buffering” is something shellfish operations already do to water, usually by adding soda ash (NaHCO3), which is also alkaline. Some hatcheries add soda ash constantly, just in case; some wait till acidification causes significant problems. Generally, for an overly busy shellfish farmer to detect acidification takes time and effort. “We’re out there daily, taking a look at the pH and figuring out how much we need to dose it,” explains John “Barley” Dunne, director of the East Hampton Shellfish Hatchery on Long Island. “If this is an automatic system…that would be much less labor intensive — one less thing to monitor when we have so many other things we need to monitor.”
Across the Sound at the hatchery he runs, Dunne annually produces 30 million hard clams, 6 million oysters, and “if we’re lucky, some years we get a million bay scallops,” he says. These mollusks are destined for restoration projects around the town of East Hampton, where they’ll create habitat, filter water, and protect the coastline from sea level rise and storm surge. So far, Dunne’s hatchery has largely escaped the ill effects of acidification, although his bay scallops are having a finicky year and he’s checking to see if acidification might be part of the problem. But “I think it's important to have these solutions ready-at-hand for when the time comes,” he says. That’s why he’s hosting a second, 70-liter Vycarb pilot starting this summer on a dock adjacent to his East Hampton operation; it will amp up to a 50,000 liter-system in a few months.
If it can buffer water over a large area, absolutely this will benefit natural spawns. -- John “Barley” Dunne.
Boudinot hopes this new pilot will act as a proof of concept for hatcheries up and down the East Coast. The area from Maine to Nova Scotia is experiencing the worst of Atlantic acidification, due in part to increased Arctic meltwater combining with Gulf of St. Lawrence freshwater; that decreases saturation of calcium carbonate, making the water more acidic. Boudinot says his system should work to adjust low pH regardless of the cause or locale. The East Hampton system will eventually test and buffer-as-necessary the water that Dunne pumps from the Sound into 100-gallon land-based tanks where larvae grow for two weeks before being transferred to an in-Sound nursery to plump up.
Dunne says this could have positive effects — not only on his hatchery but on wild shellfish populations, too, reducing at least one stressor their larvae experience (others include increasing water temperatures and decreased oxygen levels). “If it can buffer water over a large area, absolutely this will [benefit] natural spawns,” he says.
No one believes the Vycarb model — even if it proves capable of functioning at much greater scale — is the sole solution to acidification in the ocean. Wallace says new water treatment plants in New York City, which reduce nitrogen released into coastal waters, are an important part of the equation. And “certainly, some green infrastructure would help,” says Boudinot, like restoring coastal and tidal wetlands to help filter nutrient runoff.
In the meantime, Boudinot continues to collect data in advance of amping up his own operations. Still unknown is the effect of releasing huge amounts of alkalinity into the ocean. Boudinot says a pH of 9 or higher can be too harsh for marine life, plus it can also trigger a release of CO2 from the water back into the atmosphere. For a third pilot, on Governor’s Island in New York Harbor, Vycarb will install yet another system from which Boudinot’s team will frequently sample to analyze some of those and other impacts. “Let's really make sure that we know what the results are,” he says. “Let's have data to show, because in this carbon world, things behave very differently out in the real world versus on paper.”
Giving robots self-awareness as they move through space - and maybe even providing them with gene-like methods for storing rules of behavior - could be important steps toward creating more intelligent machines.
Now roboticists are going a step further, training their creations to do even better: understand their own image in space and interact with humans like humans do. Today, there are already robot-teachers like KeeKo, robot-pets like Moffin, robot-babysitters like iPal, and robotic companions for the elderly like Pepper.
But even these reasonably intelligent creations still have huge limitations, some scientists think. “There are niche applications for the current generations of robots,” says professor Anthony Zador at Cold Spring Harbor Laboratory—but they are not “generalists” who can do varied tasks all on their own, as they mostly lack the abilities to improvise, make decisions based on a multitude of facts or emotions, and adjust to rapidly changing circumstances. “We don’t have general purpose robots that can interact with the world. We’re ages away from that.”
Robotic spatial self-awareness – the achievement by the team at Columbia – is an important step toward creating more intelligent machines. Hod Lipson, professor of mechanical engineering who runs the Columbia lab, says that future robots will need this ability to assist humans better. Knowing how you look and where in space your parts are, decreases the need for human oversight. It also helps the robot to detect and compensate for damage and keep up with its own wear-and-tear. And it allows robots to realize when something is wrong with them or their parts. “We want our robots to learn and continue to grow their minds and bodies on their own,” Chen says. That’s what Zador wants too—and on a much grander level. “I want a robot who can drive my car, take my dog for a walk and have a conversation with me.”
Columbia scientists have trained a robot to become aware of its own "body," so it can map the right path to touch a ball without running into an obstacle, in this case a square.
Jane Nisselson and Yinuo Qin/ Columbia Engineering
Today’s technological advances are making some of these leaps of progress possible. One of them is the so-called Deep Learning—a method that trains artificial intelligence systems to learn and use information similar to how humans do it. Described as a machine learning method based on neural network architectures with multiple layers of processing units, Deep Learning has been used to successfully teach machines to recognize images, understand speech and even write text.
Trained by Google, one of these language machine learning geniuses, BERT, can finish sentences. Another one called GPT3, designed by San Francisco-based company OpenAI, can write little stories. Yet, both of them still make funny mistakes in their linguistic exercises that even a child wouldn’t. According to a paper published by Stanford’s Center for Research on Foundational Models, BERT seems to not understand the word “not.” When asked to fill in the word after “A robin is a __” it correctly answers “bird.” But try inserting the word “not” into that sentence (“A robin is not a __”) and BERT still completes it the same way. Similarly, in one of its stories, GPT3 wrote that if you mix a spoonful of grape juice into your cranberry juice and drink the concoction, you die. It seems that robots, and artificial intelligence systems in general, are still missing some rudimentary facts of life that humans and animals grasp naturally and effortlessly.
How does one give robots a genome? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create.
It's not exactly the robots’ fault. Compared to humans, and all other organisms that have been around for thousands or millions of years, robots are very new. They are missing out on eons of evolutionary data-building. Animals and humans are born with the ability to do certain things because they are pre-wired in them. Flies know how to fly, fish knows how to swim, cats know how to meow, and babies know how to cry. Yet, flies don’t really learn to fly, fish doesn’t learn to swim, cats don’t learn to meow, and babies don’t learn to cry—they are born able to execute such behaviors because they’re preprogrammed to do so. All that happens thanks to the millions of years of evolutions wired into their respective genomes, which give rise to the brain’s neural networks responsible for these behaviors. Robots are the newbies, missing out on that trove of information, Zador argues.
A neuroscience professor who studies how brain circuitry generates various behaviors, Zador has a different approach to developing the robotic mind. Until their creators figure out a way to imbue the bots with that information, robots will remain quite limited in their abilities. Each model will only be able to do certain things it was programmed to do, but it will never go above and beyond its original code. So Zador argues that we have to start giving robots a genome.
How does one do that? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create. Genomes lay out rules for brain development. Specifically, the genome encodes blueprints for wiring up our nervous system—the details of which neurons are connected, the strength of those connections and other specs that will later hold the information learned throughout life. “Our genomes serve as blueprints for building our nervous system and these blueprints give rise to a human brain, which contains about 100 billion neurons,” Zador says.
If you think what a genome is, he explains, it is essentially a very compact and compressed form of information storage. Conceptually, genomes are similar to CliffsNotes and other study guides. When students read these short summaries, they know about what happened in a book, without actually reading that book. And that’s how we should be designing the next generation of robots if we ever want them to act like humans, Zador says. “We should give them a set of behavioral CliffsNotes, which they can then unwrap into brain-like structures.” Robots that have such brain-like structures will acquire a set of basic rules to generate basic behaviors and use them to learn more complex ones.
Currently Zador is in the process of developing algorithms that function like simple rules that generate such behaviors. “My algorithms would write these CliffsNotes, outlining how to solve a particular problem,” he explains. “And then, the neural networks will use these CliffsNotes to figure out which ones are useful and use them in their behaviors.” That’s how all living beings operate. They use the pre-programmed info from their genetics to adapt to their changing environments and learn what’s necessary to survive and thrive in these settings.
For example, a robot’s neural network could draw from CliffsNotes with “genetic” instructions for how to be aware of its own body or learn to adjust its movements. And other, different sets of CliffsNotes may imbue it with the basics of physical safety or the fundamentals of speech.
At the moment, Zador is working on algorithms that are trying to mimic neuronal blueprints for very simple organisms—such as earthworms, which have only 302 neurons and about 7000 synapses compared to the millions we have. That’s how evolution worked, too—expanding the brains from simple creatures to more complex to the Homo Sapiens. But if it took millions of years to arrive at modern humans, how long would it take scientists to forge a robot with human intelligence? That’s a billion-dollar question. Yet, Zador is optimistic. “My hypotheses is that if you can build simple organisms that can interact with the world, then the higher level functions will not be nearly as challenging as they currently are.”