Certain gases used for anesthesia are 3,000 times more damaging for the climate than CO2. Some anesthesiologists are pointing to other solutions.
On the whole, the medical sector is responsible for a disproportionally large percentage of greenhouse gas emissions, with the U.S. as the biggest culprit. According to a key paper published in 2020 in Health Affairs, the health industry “is among the most carbon-intensive service sectors in the industrialized world,” accounting for between 4.4 percent and 4.6 percent of greenhouse gas emissions. “It’s not just anesthesia but health care that has a problem,” says Jodi Sherman, anesthesiology professor and Medical Director of the Program on Healthcare Environmental Sustainability at Yale University as well as co-director of the Lancet Planetary Health Commission on Sustainable Healthcare. In the U.S., health care greenhouse gas emissions make up about 8.5 percent of domestic greenhouse gas emissions. They rose 6 percent from 2010 to 2018, to nearly 1,700 kilograms per person, more than in any other nation.
Of course, patients worry primarily about safety, not sustainability. Yet, Koch emphasizes that “as doctors, we have the responsibility to do no harm, and this includes making sure that we use resources as sustainably as possible.” Studies show that 2018 greenhouse gas and toxic air pollutant emissions resulted in the loss of 388,000 disability-adjusted life years in the U.S. alone. “Disease burden from health care pollution is of the same order of magnitude as deaths from preventable medical errors, and should be taken just as seriously,” Sherman cautions.
When Koch, the anesthesiologist, started discussing sustainable options with colleagues, the topic was immediately met with plenty of interest. Her experience is consistent with the latest representative poll of the nonprofit Foundation Health in Germany. Nine out of ten doctors were interested in urgently finding sustainable solutions for medical services but lacked knowhow and resources. For teaching purposes, Sherman and her team have developed the Yale Gassing Greener app that allows anesthesiologists to compare how much pollution they can avoid through choosing different anesthesia methods. Sherman also published professional guidelines intended to help her colleagues better understand how various methods affect carbon emissions.
Significant traces of inhalation gases have been found in Antarctica and the Himalayas, far from the vast majority of surgery rooms.
A solution espoused by both Sherman and Koch is comparatively simple: They stopped using desflurane, which is by far the most damaging of all inhalation gases to the climate. Its greenhouse effect is 2,590 times stronger than carbon dioxide. The Yale New Haven Hospital already stopped using desflurane in 2013, becoming the first known healthcare organization to eliminate a drug based on environmental grounds. Sherman points out that this resulted in saving more than $1.2 million in costs and 1,600 tons of CO2 equivalents, about the same as the exhaust from 360 passenger vehicles per year.
At the Charité, Koch claims that switching to other anesthesiology choices, such as propofol, has eliminated 90 percent of the climate gas emissions in the anesthesiology department since 2016. Young anesthesiologists are still taught to use desflurane as the standard because desflurane is absorbed less into the patients’ bodies, and they wake up faster. However, Koch who has worked as an anesthesiologist since 2006, says that with a little bit of experience, you can learn when to stop giving the propofol so it's timed just as well with a person’s wake-up process. In addition, “patients are less likely to feel nauseous after being given propofol,” Koch says. Intravenous drugs might require more skill, she adds, "but there is nothing unique to the drug desflurane that cannot be accomplished with other medications.”
Desflurane isn’t the only gas to be concerned about. Nitrous oxide is the second most damaging because it’s extremely long-lived in the environment, and it depletes the ozone layer. Climate-conscious anesthesiologists are phasing out this gas, too, or have implemented measures to decrease leaks.
Internationally, 192 governments agreed in the Kyoto protocol of 2005 to reduce halogenated hydrocarbons – resulting from inhalation gases, including desflurane and nitrous oxide – because of their immense climate-warming potential, and in 2016, they pledged to eliminate them by 2035. However, the use of inhalation anesthetics continues to increase worldwide, not least because more people access healthcare in developing countries, and because people in industrialized countries live longer and therefore need more surgeries. Significant traces of inhalation gases have been found in Antarctica and the Himalayas, far from the vast majority of surgery rooms.
Certain companies are now pushing new technology to capture inhalation gases before they are released into the atmosphere, but both Sherman and Koch believe marketing claims of 99 percent efficiency amount to greenwashing. After investigating the technology first-hand and visiting the company that is producing such filters in Germany, Koch concluded that such technology only reduces emissions by 25 percent. And Sherman believes such initiatives are akin to the fallacy of recycling plastic. In addition to questioning their efficiency, Sherman fears such technology “gives the illusion there is a magical solution that means I don’t need to change my behavior, reduce my waste and choose less harmful options.”
Financial interests are at play, too. “Desflurane is the most expensive inhalation gas, and some think, the most expensive must be the best,” Koch says. Both Koch and Sherman lament that efforts to increase sustainability in the medical sector are entirely voluntary in their countries and led by a few dedicated individual professionals while industry-wide standards and transparency are needed, a notion expressed in the American Hospital Association’s Sustainability Roadmap.
Susanne Koch, an anesthesiologist in Berlin, wants her colleagues to stop using a gas called desflurane, which is by far the most damaging of all inhalation gases to the climate.
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Other countries have done more. The European Union recommends reducing inhalation gases and even contemplated a ban of desflurane, except in medical emergencies. In 2008, the National Health Service (NHS) created a Sustainable Development Unit, which measures CO2 emissions in the U.K. health sector. NHS is the first national health service that pledged to reach net zero carbon by 2040. The carbon footprint of the NHS fell by 26 percent from 1990 to 2019, mostly due to reduced use of certain inhalers and the switch to renewable energy for heat and power. “The evidence that the climate emergency is a health emergency is overwhelming,” said Nick Watts, the NHS Chief Sustainability Officer, in a press release, “with health professionals already needing to manage its symptoms.”
Sherman is a leading voice in demanding action in the U.S. To her, comprehensive solutions start with the mandatory, transparent measurement of emissions in the health sector to tackle the biggest sources of pollution. While the Biden administration highlighted its efforts to reduce these kinds of emissions during the United Nations Climate Conference (COP27) in November 2022 and U.S. delegates announced that more than 100 health care organizations signed the voluntary Health Sector Climate Pledge, with the aim to reduce emissions by 50 percent in the next eight years, Sherman is convinced that voluntary pledges are not enough. “Voluntary measures are insufficient,” she testified in congress. “The vast majority of U.S. health care organizations remain uncommitted to timely action. Those that are committed lack policies and knowledge to support necessary changes; even worse, existing policies drive inappropriate consumption of resources and pollution.”
Both Sherman and Koch look at the larger picture. “Health care organizations have an obligation to their communities to protect public health,” Sherman says. “We must lead by example. That includes setting ambitious, science-based carbon reduction targets to achieve net zero emissions before 2050. We must quantify current emissions and their sources, particularly throughout the health care supply chains.”
Artificial Intelligence is already helping to grow some of the food we eat.
The chef-farmers choose from among 45 types of herb and leafy-greens seeds, plop them into grow trays, and a few weeks later they pick and serve. While success is predicated on at least a small amount of these humans’ care, the systems are autonomously surveilled round-the-clock from Babylon’s base of operations. And artificial intelligence is helping to run the show.
Babylon piloted the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off.
Imagine consistently perfect greens and tomatoes and strawberries, grown hyper-locally, using less water, without chemicals or environmental contaminants. This is the hefty promise of controlled environment agriculture (CEA) — basically, indoor farms that can be hydroponic, aeroponic (plant roots are suspended and fed through misting), or aquaponic (where fish play a role in fertilizing vegetables). But whether they grow 4,160 leafy-green servings per year, like one Babylon farm, or millions of servings, like some of the large, centralized facilities starting to supply supermarkets across the U.S., they seek to minimize failure as much as possible.
Babylon’s soilless hydroponic growing system
Courtesy Babylon Micro-Farms
Here, AI is starting to play a pivotal role. CEA growers use it to help “make sense of what’s happening” to the plants in their care, says Scott Lowman, vice president of applied research at the Institute for Advanced Learning and Research (IALR) in Virginia, a state that’s investing heavily in CEA companies. And although these companies say they’re not aiming for a future with zero human employees, AI is certainly poised to take a lot of human farming intervention out of the equation — for better and worse.
Most of these companies are compiling their own data sets to identify anything that might block the success of their systems. Babylon had already integrated sensor data into its farms to measure heat and humidity, the nutrient content of water, and the amount of light plants receive. Last year, they got a National Science Foundation grant that allowed them to pilot the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off. “Will this plant be healthy tomorrow? Are there things…that the human eye can't see that the plant starts expressing?” says Amandeep Ratte, the company’s head of data science. “If our system can say, Hey, this plant is unhealthy, we can reach out to [users] preemptively about what they’re doing wrong, or is there a disease at the farm?” Ratte says. The earlier the better, to avoid crop failures.
Natural light accounts for 70 percent of Greenswell Growers’ energy use on a sunny day.
Courtesy Greenswell Growers
IALR’s Lowman says that other CEA companies are developing their AI systems to account for the different crops they grow — lettuces come in all shapes and sizes, after all, and each has different growing needs than, for example, tomatoes. The ways they run their operations differs also. Babylon is unusual in its decentralized structure. But centralized growing systems with one main location have variabilities, too. AeroFarms, which recently declared bankruptcy but will continue to run its 140,000-square foot vertical operation in Danville, Virginia, is entirely enclosed and reliant on the intense violet glow of grow lights to produce microgreens.
Different companies have different data needs. What data is essential to AeroFarms isn’t quite the same as for Greenswell Growers located in Goochland County, Virginia. Raising four kinds of lettuce in a 77,000-square-foot automated hydroponic greenhouse, the vagaries of naturally available light, which accounts for 70 percent of Greenswell’s energy use on a sunny day, affect operations. Their tech needs to account for “outside weather impacts,” says president Carl Gupton. “What adjustments do we have to make inside of the greenhouse to offset what's going on outside environmentally, to give that plant optimal conditions? When it's 85 percent humidity outside, the system needs to do X, Y and Z to get the conditions that we want inside.”
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen.
Nevertheless, every CEA system has the same core needs — consistent yield of high quality crops to keep up year-round supply to customers. Additionally, “Everybody’s got the same set of problems,” Gupton says. Pests may come into a facility with seeds. A disease called pythium, one of the most common in CEA, can damage plant roots. “Then you have root disease pressures that can also come internally — a change in [growing] substrate can change the way the plant performs,” Gupton says.
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen. So, while companies amass their own hyper-specific data sets, Lowman foresees a time within the next decade “when there will be some type of [open-source] database that has the most common types of plant stress identified” that growers will be able to tap into. Such databases will “create a community and move the science forward,” says Lowman.
In fact, IALR is working on assembling images for just such a database now. On so-called “smart tables” inside an Institute lab, a team is growing greens and subjects them to various stressors. Then, they’re administering treatments while taking images of every plant every 15 minutes, says Lowman. Some experiments generate 80,000 images; the challenge lies in analyzing and annotating the vast trove of them, marking each one to reflect outcome—for example increasing the phosphate delivery and the plant’s response to it. Eventually, they’ll be fed into AI systems to help them learn.
For all the enthusiasm surrounding this technology, it’s not without downsides. Training just one AI system can emit over 250,000 pounds of carbon dioxide, according to MIT Technology Review. AI could also be used “to enhance environmental benefit for CEA and optimize [its] energy consumption,” says Rozita Dara, a computer science professor at the University of Guelph in Canada, specializing in AI and data governance, “but we first need to collect data to measure [it].”
The chef-farmers can choose from 45 types of herb and leafy-greens seeds.
Courtesy Babylon Micro-Farms
Any system connected to the Internet of Things is also vulnerable to hacking; if CEA grows to the point where “there are many of these similar farms, and you're depending on feeding a population based on those, it would be quite scary,” Dara says. And there are privacy concerns, too, in systems where imaging is happening constantly. It’s partly for this reason, says Babylon’s Ratte, that the company’s in-farm cameras all “face down into the trays, so the only thing [visible] is pictures of plants.”
Tweaks to improve AI for CEA are happening all the time. Greenswell made its first harvest in 2022 and now has annual data points they can use to start making more intelligent choices about how to feed, water, and supply light to plants, says Gupton. Ratte says he’s confident Babylon’s system can already “get our customers reliable harvests. But in terms of how far we have to go, it's a different problem,” he says. For example, if AI could detect whether the farm is mostly empty—meaning the farm’s user hasn’t planted a new crop of greens—it can alert Babylon to check “what's going on with engagement with this user?” Ratte says. “Do they need more training? Did the main person responsible for the farm quit?”
Lowman says more automation is coming, offering greater ability for systems to identify problems and mitigate them on the spot. “We still have to develop datasets that are specific, so you can have a very clear control plan, [because] artificial intelligence is only as smart as what we tell it, and in plant science, there's so much variation,” he says. He believes AI’s next level will be “looking at those first early days of plant growth: when the seed germinates, how fast it germinates, what it looks like when it germinates.” Imaging all that and pairing it with AI, “can be a really powerful tool, for sure.”
Researchers from the University of Cambridge have laid the foundations for growing synthetic embryos that could develop a beating heart, gut and brain.
The organoid revolution
In 1981, scientists discovered how to keep stem cells alive. This was a significant breakthrough, as stem cells have notoriously rigorous demands. Nevertheless, stem cells remained a relatively niche research area, mainly because scientists didn’t know how to convince the cells to turn into other cells.
Then, in 1987, scientists embedded isolated stem cells in a gelatinous protein mixture called Matrigel, which simulated the three-dimensional environment of animal tissue. The cells thrived, but they also did something remarkable: they created breast tissue capable of producing milk proteins. This was the first organoid — a clump of cells that behave and function like a real organ. The organoid revolution had begun, and it all started with a boob in Jello.
For the next 20 years, it was rare to find a scientist who identified as an “organoid researcher,” but there were many “stem cell researchers” who wanted to figure out how to turn stem cells into other cells. Eventually, they discovered the signals (called growth factors) that stem cells require to differentiate into other types of cells.
For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells.
By the end of the 2000s, researchers began combining stem cells, Matrigel, and the newly characterized growth factors to create dozens of organoids, from liver organoids capable of producing the bile salts necessary for digesting fat to brain organoids with components that resemble eyes, the spinal cord, and arguably, the beginnings of sentience.
Synthetic embryos
Organoids possess an intrinsic flaw: they are organ-like. They share some characteristics with real organs, making them powerful tools for research. However, no one has found a way to create an organoid with all the characteristics and functions of a real organ. But Magdalena Żernicka-Goetz, a developmental biologist, might have set the foundation for that discovery.
Żernicka-Goetz hypothesized that organoids fail to develop into fully functional organs because organs develop as a collective. Organoid research often uses embryonic stem cells, which are the cells from which the developing organism is created. However, there are two other types of stem cells in an early embryo: stem cells that become the placenta and those that become the yolk sac (where the embryo grows and gets its nutrients in early development). For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells. In other words, Żernicka-Goetz suspected the best way to grow a functional organoid was to produce a synthetic embryoid.
As described in the aforementioned Nature paper, Żernicka-Goetz and her team mimicked the embryonic environment by mixing these three types of stem cells from mice. Amazingly, the stem cells self-organized into structures and progressed through the successive developmental stages until they had beating hearts and the foundations of the brain.
“Our mouse embryo model not only develops a brain, but also a beating heart [and] all the components that go on to make up the body,” said Żernicka-Goetz. “It’s just unbelievable that we’ve got this far. This has been the dream of our community for years and major focus of our work for a decade and finally we’ve done it.”
If the methods developed by Żernicka-Goetz’s team are successful with human stem cells, scientists someday could use them to guide the development of synthetic organs for patients awaiting transplants. It also opens the door to studying how embryos develop during pregnancy.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
