The world can't keep on with what it's doing and expect to reach its goals when it comes to climate change. Radical innovations are needed at this point, writes Scott Nyquist. Photo via Getty Images

Almost 3 years ago, McKinsey published a report arguing that limiting global temperature rises to 1.5 degrees Celsius above pre-industrial levels was “technically achievable,” but that the “math is daunting.” Indeed, when the 1.5°C figure was agreed to at the 2015 Paris climate conference, the assumption was that emissions would peak before 2025, and then fall 43 percent by 2030.

Given that 2022 saw the highest emissions ever—36.8 gigatons—the math is now more daunting still: cuts would need to be greater, and faster, than envisioned in Paris. Perhaps that is why the Intergovernmental Panel on Climate Change (IPCC) noted March 20 (with “high confidence”) that it was “likely that warming will exceed 1.5°C during the 21st century.”

I agree with that gloomy assessment. Given the rate of progress so far, 1.5°C looks all but impossible. That puts me in the company of people like Bill Gates; the Economist; the Australian Academy of Science, and apparently many IPCC scientists. McKinsey has estimated that even if all countries deliver on their net zero commitments, temperatures will likely be 1.7°C higher in 2100.

In October, the UN Environment Program argued that there was “no credible pathway to 1.5°C in place” and called for “an urgent system-wide transformation” to change the trajectory. Among the changes it considers necessary: carbon taxes, land use reform, dietary changes in which individuals “consume food for environmental sustainability and carbon reduction,” investment of $4 trillion to $6 trillion a year; applying current technology to all new buildings; no new fossil fuel infrastructure. And so on.

Let’s assume that the UNEP is right. What are the chances of all this happening in the next few years? Or, indeed, any of it? President Obama’s former science adviser, Daniel Schrag, put it this way: “ Who believes that we can halve global emissions by 2030?... It’s so far from reality that it’s kind of absurd.”

Having a goal is useful, concentrating minds and organizing effort. And I think that has been the case with 1.5°C, or recent commitments to get to net zero. Targets create a sense of urgency that has led to real progress on decarbonization.

The 2020 McKinsey report set out how to get on the 1.5°C pathway, and was careful to note that this was not a description of probability or reality but “a picture of a world that could be.” Three years later, that “world that could be” looks even more remote.

Consider the United States, the world’s second-largest emitter. In 2021, 79 percent of primary energy demand (see chart) was met by fossil fuels, about the same as a decade before. Globally, the figures are similar, with renewables accounting for just 12.5 percent of consumption and low-emissions nuclear another 4 percent. Those numbers would have to basically reverse in the next decade or so to get on track. I don’t see how that can happen.

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Credit: Energy Information Administration

But even if 1.5°C is improbable in the short term, that doesn’t mean that missing the target won’t have consequences. And it certainly doesn’t mean giving up on addressing climate change. And in fact, there are some positive trends. Many companies are developing comprehensive plans for achieving net-zero emissions and are making those plans part of their long-term strategy. Moreover, while global emissions grew 0.9 percent in 2022, that was much less than GDP growth (3.2 percent). It’s worth noting, too, that much of the increase came from switching from gas to coal in response to the Russian invasion of Ukraine; that is the kind of supply shock that can be reversed. The point is that growth and emissions no longer move in lockstep; rather the opposite. That is critical because poorer countries are never going to take serious climate action if they believe it threatens their future prosperity.

Another implication is that limiting emissions means addressing the use of fossil fuels. As noted, even with the substantial rise in the use of renewables, coal, gas, and oil are still the core of the global energy system. They cannot be wished away. Perhaps it is time to think differently—that is, making fossil fuels more emissions efficient, by using carbon capture or other technologies; cutting methane emissions; and electrifying oil and gas operations. This is not popular among many climate advocates, who would prefer to see fossil fuels “stay in the ground.” That just isn’t happening. The much likelier scenario is that they are gradually displaced. McKinsey projects peak oil demand later this decade, for example, and for gas, maybe sometime in the late 2030s. Even after the peak, though, oil and gas will still be important for decades.

Second, in the longer term, it may be possible to get back onto 1.5°C if, in addition to reducing emissions, we actually remove them from the atmosphere, in the form of “negative emissions,” such as direct air capture and bioenergy with carbon capture and storage in power and heavy industry. The IPCC itself assumed negative emissions would play a major role in reaching the 1.5°C target; in fact, because of cost and deployment problems, it’s been tiny.

Finally, as I have argued before, it’s hard to see how we limit warming even to 2°C without more nuclear power, which can provide low-emissions energy 24/7, and is the largest single source of such power right now.

None of these things is particularly popular; none get the publicity of things like a cool new electric truck or an offshore wind farm (of which two are operating now in the United States, generating enough power for about 20,000 homes; another 40 are in development). And we cannot assume fast development of offshore wind. NIMBY concerns have already derailed some high-profile projects, and are also emerging in regard to land-based wind farms.

Carbon capture, negative emissions, and nuclear will have to face NIMBY, too. But they all have the potential to move the needle on emissions. Think of the potential if fast-growing India and China, for example, were to develop an assembly line of small nuclear reactors. Of course, the economics have to make sense—something that is true for all climate-change technologies.

And as the UN points out, there needs to be progress on other issues, such as food, buildings, and finance. I don’t think we can assume that such progress will happen on a massive scale in the next few years; the actual record since Paris demonstrates the opposite. That is troubling: the IPCC notes that the risks of abrupt and damaging impacts, such as flooding and crop yields, rise “with every increment of global warming.” But it is the reality.

There is one way to get us to 1.5°C, although not in the Paris timeframe: a radical acceleration of innovation. The approaches being scaled now, such as wind, solar, and batteries, are the same ideas that were being discussed 30 years ago. We are benefiting from long-term, incremental improvements, not disruptive innovation. To move the ball down the field quickly, though, we need to complete a Hail Mary pass.

It’s a long shot. But we’re entering an era of accelerated innovation, driven by advanced computing, artificial intelligence, and machine learning that could narrow the odds. For example, could carbon nanotubes displace demand for high-emissions steel? Might it be possible to store carbon deep in the ocean? Could geo-engineering bend the curve?

I believe that, on the whole, the world is serious about climate change. I am certain that the energy transition is happening. But I don’t think we are anywhere near to being on track to hit the 1.5°C target. And I don’t see how doing more of the same will get us there.

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Scott Nyquist is a senior advisor at McKinsey & Company and vice chairman, Houston Energy Transition Initiative of the Greater Houston Partnership. The views expressed herein are Nyquist's own and not those of McKinsey & Company or of the Greater Houston Partnership. This article originally ran on LinkedIn.

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4 Houston researchers awarded projects in DOE's Genesis Mission

federal funding

The U.S. Department of Energy has named the nearly 300 projects selected under the Trump Administration's Genesis Mission, which aims to address some of the largest science and technology challenges in the country. The group features four projects from Houston universities and companies.

The initiative aims to unite government, industry, academia and philanthropy to lead to breakthroughs in energy, scientific discovery and national security, according to a release.

The selected projects feature 87 led by DOE and National Nuclear Security Administration (NNSA) National Laboratories, 168 led by universities, 19 led by companies and 4 led by nonprofit organizations—totalling 342 participating institutions.

“America has no shortage of bold ideas or talented scientists, and the response to the Genesis Mission proves that,” U.S. Secretary of Energy Chris Wright said in a news release. “The 278 projects selected today represent the very best of our nation’s scientific enterprise. The remarkable number of high-quality proposals we received demonstrates that America’s innovation pipeline is strong, and it points to even greater opportunities for future investment and continued expansion of the Genesis Mission portfolio.”

Twelve Texas-based projects were selected among the 278. The Houston projects and their researchers include:

Caroline Ajo-Franklin

Ajo-Franklin recieved a Phase I grant for her project "Predictive AI to Map Point Mutation Effects on Protein Function: Measurement and Biosynthesis of Isoprenoids." Ajo-Franklin is a professor of biosciences at Rice University, a CPRIT Scholar in Cancer Research and member of the Rice Synthetic Biology Institute. The project aims to accelerate the engineering of microbes that can produce isoprenoids, which are natural compounds that could replace petroleum-derived fuels, solvents and materials.

“This project creates a continuous feedback loop in which AI guides experiments and each experiment generates more detailed data to better hone the AI model,” Ajo-Franklin said in a news release. “In addition, it demonstrates the extraordinary star power Rice has recruited in protein engineering and synthetic biology.”

Anastasios Kyrillidis

Kyrillidis recived a Phase I grant for his project "Cracking the VQA Optimization Bottleneck: AI Methods for Quantum Chemistry and Materials." Kyrillidis is the Noah Harding Associate Professor of Computer Science at Rice and a member of the Ken Kennedy Institute. The project aims to develop AI tools to resolve bottlenecks in quantum computing for chemistry and materials research.

“Our goal is to replace fragile, hand-tuned optimization methods with intelligent systems that can learn from quantum computations while still operating within frameworks that provide strong mathematical guarantees,” Kyrillidis added in the release.

Myoungkyu Lee

Lee received a nearly $750,000 Phase I grant for his project "Physics-Informed AI Surrogates for Turbulent Forced Convection in Energy System." Lee is an assistant professor of mechanical aerospace engineering at the University of Houston. Lee will collaborate with researchers from Lawrence Livermore National Laboratory and University of Pennsylvania on the project and develop artificial intelligence to accelerate the design of materials for advanced nuclear fission and fusion reactors.

“The goal is to develop a tool that runs much faster than today’s most detailed simulations while keeping errors small,” Lee said in a news release. “If successful, the approach could support better heat-transfer predictions for molten-salt reactor design and provide a starting point for studying heat removal in fusion blankets. This is one contribution among many toward reliable, carbon-free energy.”

Amit Padhi

Padhi recieved a grant for his project "Probabilistic Inference of Subsurface Fracture Connectivity for Stimulation Control with Physics-Informed AI." Padhi is a scientific advisor for Halliburton.

The DOE first called for applications for the Genesis Mission in March. At the time, the DOE shared that it would grant approximately $293 million to the selected teams via Phase I awards, ranging from $500,000 to $750,000 for nine-month project periods, and Phase II awards, for $6 million to $15 million over a three-year project period.

Since then, however, the initiative has grown with 15 federal agencies now granting research awards and funding opportunities under the Genesis umbrella. The White House announced this week that it had secured more than $5 billion in federal commitments to expand the initiative.

SLB teams with Liberty Energy on modular power for AI data centers

ai alliance

Houston-headquartered SLB and Denver-based Liberty Energy Inc. announced a strategic agreement this month to support the rapid growth of new data center capacity.

Under the agreement, SLB will supply modular data center infrastructure and oversee large-scale execution, while Liberty will provide modular power generation systems and behind-the-meter power management technology for developers looking to add capacity. According to Reuters, the power will come from natural gas generation.

“The bottleneck in AI infrastructure is no longer just compute. It is the ability to deliver infrastructure and power on the timelines the market now demands,” Gavin Rennick, president of SLB’s New Energy and Industrial business, said in a news release. “By bringing together complementary infrastructure and power capabilities, we will help developers accelerate deployment of new data center capacity.”

The companies seek to specifically offer the modular technologies in areas without traditional grid connections or where grid capacity is limited.

They also aim to improve the "efficiency, flexibility and environmental performance of future data center energy systems," potentially through solutions like hybrid power systems and digital energy management, according to the news release.

Goldman Sachs estimates that U.S. data center capacity will more than double from 31 gigawatts in 2025 to 66 gigawatts in 2027. Other reports predict that Houston and Texas will be home to a significant portion of the data center boom, with capacity in the city and the state also expected to double in the next few years.

“The scale and complexity of AI energy infrastructure is fundamentally changing how power systems are built and deployed,” Ron Gusek, CEO of Liberty Energy, added in the release. “Liberty’s comprehensive power service platform is engineered to meet this transition, as customers increasingly prioritize tailored, integrated solutions. Building on our long-standing relationship with SLB, we are excited to bring power solutions that address immediate capacity constraints while supporting the next generation of energy systems.”

SLB sold its onshore hydraulic fracturing business in the United States and Canada to Liberty Energy in December 2020 in exchange for a 37 percent equity interest in the company.

New Rice study details how carbon capture could reduce AI data center emissions

by the numbers

A new study out of Rice University points to carbon capture and storage methods as pivotal solutions to addressing emissions from AI-driven data centers.

The study was authored by Hon Chung Lau, an adjunct professor in the Department of Chemical and Biomolecular Engineering at Rice University and founder of Low Carbon Energies LLC, and Steve C. Tsai, an energy transition consultant at Low Carbon Energies LLC, and published in the journal Energy & Fuels.

According to the study, U.S. data center power capacity could more than quadruple in five years, growing from 40 gigawatts in 2025 to 169 gigawatts by 2030. Without proper regulation of emissions, the report estimates that carbon dioxide produced by fossil-fuel power plants supplying electricity to data centers could grow at the same scale, increasing from 90 million metric tons to more than 404 million metric tons over the same time period.

The researchers analyzed publicly available data on announced U.S. data centers, which included energy sources, locations, and projected power capacity before estimating data center-related carbon emissions based on each state’s electricity mix. From there, they examined whether those emissions could be captured and stored underground in saline aquifers.

The team estimates that 34 states have enough saline aquifer storage capacity to store more than 100 years of projected data center-related carbon dioxide emissions beyond 2030. Aquifers could store an estimated 59 million metric tons of data center-related carbon dioxide, or about 66 percent of the sector’s emissions in 2025. However, that calculation could grow to 299 million metric tons, or about 74 percent of projected data center-related emissions by 2030.

The researchers found that more than 90 percent of data center-related carbon dioxide emissions could potentially be mitigated through carbon capture and storage when out-of-state storage options are included, even though they note that carbon capture isn’t the only solution.

“It does show that the geology exists to make a meaningful impact, especially in states where data center growth is strongest,” Lau said in a news release.

Rapid growth in states including Texas, Virginia, Pennsylvania, Ohio, Arizona, Colorado, Utah and Illinois was considered in the study. According to the findings, Texas would need to add 25 gigawatts of power capacity by 2030 to meet projected data center demand, as data centers require reliable electricity 24/7.

“Data centers are becoming one of the defining energy challenges of the AI era,” Lau added in the news release. “The question is not only whether we can build enough computing infrastructure, but whether we can power it in a way that is reliable, affordable and compatible with decarbonization goals.”