EVERYDAY ENERGY

Energy truly IS everywhere according to ChatGPT

Asking ChatGPT what all was made from petroleum produced surprising results - the answer: everything. Photo by Sanket Mishra/Unsplash

I sat down to have a conversation with ChatGPT from OpenAI about energy by-products; specifically, everyday items we use that contain some form of petrochemicals. My first prompt was rather broad, so I wasn’t surprised to get back a rather broad answer highlighting product categories instead of specific examples. Plastics, synthetic fibers, cleaning products, personal care products, medicines, paints & coatings, and adhesives were all succinctly summarized, but I wanted to dive deeper.

Given that AI has an almost limitless reach, I asked for a comprehensive list of all the products we use in everyday life that are made from petrochemicals. Turns out, ChatGPT has some healthy boundaries, so it pushed back, only offering a slightly more detailed list of the categories produced from the first prompt.

Not to be deterred, I asked for additional examples. I didn’t want to continue getting spoon-fed 10 items at a time, so I asked for 200. Less than comprehensive, more than the crumbs I was getting.

In entertaining fashion, ChatGPT told me compiling a list of 200 items might be challenging, but that it could offer up 100. The brazen negotiation made me smile.

I complimented the list and nudged a bit, encouraging ChatGPT it could come up with another 100 items if it tried. Much like a teenager wishes to stave off further questioning from a nosy parent, ChatGPT proffered up a second response of 100 items–almost half of which were simply things before which it added the qualifier “synthetic.” Salty.

As my intention is not to bore you, but rather enhance the knowledge of our readers by understanding how pervasive petrochemical products are in our everyday life, I settled on a more direct inquiry with a capped demand prompt: “What would you say are the 10 most surprising things in common everyday use that contain petrochemical products?”

Most of the answers featured wax-based products, like lotions, crayons, and lipstick–not necessarily earth-shattering realizations given my familiarity with cosmetics as petroleum by-products. I was pleasantly surprised to learn that chewing gum, with its synthetic rubber base enabling theoretically endless chewing, is derived from petroleum. I was also surprised to learn that many artificial sweeteners, like saccharin and aspartame, are made from petrochemicals. Huh.

There was one item on the list, however, that helped me see how truly pervasive the energy industry is, and not just for petrochemicals. Tucked in nonchalantly at #6 was Deodorant. My brain jumped immediately to the waxy base of a solid sweat deterrent, but my eyes got a curveball. ChatGPT writes, “Many deodorants contain aluminum, which is often derived from bauxite, a mineral that is usually mined from the earth using petroleum-powered machinery.” Now that was an answer I wasn’t expecting.

While my initial inference stood true – the smooth glide of a buttery solid antiperspirant is without a doubt derived from petrochemicals (not to mention the plastic packaging surrounding it), I wasn’t expecting ChatGPT to rope in the oft petroleum-fueled tools used to make said product. If that’s true, then nearly every item on the planet is derived from petroleum. Or at the very least, some source of energy. Regardless of whether the machinery used runs on gasoline, electricity, or wind power, literally almost everything that is produced on this earth is related to the energy industry.

Even if it’s hand-made, it’s technically still energy-adjacent, assuming we all bathe regularly with soap, yet another on the list of commonly used items derived from petroleum by-products. It’s certainly directly powering some manual activities, for those busting stress and bad breath with gum, or drinking a diet soda to power through. No pun intended.

I share this amusing tale simply to clarify the ubiquitous nature of energy in all parts of the modern world. As we look toward the #futureofenergy, we must be cognizant of its universal reach. It’s not necessarily realistic to switch from one source of energy to another overnight, but we do have a responsibility to seek cleaner, healthier, more efficient sources of energy while sustaining the life to which we have all grown accustomed.

Much like ChatGPT thought she couldn’t come up with 200 items derived from petroleum products, many think Houston will be unable to drive the Energy Transition, given our extensive petroleum focus. But like so many fellow Houstonians before us, we love a good challenge.

Just keep prompting us, and we’ll eventually unlock infinite potential for the #futureofenergy. It’s a limitless time to be in Houston, absorbing wisdom the city so willingly wants to share with the growing ecosystem of innovators. Just ask the growing number of almost 5,000 Energy-related firms in Houston. We’re just getting started.

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Lindsey Ferrell is a contributing writer to EnergyCapitalHTX and founder of Guerrella & Co.

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A View From HETI

A View From UH

A University of Houston team looked into what areas in Houston had the highest impact on emissions and how certain meteorological factors play into ozone formation. Photo via UH.edu

A team of researchers at the University of Houston are using machine learning to help guide pollution fighting strategies.

As reported in the journal Environmental Pollution last month, the team used the SHAP algorithm of machine learning (a game theory approach) and the Positive Matrix Factorization to pinpoint what areas in Houston had the highest impact on emissions and how certain meteorological factors play into ozone formation.

The paper was authored by Delaney Nelson, a doctoral student at the Department of Earth and Atmospheric Sciences of UH, and Yunsoo Choi, corresponding author and professor of atmospheric chemistry, AI deep learning, air quality modeling and satellite remote sensing.

The team's research closely tracked nitrogen-based compound and volatile organic compound measurements from Texas Commission on Environmental Quality's monitoring stations in the Houston area. After importing measurements from The Lynchburg Ferry station in Houston's ship channel and the urban Milby Park station, the machine learning and SHAP analysis showed a chemically definitive difference between the two areas.

For example, at the industrial station, the most impactful sources of pollution were from oil and gas flaring/production. At the urban site n_decane and industrial emissions/evaporation had the most impact on ozone.

According to Nelson and Choi, this shows that the machine learning and SHAP analysis approach can be used to tailor more precise air quality management strategies in different areas based on the site's unique characteristics.

“Once we know the specific emission sources and factors, we can develop targeted strategies to reduce emissions, which will in turn reduce ozone in the air and make it healthier for everyone," Choi said in a statement.

“Pollution is a critical issue in Houston, where you have extreme high heat and high concentration of ozone in the summers. The types of insights we got are very useful information for the local community to develop effective policies. That’s why we put our time, effort and technological expertise into this project," he continued.

Next the team envisions applying their approach in different cities and across the country.

“Austin, San Antonio and Dallas all have different characteristics, so I expect (volatile organic compound) sources will also be different,” Choi said. “Identifying VOC sources in different cities is very important because each city should have its own unique pollution fighting strategy.”

This summer, the City of Houston released an updated report on its major strategies to combat climate change and build a more resilient future for its residents.

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