Planckton Data co-founders were recently featured on Energy Tech Startups Podcast. Courtesy photo

There’s a reason “carbon footprint” became a buzzword. It sounds like something we should know. Something we should measure. Something that should be printed next to the calorie count on a label.

But unlike calories, a carbon footprint isn’t universal, standardized, or easy to calculate. In fact, for most companies—especially in energy and heavy industry—it’s still a black box.

That’s the problem Planckton Data is solving.

On this episode of the Energy Tech Startups Podcast, Planckton Data co-founders Robin Goswami and Sandeep Roy sit down to explain how they’re turning complex, inconsistent, and often incomplete emissions data into usable insight. Not for PR. Not for green washing. For real operational and regulatory decisions.

And they’re doing it in a way that turns sustainability from a compliance burden into a competitive advantage.

From calories to carbon: The label analogy that actually works

If you’ve ever picked up two snack bars and compared their calorie counts, you’ve made a decision based on transparency. Robin and Sandeep want that same kind of clarity for industrial products.

Whether it’s a shampoo bottle, a plastic feedstock, or a specialty chemical—there’s now consumer and regulatory pressure to know exactly how sustainable a product is. And to report it.

But that’s where the simplicity ends.

Because unlike food labels, carbon labels can’t be standardized across a single factory. They depend on where and how a product was made, what inputs were used, how far it traveled, and what method was used to calculate the data.

Even two otherwise identical chemicals—one sourced from a refinery in Texas and the other in Europe—can carry very different carbon footprints, depending on logistics, local emission factors, and energy sources.

Planckton’s solution is built to handle exactly this level of complexity.

AI that doesn’t just analyze

For most companies, supply chain emissions data is scattered, outdated, and full of gaps.

That’s where Planckton’s use of AI becomes transformative.

  • It standardizes data from multiple suppliers, geographies, and formats.
  • It uses probabilistic models to fill in the blanks when suppliers don’t provide details.
  • It applies industry-specific product category rules (PCRs) and aligns them with evolving global frameworks like ISO standards and GHG Protocol.
  • It helps companies model decarbonization pathways, not just calculate baselines.

This isn’t generative AI for show. It’s applied machine learning with a purpose: helping large industrial players move from reporting to real action.

And it’s not a side tool. For many of Planckton’s clients, it’s becoming the foundation of their sustainability strategy.

From boardrooms to smokestacks: Where the pressure is coming from

Planckton isn’t just chasing early adopters. They’re helping midstream and upstream industrial suppliers respond to pressure coming from two directions:

  1. Downstream consumer brands—especially in cosmetics, retail, and CPG—are demanding footprint data from every input supplier.
  2. Upstream regulations—especially in Europe—are introducing reporting requirements, carbon taxes, and supply chain disclosure laws.

The team gave a real-world example: a shampoo brand wants to differentiate based on lower emissions. That pressure flows up the value chain to the chemical suppliers. Who, in turn, must track data back to their own suppliers.

It’s a game of carbon traceability—and Planckton helps make it possible.

Why Planckton focused on chemicals first

With backgrounds at Infosys and McKinsey, Robin and Sandeep know how to navigate large-scale digital transformations. They also know that industry specificity matters—especially in sustainability.

So they chose to focus first on the chemicals sector—a space where:

  • Supply chains are complex and often opaque.
  • Product formulations are sensitive.
  • And pressure from cosmetics, packaging, and consumer brands is pushing for measurable, auditable impact data.

It’s a wedge into other verticals like energy, plastics, fertilizers, and industrial manufacturing—but one that’s already showing results.

Carbon accounting needs a financial system

What makes this conversation unique isn’t just the product. It’s the co-founders’ view of the ecosystem.

They see a world where sustainability reporting becomes as robust as financial reporting. Where every company knows its Scope 1, 2, and 3 emissions the way it knows revenue, gross margin, and EBITDA.

But that world doesn’t exist yet. The data infrastructure isn’t there. The standards are still in flux. And the tooling—until recently—was clunky, manual, and impossible to scale.

Planckton is building that infrastructure—starting with the industries that need it most.

Houston as a launchpad (not just a legacy hub)

Though Planckton has global ambitions, its roots in Houston matter.

The city’s legacy in energy and chemicals gives it a unique edge in understanding real-world industrial challenges. And the growing ecosystem around energy transition—investors, incubators, and founders—is helping companies like Planckton move fast.

“We thought we’d have to move to San Francisco,” Robin shares. “But the resources we needed were already here—just waiting to be activated.”

The future of sustainability is measurable—and monetizable

The takeaway from this episode is clear: measuring your carbon footprint isn’t just good PR—it’s increasingly tied to market access, regulatory approval, and bottom-line efficiency.

And the companies that embrace this shift now—using platforms like Planckton—won’t just stay compliant. They’ll gain a competitive edge.

Listen to the full conversation with Planckton Data on the Energy Tech Startups Podcast:

Hosted by Jason Ethier and Nada Ahmed, the Digital Wildcatters’ podcast, Energy Tech Startups, delves into Houston's pivotal role in the energy transition, spotlighting entrepreneurs and industry leaders shaping a low-carbon future.


Yao Huang is the guest on the latest episode of the Energy Tech Startups Podcast. Courtesy photo

Tech entrepreneur turned climate investor is on a mission to monetize carbon removal

now streaming

The climate conversation is evolving — fast. It’s no longer just about emissions targets and net-zero commitments. It’s about capital, infrastructure, and execution at industrial scale.

That’s exactly where Yao Huang operates. A seasoned tech entrepreneur turned climate investor, Yao brings sharp clarity to one of the biggest challenges in climate innovation: how do we fund and scale technologies that remove carbon without relying on goodwill or government subsidies?

In this episode of the Energy Tech Startups Podcast, Yao sits down with hosts Jason Ethier and Nada Ahmed for a wide-ranging conversation that redefines how we think about decarbonization. From algae-based photobioreactors that capture CO₂ at the smokestack, to financing models that mirror real estate and infrastructure—not venture capital—Yao lays out a case for why the climate fight will be won or lost on spreadsheets, not slogans.

Her message is as bold as it is practical: this isn’t about saving the planet for the sake of it. It’s about building profitable, resilient systems that scale. And Houston, with its industrial base and project finance expertise, is exactly the place to do it.

The 40-Gigaton Challenge—and a Pandemic Pivot

Yao’s entry into climate wasn’t part of a long-term plan. It was sparked by a quiet moment during the pandemic—and a book.

Reading How to Avoid a Climate Disaster by Bill Gates, she came to two uncomfortable realizations:

  1. The people in power don’t actually have this figured out, and
  2. She would be alive to suffer the consequences.

That insight jolted her out of the traditional tech world and into climate action. She studied at Stanford, surrounded herself with mentors, and began diving into early-stage climate deals. But she quickly realized that most of the solutions she was seeing were still years away from commercialization.

So she narrowed her focus: no R&D moonshots, no science experiments—just deployable solutions that could scale now.

Carbon Optimum: Where Algae Meets Infrastructure

That’s how she found Carbon Optimum, a company using algae photobioreactors to remove CO₂ directly from industrial emissions. Their approach is both elegant and economic:

  • Install algae reactors next to major emitters like coal and cement plants.
  • Feed the algae with flue gas, allowing it to absorb CO₂ in a controlled system.
  • Harvest the algae and convert it into valuable commodities like bio-oils, fertilizer, and food ingredients.

It’s a nature-based solution, enhanced by engineering.
One acre of tanks can capture emissions and generate profit—without subsidies.

“This is one of the few solutions I’ve seen that can scale profitably and quickly,” Yao says. “And we’re not inventing anything new—we’re just doing it better.”

The Real Problem? It’s Capital, Not Carbon

As an investor, Yao is blunt: most climate startups are misaligned with the capital markets.

They’re following a tech startup playbook—built for SaaS, not steel. But building climate infrastructure requires a completely different approach: project finance, blended capital, debt structures, carbon credit integration, and regulatory incentives.

“Climate tech is more like real estate or healthcare than software,” Yao explains. “You don’t raise six rounds of venture. You build a stack—grants, equity, debt, tax credits—and you structure your project like infrastructure.”

It’s not just theory. It’s exactly how Carbon Optimum is expanding—through partnerships, offtake agreements, and real-world deployments. And it’s why she believes many climate startups fail: they don’t speak the language of finance.

Houston’s Role in the Climate Capital Stack

For Yao, Houston isn’t just a backdrop—it’s a strategic asset.

The city’s deep bench of project finance professionals, commodity traders, lawyers, and infrastructure veterans makes it uniquely positioned to lead the deployment phase of climate solutions.

“We’ve been calling it the wrong thing,” she says. “This isn’t just about climate—it’s an energy transition. And Houston knows how to build energy infrastructure at scale.”

Still, she notes, the ecosystem needs to evolve. Less education, more execution. Fewer workshops, more closers.

“Houston could be the epicenter of this movement—if we activate the right people and get the right projects over the line.”

From Carbon Capture to Circular Economies

The potential applications of Carbon Optimum’s algae platform go beyond carbon capture. Because the output—algae biomass—can be converted into:

  • Renewable oil
  • High-efficiency fertilizers (critical in today’s geopolitically fragile supply chains)
  • Food ingredients rich in protein and nutrients
  • Even biochar, a highly stable form of carbon sequestration

It’s scalable, modular, and location-agnostic. In island nations, Yao notes, these systems can offer energy independence by turning waste CO₂ into local energy and fertilizer—without needing to import fuels or food.

“It’s not just emissions reduction. It’s economic sovereignty through circular systems.”

Doing, Not Just Talking

One of Yao’s key takeaways for founders? Don’t waste time. Climate startups don’t have the luxury of trial-and-error cycles stretched over years.

“Founders need to get real about what it takes to scale: talent, capital, storytelling, partnerships. If you’re not ready to do that, maybe you should be a CSO, not a CEO.”

She also points out that founders don’t need to hire everyone—they need to tap the right networks. And in cities like Houston, those networks exist—if you know how to motivate them.

“It takes a different kind of leadership. You’re not just raising money—you’re moving people.”

Why This Episode Matters

This conversation is for anyone who’s serious about scaling real solutions to the climate crisis. Whether you’re a founder navigating capital markets, an investor seeking return and impact, or a policymaker designing the frameworks — Yao Huang offers a grounded, urgent, and actionable perspective.

It’s not about hope. It’s about execution.

Listen to the full episode of the Energy Tech Startups Podcast with Yao Huang:


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Hosted by
Jason Ethier and Nada Ahmed, the Digital Wildcatters’ podcast, Energy Tech Startups, delves into Houston's pivotal role in the energy transition, spotlighting entrepreneurs and industry leaders shaping a low-carbon future.


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Houston companies advance 200MW green ammonia plant in South Texas

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Two global companies with a major presence in Houston are teaming up on a green ammonia plant in Port of Victoria, Texas.

Topsoe, a Danish company with operations in Houston and Bayport, Texas, has been tapped to provide ammonia synthesis technology for the project being developed by First Ammonia, a New York-based company with offices in Houston and Denmark.

The flagship 200-megawatt plant will use renewable electricity to produce green hydrogen through electrolysis, which will then be combined with nitrogen from a nearby Air Liquide pipeline to make green ammonia, according to First Ammonia. It is expected to serve both U.S. and global markets.

According to First Ammonia, every 100,000 tons of electric ammonia produced avoids approximately 240,000 tons of CO2 emissions compared to fossil ammonia

The Topsoe technology used on site is designed to be able to increase production from 10 percent to 100 percent within 30 minutes, and decrease production at a similar rate, allowing the plant to respond to fluctuations from solar- or wind-based energy sources.

“Topsoe is the world leader in ammonia synthesis, and First Ammonia is delighted to continue our partnership with them in establishing a green ammonia industry in the US and around the world,” Joel Moser, CEO of First Ammonia, said in a news release.

Topsoe has previously signed on to supply its 100-megawatt solid oxide electrolyser (SOEC) to the First Ammonia project. However, the company announced in March that it did not extend the contract after multiple delays.

The First Ammonia project was originally expected to come online by 2027 and to produce 1.1 million tonnes of green ammonia. The project is now expected to reach financial before the end of 2026, with construction slated to begin in 2027 and commercial operations launching by 2029.

“As green ammonia projects move from ambition to execution, operational flexibility becomes increasingly important,” Yassir Ghiyati, chief commercial officer at Topsoe, added in a news release. “We’re proud to support First Ammonia with technology designed to enable efficient and reliable green ammonia production. We look forward to continuing to work with the First Ammonia team to help bring this important U.S project to life.”

NASA and Houston researcher tackle climate-driven water quality risks

water watch

Climate change means far more to public health than living with hotter days. Transformations in our weather are contributing to challenges in accessing safe drinking water in some communities.

One of the most dire situations is along the US–Mexico border. The National Aeronautics and Space Administration (NASA) is seeking to address that issue with its Water Quality Applications program. An 11-researcher project led by a UTHealth Houston School of Public Health faculty member has been selected to participate.

“Drinking water is one of the most fundamental public health protections, but producing safe drinking water involves a delicate balance,” Yun Hang, assistant professor of environmental and occupational health sciences, said in a news release. Her team’s proposal was one of 93 that were submitted for funding through NASA’s Research Opportunities in Space and Earth Sciences (ROSES)-2025 program.

This is the first time that NASA has worked with a team devoted to water quality applications. The group, which includes researchers from across the nation, will use satellite observations of Earth, as well as hydrologic modeling, to potentially anticipate and act on water quality conditions as they change. Challenges addressed over the course of the three-year program, which kicked off in June, might include problems with water quality due to climate variability and increased pressure on water resources.

Hang’s team will focus on a pair of borderlands: Paso del Norte and the Rio Grande Valley.

“Working closely with El Paso Water ensures that our research addresses real operational needs while helping utilities better prepare for climate-related water quality changes and continue providing safe drinking water to communities across the Texas border region,” Hang added in the release.

She and the team will use data gathered by NASA on both past and future Earth-observing missions, which will allow them to track environmental changes that may affect source water quality. Combined with past water treatment records and hydrologic models, the team will also utilize artificial intelligence to develop predictive tools that aim to stop issues before they become larger hurdles to water safety.

Another one of the project’s goals is to create visualization tools and source water summaries that can be utilized by those without scientific expertise. The tools will be produced in English and Spanish to further broaden their accessibility.

The hope is that the materials made by the team will also go far beyond the border, with protocols that can be adapted or adopted by other areas dealing with water quality issues.

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This article originally appeared on our sister site, InnovationMap.com.

New research reveals what really drives data center location decisions

Guest Column

Recent power outages and the surge in AI-driven computing have made data center siting decisions more consequential than ever, especially as energy and water constraints tighten. Communities invest public dollars on the promise of jobs and growth, while firms weigh long-term commitments to land, power and connectivity.

Against that evolving backdrop, a critical question comes into focus: Where do data centers get built — and what actually drives those decisions?

A new study by Tommy Pan Fang (Rice Business) and Shane Greenstein (Harvard Business School) provides the first large-scale statistical analysis of data center location strategies across the United States. It offers policymakers and firms a clearer starting point for understanding how different types of data centers respond to economic and strategic incentives.

Published in the journal Strategy Science, the study examines two major types of infrastructure: third-party colocation centers that lease server space to multiple firms, and hyperscale cloud centers owned by providers like Amazon, Google and Microsoft.

Key takeaways:

  • Third-party colocation centers are physical facilities in close proximity to firms that use them, while cloud providers operate large data centers from a distance and sell access to virtualized computing resources as on‑demand services over the internet.
  • Hospitals and financial firms often require urban third-party centers for low latency and regulatory compliance, while batch processing and many AI workloads can operate more efficiently from lower-cost cloud hubs.
  • For policymakers trying to attract data centers, access to reliable power, water and high-capacity internet matter more than tax incentives.

What are the two main data center location strategies?

The study draws on pre-pandemic data from 2018 and 2019, a period of relative geographic stability in supply and demand. This window gives researchers a clean baseline before remote work, AI demand and new infrastructure pressures began reshaping internet traffic patterns.

The findings show that data centers follow a bifurcated geography:

  • Third-party centers cluster in dense urban markets, where buyers prioritize proximity to customers despite higher land and operating costs.
  • Cloud providers, by contrast, concentrate massive sites in a small number of lower-density regions, where electricity, land and construction are cheaper and economies of scale are easier to achieve.

Third-party data centers, in other words, follow demand. They locate in urban markets where firms in finance, healthcare and IT value low latency, secure storage, and compliance with regulatory standards.

Using county-level data, the researchers modeled how population density, industry mix and operating costs predict where new centers enter. Every U.S. metro with more than 700,000 residents had at least one third-party provider, while many mid-sized cities had none.

Map of data centers

This pattern challenges common assumptions. Third-party facilities are more distributed across urban America than prevailing narratives suggest.

“For industries where speed is everything, being too far from the physical infrastructure can meaningfully affect performance and risk,” Pan Fang says. “Proximity isn’t optional for sectors that can’t absorb delay.”

In critical operations, even slight pauses can have real consequences. For hospital systems, lag can affect performance and risk exposure. And in high-frequency trading, milliseconds can determine whether value is captured or lost in a transaction.

Why does distance matter for cloud data center costs?

For cloud providers, the picture looks very different. Their decisions follow a logic shaped primarily by cost and scale. Because cloud services can be delivered from afar, firms tend to build enormous sites in low-density regions where power is cheap and land is abundant.

These facilities can draw hundreds of megawatts of electricity and operate with far fewer employees than urban centers. “The cloud can serve almost anywhere,” Pan Fang says, “so location is a question of cost before geography.”

The study finds that cloud infrastructure clusters around network backbones and energy economics, not talent pools. Well-known hubs like Ashburn, Virginia — often called “Data Center Alley” — reflect this logic, having benefited from early network infrastructure that made them natural convergence points for digital traffic.

Local governments often try to lure data centers with tax incentives, betting they will create high-tech jobs. But the study suggests other factors matter more to cloud providers, including construction costs, network connectivity and access to reliable, affordable electricity.

When cloud centers need a local presence, distance can sometimes become a constraint. Providers often address this by working alongside third-party operators. “Third-party centers can complement cloud firms when they need a foothold closer to customers,” Pan Fang says.

That hybrid pattern — massive regional hubs complementing strategic colocation — may define the next phase of data center growth.

Looking ahead, shifts in remote work, climate resilience, energy prices and AI-driven computing may reshape where new facilities go. Some workloads may move closer to users, while others may consolidate into large rural hubs. Emerging data-sovereignty rules could also redirect investment beyond the United States.

“The cloud feels weightless,” Pan Fang says, “but it rests on real choices about land, power and proximity.”

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This article originally appeared on Rice Business Wisdom. Written by Scott Pett. Pan Fang and Greenstein (2025). “Where the Cloud Rests: The Economic Geography of Data Centers,” Strategy Science.