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Scientists Engineer Bacteria to Break Down Microplastics Found in Wastewater

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12 Jan, 2025

This post was originally published on Eco Watch

Microplastics — the ubiquitous tiny plastic particles that are the result of the breakdown of plastic water bottles, packaging and synthetic clothing fibers — can run through wastewater treatment plants, making their way into the environment.

Researchers have engineered bacteria that is commonly found in the treatment plants to break down microplastic pollution before it has a chance to persist in the environment.

“Wastewater treatment plants are one of the major pathways for microplastics to enter the environment. In general, microplastics are contaminants of global concern that pose risks to ecosystems and human health,” the authors wrote in the study. “With a focus on wastewater, a major pathway for microplastics to enter the environment, this study demonstrates a proof of concept for engineering environmental microbiomes to rapidly degrade PET plastics.”

University of Waterloo researchers added DNA to several bacteria species found in wastewater. They then allowed them to biodegrade a common plastic — polyethylene terephthalate (PET) — found in clothing, carpet and food and beverage containers, a press release from the University of Waterloo said.

Conjugation of pFAST-PETase-cis into wastewater bacteria. Microbial Biotechnology (2024). DOI: 10.1111/1751-7915.70015

It takes hundreds of years for PET plastics to degrade in the natural environment. They break down over time into microplastics — plastic pieces less than five millimeters in length — which then enter the food chain. Chemicals in these plastics can lead to decreased reproductive health, insulin resistance and cancer, among other adverse health impacts.

“Think of these bacteria that already exist in water systems to clean up microplastics as biorobots that can be programmed to get the job done,” said Dr. Marc Aucoin, a chemical engineering professor at the University of Waterloo, in the press release. “Microplastics in water also enhance the spread of antibiotic resistance, so this breakthrough could also address that concern.”

The research team used “bacterial sex,” a natural process where genetic material is shared between bacteria when they multiply. This enables a new trait to be introduced into the target bacteria, making them able to break down microplastics.

“As next steps, we will use modelling to understand how well the bacteria transfer the new genetic information under different environmental conditions and thus how effectively they can break down the plastics,” said Dr. Brian Ingalls, a professor of applied mathematics at the University of Waterloo, in the press release.

“The long-term vision is to break down microplastics in wastewater treatment plants at scale.”

The team also hopes to discover ways to clean up plastic waste accumulating in the world’s oceans.

“We will assess the risks of using engineered, plastic-eating bacteria in the natural environment,” said Aaron Yip, Ph.D. candidate in the University of Waterloo’s Department of Chemical Engineering, in the press release. “Right now, microplastic degradation in wastewater treatment plants is a safer application to target. Many of these facilities are already designed to neutralize bacteria in wastewater, which would kill any engineered bacteria prior to discharging water back into the environment.”

The study, “Degradation of polyethylene terephthalate (PET) plastics by wastewater bacteria engineered via conjugation,” was published in the journal Microbial Biotechnology.

The post Scientists Engineer Bacteria to Break Down Microplastics Found in Wastewater appeared first on EcoWatch.

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Turning down the heat: how innovative cooling techniques are tackling the rising costs of AI's energy demands

Turning down the heat: how innovative cooling techniques are tackling the rising costs of AI's energy demands

As enterprises accelerate their AI investments, the energy demand of AI’s power-hungry systems is worrying both the organisations footing the power bills as well as those tasked with supplying reliable electricity. From large language models to digital twins crunching massive datasets to run accurate simulations on complex city systems, AI workloads require a tremendous amount of processing power.

Of course, at the heart of this demand are data centres, which are evolving at breakneck speed to support AI’s growing potential. The International Energy Agency’s AI and Energy Special Report recently predicted that data centre electricity consumption will double by 2030, identifying AI as the most significant driver of this increase.1

The IT leaders examining these staggering predictions are rightly zeroing in on improving the efficiency of these powerful systems. However, the lack of expertise in navigating these intricate systems, combined with the rapidity of innovative developments, is causing heads to spin. Although savvy organisations are baking efficiency considerations into IT projects at the outset, and are looking across the entire AI life cycle for opportunities to minimise impact, many don’t know where to start or are leaving efficiency gains on the table. Most are underutilising the multiple IT efficiency levers that could be pulled to reduce the environmental footprint of their IT, such as using energy-efficient software languages and optimising data use to ensure maximum data efficiency of AI workloads. Among the infrastructure innovations, one of the most exciting advancements we are seeing in data centres is direct liquid cooling (DLC). Because the systems that are running AI workloads are producing more heat, traditional air cooling simply is not enough to keep up with the demands of the superchips in the latest systems.

DLC technology pumps liquid coolants through tubes in direct contact with the processors to dissipate heat and has been proven to keep high-powered AI systems running safely. Switching to DLC has had measurable and transformative impact across multiple environments, showing reductions in cooling power consumption by nearly 90% compared to air cooling in supercomputing systems2.

Thankfully, the benefits of DLC are now also extending beyond supercomputers to reach a broader range of higher-performance servers that support both supercomputing and AI workloads. Shifting DLC from a niche offering to a more mainstream option available across more compute systems is enabling more organisations to tap into the efficiency gains made possible by DLC, which in some cases has been shown to deliver up to 65% in annual power savings3. Combining this kind of cooling innovation with new and improved power-use monitoring tools, able report highly accurate and timely insights, is becoming critical for IT teams wanting to optimise their energy use. All this is a welcome evolution for organisations grappling with rising energy costs and that are carefully considering total cost of ownership (TCO) of their IT systems, and is an area of innovation to watch in the coming years.

In Australia, this kind of technical innovation is especially timely. In March 2024, the Australian Senate established the Select Committee on Adopting Artificial Intelligence to examine the opportunities and impacts of AI technologies4. Among its findings and expert submissions was a clear concern about the energy intensity of AI infrastructure. The committee concluded that the Australian Government legislate for increased regulatory clarity, greater energy efficiency standards, and increased investment in renewable energy solutions. For AI sustainability to succeed, it must be driven by policy to set actionable standards, which then fuel innovative solutions.

Infrastructure solutions like DLC will play a critical role in making this possible — not just in reducing emissions and addressing the energy consumption challenge, but also in supporting the long-term viability of AI development across sectors. We’re already seeing this approach succeed in the real world. For example, the Pawsey Supercomputing Centre in Western Australia has adopted DLC technology to support its demanding research workloads and, in doing so, has significantly reduced energy consumption while maintaining the high performance required for AI and scientific computing. It’s a powerful example of how AI data centres can scale sustainably — and telegraphs an actionable blueprint for others to follow.

Furthermore, industry leaders are shifting how they handle the heat generated by these large computing systems in order to drive further efficiency in AI. Successfully using heat from data centres for other uses will be a vital component to mitigating both overall energy security risks and the efficiency challenges that AI introduces. Data centres are being redesigned to capture by-product heat and use it as a valuable resource, rather than dispose of it as waste heat. Several industries are already benefiting from capturing data centre heat, such as in agriculture for greenhouses, or heating buildings in healthcare and residential facilities. This has been successfully implemented in the UK with the Isambard-AI supercomputer and in Finland with the LUMI supercomputer — setting the bar for AI sustainability best practice globally.

The message is clear: as AI becomes a bigger part of digital transformation projects, so too must the consideration for resource-efficient solutions grow. AI sustainability considerations must be factored into each stage of the AI life cycle, with solutions like DLC playing a part in in a multifaceted IT sustainability blueprint.

By working together with governments to set effective and actionable environmental frameworks and benchmarks, we can encourage the growth and evolution of the AI industry, spurring dynamic innovation in solutions and data centre design for the benefit of all.

1. AI is set to drive surging electricity demand from data centres while offering the potential to transform how the energy sector works – News – IEA
2. https://www.hpe.com/us/en/newsroom/blog-post/2024/08/liquid-cooling-a-cool-approach-for-ai.html
3. HPE introduces next-generation ProLiant servers engineered for advanced security, AI automation and greater performance
4. https://www.aph.gov.au/Parliamentary_Business/Committees/Senate/Adopting_Artificial_Intelligence_AI

Image credit: iStock.com/Dragon Claws

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