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Could Living Near More Trees Boost Your Heart?

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02 Sep, 2024

This post was originally published on Eco Watch

Living in a neighborhood with a high concentration of trees could significantly lower levels of inflammation and, importantly, decrease the risk of heart disease, new research from Green Heart Louisville’s first wave of clinical research from its HEAL study shows.

Aruni Bhatnagar, the medical professor and cardiology researcher at the University of Louisville who is spearheading the project, told The Washington Post that he wanted to “do something” about the air pollution plaguing the city. His solution was to plant thousands of trees in Louisville neighborhoods and methodically study health data from participating residents to see the effect they had on health. 

“We are trying to see if we can decrease the rates of heart disease in a community,” Bhatnagar told NBC.

The results showed a “significant decrease” in levels of hs-CRP, an important marker for inflammation, in areas where tree and shrub counts were more than doubled. In excess, inflammation is known to contribute to a laundry list of diseases and illnesses, including cancer, Alzheimer’s disease, diabetes, obesity, and as the study points out, heart disease. 

“I wouldn’t have expected such a strong biomarker response, Peter James, director of the Center for Occupational and Environmental Health at the University of California, Davis School of Medicine, told NBC. “And that speaks to maybe something truly is causal here with how trees impact health.” 

Bhatnagar is leading dozens of researchers who are monitoring the health data from more than 750 participants, who range from 25 to 75 years old. The participants are part of a middle-income neighborhood, which tend to have both fewer trees and worse health outcomes compared to affluent neighborhoods.

Map of the Green Heart Louisville Project area showing neighborhoods where trees were planted and those where no trees were planted for the project. University of Louisville

Some previous research has shown that people living in greener spaces tend to have better health outcomes, but the fact that most of those greener spaces happened to be in wealthy areas raises some questions. Namely, whether living in green areas can truly lead to improved health, or whether there were other factors to consider, like socioeconomic-related differences in levels of elevated stress — which has also been shown to lead to inflammation — or access to healthcare.

“We can’t just go, ‘Oh, look, this is [a] greener place and people are happier’ because most places that are greener are richer, etc.,” Bhatnagar told The Washington Post. He also mentioned his interest in the Bradford Hill criteria of causation, a group of nine scientific principles to determine whether there is a true causal — or cause and effect — relationship between two correlated things, or if the correlation is merely coincidental.

“Although several previous studies have found an association between living in areas of high surrounding greenness and health, this is the first study to show that a deliberate increase in greenness in the neighborhood can improve health,” Bhatnagar told Medical Xpress. “With these results and additional studies that we hope to report soon, we are closer to understanding the impact of local tree cover on residents’ health. This finding will bolster the push to increase urban greenspaces.”

The post Could Living Near More Trees Boost Your Heart? 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

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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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