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Northwest Alberta to become home to world’s largest AI data centre

NATURAL GAS POWERED JUST LIKE OUR HYDROGEN PRODUCTION


By Chris Hogg
December 10, 2024
DIGITAL JOURNAL

Image courtesy O'Leary Ventures

Plans for a $70-billion project to build the world’s largest artificial intelligence (AI) data centre were unveiled today, marking a bold step in Alberta’s push to become a global leader in AI innovation.

Dubbed “Wonder Valley,” the proposed data centre is set to be built in the Municipal District of Greenview, an area south and east of Grande Prairie.

The ambitious initiative led by O’Leary Ventures in collaboration with the Municipal District of Greenview, aims to position Alberta as a hub for advanced AI infrastructure and innovation

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Image courtesy O’Leary Ventures

Integrating provincial strategy with global demand

The announcement follows Alberta’s recent strategy, “Powering the Future of Artificial Intelligence,” unveiled to establish the province as North America’s premier AI data centre hub.

Alberta Technology and Innovation Minister Nate Glubish emphasized that the province’s energy resources, competitive tax environment, and cold climate provide a compelling case for such developments.

Global demand for AI data centres is expected to triple by 2030, driven by increasing reliance on machine learning, natural language processing, and other AI technologies.

Wonder Valley is positioned to capitalize on this demand with a vision of creating 7.5 gigawatts of low-cost power over the next decade.

Phase one, estimated at $2 billion, would produce 1.4 gigawatts, with subsequent expansions adding one gigawatt annually​.

Powering the data centre boom

Energy management is a critical focus for the project.

Wonder Valley plans to utilize natural gas and geothermal energy to power its hyperscale data centres.

Alberta’s government is collaborating with infrastructure providers to modernize regulations and ensure that both on-grid and off-grid energy systems can meet the demands of these massive data centres without impacting energy affordability for Albertans​.

While details are not yet known on which companies are involved in the project, CSV Midstream Solutions stated late Monday night it had collaborated with O’Leary Ventures.

KEVIN O' LEARY (MR. WONDERFUL HIS NOM DE GUERRE) FORMER CONSERVATIVE PARTY LEADERSHIP CANDIDATE, 

DUAL US CANADA CITIZEN BENEFITING FROM OUR PUBLIC HEALTHCARE WHILE LIVING AND WORKING IN THE US INCLUDING ON SHARK TANK ON CNBC

“CSV Midstream is proud to collaborate with O’Leary Ventures and the M.D. of Greenview to help facilitate this unique project in the province, creating lasting benefits for the surrounding communities, Alberta, and Canada,” the company said on LinkedIn.
Economic and social impact

Beyond its technological and energy ambitions, Wonder Valley will bring substantial economic benefits if it rolls out as described.

Thousands of jobs are expected during construction and operation, alongside increased tax revenues for the region. O’Leary Ventures has committed to working with Indigenous communities, emphasizing partnerships that create mutual benefits and respect the land’s historical and cultural significance

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This article was created with the assistance of AI. Learn more about our AI ethics policy here.


Written ByChris Hogg
Chris is an award-winning entrepreneur who has worked in publishing, digital media, broadcasting, advertising, social media & marketing, data and analytics. Chris is a partner in the media company Digital Journal, content marketing and brand storytelling firm Digital Journal Group, and Canada's leading digital transformation and innovation event, the mesh conference. He covers innovation impact where technology intersections with business, media and marketing. Chris is a member of Digital Journal's Insight Forum.

AI's Energy Appetite Sparks Global Power Grid Concerns

By Haley Zaremba - Dec 06, 2024, 6:00 PM CST

The exponential growth of AI and data centers is driving a massive surge in global energy demand, straining power grids and raising concerns about energy security.

Investors remain optimistic about AI's potential despite the challenges, but there is growing scrutiny around ESG practices and the need for sustainable energy solutions.

A rapid expansion of clean energy infrastructure, including nuclear power, is crucial to meet AI's energy needs and mitigate its environmental impact.



AI is reshaping the global energy market, and there’s no putting the genie back in the bottle. Machine learning and natural language processing require massive amounts of energy-hungry computing power, and as the industry grows it is already placing a major strain on energy grids around the world. But while there are serious concerns for the economic and environmental impact of the technology’s insatiable energy demand, AI remains a huge investment priority for both the public and the private sector. It’s clear that AI is here to stay, and contingency plans for global energy security are urgently needed.

The global data center market is expected to be valued at around USD $300 billion in 2024, with a projected average compound annual growth rate of about 10% over the next five years, driven almost entirely by the growth of artificial intelligence, according to analysis by TMT Finance.

Law firm DLA Piper recently surveyed 176 senior executives from the data center sector, and found that “70 percent of investors expect to see funding continue to rise for bit barn projects, including debt,” according to a summary report from The Register. “This is despite almost every single one of them – 98 percent of respondents – voicing concerns about the availability and reliability of power to supply those projects,” the summation went on to say.

Indeed, the DLA Piper report found that responsible governance concerns have risen sharply in priority across the sector. Seventy percent of executives surveyed said that they “expect increased scrutiny around ESG practices, particularly regarding the integration of renewable energy and advancements in energy-efficient technologies.” ESG, or ‘environmental, social, and governance’ refers to an investing principle that values social responsibility, environmental stewardship, and good governance.

Balancing AI-driven data center demand with competing energy, water needs is a critical piece of responsible investment and governance, as runaway data center construction could lead to energy shortages, skyrocketing energy prices, and sharply increased greenhouse gas production. Already, the annual power consumption of AI is more than most entire countries – only 16 nations consume more energy in a year than AI. “The almost overnight surge in electricity demand from data centers is now outstripping the available power supply in many parts of the world,” Bloomberg reported back in June.

Some countries, such as Ireland, Saudi Arabia and Malaysia are already facing serious problems with producing enough energy to power their already-planned data centers. In the United States, a recent scientific study found that unless the government invests billions of dollars in generation and transmission capacity over the next few years to meet demand surges from data centers, Americans can expect their energy costs to go up by as much as 70 percent.

Due to the currently insufficient infrastructure, data centers are already facing years-long bottlenecks for connecting to the grid. The Register reports that “utility companies in the US are being flooded with power delivery requests for sites marked for data center construction, but that they are unable to fulfill many of these until the 2030s.” What’s more, many of those utilities are demanding that those project investors pay large upfront non-refundable payments in order to fulfill the projects’ massive infrastructural needs.

Despite the challenges, AI investors remain undeterred. The growth of the sector is inevitable, but will need to be reigned in by governance frameworks to avoid disastrous consequences for the grid, the climate, and the consumer. There are some ambitious plans for making AI less energy-intensive, including through future-facing tech innovations like quantum computing and industry-disrupting algorithms. But until those ideas become reality, what we need is a whole lot more clean energy in a hurry. A rapid buildout of clean energy resources – including nuclear fission and possibly even nuclear fusion – is paramount to balancing this unstoppable market force.

By Haley Zaremba for Oilprice.com

Facebook owner Meta seeks up to 4 GW nuclear capacity

Wednesday, 4 December 2024

Meta is the latest tech company to seek nuclear as an energy source for its growing data needs as it seeks proposals for as much as 4 GW of nuclear capacity in the USA by the early 2030s.

Data centre operators are seeking clear, and 24/7 power sources (Image: Generic data centre representation)

The company, which includes Facebook, Instagram and WhatsApp among its brands, is releasing a request for proposals "to identify nuclear energy developers to help us meet our AI innovation and sustainability objectives".

The target is between 1 and 4 GW of new nuclear generation capacity in the USA. "We are seeking developers with strong community engagement, development, and permitting, and execution expertise that have development opportunities for new nuclear energy resources - either small modular reactors or larger nuclear reactors," the notice announcing the request for proposals (RFP) says. 

It adds "we are taking an open approach with this RFP so we can partner with others across the industry to bring new nuclear energy to the grid". Qualification to be considered closes on 3 January with initial RFP proposals due by 7 February.

In a blog post providing further background, it says: "We are looking to identify developers that can help accelerate the availability of new nuclear generators and create sufficient scale to achieve material cost reductions by deploying multiple units, both to provide for Meta’s future energy needs and to advance broader industry decarbonisation. We believe working with partners who will ultimately permit, design, engineer, finance, construct, and operate these power plants will ensure the long-term thinking necessary to accelerate nuclear technology."

Meta says that nuclear energy is more capital intensive, takes longer to develop, has more regulatory requirements and has a longer operational life so "we need to engage nuclear energy projects earlier in their development lifecycle and consider their operational requirements when designing a contract. And, as scaling deployments of nuclear technology offers the best chance of rapidly reducing cost, engaging with a partner across projects and locations will allow us to ensure that we can deploy strategically".

The decision of the Facebook-owner to bring on its own nuclear energy supply follows in the footsteps of fellow tech giants Microsoft, Google and Amazon, and is the result of the vast energy needs required for huge and growing data centres with artificial intelligence developments set to push those energy requirements even higher. As with renewables, nuclear provides carbon free power, but crucially it also provides that power round-the-clock, which is a key requirement of data centres.

 

After a divisive election, most U.S. adults ready to avoid politics this holiday

More than 7 in 10 U.S. adults hope to avoid political discussions with family over the holidays

American Psychological Association

A majority of U.S. adults hope to avoid political discussions during the holidays and, in some cases, family members they disagree with, according to a survey by the American Psychological Association.

More than 7 in 10 adults (72%) said they hope to avoid discussing politics with family over the holidays. And while 65% of adults said they were not worried that political discussions would hurt their relationships with their family members during the holidays, nearly 2 in 5 adults (39%) said they were stressed by the thought of politics coming up at holiday gatherings.

Perhaps to evade uncomfortable conversations altogether, nearly 2 in 5 adults (38%) said that they are avoiding family they disagree with over the holidays. Younger adults were significantly more likely than adults 65 or older to say they plan to avoid family over the holidays (45% adults ages 18-34, 47% ages 35-44, 42% ages 45-54, and 32% ages 55-64 vs. 23% ages 65+).

“Leading up to the 2024 presidential election, many Americans faced prolonged worry and uncertainty, which can significantly impact our well-being and relationships,” said APA CEO Arthur C. Evans Jr., PhD. “Avoiding conflict is not the same as coping with stress. If we distance ourselves from others due to anticipated disagreements, we risk losing the relationships and communities that are crucial for our well-being, especially during stressful times.”

Before the 2024 U.S. presidential election, APA’s 2024 Stress in America™ survey revealed that more than three-quarters of adults (77%) said the future of the nation was a significant source of stress in their lives. To see how that may have changed after the election, The Harris Poll conducted a survey on behalf of APA among more than 2,000 U.S. adults aged 18+ between Nov. 25 and 27, 2024.

The survey found that more than one-third of adults (35%) said they are more stressed about the future of the nation now than they were leading up to the election and another third of adults said they are now less stressed (32%). A quarter of adults (24%) said their stress about the future of the nation was unchanged and 9% said they were not stressed about the future of the nation then or now.

Adults who said they are more stressed about the future of the nation than they were before the election were also more likely than those who are less stressed to say that they hope to avoid discussing politics with family over the holidays (80% vs 65%) and that they were stressed by the thought of politics coming up at holiday gatherings (50% vs. 33%).

More than 4 in 5 adults (83%) agreed that the holidays are a time to forget political differences, regardless of whether their preferred candidate won or lost the election (84% and 82%, respectively), or if they felt more or less stressed about the future of our nation now than they did leading up to the election (81% and 85%). More than 7 in 10 adults (71%) said that celebrating the holidays this year will be a welcome distraction from their stress.

“Despite the tensions leading up to the election, people have consistently shown that they value meaningful relationships with friends and family over political disagreements,” said Evans. “While conversations around politics and other sensitive topics can be challenging, seeking to understand different perspectives can strengthen and enrich our relationships.”

For people who would like to connect with people who do not share their political views, APA offered the following advice to manage sensitive conversations:

• Be open and kind. Listen and ask questions to help you understand the other person, not to craft a counterargument.
• Find areas where you agree. You may disagree about certain topics but share the same underlying values.
• Accept that you may not change the other person’s mind. Instead, use the conversation as an opportunity to speak about your own experiences.
• Remember that the holidays are about bringing people together, not driving them apart, and focus on good memories that you and your family members have in common.
• Know when to end the conversation. If you find yourself getting worked up, try taking deep breaths, changing the topic of conversation or suggesting another activity – but reinforce that you value the relationship you share with the other person.

For more information on the survey findings, visit the Stress in America webpage.

 
METHODOLOGY

This survey was conducted online within the United States by The Harris Poll on behalf of the American Psychological Association from Nov. 25-27, 2024, among 2,083 U.S. adults ages 18+. The sampling precision of Harris online polls is measured by using a Bayesian credible interval. For this study, the full sample data is accurate to within ±2.5 percentage points using a 95% confidence level. A full methodology is available.

The 2024 Stress in America™ survey was conducted online within the United States by The Harris Poll on behalf of APA between Aug. 1–23, 2024, among 3,305 adults ages 18+ who reside in the U.S. that serves as a nationally representative sample. In addition to the national sample, oversamples were collected to allow for subgroup analysis within race/ethnicity groups. Sample sizes across the national and oversamples are as follows: 801 Black adults, 855 Hispanic adults and 804 Asian adults. Interviews were conducted in English and Spanish. A full methodology can be found here.

The American Psychological Association, in Washington, D.C., is the largest scientific and professional organization representing psychology in the United States. APA’s membership includes over 157,000 researchers, educators, clinicians, consultants and students. Through its divisions in 54 subfields of psychology and affiliations with 60 state, territorial and Canadian provincial associations, APA works to advance the creation, communication and application of psychological knowledge to benefit society and improve lives.

 

Family income predicts adult problems more than neighborhood poverty

Oxford University Press USA

A new paper in the Journal of Public Health, published by Oxford University Press, finds that household income in early childhood is a stronger and more consistent predictor for several major health-related problems for 17-year-olds than growing up in a poor neighborhood. The neighborhood was a slightly stronger predictor for obesity only.

The Index of Multiple Deprivation, which assesses neighborhoods in the United Kingdom according to factors including unemployment, low levels of education, crime, and barriers to housing and services, has been used widely as a measure of deficiency over the past two decades to guide UK policymakers on health disparities.

The success of the index is due, in part, to its ready availability and linkage to administrative health and other datasets in the country. Household income, however, is the primary indicator of socioeconomic status and is strongly associated with health. Yet household income is challenging for researchers to measure and link to routine health data.

Public health research and prevention policies often use the Index of Multiple Deprivation to try to represent individual socio-economic status. However, the index is a blunt instrument for guiding policies to reduce health inequalities. That’s because some 62% of the poorest households in the United Kingdom live outside the most deprived 20% of neighborhoods. The index also fails to capture the fact that household income is highly responsive to policy changes directly affecting income, such as on wages, benefits, and household costs.

Researchers here used data from the Millennium Cohort Study, a nationally representative retrospective cohort study following people born in the United Kingdom between 2000 and 2002. The first survey in 2001–02 included 18,819 children, followed in subsequent surveys until they reached age 18.

The researchers found that overall, 36.8% of the adolescents surveyed at age 17 achieved poor academic outcomes, 15.3% experienced psychological distress, 7.9% reported poor health, 10.3% were regular smokers, and 18.7% were obese.

The prevalence of all adverse outcomes was characterized by apparent inequality gradients in household income—moving from the richest to the poorest group, the prevalence

of adverse outcomes increased. Poor academic achievement, followed by smoking, exhibited the steepest income inequality gradients consistently across all neighborhood groups. Poor health also showed consistent inequality gradients in income.

But adverse outcomes exhibited moderate to no inequality gradient in neighbourhood groups within each quintile of household income. For example, the prevalence of poor academic achievement showed a moderate inequality gradient across the three middle-income quintiles, indicating that both income and neighbourhood deprivation contribute to poor academic achievement. However, children in the poorest income quintile demonstrated similarly poor attainment regardless of whether they resided in the least or most deprived neighborhoods. Those in the highest income quintile experienced the lowest rates of poor attainment in all neighborhood groups, with minimal variation within the high-income quintile according to neighborhood deprivation levels.

“The Index of Multiple Deprivation is widely used over the last two decades to guide UK policymakers on health disparities,” said Premila Webster, editor-in-chief of the Journal of Public Health. “However, authors of this article have shown that this is a relatively blunt instrument. Family income is a stronger and more consistent predictor for several major health-related problems for 17-year-olds.”

The paper, “Does household income predict health and educational outcomes in childhood better than neighbourhood deprivation?” is available (at midnight on December 10th) at https://doi.org/10.1093/pubmed/fdae283.

Direct correspondence to:
Ieva Skarda
Research Fellow, Center for Health Economics
University of York
YO10 5DD UNITED KINGDOM
ieva.skarda@york.ac.uk

To request a copy of the study, please contact:
Daniel Luzer 
daniel.luzer@oup.com

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Journal

Journal of Public Health

DOI

10.1093/pubmed/fdae283 

Method of Research

Data/statistical analysis

Subject of Research

People

Article Title

Does household income predict health and educational outcomes in childhood better than neighbourhood deprivation?

Article Publication Date

10-Dec-2024

COI Statement

Authors Richard Cookson and Ieva Skarda received support from the UK Prevention Research Partnership. Author Ruth Gilbert receives support from Health Data Research UK.

 

Pusan National University scientists designed a new model to predict metal wear for safer, lighter cars and planes

This hybrid model uses machine learning and physics to improve fatigue life prediction for lightweight magnesium alloys

Pusan National University

 

image: 

The new hybrid model uses machine learning combined with physical principles to accurately predict the fatigue life of magnesium alloys under varying stress conditions, eliminating the need for manual parameter adjustments and improving predictive accuracy.

view more 

Credit: Taekyung Lee from Pusan National University, South Korea

Magnesium alloys are increasingly popular in vehicle and aircraft design due to their strength, light weight, and ease of machining. Reducing weight is crucial because lighter vehicles need less power to move, saving energy and reducing emissions. However, since magnesium alloys behave differently under stress, predicting their ‘fatigue life’ has been challenging. Over time, parts made from these alloys can develop tiny cracks from the repeated stress during their use.

Until now, predicting exactly how and when these cracks will form has been difficult, as traditional methods involve empirical models that demand frequent adjustments for different loading conditions.  This limitation makes them difficult to implement for industrial applications, where changing loads and directions are common.

A team of researchers led by Professor Taekyung Lee from Pusan National University, South Korea along with Mr. Jinyeong Yu, a Ph. D candidate set out to tackle this challenge. In their study published in Journal of Magnesium Alloys, the group integrated machine learning with energy-based physical modeling to improve prediction accuracy. The model works by using a combination of a neural network that analyzes complex patterns in stress and strain cycles, along with an energy-based physical model that provides a more holistic understanding of material behavior under cyclic loading.

The model was built using a large dataset of hysteresis loops—the stress-strain behaviors observed during repeated loading and unloading of the material—collected from low-cycle fatigue tests of the AZ31 magnesium alloy. “The neural network learns from these stress cycles which reveal how the metal stretches, bends, and returns to shape under load. We then use a physics-based model to ground the neural network in the physical laws of material science and to forecast when cracks may form,” explains Prof. Lee.

Instead of predicting fatigue life directly, the neural network estimates the hysteresis loops for the material under different conditions. By reconstructing these loops, it can more accurately assess how the material's energy is dissipated during each cycle of loading and unloading, which is directly related to how quickly fatigue will accumulate. Then the physics-based model converts these stress cycle predictions into a reliable estimate of the number of cycles to failure, or the fatigue life of the alloy. “Because the machine learning component can continually adapt as it learns from the loop data, this method is more flexible across multiple loading directions and conditions, removing the need for manual parameter adjustments,” adds Prof. Lee.

With the advent of this new approach, manufacturers may soon benefit from greater predictive reliability when working with magnesium alloys, enabling safer, lighter, and more cost-effective designs in high-stakes environments. The model offers a more streamlined and accurate approach to the fatigue life prediction of magnesium alloys that could lead to enhanced safety and longevity of critical components in real-world applications.

 

***

Reference                                    

Title of original paper: Alternative predictive approach for low-cycle fatigue life based on machine learning and energy-based modeling

Journal: Journal of Magnesium Alloys

DOI: https://doi.org/10.1016/j.jma.2024.10.014

                                 

About the institute Pusan National University, Korea

Pusan National University, located in Busan, South Korea, was founded in 1946 and is now the No. 1 national university of South Korea in research and educational competency. The multi-campus university also has other smaller campuses in Yangsan, Miryang, and Ami. The university prides itself on the principles of truth, freedom, and service, and has approximately 30,000 students, 1200 professors, and 750 faculty members. The university is composed of 14 colleges (schools) and one independent division, with 103 departments in all.

Website: https://www.pusan.ac.kr/eng/Main.do

 

About Professor Taekyung Lee

Dr. Taekyung Lee is an Associate Professor at the School of Mechanical Engineering at Pusan National University, Korea. His group, Metal Design & Manufacturing (MEDEM) Lab, studies advanced metal-forming processes, such as the electropulsing treatment, additive manufacturing, and severe plastic deformation process. MEDEM is also interested in the optimization of processing parameters based on physics, machine learning, and microstructure-mechanical analysis. Prof. Lee earned his Ph.D. at POSTECH, Korea in 2014 and completed the postdoctoral training at Northwestern University, USA. Before coming to Pusan National University, he worked at Kumamoto University, Japan, for two years as an assistant professor.

Lab Website: https://sites.google.com/site/medemlab/

ORCID id: 0000-0002-1589-3900

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Journal

Journal of Magnesium and Alloys

DOI

10.1016/j.jma.2024.10.014 

Method of Research

Computational simulation/modeling

Subject of Research

Not applicable

Article Title

Alternative predictive approach for low-cycle fatigue life based on machine learning and energy-based modeling

The inequity of wildfire rescue resources in California

A new study finds that the most vulnerable communities are lacking state resources to reduce damages – and save lives – in a wildfire

Society for Risk Analysis

AUSTIN, TX, December 10, 2024 – Wildfires in California are intensifying due to warmer temperatures and dry vegetation – putting more residents at risk of experiencing costly damages or losing their homes. Marginalized populations (lower income, elderly, and the disabled) often suffer the most and, according to a new study, may receive less economic and emergency assistance compared to wealthy residents. 

A detailed analysis of more than 500 California wildfire incidents from 2015 to 2022 by University at Buffalo scientists shows that disaster recovery resources in California favor people living in wealthy communities over disadvantaged residents who lack the resources to plan for and recover from a wildfire. “We discovered that racial and economic inequity plays a pivotal role in resource allocation for wildfire recovery and mitigation,” says lead author Poulomee Roy, Ph.D. candidate in Industrial and Systems Engineering. She will present the results in December at the annual meeting of the Society for Risk Analysis in Austin, Texas. 

To examine the underlying relationships between resource allocation and socio-demographic factors, the researchers conducted an in-depth analysis of data (at the county level) related to 504 California wildfire incidents leveraging cutting-edge AI-driven approaches. Factors included in the analysis were: 

• wildfire impact (the spread, burnt area, structural damage, fatalities, etc.), 

• sociodemographic factors (population, race, ethnicity, poverty, educational level, populations of elderly and disabled, sex ratio, crowded households, etc.), and 

• resource allocation data (estimated cost incurred for the wildfire mitigation, personnel deployed in the rescue operation, and whether any equipment like aircraft, gulf strikes, water tenders, dozers, etc., are deployed or not).  

“Our study highlighted a pronounced trend in which counties with higher percentages of lower-income and black populations receive less personnel and funding, compared to those counties with higher proportions of high-income and white people,” says principal investigator Dr. Sayanti Mukherjee, Assistant Professor of Industrial and Systems Engineering. 

When measuring “personnel for rescue operations,” the analysis showed that racial distribution within a county plays an instrumental role in resource allocation. For example, counties with a higher number of Hispanic or Latino residents had fewer wildfire rescue personnel available to them despite facing a higher risk of wildfire. The results also showed a declining trend of recovery efforts and resources allocated in counties with higher Black or African American populations. 

By contrast, counties with a greater concentration of wealthier, single-parent households (such as Los Angeles County), received adequate personnel to mitigate a wildfire. (Wildfire mitigation is defined by FEMA as “any actions undertaken to decrease the risk of damage or loss of life from wildfires.”)  

Elderly and disabled populations likely need more assistance during an evacuation and rescue operation, yet the study revealed that the number of rescue personnel lowered as the population of elderly and disabled in a county increased. The same trend was seen when the number of “crowded households” rose -- despite the likelihood of more injuries and fatalities in crowded households during a fire.   

The results were similar when resources were measured as “cost for recovery” from a wildfire. The economically disadvantaged populations did not receive adequate resources to recover from a wildfire, compared to wealthier neighborhoods with a higher proportion of single-family households.  

“Our findings underscore the significant role of ethnicity, economic status, and proportion of the elderly population in determining wildfire resource allocation for these counties,” says Mukherjee. “The results of this study can equip policymakers to adopt an informed decision about the distribution and allocation of resources.” 

The authors argue that their findings demand action from policymakers to ensure equitable recovery efforts and support for marginalized communities.  

# 

Poulomee Roy is presenting this research Tuesday, December 10, from 3:30 pm, at the JW Marriot Austin, Texas. 

Assessing inequities and disparities in the post-wildfire recovery of socially vulnerable WUI (Wildfire Urban Interface) communities – Tuesday, December 10, 3:30 p.m. 

Part of a symposium on “Confronting the Wildfire Crisis Leveraging Risk-informed Wildfire Preparedness and Recovery Strategies” 

About SRA   

The Society for Risk Analysis is a multidisciplinary, interdisciplinary, scholarly, international society that provides an open forum for all those interested in risk analysis. SRA was established in 1980. Since 1982, it has continuously published Risk Analysis: An International Journal, the leading scholarly journal in the field. For more information, visit www.sra.org.   

 

Aerosol pollutants from cooking may last longer in the atmosphere – new study

University of Birmingham

New insights into the behaviour of aerosols from cooking emissions and sea spray reveal that particles may take up more water than previously thought, potentially changing how long the particles remain in the atmosphere. 

Research led by the University of Birmingham found pollutants that form nanostructures could absorb substantially more water than simple models have previously suggested. Taking on water means the droplets become heavier and will eventually be removed from the atmosphere when they fall as rain. 

The team, also involving researchers from the University of Bath, used facilities at Diamond Light Source, to study the water uptake of oleic acid, a molecule commonly found in emissions from cooking and in spray from the ocean’s surface.  They used a technique called Small-Angle X-ray Scattering (SAXS) to chart the relationship between the structure inside the particle and both its ability to absorb water and its reactivity.  

Working at Diamond’s I22 beamline with the I22 team and experts from the Central Laser Facility operated by the Science and Technology Facilities Council at the Rutherford Appleton Laboratory, the team also studied changes in the structures of polluting particles, caused by changes in humidity. They showed that as molecules react with ozone in the atmosphere and break down, they can also reform into different 3-D structures with varying abilities to absorb water and to react with other chemicals. 

The findings, published in Atmospheric Chemistry and Physics, suggest these combined effects work to keep oleic acid particles circulating in the atmosphere for longer. 

“As we develop our understanding of how these particles behave in the atmosphere, we will be able to design more sophisticated strategies for the control of air pollution,” said lead researcher  

Professor Christian Pfrang. “For example, protecting harmful emissions from degrading in the atmosphere could allow them to travel and disperse further through the atmosphere, thus substantially increasing the pollutant’s reach.”  

He added: “Our results show that aerosols exist in a really dynamic state, with complex structures being formed as well as being destroyed. Each of these states allows polluting molecules to linger in the atmosphere for longer. To reduce exposure to pollutants from cooking, people should consider making more use of extractor fans and ensuring that kitchens are well ventilated to allow aerosol particles to escape rapidly.” 

ENDS 

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Journal

Atmospheric Chemistry and Physics

DOI

10.1155/2024/6355613 

Method of Research

Experimental study

Subject of Research

Not applicable

Article Title

Experimental observation of the impact of nanostructure on hygroscopicity and reactivity of fatty acid atmospheric aerosol proxies

Article Publication Date

10-Dec-2024

Air pollution linked to rising depression rates, study finds

Eurasia Academic Publishing Group

A groundbreaking study published in Environmental Science and Ecotechnology has revealed a strong connection between long-term air pollution exposure and an increased risk of depression. The research, led by Harbin Medical University and Cranfield University, analyzed data from over 12,000 participants in the China Health and Retirement Longitudinal Study (CHARLS).

 

The study identifies sulfur dioxide (SO₂) as the most significant contributor to depression risk, with fine particulate matter (PM2.5) and carbon monoxide (CO) also linked to depressive symptoms. These pollutants were found to have a compounded impact when combined, highlighting the dangers of multi-pollutant exposure.

 

The research also explored potential mechanisms, finding that cognitive and physical impairments partially mediate the link between pollution and depression. The findings emphasize the mental health risks posed by environmental pollutants and call for urgent action to reduce their levels.

 

“Our findings underscore the critical need for integrated air quality management to improve both physical and mental health,” the authors noted. Targeting SO₂ and other key pollutants could significantly alleviate the public health burden of depression, particularly among vulnerable populations like middle-aged and older adults.

 

With millions exposed to unsafe air quality levels worldwide, this study highlights the intersection of environmental and mental health challenges, calling for stricter pollution controls and targeted interventions.

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Journal

Environmental Science and Ecotechnology

DOI

10.1016/j.ese.2024.100515 

Method of Research

Observational study

Subject of Research

People

Article Title

Synergistic air pollution exposure elevates depression risk: A cohort study

Woodburning creates major PM2.5 air pollution issue in UK West Midlands 

University of Birmingham

Woodburning has a major impact on air quality in Birmingham and the wider West Midlands region of the UK – accounting for a substantial proportion of all fine pollution particles and representing a significant risk to public health, a new study reveals. 

University of Birmingham researchers found that biomass burning, primarily from woodburning activities, such as heating homes using woodburning stoves or logs on open fires, contributes significantly to fine particulate matter (PM2.5) levels in the region – accounting for some 25% of the total PM2.5 mass. 

Publishing their findings today (10 Dec) in Atmospheric Environment, the researchers call for targeted measures to mitigate health risks associated with PM2.5 emissions from woodburning activities. 

The experts found woodburning-related PM2.5 concentrations seven times higher than those observed in 2008-2010. They also discovered that the impact of woodburning is particularly pronounced during winter months, contributing up to around half of PM2.5 concentrations - a seasonal spike attributed to people heating their homes. 

Exposure to elevated PM2.5 levels poses severe health risks, including respiratory and cardiovascular diseases, low birthweight, and increased mortality rates. The study estimates that reducing woodburning emissions could significantly decrease mortality and life-years lost due to air pollution in the West Midlands.  

Lead author Dr Deepchandra Srivastava commented: "Our study highlights the significant increase in woodburning activity in the past 10 years, making it one of the most important sources of air pollution in the West Midlands.” 

Lead investigator of the study, Professor Zongbo Shi commented: “We need to see immediate and coordinated actions at local and national levels to reduce wood burning, improve air quality - including enhancement and enforcement of smoke control areas to curb emissions from woodburning stoves and open fires. This has great potential to reduce PM2.5-related health risks and decrease mortality in the region.”  

The experts also recommend raising public awareness about the health impacts of woodburning and promoting best practices, such as burning only dry, seasoned wood and maintaining stoves properly, as crucial steps in reducing pollution. 

Researchers are also calling for local regulations to be strengthened to promote the use of cleaner alternatives, such as electric heating or heat pumps. They say that, to further improve air quality in the West Midlands, wider national and international policy interventions are also needed to address regional and transboundary PM2.5-related exposure. 

Larissa Lockwood, Director of Clean Air at Global Action Plan said: “Lighting fires in our homes is now the largest source of toxic fine particle air pollution in the UK, presenting a range of serious health risks including heart and lung disease, diabetes, and dementia.  

“Despite growing evidence of the UK’s burning problem - like this new research from the University of Birmingham - many people are still unaware that wood burning is harming our health and the planet.  

“While many work to communicate these harms through moments such as Clean Air Night, we need urgent action from central government to share these harms with people across the UK and empower local authorities to tackle this growing source of air pollution in ways that are appropriate for their local communities. Join people across the country in learning the facts about wood burning this Clean Air Night (22 January 2025).” 

This research was conducted as part of the Natural Environment Research Council (NERC)-funded West Midlands Air Quality Improvement Programme (WM-Air), led by Professor William Bloss. Researchers analysed PM2.5 samples collected in 2021 and 2022 at two urban background sites in Birmingham, utilizing advanced receptor modelling techniques to identify and quantify pollution sources. 

PM2.5 refers to tiny airborne particles or droplets that are 2.5 microns or less in diameter and represents a serious health concern because it can be inhaled into our lungs and cause a range of health issues. It can come from a variety of sources, including woodburning, vehicle and industrial emissions, power plants, cooking, cigarettes and smoking. 

ENDS 

For more information, please contact Tony Moran, International Communications Manager, tel: +44 (0)7827 832312: email: t.moran@bham.ac.uk   

Notes to editor: 

• The University of Birmingham is ranked amongst the world’s top 100 institutions. Its work brings people from across the world to Birmingham, including researchers, teachers and more than 8,000 international students from over 150 countries. 

• ‘Comparative Receptor Modelling for the Sources of Fine Particulate Matter (PM2.5) at Urban Sites in the UK’ - Deepchandra Srivastava, Supattarachai Saksakulkrai, W. Joe F. Acton, Daniel J. Rooney, James Hall, Siqi Hou, Mark Wolstencroft, Suzanne Bartington, Roy M. Harrison, Zongbo Shi, and William J. Bloss is published in Atmospheric Environment. 

• WM-Air – the West Midlands Air Quality Improvement Programme - is an initiative to support the improvement of air quality, and associated health, environmental and economic benefits, in the West Midlands. Project partners include the West Midlands Combined Authority, Transport for West Midlands, local authorities across the region including Birmingham and Coventry City Councils, HS2, and the Birmingham & Solihull NHS Sustainability & Transformation Partnership, plus a number of private sector organisations and local businesses. 

• Air pollution in the West Midlands affects some 2.8 million people, reducing average life expectancy by up to 6 months, and is responsible for direct and indirect economic costs of several hundred million pounds per year. Air quality is therefore a key priority for local and regional government, and for the health and wellbeing of the region’s population.  

 

 

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Journal

Atmospheric Environment

Method of Research

Experimental study

Subject of Research

People

Article Title

Comparative Receptor Modelling for the Sources of Fine Particulate Matter (PM2.5) at Urban Sites in the UK

Article Publication Date

10-Dec-2024