Sedimentary records of contaminant inputs in Frobisher Bay, Nunavut

Peer-Reviewed Publication

EURASIA ACADEMIC PUBLISHING GROUP

Although contaminant levels in Arctic environments are often lower than those in temperate locations close to cities and industrial areas, contaminant studies in the Arctic remain important due to the potential for bioaccumulation and biomagnification through food webs to top consumers and humans. Regions important for traditional food harvesting are a priority for monitoring.

 

Contaminants primarily reach the Arctic through long-range atmospheric and oceanic transport, but local sources within the Arctic, including legacy sources and new sources associated with commercial and industrial development, also contribute to the levels observed in the environment.

 

A major population centre in the Canadian Arctic that has seen increased human activity during recent decades is the City of Iqaluit, the capital of the Canadian territory of Nunavut. Iqaluit is located at the head of Frobisher Bay, an area where Inuit continue to harvest country food.

 

Research led by Meaghan C. Bartley of the Centre for Earth Observation Science (CEOS) at the University of Manitoba, and published in Environmental Science and Ecotechnology, found evidence of impacts from both local source and long-range transport in the marine sediment of Frobisher Bay,  Nunavut, via seven dated sediment cores collected from sites near Koojesse Inlet (close to Iqaluit), and inner and outer Frobisher Bay. Contaminants detected included total mercury (THg), major and trace elements, polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and per and polyfluoralkyl substances (PFASs). These findings show that pollution effects leave a long legacy in the environment and include both local and long-range effects.

 

Sediments collected 1.8 km away from Iqaluit, in the Koojesse Inlet, received inputs of THg, PAHs, PCBs, and PFASs primarily originating from activities in and around Iqaluit. Records of THg in sediment suggest that although concentrations were not different from other areas of the Arctic, inputs were connected to local civilian and military activities (e.g., thermometers, fluorescent light bulbs, electrical switches), and were potentially moved from the terrestrial to coastal environment by local activities such as construction.

 

A peak in PCB concentrations was concurrent with military site presence from the 1950-60s, and congener composition in the sediment resembled that of the industrial PCB mixture Aroclor 1260. PCB contamination associated with the historic civilian and military activity in Iqaluit continues to represent a source of PCBs to coastal sediments, albeit reduced from a factor of at least 4X from its peak in the ∼1960s.

 

PAH concentrations increased in recent sediments and exhibited a pyrogenic signature, likely reflecting increased fossil fuel burning for transportation (ships and airplanes), heating and electricity associated with the rapid population growth of Iqaluit in recent decades, northern development, and waste burning.

 

The dominant PFASs observed close to Iqaluit were associated with airport and military activities. This core exhibited a peak in PFOS and PFDS, which may be explained by legacy aqueous film-forming foam (AFFF) usage. Fluorotelomer carboxylic acids (FTCAs) increased closer to the surface, which could be from the phase out of PFOS formulations of AFFF towards fluorotelomer chemistry.

 

This study provides evidence for the importance of both long-range contaminant sources and local inputs in Arctic environments. These results highlight that even after the clean-up of legacy military sites, there remains an impact on the environment for many decades. As human activities escalate in the Arctic, comprehensive investigations into contaminant levels and prospective ecological ramifications hold paramount importance for evaluating risks within regions of significance for traditional food harvesting.

 

Journal

Environmental Science and Ecotechnology

 

DOI

https://doi.org/10.1016/j.ese.2023.100313

 

Article Title

Sedimentary records of contaminant inputs in Frobisher Bay, Nunavut

 

Article Publication Date

10 October 2023

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JOURNAL

Environmental Science and Ecotechnology

DOI

10.1016/j.ese.2023.100313 

METHOD OF RESEARCH

Observational study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Sedimentary records of contaminant inputs in Frobisher Bay, Nunavut

 

Smarter eco-cities, AI and AIoT, and environmental sustainability

Peer-Reviewed Publication

EURASIA ACADEMIC PUBLISHING GROUP

Smarter eco-cities, characterized by their advanced technological landscape, are at the forefront of ushering in a new era of environmental sustainability. These intelligent urban environments leverage cutting-edge Artificial Intelligence of Things (AIoT) solutions to address and mitigate environmental challenges. The integration of AIoT technologies enables these cities to harness real-time data, optimize resource utilization, and implement innovative approaches for ecological conservation and resilience. In doing so, they contribute significantly to the creation of more sustainable and resilient urban ecosystems, fostering a harmonious balance between technological advancement and environmental well-being. As we explore the realm of smarter eco-cities, several questions emerge:

What foundational elements define the emergence of smarter eco-cities, and how do they intertwine?

What factors serve as the key enablers and drivers propelling the evolution of smarter eco-cities?

What constitute the primary AI and AIoT solutions that can be leveraged in shaping the development of smarter eco-cities? What challenges and barriers arise in implementing AI and AIoT solutions for the development of smarter eco-cities?

 

In a recent systematic review published in Environmental Science and Ecotechnology, invaluable insights and novel perspectives are presented. These findings serve as a crucial resource for policymakers, practitioners, and researchers, providing them with the necessary knowledge to advance the integration of eco-urbanism and AI- and AIoT-driven urbanism.

 

Since the mid-2010s, the gradual influence of data-driven technologies and solutions in smart cities has been reshaping the dynamics of eco-cities. This transformation aligns with a smarter approach to environmental sustainability, characterized by the integration of core eco-city domains with those of smart cities.

 

This trajectory is expected to persist as the technologies and solutions of smart cities, including AI, IoT, and Big Data, advance and seamlessly integrate with sustainable technologies and strategies. This integration enables the development of innovative approaches, showcasing the capability to address increasingly complex challenges. Consequently, the continual advancement in AI and AIoT applications contributes to the ongoing evolution of smart eco-cities, making them even more intelligent in their commitment to achieving environmental sustainability.

 

In response to the pressing need for effective solutions, these technologies are poised to offer novel applications that not only overcome current challenges but also pave the way for sustained improvements. Moreover, a positive feedback loop is anticipated, wherein the more these solutions are implemented, the higher the likelihood of their further adoption. This can be attributed to the amplifying effects of network dynamics, continuous learning, adaptive capabilities, and enhanced coordination, creating a reinforcing cycle of positive impact on environmental sustainability efforts.

 

Nevertheless, the high energy demands associated with AI and AIoT applications, especially when relying on non-renewable energy sources, pose a challenge to the attainment of environmental objectives in smarter eco-cities. On a direct level, the construction of smarter eco-cities involves the implementation of urban operating systems, urban operations centers, and urban dashboards, necessitating substantial amounts of natural resources for the development, installation, and maintenance of AI and AIoT ecosystems. Additionally, the life cycle of IoT and AI, encompassing production, distribution, service, and disposal, generates considerable amounts of e-waste, unsustainable materials, and toxic pollution. Ensuring the sustainable growth of AI, IoT, Big Data technologies, green computing, and eco-friendly design is imperative to address the potential disparities between the environmental aspirations of smarter eco-cities and the opportunities presented by AI and AIoT technologies.

 

AI and AIoT solutions should be carefully implemented in conjunction with sustainable and eco-friendly design principles, energy-efficient policy instruments, and other relevant measures. This collaborative effort is aimed at ensuring that the efficiency gains facilitated by AI and AIoT solutions contribute to the reduction of energy use and carbon footprint.

 

Technical and ethical challenges, encompassing black-box models, bias and fairness, data privacy and security, transparency and accountability, and information asymmetries, must be systematically addressed. It is crucial for smart cities to prioritize initiatives that not only enhance socio-economic equality and foster social inclusion but also adhere to principles of openness and clarity.

 

This study identifies and evaluates critical challenges associated with environmental costs, privacy concerns regarding data collection and usage, cybersecurity risks in interconnected systems, public trust, and social acceptance. Additionally, it highlights challenges such as limited technical expertise and knowledge, the absence of robust regulatory frameworks to ensure responsible deployment of AI and AIoT, and the imperative to ensure the equitable use of AI and AIoT technologies.

 

The comprehensive insights synthesized in this study hold substantial implications for researchers, practitioners, and policymakers actively involved in the design, management, and planning of smarter eco-cities.

 

Journal

Environmental Science and Ecotechnology

 

DOI

https://doi.org/10.1016/j.ese.2023.100330

 

Article Title

Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review

 

Article Publication Date

3 November 2023

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JOURNAL

Environmental Science and Ecotechnology

DOI

10.1016/j.ese.2023.100330 

METHOD OF RESEARCH

Systematic review

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review

 

Brexit-induced spatial restrictions reveal alarming increase of fishing fleet’s carbon footprint

Spatial restrictions after Brexit lead to doubling in carbon footprint of Norwegian mackerel fishing flee

Peer-Reviewed Publication

THE UNIVERSITY OF BERGEN

 

VIDEO: 

HOW COULD BREXIT LEAD TO A DOUBLING OF THE CARBON FOOTPRINT OF NORWAY’S MACKEREL FISHERY? THIS VIDEO EXPLAINS THE FINDINGS OF A NEW STUDY ON FISHERY EMISSIONS AND AREA RESTRICTIONS, PERFORMED BY RESEARCHERS AT THE UNIVERSITY OF BERGEN, RISE (RESEARCH INSTITUTES OF SWEDEN) AND FISKEBÅT.

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CREDIT: ESPEN VIKE (STUDIO VIKE) AND CCO MUSIC: «FINAL THOUGHTS» BY APEX MUSIC (UPPBEAT.IO)

In a study published today in Marine Policy, researchers have unveiled striking evidence that fisheries management decisions such as spatial fisheries restrictions can increase greenhouse gas emissions. The study, conducted by a team of scientists led by postdoctoral researcher Kim Scherrer at the University of Bergen, sheds light on the unforeseen consequences of policy changes on fishing fleets and their carbon footprint.

In the North Atlantic, international agreements often allow fleets to follow the fish across national borders. This allows fishers to catch the fish where it is most efficient. But when the UK left the EU (Brexit), Norway’s mackerel fishing fleet was suddenly excluded from fishing grounds in the UK. Using Brexit as a natural experiment, the researchers used open fisheries data to unravel the consequences for the Norwegian mackerel fishery. The findings reveal an alarming shift in the fishery's performance and carbon emissions due to the changes in fishing practices.

As the Norwegian fleet was excluded from UK fishing grounds, the vessels were forced to areas where fishing was less efficient. The catch per fishing trip nearly halved, prompting a doubling in the number of trips per vessel. Consequently, the fuel used per kilo of mackerel more than doubled.

Because of this change, an extra 23 million liters of fuel were needed each year, costing about €18 million more. This also released an extra 72,000 tonnes of CO2 into the air annually. The area restriction thus undid about 15 years of progress in fuel efficiency in Norway's pelagic fisheries.

”This small change in fisheries’ regulations unintentionally caused as much annual CO2 emissions as half a million within-EU return flights,” said Scherrer, emphasizing the necessity of considering emissions in fisheries management. “It is important that governments that have signed the Paris agreement avoid squandering emissions like this”.

The study underscores that policymakers and managers need to consider fuel efficiency trade-offs in marine spatial management, ensuring a balance between conservation efforts, other offshore industries, and reduced carbon footprints.

Spatial restrictions inadvertently doubled the carbon footprint of Norway’s mackerel fishing fleet 

 

As the Norwegian fleet was excluded from UK fishing grounds, the vessels were forced to areas where fishing was less efficient. The catch per fishing trip nearly halved, prompting a doubling in the number of trips per vessel. Consequently, the fuel used per kilo of mackerel caught more than doubled.

CREDIT

Roar Bjånesøy/Norges Sildesalgslag

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JOURNAL

Marine Policy

DOI

10.1016/j.marpol.2024.106014 

METHOD OF RESEARCH

Case study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Spatial restrictions inadvertently doubled the carbon footprint of Norway’s mackerel fishing fleet

ARTICLE PUBLICATION DATE

30-Jan-2024

COI STATEMENT

Gjert Dingsør is employed at Fiskebåt, an interest group and employers’ organization for the Norwegian ocean-going fishing fleet. GD has helped align the methods and quantification with the practicalities of the mackerel fishery (including temporal development), pointed to openly available data sources, has commented on but not written the manuscript, and has not influenced results or conclusions. The other authors declare no competing interests.

 

Paper: Multistate foodborne illness outbreaks impact restaurant stock price, public perception

The financial impact of foodborne illness outbreaks at restaurants: Chipotle Mexican Grill

Peer-Reviewed Publication

UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN, NEWS BUREAU

 

IMAGE: 

FOODBORNE ILLNESS OUTBREAKS SPANNING MULTIPLE STATES BRING SWIFT FINANCIAL LOSSES, INCREASED MEDIA ATTENTION AND A PUBLIC-RELATIONS HIT THAT MAKES SUBSEQUENT SMALLER OUTBREAKS MORE FINANCIALLY DAMAGING, SAYS MARIA KALAITZANDONAKES, A PROFESSOR OF AGRICULTURAL AND CONSUMER ECONOMICS AT ILLINOIS.

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CREDIT: PHOTO BY FRED ZWICKY

CHAMPAIGN, Ill. — As demand for food from restaurants soars in the U.S., so does the importance in understanding the impacts of foodborne illness outbreaks. A new paper co-written by a University of Illinois Urbana-Champaign expert in food marketing and food policy finds that outbreaks spanning multiple states bring swift financial losses, increased media attention and a public-relations hit that makes smaller outbreaks more financially damaging. 

In the U.S., more than 60% of foodborne illness outbreaks occur at restaurants, and the vast majority of those outbreaks are confined to a single state. As these smaller food safety events are announced by local health agencies and media, their impact has been generally not well understood.

When restaurants experience multistate outbreaks – as did the fast-casual chain Chipotle Mexican Grill in 2015 – that can lead to a stock market penalty, substantial negative news media coverage and a discernible change for the worse in how investors and the public view the company’s smaller outbreaks, says Maria Kalaitzandonakes, a professor of agricultural and consumer economics at Illinois and lead author of the study.

“Foodborne illness outbreaks are somewhat common in the U.S. If you operate a restaurant, it’s difficult to get that risk down to zero. When a restaurant has a single-state outbreak, the public may not even hear about it,” she said. “But if you have what happened at Chipotle – where your brand becomes associated with foodborne illness after a multistate outbreak – that’s when you start to see responses to these single-state outbreaks. Investors start to get rattled, the media pays attention and we see clear impacts from those types of outbreaks.”

The paper, which was published by the journal Agribusiness, was co-written by Maria Teresa Serra Devesa, the T.A. Hieronymus Distinguished Chair in Futures Markets at Illinois, and Brenna Ellison of Purdue University.

To gauge the effect of foodborne illness outbreaks, the researchers studied eight such occurrences at the ubiquitous fast-casual chain to evaluate the media and stock market responses to both single and multistate outbreaks.

“We chose to study Chipotle because it’s publicly traded and not owned by a parent company, which means we can zero in on the financial impacts of the outbreaks through the change in its stock price,” Kalaitzandonakes said. “We were able to identify the first announcement for each outbreak and get stock price data down to the minute level.”

In their analysis, the researchers found “a fundamental shift” in news media coverage and stock market response to single‐state outbreaks before and after Chipotle’s multistate E. coli outbreaks, according to the paper.

Before Chipotle’s more well-known multistate outbreaks, the company’s single‐state outbreaks earned little public scrutiny and incurred no financial losses for the company – whereas after the multistate food safety events, subsequent single‐state outbreaks resulted in national media coverage and financial losses, Kalaitzandonakes said.

“We’d expect multistate outbreaks to be newsworthy nationally, so the fact that Chipotle’s multistate E. coli outbreaks were highly reported on is intuitive. It is less expected that single-state outbreaks would be of interest to national news,” she said. 

But the results show that media attention for single‐state outbreaks depended on whether they occurred before or after the multistate outbreaks, Kalaitzandonakes said.

“Before, media attention of single-state outbreaks was low, generating only a handful of news stories,” she said. “After, media attention was much higher, generating hundreds of news stories with national audiences.”

Similarly, the researchers found that Chipotle’s multistate outbreaks were associated with declines in stock price returns of more than 5%, resulting in a market capitalization decline of $1.75 million. But the impact of Chipotle’s single‐state outbreaks was more nuanced: Single‐state outbreaks that occurred before the multistate outbreak brought no losses, whereas single‐state outbreaks that occurred after resulted in a 4%-7% reduction in Chipotle’s stock price returns.

“This could be for a variety of reasons – increased media coverage, reduced faith in management, worry about consumers staying away and reducing revenues, and so on,” Kalaitzandonakes said.

The researchers found that the differences in both media coverage and stock market response to single‐state outbreaks before and after Chipotle’s multistate E. coli outbreaks were unrelated to their severity, suggesting that multistate outbreaks changed the calculus for both media and investor perceptions about foodborne illness risk at the chain.

“Before the multistate outbreaks, which generated significant negative national media attention, these single-state outbreaks didn’t really register,” she said. “But single-state outbreaks after the multistate outbreak – investors responded very quickly and negatively, indicating they thought these events were risky.”

The lessons from Chipotle’s case underscore the importance of restaurants investing in outbreak prevention, Kalaitzandonakes said.

“Foodborne illness outbreaks at restaurants are most frequently caused by sick workers or poor food handling practices,” she said. “So preventing foodborne illness through enhanced safety measures is a relatively straightforward fix that’s likely to have a high return on investment for both the company and public health.”

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JOURNAL

Agribusiness

DOI

10.1002/agr.21898 

METHOD OF RESEARCH

Data/statistical analysis

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

The financial impact of foodborne illness outbreaks at restaurants: Chipotle Mexican Grill

 

NRL joins Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ)

Business Announcement

NAVAL RESEARCH LABORATORY

 

IMAGE: 

IMAGE: OVERVIEW OF KEY FEATURES THAT WILL INFLUENCE METEOROLOGY DURING THE JANUARY-MARCH SAMPLING PERIOD OF ASIA-AQ. BLACK CIRCLES ARE THE AIRBORNE SAMPLING SITES FOR ASIA-AQ. THE ORANGE BOX INDICATES THE OBSERVING DOMAIN FOR GEMS. THE BACKGROUND SHADED IMAGE IS THE ANNUAL AVERAGE NO2 FROM TROPOMI. THE LOCATION OF EACH ATMOSPHERIC COMPONENT IN THIS DIAGRAM IS AN EXAMPLE AND VARIES IN REALITY. (U.S. NAVAL RESEARCH LABORATORY)

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CREDIT: U.S. NAVAL RESEARCH LABORATORY

WASHINGTON  –  U.S. Naval Research Laboratory (NRL) meteorologists, in partnership with NASA, will join a team of international scientists to participate in the Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) experiment beginning on February 2.
 
NRL’s collaborators, David Peterson, Ph.D., meteorologist, Theodore McHardy, Ph.D., American Society for Engineering Education postdoctoral researcher, Nicholas Gapp, Science Applications International Corporation and Lauren Porter, STEM Student Employment Program, will lead critical weather forecasting efforts for the duration of the experiment.
 
In partnership with team members at the University of California, Los Angeles (UCLA), NRL will provide daily briefings for the science and flight planning teams summarizing meteorology, air quality and atmospheric composition forecasts. This information will identify opportunities for data collection, including airborne measurements of many local, remote, persistent, and episodic sources of pollution.
 
“ASIA-AQ is an exciting opportunity to investigate how different climates and weather patterns influence periods of hazardous air quality and reduced visibility in several regions of eastern Asia.” said Dr. Peterson. “Beginning in the Philippines, each phase will last for two weeks then move to South Korea, Malaysia and conclude in Thailand.”
 
The primary goal of ASIA-AQ is to improve understanding of air quality in and around several Asian megacities by evaluating the factors controlling variability in daily air quality. The comprehensive study will involve South Korea’s Geostationary Environment Monitoring Spectrometer (GEMS) which measures hourly to provide a new view of air quality conditions from space that both complements and depends upon ground-based monitoring efforts of countries in its field of view. To aid in the validation and interpretation of GEMS observations, a network of ground-based remote sensing instruments (Pandora spectrometers) is being established across the GEMS domain. Pandora spectrometers can provide continuous information on the atmospheric column trace gas amounts of compounds.
 
NASA will contribute two research aircraft to the study, with flights planned over urban and marine environments in five countries in eastern Asia. ASIA-AQ flights will be conducted in full partnership with NRL and local scientists and environmental agencies responsible for air quality monitoring and assessment. These partners will contribute to the design of the flight sampling strategies, participate in the execution of the study, and be involved in the analysis of observations collected.
 
Aircraft observations provide invaluable context to the satellite and ground-based perspectives that are used more routinely to inform air quality models for both forecasting and identification of specific sources of pollution. Satellites and ground monitors focus on only a small subset of relevant atmospheric constituents. For a more complete understanding, detailed atmospheric composition measurements throughout the lower atmosphere are needed to understand how emissions, chemistry and meteorology combine to affect ozone and particulate pollution.
 
 ASIA-AQ will be able to fully harness the combination of multi-perspective observations (satellite, ground, and aircraft) and models to improve understanding of the factors controlling air quality. This calls for an international collaborative effort that includes air quality scientists, government officials, and monitoring agencies working together.
 
“We look forward to working with weather forecasters and air quality scientists in the ASIA-AQ host countries to build collaborations and broaden the impact of our work.” said Peterson.
 
After the deployment, NRL will continue to support the aircraft measurement teams and the atmospheric simulations done by ASIA-AQ scientists by providing information on how ASIA-AQ measurements were influenced by specific weather patterns. NRL will use data collected during ASIA-AQ to evaluate Navy modeling applications in eastern Asia, with the goal of improved forecasts for hazardous visibility conditions that account for potential feedback of airborne pollutants on weather.
 

About the U.S. Naval Research Laboratory

NRL is a scientific and engineering command dedicated to research that drives innovative advances for the U.S. Navy and Marine Corps from the seafloor to space and in the information domain. NRL is located in Washington, D.C. with major field sites in Stennis Space Center, Mississippi; Key West, Florida; Monterey, California, and employs approximately 3,000 civilian scientists, engineers and support personnel.

For more information, contact NRL Corporate Communications at (202) 480-3746 or nrlpao@nrl.navy.mil. 

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METHOD OF RESEARCH

Data/statistical analysis

 

Reaping agricultural emissions solutions

AI-backed model analyzes cropland ammonia emissions, identifies mitigation strategies

Business Announcement

DOE/OAK RIDGE NATIONAL LABORATORY

 

IMAGE: 

ORNL CLIMATE MODELING EXPERTISE CONTRIBUTED TO AN AI-BACKED MODEL THAT ASSESSES GLOBAL EMISSIONS OF AMMONIA FROM CROPLANDS NOW AND IN A WARMER FUTURE, WHILE IDENTIFYING MITIGATION STRATEGIES. THIS MAP HIGHLIGHTS CROPLANDS AROUND THE WORLD.

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CREDIT: CREDIT: U.S. GEOLOGICAL SURVEY

A new computational framework developed in collaboration with Oak Ridge National Laboratory scientist Jiafu Mao provides a detailed assessment of ammonia emissions from global croplands and identifies practices that could curb release of the gas.

Croplands are the largest single source of atmospheric ammonia, emitted from fields treated with nitrogen fertilizer. Ammonia can harm human health, acidify soil and waterways and contribute to biodiversity loss, food insecurity and climate change. However, the international study found that emissions could be cut by 38% without altering total fertilizer inputs, as detailed in Nature.

Mao helped devise a machine learning approach to improve ammonia emission estimates from wheat, corn and rice fields. The model enabled the identification of local best practices that could mitigate emissions, even in a warming climate.

“This valuable model, backed by artificial intelligence tools, can also fine-tune biogeochemical cycling and greenhouse gas emissions in the Department of Energy’s Earth system model,” Mao said. —Stephanie Seay

 

A sleeker facial recognition technology tested on Michelangelo’s David

Peer-Reviewed Publication

AMERICAN CHEMICAL SOCIETY

 

IMAGE: 

A NEW LENS-FREE AND COMPACT SYSTEM FOR FACIAL RECOGNITION SCANS A BUST OF MICHELANGELO’S DAVID AND RECONSTRUCTS THE IMAGE USING LESS POWER THAN EXISTING 3D SURFACE IMAGING SYSTEMS. 

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CREDIT: ADAPTED FROM NANO LETTERS, 2024, DOI: 10.1021/ACS.NANOLETT.3C05002

Many people are familiar with facial recognition systems that unlock smartphones and game systems or allow access to our bank accounts online. But the current technology can require boxy projectors and lenses. Now, researchers report in ACS’ Nano Letters a sleeker 3D surface imaging system with flatter, simplified optics. In proof-of-concept demonstrations, the new system recognized the face of Michelangelo’s David just as well as an existing smartphone system.

3D surface imaging is a common tool used in smartphone facial recognition, as well as in computer vision and autonomous driving. These systems typically consist of a dot projector that contains multiple components: a laser, lenses, a light guide and a diffractive optical element (DOE). The DOE is a special kind of lens that breaks the laser beam into an array of about 32,000 infrared dots. So, when a person looks at a locked screen, the facial recognition system projects an array of dots onto most of their face, and the device’s camera reads the pattern created to confirm the identity. However, dot projector systems are relatively large for small devices such as smartphones. So, Yu-Heng Hong, Hao-Chung Kuo, Yao-Wei Huang and colleagues set out to develop a more compact facial recognition system that would be nearly flat and require less energy to operate.

To do this, the researchers replaced a traditional dot projector with a low-power laser and a flat gallium arsenide surface, significantly reducing the imaging device’s size and power consumption. They etched the top of this thin metallic surface with a nanopillar pattern, which creates a metasurface that scatters light as it passes through the material. In this prototype, the low-powered laser light scatters into 45,700 infrared dots that are projected onto an object or face positioned in front of the light source. Like the dot projector system, the new system incorporates a camera to read the patterns that the infrared dots created.

In tests of the prototype, the system accurately identified a 3D replica of Michelangelo’s David by comparing the infrared dot patterns to online photos of the famous statue. Notably, it accomplished this using five to 10 times less power and on a platform with a surface area about 230 times smaller than a common dot-projector system. The researchers say their prototype demonstrates the usefulness of metasurfaces for effective small-scale low-power imaging solutions for facial recognition, robotics and extended reality.    

The authors acknowledge funding from Hon Hai Precision Industry, the National Science and Technology Council in Taiwan, and the Ministry of Education in Taiwan.

###

The American Chemical Society (ACS) is a nonprofit organization chartered by the U.S. Congress. ACS’ mission is to advance the broader chemistry enterprise and its practitioners for the benefit of Earth and all its people. The Society is a global leader in promoting excellence in science education and providing access to chemistry-related information and research through its multiple research solutions, peer-reviewed journals, scientific conferences, eBooks and weekly news periodical Chemical & Engineering News. ACS journals are among the most cited, most trusted and most read within the scientific literature; however, ACS itself does not conduct chemical research. As a leader in scientific information solutions, its CAS division partners with global innovators to accelerate breakthroughs by curating, connecting and analyzing the world’s scientific knowledge. ACS’ main offices are in Washington, D.C., and Columbus, Ohio.

To automatically receive news releases from the American Chemical Society, contact newsroom@acs.org.

Note: ACS does not conduct research, but publishes and publicizes peer-reviewed scientific studies.

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JOURNAL

Nano Letters

DOI

10.1021/acs.nanolett.3c05002 

ARTICLE TITLE

“Metasurface- and PCSEL-Based Structured Light for Monocular Depth Perception and Facial Recognition”

@ IS SELF ORGANIZATION

Plant groupings in drylands support ecosystem resilience

Peer-Reviewed Publication

SANTA FE INSTITUTE

Many complex systems, from microbial communities to mussel beds to drylands, display striking self-organized clusters. According to theoretical models, these groupings play an important role in how an ecosystem works and its ability to respond to environmental changes. A new paper in PNAS focused on the spatial patterns found in drylands offers important empirical evidence validating the models.

Drylands make up 40 percent of the Earth’s landmass and are places where water is the limiting resource for life. They often display a characteristic clustering of vegetation surrounded by bare soil — patterns that are easy to spot in aerial images. The new study, led by SFI External Professor Sonia Kéfi, who is a researcher at CNRS in France, finds that not only are these spatial patterns caused by the stressful environmental conditions of drylands, but they are also a critical adaptation that allows drylands to function in changing conditions. When a dryland ecosystem tips into a degraded state, the spatial patterns disappear.

“Many people have the idea that ‘interesting’ ecosystems are places like the Amazon, and that drylands are poor in some way,” says SFI External Professor Ricard Solé (Pompeu Fabra University), a co-author on the paper. “But they can be very rich. They are responsible for managing how water is being retained or not in these habitats, and are important for CO2 exchange.” Beyond their ecological importance, drylands are also home to one-third of the world’s human population, making them important economically and culturally.

In healthy dryland ecosystems, islands of vegetation create oases where conditions are a bit better than the rest of the landscape. There’s more water, more nutrients, and more shade. If an ecosystem’s climate becomes drier, those clusters tend to move further apart.

And this, says Kéfi, is a double-edged sword. While improving local conditions, these clusters also create spaces without vegetation — harsh places where a single plant would not survive on its own. If conditions become too harsh, the ecosystem can reach a tipping point into desertification.

Kéfi and her colleagues wondered if aerial images, and their evidence of changes in spatial patterns, could themselves indicate the health or level of degradation in a given plot of land.

“In theory, we could tell something about the ecosystem from the sky — that’s what the models predict, in very broad terms,” says Kéfi. To test this, the team paired aerial images with soil and vegetation data gathered from 115 dryland ecosystems across 13 different countries. “This on-the-ground data shows us where one ecosystem is healthier or functioning better than other ecosystems.” Using the two types of data, the team could test the predictions of the model against real-world observations.

“Our results represent a significant advance in the development of tools for the management and preservation of dryland ecosystems in a warmer, drier world,” says Kéfi. “More specifically, changes in spatial vegetation patterns (or the lack thereof) could be used as indicators of degradation.”

According to Solé, the study offers, for the first time, real validation that the model correctly predicts the nonlinear dynamics of what has been unfolding in dryland ecosystems. “The beauty of this work is that it reveals something that goes beyond the pattern-forming problem. You can talk about ecosystem health in ways that are not metaphoric, and it opens new interesting questions about how to address the future of these ecosystems,” he says.

The authors hope their work will make it easier to spot degrading systems that might be approaching a tipping point. And, because vegetation patterning seems to also be key in other natural systems, such as microbial communities or coastal wetlands, their results could have implications for systems beyond arid zones.

Read the paper "Self-organization as a mechanism of resilience in dryland ecosystems" in PNAS (February 2, 2024) DOI: 10.1073/pnas.2305153121

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JOURNAL

Proceedings of the National Academy of Sciences

DOI

10.1073/pnas.2305153121 

ARTICLE TITLE

Self-organization as a mechanism of resilience in dryland ecosystems

ARTICLE PUBLICATION DATE

2-Feb-2024