Source of large rise in emissions of unregulated ozone destroying substance identified

New research, led by the University of Bristol and Peking University, has discovered that emissions coming from China of the ozone-destroying chemical, dichloromethane, have more than doubled over the last decade.

Since the signing of the Montreal Protocol, there has been a dramatic drop in emissions of the main substances that are responsible for depleting the stratospheric ozone layer, the part of the atmosphere that protects us from harmful solar radiation.

Compared to the CFCs, and other regulated ozone-destroying compounds, dichloromethane only lasts for a short time in the atmosphere – around six months. Mainly for this reason, its production and use hasn’t been controlled under the Montreal Protocol in the same way as longer-lived ozone-depleting substances.

Dr Luke Western from the University of Bristol’s School of Chemistry, said: “International monitoring networks have known that global atmospheric concentrations of dichloromethane have been rising rapidly over the last decade, but until now, it was unclear what was driving the increase.”

To answer that question researchers from Peking University, the China Meteorological Administration and the University of Bristol teamed up to examine new data collected within China. Their results are published today in the journal Nature Communications.

Minde An, a postgraduate student from Peking University, and visiting researcher at the University of Bristol led the study.

He said: “China is an important producer and user of compounds such as dichloromethane. Therefore, we wanted to examine measurements within the country to determine its contribution to global emissions.

A medication against SARS-CoV-2

Prof. Dr. med. Ulrike Protzer (r), head of the Institute for Virology at the Technical University of Munich and Director at the Helmholtz Munich, with an employee at the PCR analyzer in the Institute for Virology at the TUM university hospital Klinikum rechts der Isar.
Image: Astrid Eckert / TUM

Vaccines against the SARS-CoV-2 virus have been made possible by an unprecedented worldwide collaboration. But medications against Covid-19 have as yet seen only partial success. With the support of the Bavarian Research Foundation, a Munich research team has developed a protein which has reliably prevented infection by the virus and its variants in cell culture tests.

The SARS-CoV-2 virus uses a protein called Angiotensin Converting Enzyme 2 (ACE2) on the surface of human cells as an entry gate. This is where the spike protein of the virus finds a hold in order to ultimately infect the cell.

Recombinant antibodies are already being used in therapy for Covid-19 illnesses, including at the TUM University Hospital rechts der Isar; nevertheless the virus has used mutation to evade attacks by therapeutic antibodies and in part also the natural antibodies formed after vaccination.

A team of scientists from the Technical University of Munich (TUM), the Ludwig Maximilians-University of Munich, Helmholtz Munich, and Munich-based Formycon AG are pursuing a different strategy: They have combined the ACE2 protein with part of a human antibody protein and have thus created an active ingredient which blocks the spike protein of the virus. In cell culture tests they were able to completely neutralize the virus and prevent infection.

Neutralizing antibodies for emerging viruses

Researchers at Sandia National Laboratories have created a platform for discovering, designing and engineering novel antibody countermeasures for emerging viruses. This new process of screening for nanobodies that “neutralize” or disable the virus represents a faster, more effective approach to developing nanobody therapies that prevent or treat viral infection.

Traditionally used to treat a variety of conditions, including cancer, autoimmune and inflammatory diseases, nanobodies are smaller components of conventional antibodies — a vital element of the body’s immune system that defends against disease-causing viruses or bacteria.

After screening a large, diverse library of synthetic nanobodies, Sandia researchers identified and evaluated several potent nanobodies that can protect against COVID-19. The scientists now aim to replicate this method to defend against current and future biological threats.

“The coronavirus pandemic has made evident the need for a broad range of preventive and therapeutic strategies to control diseases associated with novel viruses,” said Craig Tewell, director of Sandia’s Chemical, Biological, Radiological, and Nuclear Defense and Energy Technologies Center.

With a rich history of biodefense research, Sandia helps protect the nation and the world from threats presented by bioterrorism and naturally occurring diseases, Tewell said.

Scientists expose tumor-causing protein

The structure of the protein behind NF1 has been discovered.

Monash University scientists have discovered the structure of the protein behind neurofibromatosis type 1 (NF1), a common genetic condition that causes tumors to form on nerve tissue.

A collaboration between Monash Biomedicine Discovery Institute (BDI) and the Monash Institute of Pharmaceutical Sciences (MIPS) used cryogenic electron microscopy (cryo-EM) to take high-resolution pictures revealing the complex shape of the protein. The detailed pictures will help scientists better understand how the protein works, how it is changed by genetic mutation and could lead to new strategies for treatment.

The study was co-led by BDI’s Dr Andrew Ellisdon and Associate Professor Michelle Halls from MIPS and is now published in Nature Structural & Molecular Biology.

NF1 or Von Recklinghausen's disease is an extremely variable condition affecting one in 2500 Australians. Most people with it will never be impacted by major medical complications; for others, the condition can be debilitating and life-threatening. There is no known cure and treatment options are limited. People with NF1 have a higher risk of developing a number of cancers, and the protein itself is mutated in cancers in people who don’t have the condition.

Dr Ellisdon stated: “When we lose function in that protein it basically takes away a ‘stop’ signal for cell growth and we get the formations of tumors in the body.”

The gene for NF1 was discovered in 1990 by a group of US scientists but until now researchers had no idea what the protein looked like.

With Fuzzy Nanoparticles, Researchers Reveal a Way to Design Tougher Ballistic Materials

Researchers at NIST examined the toughness of films composed of silica nanoparticles coated in polymer chains using Laser-Induced Projectile Impact Testing, or LIPIT. With LIPIT, they propelled tiny projectiles toward the films and used a camera and strobe light to capture their position every 100 nanoseconds. The amount that the projectiles slowed down after piercing the films revealed the material's toughness. 
Credit: NIST

Researchers at the National Institute of Standards and Technology (NIST) and Columbia Engineering have discovered a new method to improve the toughness of materials that could lead to stronger versions of body armor, bulletproof glass and other ballistic equipment.

In a study published today in Soft Matter, the team produced films composed of nanometer-scale ceramic particles decorated with polymer strands (resembling fuzzy orbs) and made them targets in miniature impact tests that showed off the material’s enhanced toughness. Further tests unveiled a unique property not shared by typical polymer-based materials that allowed the films to dissipate energy from impacts rapidly.

“Because this material doesn't follow traditional concepts of toughening that you see in classical polymers, it opens up new ways to design materials for impact mitigation,” said NIST materials research engineer Edwin Chan, a co-author of the study.

The polymers that constitute most of the high-impact plastics today consist of linear chains of repeating synthetic molecules that either physically intertwine or form chemical bonds with each other, forming a highly entangled network. The same principle applies to most polymer composites, which are often strengthened or toughened by having some nonpolymer material mixed in. The films in the new study fall into this category but feature a unique design.

Challenging Einstein's Greatest Theory with Extreme Stars

Researchers have conducted a 16-year long experiment to challenge Einstein’s theory of general relativity. The international team looked to the stars - a pair of extreme stars called pulsars to be precise – through seven radio telescopes across the globe.
Credit: Max Planck Institute for Radio Astronomy

Researchers at the University of East Anglia and the University of Manchester have helped conduct a 16-year long experiment to challenge Einstein’s theory of general relativity.

The international team looked to the stars - a pair of extreme stars called pulsars to be precise – through seven radio telescopes across the globe.

And they used them to challenge Einstein’s most famous theory with some of the most rigorous tests yet.

The study, published today in the journal Physical Review X, reveals new relativistic effects that, although expected, have now been observed for the first time.

Dr Robert Ferdman, from UEA’s School of Physics, said: “As spectacularly successful as Einstein’s theory of general relativity has proven to be, we know that is not the final word in gravitational theory.

“More than 100 years later, scientists around the world continue their efforts to find flaws in his theory.

“General relativity is not compatible with the other fundamental forces, described by quantum mechanics. It is therefore important to continue to place the most stringent tests upon general relativity as possible, to discover how and when the theory breaks down.

Technique Speeds Up Thermal Actuation for Soft Robotics

Image Credit: Shuang Wu.

Researchers from North Carolina State University have come up with a new design for thermal actuators, which can be used to create rapid movement in soft robotic devices.

“Using thermal actuation is not new for soft robots, but the biggest challenge for soft thermal actuators was that they were relatively slow – and we’ve made them fast,” says Yong Zhu, corresponding author of the paper and the Andrew A. Adams Distinguished Professor of Mechanical and Aerospace Engineering at NC State.

Actuators are the parts of a device – such as a soft robot – that create motion by converting energy into work.

“What makes this new actuator design work is a structure with a bi-stable design,” says Shuang Wu, first author of the paper and a Ph.D. student at NC State. “Think of a snap hair clip. It’s stable until you apply a certain amount of energy (by bending it over), and then it snaps into a different shape – which is also stable.”

In the case of the new thermal actuator, the material is bi-stable, but which shape the material prefers is dictated by temperature.

Here’s how that works. The researchers layer two materials on top of each other, with silver nanowires in the middle. The two materials have different coefficients of thermal expansion, which means they expand at different rates as they heat up. In practical terms, that means the structure bends when you heat it.

How we measure the effects of methane matters for climate policy

How effective is the promotion of low-meat diets at reducing greenhouse gas emissions compared to carbon pricing when the effectiveness of mitigation policies is measured against methane’s long-term behavior? An international team of researchers explored how focusing either on the short- or long-term warming effects of methane can affect climate mitigation policies and dietary transitions in agriculture.

Unlike the other main greenhouse gases (GHG) and particularly carbon dioxide (CO2), methane (CH4) has a short atmospheric life (around 10 years). Its warming effect is significant in the short term but diminishes in the long term. Depending on the time scale considered, methane’s contribution to agricultural emissions and climate change may vary substantially. This has important implications in the design of global climate change mitigation policies for agriculture.

Based on projections from three agricultural economic models, the study just published in the journal Nature Food shows how different valuations of methane, reflecting either a short- or long-term focus, may affect the cost-effectiveness of mitigation policies and the benefits of low-meat diets.

Conventionally, the climate impact of a certain sector is evaluated through its annual greenhouse gas emissions, typically using the Global Warming Potential over a 100 year period metric ̶ GWP100 ̶ which estimates the change in atmospheric energy balance resulting from a particular type of GHG emission. However, as GHG emissions are reported as CO2-equivalents (which is a very stable GHG), GWP100 can fail to capture how the relative impacts of different gases change over time.

The short-lived character of methane emissions has been arguably overlooked in most assessments of emission reductions required from the agricultural sector to achieve climate targets. The authors explored how different valuations of methane affect the ranking of mitigation policies in agriculture and, consequently, the sector’s contribution to global warming.

Farmed seafood supply at risk if we don’t act on climate change

Credit: Bob Brewer/Unsplash

The supply of farmed seafood such as salmon and mussels are projected to drop 16 per cent globally by 2090 if no action is taken to mitigate climate change, according to a new UBC study.

Ocean-farmed seafood or mariculture is often seen as a panacea to the problems of depleted stocks of wild fish and growing human demand, and is expected to grow substantially in the coming years, says lead author Dr. Muhammed Oyinlola (he/him), a postdoctoral research fellow at the Institute for the Oceans and Fisheries (IOF). But the new modeling study highlights the industry is as vulnerable to the effects of climate change as any other. “If we continue to burn fossil fuels at our current rate, the amount of seafood such as fish or mussels able to be farmed sustainably will increase by only eight per cent by 2050, and decline by 16 per cent by 2090.”

By comparison, in a low emissions scenario where the action is taken to mitigate climate change, mariculture is projected to grow by about 17 per cent by the mid-21st century and by about 33 per cent by the end of the century, relative to the 2000s.

The model takes into account many factors, including changing ocean temperatures, suitable mariculture areas in the future, and the supply of fishmeal and fish oil. It examined approximately 70 per cent of the world’s mariculture production as of 2015, focusing on Exclusive Economic Zones, where most of the world’s seafood farming occurs.

Climate change will affect mariculture production differently depending on where farms are in the world, and what they produce, says Dr. Oyinlola. The hardest-hit regions in the high-emissions scenario— Norway, Myanmar, Bangladesh, the Netherlands, and China—could see their mariculture production decline by as much as 40 to 90 per cent.

Artificial intelligence can create better lightning forecasts

Lightning is one of the most destructive forces of nature, as in 2020 when it sparked the massive California Lightning Complex fires, but it remains hard to predict. A new study led by the University of Washington shows that machine learning — computer algorithms that improve themselves without direct programming by humans — can be used to improve lightning forecasts.

Better lightning forecasts could help to prepare for potential wildfires, improve safety warnings for lightning and create more accurate long-range climate models.

“The best subjects for machine learning are things that we don’t fully understand. And what is something in the atmospheric sciences field that remains poorly understood? Lightning,” said Daehyun Kim, a UW associate professor of atmospheric sciences. “To our knowledge, our work is the first to demonstrate that machine learning algorithms can work for lightning.”

The new technique combines weather forecasts with a machine learning equation based on analyses of past lightning events. The hybrid method, presented Dec. 13 at the American Geophysical Union’s fall meeting, can forecast lightning over the southeastern U.S. two days earlier than the leading existing technique.

“This demonstrates that forecasts of severe weather systems, such as thunderstorms, can be improved by using methods based on machine learning,” said Wei-Yi Cheng, who did the work for his UW doctorate in atmospheric sciences. “It encourages the exploration of machine learning methods for other types of severe weather forecasts, such as tornadoes or hailstorms.”