Tyler O'Neal, Staff Editor GOVERNMENT

Munich deploys sensor network to create a spatially resolved emission map of the city

MUCCnet: Precision technology allows quantification of urban greenhouse gas emissions

The sensor network MUCCnet (Munich Urban Carbon Column network) consists of five high-precision optical instruments that analyze the sun's light spectra. They measure the concentration of the gases carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO). Since each gas has its own unique spectral "fingerprint", concentrations of these gases can be determined in the columns of air between the instruments and the sun.

"By measuring a vertical column of the atmosphere, local disturbances, such as the disproportionate influence of neighboring stacks, can be removed. Therefore, this type of greenhouse gas balancing is considered particularly robust and accurate," says Prof. Jia Chen. Measuring device of the MUCCnet sensor network set up by Prof. Jia Chen, Chair of Environmental Sensing and Modeling, at the TUM Department of Electrical and Computer Engineering of the Technical University of Munich (TUM) on the roof of a building in Taufkirchen. CREDIT F. Dietrich / TUM

Measurements at five locations in and around Munich

One of MUCCnet's measurement devices is located on the main campus of TUM and measures inner-city concentrations. Four other devices are located at the Munich city borders in all four cardinal directions (north: Oberschleissheim, east: Feldkirchen, south: Taufkirchen, and west: Graefelfing).

Chen explains the principle in simple terms: "We set up one sensor upwind from the city and the second downwind. So any increase in gases between the first sensor and the second must have been generated from inside the city." To cover as many wind directions as possible, there is a sensor in each cardinal direction. With the input of the sensor data and meteorological parameters, high-performance supercomputers can create a spatially resolved emission map of the city. Prof. Jia Chen, Chair of Environmental Sensing and Modeling at the TUM Department of Electrical and Computer Engineering of the Technical University of Munich (TUM) at a measuring device of the MUCCnet sensor network on the roof of a building at the main campus of the TUM in Munich. CREDIT A. Heddergott / TUM

Using measured data to improve the calculated emission figures

Under the Paris Climate Agreement, atmospheric measurements are not required to meet emissions targets. "Instead, the emissions numbers we hear in the news are based on calculations," explains Prof. Chen.

Among other things, this makes it impossible to detect so far unknown sources - such as leaks in gas pipelines. Therefore, Prof. Jia Chen's team and project leader Florian Dietrich created MUCCnet to measure emissions with high precision, which can reduce inaccuracies in calculations.

Corona lockdown as a natural experiment for the measurement data series

The current Corona crisis provides a useful natural experiment for researchers because as a result of the two German lockdowns in spring 2020 as well as winter 2020/21 and severe air traffic curtailment, there have been changes in urban greenhouse gas emissions, which can be used to validate measurements as well as atmospheric transport models.

Unfortunately, the lifetime of CO2 is very long (several hundred years) and measurement results show that even such a drastic global event as this pandemic has not stopped the annual increase of CO2 concentration in the atmosphere.

Measurement data can be accessed online

Since the start of 2021, the researchers have operated a website (http://atmosphere.ei.tum.de) which not only makes measurement data available to everyone but also explains the devices used and the principles employed to gain the data. Interested parties can find absolute values of greenhouse gas concentrations on the portal and can, for example, draw comparisons between stations at different locations. 

"Since climate change is a global problem, the Munich network should only be the first step," says Prof. Chen. In the future, Chen's team plans to use measurements from existing greenhouse gas satellites to expand the methods and models developed in Munich worldwide and thus make a decisive contribution to understanding and solving the climate problem. 

RELATED JOURNAL ARTICLE http://dx.doi.org/10.5194/amt-14-1111-2021

Swiss geophysicists show how volcanoes light up the night sky of this planet

Tyler O'Neal, Staff Editor GOVERNMENT

On Earth, plate tectonics is not only responsible for the rise of mountains and earthquakes. It is also an essential part of the cycle that brings material from the planet's interior to the surface and the atmosphere and then transports it back beneath the Earth's crust. Tectonics thus has a vital influence on the conditions that ultimately make Earth habitable.

Until now, researchers have found no evidence of global tectonic activity on planets outside our solar system. A team of researchers led by Tobias Meier from the Center for Space and Habitability (CSH) at the University of Bern and with the participation of ETH Zurich, the University of Oxford, and the National Center of Competence in Research NCCR PlanetS has now found evidence of the flow patterns inside a planet, located 45 light-years from Earth: LHS 3844b. Their results were published in The Astrophysical Journal Letters. Tobias G. Meier, Center for Space and Habitability (CSH) and NCCR PlanetS, University of Bern CREDIT © Universität Bern / University of Bern, Photo: Felix Meier

An extreme contrast and no atmosphere

"Observing signs of tectonic activity is very difficult because they are usually hidden beneath an atmosphere", Meier explains. However, recent results suggested that LHS 3844b probably does not have an atmosphere. Slightly larger than Earth and likely similarly rocky, it orbits around its star so closely that one side of the planet is in constant daylight and the other in the permanent night - just like the same side of the Moon always faces the Earth. With no atmosphere shielding it from the intense radiation, the surface gets blisteringly hot: it can reach up to 800°C on the dayside. The night side, on the other hand, is freezing. Temperatures there might fall below minus 250°C. "We thought that this severe temperature contrast might affect material flow in the planet's interior", Meier recalls.

To test their theory, the team ran supercomputer simulations with different strengths of material and internal heating sources, such as heat from the planet's core and the decay of radioactive elements. The supercomputing included the large temperature contrast on the surface imposed by the host star.

Flow inside the planet from one hemisphere to the other

"Most simulations showed that there was only upwards flow on one side of the planet and downwards flow on the other. Material, therefore, flowed from one hemisphere to the other", Meier reports. Surprisingly, the direction was not always the same. "Based on what we are used to from Earth, you would expect the material on the hot dayside to be lighter and therefore flow upwards and vice versa", co-author Dan Bower at the University of Bern and the NCCR PlanetS explains. Yet, some of the teams' supercomputer simulations also showed the opposite flow direction. "This initially counter-intuitive result is due to the change in viscosity with temperature: cold material is stiffer and therefore doesn't want to bend, break or subduct into the interior. Warm material, however, is less viscous - so even solid rock becomes more mobile when heated - and can readily flow towards the planet's interior", Bower elaborates. Either way, these results show how a planetary surface and interior can exchange material under conditions very different from those on Earth. Dr. Dan J. Bower, Center for Space and Habitability (CSH) and NCCR PlanetS, University of Bern CREDIT © Universität Bern / University of Bern, Photo: D. Bower

A volcanic hemisphere

Such material flow could have bizarre consequences. "On whichever side of the planet the material flows upwards, one would expect a large amount of volcanism on that particular side", Bower points out. He continues "similar deep upwelling flows on Earth drive volcanic activity at Hawaii and Iceland". One could therefore imagine a hemisphere with countless volcanoes - a volcanic hemisphere so to speak - and one with almost none.

"Our simulations show how such patterns could manifest, but it would require more detailed observations to verify. For example, a higher-resolution map of surface temperature could point to enhanced outgassing from volcanism or detection of volcanic gases. This is something we hope future research will help us to understand", Meier concludes.

Bernese space exploration: With the world's elite since the first moon landing 

When the second man, "Buzz" Aldrin, stepped out of the lunar module on July 21, 1969, the first task he did was to set up the Bernese Solar Wind Composition Experiment (SWC) also known as the "solar wind sail" by planting it in the ground of the moon, even before the American flag. This experiment, which was planned and the results analyzed by Prof. Dr. Johannes Geiss and his team from the Physics Institute of the University of Bern, was the first great highlight in the history of Bernese space exploration.

Ever since Bernese space exploration has been among the world's elite. The numbers are impressive: 25 times were instruments flown into the upper atmosphere and ionosphere using rockets (1967-1993), 9 times into the stratosphere with balloon flights (1991-2008), over 30 instruments were flown on space probes, and with CHEOPS the University of Bern shares responsibility with ESA for a whole mission. This artist's illustration represents the possible interior dynamics of the super-Earth exoplanet LHS 3844b. The planet's interior properties and the strong stellar irradiation might lead to a hemispheric tectonic regime. CREDIT © Universität Bern / University of Bern, Illustration: Thibaut Roger

The successful work of the Department of Space Research and Planetary Sciences (WP)from the Physics Institute of the University of Bern was consolidated by the foundation of a university competence center, the Center for Space and Habitability (CSH). The Swiss National Fund also awarded the University of Bern the National Center of Competence in Research (NCCR) PlanetS, which it manages together with the University of Geneva.

Geisinger, Tempus scientists use AI to predict new atrial fibrillation, stroke risk

Tyler O'Neal, Staff Editor GOVERNMENT

A team of scientists from Geisinger and Tempus has found that artificial intelligence can predict the risk of new atrial fibrillation (AF) and AF-related stroke. Tempus is a technology company advancing precision medicine through the practical application of artificial intelligence in healthcare. 

Atrial fibrillation is the most common cardiac arrhythmia and is associated with numerous health risks, including stroke and death. The study, published in Circulation, used electrical signals from the heart--measured from a 12-lead electrocardiogram (ECG)--to identify patients who are likely to develop AF, including those at risk for AF-related stroke.

"Each year, over 300 million ECGs are performed in the U.S. to identify cardiac abnormalities within an episode of care. However, these tests cannot generally detect the future potential for negative events like atrial fibrillation or stroke," said Joel Dudley, chief scientific officer at Tempus. "This critical work stems from our major investments in cardiology to generate algorithms that make existing cardiology tests, such as ECGs, smarter and capable of predicting future clinical events. Our goal is to enable clinicians to act earlier in the course of the disease."

To develop their model, the team of data scientists and medical researchers used 1.6 million ECGs from 430,000 patients over 35 years of patient care at Geisinger. These data were used to train a deep neural network--a specialized class of artificial intelligence--to predict, among patients without a previous history of AF, who would develop AF within 12 months. The neural network performance exceeded that of current clinical models for predicting AF risk. Furthermore, 62% of patients without known AF who experienced an AF-related stroke within three years were identified as high risk by the model before the stroke occurred.

"Not only can we now predict who is at risk of developing atrial fibrillation, but this work shows that the high-risk prediction precedes many AF-related strokes," said Brandon Fornwalt, M.D., Ph.D., co-senior author and chair of Geisinger's Department of Translational Data Science and Informatics. "With that kind of information, we can change the way these patients are screened and treated, potentially preventing such severe outcomes. This is huge for patients."