Earth has many unique features for a planet, such as a magnetic field, a large moon, and plate tectonics. It’s also the only planet we know of that harbors life. These facts form the basis of the Rare Earth hypothesis, which posits that we haven’t found aliens because other planets in the Galaxy probably don’t have all the right conditions for life. 

Another characteristic of Earth is that about 30% of its surface is land and about 70% is ocean. Recently, Columbia University Assistant Professor David Kipping investigated whether the proportion of Earth’s surface covered by dry land versus ocean, or its land fraction, is another reason Earth is habitable not only for simple single-celled organisms, but also for intelligent species like humans. 

To test this hypothesis, Kipping created 4 statistical models of planets with different land fractions that intelligent aliens could potentially evolve on. First, he created an equation to describe the likelihood that a planet in its star’s habitable zone has a particular land fraction, known as a probability distribution. Kipping weighted this probability distribution toward the extreme ends, making it more likely that a planet would be covered by a single huge landmass or a single vast ocean than by a mix of both, as on Earth. 

Kipping then incorporated this land fraction probability distribution into his statistical models to calculate the probability that a random planet will have that land fraction and host intelligent life. The 4 scenarios Kipping tested were: 1) that intelligent life is more likely to emerge on land-dominated planets, 2) that it’s more likely to emerge on ocean-dominated planets, 3) that it’s more likely to emerge on planets with roughly equal amounts of land and ocean, and 4) that its emergence is independent of a planet’s land fraction. 

As a first step in determining the kinds of planets intelligent aliens would tend to emerge on, Kipping used each model to predict the probability that intelligent life would emerge on a planet with the same land fraction as Earth. He then compared these probabilities by calculating the ratios between each value. Because Earth is the only known planet with intelligent life, a model that predicted a greater probability for humanity’s existence on Earth would be more likely to reflect reality.

Kipping considered it strong evidence that a given model was more realistic than another if the ratio between 2 of them was greater than 10, meaning one model was 10 times more likely to predict the existence of Earth and humanity. Kipping found that no comparison of any 2 models passed this threshold. However, the models assuming that intelligent life prefers ocean-dominated planets or planets with a land-ocean balance were 2.5 and 3 times more likely to predict the existence of humanity than the model assuming that intelligent life prefers land-dominated planets. Additionally, the model assuming that intelligent life prefers a land-ocean balance was always more likely to predict humanity than any other model, though marginally. 

Kipping also addressed whether finding more planets with intelligent life would affect which model was deemed most realistic, for example, if scientists discovered conclusive evidence of life on Mars in its distant past. Here, Kipping identified 2 complications. First, it’s uncertain how much of Mars’s surface was once covered by water – some estimate it had a land fraction as high as 81%, while others estimate it was as low as 25%. Second, proving that Mars once had life would not prove it once had intelligent life.

Regardless, Kipping reran the models assuming that ancient Mars had a land fraction comparable to Earth’s. Adding this second data point produced ratios similar to those in the earlier Earth-only calculations, meaning it still didn’t make any single model 10 times more likely to predict the existence of humans and Martians, respectively. 

Kipping then took the 10-times threshold and reversed the calculations to find what conditions would exceed it. In doing so, he calculated that astronomers would need to find 14 other planets with intelligent life and known land fractions to robustly determine whether intelligent life is more likely to occur on desert planets, ocean planets, balanced planets, or without bias.

Kipping concluded that he can’t yet definitively state whether there is something special about Earth’s land fraction when it comes to producing intelligent species. However, Earth’s existence would suggest that intelligent life is unlikely to favor extreme desert planets, so the Milky Way probably isn’t filled with Tatooines and Jakkus. And while his analysis doesn’t debunk the Rare Earth hypothesis, it does undermine the argument that Earth’s ocean size explains why Earth is rare. 

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About 400 million years ago, the population of plants with vein systems for transferring water and nutrients, called vascular land plants, exploded. Soon thereafter, rocks from some continental magmas showed notable shifts in their chemical compositions. Geologists have suggested that these magma changes happened worldwide, but some argue that the data might be biased because some geographic regions have more samples to analyze than others. A new research team recently tested whether these magmatic changes occurred on a global scale, versus in isolated mountain belts or volcanic islands. 

Geologists use the chemistry of rocks formed from magma to understand a magma’s history. In particular, a mineral called zircon that forms from cooling magma preserves chemical clues about where the magma came from and what it interacted with. To test whether magma changes were global or local, the authors needed data ranging from the equator to the poles. Continents have shifted over the past 400 million years, so scientists use the latitude a rock had when it formed, called its paleolatitude, to compare samples from different parts of ancient Earth. To understand magma histories worldwide, the team used publicly available chemical data from zircons in magmatic rocks that formed across a wide spread of paleolatitudes.

Chemical elements with the same number of protons but different numbers of neutrons are called isotopes with different masses. To discern how plants influenced magma, the researchers analyzed 2 different isotope signals preserved in the zircons. The first isotope signal comes from the ratio of the heavy to light oxygen isotopes, which increases when sediment mixes into magma. Scientists refer to this value as δ¹⁸O, pronounced “delta 18-O.” 

The second isotope signal comes from the element hafnium, denoted Hf. Geologists use hafnium to estimate how long ago magmas melted and separated from the mantle. Zircon contains 2 Hf isotopes, one of which is stable and one of which is produced by radioactive decay. Because this decay happens over billions of years, the ratio between the 2 Hf isotopes over time shifts only slightly. Geologists express these tiny differences using a shorthand called εHf, pronounced “epsilon hafnium,” which shows how much a magma’s Hf signature has changed from Earth’s original mantle. Lower εHf values indicate magmas that incorporated older crustal rock, while higher εHf values reflect mantle sources.

The researchers found that δ¹⁸O values increased as εHf values decreased in these zircons. They concluded that this trend indicates increasing amounts of land-derived sediment in magmas, corresponding with the evolution of land plants. They suggested that land plants altered the ancient landscape, changing how sediments weathered and moved over land. 

To explore this pattern in detail, the team focused on the Andes Mountains, a region that preserves a long history of magmatic activity across a long span of space and time. Using a database, they accessed isotope data from zircon samples collected in the Andes Mountains by dozens of other research groups. These samples covered 32 degrees of modern latitude and 520 million years of Earth’s history, offering a broad window into how magma chemistry changed during that time.

They found that zircons older than 450 million years had no relationship between their εHf and δ¹⁸O values. However, in zircons younger than 450 million years, δ¹⁸O increased as εHf decreased. The researchers saw this pattern in magmas that formed along the edge of the continent, where one tectonic plate sinks below the other, called a subduction zone. They also saw this pattern in magmas that formed inland, away from the subduction zone, around 200 million years ago during the breakup of the supercontinent Pangaea.

 They found similar results in published zircon isotope data from igneous rocks in China, the Caribbean, Antarctica, Madagascar, and Tasmania. Zircons from each region showed the same relationship as zircons in the Andes. Since paleolatitude can also reflect ancient climate, the researchers compared the ratio of εHf and δ¹⁸O, written as εHf/δ¹⁸O, with paleolatitude to test whether ancient climate zones influenced magma chemistry. They found no link between paleolatitude and εHf/δ¹⁸O. 

With these results in mind, the researchers concluded that the relationship between εHf and δ¹⁸O shifted worldwide after vascular land plants evolved. They argued that as plants spread across the continents, their roots accelerated the breakdown of rocks. This accelerated weathering produced large amounts of sediment that washed into ocean basins and was eventually subducted into the mantle, forever changing the chemistry of magma formed there. They suggested that this chain of events illustrates how life on Earth’s surface can drive changes deep within the planet. 

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The evolution of land plants about 450 million years ago altered many of Earth’s geologic processes, like weathering and erosion. Due to the lack of evidence for meandering rivers before then, past scientists hypothesized that plants could have caused straight rivers to meander. However, in recent decades, researchers have challenged this idea. They’ve suggested that plants could have changed rivers without causing them to meander.

To understand how vegetation changed rivers in the past, researchers recently studied 49 modern meandering rivers. They sorted these rivers into 3 categories – vegetated, unvegetated, and semi-vegetated – by analyzing color images taken of them from the air. They identified 18 vegetated rivers located in South America, 24 unvegetated rivers in the western United States, and 7 semi-vegetated rivers in China and the Eastern United States. 

To examine the impact of plants on these rivers, the researchers quantified how much each river channel curves, known as its sinuosity. They used opposite banks of each river bend to find its center point, then, using digital maps, drew a line along the river’s trajectory at an equal distance between the bend center points. They used this line to calculate the angle between the river’s curve and the center point. This angle, called the migration angle, shows how a river bend relates to the river’s downstream direction. By measuring it, researchers can tell whether a river is developing more vertically or horizontally, and how sharp its bends are, either of which could be influenced by plants. 

The researchers compared migration angles across each river system to determine how river bends varied between vegetated and unvegetated rivers. They found that vegetated rivers tend to deposit sediments in the river bend, leading to curvier bends that develop horizontally and widen over time. In contrast, unvegetated rivers deposit sediment downstream, which means the rivers bend less and have greater variability in bend width.

The question remained whether plants were the primary cause of these differences or whether other factors were at play. To resolve this, the researchers investigated 3 additional factors. The first was the natural fluctuations in water flow across a river system, called its flow variability. They found that during storms, flow variability caused river bends to move downstream in unvegetated rivers, but not in vegetated rivers. This result suggested that flow variability alone didn’t drive downstream migration, although it can directly impact vegetation. 

The second variable the researchers analyzed was the amount of sediment a river can carry, or its sediment flux. They found that rivers carrying more sediment can erode more banks, also shifting river bends. However, rivers with more sediment but the same level of plant coverage had statistically similar bend angles. Thus, the researchers concluded that sediment flux alone can’t drive bend development, and that the changes were instead dependent on vegetation cover. 

The third variable they analyzed was riverbank strength. The researchers observed rivers with strong banks, made of rock or compacted sediment, and weak banks, made of loose sediment. They observed no difference in river bends with the same vegetation cover but different bank strengths. The researchers concluded that bank strength is also not the primary driver of bend migration in vegetated or unvegetated rivers. 

Of the 4 variables the researchers examined – flow variability, sediment flux, bank strength, and vegetation cover – vegetation cover consistently had the greatest impact on the appearance of meandering rivers. They concluded that meandering rivers could have existed before plants, but would have looked different. Like modern unvegetated rivers, ancient meandering rivers likely had lower-angle bends. As plants evolved and grew on river banks, the bends would have developed differently, becoming curvier like modern vegetated rivers. They suggested that understanding this process provides insight into life on Earth before plants evolved 450 million years ago. 

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Most people think of Mars as a big red dustball, but researchers recently found Martian mineral deposits suggesting it was once warm and humid. The team used the Compact Reconnaissance Imaging Spectrometer aboard NASA’s Mars Reconnaissance Orbiter to analyze specific wavelengths of visible and near-infrared light from minerals on Mars’s surface to determine their chemical composition from afar.

Past researchers identified layered silicate minerals, called clays, across the Martian surface. Clays form when water interacts with rock, and record the amounts and chemical compositions of the waters that formed them. As water interacted with Martian surface rocks, it picked up more mobile elements like magnesium and iron and carried them to lower depths in the Martian soils, while less mobile elements like aluminum stayed in place. This process, called leaching, created 2 distinct layers of clays in the Martian rocks. 

Scientists have proposed 2 main hypotheses for how these layered clays formed on Mars. The first is that they formed through underwater leaching in pools or lakes sometime in Mars’ past. The second is that they formed across the Martian surface, where a widespread humid environment provided the moisture needed to leach them. 

To evaluate these hypotheses, a team led by researchers at Purdue University recently estimated the “true” thicknesses of Martian clay layers with a method scientists had previously only used on Earth. Rock layers containing clays can become tilted, making them appear thicker or thinner than they actually are. To address this discrepancy, the team used the High Resolution Imaging Science Experiment (HiRISE) tool on the Mars Reconnaissance Orbiter to create high-resolution elevation maps of the Martian surface. Then they combined these maps with surface composition data from the Compact Reconnaissance Imaging Spectrometer to create 3D composition maps. 

Using the 3D composition maps, the researchers found where each clay layer was exposed at the surface and traced it underground to estimate an angle of tilt. They then used trigonometry to calculate the true thicknesses of each clay layer. They analysed 46 regions across the Martian surface, and found that the combined thickness of both clay layers was around 20 to 680 feet (6 to 200 meters), with an average of about 190 feet (60 meters). That’s a maximum thickness as high as a 60-story building! 

Next, the researchers tested the extent of the clay deposits in a large ancient Martian valley known as the Mawrth Vallis Region. They focused on this region because it had large elevation changes, and scientists in the past had already collected high-resolution chemical composition and elevation data there. 

They explained that if the clay layers were restricted to the lowest parts of the valley where water once existed, and had changing thicknesses and boundaries between layers, this would provide strong evidence in favor of the “underwater leaching” hypothesis. In contrast, if the clay layers were more widespread, with consistent layer boundaries and thicknesses, this would provide strong evidence of a humid surface environment, in favor of the “surface leaching” hypothesis. 

The researchers found that the clay layers extended beyond the lowest parts of the valley and had consistent layer boundaries across more than half a mile (about a kilometer) of elevation change. Thus, they concluded that the clay layers formed by surface leaching in a humid environment. 

These findings conflict with climate models of early Mars, which generally suggest that the Martian surface rarely got above freezing temperatures. To address this discrepancy, the team proposed that these deposits could have formed over a long period of time rather than in a consistently warm and wet environment. If the surface was frozen most of the time, but got above freezing in short bursts, these clay deposits could still have formed, just over a much longer time period. In this case, the Mars climate models and the researchers’ findings would agree.

The researchers acknowledged that their study has some limitations, particularly regarding the sparse sample locations. Though they found strong evidence for a widespread humid environment on early Mars, more in-depth studies of locations like Mawrth Vallis could better constrain the specific surface environmental conditions under which these clays formed and potentially reconcile their data with Martian climate models.

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The universe is around 14 billion years old, but scientists theorize that no stars formed for the first several hundred million years, during an era known as the cosmic dark ages. They refer to the first billion years or so after this, when stars formed, as the cosmic dawn. At that time, the very oldest galaxies first assembled from collections of gas and plasma. 

As these galaxies assembled and more material became available, the number of stars formed each year increased. Around 2 to 3 billion years after the Big Bang, galaxies grew faster than they ever would, producing stars at the highest rate in the universe’s history. This era is called cosmic noon.

Researchers from the Netherlands recently investigated 3 distant galaxies whose light began its journey to Earth during cosmic noon. They selected targets from a set of ancient star-forming galaxies identified in the ALMA – Archival Large Program to Advance Kinematic Analysis or ALMA-ALPAKA project. Of these, they chose to study 3 galaxies labeled ID1, ID3, and ID13.

They combined 2 different types of data to produce a detailed description of these galaxies. First, they collected data from an enormous telescope comprising 66 antennas in Chile, known as the Atacama Large Millimeter/submillimeter Array or ALMA. They used ALMA to detect radio-wave emissions from carbon monoxide and elemental carbon in these galaxies. The researchers stated that studying these chemicals in distant galaxies could reveal how their free-floating gas clouds move. They also used publicly available data from JWST’s Near Infrared Camera, or NIRCam, to determine how much light the galaxies’ stars emitted. By analyzing cosmic noon galaxies in multiple different ways, the team aimed to measure their masses and the relative contributions of regular matter and dark matter.

They used a computer program developed by other astronomers to interpret the JWST data as a series of maps showing the distribution of stars across each galaxy. They used this light-emission data to estimate the total mass of all the stars in these galaxies. Then they developed an original computer program to map the distribution of gas through each galaxy using the ALMA data. The team used these maps to create plots, known as rotation curves, which show how fast particles orbit each galaxy’s center as a function of their distance from it. 

The astronomers used these rotation curves to estimate the amount of dark matter in each galaxy. They explained that this method works because dark matter is totally invisible, but it still exerts a gravitational pull. Its gravitational pull causes visible material like stars and gas closer to the edges of these galaxies to move faster than they would in galaxies without dark matter. 

The team found that these galaxies had between 39 and 80 billion times the mass of our sun, or solar masses, in stars. They had between 4 billion and nearly 16 billion solar masses worth of free-floating gas. And they had from 1 trillion to 31 trillion solar masses of dark matter.

However, when the team compared the light-emission data with the rotation curves, they found a discrepancy. Typically, dark matter resides in a shell or halo surrounding a galaxy, meaning it should mostly affect material near the galaxy’s outer edge. Since astronomers don’t usually have to account for dark matter near a galaxy’s center, they can calculate the total mass of center material based on the amount of gas and stars they see there. But near the centers of these galaxies, the team found that the masses they derived from the light emissions were less than what they calculated from the rotation curves. 

They proposed multiple potential explanations for this discrepancy. First, they suggested that the halo shape might not be a good model for the dark matter distribution in all galaxies, meaning that cosmic noon galaxies could contain dark matter near their centers. Second, they suggested that stars could be packed tightly in the center of these galaxies, blocking each other’s light emissions. Third, they suggested that galaxy ID1 could have a supermassive black hole as big as 1.5% its total stellar mass at its center.

The team concluded that they now have a detailed picture of the mass distribution in these cosmic noon galaxies, but the reason for their center mass discrepancies remains elusive. They suggested that a complex relationship exists between the dark matter halos and the rest of the material within these galaxies. They indicated that future astronomers could adapt their methods to study the distribution of material in other distant galaxies studied by ALMA-ALPAKA and forthcoming galactic surveys.

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Greenhouse gases trap heat within the atmosphere. One such gas that exists beneath the ocean floor is methane. Ice-like substances on the seafloor that contain methane, known as methane hydrates, can break apart or melt, releasing methane gas into the ocean, risking further global warming. Melting permafrost, active tectonics, daily tidal patterns, and changing sea levels can similarly trigger methane’s escape from sediments. However, scientists don’t understand how these triggers will respond to future climate change.

A team of researchers hypothesized that future global warming could actually accelerate methane’s escape into the ocean. To investigate this hypothesis, they focused on an ancient global warming event approximately 56 million years ago, called the Paleocene-Eocene Thermal Maximum or PETM. Arctic Ocean temperatures at times exceeded 20°C (68°F) during this event. These elevated temperatures serve as an analog for today’s rapidly warming conditions. 

Once methane enters seawater, its fate is largely determined by 2 sets of biological processes. Today, 90% of methane released into the ocean from the seafloor is consumed by tiny organisms called microbes via a process known as anaerobic methane oxidation. During this process, microbes consume methane alongside sulfate, producing a solid iron-sulfur mineral, pyrite. Anaerobic methane oxidation prevents methane from escaping into the atmosphere by trapping it in minerals. In this case, the ocean becomes a reservoir, or sink, for methane. 

Despite this, too much methane could overwhelm the sulfate-dependent cycle. If that occurs, a different set of microbes consumes methane alongside oxygen in a process known as aerobic methane oxidation. Aerobic methane oxidation produces carbon dioxide, a potent heat-trapping greenhouse gas that escapes from the ocean. Aerobic oxidation accounts for 10% of methane consumption in oceans today, though this could have been different in the past. 

To determine how much anaerobic versus aerobic methane oxidation occurred during the PETM, the team extracted data from sediments retrieved from the Arctic Ocean floor. As sediment piles up on the seafloor, it compacts. Scientists can drill deep into the seafloor to extract a cylindrical sample, or core, of this compacted sediment. 

The age of sediments in a core increases with depth. Therefore, younger sediments exist at the top of the core, and older sediments exist at the bottom. For this project, the team used a previously extracted core from the Arctic Ocean that contained sediments dating back 100 million years. They found 56-million-year-old sediments from the PETM at a depth of 386 meters, or 1,266 feet, in this core. 

The researchers explained that microbes leave behind unique carbon-based molecules called organic biomarkers when they decompose. These organic biomarkers accumulate in seafloor sediments. The 2 different types of methane-consuming microbes leave behind 2 different biomarkers, one for anaerobic methane oxidation and one for aerobic methane oxidation. This team measured the amount of each biomarker in the sediment core to determine which microbes were dominant during the PETM. 

The biomarker left behind from microbes performing aerobic methane oxidation is called hop(17)21-ene. The researchers noticed that the amount of hop(17)21-ene increased by a factor of 4 during the PETM. At the same time, the biomarker left behind from microbes performing anaerobic methane oxidation, called glycerol dialkyl tetraether, decreased to half. They interpreted these trends to reflect the rise of aerobic methane cycling and the shutdown of anaerobic methane cycling, respectively. They attributed this transition to the release of enough methane to overwhelm the sulfate-dependent methane cycle under warming conditions.

To estimate the amount of carbon dioxide produced by aerobic methane oxidation during the PETM, the researchers located another biomarker in the sediment core, called phytane. Phytane is produced by organisms that consume carbon dioxide during photosynthesis, and its structure preserves clues to the amount of carbon dioxide available at the time. The researchers found that during and well after the PETM, the concentration of carbon dioxide in the Arctic Ocean was 4 times greater than modern levels. They concluded that the Arctic Ocean became a prolonged source of carbon dioxide to the atmosphere, even after the PETM.

The team suggested that the uptick in aerobic methane oxidation during the PETM serves as an analog for the modern Arctic Ocean, which continues to warm rapidly in the face of modern climate change. Their results highlight how the transformation of methane into carbon dioxide poses a threat. More carbon dioxide in the atmosphere warms the air, which heats the oceans, causing more methane to escape from the seafloor and eventually be converted into additional carbon dioxide. When triggered, this feedback would continue to amplify and could become difficult to recover from.  

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Over 20 million tons of polystyrene plastic are produced annually, yet only a small fraction is recycled worldwide. Current recycling methods consume large amounts of energy and often rely on harsh and toxic chemicals to break the strong molecular chains that make up polystyrene. One possible solution is the use of sulfur, which is an inexpensive byproduct formed when refining crude oil. Its unique chemical structure allows it to break up strong chemical chains in long plastic molecules. Despite its abundance, sulfur has very limited applications, and converting it into more usable forms tends to require a lot of heat, rendering it unused for long periods of time. 

Researchers at the Dalian Institute of Chemical Physics hypothesized that sulfur could help break down polystyrene waste to form more valuable chemicals. To power this reaction, they converted sunlight into heat energy through a process called photothermal conversion. They used this heat to transform polystyrene and sulfur into valuable chemicals like 2,4-diphenylthiophene, or chemical D, and 1,3,5-triphenylbenzene, or chemical T, which are used to make semiconductors and chemical sensors. 

To test this, the team mixed ground polystyrene and sulfur at a molar ratio of 1:0.5 in a glass test tube. They sealed the tube with a balloon and secured it onto an iron stand. Then, they focused sunlight onto the bottom of the tube using a curved mirror. As the mixture heated up, the yellow-white solids gradually melted and transformed into a reddish-black liquid after 2 minutes. After heating, the researchers removed the mirror and allowed the system to cool before collecting the gaseous products from the balloon and dissolving the remaining solids for further purification and analysis. 

The researchers then adjusted the reaction conditions to understand what factors influenced their results. They tested the reaction without sulfur, varied the sulfur ratios from 0.2 to 0.8, and replaced elemental sulfur with other sulfur-containing compounds. They also explored adding known photothermal agents, specifically metal oxide additives, to the mixture. 

To compare the difference between sunlight and artificial light, the researchers repeated the experiment indoors using a 100 Watt LED bulb and monitored temperature changes with a thermal camera. They also ran a control experiment using only polystyrene to check how sulfur affected the yield under LED light. They also tested exposure times from 1 to 6 minutes in 1-minute increments to determine how long it took to achieve the highest yields under LED. The researchers used these tests to identify which conditions were necessary for the reaction to occur and how different factors influenced its outcome.

They found that without sulfur or with alternative sulfur-containing compounds, the reaction did not produce chemical D or T under sunlight. In contrast, reactions that included sulfur successfully produced these target products, with the highest yields of 34% for D and 16% for T at a sulfur ratio of 0.5. When they added metal oxides, the chemical yields decreased to 22% and 12%, respectively, suggesting that these additives interfered with the desired reactions. In addition, when the researchers switched from sunlight to LED, the reaction yields dropped to 26% for D and 13% for T. 

Next, they examined how reaction time influenced product formation. They found that yields increased gradually before reaching the maximum at 4 minutes and leveling off. They also noted that mixtures containing sulfur heated up from room temperature to 320°C (608°F), while the control setup only showed a slight temperature increase. The researchers interpreted these results as confirmation of sulfur’s dual role as a reactant and a light-to-heat converter that enables the conversion of polystyrene to useful chemicals.

Taking it a step further, the researchers tested their method on real-world polystyrene wastes, including food packaging, cup lids, and foamed plastics. They successfully produced chemicals D and T from these materials, demonstrating that their process works beyond laboratory samples.

The team concluded that their study presents a simple, fast, and solvent-free approach to converting 2 abundant waste materials into valuable chemicals using sunlight. By combining polystyrene waste and excess sulfur, the researchers offer a new pathway for sustainable polymer upcycling that uses clean energy and is broadly applicable to everyday plastics.

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The continent of Africa is splitting into 2 tectonic plates in the middle of Ethiopia. In the recent past, geophysicists have improved their understanding of how tectonic plates like these separate. They’ve shown that continents begin to split apart as the crust and upper mantle, known as the lithosphere, crack and shift. Later, magma from deep within the Earth travels upward through these cracks to Earth’s surface, forming volcanoes. Therefore, scientists know that volcanoes form in areas of continental rifting, but not how quickly they form, which complicates efforts to assess volcanic hazards in rift zones.

Researchers led by Kevin Wong sought to answer this question by examining a mineral formed when magma cools, called olivine. They focused on 72 olivine crystals ranging in size from 1 to 4 millimeters (0.04 to 0.16 inches) from rocks collected at the Boku and Ziway volcanic fields in the Main Ethiopian Rift (MER) zone in Africa. They explained that the lithosphere in this area is still about 35 to 40 kilometers (21 to 25 miles) thick. This thick lithosphere suggests that the MER represents an intermediate stage of continental separation and offers a rare opportunity to study how tectonic stretching transitions into magmatic rifting in the process.

Wong and his team analyzed olivine because it’s one of the first minerals to crystallize from magma, and it continues to grow as the magma rises and cools. As magma rises, its composition changes, producing sharp chemical “zones” within the growing crystals, analogous to growth rings in trees. Changing temperatures and magma compositions cause different elements, like magnesium and iron, to diffuse into and out of the crystals at various rates during the magma’s ascent. So scientists can model these chemical zones and their boundaries in olivine crystals to determine how quickly the magma ascended from the upper mantle to erupt in the rift.

Wong and colleagues examined the olivine crystals from the MER volcanic fields using high-magnification imaging and chemical analyses, with an instrument known as an electron microprobe. Within each crystal, the team mapped 10 to 15 points spaced approximately 5 to 15 microns apart (about 10% of the thickness of a human hair) along a transect from the inner core to the outer rim, spanning its growth zones. 

They found 2 different populations of olivine crystals. The first consisted of normal-zoned crystals with magnesium-rich inner cores, and the second consisted of reverse-zoned crystals with lower magnesium cores. They explained that recently-formed magmas in the deep Earth contain higher amounts of the element magnesium relative to iron. The magnesium-rich zone has a sharp boundary with the magnesium-poor zone, but this boundary can get blurred when elements diffuse across it. Diffusion progressively smooths these crystal boundaries over time at known rates, so researchers can use their “blurryness” to extract information on how quickly the crystals equilibrated with the surrounding magma.

The researchers used numerical models to estimate how quickly magnesium and iron would diffuse across these chemical boundaries at different temperatures and surrounding magma chemistries. They compared thousands of simulated diffusion profiles to their measured olivine diffusion profiles. They used this iterative process to estimate that the crystals diffused, on average, for 40 and 17 days in the surrounding magma while ascending from the deep Earth to erupt at Boku and Ziway, respectively. They further tested these estimates using a growth-diffusion model that better represented natural crystal behavior. That model produced ascent times of about 27 days on average and better reproduced the crystal zoning patterns they observed.

Based on these models, the researchers concluded that intermediate-stage rifting events happen on unexpectedly short timescales. Magmas travel up to 40 kilometers (25 miles) from the deep Earth to the surface within, on average, a single calendar month, which is closer to human timescales than geologic timescales. They suggested that this rapid ascent is likely due to highly developed magmatic plumbing systems in the lithosphere that form before much lithospheric thinning. However, they noted that their results still suggest a wider range in ascension timescales than optimal for disaster mitigation and prediction. 

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The Star Wars series depicted alien heroes fighting against evildoers and their planet-destroying superweapons “a long time ago in a galaxy far, far away.” But what do scientists really know about alien planets in distant galaxies beyond our own? These worlds, known as extragalactic exoplanets, are expected to exist, assuming the Milky Way is no different from other galaxies. However, we have yet to find them since other galaxies are still too far, far away for modern exoplanet-observing techniques.

Recently, a team of astronomers analyzed a stream of over 700,000 stars that the Milky Way likely absorbed from the dissolving Sagittarius dwarf galaxy. These stars are very distant, so the team investigated whether any of them host large, close-orbiting exoplanets called hot Jupiters, which are relatively easy to find.  

They established a set of 3 criteria to narrow down their list of stars. First, each star should appear bright enough when observed by the Transiting Exoplanet Survey Satellite, or TESS, to ensure high-precision results from the team’s data processing software. Second, each star must have more than a 50% likelihood that it originated from the Sagittarius dwarf galaxy, based on motion and position measurements from the Gaia mission. Finally, each star should have a radius of less than twice the Sun’s, as it’s easier to find planets around smaller stars. They used these criteria to limit their candidate list to around 20,000 stars.

After selecting their candidate stars, the team analyzed publicly available TESS catalog data using the software packages eleanor and TESS-Gaia Light Curve, or TGLC. These tools allowed them to plot each star’s brightness over time, in graphs called light curves. Then, the astronomers looked for periodic brightness dips in these light curves as evidence that an exoplanet passed in front of the star. From this, they excluded several thousand additional stars with too much light interference from their surroundings, reducing their final sample size to just over 15,000 stars.

To find hot Jupiters, the team looked for brightness dips at intervals of 14 hours to 10 days, which is the typical orbital period range for hot Jupiters. Then, they used geometry to derive each exoplanet’s radius from the fraction of the starlight it blocked. They excluded candidates with dips corresponding to objects with radii at least twice that of Jupiter’s, as these are likely caused by orbiting companion stars rather than exoplanets.

Among all the stars they surveyed, the team’s strongest candidate to host a hot Jupiter was a star labeled TIC 92223525. They calculated that this star could host an exoplanet with a radius 1.76 times the size of Jupiter’s and an orbital period of 7.2 days. However, when they reviewed this star’s light curve, they found that it was likely contaminated by its neighbor, TIC 92223526. The regular brightness dips from this system of orbiting stars mimicked that of an exoplanet, creating a false positive for TIC 92223525 that was difficult to detect during initial screening. As a result, the team ultimately excluded this candidate, leaving them with no confirmed exoplanets.

The researchers drew several conclusions from their inability to find hot Jupiters in their sample of stars from the Sagittarius dwarf stream. They estimated that if more than 1% of these stars hosted hot Jupiters, it would have been highly unlikely not to detect one in a sample of over 15,000 stars. This places an upper limit of about 1% on the occurrence rate of hot Jupiters. If this estimate is accurate, then even an ideal exoplanet search team would need to examine over 11,000 stars to find an extragalactic hot Jupiter. Accounting for more realistic levels of scientific uncertainty, a future team would likely need to study at least 80,000 stars to find one. 

Although this survey of the Sagittarius dwarf stream yielded null results, the team suggested that future researchers continue searching it and other star streams from different galaxies. Scientists have identified over 20 such streams in the Milky Way. Researchers studying these streams could find the first extragalactic exoplanet or provide evidence that other galaxies produce fewer hot Jupiters than our own. But let’s hope none of them find the first extragalactic Death Star!

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The years 2023 and 2024 were the warmest on record, coinciding with a powerful Pacific climate event known as El Niño. El Niño is the warm phase of a natural climate cycle in which surface waters in the eastern Pacific are unusually warm, bringing record-breaking heatwaves in the Amazon and heavy rainfall in the southern USA. Its counterpart, La Niña, is the cool phase that brings wetter conditions to the Northern USA. 

In a typical El Niño, warm water in the eastern Pacific weakens the winds blowing westward across the tropical Pacific, known as trade winds, allowing more warm water to flow eastward – a self-reinforcing cycle that amplifies the event. However, the 2023 El Niño differed because the ocean warmed intensely, but the trade winds remained strong. Researchers from the Scripps Institution of Oceanography, led by Qihua Peng and Shang-Ping Xie, recently investigated how and why this unusual event occurred.

First, the researchers tracked how air pressures changed across the Pacific during the event using a metric calculated by NOAA, known as the Southern Oscillation Index. When the eastern Pacific warms during an El Niño, the difference in air pressure across the Pacific typically decreases. In 2023, they found that temperatures in the eastern Pacific rose to more than 3°F (2°C) above normal, yet the drop in air pressure was only about 31% as strong as they expected. They also calculated that changes in wind speed and direction could only account for about 30% of the warming. So why was the 2023 El Niño so strong?

To answer this question, the research team then looked beyond the Pacific, analyzing sea surface temperatures from NOAA satellite data. They found that the North Atlantic and Indian Oceans also experienced record-breaking heat in 2023, with temperatures in the North Atlantic exceeding 2°F (1°C) above normal – the warmest in recent history. This suggested that El Niño events can develop in response to ocean conditions worldwide, not just those in the Pacific.

Next, the team used a computer program that simulates how the atmosphere responds to ocean temperatures, called the Community Atmosphere Model, to examine how heat from other oceans affects the Pacific. They found that heat in the North Atlantic and Indian Oceans generated large columns of hot air rising over those regions. This air cooled at high altitudes and then sank over the central Pacific, strengthening a large-scale loop of rising and sinking air that drives trade winds westward. Strengthening this circulation worked against El Niño by keeping trade winds blowing westward about 30% more strongly than Pacific warming alone would have. If the trade winds remained strong, why was the eastern Pacific so warm in 2023?  

To answer this question, the researchers studied 3 consecutive La Niña years between 2020 and 2023, analyzing ocean temperature and sea level data from NOAA’s Global Ocean Data System. During those years, strengthened trade winds transported heat into the western Pacific. As the seawater got warmer, it expanded, a process known as thermal expansion. Over those 3 years, thermal expansion and constant wind created a “pile” of warm water in the western Pacific, which reached its highest level of stored heat since 1982. When the trade winds eventually relaxed as La Niña faded, this piled-up warm water surged eastward, setting the stage for the El Niño event.

To test whether this stored heat alone could drive an El Niño, the team used a computer program that models oceanic and atmospheric interactions, called a coupled general circulation model. They input observed ocean temperatures from April 1, 2023, when La Niña ended, but removed all wind changes after that date. Their model successfully reproduced 87% of the warming observed between June and December 2023, which suggested that trade winds contributed just 13%. Stored heat was carried eastward by massive underwater waves traveling along the equator. As these waves reached the Eastern Pacific, they pushed cold water deeper, allowing surface water to warm. The researchers concluded that this oceanic process drove the 2023 El Niño to develop without the usual wind-driven feedback.

The team suggested that in a warming world, large heat reservoirs in the western Pacific will likely become more common, leading to more frequent strong El Niños. However, because their analysis focused on a single event, it remains unclear how often El Niños develop through oceanic processes alone. Ultimately, their study showed that the ocean can be more than a passive partner in El Niño – it can be the driving force.

The post Why the 2023 El Niño broke records appeared first on Sciworthy.

Stars are mostly made of 2 elements: hydrogen and helium. While this has always been the case, those 2 elements and lithium were the only elements in existence when the Big Bang occurred around 14 billion years ago. When the first stars exploded, they released those primordial elements, as well as heavier elements produced by nuclear fusion inside them. 

Astronomers call all elements heavier than hydrogen and helium metals, a term chemists use quite differently. Subsequent generations of stars, including the Sun, formed in clouds of gas and dust enriched with these metals, such as carbon, oxygen, magnesium, and silicon. Scientists estimate that modern stars are 1% to 5% metal by mass.

Astronomers claim there is no solid evidence that stars contain exceptionally high amounts of metals, but some, called chemically peculiar stars, appear to. Astronomers study stars by looking at the patterns of light they emit, called spectra. Each element produces a unique light pattern, so astronomers can compare the light patterns in a star’s spectra to determine how much of each element is present, especially in the outer layers of the star. Researchers theorize that chemically peculiar stars don’t actually have more metals than average stars. Instead, they think that metals from their interiors diffuse to their outer layers more than in most stars.

A team of researchers from the American Association of Variable Star Observers and Masaryk University in Czechia recently observed 85 chemically peculiar stars to understand their behavior and better classify them. For their study, they first used the General Catalog of CP Stars, published in 2009 in Astronomy & Astrophysics, to identify targets across the 4 classes of these stars, labeled CP1 through CP4. CP1 stars have strong spectral patterns for iron and other heavy elements, CP2 stars have strong patterns for silicon, chromium, strontium, and europium, CP3 stars have strong patterns for mercury and manganese, and CP4 stars have either unusually weak or usually strong helium patterns. 

The team compiled a list of 85 stars to observe, then used the BRIght Target Explorer (BRITE) Constellation to monitor changes in their brightness. The BRITE Constellation is a set of 5 satellites equipped with telescopes and cameras for either red or blue light. Using the BRITE Constellation, the team monitored each star for several days. 

They found that 74 of these 85 chemically peculiar stars varied in brightness during their survey. They attributed this to the varied abundance of metals on their surfaces, which would form dark patches that go in and out of view from Earth’s perspective as the stars rotate. The team observed that 6 of these 74 stars appeared to change in brightness over multiple periods. They were surprised by this result because a star’s brightness wouldn’t vary over multiple periods if the changes were due to rotation. They compared their findings to data other scientists had collected from these stars with the Transiting Exoplanet Survey Satellite, or TESS, and found that all 6 stars had been misclassified as chemically peculiar stars.

The other 11 chemically peculiar stars appeared to show no periodic changes in their brightness, suggesting that they’re stationary. The team claimed that some CP1 and CP3 stars don’t rotate, but they identified cases in which CP2 and CP4 stars that ought to rotate appeared to be stationary. They suggested 2 potential reasons for this. One is that these CP2 and CP4 stars are misclassified, requiring more thorough analysis of their spectra to confirm their classifications. The other is that the stars rotate slowly, with rotational periods of 50 days or longer, which would be difficult to distinguish from those of totally stationary stars.

The team concluded that more astronomers should revisit the historical classifications of stars, especially as technology advances and more space-based telescopes become available. This strategy would allow future researchers to draw better data from research archives and catalogs. Additionally, they claimed that their method of pairing long-term monitoring via small satellites with TESS data is well-suited for refining classifications, identifying misclassified objects, and further exploring the structure and mechanics of chemically peculiar stars.

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