Tyler O'Neal, Staff Editor SCIENCE

Modeling by UMass Amherst researcher demonstrates strategy is a win-win for combating climate change

Carbon markets have become a critical policy tool to combat climate change. They allow firms that emit greenhouse gases to buy and sell the right to pollute, which gives the firms flexibility while also reducing carbon emissions at the lowest cost. A patchwork of dozens of markets exists around the world, often with drastically different prices for carbon credits. In a new paper, a University of Massachusetts Amherst resource economist demonstrates that linking fragmented carbon markets with an exchange rate has the potential to be a significant step toward forming a global climate policy.

Matt Woerman, assistant professor of resource economics at UMass Amherst, explores linking carbon markets using an allowance exchange rate, which denominates the compliance value of an emissions allowance differently in each program. Using simulation modeling, he finds that while an exchange rate may reduce emissions abatement in certain programs, it achieves greater emissions reductions and cost efficiencies overall. Matt Woerman, assistant professor of resource economics

“Climate change is a global problem,” Woerman says. “Linking carbon markets with an allowance exchange rate is a great step toward a larger global climate policy that we need to solve climate change.”

The modeling indicates that an exchange rate among linked carbon markets in various regions would move prices closer together and reduce pollution.

“This suggests that both regions would win, and the environment wins,” Woerman says.

One potential downside of linking carbon markets is that each participating jurisdiction would give up a small amount of its sovereignty, but Woerman’s research finds that the exchange rate would act as a cushion of sorts.

“It’s this extra lever that allows policymakers to still retain some of that sovereignty and not force everything to be equal across the linked markets,” he notes.

Woerman hopes the findings can be used to build political momentum toward forming larger coalitions to trade carbon credits.

“The next step is to think about how this work fits into a more dynamic framework in the longer run, particularly how we can use the allowance exchange rate perhaps as a first step toward a global market,” Woerman says.

The paper is based on a previous manuscript coauthored by Dallas Burtraw and Karen Palmer of Resources for the Future and Clayton Munnings, a U.S. strategic advisor for the International Emissions Trading Association. The research was supported by Mistra Carbon Exit and the nonprofit research institution Resources for the Future Electric Power Program.

The paper appears in the Journal of Environmental Economics and Management and is available at https://www.sciencedirect.com/science/article/pii/S0095069623000384.

China's Institute of Oceanology uses deep learning for global estimation of phytoplankton pigment concentrations

Tyler O'Neal, Staff Editor SCIENCE

The phytoplankton community structure can reflect changes in the marine environment and help us understand the driving factors behind ecological evolution. The quantifying pigment concentration in phytoplankton is crucial for a comprehensive assessment of taxonomic classification and community structure.

Recently, a research team led by Prof. LI Xiaofeng from the Institute of Oceanology of the Chinese Academy of Sciences (IOCAS) has made progress in the inversion of global phytoplankton pigment concentrations using deep learning algorithms. Using satellite data, they developed a deep-learning-based model (DL-PPCE model) for estimating concentrations of 17 different phytoplankton pigments globally.

The study was published in Remote Sensing of Environment on May 19.

The model inputs include ocean color parameters, satellite-derived environmental parameters, and the slope of above-surface remote-sensing reflectance. The model was validated against high-performance liquid chromatography (HPLC) data and was advantageous for analyzing the phytoplankton community dynamics on a large spatiotemporal scale.

Using the established DL-PPCE model, the researchers conducted a time series analysis of global pigment concentrations retrieved by Moderate-resolution Imaging Spectroradiometer (MODIS) during the period of 2003-2021. They found that the prokaryotes-dominated area extended eastward from180°E to 150°W during the 2015/2016 El Nino event. From 2003 to 2021, prokaryotic abundance was positively correlated with El Nino intensity but negatively correlated with the quantity of the entire phytoplankton community.

Ocean color remote sensing enables the retrieval of phytoplankton absorption, which is directly linked to pigment concentration. "However, the simultaneous retrieval of multiple pigment concentrations globally is challenging due to optical property variability in seawater and the packaging effect on phytoplankton absorption," said LI Xiaolong, the first author of the study.

"In our study, we employ a novel approach to estimate global phytoplankton pigment concentrations," said Prof. LI, corresponding author of the study. "By avoiding assumptions about pigment absorption spectra and employing deep learning, we established non-linear relationships between remote sensing variables and phytoplankton pigment concentrations. This approach yielded high accuracy in estimating pigment concentrations."

Breakthrough Listen / Danielle Futselaar An artist's conception of an alien device that generates repetitive signals.
Breakthrough Listen / Danielle Futselaar An artist's conception of an alien device that generates repetitive signals.

Cornell develops software based on a FFA that offers new way to listen for signals from the stars

Tyler O'Neal, Staff Editor SCIENCE

The Breakthrough Listen Investigation for Periodic Spectral Signals (BLIPSS), led by Akshay Suresh, Cornell doctoral candidate in astronomy, is pioneering a search for periodic signals emanating from the core of our galaxy, the Milky Way. The research aims to detect repetitive patterns, a way to search for extraterrestrial intelligence (SETI) within our cosmic neighborhood. 

The researchers developed software based on a Fast Folding Algorithm (FFA), an efficient search method offering enhanced sensitivity to periodic sequences of narrow pulses. Their paper, “A 4–8 GHz Galactic Center Search for Periodic Technosignatures,” was published May 30 in The Astronomical Journal.

Pulsars -- rapidly rotating neutron stars that sweep beams of radio energy across the Earth -- are natural astrophysical objects that generate periodic signals but humans also use directed periodic transmissions for a variety of applications, including radar. Such signals would be a good way to get someone’s attention across interstellar space, standing out from the background of non-periodic signals, as well as using much less energy than a transmitter that is broadcasting continuously.

“BLIPSS is an example of cutting-edge software as a science multiplier for SETI,” said Suresh. “Our study introduces to SETI, for the first time, the Fast Folding Algorithm; our open-source software utilizes an FFA to crunch over 1.5 million time series for periodic signals in roughly 30 minutes.”

BLIPSS is a collaborative effort between Cornell, the SETI Institute, and Breakthrough Listen. The project significantly enhances the probability of capturing evidence of extraterrestrial technology by focusing on the central region of the Milky Way, known for its dense concentration of stars and potentially habitable exoplanets. The center of the Milky Way would also be an ideal place for aliens to place a beacon to contact large swaths of the Galaxy.

The team tested their algorithm on known pulsars and were able to detect periodic emissions1. Use simpler language: While the text is informative and technical, some of the language used may be difficult for the average reader to understand. To improve the effectiveness of the writing, it may be helpful to use simpler language to explain concepts and avoid jargon.

2. Provide more context: While the text provides some context, it may be helpful to provide more information on the significance of the research and its potential implications for the field of astronomy and the search for extraterrestrial life.

3. Include visuals: To make the text more engaging and easier to understand, it may be helpful to include visuals such as diagrams or illustrations to explain the concepts being discussed. This can help readers better understand the research and its potential implications. as expected. They then turned to a larger dataset of scans of the Galactic Center undertaken using the Breakthrough Listen instrument on the 100-meter Green Bank Telescope (GBT) in West Virginia. In contrast to pulsars, which emit across a wide swath of radio frequencies, BLIPSS looked for repeating signals in a narrower range of frequencies, covering less than one-tenth of the width of an average FM radio station.

“The combination of these relatively narrow bandwidths with periodic patterns could be indicative of deliberate technological activities of intelligent civilizations,” said co-author Steve Croft, Breakthrough Listen project scientist. “Breakthrough Listen captures huge volumes of data, and Akshay’s technique provides a new method to help us search that haystack for needles that could provide tantalizing evidence of advanced extraterrestrial life forms.”

“Until now, radio SETI has primarily dedicated its efforts to the search for continuous signals,” said co-author Vishal Gajjar, a SETI Institute astronomer. “Our study sheds light on the remarkable energy efficiency of a train of pulses as a means of interstellar communication across vast distances. Notably, this study marks the first-ever comprehensive endeavor to conduct in-depth searches for these signals.”