It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Tuesday, October 03, 2023
Model of photosynthetic antenna suggests different types of plants may grow on Earth-like rocky planets
by Bob Yirka , Phys.org
A schematic diagram of the concept of a dual-input noise-canceling antenna. Two sub-populations of pigments with similar (but different) absorption maxima funnel energy to the reaction center (RC) which oxidizes an electron donor and reduces an acceptor. The two absorbing populations tend to operate in series (e.g., Chl b transferring energy to Chl a in plant antenna complexes) and are subject to both external and internal noise. The former reflects the highly dynamic nature of the light-environment while the latter results from fluctuations of the energy transfer pathways within the antenna. Credit: Monthly Notices of the Royal Astronomical Society (2023). DOI: 10.1093/mnras/stad2823
A small team of biologists, environmental scientists and chemists at Queen Mary University of London, U.K., has found via modeling, that it might be possible for different types of plants to grow on Earth-like rocky planets. In their paper published in Monthly Notices of the Royal Astronomical Society, the group describes how they modeled photosynthetic antenna, taking into account possible scenarios on planets in other star systems and the results of their experiments.
As scientists continue to consider the possibility of life existing somewhere other than Earth, they attempt to expand the possible scenarios under which life might exist. After all, the likelihood of life only existing on exoplanets that are nearly identical to Earth would seem to seriously limit the possibilities. In this new effort, the research team looked at the basic machinery involved in photosynthesis here on Earth and at possible changes to such a process that might allow different types of plants to grow on other worlds.
To create a model of photosynthesis that might include extraterrestrial plants, the researchers looked most specifically at photosynthetic antenna—the parts of a plant that are actively involved in harvesting light. On Earth, such antennae work only on light in the range from 400 nm to 700 nm.
They noted also that to date most goldilocks-zone exoplanets that have been observed circle red dwarfs, which emit light in wavelengths beyond 700 nm. That means that plants that process such light would need to be extremely efficient, and because of that, they likely would not be able to evolve beyond very basic structures. But the possibility exists for photosynthetic antenna that could work with gases other than oxygen, such as sulfur.
Under such scenarios, the plants using them would not be green—they might be purple, for example, or orange or red. It would depend on which wavelength of light they were using as their energy source. Such plants, they claim, would likely still need to extract nutrients from whatever type of soil they were growing on, though the types would be different from those on Earth.
The researchers suggest their model shows that the basic mechanics of photosynthetic antennae does allow for processing wavelengths of light in the ranges that shine on exoplanets that have already been observed—which means that new ways of studying them might be needed to detect the plants living on them.
More information: Christopher D P Duffy et al, Photosynthesis Under a Red Sun: Predicting the absorption characteristics of an extraterrestrial light-harvesting antenna, Monthly Notices of the Royal Astronomical Society (2023). DOI: 10.1093/mnras/stad2823
Because names are among the first things you learn about someone, they can influence first impressions.
That this is particularly true for names associated with Black people came to light in 2004 with the release of a study that found employers seeing identical resumes were 50% more likely to call back an applicant with stereotypical white names like Emily or Greg versus applicants with names like Jamal or Lakisha.
To conduct this study, we recruited 1,500 people from all 50 U.S. states in 2022 to participate in an online experiment on Prolific, a survey platform. The group was nationally representative in terms of race and ethnicity, age and gender.
We first collected data on their beliefs about the race and ethnicity, education, productivity and personality traits of people with six names picked from a pool of 2,400 workers whom we hired in an early stage of our experiment for a transcription task. Data from these individual responses made it possible for us to categorize how they perceived the candidates.
We found that the names of workers perceived as Black, such as Shanice or Terell, were more likely to elicit negative presumptions, such as being less educated, productive, trustworthy and reliable, than people with either white-sounding names, such as Melanie or Adam, or racially ambiguous names, such as Krystal or Jackson.
We were specifically studying discrimination against Black people, so we did not include names in this experiment that are frequently associated with Hispanics or Asians.
Participants were next presented with pairs of names and were told they could earn money for selecting the worker who was more productive in the transcription task. The chance that they would choose job candidates they perceived to be white because of their names was almost twice as high than if they thought the candidates to be Black. This tendency to discriminate against people with Black-sounding names was greatest among men, people over 55, whites and conservatives.
Educational attainment, the level of racial diversity in the participants' ZIP codes or whether they had personally hired anyone before didn't influence their apparent biases.
Rushing can cause more discriminatory behavior
Most real-world hiring managers spend less than 10 seconds reviewing each resume during the initial screening stage. To keep up that swift pace, they may resort to using mental shortcuts—including racial stereotypes—to assess job applications.
We found that requiring the study participants to select a worker within only 2 seconds led them to be 25% more likely to discriminate against candidates with names they perceived as Black-sounding. Similar patterns of biased decision-making under time pressure have been documented in the context of police shootings and medical decisions.
However, making decisions more slowly is not a panacea.
We found that the most important factor for whether more deliberate decisions reduce discrimination was a participant's view on affirmative action—the consideration of race in a workforce or student body to ensure that their share of people of color is roughly proportionate to the general public or a local community.
White participants who opposed affirmative action were more than twice as likely to select an applicant with a white-sounding name compared with applicants perceived as Black—whether or not they had to make the simulated hiring decision in a hurry.
By contrast, giving white participants who favor affirmative action unlimited time to choose a name from the hiring list reduced discrimination against the job candidates with names they perceived as Black-sounding by almost half. The data showed that this decline had to do with people basing their decision more on their perceptions of a worker's performance, rather than relying on mental shortcuts based on their perceived race.
We assessed the participants' views on affirmative action by doing a survey at the end of this experiment.
Discrimination hasn't gone away
A study published in 2021 suggested that hiring discrimination based on Black-souding names had declined, although discriminatory practices remained high in some customer-facing lines of work, such as auto sales or retail.
There is ample evidence that people of color face discrimination in many important domains beyond employment, including finding housing or obtaining loans.
Our results suggest that slowing down the initial assessment of applicants can be a first step toward reducing this type of discrimination.
The 2022 Global Gender Gap Report showed Asian countries have managed to narrow the gender gap in economic, education and health sectors. But when it comes to political participation, the gap persists.
Studies about representation of women in modern diplomacy also assert that in general, Asian women continue to be the minority in this field, with very low percentage.
Despite some progress and efforts to achieve gender parity, Asian women are still in constant conflict with cultural dynamics that hamper their advancement in foreign affairs.
Here's how we fix it.
Women are not represented
As of 2023, the global share of women serving as cabinet ministers globally is just 22.8%, according to the the Inter-Parliamentary Union. Asian countries (Central and Southern Asia) rank the second lowest of the world regions or at 10.1%.
Most of the women (84%) in the cabinet ministers in Asia are assigned in ministries or institutions related to women's issues, gender equality and children. Meanwhile, the number of women serving in traditionally male-dominated fields, such as defense, energy and transportation, remains small—less than 12%.
Globally, out of 193 countries, the portion of women who serve in ministerial positions at the ministries of foreign affairs is only around 20%.
In Asia, the proportion of women as ambassadors and permanent representatives in United Nations (UN) organizations is just 12%, far less than the global average of 20.54%. The Maldives has the greatest ratio of female ambassadors among Asian countries—at 50%, while Cambodia with 25% share is the lowest in Asia.
Right now, only 17 Asian nations that currently have ever had female foreign ministers. In Southeast Asia, it is only Philippines, Timor Leste, Myanmar and Indonesia.
During President Joko "Jokowi" Widodo term, Indonesian female ambassadors made up 13.46% from the total 95 embassies and three permanent missions, that is higher than the previous administration which stood at 9.55%.
The challenges
There are three challenges behind the low representation of women in Asian foreign affairs.
First, the dearth of representation of women in international affairs is inextricably linked to the notion in most Asian nations that males still dominate this field. Historically, diplomacy has been a male-dominated domain with very few provisions for women.
Third, female diplomats are also affected more disproportionately because they carry double burden in balancing work and personal life.
While they hold public positions, most of them still carry domestic responsibilities. It is still more difficult for women, compared to men, to deal with frequent job rotations, long working hours and placements abroad.
Promoting gender-responsive policies
Research has shown that if women achieved critical mass –somewhere between 20-30%—within an organization they can wield power and influence in public life and the workforce.
But it is not enough to only ensure women receive fair representation in organizations. After achieving critical mass, the next step is to include a gender perspective in foreign policy approaches, formulation and implementation.
Indonesia, for example, has issued a ministerial regulation that facilitates gender-related concerns in ministries, including facilities for female employees.
Other Asian countries are also beginning to implement gender-responsive foreign policy. Several Asian countries have developed National Action Plans on women, peace and security. These include Indonesia (2014), the Philippines (2010 and 2017), South Korea (2014) and Timor Leste (2016).
Sending more female ambassadors to regional and global forums is another way for achieving gender balance and equality.
Efforts have been started but much more is needed. All stakeholders must keep echoing the necessity of gender equality in the work place through better and wider attempts to normalize gender equality in foreign policy institutions.
Graphical abstract . Credit: Journal of Chemical Information and Modeling (2023). DOI: 10.1021/acs.jcim.3c01239
Boosting virtual screening with machine learning allowed for a 10-fold time reduction in the processing of 1.56 billion drug-like molecules. Researchers from the University of Eastern Finland teamed up with industry and supercomputers to carry out one of the world's largest virtual drug screens.
In their efforts to find novel drug molecules, researchers often rely on fast computer-aided screening of large compound libraries to identify agents that can block a drug target. Such a target can, for instance, be an enzyme that enables a bacterium to withstand antibiotics or a virus to infect its host. The size of these collections of small organic molecules has seen a massive surge over the past years.
With libraries growing faster than the speed of the computers needed to process them, the screening of a modern billion-scale compound library against only a single drug target can take several months or years—even when using state-of-the-art supercomputers. Therefore, quite evidently, faster approaches are desperately needed.
In a study published in the Journal of Chemical Information and Modeling, Dr. Ina Pöhner and colleagues from the University of Eastern Finland's School of Pharmacy teamed up with the host organization of Finland's powerful supercomputers, CSC—IT Center for Science Ltd—and industrial collaborators from Orion Pharma to study the prospect of machine learning in the speed-up of giga-scale virtual screens.
Before applying artificial intelligence to accelerate the screening, the researchers first established a baseline: In a virtual screening campaign of unprecedented size, 1.56 billion drug-like molecules were evaluated against two pharmacologically relevant targets over almost six months with the help of the supercomputers Mahti and Puhti, and molecular docking. Docking is a computational technique that fits the small molecules into a binding region of the target and computes a "docking score" to express how well they fit. This way, docking scores were first determined for all 1.56 billion molecules.
Next, the results were compared to a machine learning-boosted screen using HASTEN, a tool developed by Dr. Tuomo Kalliokoski from Orion Pharma, a co-author of the study.
"HASTEN uses machine learning to learn the properties of molecules and how those properties affect how well the compounds score. When presented with enough examples drawn from conventional docking, the machine learning model can predict docking scores for other compounds in the library much faster than the brute-force docking approach," Kalliokoski explains.
Indeed, with only 1% of the whole library docked and used as training data, the tool correctly identified 90% of the best-scoring compounds within less than 10 days.
The study represented the first rigorous comparison of a machine learning-boosted docking tool with a conventional docking baseline on the giga-scale. "We found the machine learning-boosted tool to reliably and repeatedly reproduce the majority of the top-scoring compounds identified by conventional docking in a significantly shortened time frame," Pöhner says.
"This project is an excellent example of collaboration between academia and industry, and how CSC can offer one of the best computational resources in the world. By combining our ideas, resources and technology, it was possible to reach our ambitious goals," said Professor Antti Poso, who leads the computational drug discovery group within the University of Eastern Finland's DrugTech Research Community.
Studies on a comparable scale remain elusive in most settings. Thus, the authors released large datasets generated as part of the study into the public domain. Their ready-to-use screening library for docking enables others to speed up their respective screening efforts, with 1.56 billion compound-docking results for two targets that can be used as benchmarking data.
This data will encourage the future development of tools to save time and resources and will ultimately advance the field of computational drug discovery.
More information: Toni Sivula et al, Machine Learning-Boosted Docking Enables the Efficient Structure-Based Virtual Screening of Giga-Scale Enumerated Chemical Libraries, Journal of Chemical Information and Modeling (2023). DOI: 10.1021/acs.jcim.3c01239
The UK Met Office Hadley Centre, introduces an innovative data product, HadISDH.extremes, offering invaluable insights into temperature extremes and their humidity characteristics. This globally gridded monitoring product covers the period from January 1973 to December 2022. The findings, along with the dataset description, are published in Advances in Atmospheric Sciences.
Dr. Kate Willett, who led this research, explains, "HadISDH.extremes is an annually updated product designed to monitor and analyze heat extremes worldwide. Our dataset places a strong emphasis on data quality and stability for reliable insights. We've used quality-controlled hourly data from weather stations and introduced a unique approach to minimize inhomogeneity at the monthly level. This approach balances temporal stability with spatial coverage to provide a globally consistent product."
One of the standout features of HadISDH.extremes is its provision of both wet and dry bulb extremes indices. This unique capability allows researchers and scientists to distinguish between various types of heat events, which may be hot and dry, hot and humid or warm and very humid. It is particularly valuable for the study of long-term trends in regional climate features.
Additionally, HadISDH.extremes allows exploration of what Dr. Willett refers to as "stealth heat events." These events are characterized by high humidity levels, which can impact productivity and health, even when the temperature remains moderate. Such events may not be traditionally identified as "heat events" by temperature-focused indices.
Over the study period from 1973 to 2022, HadISDH.extremes uncovers significant trends in humid and dry heat extremes. The dataset contributes to the understanding of exposure to different types of heat events and underscores the importance of considering both temperature and humidity in climate studies.
More information: Kate M. Willett, HadISDH.extremes Part I: A Gridded Wet Bulb Temperature Extremes Index Product for Climate Monitoring, Advances in Atmospheric Sciences (2023). DOI: 10.1007/s00376-023-2347-8
Kate M. Willett, HadlSDH•extremes Part II: Exploring Humid Heat Extremes Using Wet Bulb Temperature Indices, Advances in Atmospheric Sciences (2023). DOI: 10.1007/s00376-023-2348-7
In the realm of air quality forecasting, the precision of predictions largely hinges on the accuracy of emission inventory data. Traditional methods, which often update only once a year or less, face challenges in keeping pace with the dynamic nature of air pollutant emissions. This issue is particularly significant in China, where rapid changes in atmospheric pollutants demand a more agile approach.
Addressing this challenge, a recent study by the Institute of Atmospheric Physics, published in Environmental Science & Technology Letters and featured as a supplementary cover of the journal, has proposed an innovative emission update scheme tailored for air quality forecasting.
According to the first author Dr. Huangjian Wu, the strength in the new approach lies in that, in contrast to conventional methodologies, the new approach significantly reduces computational demands by an impressive 84%, making ensemble-based emission inversion cost-effective and practical for operational air quality forecasting.
Co-author Prof. Xiao Tang explained the essence of the approach, "Our methodology builds upon the ChemDAS data assimilation system and takes a significant step forward by decoupling ensemble simulations and forecasts required for emission inversion. This enables the daily estimation of emissions for major pollutants in urban areas."
This is echoed by Dr. Lei Kong, another contributor to the study, "Our technique estimates emissions for key pollutants like CO, SO2, NOx, VOCs, and PM2.5 and PM10 precursors by assimilating observed concentrations of CO, SO2, NO2, O3, PM2.5, and PM10, respectively."
The innovative method has already been successfully implemented at the China National Environmental Monitoring Centre (CNEMC), where it facilitates online inversion and updates of emission inventories for operational forecasting. "Our approach not only enhances forecast accuracy but also enables timely assessments of changes in atmospheric pollutant emissions," emphasized Prof. Zifa Wang, the corresponding author of the study.
In testing conducted between January and February 2022, the new method led to a notable 7.1% reduction in root mean square errors in 7-day PM2.5 forecasts and significantly improved predictions for pollutants like O3. Moreover, the updated emission data revealed significant reductions in nitrogen oxide emissions during the 2022 Beijing Winter Olympics, with Beijing experiencing a 53.5% reduction, Zhangjiakou a 42.7% reduction, and Hebei Province a 48.6% reduction.
This approach could advance air quality forecasting by providing timely, accurate, and cost-effective emission updates, contributing to the goal of healthier air for all.
More information: Huangjian Wu et al, Air Quality Forecasting with Inversely Updated Emissions for China, Environmental Science & Technology Letters (2023). DOI: 10.1021/acs.estlett.3c00266
by Ben Langford, James Ryalls and Robbie Girling, The Conversation
Honeybee (Apis mellifera) landing on a milk thistle flower (Silybum marianum). Credit: Fir0002/Flagstaffotos/ Wikipedia/GFDL v1.2
Whether you love them or loathe them, we all depend on bugs. Insects help to pollinate three-quarters of the world's crop varieties, making them a treasured resource.
But we're making the lives of insects tough—and not just by swatting them away with a newspaper. Insect populations worldwide are in sharp decline as they battle against climate change, habitat loss and pesticides.
Now, we can add air pollution to the list of threats. Our research from 2022 revealed that when exposed to two common air pollutants at concentrations within EU air quality limits, the visits of pollinating insects to flowers plummeted by as much as 90%.
Over a span of two years, we artificially elevated the levels of either ozone or diesel exhaust fumes around plots of flowering black mustard plants, all within fields of non-flowering wheat. We carefully monitored and controlled the release of pollutants using rings constructed around each plot.
This method allowed us to monitor the number of pollinating insects visiting the flowers in polluted plots and draw comparisons with plots devoid of pollutants.
We were surprised by what we found. In the rings where we released ozone or diesel exhaust fumes, the number of pollinating insects decreased by 70% and overall pollination success rates decreased by up to 31%.
It wasn't just bees and butterflies that were affected. Ground-dwelling insects suffered too, with exposure to these pollutants causing their numbers to decrease by as much as 36%.
Like Pavlov’s dogs, bees can be trained to respond to a dinner bell – or in their case, the scent of a flower.
Why air pollution makes life so hard
Many insects rely on their sense of smell to locate flowers. When they feed on nectar, they quickly connect the flower's scent with its sugary reward. Consequently, when they come across the same scent later on, they track its trail in pursuit of another tasty treat.
Thus, flowers serve a dual purpose. They are not just pretty to look at but also function as beacons that release a specific blend of fragrant chemicals designed to attract pollinators.
But these signals are under threat. Air pollutants like ozone are highly reactive and can degrade the signals by destroying the chemicals that make up a flower's scent.
In our more recent research, we simulated a floral scent in a 20-meter long wind tunnel and then mapped out how the levels of each of the chemicals that made up the scent changed in response to increasing ozone pollution. We found that ozone quickly ate away at the edges of the plume, reducing both its width and length.
Essentially, the chemical signal could travel only a shorter distance, which limited the number of insects it could reach.
Adding ozone also changes the smell of each of the chemicals that make up a flower's scent. By observing these changes in a wind tunnel, we could measure the speed at which these chemical changes occur.
Some chemicals degraded within seconds, whereas others were not affected at all. How far away you are from the scent's source appears to change how the scent smells.
Pavlov's Bees
To understand how changes to the floral scent might affect pollinators, we taught honeybees to recognize the same floral scent that we released into the wind tunnel. Much like Pavlov's dogs drooling at the sound of a dinner bell, bees stick out their proboscis (tube-like tongue) when they sniff an odor they have learned to associate with a sugary reward. This allowed us to see how many bees could still recognize the floral scent once it had been exposed to ozone pollution.
We first tested the honeybees with scent blends replicating those observed at the plume center when ozone levels were elevated. At a distance of six meters from the flower, 52% of bees recognized the scent. This fell to only 38% at a distance of 12 meters.
We then tested the response of honeybees to the more degraded plume edges. Only 32% of the bees responded at six meters, falling to just 10% at 12 meters.
These results help to explain the significant decline in the number and diversity of insect visits and pollination rates observed in our field trials. Put simply, ozone pollution limits the reach of chemical signals and changes their meaning, leaving insects confused.
But this is unlikely to be the full story. Although we replicated the effects of ozone pollution on floral scents, we never exposed the bees directly to ozone. Separate research carried out in France suggests that direct exposure to ozone might also impair the ability of bees to detect floral scents.
The full extent to which air pollution is impacting the insects we all depend on is only just beginning to be revealed. So, the next time you lift your newspaper to swat a bug, take a second and ask yourself—don't they have it tough enough already?
Climate change has made extreme weather events more frequent and intense worldwide. Some examples of climate-related disasters in recent years include the serious flooding in Venice, Italy in 2019, the terrible heat waves and wildfires in Australia in 2020, and the widespread flooding in Central Europe in 2021.
Although our understanding of climate extremes and their impacts continues to improve, events that overwhelm the coping capacity of social and environmental systems often take us by surprise. This is partly because current climate and impact modeling efforts are very limited in their ability to model compound events, making it difficult to plan for appropriate ways to adapt.
The COST Action Understanding and modeling compound climate and weather events (DAMOCLES) has succeeded in changing this situation. The Action has raised awareness of the importance of compound events and their impacts across different scientific fields. A recent study based on work from COST Action DAMOCLES has been published in iScience.
It has also created a new community bringing together experts in climate science, climate impact research, hydrology, and statistics. Bart van den Hurk of Deltares Institute, NL, and the vice-Chair of the Action, talks about the successes and challenges of DAMOCLES.
What are compound events?
Many major hydrometeorological disasters are often the result of compound events. These extreme events have a complex structure because they are caused by several factors or have multiple effects. For example, a coastal flood may become extreme due to a combination of a strong storm surge and heavy rainfall in the coastal area. A better understanding of these events can improve early warning, help design more effective defense infrastructure, and provide valuable information about the risks people face.
High-impact compound events come in many forms, such as droughts, heat waves, wildfires, and air pollution, where interactions between temperature, humidity, and precipitation play an important role. In addition, interactions between extreme precipitation, river discharge, and storm surge link coastal storm processes with fluvial/pluvial and ocean dynamics. Clustering of major storm events resulting in spatial and/or temporal dependence, is another example.
A notable example of a compound event occurred in Portugal in October 2017. Wildfires ravaged nearly 200,000 hectares of land in just 24 hours, resulting in 50 deaths. Several compounding factors contributed to this disaster, including long-term vegetation stress, the influence of Hurricane Ophelia, which brought hot and dry air masses to the region, and human negligence related to agricultural practices.
Another example is Russia in 2010, where a lack of rainfall combined with an atmospheric blocking event over western Russia led to an exceptionally hot and dry summer. This, in turn, led to widespread wildfires and air pollution, resulting in over 50,000 deaths, and destroying a quarter of Russia's crops.
Practical applications of DAMOCLES
When DAMOCLES started, the idea of compound weather and climate events was new and not widely understood. Only a few specialists, mostly coastal hydrologists, had expert knowledge of the underlying principles. DAMOCLES has played a crucial role in creating a framework for defining and managing compound events. It has also focused on showing how this framework can be applied in practice.
Van den Hurk, the vice-Chair of DAMOCLES, shared his personal experience with a client who was faced with a flood caused by a combination of different flooding factors. The client wanted to ensure that their analysis of the event would provide accurate inputs for the associated quantitative risk assessment associated with it. By demonstrating the physical connection between the various drivers, DAMOCLES enabled the client to adjust the risk calculations. This adjustment helped the client make an informed decision to invest in flood infrastructure, albeit a costly investment.
DAMOCLES success and impact
The Action has been very successful in defining and analyzing compound weather and climate events and has created a new category of specialists in this field. It has achieved very high visibility in the research community. DAMOCLES has published highly influential research papers that are expected to shape our thinking about compound events for years to come.
DAMOCLES scientific results are a key reference for studying and assessing compound events and associated risks that pose the most serious challenges to modern society from ongoing climate changes.
Van den Hurk states, "One of the major achievements of DAMOCLES has been the development of a typology for categorizing compound events. This typology helped to structure the extreme diversity of different event types, leading to improved methods for understanding compound events. The original paper presenting the typology, titled 'A typology of compound weather and climate events' was published in Nature Reviews Earth & Environment in 2020. It has already been cited more than 400 times according to Google Scholar.
"The typology has been used as a basis for follow-up activities of DAMOCLES, to provide Guidelines for Studying Diverse Types of Compound Weather and Climate Events and to link compound event thinking to the disaster risk reduction cycle (Consideration of compound drivers and impacts in the disaster risk reduction cycle).
"Another excellent outcome has been the inclusion of compound events in The Intergovernmental Panel on Climate Change IPCC. As the preeminent authority on climate change, the IPCC synthesizes the latest knowledge in the field and serves diverse audiences including policy makers, NGOs, scientists, industry, and the general public.
"These scientific findings are, and will continue to be, a key reference for studying and assessing compound events and associated risks that pose the most serious challenges to modern society from ongoing climate changes," concludes Van den Hurk.
More information: Bart J.J.M. van den Hurk et al, Consideration of compound drivers and impacts in the disaster risk reduction cycle, iScience (2023). DOI: 10.1016/j.isci.2023.106030
