Special insecticide paint may help curb zika and dengue fever outbreaks

Scientists showed that insecticide paint could effectively decrease mosquito presence in Cabo Verde (Cape Verde) for up to one year, making this paint a potential strategy to decrease the transmission of vector-borne diseases.

Peer-Reviewed Publication

FRONTIERS

 

IMAGE: 

VOLUNTEERS WERE TRAINED TO PAINT HOUSES WITH INSECTICIDE PAINT IN TWO PRAIA NEIGHBORHOODS. 

view more 

CREDIT: IMAGE: COMMUNICATION AND INFORMATION OFFICE OF THE UNIVERSIDADE JEAN PIAGET OF CABO VERDE

Malaria and other illnesses caused by parasites, viruses, and bacteria transmitted by organisms that spread infectious pathogens account for more than 17% of all infectious diseases worldwide. These vector-borne diseases, typically transmitted by insects like mosquitoes, flies, and ticks, disproportionally affect the poorest populations in tropical and subtropical regions.

In Cabo Verde, an island nation off west Africa, vector-borne disease has been prevalent for centuries, in part due to the island’s geographical location and climate. Now, researchers in Cabo Verde and Spain set out to test the efficacy of three insecticide paint formulations to reinforce the existing national program aiming to minimize the occurrence of disease outbreaks. The results have been published in Frontiers in Tropical Diseases.

“Here we show that VESTA insecticide paint is effective at killing Aedes aegypti, the yellow fever mosquito, in the city of Praia for at least one year,” said lead author Dr Lara Ferrero Gómez, who coordinates a research group on tropical diseases at the Jean Piaget University of Cabo Verde. “We also found it has good acceptance in the population, with 98% confirming the decrease in mosquitoes in their residences after paint application.”

Mosquito control for up to a year

In a large-scale field trial, trained volunteers painted 228 houses in two Praia neighborhoods that are particularly vulnerable to diseases transmitted by mosquitoes. This is due to insufficient drainage which leads to flooding in the rainy season and poor wastewater management. Additionally, many residences in Cabo Verde store water due to insufficient and disrupted water supply, and water storage is often unsafe.

After one, three, six, and 12 months, WHO cone bioassays were conducted at two randomly selected houses in each neighborhood. “Bioassays record the mortality of A. aegypti mosquitoes after exposing them for half an hour to the insecticidal paint. This allows us to directly evaluate the effectiveness of the insecticidal paint,” Ferrero Gómez explained.

All three insecticide paint mixtures lead to complete mortality of A. aegypti mosquitoes one month after the houses were painted. Three months after painting, all formulations still exceeded the WHO efficiency threshold, which lies at 80%. At month six, two formulations fell below this threshold. The VESTA formulation, however, also met WHO requirements at months six and 12. “The paint works by releasing very small quantities of insecticide over a long period, which makes it more sustainable and eco-friendlier,” Ferrero Gómez pointed out.

The researchers did not register any serious effects of the paint on residents’ health. Adverse effects reported by few residents included mild eye or nose irritation (10%) and headache (4%).

Malaria free – what’s next?

At the beginning of the year, Cabo Verde was the third country in Africa to be declared free of Malaria by the WHO. The challenge to stop its reoccurrence, however, remains. The researchers said that insecticidal paint is also a promising strategy to strengthen the prevention and control of malaria cases at a household level since insecticide paint is effective for any type of vector disease transmitted by mosquitos, not just zika and dengue fever.

While the researchers face certain limitations, such as the need to meticulously apply the paint in two layers to ensure it does not lose its effectiveness, the TINTAEDES project is expected to extend to more locations across Praia, which is a hotspot for vector-borne diseases, as well as across all of Cabo Verde.

Dr Lara Ferrero Gómez coordinates a research group on tropical diseases at the Jean Piaget University of Cabo Verde. 

CREDIT

Image: Communication and Information Office of the Universidade Jean Piaget of Cabo Verde

JOURNAL

Frontiers in Tropical Diseases

DOI

10.3389/fitd.2024.1321687 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Insecticide paints, a new community strategy for controlling dengue and zika mosquito vectors in Cabo Verde

ARTICLE PUBLICATION DATE

5-Mar-2024

COI STATEMENT

Author IGT is employed by Inesfly Corporation S.L., a manufacturer of vector control products. Authors JCF, LVS and JTR are employed by SITA S.A., the distributor of these products in Cabo Verde. All authors declare no other competing interests.

 

Audit of food donations prompts call for new nutrition and safety standards

Peer-Reviewed Publication

CURTIN UNIVERSITY

 

IMAGE: 

A LOAD OF DRINKS DONATED TO FOODBANK.

view more 

CREDIT: CURTIN UNIVERSITY

New Curtin University research that analysed a whopping 85,000 kilograms of food donated to Foodbank WA over five days has prompted calls for an overhaul of laws and policies to ensure safe and nutritious food is available for its vulnerable clients. 

Lead author PhD student Sharonna Mossenson from the Curtin School of Population Health said of the 1222 items of surplus or unsalable food donated, 96 per cent met food safety standards, while four per cent were not safe for human consumption and were disposed of by Foodbank WA.

“Nutritionally poor sweet and savoury snacks were the main types of foods donated, and nutritious foods were the least commonly donated, with only six per cent of donated products being dairy foods, eight per cent being meat and 13 per cent being fruit and vegetables,” Ms Mossenson said.

“Supermarkets were responsible for 82 per cent of all sweet and savoury snacks donated and 90 per cent of soft drinks, while the type of food they donated least was fruit and vegetables.

“The Australian food relief sector plays a vital role in helping people experiencing severe food insecurity and given the health vulnerabilities of people accessing their services, these types of donations pose a health risk.

Ms Mossenson said the findings highlighted the need for donors, particularly supermarkets, to take action to improve the quality of food they donate.

“Supermarkets donated the most food overall, half of which was in small mixed loads from local supermarkets, which is a process that needs closer attention as most of the unsafe food (93 per cent) was in these mixed loads,” Ms Mossenson said.

“On average, 49 minutes was spent sorting and inspecting each load for damaged and unsafe products adding a significant burden on Foodbank WA and reducing efficiency in the system.

“While Foodbank WA has extensive processes in place to dispose of unsafe foods, the time it takes for staff and volunteers to unpack and check each donated item is substantial. Introducing explicit regulations requiring food donors to eliminate inappropriate foods before they are donated could free up Foodbank WA staff time so they can focus more on their clients.

“A food safety regulatory framework and fit-for-purpose nutrition guidelines for donated food in Australia are needed to ensure safe and healthy food is donated.”

Foodbank WA Chief Executive Officer Kate O’Hara said Foodbank WA relied on donations of surplus food across the food supply chain including from growers, manufacturers and retailers and the unknown nature of donations created challenges.

“We work closely with all our food donors including supermarkets to ensure quality nutritious food for Western Australians doing it tough,” Ms O’Hara said.

“Since this study in 2022, Foodbank WA continues to monitor its food donations and is taking a proactive approach to sourcing safe and nutritious food such as breads, breakfast cereals, tinned fruit and vegetables, dairy products and meat to support our clients to achieve a balanced diet.

“There are always improvements to be made across the entire food relief sector, particularly to ensure donations are made within a safe timeframe and appropriate refrigerated transportation and storage is utilised.”

The research papers, ‘The Nutritional Quality of Food Donated to a Western Australian food bank’ and ‘Evidence for initiating food safety policy: An assessment of the quality and safety of donated food at an Australian food bank’ were published in the journals Nutrients and Food Policy, respectively.  

---

JOURNAL

Nutrients

DOI

10.3390/nu16040509 

METHOD OF RESEARCH

Case study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

The Nutritional Quality of Food Donated to a Western Australian Food Bank

 

A consortium of algae and bacteria boosts the production of green hydrogen and biomass while cleaning water

Peer-Reviewed Publication

UNIVERSITY OF CÓRDOBA

 

IMAGE: 

RESEARCHERS WHO CARRIED OUT THE STUDY

view more 

CREDIT: UNIVERSITY OF CÓRDOBA

A consortium of algae and bacteria boosts the production of green hydrogen and biomass while cleaning water

The mutual relationship between an algae and three bacteria studied by a team at the University of Cordoba presents the highest hydrogen production obtained so far by this type of consortium

Hydrogen is set to become one of the fuels of the future, so researchers are striving to make it as sustainable and green as possible. Hydrogen production using algae and bacteria consortia is a strategy that averts the use of fossil fuels or the electrolysis of water using energy, which are the current ways this fuel is produced. Within this approach, guided by the principles of the Circular Economy, the question is: what is the most effective combination of algae and bacteria?

The BIO128 research group at the University of Córdoba has been looking for these relationships of mutualism where algae and bacteria benefit from their union, resulting in a combination of hydrogen and biomass production while cleaning the wastewater where they grow.

Now they have discovered the relationship between a combination of an algae and three bacteria that, when working together, are able to produce hydrogen and to grow together, producing biomass that can then be recovered and, at the same time, that cleans the wastewater in which they grow. This winning combination is composed of the Chlamydomonas reinhardtiialga model and the three bacteria Microbacterium forte sp. nov., Bacilluscereusand  Stenotrophomonas goyi sp. nov., and the production of hydrogen obtained is the highest reported for any combination of algae and bacteria.

The M. forte bacterium helps the Chlamydomonas alga generate hydrogen. With the inclusion of the other two bacteria in the combination, while hydrogen is generated, both the bacteria and the algae grow, thus producing the biomass, which can then be recovered as a fuel or energy source. "This consortium is better because it is more lasting; you can grow it and obtain hydrogen and biomass for a long time, unlike other consortia," explains researcher David González. "We also discovered that Microbacterium forte and Stenotrophomonas goyi need vitamins (biotin and thiamine) and reduced sources of sulfur to grow, and what Chlamydomonas surely does is provide them with those nutrients that bacteria need to grow." Thus, the bacteria benefit from the relationship with the alga to grow, offering it the CO2 and acetic acid that the alga requires to grow and produce hydrogen.

In this win-win relationship, water and the environment also win. These consortia are grown in wastewater, using that waste to grow and completing water bioremediation tasks. This specific consortium has been tested in synthetic wastewater mimicking lactic residues including, for example, lactose. As another author, Neda Fakhimi, points out, "our approach also harnesses the potential of using waste materials as a source of nutrients, thereby facilitating renewable and sustainable biohydrogen production. With the advantage that this consortium has a hydrogen production approximately ten times greater than that of the previous ones"

The result of accidental contamination in the laboratory

"This consortium came about thanks to a fortuitous contamination of a Chlamydomonas culture in the laboratory, which led to the discovery and sequencing of the genome of two new bacteria: Microbacterium forte and Stenotrophomonas goyi," says researcher Alexandra Dubini, also an author of the work. "We realized that the contaminated culture produced more hydrogen than those that were not, and from there we followed up and saw that there were three bacteria," continues David González.

Therefore, in addition to the progress in the search for biological and sustainable methods to produce green hydrogen, this work also yields the genomes of these two newly discovered bacteria.

References

Fakhimi N, Torres MJ, Fernández E, Galván A, Dubini A, González-Ballester D. Chlamydomonas reinhardtii and Microbacterium forte sp. nov., a mutualistic association that favors sustainable hydrogen production. Sci Total Environ. 2024 Feb 25;913:169559. doi: 10.1016/j.scitotenv.2023.169559

---

JOURNAL

Science of The Total Environment

DOI

10.1016/j.scitotenv.2023.169559 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Cells

ARTICLE TITLE

Chlamydomonas reinhardtii and Microbacterium forte sp. nov., a mutualistic association that favors sustainable hydrogen production

 

New ‘digital twin’ Earth technology could help predict water-based natural disasters before they strike

Scientists demonstrate the use of next-generation satellite data and advanced modeling to build virtual replicas of the terrestrial water cycle that can track water resources and create detailed simulations of flooding and other extreme events

Peer-Reviewed Publication

FRONTIERS

 

IMAGE: 

DIGITAL TWIN EARTH TECHNOLOGY CAN SIMULATE THE TERRESTRIAL WATER CYCLE

view more 

CREDIT: BROCCA L ET AL/FRONTIERS

The water cycle looks simple in theory — but human impacts, climate change, and complicated geography mean that in practice, floods and droughts remain hard to predict. To model water on Earth, you need incredibly high-resolution data across an immense expanse, and you need modeling sophisticated enough to account for everything from snowcaps on mountains to soil moisture in valleys. Now, scientists funded by the European Space Agency have made a tremendous step forward by building the most detailed models created to date.       

“Simulating the Earth at high resolution is very complex, and so basically the idea is to first focus on a specific target,” said Dr Luca Brocca of the National Research Council of Italy, lead author of the article published in Frontiers in Science. “That’s the idea behind what we have developed — digital twin case studies for the terrestrial water cycle in the Mediterranean Basin. Our goal is to create a system that allows non-experts, including decision-makers and citizens, to run interactive simulations.”   

A test environment for the planet  

In engineering, a digital twin is a virtual model of a physical object which can be tested to destruction without doing real damage. A digital twin of the Earth, constantly updated with new data, would allow us to simulate best and worst-case scenarios, assess risks, and track the development of dangerous conditions before they occur. Such information is vital for sustainable development and protecting vulnerable populations.  

To build their digital twin models, Brocca and his colleagues harnessed extraordinary volumes of satellite data, combining new Earth observation data that measures soil moisture, precipitation, evaporation, river discharge, and snow depth. This newly available data, crucial to the development of the models, includes measurements taken much more frequently across space and time: as often as once a kilometer and once an hour. Like a screen with more pixels, this higher-resolution data creates a more detailed picture. The scientists used this data to develop their modeling, and then integrated the modeling into a cloud-based platform which can be used for simulations and visualizations. This is the ultimate goal: an interactive tool anyone can use to map risks like floods and landslides and manage water resources.   

“This project is a perfect example of the synergy between cutting-edge satellite missions and the scientific community,” said Brocca. “Collaborations like this, coupled with investments in computational infrastructures, will be crucial for managing the effects of climate change and other human impacts.”  

Helping people plan the future  

The scientists began by modeling the Po River valley, then expanded the digital twin to other parts of the Mediterranean basin. Upcoming projects plan to expand to cover all of Europe, and future collaborations will allow the same principles to be applied around the world.   

“The story started with an initiative from the European Space Agency,” said Brocca. “I said we should start from something we know very well. The Po River valley is very complex — we have the Alps, we have snow, which is difficult to simulate, especially in irregular and complex terrain like mountains. Then there is the valley with all the human activities – industry, irrigation. Then we have a river and extreme events — floods, drought. And then we moved to the Mediterranean, which is a good place to investigate extreme events both for too much and too little water.”  

The platform's primary use-case is to enhance flood and landslide prediction and optimize water resource management. To make this work better on a more local level, more granular data and more sophisticated modeling will be needed. For instance, to maximize the potential of a digital twin for agriculture, data resolution should be measured in tens of meters, not hundreds.   

Known unknowns  

Additional challenges persist. These include delays in the transfer of satellite data to the model, the need for more ground observations to validate satellite data, and the increasing complexity of the algorithms needed to handle the data. Furthermore, no model is perfect, and satellite data can contain errors: uncertainties must be properly characterized so that users have an accurate picture of the model’s reliability. According to Brocca, artificial intelligence and machine learning will have a pivotal role in overcoming these challenges, by enhancing data analysis, collection, and processing speed, and streamlining data quality assessment.  

“The collaborative efforts of scientists, space agencies, and decision-makers promise a future where Digital Twin Earths for hydrology provide invaluable insights for sustainable water management and disaster resilience,” Brocca concluded.    

The article is part of the Frontiers in Science multimedia article hub ‘The Digital Twin Earth Hydrology Platform’. The hub features an editorial, viewpoints, and policy outlook from other eminent experts: Prof Ana P. Barros (University of Illinois Urbana Champaign, USA), Prof Christina (Naomi) Tague (University of California, Santa Barbara, USA), Prof Zhongbo Bob Su (University of Twente, Netherlands), Dr Yijian Zeng (University of Twente, Netherlands), and Dr Giriraj Amarnath (International Water Management Institute, Sri Lanka). 

The Digital Twin Earth hydrology platform: toward better water use and disaster prediction

Key milestones for creating a planetary-scale Digital Twin Earth

CREDIT

Brocca L et al/Frontiers

JOURNAL

Frontiers in Science

DOI

10.3389/fsci.2023.1190191 

METHOD OF RESEARCH

Computational simulation/modeling

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

A Digital Twin of the terrestrial water cycle: a glimpse into the future through high-resolution Earth observations

ARTICLE PUBLICATION DATE

5-Mar-2024

COI STATEMENT

The author SM is employed by Meteorological Environmental Earth Observation s.r.l. The author CB is employed by Earth Observation Data Centre for Water Resources Monitoring GmbH. These companies had no involvement in the study and did not provide funding. The funders listed under “Funding” had the following involvement with the study: supervision of the research activities, editing of the manuscript, discussion and interpretation of the results. The Frontiers Editorial Office assisted in the conceptualization, interpretation, and design of the figures in this article. The authors LB, SC, LC, JD, CM, SM, AT, MV, LA, DR, DM declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Disclaimer: AAAS and EurekAlert! are not responsibl

 

Enhancing statistical reliability of weather forecasts with machine learning

Peer-Reviewed Publication

INSTITUTE OF ATMOSPHERIC PHYSICS, CHINESE ACADEMY OF SCIENCES

 

IMAGE: 

THE REVIEW PAPER FEATURED ON THE COVER OF THE 8TH ISSUE OF ADVANCES IN ATMOSPHERIC SCIENCES IN 2024 AIMS TO ASSIST READERS IN THE FIELD OF ATMOSPHERIC SCIENCES IN GAINING A THOROUGH UNDERSTANDING OF SOLAR POWER CURVE MODELING AND STAYING UPDATED ON RELEVANT RESEARCH ADVANCEMENTS.

view more 

CREDIT: ADVANCES IN ATMOSPHERIC SCIENCES

A global team of researchers has made strides in refining weather forecasting methods, with a specific focus on addressing the persistent issue of "quantile crossing."  This phenomenon disrupts the order of predicted values in weather forecasts and arises from the numerical weather prediction (NWP) process—a two-step forecasting method involving observations and atmospheric evolution laws.

Despite NWP advancements, models still yield biased and under-scattered forecasts. To mitigate this, past attempts explored nonparametric methods like quantile regression neural networks (QRNN) and their variants, designed to output quantiles reflecting value ranks in the forecast distribution. However, these methods often face "quantile crossing," hindering forecast interpretation.

Ad hoc solutions, like naive sorting, didn't address the core issue. Enter the team's breakthrough: the non-crossing quantile regression neural network (NCQRNN) model.

This innovation, developed by Professor Dazhi Yang and his co-workers from the Harbin Institute of Technology, Karlsruhe Institute of Technology, Chinese Academy of Sciences, National University of Singapore, UK Power Networks, China Meteorological Administration, Heilongjiang Meteorological Bureau, and Budapest University of Technology and Economics, tweaks the traditional QRNN structure.  The NCQRNN model modifies the structure of the traditional QRNN by adding a new layer that preserves the rank order of output nodes, such that the lower quantiles are constrained to be perpetually smaller than higher ones without losing accuracy.

Their findings are published in Advances in Atmospheric Sciences.

Professor Yang emphasizes, "Our NCQRNN model maintains the natural order of forecast values, ensuring lower quantiles stay smaller than higher ones. This boosts accuracy and significantly improves forecast interpretability."

Dr. Martin J. Mayer from the Budapest University of Technology and Economics adds, "The idea is simple but effective: The neural network indirectly learns the differences between the quantiles as intermediate variables and uses these non-negative values in an additive way for estimating the quantiles, inherently guaranteeing their increasing order. Moreover, this non-crossing layer can be added to a wide range of different neural network structures, ensuring the wide applicability of the proposed technique."

Indeed, successfully applied to solar irradiance forecasts, this innovative machine learning approach showcased substantial improvements over existing models. Its adaptable design allows seamless integration into various weather forecasting systems, promising clearer and more reliable predictions for a range of weather variables.

Dr. Sebastian Lerch from the Karlsruhe Institute of Technology commented, "The proposed neural network model for quantile regression is very general and can be applied to other target variables with minimal adaptations. Therefore, the method will also be of interest for other weather and climate applications beyond solar irradiance forecasting."

Dr. Xiang'ao Xia from the Institute of Atmospheric Physics at the Chinese Academy of Sciences concludes, "Machine learning has important application prospects in the field of weather and climate research. This study provides an instructive case study on how to apply advanced machine learning methods to numerical weather prediction models to improve the accuracy of weather forecasts and climate predictions."

The international research team comprises individuals with diverse backgrounds, spanning atmospheric sciences, solar energy, computational statistics, engineering, and data sciences. Notably, certain team members involved in this study have collaborated on a review paper elucidating fundamental concepts and recent advancements in solar power curves. Published on March 1 and featured on the cover of the 8th issue of Advances in Atmospheric Sciences, this review paper not only establishes a robust understanding of solar power curve modeling principles but also functions as a bridgehead for atmospheric scientists, connecting their knowledge on radiation to the practical utilization of solar power.

---

JOURNAL

Advances in Atmospheric Sciences

DOI

10.1007/s00376-023-3184-5 

ARTICLE TITLE

Non-crossing Quantile Regression Neural Network as a Calibration Tool for Ensemble Weather Forecasts

 

Scientists sort out uncertainties in sea level projections

Peer-Reviewed Publication

INSTITUTE OF ATMOSPHERIC PHYSICS, CHINESE ACADEMY OF SCIENCES

As global temperatures continue to rise, coastal communities are confronted with the pressing challenge of surging sea levels. The urgency to provide decision-makers with reliable forecasts of future sea levels becomes increasingly critical. At the forefront of this predictive effort lies Dynamic Sea Level (DSL), a nuanced variable intricately linked to seawater density and ocean circulation, currently under intensive scrutiny in climate models.

The Ocean Modeling Team at the Institute of Atmospheric Physics, Chinese Academy of Sciences, recently conducted an extensive study, unraveling the uncertainties surrounding DSL projections using the cutting-edge Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble and the expansive FGOALS-g3 super-large ensemble.

Their study reveals that concerning basin-scale dynamics, intermodel uncertainty plays a leading role, contributing over 55%, 80%, and 70% to the total uncertainty of DSL projections in the near term (2021-2040), midterm (2041-2060), and long term (2081-2100), respectively. Following closely is internal variability, accounting for 10-42% in the near term and less than 20% in the midterm. While the impact of scenario uncertainty is initially minimal, it gradually ascends, surpassing contributions from internal variability in the long term.

Professor Hailong Liu, the corresponding author of the series of recently published studies, emphasized, “There are also regional nuances. At the regional scale, internal variability dominates in the near term for the Pacific Ocean, Indian Ocean, and the western boundary of the Atlantic Ocean. Conversely, intermodel uncertainty takes the spotlight in other regions. Contributions evolve over time, with scenario uncertainty becoming significant in the Southern, Pacific, and Atlantic Oceans in the long term.”

The research team also observed that anthropogenic DSL signals are expected to emerge from specific regions by the close of this century. The refinement of the CMIP6 ensemble, achieved by eliminating model differences, enhances our ability to detect these signals in advance.

“Imagine trying to understand Earth's climate using a computer model. Instead of running the model just once, we run it many times with slight variations in the starting conditions. This helps us see how the model responds to different situations,” explained Prof. Liu. “By doing this, we can better measure how the Earth's climate reacts to external factors, like changes in greenhouse gases, and also understand the natural ups and downs that happen on their own. This way, we get a clearer and more reliable picture of how our climate works.”

The team, therefore, gains insights from the FGOALS-g3 Super-Large Ensemble, featuring 110 model members, aligning seamlessly with CMIP6 members in basin-mean DSL projections. A comparative analysis with the CMIP6 ensemble reveals larger estimates of internal variability in the FGOALS-g3 super-large ensemble.

So, what are the implications for tomorrow? The team’s research not only deepens our comprehension of rising sea levels but also lays the groundwork for more accurate and informed climate models. The insights gleaned are instrumental in securing the future of our coastal communities.

These findings have recently been published in the Journal of Climate, Advances in Atmospheric Sciences, and Geoscience Letters.

---

DOI

10.1175/JCLI-D-23-0272.1 

ARTICLE TITLE

Uncertainties in the Projection of Dynamic Sea Level in CMIP6 and FGOALS-g3 Large Ensemble

 

RISEnergy: Pushing innovations for climate neutrality

KIT-coordinated EU project aims to push and interconnect renewable energy technologies

Business Announcement

KARLSRUHER INSTITUT FÜR TECHNOLOGIE (KIT)

 

IMAGE: 

RESEARCH INTO THE PRODUCTION OF CLIMATE-NEUTRAL FUELS AT THE ENERGY LAB, EUROPE’S LARGEST RESEARCH INFRASTRUCTURE FOR THE USE OF RENEWABLE ENERGY SOURCES AT KIT WILL ALSO BECOME PART OF THE RISENERGY ECOSYSTEM. (PHOTO: AMADEUS BRAMSIEPE, KIT)

view more 

CREDIT: AMADEUS BRAMSIEPE

“RISEnergy will create  a European ecosystem covering all areas of renewable energy technologies,” says Dr. Olga Sumińska-Ebersoldt, co-coordinator of RISEnergy and researcher at the Helmholtz Institute Ulm (HIU) that was established by KIT and Ulm University. “We want to push the development of promising technologies from the laboratory level to industrial maturity.” Joint research infrastructure projects have already been launched for certain technologies, but RISEnergy is the first project of this dimension in Europe that covers all areas of renewable energy technologies: Photovoltaics, Concentrated Solar Power, Hydrogen, Biofuels, Wind Energy, OceanEnergy, as well as Integrated Grids, Energy Storage, Materials Research, Information and Communication Technologies.

 

Consortium of Institutions from 22 Countries 

The RISEnergy consortium consists of 69 technology institutes, universities, and industry partners from 22 countries. The partners contribute with their infrastructures, know-how, or provide organizational support. 

 

The core of the network is the European Energy Research Alliance EERA. EERA provides world-leading expertise via 18 Joint Programmes. “To integrate all major stakeholders, we asked EERA Joint Programmes to propose the best research infrastructures and experts for RISEnergy,” says Dr. Myriam E. Gil Bardají, researcher at HIU, coordinator of the EERA Joint Programme on Energy Storage, and co-coordinator of RISEnergy. Participation of organizations from the USA, Canada, and Japan ensures access to innovation outside of Europe. 

 

Researchers Can Apply

Within the framework of RISEnergy, 84 research infrastructures from 19 European countries, the USA, Canada, and Japan will open their facilities to external researchers and company developers, who can apply for access. An expert committee will decide. If approved, RISEnergy will cover the costs of the research facility as well as travel and accommodation expenses. Most of the project budget will be used for this purpose. 

 

The offer is specifically aimed at small and medium-sized companies. Uncomplicated access to major research infrastructures is expected to boost their innovations. “We offer cost-free use of laboratories. Researchers and experts from companies can travel, exchange ideas, and conduct experiments,” Sumińska-Ebersoldt says.

 

Networking, Exchange, and Communication

“When we think of using renewable energy sources, we always refer to combinations of technologies,” says Dr. Peter Holtappels, head of a working group at KIT’s Institute for Micro Process Engineering and scientific project coordinator of RISEnergy. He therefore emphasizes the importance of experts from different disciplines understanding each other. “Those designing energy storage systems or studying photovoltaics, wind and tidal energy usually are members of separate communities. We want to bring these people together and to encourage exchange and interdisciplinary collaboration.” There are plans to organize workshops and advisory services on overarching topics, such as lifecycle assessment and projects to standardise terminology and data processing. “Another focus will lie on digital tools for the energy transition: Artificial intelligence will help optimize the properties of materials and instruments and replace critical materials in supply chains,” says Dr. Holger Ihssen from the Helmholtz Association's Brussels office that helped establish the new research consortium. 

The project team will assess funding measures and identify reasonable ones. It will also develop roadmaps for policy makers. 

 

About RISEnergy (Research Infrastructure Services for Renewable Energy) 

RISEnergy is part of the Horizon Europe Funding Programme for Research and Innovation and of the module “Materials for Energy” of the global Mission Innovation initiative. The core of the project consortium is the European Energy Research Alliance EERA, the biggest research alliance for low-carbon energy technologies in Europe and major stakeholder in the EU’s strategic energy technologies plan (SET). Within the framework of Transnational Access (TNA) programmes, researchers and companies can apply for access to research infrastructures. The project coordinated by KIT is scheduled to start on March 1, 2024 and to expire on August 31, 2028. The project will be kicked off in Brussels on March 12 and 13, 2024. 

 

More Information:
European Energy Research Alliance

KIT Institute for Micro Process Engineering