• Skip to primary navigation
  • Skip to main content
  • Skip to footer
Vaikuttavuussaatio

Vaikuttavuussaatio

Vaikuttavuussäätiö vahvistaa ja tukee huippututkimuksen vaikuttavuutta ja elinkeinoelämän yhteyksiä.

  • FI
  • EN
  • Front page
  • Funding
    • Open calls
    • Previous calls
    • Projects funded
  • Foundation
    • About
    • Annual reports
    • Blog
    • Assessment of Impact
  • Publications
  • Contact

Annual Report 2021

University of Helsinki and Valio join forces in project that challenges current indicators of milk’s carbon footprint

19.5.2022 by vaikuttavuussaatio

« back to the annual report

Project title: Mitigating grassland N2O emissions – towards carbon neutral milk production (MiNiMi)
Approved funding: 232 690 €
Applicant: University of Helsinki (Mari Pihlatie)
Industrial partner: Valio
Principal investigator: professor Mari Pihlatie

Understanding and cutting the carbon footprint of milk production requires in-depth knowledge about true greenhouse gas emissions from dairy farming. To this end, the University of Helsinki and Valio have turned their focus to studying nitrous oxide. It contributes significantly to dairy production emissions but has largely been overshadowed in research by carbon dioxide.

The carbon footprint of food production is an important current topic of debate both nationally and internationally. UN estimates are that the agri-food system accounts for over 30 per cent of greenhouse gas emissions from human activities. Milk production is one part of this system. Valio has for years been doing research to establish exactly what kind of emissions are released from milk production and what could be done to them. But the main focus has long been on carbon dioxide.

Less interest has been given to nitrous oxide emissions, even though they are known to account for up to 30 per cent of milk’s carbon footprint. The University of Helsinki and Valio are working in a joint project to shed light specifically on nitrous oxide, which is commonly known by its chemical formula N2O. It is a potent greenhouse gas that is emitted especially from fertilized soil, such as grassland that is used to feed cattle.

“Nitrous oxide emissions are unpredictable and episodic, and therefore modelling these emissions is extremely challenging. Measurement requires expensive instrumentation, which is why N2O emissions have been measured less frequently than carbon dioxide emissions,” says Mari Pihlatie, professor of environmental soil science and principal investigator in the project. She has been studying nitrous oxide emissions her entire career.

The project is set to produce completely new information about nitrous oxide emissions, based on regular measurements conducted at the SMEAR-Agri station in connection with the University of Helsinki Viikki campus and at Valio grassland farms across the country.

“There’s a scarcity of research on emissions in northern environments, even though the climate here is completely unique. This project will allow us to show how our short growing season and topsoil freezing and thawing impact emissions. At the moment this information is not available anywhere.”

Current estimates of nitrous oxide emissions from grassland production are based on the IPCC emission coefficient, which has been created on the basis of the existing research evidence. Because northern regions are underrepresented in earlier research it is hard to tell whether the coefficient accurately reflects the real situation on Nordic farms. Pihlatie and her colleagues are working to verify the data. 

In addition to Valio and the University of Helsinki, the project involves a wide variety of other partners: dairy farms across Finland; the Finnish Meteorological Institute; Natural Resources Institute Finland; Yara Finland; Vaisala; Datasense; and Soil Scout. Combining the expertise of these different organizations will help to discover new ways of reducing nitrous oxide emissions. Potential new solutions include new types of fertilizer and optimizing the timing of fertilizer application in order to minimize emission levels. 

The project team have been keen to ensure that the information they produce will also have international significance. All measurements are conducted using high-quality instrumentation. Apart from nitrous oxide emissions and methane and carbon dioxide emissions, the team are looking at critical environmental factors such as soil nitrogen content, soil humidity and temperature. “This produces valuable data for the modelling of nitrous oxide emissions and ultimately for assessing the climate impact of grasslands.”

The academic goal is to report the results in the most prestigious publication series. However, Pihlatie is well aware that two years will do little more than scratch the surface of the subject – the research must be continued for much longer. Indeed, plans are already in place to apply for additional funding in the coming winter when the first measurement results are received.


N2O, CH4 and CO2 emission measurements underway at the Viikki SMEAR-Agri station. Chamber gas concentrations are measured using automated laser equipment housed within the protected trolley. From left to right: Phillip Krauss, Pinja Rauhamäki and Lisa Leinonen.

Filed Under: Annual Report 2021

Tampere University and Danfoss are developing a revolutionary energy efficiency solution

19.5.2022 by vaikuttavuussaatio

« back to the annual report

Project title: Optimal Control for Maximizing the Effectiveness of Power Electronic Systems (OPT4MAX)
Approved funding: 197 710 €
Applicant: Tampere University (Petros Karamanakos)
Industrial partner: Danfoss Drives/Vacon
Postdoctoral researcher: Mattia Rossi

Electricity prices have reached historical highs during the past spring. Improving energy efficiency is therefore a timely step towards greater climate and economic sustainability. Tampere University and Danfoss are working closely to develop a solution that can help achieve significant energy savings in industrial machinery.

Energy efficiency is one of the fastest and cheapest ways to reduce carbon dioxide emissions. For cost reasons alone, improving energy efficiency is of great interest to both businesses and private citizens because the sanctions imposed on Russia in response to its invasion of Ukraine are limiting access to energy resources and driving up prices.

The International Energy Agency’s Net Zero by 2050 Scenario has set the target of reaching 35 per cent cuts in energy intensity by 2030. In other words, the growing population on the planet should secure the energy it needs with 35 per cent greater efficiency. The changes are driven by accelerating electrification in society, changes in consumer behaviour and improvements in energy efficiency.

Energy efficiency is a particularly critical concern in industries that use big machinery. Almost one-quarter of all electric industrial motors use variable speed drives (VSD), which control the motors by adjusting the frequency and voltage of the power supply. Various kinds of fans and pumps are typical examples of devices that make use of VSDs. VSDs improve energy efficiency as such because they are used to regulate the motor’s energy consumption.

But VSDs themselves have so far not operated at their maximum efficiency. VSDs can account for up to half of all the energy consumed. There is room to improve the energy efficiency as well as production and operating costs. Researchers from Tampere University and Danfoss are now working closely to develop a solution that would reduce power and energy losses in VSDs.

Mattia Rossi, postdoctoral researcher on the project from Tampere University, explains: “Traditionally VSD control methods are not particularly suited to deal with the multiple needs of modern industry applications. The new method we’re developing helps to minimize the power losses and extract every bit of energy available. This means we are getting more power and higher device efficiency.”

The project team’s results confirm that this advanced control method based on model predictive control (MPC) is highly effective. The first tests have produced savings of 1–2 per cent. “Savings of just one per cent are significant when we’re dealing with industrial machinery in kilowatt range,” Rossi continues. Besides, he points out, these are just the first preliminary results. The full power of the new solution will become clear when the project moves on from the current simulation stage to real industrial scale trial runs.

The opportunity to conduct laboratory trials on industry hardware is one of the best sides of industry-academia cooperation, Rossi says: “This research would not be possible without an industrial partner. The collaboration helps to align the research with market requirements. Without a business partner, we would not have such validation part which is necessary to drive our software development.”

The research team will have access to the first trial results during 2022, and the project will be completed in 2023. By then it will become clear just how big a revolution they will be achieving in energy efficiency. If they are successful in optimizing VSD energy consumption, the technology will have extensive application prospects in many industry branches. The solution developed in the project may also have practical application in energy storage and battery technology, for instance.

The project team’s goals are far-reaching: “When we come to wrap up this project we will hopefully have produced not just research but also a finalized software feature that can be further patented and potentially commercialized. We can then look ahead to improving energy efficiency in other energy branches as well.”

Filed Under: Annual Report 2021

Orion and University of Helsinki harnessing AI to improve efficiency of pharmaceutical substances production

19.5.2022 by vaikuttavuussaatio

« back to the annual report

Project title: Optimizing synthesis of pharmaceuticals by machine learning
Approved funding: 222 000 €
Applicant: University of Helsinki (Jari Yli-Kauhaluoma) 
Industrial partner: Orion Corporation, Orion Pharma
Industrial supervisor: Toni Metsänen, vanhempi tutkija, Orion

The coronavirus vaccine brought home to many people just how much the efficiency of pharmaceutical product development can be improved if scientists work more closely with pharmaceutical companies. The University of Helsinki and Orion have launched a joint project to develop a databank that uses AI and machine learning algorithms and that will greatly speed up the work of chemists.

Pharmaceutical drug development is a slow process. From the initial idea, it takes at least 10–12 years to get the final product on the shelf. There are several reasons for this, starting from the slow funding mechanisms for pharmaceutical research and the expertise required by synthesis technology to complex pharmaceutical licensing procedures. A joint research venture between Orion Pharma and the University of Helsinki is now focused on speeding up one crucial stage in this process: laboratory studies on chemical synthesis reactions. To this end, the team have turned to AI and machine learning.

The development of a new pharmaceutical substance can require the production of thousands of new chemical compounds. Each and every one of them has to be manufactured separately using a new synthesis route, or cluster of chemical reactions. Each reaction has its own reagents, catalysts, solvents, temperatures and volumes. Given the large number of variables, there are also countless potential outcomes.

“Research into chemical reactions today relies largely on the professional expertise and experience of chemists,” says Toni Metsänen, senior researcher at Orion. “Chemists are inclined to use the synthesis routes that they’re already familiar with. This gives greater certainty of a successful outcome and ensures high efficiency,” he continues. Without prior knowledge of the reactions, the alternative is to turn to the literature and earlier research. But that is a slow route.

The project between the University of Helsinki and Orion is aimed at digitalizing the tacit knowledge possessed by chemists and the body of extant research and on this basis to create a rich reaction database that provides immediate access to critical information.

With reaction data readily available, optimization of a certain synthesis route will happen far more quickly – which in turn will translate into greater efficiency in the development of new pharmaceutical substances. Chemists can put more of their effort into work that counts the most and minimize loss of time.

Artificial intelligence plays a key role in medical development in all pharmaceutical companies. “Companies will typically aim to optimize a certain synthesis route so that it’s as quick and easy as possible for them to produce tonnes of a certain medicinal substance. 

In this research project we’re taking a somewhat wider view on what AI can offer and trying to find answers to completely new chemical reactions,” Metsänen explains. In other words, AI could predict what is going to happen when a certain previously used reagent is replaced by a new one or when there are changes to some other part of the synthesis route.

Toni Metsänen says the ongoing project is highly significant because it involves three different university departments: chemistry, pharmacy and computer science. What is more, the team have two full years to concentrate on their research, a rare opportunity indeed for anyone working in industry. “We will also be gaining access to special expertise in AI that  would be very hard for us to develop within the company.”

Apart from the professors working on the project, the team includes a postdoc researcher and a Master’s student. Both of them will accumulate great expertise in the project that will be in high demand in the future. “Chemists of the future will need to know how to make use of machine learning in support of the work that is done in the lab,” Metsänen says.

The project has now moved on to a phase where a significant amount of existing data has been uploaded into the software and tested. The project’s basic idea is up and running, but Metsänen is keen to stress the importance of speed: the aim is to be able to access the information required in a matter of seconds. “We don’t want to develop a separate software suite but a tool that can be adopted as part of chemists’ existing toolbox. The value of the end result will be measured in terms of ease of use.”



AI helps the chemist to discover the most appropriate conditions for chemical reactions. 

Filed Under: Annual Report 2021

Research collaboration can even offer solutions to current world crises

18.5.2022 by vaikuttavuussaatio

Research collaboration can even offer solutions to current world crises

« back to the annual report

All foundations have a charter which lays down their goal, objective or mission as defined by the people who set up the foundation. The Finnish Research Impact Foundation is no exception: its declared aim is to strengthen public-private partnerships and in this way to build a stronger platform for the development of Finnish know-how and renewal in the long term. This is an important goal in its own right, but this importance is further emphasized when we ask “why”.

Public-private partnerships serve not only to drive the growth of the Finnish economy – by building a stronger platform for know-how and renewal – but they can also bring practical solutions to current world problems, such as the climate crisis. Research produces knowledge about the world that industries can use to develop new innovations and solutions. This creates a win-win cycle that generates new resources for doing better research and for building a healthier environment and society. This is the answer to the question of why.

But this cycle cannot be kept going full circle without cooperation. In the worst case it can even turn in on itself: less research means less inventions and innovations and less access to resources. In early 2021 the Finnish Research Impact Foundation published the results of its survey and sparked serious debate about the state of industry-academia cooperation in Finland and the reasons why it has been slowing. Later in the year the Parliamentary RDI Working Group submitted its proposal for a legislative act that would secure increased funding for research and development. This is a welcome mechanism that will help to ensure greater predictability in funding levels and to strengthen the commitment of companies to  step up their own investment in innovation.

The money invested in research and development will perhaps eventually come to boost industry-academia cooperation as well, but that will also require new funding models and new incentives. Someone has to actively turn the wheel and create fertile soil for cooperation. In line with its 2021 strategy, the Finnish Research Impact Foundation is committed to work towards these ends by piloting new funding models intended to promote cooperation.

In 2021 FRIF granted funding to 11 new joint research projects between academic and industry partners. The themes of these projects range from fine particle measurement technologies to dairy production emissions and potential uses of AI in pharmaceutical drug development. The research organizations and companies involved represent the absolute highest standards of Finnish and international excellence in their respective technology branches.

Projects aimed in one way or another at improving the state of the environment through science and innovation have a strong representation among the work we have decided to support. This is a positive signal, indicating that there are multiple ways in which to conduct research and business committed to environmental management and improvement and to do this in collaborative settings. A great example is the energy efficiency project between Tampere University and Danfoss: the partners are working to explore and develop methods for controlling VSDs that are used to regulate the power supply to industry motors. More sophisticated control mechanisms promise to achieve significant energy savings and to reduce emissions, producing both short-term effects and longer-term impact.

I hope you enjoy our annual report and take the time to read its excellent articles about the projects we are funding!

Filed Under: Annual Report 2021

Footer

Vaikuttavuussäätiö

Eteläranta 10 (PL 5), 00130 Helsinki
+358 40 767 1631
petro (at) vaikuttavuussaatio.fi

Laskutustiedot →

  • Facebook
  • Instagram
  • LinkedIn
  • Twitter

Privacy Policy →

Copyright © 2023 Vaikuttavuussäätiö

By accepting cookies, you make your service experience as smooth as possible. Some cookies are used for statistical purposes and others are related to services provided by third parties. By selecting ACCEPT, you agree to the use of cookies. Read moreSettings REJECTACCEPT
Cookiesettings

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary
Always Enabled
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
CookieDurationDescription
cookielawinfo-checkbox-advertisement1 yearSet by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Advertisement" category .
cookielawinfo-checkbox-analytics1 yearSet by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Analytics" category .
cookielawinfo-checkbox-functional1 yearThe cookie is set by the GDPR Cookie Consent plugin to record the user consent for the cookies in the category "Functional".
cookielawinfo-checkbox-necessary1 yearSet by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Necessary" category .
cookielawinfo-checkbox-others1 yearSet by the GDPR Cookie Consent plugin, this cookie is used to store the user consent for cookies in the category "Others".
cookielawinfo-checkbox-performance1 yearSet by the GDPR Cookie Consent plugin, this cookie is used to store the user consent for cookies in the category "Performance".
viewed_cookie_policy1 yearThe cookie is set by the GDPR Cookie Consent plugin to store whether or not the user has consented to the use of cookies. It does not store any personal data.
Functional
Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features.
CookieDurationDescription
bcookie2 yearsLinkedIn sets this cookie from LinkedIn share buttons and ad tags to recognize browser ID.
bscookie2 yearsLinkedIn sets this cookie to store performed actions on the website.
langsessionLinkedIn sets this cookie to remember a user's language setting.
lidc1 dayLinkedIn sets the lidc cookie to facilitate data center selection.
UserMatchHistory1 monthLinkedIn sets this cookie for LinkedIn Ads ID syncing.
Performance
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
Analytics
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.
CookieDurationDescription
_ga2 yearsThe _ga cookie, installed by Google Analytics, calculates visitor, session and campaign data and also keeps track of site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognize unique visitors.
_ga_MEFLNRCR5S2 yearsThis cookie is installed by Google Analytics.
_gat_UA-160708278-11 minuteA variation of the _gat cookie set by Google Analytics and Google Tag Manager to allow website owners to track visitor behaviour and measure site performance. The pattern element in the name contains the unique identity number of the account or website it relates to.
_gcl_au3 monthsProvided by Google Tag Manager to experiment advertisement efficiency of websites using their services.
_gid1 dayInstalled by Google Analytics, _gid cookie stores information on how visitors use a website, while also creating an analytics report of the website's performance. Some of the data that are collected include the number of visitors, their source, and the pages they visit anonymously.
CONSENT2 yearsYouTube sets this cookie via embedded youtube-videos and registers anonymous statistical data.
Advertisement
Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.
CookieDurationDescription
_fbp3 monthsThis cookie is set by Facebook to display advertisements when either on Facebook or on a digital platform powered by Facebook advertising, after visiting the website.
fr3 monthsFacebook sets this cookie to show relevant advertisements to users by tracking user behaviour across the web, on sites that have Facebook pixel or Facebook social plugin.
VISITOR_INFO1_LIVE5 months 27 daysA cookie set by YouTube to measure bandwidth that determines whether the user gets the new or old player interface.
YSCsessionYSC cookie is set by Youtube and is used to track the views of embedded videos on Youtube pages.
yt-remote-connected-devicesneverYouTube sets this cookie to store the video preferences of the user using embedded YouTube video.
yt-remote-device-idneverYouTube sets this cookie to store the video preferences of the user using embedded YouTube video.
Others
Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet.
CookieDurationDescription
AnalyticsSyncHistory1 monthNo description
li_gc2 yearsNo description
Save & Accept