Arkiv for Projects
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NILU
A good indoor environment at school is important for the health and well-being of pupils and staff, and has a significant impact on pupils' learning outcomes.

Good maintenance of buildings and operation of the technical facilities is important to have good indoor climate, but it is also crucial that staff and pupils use the school buildings correctly and are involved in practical indoor environment work at school level.

This requires that staff and pupils are aware of and have knowledge of how their behavior affects the indoor climate, as well as how the individual can contribute to ensuring as good an indoor climate as possible at the school.

Data from indoor climate sensors, combined with information about how employees and pupils experience indoor climate and related health problems, can provide new opportunities to both identify indoor climate problems, find the cause and identify the right measures, and to create new tools that engage and involve the users of the school buildings.

Today's schools are largely equipped with sensor systems for indoor climate, but there are no tools to collect data on user experiences. Data from integrated sensors is to a small extent available to the school. Information on connections between sensor data and experiences is currently lacking.

DIGG-MIN-SKOLE vill combine data from sensors that are an integral part of the school's technical facilities and/or individual indoor climate sensors with self-acquired data related to user experience.

This data will be used to develop a machine learning model that can estimate the probability that the users will experience reduced well-being/health problems, which factors in the indoor climate are most likely to be the cause of the health problems (temperature, light conditions, noise, CO2 etc.) and identify targeted mitigating measures at school /classroom level.

Unit managers, staff and students must contribute to the design of (part) tools so that the results from the machine learning model are suitable for use in the school's everyday life. The end result will be a technical specification and demonstration of a user-oriented management system (BOF) in several schools.

Transformative adaptation is gaining recognition as the appropriate response to climate change as the current adaptive measures reach their limits.

In addressing health risks associated with heat waves, air pollution, wildfire emission and pollen, the implementation of comprehensive transformative adaptation remains largely unreported in Europe.

healthRiskADAPT’s objective is to develop and implement a health risk assessment system for Mediterranean, Alpine and Continental regions. Its contents and tools will be in line with Climate-ADAPT described Urban adaptation support tool. This will support empowerment of local and regional authorities to make informed decisions in strategic planning, management and daily operational mitigation of health challenges related to climate change.

healthRiskADAPT will address the fundamental causes of vulnerability and implement concrete adaptation measures aiming to mitigate the health impacts of climate change. The key details of this approach include:

1) Co-creation with users of integrated transformative adaptation options encompassing technical, nature based, and social solutions, reducing the impact of climate-related risks on human health in both indoor and outdoor environments. (SO1, SO5, SO6)

2) Vulnerability assessments, health indicators, and risk indices related to climate change impact on health, considering different temporal and spatial scales. (SO2, SO3)

3) Interactive and user-friendly toolkit for local & regional authorities to assess hazards, vulnerability, and risks specific to their regions. These toolkits will facilitate the prioritization, planning, and evaluation of adaptation options. (SO4)

healthRiskADAPT will use various communication techniques (SO7) to actively engage with all stakeholders involved in the adaptation process, and develop an upscaling strategy to meet the ambitions of the Climate mission. Furthermore, we seek to enhance the preparedness of the healthcare system to respond effectively to the challenges posed by the effects of climate change.

DOI: https://cordis.europa.eu/project/id/101157458

[caption id="attachment_53972" align="alignnone" width="1037"] Floatchart for the project HealthRiskADAPT[/caption]

Hydrovolt is a joint venture owned by Hydro (NO) and Northvolt (SE), and the company operates a battery recycling facility in Fredrikstad, S-E Norway.

The purpose of the NILU monitoring was to quantify the levels of VOCs (Volatile Organic Compounds) at the Hydrovolt plant. The sampling took place at various steps throughout the production line.

The NILU technology to remove hydrogen fluoride (HF) was applied. If HF is not removed, HF can dissolve the TenaxTM sampling material and hence give erroneously high concentrations of VOCs.

There was also sampling of nitrogen dioxide (NO2), hydrogen fluoride (HF), ozone (O3), sulphur dioxide (SO2), formic acid (HCOOH), and acetic acid (CH3COOH) using passive samplers.

The monitoring results will be sent to Norwegian authorities (County Governor) to document components emitted from the Hydrovolt facility.

For all practical purposes, the volume flow emitted from Hydrovolt is small (55 m3/h) and the total amount emitted is regarded as minor.

NILU has, on behalf of LKAB Norge AS, carried out emission and dispersion calculations for combined emissions from point sources and diffuse sources from the facility in Narvik. The purpose of the project was to develop dispersion calculations that indicate LKAB's contribution to the pollution situation in Narvik.

LKAB Norge AS in Narvik is responsible for loading iron ore from Sweden onto ships at LKAB's port in Narvik, as well as unloading additives for transport back to LKAB in Sweden. This process involves both controlled point source emissions and emissions from diffuse sources. Several factors, including correlation between loading activity and measured deposition, suggest that the loading and unloading operation is the most significant diffuse source.

The dispersion calculations have been conducted using FLEXPART-WRF, an atmospheric dispersion model based on meteorological data from the weather forecasting model WRF. FLEXPART models particles that follow the turbulent air movements of the atmosphere and are deposited on the surface through dry and wet deposition. In this analysis, total emissions are estimated on inverse calculations from the relationship between measured and calculated dust deposition, rather than from generic emission factors such as the EEA/EMEP air pollutant emission inventory Guidebook (2019).

This, along with an assumption about the size distribution of dust emissions, yields a resulting field of ground concentrations for PM10 and PM2.5. The concentration field can be extracted from the model at the desired time and spatial resolution.

The figure shows three snapshots of the PM10 concentration field along with the temporal variation at a given point over a period in February. A full calendar year is calculated, providing annual mean, daily mean, and hourly mean concentrations.

[caption id="attachment_52069" align="alignnone" width="1171"] The figure shows three snapshots of the PM10 concentration field along with the temporal variation at a given point over a period in February. A full calendar year is calculated, providing annual mean, daily mean, and hourly mean concentrations.[/caption]

[caption id="attachment_52067" align="aligncenter" width="1379"] LKAB in Narvik. Copyright: LKAB.[/caption]

Socio-economic growth has led to rapid urban development in Polish cities, and major and recurrent challenges have arisen linked to uncontrollable urban sprawl development (e.g., transport congestion, high traffic emissions).

This feedback relation is not properly understood by decision-makers, often due to missing evidence-based support.

We aim at developing an integrated framework for analyzing the nexus land use – transport – traffic emissions (LUTEm) associated with urban sprawl development in Polish cities by combining advanced multimodal transport planning and emission modelling.

The LUTEm framework will be applied to real-world case studies in Polish cities to

underline negative effects induced by suburbanisation,

assess intervention scenarios and

formulate paths towards green transition in land-use-transport development in case-study cities.

The results will be a novel research support for decision-makers in understanding the land-use-transport interactions, and resultant traffic emissions to improve air quality and mitigate climate change.

To achieve this, we will perform transport modelling, where the effects of spatial development vs. transport system structures upon travel choices will be simulated.

The transport model will be integrated with a state-of-the-art model to estimate air pollutant and GHGs emissions to provide insights on the relationship between urban planning and environmental sustainability across the case-studies.

The LUTEm analysis will reveal co-beneficial interventions and measures to mitigate the negative urban sprawl consequences for traffic emissions, discussed then with city policymakers and stakeholders.

The scientific community still has no consensus on if and how Arctic warming and sea ice loss can influence weather and climate in the Northern Hemisphere. The BASIC project sets out to better understand the climate response to Arctic change, especially focusing on the new Arctic characterized by more open water in summer (hence bluer) and increased newly-formed sea ice in winter. This latter change has been mostly overlooked, but it has potentially profound climate impacts.

Sea ice change can affect the Atlantic Meridional Overturning Circulation (AMOC) through modulating ocean salinity: AMOC is a large ocean current driven by the sinking of denser water in the northern North Atlantic. It carries tropic warm water into the North Atlantic and thus along the Norwegian coast, but has been weakened by the increase of freshwater due to long-term sea ice melting. As multi-year ice is decreasing rapidly, the recent and future increasing newly-formed ice may change such impacts.

A bluer Arctic may change the respective roles of Arctic Ocean temperature and sea ice in impacting climate. Model experiments have shown that the climate responses to an ice-free state are appreciably distinct from an ice-covered state. We expect that, before the Arctic reaches an ice-free state, Arctic sea ice may shrink stepwise and go through a threshold where ocean temperature takes over to impact climate. Identifying this threshold is important for climate prediction.

Bluer Arctic with increased newly-formed winter sea ice is concurrent with an Arctic warming extending downwards into ocean interior and upwards to mid-troposphere (~5 km). But the climate models have divergent abilities to simulate the observed deep Arctic warming, which caused debates in this field. BASIC will develop a new methodology to conquer this problem.

The BASIC project will analyze available observed and simulated datasets and run new experiments with the Norwegian Earth System Model to address the above issues.

Air pollution has serious impacts on human health, wellbeing and welfare. The main challenge is to understand how to regulate air pollution in an optimal way both on global and local scales.

The aim of the project is to link detailed information of the spatio-temporal distribution of air pollution levels with register data for mortality and morbidity in the Nordic countries to gain new understanding of the various health impacts from different kinds of air pollution from different sources.

This will provide the basic understanding needed for policy making of strategies to optimally reduce the air pollution challenge and to assess the related impacts on the distribution of health impacts and related societal costs and welfare.

The results from the project will be used in both a Nordic as well as global perspective to improve the health and welfare by finding the optimal solutions to societal and public health challenges from air pollution through high-quality research. The study will provide a Nordic contribution to international research on the topics of environmental equality and justice within the area of air quality related risks, amenities and wellbeing.

The project was coordinated by Aarhus University in collaboration with 16 partners from other Nordic countries:

Partners

The research collaboration will run for five years and has 16 partners from the Nordic countries.

The project is coordinated by Prof. Jørgen Brandt and Senior Scientist Camilla Geels, Department of Environmental Science, Aarhus University.

All the partners:

Denmark

Aarhus University, Department of Environmental Science (AU-ENVS) (all WPs)

Aarhus University, Department of Public Health (AU-DPH) (WP3)

Aarhus University, CIRRAU (AU-CIRRAU) (WP3)

Danish Cancer Society Research Center (DCRC) (WP3)

Finland

Finnish environment institute (SYKE) (WP1 & WP5)

Finnish Meteorological Institute (FMI) (WP2)

National Institute for Health and Welfare (THL) (WP3 & WP4)

Sweden

Swedish Meteorological and Hydrological Institute (SMHI) (WP1 & WP2)

Umeå University (UMU) (WP3)

Swedish Environmental Research Institute Ltd. (IVL) (WP4)

Norway

Norwegian Institute for Air Research (NILU) (WP1)

Norwegian Institute for Water Research (NIVA) (WP5)

Vista Analysis (Vista) (WP4)

Norwegian Institute of Public Health (NIPH) (WP3)

Iceland

The National University Hospital/University of Iceland (Landspitali) (WP3)

University of Iceland (UI) (WP1 and WP2)

NILU has studied the effect of aluminum production on the environment around Norwegian aluminum smelters by doing calculations and measurements since the early 1970s.

In this project, surface concentrations have been calculated for SO2, dust and fluorides, as well as the metal components listed in the emission permit close to the smelter in Årdal, Western Norway.

The calculations are based on a conservative methodology (CONDEP) and the emission inventories are taken from the emissions permit as a worst-case assessment.

The mapping provides answers as to whether there is a risk of certain pollution components being exceeded, or whether the emissions indicate ground concentrations below the current limit values.

For example, the results show that the limit values for SO2 around the plant will not be exceeded by a good margin.

The CERISE project kicked-off January 1 2023. It aims to enhance the quality of the Copernicus Climate Change Service (C3S) reanalysis and seasonal forecast portfolio, with a focus on land-atmosphere coupling.

It will support the evolution of C3S by improving the C3S climate reanalysis and seasonal prediction systems and products towards enhanced integrity and coherence of the C3S Earth system Essential Climate Variables.

CERISE will develop new and innovative coupled land-atmosphere data assimilation approaches and land initialisation techniques to pave the way for the next generations of the C3S reanalysis and seasonal prediction systems.

These developments will include innovative work on observation operators using Artificial Intelligence to ensure optimal data fusion integrated in coupled assimilation systems. They will enhance the exploitation of Earth system observations over land surfaces, including from the Copernicus Sentinels and from the European Space Agency Earth Explorer missions, moving towards an all-sky and all-surface approach.

CERISE Research and Innovation will bring the C3S tools beyond the state-of-the-art in the areas of coupled land-atmosphere data assimilation, observation operators, and land initialisation methodologies.

CERISE will develop diagnostic tools and prediction skill metrics that include integrated hydrological variables to go beyond the traditional skill scores to assess Earth system coupled reanalysis and seasonal prediction. It will deliver proof-of-concept prototypes and demonstrators, to demonstrate the feasibility of the integration of the developed approaches in the operational C3S.

The CERISE outputs aim at medium to long-term upgrades of the C3S systems with targeted progressive implementation in the next three years and beyond. CERISE will improve the quality and consistency of the C3S reanalysis and multi-system seasonal prediction, directly addressing the evolving user needs for improved and more consistent C3S Earth system products.

DOI: https://doi.org/10.3030/101082139

Climate warming is driven by increased concentrations of greenhouse gasses (GHGs) e.g., CO2 and CH4, in the atmosphere. Existing observatories are able to capture GHG information for large-scale global assessments, but short-term natural variability and climate-driven changes in atmospheric CO2 and CH4 remain less known. There is also currently a lack of sufficiently precise, autonomous, and cost-efficient GHG sensors for GHG monitoring at sufficient spatial scale, and in hard-to-reach areas.

MISO will develop and demonstrate an autonomous in-situ observation platform for use in hard to reach areas (Arctic, wetlands), for detecting and quantifying carbon dioxide and methane gasses, using a combination of stationary and mobile (drone) solutions and requiring minimum on-site intervention when deployed.

To achieve this objective, MISO will improve detection limit and accuracy of a NDIR GHG sensor, which will then be used in three observing platforms (a static tower, a static chamber and a UAV-mounted sensor) operated with the help of a central base unit. All elements will be designed for operation in harsh environments and with minimum human intervention. The static observatories will be powered by a unique geothermal device.

Communication between the three observatories and a data cloud will use a combination of P2P, G4/G5/LTE, LORAWAN and wifi technologies. The specifications of the platform will be co-developed with stakeholders from academia, monitoring and measurement systems, industry and policy.

A clear DCE strategy and focus on short-term impact management and medium and long-term commercialization will target several user groups including industries and representatives of main monitoring systems and infrastructures (e.g., ICOS). This will support innovative governance models and science-based policy design, implementation and monitoring. Sustainability performance and competitiveness in the domains covered by HE Cluster 6 will be enhanced.

Project DOI: https://doi.org/10.3030/101086541