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2020
Multisensory Representation of Air Pollution in Virtual Reality: Lessons from Visual Representation
The world is facing the problem of anthropogenic climate
change and air pollution. Despite many years of development, already
established methods of influencing behaviour remain ineffective. The
effect of such interventions is very often a declaration of behaviour change
that is not followed by actual action. Moreover, despite intensive informa-
tion campaigns, many people still do not have adequate knowledge on the
subject, are not aware of the problem or, worse, deny its existence. Pre-
vious attempts to introduce real change were based on providing infor-
mation, persuasion or visualisation. We propose the use of multi-sensory
virtual reality to investigate the problem more thoroughly and then design
appropriate solutions. In this paper, we introduce a new immersive virtual
environment that combines free exploration with a high level of experi-
mental control, physiological and behavioural measures. It was created on
the basis of transdisciplinary scientific cooperation, participatory design
and research. We used the unique features of virtual environments to
reverse and expand the idea of pollution pods by Pinsky. Instead of closing
participants in small domes filled with chemical substances imitating pol-
lution, we made it possible for them to freely explore an open environment
- admiring the panorama of a small town from the observation deck located
on a nearby hill. Virtual reality technology enables the manipulation of
representations of air pollution, the sensory modalities with which they are
transmitted (visual, auditory, tactile and smell stimuli) and their intensity.
Participants’ reactions from the initial tests of the application showed that
it is a promising solution. We present the possibilities of applying the new
solution in psychological research and its further design and development
opportunities in collaboration with communities and other stakeholders
in the spirit of citizen science.
2022
2024
Towards an integrated data-driven infrastructure (InfraNor)
The Arctic is warming almost four times faster compared to the rest of the world (Rantanen et al. 2022). Svalbard and its surroundings have warmed faster than most of the Arctic (Cai et al. 2021; Isaksen et al. 2022). The Svalbard archipelago also shows large temperature variations from south to north and east to west (Østby et al. 2017). Svalbard has good infrastructure, logistics and communications (airport, port, laboratories), and excellent possibilities for data transfer. This makes Svalbard and its surroundings an attractive living natural laboratory for long-term and campaign-based Arctic studies.
2025
Review on the methodology supporting the health impact assessment by the European Environment Agency
2020
Estimation of pollutant releases into the atmosphere is an important problem in the environmental sciences. It is typically formalized as an inverse problem using a linear model that can explain observable quantities (e.g., concentrations or deposition values) as a product of the source-receptor sensitivity (SRS) matrix obtained from an atmospheric transport model multiplied by the unknown source-term vector. Since this problem is typically ill-posed, current state-of-the-art methods are based on regularization of the problem and solution of a formulated optimization problem. This procedure depends on manual settings of uncertainties that are often very poorly quantified, effectively making them tuning parameters. We formulate a probabilistic model, that has the same maximum likelihood solution as the conventional method using pre-specified uncertainties. Replacement of the maximum likelihood solution by full Bayesian estimation also allows estimation of all tuning parameters from the measurements. The estimation procedure is based on the variational Bayes approximation which is evaluated by an iterative algorithm. The resulting method is thus very similar to the conventional approach, but with the possibility to also estimate all tuning parameters from the observations. The proposed algorithm is tested and compared with the standard methods on data from the European Tracer Experiment (ETEX) where advantages of the new method are demonstrated. A MATLAB implementation of the proposed algorithm is available for download.
2020
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2024
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2019
Aerosols are an important constituent of the atmosphere both influencing the climate system and contributing to increasing pollution of the Arctic. At the same time, their adequate monitoring is a big challenge, as instruments on the ground only can sample aerosols in the lowermost atmosphere. For this reason, these measurements are complemented with observations of aerosol optical depth (AOD) which quantify the total amount of aerosols throughout the atmosphere from the attenuation of direct sunlight (and moonlight). This procedure requires extremely careful instrument calibration and removal of cloud contaminated data. In Svalbard, such measurements have been performed by several research groups with different instruments, mostly in Ny-Ålesund and in Hornsund, but also on research vessels offshore. In the framework of the SSF Strategic Grant project ReHearsol, all AOD data from the Svalbard region since 2002 have been collected and made available to the SIOS research community. They indicate that number and intensity of Arctic haze episodes occurring in late winter and spring have decreased consistently and significantly in the last 20 years, while pollution events in summer/early autumn, caused by boreal biomass burning, are on the rise, though not as consistently. Comparison between in-situ measurements at Gruvebadet Atmosphere Laboratory in Ny-Ålesund and AOD measurements indicate that most (more than 65%) of the episodes with high aerosol load are not captured by surface measurements. This finding does not change when one includes in-situ measurements at Zeppelin Observatory (475 m a.s.l.). Studying extensive high-AOD episodes such as those in summer 2019 requires a multi-tool approach including in-situ and remote-sensing measurements combined with model tools.
2023
2018
Adequate infrastructure for citizen science is constantly growing and has become increasingly important in providing support to citizen science activities, both nationally and internationally. Many types of citizen science infrastructures exist, with different functionalities. This chapter focuses on current citizen science platforms. The platforms addressed in this chapter are those which display citizen science data and information, provide good practical examples and toolkits, collect relevant scientific outcomes, and are accessible to different stakeholders, ranging from interested citizens to scientific institutions to authorities, politicians, and public media. We present current citizen science platforms in Europe and associated (inter)national citizen science networks and discuss how these platforms have become increasingly vital within citizen science. Based on these examples, we elaborate on challenges for citizen science platforms, such as establishing and financing platforms, designing user interfaces, maintaining platforms, promoting the usage of platforms, etc. We conclude with an outlook into potential development needs of citizen science platforms in the future.
2021
2019