Abstract
<p>Atmospheric new particle formation (NPF) generates secondary aerosol particles into the lower atmosphere via gas-to-particle phase transition. Secondary aerosol particles dominate the total particle number concentration and are an important source for cloud condensation nuclei <sup>[1]</sup>. NPF typically begins with clustering among gaseous molecules. Once the newly formed clusters attain a size larger than the critical cluster size (~1.5 nm), their growth to larger sizes is energetically favoured and eventually they become nanoparticles <sup>[2]</sup>. NPF is often observed with the participation of air ions <sup>[3]</sup> and sometimes is induced by ions <sup>[4]</sup>. Air ions are a constituent of atmospheric electricity. The presence of the Earth-atmosphere electric field poses an electrical force on air ions. The earth-atmosphere electric field exhibits variability at different time scales under fair-weather conditions <sup>[5]</sup>. It is therefore interesting to understand whether the Earth-atmosphere electric field influences atmospheric new particle formation.</p> <p>We analysed the Earth-atmosphere electric field together with the number size distribution data of air ions and aerosol particles under fair-weather conditions measured at Hyytiälä SMEAR II station in Southern Finland <sup>[6]</sup>. The electric field were measured by two Campbell CS 110 field mills in parallel. Air ion data were obtained with a Balance Scanning Mobility Analyser (BSMA) and a Neutral and Air Ion Spectrometer (NAIS), and aerosol particle data with a Differential Mobility Particle Sizer (DMPS). We used condensation Sinks (CS) derived from the DMPS measurement, air temperature, relative humidity, wind speed, global radiation as well as brightness derived from the global radiation measurement to assist the analysis. The measured earth-atmosphere electric field on NPF days was higher than on non-NPF days. We found that under low CS conditions, the electric field can enhance the formation of 1.7-3 nm air ions, but the concentration of 1.7-3 nm ions decreased with an increasing electric field under high CS conditions.</p> <p>References:</p> <p>[1]       Kerminen V.-M. et al., Environ. Res. Lett. <strong>2018</strong>, 13, 103003.</p> <p>[2]       Kulmala M. et al., Science <strong>2013</strong>, 339, 943-946.</p> <p>[3]       Manninen H. E. et al., Atmos. Chem. Phys. <strong>2010</strong>, 10, 7907-7927.</p> <p>[4]       Jokinen T. et al., Science Advances <strong>2018</strong>, 4, eaat9744.</p> <p>[5]       Bennett A. J., Harrison R. G., Journal of Physics: Conference Series <strong>2008</strong>, 142, 012046.</p> <p>[6]       Hari P., Kulmala M., Boreal Environ. Res. <strong>2005</strong>, 10, 315-322.</p>

Abstract
<p>Although the Earth system is described to react relatively abruptly to present anthropogenic forcings, the notion of abruptness remains questionable as it refers to a time scale that is difficult to constrain properly. Recognizing this issue, the tipping elements as listed in Lenton et al. (2008) rely on long-term observations under controlled conditions, which enabled the associated tipping points to be identified. For example, there is evidence nowadays that if the rate of deforestation from forest fires and the climate change does not decrease, the Amazonian forest will reach a tipping point towards savanna (Nobre, 2019), which would impact the regional and global climate systems as well as various other ecosystems, directly or indirectly (Magalhães et al., 2020). However, if the present tipping elements, which are now evidenced, are mostly related to the present climate change and thus directly or indirectly related to anthropogenic forcing, their interpretation must still rely on former cases detected in the past, and especially from studies of abrupt climatic transitions evidenced in paleoclimate proxy records. Moreover, recent studies of past changes have shown that addressing abrupt transitions in the past raises the issue of data quality of individual records, including the precision of the time scale and the quantification of associated uncertainties. Investigating past abrupt transitions and the mechanisms involved requires the best data quality possible. This can be a serious limitation when considering the sparse spatial coverage of high resolution paleo-records where dating is critical and corresponding errors often challenging to control. In theory, this would therefore almost limit our investigations to ice-core records of the last climate cycle, because they offer the best possible time resolution. However, evidence shows that abrupt transitions can also be identified in deeper time with lower resolution records, but still revealing changes or transitions that have impacted the dynamics of the Earth system globally. TiPES Work Package 1 will address these issues and collect paleorecords permitting to evidence the temporal behavior of tipping elements in past climates, including several examples.</p> <p>Lenton T. et al. (2008). PNAS 105, 1786-1793.</p> <p>Nobre C. (2019). Nature 574, 455.</p> <p>Magalhães N.d. et al. (2020). Sci. Rep. 16914 (2019) doi:10.1038/s41598-019-53284-1</p> <p>This work is performed under the TiPES project funded by the European Union’s Horizon 2020 research and innovation program under grant agreement # 820970 <https://tipes.sites.ku.dk/></p>

Abstract
System identification approaches have been used to design an experiment, generate data, and estimate dynamical system models for Just Walk, a behavioral intervention intended to increase physical activity in sedentary adults. The estimated models serve a number of important purposes, such as understanding the factors that influence behavior and as the basis for using control systems as decision algorithms in optimized interventions. A class of identification algorithms known as matchable-observable linear identification has been reformulated and adapted to estimate linear time-invariant models from data obtained from this intervention. The experimental design, estimation algorithms, and validation procedures are described, with the best models estimated from data corresponding to an individual intervention participant. The results provide insights into the individual and the intervention, which can be used to improve the design of future studies.

Abstract

Abstract
In view to the decentralised problem of gas network optimisation, we model the problem as differential game where the players are the network controllable elements that communicate through nearest-neighbour network components. The controllable elements are sources and compressors. But since these do not have the same relevance within the network, it will be interesting to use a game hierarchical framework, i.e., to model the network operation as a Stackelberg game. Also, the disturbed version of the same problem suits the problem better because is is assumed that the network works with nominated operational levels. The variations of the real operation can then be viewed as disturbances to these system operational levels.

Abstract
The Kyrgyz Republic, as well as other countries of Central Asia, is highly exposed to natural-environmental hazards, which continues undermining efforts to achieve sustainable development. National disaster risk assessment procedures in Central Asian countries are mainly based on the evaluation of hazards without a detailed analysis of vulnerability and resilience. Additionally, the available practices of hazard assessments are mostly based on a zone-by-zone approach, which would make it difficult to develop a comparative assessment of facilities located in the same hazard zone. This situation hampers the efforts of the local governments to effectively plan and implement disaster risk reduction (DRR) actions when they cannot differentiate the individual facilities according to the risk level in order to focus the existing capacity (which is usually very limited) on increasing the resilience and reducing the vulnerability of the facilities with the highest risk. For improvement of DRR practices, the quantitative comprehensive approach of risk analysis applied in this study is used for risk assessment of educational institutions in one of the most seismically active and most disaster-prone mountain regions of Central Asia - the Alay valley, a wide intermontane valley situated in between the two biggest mountain systems in Asia: Tian Shan and Pamir. The developed multidisciplinary study suggests that the quantitative multi-risk assessment approach - can play a crucial role in understanding risks and can significantly improve the quality of disaster risk reduction planning.