Considering the role of presence and absence in space constructions: ethnography as methodology in human geography

In this article, we discuss methodological issues and problems in researching relational space. We argue that despite all innovations after recent spatial turns, research on space is often still marked by what we call ‘presentism’ and ‘concretism’. Instead, we seek to show how spatial encounters today are more and more marked and shaped by different absences. Using some insights from the poststructuralist take on assemblages we argue that any spatial method to understand spatial complexity is incomplete if the role of absences in shaping spatial presences and spatial encounters is left unconsidered. Addressing ques-tions of methodology and methods we vote for the ethnographic approach which, to us, has the strongest potential to undertake spatial research sensitive to the problem of present absences, i.e. that the complexity of places is often shaped by absent spatial events

Causes and importance of new particle formation in the present-day and preindustrial atmospheres

New particle formation has been estimated to produce around half of cloud-forming particles in the present-day atmosphere, via gas-to-particle conversion. Here we assess the importance of new particle formation (NPF) for both the present-day and the preindustrial atmospheres. We use a global aerosol model with parametrizations of NPF from previously published CLOUD chamber experiments involving sulfuric acid, ammonia, organic molecules, and ions. We find that NPF produces around 67% of cloud condensation nuclei at 0.2% supersaturation (CCN0.2%) at the level of low clouds in the preindustrial atmosphere (estimated uncertainty range 45-84%) and 54% in the present day (estimated uncertainty range 38-66%). Concerning causes, we find that the importance of biogenic volatile organic compounds (BVOCs) in NPF and CCN formation is greater than previously thought. Removing BVOCs and hence all secondary organic aerosol from our model reduces low-cloud-level CCN concentrations at 0.2% supersaturation by 26% in the present-day atmosphere and 41% in the preindustrial. Around three quarters of this reduction is due to the tiny fraction of the oxidation products of BVOCs that have sufficiently low volatility to be involved in NPF and early growth. Furthermore, we estimate that 40% of preindustrial CCN0.2% are formed via ion-induced NPF, compared with 27% in the present day, although we caution that the ion-induced fraction of NPF involving BVOCs is poorly measured at present. Our model suggests that the effect of changes in cosmic ray intensity on CCN is small and unlikely to be comparable to the effect of large variations in natural primary aerosol emissions. Plain Language Summary New particle formation in the atmosphere is the process by which gas molecules collide and stick together to form atmospheric aerosol particles. Aerosols act as seeds for cloud droplets, so the concentration of aerosols in the atmosphere affects the properties of clouds. It is important to understand how aerosols affect clouds because they reflect a lot of incoming solar radiation away from Earth's surface, so changes in cloud properties can affect the climate. Before the Industrial Revolution, aerosol concentrations were significantly lower than they are today. In this article, we show using global model simulations that new particle formation was a more important mechanism for aerosol production than it is now. We also study the importance of gases emitted by vegetation, and of atmospheric ions made by radon gas or cosmic rays, in preindustrial aerosol formation. We find that the contribution of ions and vegetation to new particle formation was also greater in the preindustrial period than it is today. However, the effect on particle formation of variations in ion concentration due to changes in the intensity of cosmic rays reaching Earth was small.Peer reviewe

Wie entsteht Burnout im Jugendamt?

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Mothers Matter: Using Regression Tree Algorithms to Predict Adolescents’ Sharing of Drunk References on Social Media

Exposure to online drinking on social media is associated with real-life alcohol consumption. Building on the Theory of planned behavior, the current study substantially adds to this line of research by identifying the predictors of sharing drunk references on social media. Based on a cross-sectional survey among 1639 adolescents with a mean age of 15 (59% female), this study compares and discusses multiple regression tree algorithms predicting the sharing of drunk references. More specifically, this paper compares the accuracy of classification and regression tree, bagging, random forest and extreme gradient boosting algorithms. The analysis indicates that four concepts are central to predicting adolescents’ sharing of drunk references: (1) exposure to them on social media; (2) the perceived injunctive norms of the mother towards alcohol consumption; (3) the perceived descriptive norms of best friends towards alcohol consumption; and (4) willingness to drink alcohol. The most accurate results were obtained using extreme gradient boosting. This study provides theoretical, practical, and methodological conclusions. It shows that maternal norms toward alcohol consumption are a central predictor for sharing drunk references. Therefore, future media literacy interventions should take an ecological perspective. In addition, this analysis indicates that regression trees are an advantageous method in youth research, combining accurate predictions with straightforward interpretations

#Coronavirus: Monitoring the Belgian Twitter Discourse on the Severe Acute Respiratory Syndrome Coronavirus 2 Pandemic

In this study, a social media analysis is conducted to examine the public discourse about the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic on Twitter. In particular, this study aims to examine (a) how the number of tweets varies as a function of the timeline of the pandemic and associated measures and (b) how the content of these tweets, including displayed emotions, changes. Therefore, 373,908 tweets and retweets from Belgium were collected from February 25, 2020 to the March 30. Time series analysis, network bigrams, topic models, and emotional lexica were deployed for analysis. The results showed that significant events related to the virus correlated with an immediate increase in the number of tweets addressing them. Furthermore, the Belgian Twitter discourse was characterized by positively connoted words, which also refer to European solidarity. These findings do not only stress the relevance of Twitter as a medium for public discourse during lockdowns, but also seem to indicate that the Belgian public supports policy measures that respect solidarity in Europe.status: Published onlin