An Assessment To Evaluate Potential Passive Cooling Patterns For Climate Change Adaptation In A Residential Neighbourhood Of A Mediterranean Coastal City (Athens, Greece)

This study investigates the potential for passive cooling patterns inside the urban fabric in the Mediterranean climate city of Athens (Greece), especially with regard to quantify air temperature reduction and thermal comfort amelioration at the neighbourhood scale. Using both field measurements and an urban microclimate simulation model, we assessed cooling and warming patterns in various sites of an Athens residential neighbourhood. Results show that, under Mediterranean climate conditions, urban design elements such as wooded courtyards and appropriately oriented urban design elements such as galleries have a considerable cooling effect and can be used as cool places inside the neighbourhood for occupants\u27 comfort amelioration and also as passive cooling tools for buildings to reduce summer energy consumption. They may then function as passive design strategies to adapt the urban site form to different climate change scenarios

An assessment to evaluate potential passive cooling patterns for climate change adaptation in a residential neighbourhood of a Mediterranean coastal city (Athens, Greece)

© 2018 Inderscience Enterprises Ltd. This study investigates the potential for passive cooling patterns inside the urban fabric in the Mediterranean climate city of Athens (Greece), especially with regard to quantify air temperature reduction and thermal comfort amelioration at the neighbourhood scale. Using both field measurements and an urban microclimate simulation model, we assessed cooling and warming patterns in various sites of an Athens residential neighbourhood. Results show that, under Mediterranean climate conditions, urban design elements such as wooded courtyards and appropriately oriented urban design elements such as galleries have a considerable cooling effect and can be used as cool places inside the neighbourhood for occupants\u27 comfort amelioration and also as passive cooling tools for buildings to reduce summer energy consumption. They may then function as passive design strategies to adapt the urban site form to different climate change scenarios

Evaluating the effects of different mitigation strategies on the warm thermal environment of an urban square in Athens, Greece

The present study examines the effect of different mitigation strategies on the microclimate and thermal sensation in an urban open area in Athens. The microclimatic model ENVI-met was applied to simulate thermal conditions for a warm summer day (15.07.2010). Thermal conditions were assessed based on air temperature and the Mediterranean thermal sensation scales of the Physiologically Equivalent Temperature (PET) and the Universal Thermal Climate Index (UTCI). The spatial and temporal resolution of PET throughout the square was developed per design scenario and was compared to the Current design layout to analyse and quantify the effectiveness of the mitigation strategies on the amelioration of thermal conditions. Results showed that the combination of the design scenarios was found to be the most advantageous mitigation strategy. The average PET and UTCI reduction of 6.9 °C and 6.1 °C, respectively, achieved a 15.5% improvement in thermal comfort. The aim of this research was to set specific targets on thermal sensation improvement and, based on the obtained results, it suggests certain mitigation strategies that will allow the specification of the appropriate microclimatic interventions to improve thermal comfort to the desired extent in the context of developing urban design guidelines

Pandemic Boredom: Little Evidence That Lockdown-Related Boredom Affects Risky Public Health Behaviors Across 116 Countries

Some public officials have expressed concern that policies mandating collective public health behaviors (e.g., national/regional "lockdown ") may result in behavioral fatigue that ultimately renders such policies ineffective. Boredom, specifically, has been singled out as one potential risk factor for noncompliance. We examined whether there was empirical evidence to support this concern during the COVID-19 pandemic in a large cross-national sample of 63,336 community respondents from 116 countries. Although boredom was higher in countries with more COVID-19 cases and in countries that instituted more stringent lockdowns, such boredom did not predict longitudinal within-person decreases in social distancing behavior (or vice versa; n = 8,031) in early spring and summer of 2020. Overall, we found little evidence that changes in boredom predict individual public health behaviors (handwashing, staying home, self-quarantining, and avoiding crowds) over time, or that such behaviors had any reliable longitudinal effects on boredom itself. In summary, contrary to concerns, we found little evidence that boredom posed a public health risk during lockdown and quarantine

Lives versus Livelihoods? Perceived economic risk has a stronger association with support for COVID-19 preventive measures than perceived health risk

This paper examines whether compliance with COVID-19 mitigation measures is motivated by wanting to save lives or save the economy (or both), and which implications this carries to fight the pandemic. National representative samples were collected from 24 countries (N = 25,435). The main predictors were (1) perceived risk to contract coronavirus, (2) perceived risk to suffer economic losses due to coronavirus, and (3) their interaction effect. Individual and country-level variables were added as covariates in multilevel regression models. We examined compliance with various preventive health behaviors and support for strict containment policies. Results show that perceived economic risk consistently predicted mitigation behavior and policy support—and its effects were positive. Perceived health risk had mixed effects. Only two significant interactions between health and economic risk were identified—both positive

A pan-European epidemiological study reveals honey bee colony survival depends on beekeeper education and disease control

Reports of honey bee population decline has spurred many national efforts to understand the extent of the problem and to identify causative or associated factors. However, our collective understanding of the factors has been hampered by a lack of joined up trans-national effort. Moreover, the impacts of beekeeper knowledge and beekeeping management practices have often been overlooked, despite honey bees being a managed pollinator. Here, we established a standardised active monitoring network for 5 798 apiaries over two consecutive years to quantify honey bee colony mortality across 17 European countries. Our data demonstrate that overwinter losses ranged between 2% and 32%, and that high summer losses were likely to follow high winter losses. Multivariate Poisson regression models revealed that hobbyist beekeepers with small apiaries and little experience in beekeeping had double the winter mortality rate when compared to professional beekeepers. Furthermore, honey bees kept by professional beekeepers never showed signs of disease, unlike apiaries from hobbyist beekeepers that had symptoms of bacterial infection and heavy Varroa infestation. Our data highlight beekeeper background and apicultural practices as major drivers of honey bee colony losses. The benefits of conducting trans-national monitoring schemes and improving beekeeper training are discussed

Identifying important individual‐ and country‐level predictors of conspiracy theorizing: a machine learning analysis

Psychological research on the predictors of conspiracy theorizing—explaining important social and political events or circumstances as secret plots by malevolent groups—has flourished in recent years. However, research has typically examined only a small number of predictors in one, or a small number of, national contexts. Such approaches make it difficult to examine the relative importance of predictors, and risk overlooking some potentially relevant variables altogether. To overcome this limitation, the present study used machine learning to rank-order the importance of 115 individual- and country-level variables in predicting conspiracy theorizing. Data were collected from 56,072 respondents across 28 countries during the early weeks of the COVID-19 pandemic. Echoing previous findings, important predictors at the individual level included societal discontent, paranoia, and personal struggle. Contrary to prior research, important country-level predictors included indicators of political stability and effective government COVID response, which suggests that conspiracy theorizing may thrive in relatively well-functioning democracies

Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic

Before vaccines for coronavirus disease 2019 (COVID-19) became available, a set of infection-prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine-learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection-prevention behavior in 56,072 participants across 28 countries, administered in March to May 2020. The machine-learning model predicted 52% of the variance in infection-prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individual-level injunctive norms. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically derived predictors were relatively unimportant