Heat, health, and humidity in Australia's monsoon tropics: a critical review of the problematization of 'heat' in a changing climate

Exposure to heat has killed more people in Australia than all other natural hazards combined. As the climate warms, temperatures are projected to rise substantially, increasing the impact of heat stress and heat illness nation-wide. The relation between heat and health is profoundly complex, however, and is understood differently across multiple sectors. This paper thus provides a critical review of how heat is currently measured and managed in Australia, highlighting how humidity, exposure, and exertion are key elements that are not consistently incorporated into 'problematizations' of heat. The presence or absence of these elements produces different spatial and temporal geographies of danger, as well as different governance practices. In particular, the invisibility of humidity as having a significant impact on heat and health shapes whether Australia's tropical monsoon zone is visible as a region at risk or not, and whether prolonged periods of seasonal heat are treated as dangerous. Similarly, different populations and practices become visible depending on whether the human body (its exposure, exertion, cooling, and hydration) is included in accounts of what constitutes 'heat.' As a result, the outdoor, manual workforce is visible as a population at risk in some accounts but not others. A brief review of key policy areas including housing, public health and work health and safety is presented to demonstrate how specific problematizations of heat are critical to the identification of, and response to, current and future climatic conditions. This has implications for how populations, places, and practices are constituted in the region

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution-individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.Published versio

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic

MODELING OF A TiO2-COATED QUARTZ -WOOL PACKED-BED PHOTOCATALYTIC REACTOR

A fixed-bed, photocatalytic laboratory reactor aimed to degrade pollutants from water streams was designed and built. Quartz wool coated with a thin film of TiO2 was employed as the reactor filling. The photocatalyst was placed in the reactor forming a loose packing to guarantee the intimate contact among reactants, photons, and the photocatalytic surface. This reactor was employed to study the photocatalytic decomposition of a model pollutant (formic acid). A reactor-radiation-reaction model was developed, which was comprised of the reactor mass balance, radiation model, and kinetic model for the degradation of formic acid. The local superficial rate of photon absorption, which was necessary to evaluate the kinetic, was obtained from the results of a radiation model. The Monte Carlo approach was employed to solve the radiation model, where the interaction between photons and the TiO2-coated fibers of the packing was considered. The kinetic model was derived from a plausible kinetic scheme. Experimental results obtained in the packed-bed reactor, operating in a differential mode and without mass transfer limitations, were used to estimate the parameters of the kinetic model. A satisfactory agreement was observed between model simulations with the derived parameters and experimental results, with a root mean square error less than 8.3%. The developed methodology can be used for scaling up purposes

Visible light TiO\u3csub\u3e2\u3c/sub\u3e photocatalysts assessment for air decontamination

\u3cp\u3eDifferent visible light responses of commercial TiO\u3csub\u3e2\u3c/sub\u3e photocatalysts are assessed for their application in air decontamination. To do that the modified TiO\u3csub\u3e2\u3c/sub\u3e catalysts were immobilized on borosilicate glass plates according to a dip coating method. Then, the photocatalytic performance of these plates was evaluated in a continuous gas flat plate photoreactor irradiated with visible light lamps using two representative air pollutants: nitrogen oxide and acetaldehyde. Working under visible light, the modified TiO\u3csub\u3e2\u3c/sub\u3e catalysts were compared by means of efficiency parameters: the true quantum efficiency, which relates the moles of degraded pollutant with the moles of the absorbed photons, and the apparent photonic efficiency, which relates the moles of degraded pollutant with the moles of incident photons. Also, the photocatalytic pollutants degradation by immobilized modified TiO\u3csub\u3e2\u3c/sub\u3e could be related with their optical properties, finding a clear correlation between them. These results are useful to decide which TiO\u3csub\u3e2\u3c/sub\u3e will be more efficient for a full scale air decontamination process under visible light illumination.\u3c/p\u3