Diagnostic of meteorological extremes for urban heat island case study: Lisbon

A execução deste estudo teve como objectivo a avaliação do fenómeno da "ilha de calor urbano" no que respeita ao seu comportamento, i.e., à sua variação, forma e intensidade. Numa primeira fase foram analisadas as séries de dados meteorológicos relativos à temperatura do ar (máxima e mínima diária) a 1.5 metros de altura em algumas estações da região da Grande Lisboa no período entre 1941 e 2001, com o intuito de detectar e avaliar as tendências associadas a cada série de dados. Para a execução desta primeira fase foi necessário implementar um algoritmo para recuperar os registos com falhas, chamado modelo integrado de recuperação de séries (MIRS), que na sua essência se dividiu em dois momentos: interpolação temporal recorrendo a autocorrelação, e interpolação espacial baseado na distância horizontal e vertical entre estações meteorológicas. Numa segunda fase deste estudo, recorrendo às séries de dados meteorológicos do ano de 2002, resultado das observações executadas nas estações meteorológicas automáticas do IM instaladas na região de Lisboa com a integração em períodos de 10 minutos, procurou-se observar a interacção do fenómeno da "ilha de calor urbano" no que respeita ao seu comportamento com a situação meteorológica e outros parâmetros meteorológicos, designadamente campo do vento (intensidade e direcção) à superfície. O resultado da análise de tendência, aplicado à série da média anual da temperatura mínima do ar entre 1958-2001, traduz-se num aumento de 1.0°C na estação meteorológica instalada no Geofísico, centro da cidade Lisboa. Este facto é parcialmente corroborado pelo processo do fenómeno de ilha de calor urbano cuja a intensidade apresenta uma forte dependência sazonal e diária, bem como circulações de anticiclone, vento fraco e céu pouco nublado. /*** Abstract - In this study is proposed to research the influence of urban heat advection on the air temperature time series, or to observe the space-time behavior, shape, intensity and form, of the Urban Heat Island phenomenon. The procedures for evaluating extreme air temperature time series obey a sequential strategy divided in two phases: the first one uses the annual series of extreme air temperature anomalies for each meteorological station and analyzed the respective tendencies. Moreover, the first phase was still subdivided in two moments to deal with the reconstruction of climate time series, taking into account daily data sets: interpolation considering the autocorrelation time-memory; and the spatial interpolation procedure based upon the "optimum distance" between stations. Hence, an integrated modal for the reconstruction of time series was developed, which conjugates small-scale space-time interaction between meteorological stations. In the second phase was used the air temperature time series of the several station to studied, empirically by comparing the hourly meteorological data series from the Meteorological Institute (2002) obtained through the automatic meteorological stations installed in the metropolitan area of Lisbon, the space/time behavior of the Urban Heat Island phenomenon duo to the different wind regimes and synoptic situations that affect Lisbon. Particular situations of wind direction and regimes are analysed and associated with the heat urban island phenomenon. Because the urban areas around the site expanded in the past century, urban heat advection trends contaminate the long-term trends in the air temperature series, the linear trend obtained was 0.0233°C/year in the minimum air temperature annual average. The Urban Heat Island phenomenon is observed in the large metropolitan areas, and it can be described as a thermal anomaly [AT] between a well characterized urban area and the rural background, in which the air near the ground in urban areas has high values than rural areas

Higher airborne pollen concentrations correlated with increased SARS-CoV-2 infection rates, as evidenced from 31 countries across the globe

Pollen exposure weakens the immunity against certain seasonal respiratory viruses by diminishing the antiviral interferon response. Here we investigate whether the same applies to the pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is sensitive to antiviral interferons, if infection waves coincide with high airborne pollen concentrations. Our original hypothesis was that more airborne pollen would lead to increases in infection rates. To examine this, we performed a cross-sectional and longitudinal data analysis on SARS-CoV-2 infection, airborne pollen, and meteorological factors. Our dataset is the most comprehensive, largest possible worldwide from 130 stations, across 31 countries and five continents. To explicitly investigate the effects of social contact, we additionally considered population density of each study area, as well as lockdown effects, in all possible combinations: without any lockdown, with mixed lockdown−no lockdown regime, and under complete lockdown. We found that airborne pollen, sometimes in synergy with humidity and temperature, explained, on average, 44% of the infection rate variability. Infection rates increased after higher pollen concentrations most frequently during the four previous days. Without lockdown, an increase of pollen abundance by 100 pollen/m3 resulted in a 4% average increase of infection rates. Lockdown halved infection rates under similar pollen concentrations. As there can be no preventive measures against airborne pollen exposure, we suggest wide dissemination of pollen−virus coexposure dire effect information to encourage high-risk individuals to wear particle filter masks during high springtime pollen concentrations.</p