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Microplastic (MPs) contamination is ubiquitous in most terrestrial and aquatic ecosystems. Recently MPs have been reported at high altitudes which indicates that air masses can transport and deposit MPs in the surface snow of high mountain ecosystems, however, whether MPs typification and abundance can be influenced by direction and origin of air masses still remains an open question. Here we present the first report of MPs above 5000 m a.s.l from surface snow of a glacier in the tropical Andes. We collected surface snow along an elevational gradient, from 5000 to 5400 m a.s.l., in the Antisana Glacier, in the northern Andes cordillera of Ecuador to analyze MPs abundance and polymeric identification with the Fourier Transform Infrared (FTIR) and also to hypothesized the possible MPs sources in this remote area by comparing the oxygen and hydrogen stable isotopic ratio composition of the snow samples and by analyzing the wind direction. We observed an average of 131 ± 24 MPs L-1 in our samples. Fibers corresponded to 70% of all MP shapes; FTIR results showed that MPs composition mainly included polyurethane, polyethylene, polyamide, polyester, and high-density polyethylene in surface snow. There were no statistically significant differences of MPs abundance among sampled elevations, and the isotopic ratio composition did not differ among locations. Our results suggest that MP that accumulated in the glacier may be transported from the east, across the Amazonia, by the prevalent eastward air flow. The absence of industrial cities at least 2000 km further east from Antisana, indicates that the remote Andean glaciers could constitute important depositional zones for long-distance transported contaminants.

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Resumen En Colombia, hay una carencia en los estudios climatológicos del viento, ya que, los que existen actualmente no aplican técnicas estadísticas ni periodos representativos adecuados. Por consiguiente, el presente estudio analiza el comportamiento climatológico del viento en la ciudad de Bogotá, para el periodo 2010 a 2016, buscando describir estadística, espacial y vectorialmente esta variable climatológica. Para empezar se realizó un análisis estadístico del conjunto de datos, de la velocidad del viento, mediante el software Windographer©, utilizando las técnicas exploratorias para la distribución Weibull, describiendo así los parámetros estadísticos de las estaciones en las principales zonas de la ciudad. Del mismo modo, se elaboraron las rosas de los vientos por estación, con el software WRPLOT™; y para finalizar se realizó un mapa vectorial mediante el método de interpolación Co-Kriging utilizando el sistema de información geográfica ArcGis®. Observando que el régimen de circulación atmosférico en Bogotá está estrechamente relacionado con la presencia de los cerros orientales y con la predominancia de los vientos alisios; así mismo, se encontró que la mayor velocidad del viento se presenta al suroeste, y las magnitudes más débiles, al norte y en cercanía a los cerros orientales.

Abstract In Colombia, there is a lack in wind weather studies, since those that currently exist do not apply statistical techniques or adequate representative periods. Therefore, the present study analyzes the wind weather behavior in the city of Bogotá, for the period 2010 to 2016, seeking to describe this weather variable statistically spatially and vectorially. To begin with, a statistical analysis of the data set, of the wind speed, was performed using the Windographer© software, using the exploratory techniques for the Weibull distribution, thus describing the statistical parameters of the stations in the main areas of the city. Similarly wind roses were made per season, using the WRPLOT ™ software; and, finally, a vector map was made using the Co-Kriging interpolation method, using the ArcGis® geographic information system. Noting that the atmospheric circulation regime in Bogotá is closely related to the presence of the eastern hills and the predominance of trade winds; Likewise, it was found that the highest wind speed is presented to the southwest, and the weakest magnitudes, to the north and in proximity to the eastern hills.

Resumo Na Colômbia, há falta de estudos sobre o clima do vento, uma vez que os existentes atualmente não aplicam técnicas estatísticas ou períodos representativos adequados. Portanto, o presente estudo analisa o comportamento do clima eólico na cidade de Bogotá, no período de 2010 a 2016, buscando descrever esta variável climática de forma estatística, espacial e vetorial. Para começar foi realizada uma análise estatística do conjunto de dados, da velocidade do vento, utilizando o software Windographer©, utilizando as técnicas exploratórias para a distribuição de Weibull, descrevendo assim os parâmetros estatísticos das estacoes nas principais áreas da cidade. Da mesma forma, foram feitas rosas de vento por temporada, usando o software WRPLOT ™; e, finalmente, foi feito um mapa vetorial usando o método de interpolação Co-Kriging, usando o sistema de informação geográfica ArcGis®. Observando que o regime de circulação atmosférica em Bogotá está intimamente relacionado com a presença dos montes orientais e predominância de ventos alísios; da mesma forma, verificou-se que a maior velocidade do vento é apresentada na região sudeste, e as magnitudes mais fracas, ao norte e nas proximidades das colinas orientais.

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This paper presents wind speed and direction data measured with a weather station located in Puerto Bolivar, department of La Guajira, situated in the extreme north of Colombia, whose geographic coordinates are 12°11'N 71°55'W. A wind speed and direction sensor, a barometric pressure sensor, and a temperature sensor were used to obtain the presented data. These data were taken at the height of 10 m, which is the highest point of the weather station. The data taken by the meteorological station correspond to a period of 20 years (1993-2013), with hourly frequency. For the missing data, a mathematical model to estimate the Julian averages was developed, allowing to calculate the frequency histograms and four types of probability distributions for these data. Also, the representative wind roses were generated, taking into account the averages in each of the 12 months of the year.

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Abstract INTRODUCTION: Meteorological influences along with the lack of basic sanitation has contributed to disease outbreaks, resulting in large socio-economic losses, especially in terms of dengue. This study aimed to evaluate the meteorological influences on the monthly incidence of dengue in Arapiraca-AL, Brazil during 2008-2015. METHODS: We used generalized linear models constructed via logistic regression to assess the association between the monthly incidence of dengue (MID) of and 8 meteorological variables [rainfall (R), air temperature (AT), dew point temperature (DPT), relative humidity (RH), pressure surface, wind speed (WS), wind direction (WD), and gust], based on data obtained from DATASUS and meteorological station databases, respectively. The dengue-1 model included R, AT, DPT, and RH and the dengue-2 model included AT, DPT, RH, WS, and WD. A MID >100 (classified as moderate incidence) indicated an abnormal month. RESULTS: Based on the dengue-1 model, variables with the highest odds ratio included R-lag1, DPT-lag1, and AT-lag1 with a 10.1, 18.3, and 26.7 times greater probability of a moderate MID, respectively. Based on the dengue-2 model, variables with the highest odds ratio were AT-lag1 and RH-lag0 indicating an 8.9 and 18.1 times greater probability of a moderate MID, respectively. CONCLUSIONS: AT, DPT, R, RH and WS influenced the occurrence of a moderate MID.

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Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B(3) spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms(-1). Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms.

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