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A series of 3D obstacle limitation surfaces (OLS) define the limits to which objects may project in the airspace in order to configure the airspace around aerodromes that must be kept free from obstacles. The aim is to ensure that aircraft can safely carry out their scheduled operations, and to prevent the aerodromes from becoming unusable due to the proliferation of obstacles in the surrounding area. One such possible obstacle is the vegetation growing in the zone. This work consists of a study of the variation in the vegetation in the El Prat airport (Barcelona-El Prat Josep Tarradellas) and the surrounding area in the years 2011-2018, and of the way in which it has influenced the configuration of the OLS. Until 2010, obstacle studies were carried out every four years but the growth of plant obstacles during this period was not controlled. Although the rate of tree growth depends on several factors such as age, species, site quality and forestry treatment, the parameter analysed in this research is height, as this is what will interfere in the OLS. This study therefore focuses on measuring the height and geolocation of the obstacle in order to determine its influence on the OLS, and on determining the subsequent actions, if any, that need to be taken in regard to this vegetation element to avoid it becoming a risk to operational safety. As a result, the growth and vulnerability of 84 vegetation obstacles from 794 terrain elements have been detected. The result of this study is the design, using geographic information systems, of a tool to assist airport managers in the automated control and monitoring of the vegetation in the obstacle limitation surfaces to avoid compromising the safety of airport operations and mitigating environmental impacts.

Se critican los intentos concienciadores desde las vanguardias auto-proclamadas. Se ofrece un esquema de cómo son las relaciones de comunicación actuales y unas posibles estrategias con “conjuntos de acción” que venimos practicando desde las metodologías participativas. La construcción de la conciencia social parte de lo biológico y pre-consciente en los ciclos vitales básicos, y mediante “ritos de paso” construye las conciencias colectivas en las que nos movemos. Se acaba proponiendo trabajar con “grupos motores” en las democracias participativas.

Optic neuropathies, such as glaucoma, are some of the leading causes of irreversible blindness worldwide. There has been a lot of research for potential therapies that could attenuate and even reduce the impact of the pathological pathways that lead to the loss of retinal ganglion cells (RGCs). In recent years, vitamin B3 (nicotinamide) has gained some interest as a viable option for these neurodegenerative diseases due to its fundamental role in enhancing the mitochondria metabolism of the RGCs. This review focuses on elucidating the impact of vitamin B3 on retinal cells, especially when in a dysfunctional state like what happens in optic neuropathies, especially glaucoma. This review also summarizes the existing and future research on the clinical effects of vitamin B3 in these optic neuropathies, and determines appropriate recommendations regarding its dosing, efficacy, and eventual side effects. [ABSTRACT FROM AUTHOR]

The aim of this work was to analyze the changes in the emissions from the transport sector during the COVID-19 lockdown in Colombia. We compared estimated emissions from road transportation of four groups of pollutants, namely, greenhouse gases (CO2, CH4, N2O), ozone precursor gases (CO, NMVOC, NOx), aerosols (BC, PM2.5, PM10), and acidifying gases (NH3, SO2), during the first half of 2020 with values obtained in the same period of 2018. The estimate of emissions from road transportation was determined using a standardized methodology consistent with the 2006 Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories and the European Environment Agency/European Monitoring and Evaluation Program. We found a substantial reduction in GHG emissions for CH4, N2O, and CO2 by 17%, 21%, and 28%, respectively. The ozone precursors CO and NMVOC presented a decrease of 21% and 22%, respectively, while NOx emissions were reduced up to 15% for the study period. In addition, BC decreased 15%, and there was a reduction of 17% for both PM10 and PM2.5 emissions. Finally, acidifying gases presented negative variations of 19% for SO2 and 23% for NH3 emissions. Furthermore, these results were consistent with the Ozone Monitoring Instrument (OMI) satellite observations and measurements at air quality stations. Our results suggest that the largest decreases were due to the reduction in the burning of gasoline and diesel oil from the transport sector during the COVID-19 lockdown. These results can serve decision makers in adopting strategies to improve air quality related to the analyzed sector.

Snow albedo is an important variable in the coupled atmosphere-earth system at the global level. Moreover, studying its behavior allows us to know the state of the cryosphere. The Sierra Nevada de Santa Marta (SNSM) is a glacier area and the northernmost tropical (10.82° N, 73.75° W) region in South America. It has a height of up to 5775 m.a.sl., which is the second highest mountain in the world near the marine coast. We analyzed variations in snow albedo related to snow cover, snowfall, temperature, light-absorbing impurities such as blank carbon (BC), organic carbon (OC) and dust, and El Niño—Southern Oscillation (ENSO) phenomenon through 20 years (2000–2020). We mainly use daily data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua NASA satellites. Results showed through correlations that snow albedo has decreased due to Land Surface Temperature (55%, p < 0.001), a positive phase of ENSO (42%, p < 0.001) and dust (37%, p < 0.01) in the SNSM. Additionally, a dust negative effect was more evident on the southern side (up to 49%, p < 0.001) of the SNSM. Backward trajectories by the NOAA HYSPLIT model suggest that dust sources would be soil erosion in the surrounding region. Results can help recognize the influence of ENSO and dust in the glacier decrease of the SNSM.

The kriging methodology can be applied to predict the value of a spatial variable at an unsampled location, from the available spatial data. Furthermore, additional information from secondary variables, correlated with the target one, can be included in the resulting predictor by using the cokriging techniques. The latter procedures require a previous specification of the multivariate dependence structure, difficult to characterize in practice in an appropriate way. To simplify this task, the current work introduces a nonparametric kernel approach for prediction, which satisfies good properties, such as asymptotic unbiasedness or the convergence to zero of the mean squared prediction error. The selection of the bandwidth parameters involved is also addressed, as well as the estimation of the remaining unknown terms in the kernel predictor. The performance of the new methodology is illustrated through numerical studies with simulated data, carried out in different scenarios. In addition, the proposed nonparametric approach is applied to predict the concentrations of a pollutant that represents a risk to human health, the cadmium, in the floodplain of the Meuse river (Netherlands), by incorporating the lead level as an auxiliary variable.

This work studied the spread of COVID-19, the meteorological conditions and the air quality in a megacity from two viewpoints: (1) the correlation between meteorological and air quality (PM10 and NO2) variables with infections and deaths due COVID-19, and (2) the improvement in air quality. Both analyses were performed for the pandemic lockdown due to COVID-19 in the City of Buenos Aires (CABA), the capital and the largest city in Argentina. Daily data from temperature, rainfall, average relative humidity, wind speed, PM10, NO2, new cases and deaths due COVID-19 were analyzed. Our findings showed a significant correlation of meteorological and air quality variables with COVID-19 cases. The highest temperature correlation occurred before the confirmation day of new cases. PM10 presented the highest correlation within 13 to 15 days lag, while NO2 within 3 to 6 days lag. Also, reductions in PM10 and NO2 were observed. This study shows that exposure to air pollution was significantly correlated with an increased risk of becoming infected and dying due to COVID-19. Thus, these results show that the NO2 and PM10 levels in CABA can serve as one of the indicators to assess vulnerability to COVID-19. In addition, decision-makers can use this information to adopt strategies to restrict human mobility during the COVID-19 pandemic and future outbreaks of similar diseases in CABA.