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La modelación de la dispersión de contaminantes es una herramienta indicativa que aporta en la gestión y planificación del territorio, en la realización de estudios de impacto ambiental y en los planes de manejo ambiental. Información relevante: para simular y/o entender la dispersión de las emisiones de contaminantes atmosféricos provenientes de fuentes fijas se han establecido diferentes modelos atmosféricos: caja, modelo gaussiano, euleriano, lagrangiano, tipo “puff”, receptor y hasta estadísticos. En el caso de los modelos gaussianos se busca describir la dispersión en la horizontal y en la vertical con una distribución normal o de gauss que depende de los coeficientes de dispersión (variantes respecto a la estabilidad atmosférica). El modelo gaussiano se divide en tipo screening (simple) y complejo/refinado dependiendo de la cantidad y complejidad de variables y enfoque. Propósito de la nota de campus: el presente documento se constituye como una guía rápida para el entendimiento conceptual, uso y análisis de resultados de un modelo gaussiano simple de fuente única. Metodología: el documento aborda las temáticas asociadas al modelo Screen View como generalidades de los modelos gaussianos simples, influencia de la meteorología y del terreno en la dispersión de contaminantes, tipos de fuentes de emisión, coeficientes de dispersión, receptores, distancia automática & distancia discreta, efecto “downwash” por edificaciones, y la opción fumigación. Así mismo, brinda un video explicativo y consejos para el análisis de datos. Cursos de formación: 358056 - Transporte y dispersión de contaminantes; 358055 - Red de Monitoreo y Calidad del Aire. Conclusiones: el modelo gaussiano simple Screen View es una herramienta rápida y útil para el estudio preliminar de la dispersión de emisiones de contaminantes primarios asociados a una fuente fija.

Light-absorbing aerosols emitted during open biomass burning (BB) events such as wildfires and agricultural burns have a strong impact on the Earth’s radiation budget through both direct and indirect effects. Additionally, BB aerosols and gas-phase emissions can substantially reduce air quality at local, regional, and global scales, negatively affecting human health. South America is one of largest contributors to BB emissions globally. After Amazonia, the BB emissions from the wildfires and agricultural burns in the grassland plains of Northern South America (NSA) are the most significant in the region. However, few studies have analyzed the potential impact of NSA BB emissions on regional air quality. Recent evidence suggests that seasonal variations in air quality in several major cities in NSA could be associated with open biomass burning emissions, but it is still uncertain to what those sources impact air quality in the region. In this work, we report on 3 years of continuous equivalent Black Carbon (eBC) and Brown Carbon (BrC) observations at a hill-top site located upwind of the city of Bogotá and we demonstrate its association with MODIS detected fires in a 3000 km × 2000 km domain. Off-line PM2.5 filter samples collected during three field campaigns were analyzed to quantify water-soluble organic carbon (WSOC), organic and elemental carbon (OC/EC), and biomass burning tracers such as levoglucosan, galactosan, and potassium. MODIS Active Fire Data and HYSPLIT back-trajectories were used to identify potential biomass burning plumes transported to the city. We analyzed the relationship between BrC, WSOC, water-soluble potassium, and levoglucosan to identify signals of regional transport of BB aerosols. Our results confirm that regional biomass burning transport from wildfires occurs annually during the months of January and April. The seasonality of eBC followed closely that of PM2.5 at the city air quality stations, however, the observed seasonality of BrC is distinctly different to that of eBC and strongly associated to regional fire counts. The strong correlation between BrC and regional fire counts was observed both at daily, weekly, and monthly time-scales. WSOC at the measurement site was observed to increase linearly with levoglucosan during high BB periods, and to remain constant at ∼ 2.5 µgC m−3 during the low BB activity seasons. Our findings show, for the first time in this region, that aged BB plumes can regularly reach densely populated areas in the Central Andes of Northern South America. A source footprint analysis involving BrC observations, back-trajectories, and remotely sensed fire activity shows that the eastern savannas in NSA are the main BB source region for the domain analyzed.

In this letter, we present an implementation of a random number generator based on photon polarization superposition. We prepare photons in a superposition state of vertical and horizontal polarizations, let them pass through a polarizing beamsplitter and set two detectors at each path to get a 50–50 chance of finding the photon at each detector. We present the results of the NIST test suite for random number generators for our binary sequence of approximately 1.4 × 107 bits and analyze the different p -values obtained to statistically assess its randomness. In doing so, we use von Neumann’s algorithm for bias removal and briefly explain how the statistical tests work.