A bacterial strain capable of Zinc and Lead biosorption was isolated from mine tailings. This strain showed the highest minimum inhibitory concentrations (MIC) of metals among other isolates in metal-resistance tests. Sorption tests were conducted placing 0.015 g of dry biomass in 10 ml of metallic solution at fixed pH. Contact was analyzed at different times (kinetics) and different initial concentrations (isotherm). The biomass was separated by centrifugation and the concentration of non-absorbed metal was determined using atomic absorption spectroscopy. The strain was identified by 16S sequencing as Delftia tsuruhatensis. The order of toxicity of the metals to the bacterium was Zn > Pb > Se > Ni > Cu = Al. Zinc and Lead absorption kinetics were adjusted to the pseudo second order equation (r 2 = 0.99), showing that equilibrium was reached at 40 and 20 min, respectively. Maximal absorption of Pb and Zn was 0.216 and 0.207 mmol·g -1 , respectively; which can be considered a median magnitude capacity when compared to other biosorbents described in the literature.

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El presente trabajo muestra la arquitectura y las funcionalidades del software conocido como “Sistema de análisis de datos para el monitoreo regional y local del cambio climático con índices agroclimáticos” Moclic. El software funciona como: a) base de datos, b) herramienta de procesamiento de datos agroclimáticos, y c) herramienta para identificar las tendencias locales del cambio climático. Entre las ventajas de utilizar Moclic se incluye su capacidad para evaluar el cambio climático dentro de una interfaz gráfica de usuario. El software requiere datos de entrada de la estación meteorológica, los cuales contienen la siguiente información: nombre de la estación; número de clave; localidad y estado; promedios mensuales, temperaturas mínimas y máximas, precipitación mensual y coordenadas geográficas de la estación. Con Moclic se pueden procesar los datos de entrada y calcular las variables relacionadas con la evapotranspiración potencial y los índices (anuales y mensuales) de humedad, aridez, estación de crecimiento, concentración de precipitación, erodabilidad y lixiviación del suelo. Moclic funciona tanto en inglés como en español. En este trabajo se presenta un estudio de caso de la Estación de Abalá en el estado de Yucatán, México, para mostrar la aplicabilidad de Moclic a nivel local. Los resultados obtenidos muestran la gran exactitud de este software, para la predicción de las tendencias de cambio climático a lo largo de los últimos 40 años, y sugieren su alto potencial, para que sea utilizado en los nuevos escenarios climáticos.

Environmental pollution is a negative externality of urbanization and is of great concern due to the fact that it poses serious problems to human health. Pollutants, such as heavy metals, have been found in urban road dust; however, it is unclear whether the urban form has a role in its accumulation, mainly in cases where there is no dominant unique source. We collected 482 samples of road dust, we determined the concentrations of five heavy metals (Cr, Cu, Pb, Zn, and Ni) using inductively coupled plasma optical emission spectrometry (ICP-OES), and then we derived the pollution load index (PLI). After estimating the mostly anthropogenic origin of these pollutants based on global levels of reference, there were two main aims of this study. Firstly, to analyze the spatial correlation of heavy metals, and secondly, to identify the main factors that influenced the heavy metal concentrations in the road dust of Mexico City. We did this by using a spatial autocorrelation indicator (Global Moran’s I) and applying ordinary least squares (OLS) and spatial regression models. The results indicated low levels of positive spatial autocorrelation for all heavy metals. Most variables failed to detect any relationship with heavy metals. The median strip area in the roads had a weak (significance level of 90%) but consistent positive relationship with Cr, Cu, Ni, Pb, and the PLI. The distance to the airport had a weak (significance level of 90%) and inverse relationship with Pb. Manufacturing units were associated with an increase in Cu (significance level of 95%), while the entropy index was associated with an increase in Ni (significance level of 95%).