Integración de la calidad del aire en la planificación física

En esta tesis se presenta una nueva aproximación para la realización de mapas de calidad del aire, con objeto de que esta variable del medio físico pueda ser tenida en cuenta en los procesos de planificación física o territorial. La calidad del aire no se considera normalmente en estos procesos debido a su composición y a la complejidad de su comportamiento, así como a la dificultad de contar con información fiable y contrastada. Además, la variabilidad espacial y temporal de las medidas de calidad del aire hace que sea difícil su consideración territorial y exige la georeferenciación de la información. Ello implica la predicción de medidas para lugares del territorio donde no existen datos. Esta tesis desarrolla un modelo geoestadístico para la predicción de valores de calidad del aire en un territorio. El modelo propuesto se basa en la interpolación de las medidas de concentración de contaminantes registradas en las estaciones de monitorización, mediante kriging ordinario, previa homogeneización de estos datos para eliminar su carácter local. Con el proceso de eliminación del carácter local, desaparecen las tendencias de las series muestrales de datos debidas a las variaciones temporales y espaciales de la calidad del aire. La transformación de los valores de calidad del aire en cantidades independientes del lugar de muestreo, se realiza a través de parámetros de uso del suelo y de otras variables características de la escala local. Como resultado, se obtienen unos datos de entrada espacialmente homogéneos, que es un requisito fundamental para la utilización de cualquier algoritmo de interpolación, en concreto, del kriging ordinario. Después de la interpolación, se aplica una retransformación de los datos para devolver el carácter local al mapa final. Para el desarrollo del modelo, se ha elegido como área de estudio la Comunidad de Madrid, por la disponibilidad de datos reales. Estos datos, valores de calidad del aire y variables territoriales, se utilizan en dos momentos. Un momento inicial, donde se optimiza la selección de los parámetros más adecuados para la eliminación del carácter local de las medidas y se desarrolla cada una de las etapas del modelo. Y un segundo momento, en el que se aplica en su totalidad el modelo desarrollado y se contrasta su eficacia predictiva. El modelo se aplica para la estimación de los valores medios y máximos de NO2 del territorio de estudio. Con la implementación del modelo propuesto se acomete la territorialización de los datos de calidad del aire con la reducción de tres factores clave para su efectiva integración en la planificación territorial o en el proceso de toma de decisiones asociado: incertidumbre, tiempo empleado para generar la predicción y recursos (datos y costes) asociados. El modelo permite obtener una predicción de valores del contaminante objeto de análisis en unas horas, frente a los periodos de modelización o análisis requeridos por otras metodologías. Los recursos necesarios son mínimos, únicamente contar con los datos de las estaciones de monitorización del territorio que, normalmente, están disponibles en las páginas web viii institucionales de los organismos gestores de las redes de medida de la calidad del aire. Por lo que respecta a las incertidumbres de la predicción, puede decirse que los resultados del modelo propuesto en esta tesis son estadísticamente muy correctos y que los errores medios son, en general, similares o menores que los encontrados con la aplicación de las metodologías existentes. ABSTRACT This thesis presents a new approach for mapping air quality, so that this variable of physical environment can be taken into account in physical or territorial planning. Ambient air quality is not normally considered in territorial planning mainly due to the complexity of its composition and behavior and the difficulty of counting with reliable and contrasted information. In addition, the wide spatial and temporal variability of the measurements of air quality makes his territorial consideration difficult and requires georeferenced information. This involves predicting measurements in the places of the territory where there are no data. This thesis develops a geostatistical model for predicting air quality values in a territory. The proposed model is based on the interpolation of measurements of pollutants from the monitoring stations, using ordinary kriging, after a detrending or removal of the local character of sampling values process. With the detrending process, the local character of the time series of sampling data, due to temporal and spatial variations of air quality, is removed. The transformation of the air quality values into site-independent quantities is performed using land use parameters and other characteristic parameters of local scale. This detrending of the monitoring data process results in a spatial homogeneous input set which is a prerequisite for a correct use of any interpolation algorithm, particularly, ordinary kriging. After the interpolation step, a retrending or retransformation is applied in order to incorporate the local character in the final map at places where no monitoring data is available. For the development of this model, the Community of Madrid is chosen as study area, because of the availability of actual data. These data, air quality values and local parameters, are used in two moments. A starting point, to optimize the selection of the most suitable indicators for the detrending process and to develop each one of the model stages. And a second moment, to fully implement the developed model and to evaluate its predictive power. The model is applied to estimate the average and maximum values of NO2 in the study territory. With the implementation of the proposed model, the territorialization of air quality data is undertaken with the reduction in three key factors for the effective integration of this parameter in territorial planning or in the associated decision making process: uncertainty, time taken to generate the prediction and associated resources (data and costs). This model allows the prediction of pollutant values in hours, compared to the implementation time periods required for other modeling or analysis methodologies. The required resources are also minimal, only having data from monitoring stations in the territory, that are normally available on institutional websites of the authorities responsible for air quality networks control and management. With regard to the prediction uncertainties, it can be concluded that the results of the proposed model are statistically very accurate and the mean errors are generally similar to or lower than those found with the application of existing methodologies.

Advanced predictive quality control strategy involving different facilities

There are many industries that use highly technological solutions to improve quality in all of their products. The steel industry is one example. Several automatic surface-inspection systems are used in the steel industry to identify various types of defects and to help operators decide whether to accept, reroute, or downgrade the material, subject to the assessment process. This paper focuses on promoting a strategy that considers all defects in an integrated fashion. It does this by managing the uncertainty about the exact position of a defect due to different process conditions by means of Gaussian additive influence functions. The relevance of the approach is in making possible consistency and reliability between surface inspection systems. The results obtained are an increase in confidence in the automatic inspection system and an ability to introduce improved prediction and advanced routing models. The prediction is provided to technical operators to help them in their decision-making process. It shows the increase in improvement gained by reducing the 40 % of coils that are downgraded at the hot strip mill because of specific defects. In addition, this technology facilitates an increase of 50 % in the accuracy of the estimate of defect survival after the cleaning facility in comparison to the former approach. The proposed technology is implemented by means of software-based, multi-agent solutions. It makes possible the independent treatment of information, presentation, quality analysis, and other relevant functions.

Analysis and Quality Control from ARIMA Modeling

In this paper, we use ARIMA modelling to estimate a set of characteristics of a short-term indicator (for example, the index of industrial production), as trends, seasonal variations, cyclical oscillations, unpredictability, deterministic effects (as a strike), etc. Thus for each sector and product (more than 1000), we construct a vector of values corresponding to the above-mentioned characteristics, that can be used for data editing.

Seismic Risk Scenarios in Puerto Principe (Haiti). A Tool for Reconstruction and Emergency Planning

The 12 January 2010, an earthquake hit the city of Port-au-Prince, capital of Haiti. The earthquake reached a magnitude Mw 7.0 and the epicenter was located near the town of Léogâne, approximately 25 km west of the capital. The earthquake occurred in the boundary region separating the Caribbean plate and the North American plate. This plate boundary is dominated by left-lateral strike slip motion and compression, and accommodates about 20 mm/y slip, with the Caribbean plate moving eastward with respect to the North American plate (DeMets et al., 2000). Initially the location and focal mechanism of the earthquake seemed to involve straightforward accommodation of oblique relative motion between the Caribbean and North American plates along the Enriquillo-Plantain Garden fault system (EPGFZ), however Hayes et al., (2010) combined seismological observations, geologic field data and space geodetic measurements to show that, instead, the rupture process involved slip on multiple faults. Besides, the authors showed that remaining shallow shear strain will be released in future surface-rupturing earthquakes on the EPGFZ. In December 2010, a Spanish cooperation project financed by the Politechnical University of Madrid started with a clear objective: Evaluation of seismic hazard and risk in Haiti and its application to the seismic design, urban planning, emergency and resource management. One of the tasks of the project was devoted to vulnerability assessment of the current building stock and the estimation of seismic risk scenarios. The study was carried out by following the capacity spectrum method as implemented in the software SELENA (Molina et al., 2010). The method requires a detailed classification of the building stock in predominant building typologies (according to the materials in the structure and walls, number of stories and age of construction) and the use of the building (residential, commercial, etc.). Later, the knowledge of the soil characteristics of the city and the simulation of a scenario earthquake will provide the seismic risk scenarios (damaged buildings). The initial results of the study show that one of the highest sources of uncertainties comes from the difficulty of achieving a precise building typologies classification due to the craft construction without any regulations. Also it is observed that although the occurrence of big earthquakes usually helps to decrease the vulnerability of the cities due to the collapse of low quality buildings and the reconstruction of seismically designed buildings, in the case of Port-au-Prince the seismic risk in most of the districts remains high, showing very vulnerable areas. Therefore the local authorities have to drive their efforts towards the quality control of the new buildings, the reinforcement of the existing building stock, the establishment of seismic normatives and the development of emergency planning also through the education of the population.

Dust suppressant treatments. Quality control = Tratamientos supresores de polvo. Control de calidad

La emisión de polvo por efecto del viento desde depósitos de residuos mineros o industriales y el paso de vehículos en vías no pavimentadas, es un problema que afecta las actividades productivas; el ambiente y la salud de las personas que permanecen en el área contaminada. En Chile, en los últimos años la sensibilidad social y las exigencias ambientales han aumentado, así como la oferta de diferentes supresores y tecnologías de aplicación. Se han revisado las causas que provocan emisión de polvo y las tecnologías disponibles en Chile para la supresión de polvo, además de las metodologías y normativa para evaluar el desempeño de los materiales tratados con diferentes supresores. En algunos casos no es posible comparar propiedades de desempeño, como durabilidad, dosis a aplicar y frecuencia de las aplicaciones, entre otros aspectos. Los procedimientos descritos en la norma NCh3266-2012 permiten evaluar la erosión eólica en depósitos de residuos, sitios eriazos y caminos no pavimentados, entre otros, junto con evaluar el desempeño de diferentes tipos de supresores de polvo a partir de datos objetivos comparables. Esto permite seleccionar el supresor más adecuado, mejorar la eficiencia de los tratamientos, optimizar los costos y mejorar los procesos productivos. Palabras clave: Erosión-eólica, supresor de polvo, residuos-mineros, caminos-no pavimentados. Dust emissions by wind effect from mining deposits or industrial waste and passing vehicles on unpaved roads, is a problem that affects the productive activities; the environment and the health of those who remain in the contaminated area. The social sensitivity and environmental requirements on this issue in Chile have increased, as well as offering different suppressors and application technologies. Have been reviewed the causes of dust emission and technologies available in Chile for dust suppression, plus methodologies and standards for assessing the performance of the treated materials with different suppressors. In some cases it is not possible to compare performance properties such as durability, application dose and frequency of applications, among others aspects. The procedures described in the NCh 3266-2012 standard allows the assessment of wind erosion in waste deposits, vacant lots and unpaved roads, among others, along with evaluating the performance of different types of dust suppressants from comparable objective data. This allows selecting the most suitable suppressor, improve efficiency of treatments, optimize costs and improve production processes. Keywords: Wind-erosion, dust-suppressor, mining-waste, unpavedroads