La presente Tesis Doctoral pretende establecer las características fundamentales de los niveles sonoros LDEN, LDAY, LEVENING y LNIGHT dentro del ámbito urbano. En este sentido se pretende, tras un análisis de las características que presentan estos niveles, establecer un estudio que permita determinar las incertidumbres cometidas cuando se realizan estimaciones de larga duración en base a medidas de menor duración. Como parte de esta investigación, y teniendo en cuenta el objetivo perseguido, se recabó información de estudios y publicaciones que versaran sobre la temática a desarrollar. En estos estudios encontrados se observa que en la mayoría de ellos los períodos de tiempo empleados son de corta duración (menor a una semana), existiendo un menor número de publicaciones con datos de media duración (uno o dos meses) y una práctica ausencia de estudios de niveles sonoros de larga duración. Asimismo, en la práctica totalidad de estos estudios sólo es estudiado el nivel sonoro LAeq, sin llegar a evaluar los niveles sonoros que establece la normativa europea 2002/49/CE, por lo que se considera que debe establecerse un punto de partida para la estimación y determinación de estos niveles sonoros. El desarrollo de la investigación parte del conocimiento de los niveles sonoros de una hora de duración durante cinco años en continuo correspondientes a cinco localizaciones distintas de la ciudad de Madrid. El hecho de realizar el estudio en distintas localizaciones tiene como objetivo el poder comparar los resultados entre las localizaciones de forma que se puedan establecer semejanzas o similitudes en función de la zona (residencial, comercial, tráfico,...). Una vez analizadas las características de los niveles sonoros de cada una de las localizaciones se establecen, a priori, tres metodologías a seguir para la estimación de los niveles sonoros. La primera de estas metodologías se basa en la estimación de los niveles en base al muestreo. / Giménez Sancho, A. (2010). CONTRIBUCIÓN AL ESTUDIO DE LOS ÍNDICES EUROPEOS DE VALORACIÓN DEL RUIDO AMBIENTAL EN AMBIENTE URBANO [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/8475 / Palancia

In a time when urban areas continue to expand, environmental noise pollution especially from road traffic remains a big challenge. This study was aimed at using open-source GIS tools to predict road traffic noise pollution using the mid-sized city of Gävle as a case study. The noise indicators measured were the equivalent day (Lday), evening (Levening), nighttime (Lnight), and the equivalent daily average (Lden). Traffic data (composition and flow of vehicles on selected roads), traffic source characteristics (road gradient, road surface type), and buildings (geometry) were integrated into Quantum GIS (QGIS) using the CNOSSOS-EU prediction method packaged in OpeNoise, a QGIS plug-in. The resultant noise levels at receiver points were interpolated using the Inverse Distance Weighting method to create noise maps for the city.  The results showed the maximum equivalent day, evening, nighttime predicted noise levels at 85 dB (A), 80 dB (A), 75 dB (A) respectively while the maximum for overall daily average noise level predicted was 85 dB (A). These limits far exceed population exposure threshold limits for the onset of annoyance (55 dB (A)) and sleep disturbance (40 dB (A)). This result is indicative of a poor sound acoustic environment. The pattern of noise level across the city was found to follow street connectivity and traffic intensity. The maximum noise levels were clustered around the highway. Within the city, areas with the highest noise levels were found close to main roads. Residential areas served by service roads were areas with the lowest noise levels. Predicted daytime noise levels (Lday) were compared with 60-second measurements of equivalent noise levels measured at 85 locations during the day in residential and mixed land use areas in the city. The mean of differences between predicted and observed noise levels was found at +1 dB for both residential and areas of mixed land use respectively. Correlation and regression analyses performed for observed and predicted values showed an initial weak positive association with a correlation coefficient of 0.21. However, when outliers were excluded, a correlation coefficient of 0.69 was observed indicating a strong association and linear relationship between the observed and predicted noise levels. Most outliers were underestimations recorded in residential areas at hidden facades. These were attributed to local effects at the measuring locations and assumptions made for building diffraction. The application of the CNOSSOS-EU method in this study did not consider attenuation from ground reflection and terrain effects. Despite these limitations, the results show that the CNOSSOS-EU has good predictive power. However, this study has only been exploratory in nature. It is recommended that further studies be performed with this model as well as in comparison with other models to find the one that best reflects the acoustic environment of the city. A wide application of the CNOSSOS-EU method across several cities will be integral in increasing our understanding of its strengths and weaknesses.