The influence of low-frequency noise pollution on the quality of life and place in sustainable cities: a case study from northern Portugal

Discussing urban planning requires rethinking sustainability in cities and building healthy environments. Historically, some aspects of advancing the urban way of life have not been considered important in city planning. This is particularly the case where technological advances have led to conflicting land use, as with the installation of power poles and building electrical substations near residential areas. This research aims to discuss and rethink sustainability in cities, focusing on the environmental impact of low-frequency noise and electromagnetic radiation on human health. It presents data from a case study in an urban space in northern Portugal, and focuses on four guiding questions: Can power poles and power lines cause noise? Do power poles and power lines cause discomfort? Do power poles and power lines cause discomfort due to noise? Can power poles and power lines affect human health? To answer these questions, we undertook research between 2014 and 2015 that was comprised of two approaches. The first approach consisted of evaluating the noise of nine points divided into two groups â near the sourceâ (e.g., up to 50 m from power poles) and â away from the sourceâ (e.g., more than 250 m away from the source). In the second approach, noise levels were measured for 72 h in houses located up to 20 m from the source. The groups consist of residents living within the distance range specified for each group. The measurement values were compared with the proposed criteria for assessing low-frequency noise using the DEFRA Guidance (University of Salford). In the first approach, the noise caused discomfort, regardless of the group. In the second approach, the noise had fluctuating characteristics, which led us to conclude that the noise caused discomfort.

Toxicity measurement techniques for building materials with wastes

The innovative Horizon 2020 program sponsored by the European Union (EU) aims to promote and develop processes of waste integration in construction materials. However, several potential health hazards caused by building materials have been identified and, there-fore, there is an ongoing need to develop new recycling methods for hazardous wastes and effi-cient barriers in order to prevent toxic releases from the new construction solutions with wastes. This paper presents an overview that focus on two main aspects: the identification of the health risks related to radioactivity and heavy metals present in building materials and identification of these toxic substances in new construction solutions that contain recycled wastes. Different waste materials were selected and distinct methodologies of toxicity evaluation are presented to analyse the potential hazardous, the feasibility of using those wastes and the achievement of op-timal construction solutions involving wastes.

Hydrocarbonoclastic bacteria: from bioremediation to bioenergy feedstock

Tese de Doutoramento em Engenharia Química e Biológica.

Remoção fotocatalítica de micropoluentes em meios porosos funcionalizados

Dissertação de mestrado integrado em Engenharia Civil

Predicting SO2 pollution incidents by means of additive models with optimum variable selection

The aim of this paper is to predict time series of SO2 concentrations emitted by coal-fired power stations in order to estimate in advance emission episodes and analyze the influence of some meteorological variables in the prediction. An emission episode is said to occur when the series of bi-hourly means of SO2 is greater than a specific level. For coal-fired power stations it is essential to predict emission epi- sodes sufficiently in advance so appropriate preventive measures can be taken. We proposed a meth- odology to predict SO2 emission episodes based on using an additive model and an algorithm for variable selection. The methodology was applied to the estimation of SO2 emissions registered in sampling lo- cations near a coal-fired power station located in Northern Spain. The results obtained indicate a good performance of the model considering only two terms of the time series and that the inclusion of the meteorological variables in the model is not significant.