Time-series regression models to study the short-term effects of environmental factors on health

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

Operation and control of SBR processes for enhanced biological nutrient removal from wastewater

In the last decades, the awareness of environmental issues has increased in society considerably. There is an increasing need to improve the effluent quality of domestic wastewater treatment processes. This thesis describes the application of the Sequencing Batch Reactor (SBR) technology for Biological Nutrient Removal (BNR) from the wastewater. In particular, the work presented evolves from the nitrogen removal to the biological nutrient removal (i.e. nitrogen plus phosphorous removal) with special attention to the operational strategy design, the identification of possible reactor cycle controls or the influent composition related to the process efficiency. In such sense, also the use of ethanol as an external carbon (when low influent Carbon:Phosphorus (C:P) or Carbon:Nitrogen (C:N) ratios are presented) are studied as an alternative to maintain the BNR efficiency.