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This paper examines the beliefs and environmental attitudes of university individuals towards bottled and tap water use and examines tap and bottled water availability and sales volumes at the University of the Basque Country. The research employed a mixed methods approach including (i) an exploratory survey to document environmental beliefs and behaviors towards bottled and tap water; (ii) written questionnaires addressed to faculty administrators to inquire about accessibility to tap water and, (iii) personal interviews with restaurant managers to inquire about sales volumes of bottled water. Respondents to our survey predominately drink tap water and no health or taste issues associated with its consumption are perceived among respondents reporting to drink two or fewer bottles per week. These results imply that in our context, there are positive perceptions towards tap water and pro-environmental behavior regarding water consumption. However, respondents also claimed to use reused plastic water bottles as the most common tap water container. Moreover, there was widespread presence of bottled water sales at university premises, confirming the ubiquity of this commodity worldwide. Collectively, both survey and sales volume analyses suggest that a greater shift in sustainable behavior is needed in our community. Regarding measures and policies to promote tap water accessibility, considerable differences were found within and between campuses. These findings should help to inform university managers and support sustainability goals where bottled water consumption could be minimized or even eliminated.

The goal of this work is to build and evaluate a multilayer perceptron based model to forecast tropospheric ozone (O 3 ) levels, in real-time, up to eight hours ahead at two rural stations located in the Autonomous Community of the Basque Country (North Central Spain). Current and historical hourly concentrations of ozone, nitrogen dioxide (NO 2 ) and meteorological variables were used to determine the input variables of the model. The designed basic model established sixteen multilayer perceptrons, which were trained using the scaled conjugate gradient algorithm. The performance of the model was evaluated using the statistics of the Model Validation Kit. The study proved the capability of artificial neural networks to forecast efficiently ozone concentrations at rural stations in the Basque Country.

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