The impact of urban noise on primary schools: perceptive evaluation and objective assessment

This paper aims to assess the impact of environmental noise in the vicinity of primary schools and to analyze its influence in the workplace and in student performance through perceptions and objective evaluation. The subjective evaluation consisted of the application of questionnaires to students and teachers, and the objective assessment consisted of measuring in situ noise levels. The survey covered nine classes located in three primary schools. Statistical Package for Social Sciences was used for data processing and to draw conclusions. Additionally, the relationship of the difference between environmental and background noise levels of each classroom and students with difficulties in hearing the teacherâ s voice was examined. Noise levels in front of the school, the schoolyard, and the most noise-exposed classrooms (occupied and unoccupied) were measured. Indoor noise levels were much higher than World Health Organization (WHO) recommended values: LAeq,30min averaged 70.5 dB(A) in occupied classrooms, and 38.6 dB(A) in unoccupied ones. Measurements of indoor and outdoor noise suggest that noise from the outside (road, schoolyard) affects the background noise level in classrooms but in varying degrees. It was concluded that the façades most exposed to road traffic noise are subjected to values higher than 55.0 dB(A), and noise levels inside the classrooms are mainly due to the schoolyard, students, and the road traffic. The difference between background (LA95,30min) and the equivalent noise levels (LAeq,30min) in occupied classrooms was 19.2 dB(A), which shows that studentsâ activities are a significant source of classroom noise.

Improving selective collection of urban waste using a business intelligence system

Today recovering urban waste requires effective management services, which usually imply sophisticated monitoring and analysis mechanisms. This is essential for the smooth running of the entire recycling process as well as for planning and control urban waste recovering. In this paper we present a business intelligence system especially designed and im- plemented to support regular decision-making tasks on urban waste management processes. The system provides a set of domain-oriented analytical tools for studying and characterizing poten- tial scenarios of collection processes of urban waste, as well as for supporting waste manage- ment in urban areas, allowing for the organization and optimization of collection services. In or- der to clarify the way the system was developed and the how it operates, particularly in process visualization and data analysis, we also present the organization model of the system, the ser- vices it disposes, and the interface platforms for exploring data.

Random walk forecast of urban water in Iran under uncertainty

There are two significant reasons for the uncertainties of water demand. On one hand, an evolving technological world is plagued with accelerated change in lifestyles and consumption patterns; and on the other hand, intensifying climate change. Therefore, with an uncertain future, what enables policymakers to define the state of water resources, which are affected by withdrawals and demands? Through a case study based on thirteen years of observation data in the Zayandeh Rud River basin in Isfahan province located in Iran, this paper forecasts a wide range of urban water demand possibilities in order to create a portfolio of plans which could be utilized by different water managers. A comparison and contrast of two existing methods are discussed, demonstrating the Random Walk Methodology, which will be referred to as the â On uncertainty pathâ , because it takes the uncertainties into account and can be recommended to managers. This On Uncertainty Path is composed of both dynamic forecasting method and system simulation. The outcomes show the advantage of such methods particularly for places that climate change will aggravate their water scarcity, such as Iran.