Correlation between facade sound insulation and urban noise: A contribution to the acoustic classification of existing buildings

Casini, David; Cellai, Gianfranco; Fogola, Jacopo; Scamoni, Fabio; Secchi, Simone

doi:10.1177/1351010x16670173

Cited by 20 publications

(10 citation statements)

References 8 publications

(10 reference statements)

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“…External noise sources, façade insulation, and reverberation time provided the most negative contribution to GNS. A recent study considering more than one hundred façades of Italian schools of all levels (from nursery to upper secondary school) and built in different time periods and building technologies, revealed that almost all the schools needed sound insulation refurbishment and acoustic treatment of classrooms [ 62 ]. Thus, the schools selected within the project across the country can be considered as representative of the general conditions in Italian schools.…”

Section: Discussionmentioning

confidence: 99%

Annoyance Judgment and Measurements of Environmental Noise: A Focus on Italian Secondary Schools

Minichilli

Gorini

Ascari

et al. 2018

IJERPH

130

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The effects of noise on students’ health, well-being, and learning are of growing concern among both the general public and policy-makers in Europe. Several studies have highlighted the consequences of noise on children’s learning and performance at school. This study investigates the relationship between noise judgment in school goers aged 11–18 and noise measurements aimed at evaluating their exposure at school. For this purpose, a questionnaire was administered to 521 individuals in 28 classrooms in eight schools of four cities in Italy, with different environmental characteristics. Using a Likert-type scale, a selected set of responses related to noise generated an Annoyance Index (AI) score for each student and a classroom median score (MAI). From the noise data acquired, a global noise score (GNS) was assigned to each classroom. A higher AI was found in industrialized areas and among younger students. No significant differences in noise judgment were found by gender. A significant inverse correlation was described between MAI and GNS, thus the better the acoustic quality of the classrooms, the less the perceived noise and annoyance. The results show that noise perception and consequent disturbance are highly correlated with classroom acoustics, and confirm that annoyance represents the most widespread subjective response to noise.

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Section: Discussionmentioning

confidence: 99%

Annoyance Judgment and Measurements of Environmental Noise: A Focus on Italian Secondary Schools

Minichilli

Gorini

Ascari

et al. 2018

IJERPH

130

View full text Add to dashboard Cite

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“…The current framework can face this issue by exploiting the flexibility and the reliability of the low cost devices integrated in a Wireless Sensor Network. Finally, the interaction between the environmental parameters, such as CO 2 concentration and illuminance level, and the users’ thermal sensation will be investigated by exploiting the potential provided by ML techniques, thus allowing to include other aspects related to IEQ: Indoor Air Quality (IAQ), Indoor Lighting Quality (ILQ) [ 66 , 67 , 68 ], Acoustic comfort [ 69 , 70 , 71 ] and their interaction with the energy performance of buildings [ 72 , 73 , 74 , 75 ].…”

Section: Discussionmentioning

confidence: 99%

Integrated Method for Personal Thermal Comfort Assessment and Optimization through Users’ Feedback, IoT and Machine Learning: A Case Study †

Salamone

Belussi

Currò³

et al. 2018

Sensors

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Thermal comfort has become a topic issue in building performance assessment as well as energy efficiency. Three methods are mainly recognized for its assessment. Two of them based on standardized methodologies, face the problem by considering the indoor environment in steady-state conditions (PMV and PPD) and users as active subjects whose thermal perception is influenced by outdoor climatic conditions (adaptive approach). The latter method is the starting point to investigate thermal comfort from an overall perspective by considering endogenous variables besides the traditional physical and environmental ones. Following this perspective, the paper describes the results of an in-field investigation of thermal conditions through the use of nearable and wearable solutions, parametric models and machine learning techniques. The aim of the research is the exploration of the reliability of IoT-based solutions combined with advanced algorithms, in order to create a replicable framework for the assessment and improvement of user thermal satisfaction. For this purpose, an experimental test in real offices was carried out involving eight workers. Parametric models are applied for the assessment of thermal comfort; IoT solutions are used to monitor the environmental variables and the users’ parameters; the machine learning CART method allows to predict the users’ profile and the thermal comfort perception respect to the indoor environment.

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“…Some researches face the problem from a technological point of view, developing methods and tools aimed at managing and controlling the environmental variables in order to guarantee the best indoor conditions and energy savings [10,11]. Other researches aim at defining a classification of buildings from the point of view of indoor comfort [12].…”

Section: Introductionmentioning

confidence: 99%

Development of an Indoor Environmental Quality Assessment Tool for the Rating of Offices in Real Working Conditions

et al. 2019

Self Cite

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The Indoor Environmental Quality (IEQ) refers to the quality of indoor spaces in relation to the health and well-being of users. IEQ is a holistic concept considering various components of the overall indoor comfort: thermo-hygrometric, lighting, air quality and acoustics. Each component is described through specific performance indicators and benchmarks. The quality of the built environment is assessed at different stages from design to operational phase. The scientific literature reports several case studies related to the assessment of the individual components of the IEQ Tools aimed at the evaluation of the overall IEQ. The paper proposes an assessment tool based on the SB Method (Sustainable Building Method) and the Multi Criteria Analysis for the evaluation of IEQ during the operational phase of a building. Each component of IEQ is analysed through objective indicators and calculation methods. The tool provides two main outcomes: a global score expressing the overall performance of the building from the IEQ perspective; quantitative evaluations of all indoor comfort components through monitoring and measurement of the environmental variables. The above contributes to select intervention areas to optimize indoor design and to identify technologies aimed at ensuring the best IEQ levels for users at the operational stage. The system was applied to an open-plan working space of an office building. Monitoring activities and measurements are carried out to detect the indoor and outdoor variables affecting the IEQ. All aspects of IEQ were analysed and quantified so to evaluate the overall performance of the building and provide data to improve the working conditions.

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Correlation between facade sound insulation and urban noise: A contribution to the acoustic classification of existing buildings

Cited by 20 publications

References 8 publications

Annoyance Judgment and Measurements of Environmental Noise: A Focus on Italian Secondary Schools

Annoyance Judgment and Measurements of Environmental Noise: A Focus on Italian Secondary Schools

Integrated Method for Personal Thermal Comfort Assessment and Optimization through Users’ Feedback, IoT and Machine Learning: A Case Study †

Development of an Indoor Environmental Quality Assessment Tool for the Rating of Offices in Real Working Conditions

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