Assessing noise and overheating in dwellings: Aligning acoustic and thermal models for partially open windows

Abstract

Building regulations increasingly require balanced solutions for thermal comfort and acoustic performance, particularly for naturally ventilated dwellings. England’s Approved Document O (ADO) establishes noise thresholds for bedrooms using open windows for ventilation, allowing partially open windows (POW) rather than fully open ones to balance sound insulation with overheating mitigation. This study addresses the fundamental challenge of aligning acoustic and thermal modelling methodologies for POWs. Through field measurements at eight residential sites with diverse window configurations, we compared two assessment approaches: the theoretically-derived ‘Acoustic Open Area’ (AcOA) and the ventilation-based ‘Equivalent Area’ (EA). Statistical analysis revealed comparable accuracy between methods (standard deviations of 1.9 and 1.8 dB respectively), with no significant additional uncertainty when using EA instead of AcOA. Spectral analysis demonstrated that while measured sound insulation varies considerably with frequency, both methods effectively predict overall performance for typical environmental noise sources. This research establishes that EA – already used in thermal modelling – can reliably replace AcOA for acoustic assessments, significantly simplifying interdisciplinary coordination. These findings provide practical guidance for designers, engineers, and regulators developing integrated façade solutions that simultaneously address ventilation requirements and acoustic comfort.

Keywords

Façade sound insulation ventilation partially open windows thermal comfort measurement uncertainty

Introduction

In the last decades, the current environmental crisis and new building solutions for overheating and ventilation have raised attention among the scientific and regulatory communities. For example the European EN 13779 (provides ventilation rate values for non-smoking rooms’ indoor air quality (IDA), from IDA1 (High indoor air quality) to IDA4 (Low indoor air quality)),¹ the Italian UNI 10339 (regards aeraulic systems for indoor comfort, considering different flow rates according to room intended use),² and German DIN 1946-7:2002 (defines a specific amount of ACR per Hour (ACPH) according to the destination).³ Moreover, after recent historical events such as COVID-19, studies and reviews such as those by De Salis et al.,⁴ Fusaro et al.,⁵ and Tang⁶ have raised attention on Noise reduction façade devices allowing natural ventilation due to the increasing awareness of concepts such as indoor air quality (IAQ) and Indoor Environmental Quality IEQ.⁷ Moreover, ISO 17772-1⁸ (on indoor environmental quality) highlights that a good indoor environment requires an operable window which allows occupants to operate natural ventilation and be connected to the outdoors. This specifically applies to the IEQ of (i) bedrooms or living rooms in dwellings, (ii) other buildings with rooms intended for sleep (e.g. elderly homes) and (iii) schools and childcare facilities. However, even if the main aim of such studies and standards is crucial to ensure higher healthiness of the interior of the building, making it suitable for high occupancy spaces (houses, offices, classrooms, hospitals),⁹ there are no clear guidelines for aligning the airflow performance with the sound insulation performance of an open window.

Current literature and international standards do not define the acoustic operational conditions for standard windows (including partially open windows) for which there can be a reasonable balance between ventilation and acoustic comfort. The airflow rate (and hence the extent of opening) required depends heavily on whether the purpose of the ventilation is to achieve an air quality target or to mitigate overheating. These design goals require very different air flow rates; in each case (for IAQ or thermal performance) the airflow rates depend on other aspects of the design and operation. The assessment of sound insulation of a building façade with standard open windows is generally measured according to international standards (such as ISO 16283-310); it is understood that some national regulations (such as Danish Regulations¹¹) have requirements for indoor sound levels with open windows. A few frameworks in international guidelines highlight ranges for the use of standard open windows in noisy outdoor environments according to the evaluation of health risks. The WHO Environmental Noise Guidelines for the European Region¹² demonstrate how health-based guidelines for environmental noise exposure are derived for specific sources – road, rail and air traffic – based on the highest exposed facade, in terms of L_den (associated primarily with noise annoyance but also other adverse health impacts), and L_night (mainly associated with sleep disturbance). This approach marks a significant departure from the WHO Community Noise Guidelines 1999,¹³ which indicated indoor sound levels due to all environmental sources. It has recently been clarified that the indoor sound levels for dwellings should only have been associated with the corresponding outdoor sound levels, assuming a fixed difference of 15 dB.¹⁴ Many countries’ design codes, such as BS 8233¹⁵ in the UK, have been treating the indoor levels as targets to be achieved, irrespective of outdoor sound levels, to demonstrate mitigation of adverse noise effects, as described by Harvie-Clark & Fenech.^16,17 In contrast, the WHO 2018 Guidelines make no health-based recommendations regarding internal levels for different sources, beyond reference to the WHO 1999 Guidelines. Developing evidence-based internal-level guidelines therefore remains a priority. In this context, it is not yet possible to indicate outdoor sound levels that may be suitable for different types of accommodation with opening windows for the provision of either good IAQ or reasonable thermal comfort. Sound insulation with standard open windows is therefore viable in areas with moderate outdoor environmental noise levels, where a reasonable balance between ventilation and acoustic comfort could still be achieved but might become ineffective in noisier environments.^10,12,18 If the building is exposed to higher environmental noise impacts, it might become highly challenging to maintain acceptable indoor acoustic conditions with standard open windows. In such cases, alternative window technologies or ventilation strategies, such as metamaterial-based windows⁵ or controlled mechanical ventilation,¹⁹ may be necessary to ensure both fresh air supply and acoustic comfort. This consideration highlights the broader discussion on the role of windows and partially open windows in ensuring both acoustic and thermal comfort within a convenient energetic approach, particularly in buildings with diverse functions such as residential, educational and office spaces.

The importance of implementing natural or mechanical ventilation in buildings with wide functions such as residential, educational, and offices, highlights the discussion revolving around windows and partially open windows. These features are influenced by several holistic approaches such as thermal and acoustic comfort,^7,20 ergonomics,²¹ air quality²² and energetic impact.⁴ For example, De Salis et al.⁴ discusses how natural ventilation can enhance indoor comfort and significantly reduce energy use when designed well. The CIBSE Applications Guide adds that natural ventilation can also lower construction costs, reduce reliance on mechanical systems, and be more user-friendly.²³ Notably, HVAC systems account for about 50% of energy consumption in buildings, according to the European Commission’s 2012 Energy Efficiency Status Report.²⁴ It is important to distinguish between ventilation for indoor air quality (IAQ) and ventilative cooling; IAQ focuses on removing pollutants, while ventilative cooling focuses on using ventilation to remove excess heat, as described in the AVO Residential Design Guide.²⁵ De Salis suggests that combining natural ventilation with controlled mechanical extraction can optimise comfort and energy savings.⁴ Passive noise control methods, including plenum or ventilated windows, offer ventilation while managing sound but often limit flexibility and customisation.⁴ Recently, this typology of windows has been enhanced with Acoustic Metamaterials (AMMs),⁵ providing ventilation and sound control while potentially offering ergonomic, user-focussed designs.²⁶ Therefore, partially open windows could represent an effective solution for dealing with noise reduction and thermal regulation through natural ventilation. The related method, which is now divided could be implemented and simplified towards a multi-domain approach. To optimise the effectiveness of natural ventilation and noise control solutions, it is essential to assess their performance through advanced building simulation tools, which have significantly improved the ability to model heat transfer and airflow dynamics in building design.

Building performance simulation and its related tools have lately increased the engineering community’s ability to process several heat transfer models and their efficiency in building design. Specifically, the study run by Petrou et al.,²⁷ highlights that the simulation setup should be selected carefully according to specific algorithms with an improvement from a default one to a specific one in 33% of the analysed cases with double the predicted overheating hours. Petrou et al.²⁸ focus on the magnitude of possible parameter uncertainties associated with the modellers’ algorithm choice. Moreover, according to Tian et al., building performance simulation uncertainty can be classiﬁed into two broad categories: (a) Model form and (b) parameter uncertainties.²⁷ Then, Strachan et al.²⁹ demonstrated through empirical validation how combining both types could lead to signiﬁcant discrepancies between the model and the actual indoor environment. In the thermal model, a façade opening permits air exchange between inside and outside. The complexity of this in practice is described by Sharpe et al.,³⁰ highlighting 15%–25% prediction errors of free area models commonly used in practice. The options available to modellers are complex, and they generally adopt default practices since these are generally considered to be ‘good practice’. Wind-driven ventilation and surface convection algorithms were the main sources of the observed discrepancies. The choice of the algorithm within each building simulation tool was investigated by Petrou et al.²⁷ The selection of non-default algorithms within each model also had a very significant impact on the results. Roberts et al.³¹ compared overheating risk predictions and measurements in synthetically occupied test houses through the CIBSE Technical Memorandum (TM59).³² It is understood that the design methodology TM59 for the assessment of overheating risk in homes is currently under revision, especially with the updated science around tolerable night-time temperatures in bedrooms according to Lomas and Li.²³ Therefore, parameters such as Equivalent Area (EA), which can be applicable overall for measuring the amount of opening of the window due to the controllable uncertainty on the airflow prediction, could be considered for aligning the provisional method to calculate the ventilation rate and sound insulation performance. The growing recognition of uncertainties in building performance simulations underscores the need for regulatory frameworks that integrate both thermal and acoustic considerations, as seen in recent legislative developments aimed at mitigating overheating while ensuring indoor environmental quality.

In 2021, the English government introduced a new Building Regulation³³ to mitigate overheating in new residential buildings, and Approved Document O (ADO)³⁴ was provided to guide its application. When the Regulation was enacted in June 2022, the government published a series of FAQs on its website³⁵ (ADO-FAQ). These ADO-FAQs modify the guidance given in ADO in materially significant ways. ADO, for example, describes how windows cannot be assumed to be open during the night-time if internal noise levels exceed guideline values. This means that acoustic and overheating assessments are required to simultaneously evaluate the indoor environmental quality (IEQ) conditions. Aligning assumptions regarding acoustic and thermal models of a partially open window is a challenging aim since, in both standards and regulations, they were formulated starting from a completely different background field of use and application.^30,36 Therefore, this study proposes a new solution to facilitate the discussion between building acoustic and thermal modellers.

Background overview

Given the complexity of ensuring both thermal and acoustic comfort in buildings, various methods have been developed to assess ventilation performance and sound insulation. A clear understanding of key terminologies and calculation and measurement approaches is essential for evaluating these systems preliminarily and measuring their performances in laboratory and on-site conditions. The following section provides an overview of the fundamental definitions and methodologies used in this study.

Open area terminology and ADO simplified method

Jones et al.³⁶ provide descriptions that can be used unambiguously to characterise façade openings for ventilation performance. ‘Free area’ remains an ambiguous term without a consistent definition despite its widespread use. For example, six different methods of attributing a value of ‘free area’ to an open window are presented by Sharpe et al.³⁰ The ‘Equivalent Area’ (EA) is a description of flow performance that is used in ADO.³⁵ It is the area of a circular hole in an orifice plate that passes the same volumetric airflow as the element or flow device in question for the same pressure difference – hence the definition ‘Equivalent’.³⁵ Moreover, The Simplified Method within ADO itself, describes requirements for the so-called ‘minimum free area’ as: ‘Openings should be designed to achieve the free areas in paragraphs 1.10 and 1.11 [of ADO]. The equivalent area of the opening should meet or exceed the free area of the opening’.(from paragraph 1.12 of ADO). This could raise considerable confusion over the use of the term ‘minimum free area’ within ADO. However, the ADO-FAQs #8,³⁵ clarifies that the ‘minimum free area’ mentioned in ADO corresponds to ‘minimum equivalent area’.³⁵ Finally, Appendix D of ADO refers to an Excel tool³⁷ where EA is calculated through the equations:

E A = \frac{A_{e f f}}{C_{d o}} [m^{2}]

(1)

A_{e f f} = C_{d} . A_{f r e e} [m^{2}]

(2)

C_{d} = C_{d m a x} (1 - e^{- M α})

(3)

M = 0.0016 (σ + 1)

(4)

A_{f r e e} = w . h [m^{2}]

(5)

Where $A_{e f f}$ is the effective area, $C_{d o}$ is the Orifice Discharge coefficient, $C_{d}$ is the Discharge coefficient, $A_{f r e e}$ is the free area of the opening on the wall where the window is placed, $C_{d m a x}$ is the Maximum Discharge coefficient, $M$ is a gradient, $α$ is the opening angle, and $σ$ is the aspect ratio, h:w (h and w are respectively the height and the width of the window’s opening, or ‘free area’). These parameters are further specified in the study of Sharpe et al.³⁰ from a measurement campaign involving a series of common operable windows.

If the Simplified Method cannot be used, then dynamic thermal modelling should be used to demonstrate compliance with overheating requirements. Regarding this method, ADO refers to CIBSE TM59 but with additional constraints to how that methodology is applied. ADO indicates, ‘At night (11pm to 8am), openings should be modelled as fully open if . . . the following apply. . ..’ However, the guidance of ADO FAQ #14 supersedes the guidance in ADO, by indicating that a strategy relying on: ‘. . .opening windows a smaller amount at night. . .’³⁵ is permissible. This note may facilitate demonstration of compliance with ADO by using natural ventilation, as partially open windows provide greater sound insulation than fully open windows, and may thereby meet the noise criteria when fully open windows would indicate limitations.

One of the requirements indicated in ADO for the ‘reasonable enjoyment of the residence’ concerns noise levels. ADO indicates that: ‘. . . the overheating mitigation strategy should take account of the likelihood that windows will be closed during sleeping hours (11pm to 7am). Windows are likely to be closed during sleeping hours if noise within bedrooms exceeds the following limits: a. 40 dB L_Aeq,T, averaged over 8 hours (between 11pm and 7am); b. 55 dB L_AFmax, more than 10 times a night (between 11pm and 7am)’. This requirement connects the need for air change and overheating control with the acoustic comfort of the indoor environment, yet no specific definition of the opening area for a partially open window is given for such a multi-domain approach.

This integration of ventilation strategies with acoustic considerations highlights a critical challenge in balancing overheating mitigation with indoor comfort. While the ADO framework provides guidance on acceptable noise levels within sleeping areas, it does not quantify the effect of partially open windows on sound insulation. This gap raises questions about the extent to which windows can remain open while still ensuring compliance with noise criteria. Understanding the acoustic performance of façade openings is therefore essential for a multi-domain approach that addresses both ventilation effectiveness and sound insulation. In the following sub-section, different methodologies for assessing the sound insulation properties of partially open windows are explored.

Assessment methods for façade sound insulation of open windows

In order to determine the internal noise levels from external sources it is necessary to determine the façade sound insulation provided by a partially open window. For many practitioners, the ‘10–15 dB’ quoted by the WHO GCN³⁸ is the answer to this question. This rule of thumb takes no account of the extent of window opening or any of the other factors that may affect the façade level difference. There are four methods for assessing the sound insulation of a partially open window that must be considered and each of these approaches is discussed in the following subsections:

Theoretical assessment (BS EN ISO 12354-3¹⁰)

Laboratory measurement (ISO 10140 series,^39,40 or simulated field)

Field measurement with a loudspeaker sound source (ISO 16283-3⁴¹)

Field measurement with road traffic as a sound source (ISO 12354-3¹⁰)

Theoretical assessment of façade sound insulation and acoustic open area, AcOA

The sound insulation of a building façade against outdoor sound can be calculated according to BS EN ISO 12354-3.¹⁰ The informative Annexe D of that Standard suggests that for small openings, a global indication is given by treating the element as an opening with negligible sound reduction. This results in an element normalised level difference as shown in equation (6):

D_{n, e} = - 10 l o g (\frac{S_{o p e n}}{A_{0}}) [dB]

(6)

Where S_open is the area of the opening, in square metres and A₀ is the reference equivalent sound absorption area, 10 m². Where the value for element-normalised level difference (D_n,e) is the same in each frequency band (as implied here), the single-number weighted value (D_n,e,w) has the same value, and the spectrum adaptation term (C_tr) has a value of zero. Thus D_n,e = D_n,e,w = D_n,e,w + C_tr.

The proposal in the draft GDC-ADO⁴² was to use the ‘area of the opening’ (S_open) of a partially open window to determine the appropriate sound insulation [Note that the updated version of this draft, the Approved Document O Noise Guide,⁴³ was published in November 2024 and refers to the use of EA for calculating sound insulation, as per the proposal in this paper.]. However, the ‘area of the opening’ of a partially open window is not well defined. The GDC-ADO originally proposed that an ‘acoustic open area’ (AcOA) should be considered for evaluating the acoustic performance of a partially open window. This is derived by considering a partially open window light as a flat rectangular plane, within a two-dimensional plane façade. This disregards (i) the depth of the window opening light frame and its overlap with the surrounding window frame, and (ii) the geometry of the interaction between the opening light and what is revealed, yet representing a simple model.

The AcOA is conceived as the lesser of two potential areas:

The sum of the rectangular area at the base (of a top-hung window) and the two triangular areas formed on each side of the opening light;

The width × height (W.h) of the opening in which the opening light sits.

The potential AcOA is shown shaded in Figure 1, with a representation on a side-hung window. The dimension ‘z’ is given by simple geometry as shown in equation (7).

z = 2 W s i n (\frac{α}{2})

(7)

Where α is the opening angle. The area of top shaded triangle is given by (0.5 × base × height), which is $0.5 . W . W s i n (α)$ . Therefore the area of both triangles, top and bottom, reduces to W²sin(α). (7)

Figure 1.

The concept of an ‘acoustic open area’ is shown shaded, with the window opening light opening out of the page.

The total AcOA is given by the lesser of areas from equation (8) or equation (9):

A c O A \leq W^{2} s i n (α) + z h

(8)

A c O A \leq W h

(9)

For a given room volume, the partial internal level due to a partially open window can be calculated using equation (6), using the methods described by Harvie-Clark⁴⁴ (see the next subsection).

Laboratory measurement of open windows

Acoustic laboratory tests complying with ISO 10140-2⁴⁰ are the industry-standard method for qualifying the sound insulation of a specific building element or product. The laboratory setup concerns a carefully constructed diffuse sound field (both for the source and receiving room) – that is, the sound impacts the test specimen from all angles of incidence equally, in theory. In the traditional measurement approach outlined in the ISO 10140 series, a test specimen is positioned in a partition between two connected reverberant rooms, assessing airborne sound insulation performance related to a small element and a façade opening. This process is referenced in ISO 10140-1,³⁹ particularly in Appendix E ‘Small technical elements — Airborne sound insulation’, and Appendix C ‘Windows — Airborne sound insulation’. The dimensions of the reduced opening are detailed in ISO 10140-2,⁴⁰ Sections 6.4 and 6.5. A sound source is placed in one room, and sound pressure levels are recorded in both the source and receiving rooms. Sealant is applied around the edges where the structural window components meet the wall to maintain airtightness. The sound level difference for a small element, denoted as D_n,e, is calculated using the following equation (5; refer to section 3.3 of ISO 10140-2⁴⁰):

D_{n, e} = L_{1} - L_{2} + 10 \log \frac{A}{A_{0}} [dB]

(10)

In this formula, the subscripts n and e indicate that the level difference is normalised over the equivalent absorption area of the room and pertains to a small element. Here, L₁ represents the energy-averaged sound pressure level in the source room (in decibels), L₂ denotes the energy-averaged sound pressure level in the receiving room (in decibels), A is the equivalent absorption area in the receiving room (in square metres), and A₀ = 10 m² is the reference absorption area.⁴⁰

The test involved in a preliminary study⁴⁵ presented a window with an opening light 1.1 × 0.3 m (W.h) open to different dimensions. The simple assumptions of the AcOA model were used to calculate the element-normalised level difference. Figure 2 shows a comparison of the reported values of Calculated D_n,e (AcOA), Measured D_n,e,w, and Measured D_n,e,w + C_tr according to a range of opening angles from 0° (closed) to 50° (fully open). These results showed good agreement between measurements and calculated values – to the limit of precision of the reported D_n,e,w + C_tr values (integer values).

Figure 2.

Proprietary window level differences calculated and measured.

The largest laboratory study of partially open windows is reported in NANR116,⁴⁶ in which the measurements were not made according to ISO 10140-2, but rather from an anechoic chamber with a discrete sound source (loudspeaker), coupled with a reverberant room. With such constraints assumption, the values reported for the level difference or normalised element level difference, D_n,e would be different than values measured according to ISO 10140 but could be more realistic of field conditions. NANR116 aims to provide data that is intended to be more representative of field conditions compared to ISO 10140-2 test methods. The NANR116 report summarises that opening sizes can be broadly represented by the sound insulation levels shown in Table 1.⁴⁶ The corresponding insulation values calculated using the AcOA approach would be 23, 20, and 17 dB for 0.05, 0.1, 0.2 m² respectively. At larger open areas, the discrepancy between calculated and measured values is reduced.

Table 1.

NANR116 summary of insulation.⁴⁶

Opening size (m²)	D_n,e,w + C_tr
0.05	18
0.1	17
0.2	15

The calculated Acoustic Open Area (AcOA) and the measured level differences are analysed for a representative selection of window types (A1, A3, C, D, E, F, and G) with two open areas: 0.2 m² (represented by solid blue bars) and 0.1 m² (represented by solid green bars), as shown in Figure 3. Although not defined in NANR116, it is understood from the authors that these areas correspond with the description of AcOA given in this paper. For the 0.1 m² AcOA cases, the measured values (solid blue bars) can be compared to the level of 20 dB calculated using AcOA. Similarly, for the 0.2 m² AcOA cases, the measured values (solid green bars) can be compared to the level of 17 dB calculated with AcOA. Figure 3 also includes the Equivalent Area (EA) values calculated for each window arrangement, considering different window positions and their respective room applications, illustrated with hatched bars in blue and green respectively. The results indicate that the difference between measured and calculated values does not exceed 2 dB. Configuration B is not included in Figure 3 because reversible windows are uncommon and were not assessed in this study. The agreement between Measured and Calculated level difference results considering a reference reverberation time of 0.35 s and the Australian method in AS 3671.⁵⁴ is also supported by Figure 4, which shows the dispersion of the measured and calculated level difference results.

Figure 3.

NANR116 measured and calculated level differences. Solid bars are measured values (NB not to ISO 10140). Hatched bars are calculated based on EA. The two colours represent ventilation areas of 0.2 m² (blue) and 0.1 m² (green).

Figure 4.

Measured and Calculated level difference results considering a reference reverberation time of 0.35 s and the Australian method in AS 3671.⁵⁴ This graph represents the dispersion of the measured and calculated level difference results.

Field measurements of opening windows with a loudspeaker

While the field loudspeaker test method is well established, recent research has raised concerns about its accuracy compared to long-term assessments of global façade sound insulation using environmental sound as the source. Specifically, its reliability has been questioned when compared with the model described in ISO 12354-3¹⁰ for predicting façade sound insulation based on element performance and with real-world measurements following ISO 16283-3.⁴¹ A study by Scrosati et al.⁴⁷ found that the correlation between the noise level descriptor L_den (measured both indoors and outdoors over 25 days) and the façade sound insulation descriptor D_2m,nT (measured using a loudspeaker according to ISO 16283-3⁴¹) was not reliable. Additionally, they discovered that the single-number rating D_2m,nT,50 which includes a low-frequency adaptation term for road traffic noise, differed by 8–9 dB when directly measured versus when calculated using the correlation between D_2m,nT and indoor/outdoor L_den values. Notably, the loudspeaker measurements in this study were conducted as part of a round-robin test, meaning they represent a benchmark for standardised façade sound insulation assessments using loudspeakers.^41,47

Previously, Nunes et al.²² investigated the acoustic performance of open windows, comparing the free field and diffuse field sound reduction for the same proprietary window that was tested in a laboratory as the one previously described, but with sound from a loudspeaker under controlled test conditions. The proprietary window investigated in that study presented different results between free field and diffuse field conditions, with higher performance in free field conditions. The authors suggested that openable windows should not be tested in diffuse conditions (as in the standard laboratory conditions described in the ISO 10140 series). Nunes suggests that laboratory measurements tend to underestimate sound insulation compared to field measurements of partially open windows. The field measurements ran in that study achieved consistently higher insulation ratings across octave bands.²² In addition, theoretical calculations based just on the open area (i.e. 10log(S), where S is the ‘open area’) overpredict the reduction in insulation with increasing open area. Moreover, it was demonstrated that façade sound insulation improves with increasing angles away from normal incidence, both horizontally and vertically. Finally, Søndergaard et al.⁴⁸ investigated the range of permissible loudspeaker positions relative to the window opening according to ISO 16283-3.⁴¹ This demonstrated a range of 8–10 dB for the R’_w + C_tr for the different loudspeaker positions, and a value of 6 dB when using road traffic as the sound source.⁴⁸

Field measurements of opening windows with environmental sound sources

There is a range of studies of the in-situ performance of opening windows, for example, Locher et al.⁴⁹ includes a review of previous significant studies considering building applications with windows being (i) closed, (ii) open in the tilted position, or (iii) open in the turned position (the area of the opening is not explicitly identified). Søndergaard et al.’s⁴⁸ study illustrates a discreet difference between loudspeaker tests and tests using road traffic as the sound source. Moreover, Ryan et al.⁵⁰ ran a study including window open areas and room volumes, along with external and internal level differences and standardised level differences. This study reports an external measurement campaign run in front of the façade at ground level, and with 3 dB correction applied to take account for this.⁵⁰ This method targeted the L_eq and L_max using road traffic noise and car door slams as the noise sources. Therefore a simultaneous multiple microphone method was developed using adapted testing procedures outlined in both AS 2702 ‘Acoustics – Methods for the measurement of road traffic noise’⁵¹ and ISO 140-5 ‘Acoustics – Measurement of sound insulation in buildings and of building elements’⁵² (now withdrawn and replaced by ISO 16283-1:2014⁵³ and ISO 16283-3:2016¹⁰). For the noise prediction calculation, the method used is the same as the AcOA method (following EN 12354-3: 2000¹⁰), to a different reference reverberation time than is typically used in the UK (0.35s, c.f. 0.5 s). Even if the study from Ryan et al.⁵⁰ presents separate results, for the sake of completeness of this study, in Figure 5 the Measured and Calculated level difference results can be related considering a reference reverberation time of 0.35 s and the Australian method in AS 3671.⁵⁴ The equation used to calculate the noise reduction is $N R = 10 \log (A / 100)$ , where A is the open area % of the building envelope.⁵⁴ From this figure, it is clear that the AcOA method generally over-predicts the insulation achieved, whereas in the commentary, Ryan indicates that ‘in general the calculated level internally was above the levels that the field measurement achieved’. Therefore, the AcOA calculation method would be prudent, although other evidence presented in this study might suggest otherwise.

Figure 5.

Schematic representing the overall measurement setup.

Field measurements method aligning acoustic and thermal models for partially open windows

In order to run a study as comprehensively as possible, a total of eight sites were investigated in the UK. Although the volume and the furniture of each room were different (see Table 2), these sites had in common a partially open window facing a road with a distance to the nearest edge of the lane between 3 and 13 m. From Table 2 a few details of each site are represented. Site 1 featured a residential window overlooking shops on a high street, with terraced buildings on both sides of the street. This room is largely unfurnished, with an unfinished look – bare walls and an exposed light fixture. The window of the specific site is highlighted. Site 2 is an occupied dwelling, with an opening light on a dual pivot system. The room is full of furniture and lived in and used as a working space. There are terraced dwellings on both sides of the road. For Site 3 only the window and outdoor picture were available, the indoor image is sketched to illustrate the empty room. The window overlooks the road, beyond the construction site that is not complete. Site 4 featured a window in a quite narrow and long furnished room. Externally there is a dual carriageway. For Site 5 an indoor picture was not available, however, the window of the detached dwelling looks out onto a newly-built residential road. Site 6 is characterised by a window with an outdoor view of a road, with trees on the opposite side of the road. The window is in a furnished bedroom. The exterior shot shows a low wall between the residential building and the road. For site 6, the external microphone was located at 1.5 m above the ground (due to practical constraints), whereas the window and room tested were on the first floor. The difference between external sounds levels at the ground and first-floor level were considered to be equivalent. Site 7 is an unfurnished bedroom at first-floor level, overlooking a road to the front of the property. Site 8a and 8b are measurements of two different windows in the same room. 8a is a top-hung section of a French window to a large furnished living room with hard flooring. 8b is a side-hung section of the French window to the same room.

Table 2.

List of measured sites and illustration of key features of each site.

Measurements setup

A selection of sites subjected to consistent road traffic noise was chosen, following the requirements of ISO 16283-3.⁴¹ A count of fifty vehicles passing each site was conducted to determine the minimum measurement duration, which varied between 30 s and 4 min across different locations. Sound measurements were taken simultaneously outdoors, positioned 1–2 m from the façade with a fixed microphone, and indoors using a manual swept microphone technique (following ISO 16283-2⁵³). For Site 6, the measurement setup as described in the Global road traffic method in ISO 16283-3 was approximated as the external microphone position was below 1.5 m above the receiving room floor. However, the microphone in Site 6 was not shielded significantly, as you can see from Table 2, which makes it reasonable to consider the results from Site 6 comparable to the others. Measurements were recorded in frequency bands (predominantly one-third octaves, with one site using 1/1 octaves) across the relevant frequency range to calculate the façade level difference, D_{nT, 2m,w} + C_tr, for each window position. Reverberation time was measured with the window closed, following the guidelines of ISO 3382-2.⁵⁵ Key parameters for each site are summarised in Table 3, while specific features are illustrated in Table 2.

Table 3.

Summary of room parameters, windows characteristics, and Façade position towards the source (nearest lane).

Site reference	Room volume (m³)	Openable pane H × W (mm)	Hanging type	Opening direction	Dist. to nearest lane edge (m)	Ground (G)/first floor (FF) level
1	29.5	1355 × 555	Top hung	Outward	06.25	FF
2	53.8	730 × 780	Top hung	Outward	09.05	FF
3	16.6	1140 × 780	Side hung	Outward	05.50	G
4	12.1	345 × 770	Top hung	Outward	03.30	FF
5	26.5	1020 × 795	Top hung	Outward	13.00	FF
6	26.9	780 × 1150	Top hung	Outward	05.90	FF
7	31.5	550 × 920	Top Hung	Outward	17.00	FF
8a	51.7	400 × 555	Top Hung	Outward	77.00	G
8b	51.7	555 × 1000	Side Hung	Outward	77.00	G

The extent of window openings was measured using a tape measure, as depicted in Figure 6. This measurement represents the distance between the closed position of the window opening and its fully open position. It is conceptualised as a partially open window functioning as a flat rectangular plane hinged to pivot within a flat plane, as described in the Equivalent Area calculator (see the Excel tool³⁷ and the EA-related equations (1)–(5)). This model neglects the thickness of the window frame and opening light, as well as any effects of the reveal, which may influence both airflow and sound insulation performance in various ways. The window was opened in increments of 50 mm, up to approximately 400 mm when feasible, resulting in diverse window opening angles (from 2° to 52°) and areas (ranging from 0.27 to 0.89 m²) across sites. Additionally, measurements of room volume were also conducted (with values from 12.1 to 53.8 m³).

Figure 6.

Measurement of window position, illustrating 0.4 m stroke length (window opening) and 2 m (distance from the wall).

Calculation method

The internal sound level measurements were standardised to a reference reverberation time of 0.5 s. From Practical Acoustic Design – The Apex Method,⁴⁴ the equation for the standardised internal level due to a single element of performance D_n,e can be derived as shown in equation (6). As the external noise ingress through the partially open window dominates the external noise ingress (i.e. other noise ingress paths are of no significance), this equation can be used directly to evaluate the performance of the partially open window, D_n,e:

L_{e q, 2, n T} = L_{1, 2 m} - D_{n, e} - 10 \log (V) + 15

(11)

Where L_{eq,2, nT} is the standardised, spatially-averaged internal sound level, L_{1, 2m} is the level between 1 and 2 m in front of a plane façade, D_n,e is the element normalised level difference, and V is the room volume. The calculations are carried out in frequency bands. The single figure quantity, D_n,e,w + C_tr is calculated according to ISO 717-1.⁵⁶

Results

Comparison of level difference measured and calculated through AcOA and EA

For completeness, each site measurement was run according to the window’s opening angle range. Including a new variable (i.e. the opening angle α) may help to make a potential correlation with a certain degree between this parameter and the level difference (measured or calculated). Indeed, changing the opening angle substantially impacts the area of the opening and therefore the AcOA and EA. In the following results, for each site and each window opening angle, three values of level difference are reported: (i) Measured according to ISO 16283-3,⁴¹ with the element-normalised level difference calculated according to equation (11); (ii) calculated according to equation (6) based on AcOA following equations (7)–(9), and (iii) calculated according to equation (6) based on EA, derived from Appendix D of ADO (Excel tool to calculate EA³⁷). The window opening position can be given in terms of stroke length as measured (mm), or in terms of opening angle as below, calculated from the simplified model of an opening light as a flat rectangular plane. The results are shown in Table 4 and Figure 7.

Table 4.

Summary of all data from the measurement sites including details related to the angle, AcOA, EA, and Level Difference measured and calculated.

Site ref	Opening angle (α)	Acoustic open area, AcOA (m²)	Equivalent Area, EA (m²)	D_n,e,w + C_tr/dB
Site ref	Opening angle (α)	Acoustic open area, AcOA (m²)	Equivalent Area, EA (m²)	Measured	AcOA calculated	EA calculated
1	17	0.75	0.47	11.0	11.2	13.2
	15	0.66	0.44	14.4	11.8	13.6
	13	0.57	0.40	14.8	12.4	14.0
	11	0.48	0.35	15.3	13.2	14.6
	8	0.38	0.30	15.8	14.2	15.3
	6	0.29	0.24	16.7	15.4	16.3
	4	0.19	0.17	17.3	17.2	17.8
	2	0.09	0.09	18.9	20.2	20.6
2	32	0.57	0.37	11.7	12.4	14.3
	28	0.52	0.35	12.7	12.8	14.6
	24	0.45	0.32	12.7	13.5	15.0
	20	0.37	0.28	13.4	14.3	15.5
	16	0.30	0.24	13.4	15.2	16.2
	12	0.23	0.19	14.7	16.5	17.1
	8	0.15	0.14	15.9	18.2	18.6
	4	0.07	0.07	18.0	21.2	21.3
3	30	0.76	0.56	14.5	11.2	12.5
	26	0.67	0.52	14.0	11.8	12.8
	22	0.57	0.47	15.2	12.4	13.2
	18	0.48	0.42	15.5	13.2	13.8
	15	0.38	0.36	16.3	14.2	14.4
	11	0.29	0.29	17.8	15.4	15.4
	7	0.19	0.21	16.8	17.2	16.9
	4	0.10	0.11	18.9	20.2	19.6
4	52	0.27	0.20	17.3	15.8	17.0
	42	0.27	0.19	18.0	15.8	17.3
	34	0.22	0.17	17.8	16.6	17.7
	25	0.17	0.14	18.6	17.8	18.4
	17	0.11	0.11	19.5	19.5	19.6
	8	0.06	0.06	20.3	22.5	22.0
5	23	0.72	0.51	13.5	11.4	12.9
	20	0.63	0.47	14.0	12.0	13.3
	17	0.54	0.43	14.2	12.7	13.7
	14	0.45	0.38	14.8	13.5	14.2
	11	0.36	0.32	14.7	14.4	14.9
	8	0.27	0.26	16.2	15.7	15.9
6	20	0.76	0.53	10.3	11.2	12.8
	18	0.67	0.48	10.4	11.7	13.1
	15	0.58	0.44	10.8	12.4	13.6
	12	0.48	0.38	11.6	13.2	14.2
	10	0.39	0.32	11.6	14.1	14.9
	7	0.29	0.26	12.9	15.4	15.9
	5	0.19	0.18	13.5	17.1	17.4
	2	0.10	0.10	15.3	20.2	20.2
7	43	0,51	0,38	10	13	14
	37	0,50	0,36	11	13	14
	32	0,43	0,33	12	14	15
	26	0,36	0,30	13	14	15
	21	0,29	0,26	14	15	16
	16	0,22	0,21	14	17	17
	10	0,15	0,16	16	18	18
	5	0,07	0,09	18	21	21
8a	60	0.22	0.18	16	17	17
	52	0.22	0.18	17	17	18
	44	0.22	0.17	17	17	18
	36	0.22	0.15	18	17	18
	29	0.19	0.14	18	17	19
	22	0.14	0.12	20	18	19
	14	0.10	0.09	19	20	21
	7	0.05	0.05	21	23	23
8b	43	0.51	0.38	10.5	13.0	14.2
	37	0.50	0.36	11.2	13.0	14.5
	32	0.43	0.33	11.5	13.6	14.8
	26	0.36	0.30	12.8	14.4	15.2
	21	0.29	0.26	13.6	15.3	15.8
	16	0.22	0.21	14.3	16.6	16.7
	10	0.15	0.16	15.5	18.3	18.0
	5	0.07	0.09	18.0	21.3	20.6

Figure 7.

Illustration of all results by site, calculated by EA.

If the data is reviewed site-by-site, as shown in Table 4 and Figure 7, it can be seen that two sites, #2 and #6, exhibit a markedly different pattern from the other sites. Other sites also have outlying points (see site #1, which has the lowest value, and site #4, which has the highest value). With further data, this suggests that it may be possible to subdivide the single classification of a ‘partially open window’ to gain a more accurate calculation if this is considered desirable.

Sites #2 and #6 are the only fully furnished (occupied) rooms. The amount of sound absorption should not make a difference to the measured façade sound insulation performance. Site #2 also differs from others since the opening light does not hinge from the side of the frame, but the hinges allow a certain amount of rotation of the opening light. This means that the simple geometric model of an opening light as a flat plane in a flat plane opening is quite different from reality; the additional opening around the other edges of the opening light in practice may permit more external noise ingress than other window opening light arrangements. The air flow performance may also differ from the simple model.

Site #6 was measured externally at ground level, with the opening window at the first-floor level. There is a low wall between the external microphone position and the road, which could lead to lower sound levels at the microphone position than those incident on the façade at the first-floor level. As the façade is also close to the road, there may be a line of sight from the road directly into the room – it has been demonstrated^22,48 that the insulation of an open window is sensitive to the angle of incidence of incoming sound.

Uncertainty between the measured and calculated values

The graph in Figure 8 shows the error values calculated as the difference between the measured D_n,e,w + C_tr (weighted standardised level difference with spectrum adaptation term) and the D_n,e,w + C_tr values obtained from two calculation methods: (i) based on AcOA and (ii) based on EA. The x-axis represents the AcOA (i.e. window geometrical opening sizes), while the y-axis shows the error between calculated and measured D_n,e,w + C_tr in dB. Positive values indicate an overestimation by the calculation method compared to the measured values, while negative values indicate an underestimation. Two distinct sets of data points are plotted: blue dots correspond to the errors derived from the AcOA method, and orange dots represent the errors from the EA method. From the plot, we observe a distribution of error values, with both methods displaying variations in accuracy across the AcOA range (0 –0.8). Overall, the results show reasonable agreement between the modelled (calculated) values and measured values, on average, although there is quite a large amount of scatter in the data. The EA calculation method results in a standard deviation (1.8 dB) marginally lower than the one of the AcOA calculation method (1.9 dB), but the two models are effectively of similar accuracy in the context of the uncertainties involved.

Figure 8.

Error values related to the difference between the calculated and measured weighted level difference calculated from the acoustic open area (blue dots) and from the equivalent area (orange dots).

The AcOA-based results show better agreement at higher window opening sizes and the EA-based results show better agreement at small window opening sizes. The average error of all data points as an absolute dB value and as a % of the measured D_n,e,w + C_tr is shown in Table 5.

Table 5.

Average errors of modelled results in comparison to measured data.

	All sites		Sites 1, 3, 4, 5, 7, 8a and 8b		Sites 2 and 6
	AcOA	EA	AcOA	EA	AcOA	EA
Average error, dB	1.6	1.6	1.5	1.2	1.9	2.9

Table 5 presents the average errors of modelled D_n,e,w + C_tr results compared to measured data across multiple sites, categorised by the methods used: Acoustical Opening Area (AcOA) and Equivalent Area (EA). The data is divided into three categories: ‘All Sites’, ‘Sites 1, 3, 4, 5, 7, 8a and 8b’ and ‘Sites 2 and 6’. For ‘All Sites’, the average error in dB is the same for both AcOA (1.6 dB) and EA (1.6 dB). Looking at ‘Sites 1, 3, 4, 5, 7, 8a and 8b’ the average error in dB for AcOA is 1.5, while for EA it is significantly lower at 1.2 dB. For ‘Sites 2 and 6’, the results differ more significantly. The AcOA method shows an average error of 1.9 dB, whereas the EA method has a higher error at 2.9 dB. However, comparing an error up to 2.9 dB with the just noticeable difference (JND) of 3 dB,⁵⁷ the difference between results calculated by using AcOA or EA is slightly detectable from a perceptive point of view.

In summary, Table 5 shows that for most sites, the EA method yields lower average errors, especially in the ‘Sites 1, 3, 4, 5, 7, 8a and 8b’ group, while the AcOA method performs better in the ‘Sites 2 and 6’. An obvious reason for this pattern is not apparent through either the conditions between the road and the window or in the type of window itself. It is considered a bigger dataset would need to be reviewed both to confirm such a pattern remains and potential influencing factors.

Influence of the opening angle and the opening area

Whilst the modelled results show reasonable agreement with the measured values for the single figure D_n,e,w + C_tr, the model used assumes the same D_n,e value at each frequency. The measured results do not validate this assumption. To compare spectral data across the various measurement results, the D_n,e values in each 1/3^rd octave band have been shifted such that the D_n,e,w + C_tr value is 15. Third-octave measurement data ranging from 50 to 5000 Hz has been collected for sites 1 to 5 and the adjusted D_n,e values in third-octave bands are shown in Figure 9. Meanwhile,

Figure 9.

Measured spectral D_n,e values for sites 1–5 for AcOA closest to 0.28.

Table 6 lists the opening angles and AcOA values for the corresponding sites. The graph in Figure 9 shows distinct patterns of D_n,e values for each site, with significant variations across the frequency spectrum. Results from Site 1 (Blue line) exhibit a relatively low D_n,e in the lower frequency range (50–315 Hz), with values oscillating between 10 and 15 dB. A large peak occurs around 1600 Hz, where the D_n,e value reaches 30 dB, followed by a significant dip around 3150 Hz and a recovery above 15 dB at 5000 Hz. Similarly to Site 1, Site 2 (Orange line) also shows low sound reduction performance in the lower frequencies, with values around 10–15 dB until 800 Hz. However, unlike Site 1, it has a smoother increase in the middle frequencies, peaking at around 25 dB at 1600 Hz and maintaining moderate performance through the higher frequencies. In Site 3 (Grey line) D_n,e has less fluctuation and is relatively stable across frequencies. It starts at approximately 15 dB and fluctuates minimally between 10 and 20 dB across the entire spectrum. This suggests more consistent sound insulation, though without dramatic improvements at higher frequencies. Results from Site 4 (Yellow line) show substantial fluctuations. The D_n,e is lowest at low frequencies (50–200 Hz) but rapidly increases to around 25 dB by 1000 Hz. It reaches a peak of 30 dB around 3150 Hz before declining sharply at the highest frequencies (5000 Hz). Finally, in Site 5 (Light blue line) results displays the most stable performance in the mid-to-high frequencies with relatively low D_n,e values in the low frequencies (about 10 dB), peaking at 25 dB at 1600 Hz, and declines slightly after 3150 Hz.

Table 6.

Opening angle plotted in Figure 9 for each site.

Site	1	2	3	4	5	7	8a	8b
Opening angle	6	16	11	52	8	21	60	21
AcOA	0.29	0.3	0.29	0.27	0.27	0.29	0.22	0.31

Table 6 provides the opening angles and AcOA values for each of the five sites. The opening angles vary significantly between the sites, with Site 1 having the smallest opening angle (6°) and Site 4 having the largest (52°). Larger opening angles typically correspond to more significant exposure to external noise, potentially impacting the measured sound insulation performance. Site 4, with the largest opening angle, shows large fluctuations in its D_n,e values. The AcOA values, representing the opening area for each site, are fairly consistent across all sites, ranging from 0.27 to 0.30. This suggests that while the opening area conditions may vary slightly, other factors such as opening angles and structural differences likely contribute more to the differences in measured D_n,e performance across the sites.

In general, all sites show lower D_n,e values at lower frequencies (below 315 Hz), indicating poorer sound reduction at these frequencies. This is expected, as lower frequencies diffract around barriers more easily than higher frequencies due to longer wavelengths. As frequency increases, most sites display improved sound reduction, with peaks often occurring in the 1000–3150 Hz range, a frequency band where soundproofing measures tend to be most effective. The variability in sound reduction across the five sites can be attributed to the opening angle, the unique geometrical properties of each site, which also affects sound field structure at the window location. Sites with larger opening angles (such as Site 4) tend to show greater fluctuation in D_n,e values (see Figure 9 and Table 6), possibly due to more significant exposure to external noise. Meanwhile, the consistency in AcOA values suggests that the opening area is not the primary cause of these variations. The performance in the high-frequency range (above 1000 Hz) is generally better across all sites, with most sites achieving D_n,e values of 20 dB or higher. Again, this is potentially due to the difference in diffraction characteristics of different wavelengths and wave interactions associated with the opening geometry.

Figure 9 and Table 6 demonstrate that the sound insulation performance, as measured by D_n,e, varies considerably across frequencies and between sites. While the AcOA values remain relatively stable, factors like the opening angle and specific site conditions (e.g. construction materials, geometry, exposure, sound field structure) contribute to the observed differences in sound reduction. This highlights the importance of site-specific analysis when evaluating sound insulation performance in practice, although with current technology, these effects cannot yet be accounted for.

Significant variation in the spectrum shape is observed across the different sites when comparing similar values for AcOA. Similar results are observed when comparing similar opening angles or similar EA values, as the spectrum shapes for each site are relatively consistent across the various openings. The biggest variations in spectrum shape across the sites are observed in the low and high frequencies, between 630 and 1600 Hz the modelled assumption of a flat spectrum correlates better with the measured data. The frequency range of 630–1600 Hz is the most important in determining the single figure D_n,e,w + C_tr value.

For the measurements listed in Table 6, internal noise levels are calculated based on a road traffic level externally of 65 dBA with a frequency spectrum as given in BS EN 1793-3.⁵⁸ A comparison of overall A-weighted and Linear internal noise levels for a flat D_n,e spectrum and the measured D_n,e spectrum are shown in Table 7. Comparing the results of Table 7, when considering a road traffic noise source and internal A-weighted noise levels, the assumption of a flat spectrum is not likely to contribute significantly to the uncertainty when compared to the measured spectrum at each site. However, more significant differences are observed at low and high frequencies, such that the uncertainty of the model when specific frequency bands are of interest is higher than the overall uncertainty presented.

Table 7.

Comparison of spectrum shapes when calculating internal noise levels.

Site	Calculated from flat D_n,e spectrum		Calculated from measured D_n,e spectrum
Site	dB(A)	dB(Z)	dB(A)	dB(Z)
1	48	54	48	57
2	52	57	52	57
3	47	52	47	53
4	48	53	48	56
5	49	54	49	55
7	52	57	51	54
8a	49	54	49	55
8b	50	55	50	57

Discussion on practical façade assessment for sound insulation and thermal comfort

The sound insulation performance of a façade depends on several factors, including the type of incoming sound field (degree of diffusivity), the angle at which sound waves hit the façade, the design and positioning of the window opening, the depth of the window reveal, the type of opening mechanism, and the acoustic conditions inside the room. However, many of these factors are either unknown or cannot be accurately measured with current technology. Ryan et al.⁵⁰ suggest that there are even more uncertainties when dealing with L_max. Additionally, based on extensive experimental data from Scrosati et al.,⁴⁷ it is not recommended to use loudspeaker tests to characterise façade performance when trying to establish a correlation between external and internal noise level descriptors for environmental noise sources.

In this study, the comparison of results from AcOA and EA was highlighted. The use of the AcOA is based on an engineering concept of the façade element with a sound reduction index of zero, as described in Appendix D of ISO 12354-3.¹⁰ Although we have defined how to calculate the facade element area for consistency, this process is complicated and laborious. ‘All models are wrong - some are useful’, according to George Box.⁵⁹ So, while there is a theoretical justification for using AcOA, there is no physical basis for using EA – there is no physical model that suggests that sound insulation should be based on the airflow performance of an opening. However, the measurements presented here demonstrate that there is no additional uncertainty introduced by the use of EA as opposed to AcOA.

The proprietary window laboratory tests have a calculated EA that matches almost exactly the AcOA, therefore there is no loss of accuracy. The NANR116 data indicates that using EA in this way makes a small difference to the predictions – sometimes they are more accurate, sometimes less. There is a very significant practical advantage in calculating façade sound insulation based on EA, as this aligns with the performance parameter in the thermal (aerodynamic) model. It greatly facilitates the exchange of model attributes with the overheating modeller. The most significant advantage is that in the design process, to assess thermal and acoustic compliance with guidelines, both disciplines use the same values to assess the performance of a partially open window. This also overcomes any need to know the window dimensions and angle of opening (these details of the façade are not needed in the models). Many modellers and other practitioners find the description of AcOA difficult, especially when there is the need to translate it into the intended EA. The combined assessment of thermal and acoustic compliance is complicated. Basing sound insulation on the EA simplifies the process and reduces the risk of greater discrepancies between acoustic modelling assumptions and thermal modelling assumptions.

Conclusions and future studies

This study investigated the relevance of using two parameters related to overheating (EA) and acoustic (AcOA) regulations to determine the Level Difference for partially open windows. The main aim is to facilitate the dialogue between the models in two domains - overheating and acoustics. For this reason, eight sites featuring buildings with partially open windows in the UK were measured according to the BS EN ISO 16283-3⁴¹ and at the same time calculation of the D_n,e was done using AcOA and EA in the equation from BS EN ISO 12354-3.¹⁰ The results suggested that the sound insulation of façade openings may be based on either Acoustic Open Area, AcOA or Equivalent Area, EA with equivalent uncertainty based on the preliminary measurements presented. There are significant practical advantages to the use of EA over AcOA in the modelling of new buildings. There is uncertainty in the prediction of the façade sound insulation of a partially open window. Many advances in acoustic measurements, modelling, laboratory tests, and standardisation of new methods would be required to significantly reduce this uncertainty. The acoustic industry will need to judge if this is a priority, or if simple methods are considered sufficiently accurate. A risk of this approach is that practical details that could improve the sound insulation – for example, a side-hung window opening away from the main noise source, rather than towards it – are not accounted for, and hence appear to have no value in the design, whereas it could potentially make a noticeable difference in practice. Further work is required to expand the data set to a representative sample for the range of different conditions encountered in practice. The performance may also vary with aircraft sound which impacts a partially open window from a different angle.

Footnotes

Authors’ contributions

Jack Harvie-Clark: Conceptualisation, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing; Gioia Fusaro: Data curation, Validation, Visualisation, Writing – original draft, Writing – review & editing; Luis Pereira: Data curation, Formal analysis, Validation; James Hill: Data curation, Formal analysis, Investigation, Validation, Visualisation, Writing – review & editing; James Healey: Conceptualisation, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – original draft.

Data availability statement

The data presented in this study is available on request from the corresponding author.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Jack Harvie-Clark

Gioia Fusaro

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