Remodelling Building Design Sustainability from a Human Centred Approach (Refresh) project overview

By: Hannah Gough

In 2014, 54 % of the world’s population resided in an urban area and this is projected to rise to 66 % by 2050 (United Nations, 2014). It is also estimated that 90 % of people’s time in developed countries is spent indoors, either at home, at work, or travelling between the two (Klepeis et al., 2001). This equates to a lot of time spent indoors within an urban environment with the indoor and outdoor environments being strongly interlinked.

We’ve all experienced the after-lunch productivity slump, or wished to escape from a dark, stuffy and overcrowded meeting room. The Refresh project set out to explore the impact of urban microclimate on building ventilation for optimal performance of occupants using the meteorological knowledge from Reading, the indoor environmental expertise from Leeds and the human behaviour measurement skills from Southampton. The quality of indoor environments plays an important role in the physical and mental health and
well-being of the occupants (Vardoulakis and Heaviside, 2012).

Figure 1: a) Full-scale array at Silsoe UK, with scale marked in yellow, Car circled to give an indication of size. Red dot represents the reference mast, with the orange dot highlighting the location of the local mast. b) and c) are outputs of the CFD model. d) is the 20 mm cube used in the 1:300 scale wind tunnel model and e) is the cube from d) within the array. Refs: Gough et al., in review; King et al., 2017a; 2017b,  Gough, 2017; Gough et al., 2018a; Gough et al., 2018b

One part focused on flow behaviour in and around a building within a simplified urban environment through a full-scale field campaign which combined the methodologies of meteorology and engineering (Figure 1, Gough, 2017; Gough et al., 2018a; Gough et al., 2018b). The dataset spans nine months and is accompanied by wind tunnel (1:300 scale) experiments and CFD (Computational Fluid Dynamics) modelling to aid understanding (Figure 1, Gough et al., in review; King et al., 2017a; 2017b). So far, it’s been found that two methods of measuring ventilation (tracer gas and pressure difference) vary depending on the external driving conditions (Gough et al., 2018b) and that natural ventilation is difficult to predict due to the interaction of wind direction, wind speed, temperature and turbulence, sometimes causing a dual local flow behaviour for a single reference wind direction (Gough et al., 2018a). For the pressure on the cube faces, current models capture it well for a single building, but do not capture the correct shape for a surrounded building, due to the unique features of the site not being accounted for (Gough et al., in review). This will have a larger effect, especially in more built up urban areas.

Current work includes using the models created by the Dispersion of Air Pollution and its Penetration into the Local Environment (DAPPLE project)(Arnold et al., 2004; Dobre et al., 2005; Barlow et al., 2009) to predict local flow and testing existing models to predict natural ventilation rate against Refresh data (De Gids and Phaff, 1982; Warren and Parkins, 1985; Larsen et al., 2018).

Figure 2: Example of the Aether device highlighting the levels of CO2, temperature and humidity within a room with colour coded feedback for ease of understanding (Snow et al, in Prep)

Focusing on human behaviour within offices, poor indoor air quality does not always equate to rational actions by office workers to improve conditions (Snow et al., 2016). This means that although a building may operate perfectly in design tests, when you include people, you find that they may work against the design! Shared offices often have a social hierarchy of people, with ‘Gatekeepers’ for window opening or thermostat control. By including devices such as the Aether  (Snow et al, in prep) in the room indoor air quality is then socially negotiated.

Figure 3: Participant undergoing the calibration procedure of the EEG studies into the effect of CO2 within a typical university office environment. A CO2 sensor is visible on the drawers with cognitive performance tests being undertaken on the computer.

Tests using EEG (electroencephalogram) found a marginal effect of a 2,700 ppm CO2 environment (offices regularly reach this level) on executive function and the ability to sustain attention, regardless of the perception of the air quality (Snow et al., 2018) (Figure 3). This gives us the hypothesis that poor indoor air quality can impact cognitive performance prior to individual awareness.

Looking forwards, we’re going to be working with the MAGIC project at their field-site in London (Figure 4) using Doppler lidar wind data and looking into the benefits of post-occupancy evaluations.

References:
Arnold, S.J., ApSimon, H., Barlow, J., Belcher, S., Bell, M., Boddy, J.W., Britter, R., Cheng, H., Clark, R., Colvile, R.N., Dimitroulopoulou, S., Dobre, a, Greally, B., Kaur, S., Knights, a, Lawton, T., Makepeace, a, Martin, D., Neophytou, M., Neville, S., Nieuwenhuijsen, M., Nickless, G., Price, C., Robins, a, Shallcross, D., Simmonds, P., Smalley, R.J., Tate, J., Tomlin, a S., Wang, H., Walsh, P., 2004. Introduction to the DAPPLE Air Pollution Project. Sci. Total Environ. 332, 139–53. doi:10.1016/j.scitotenv.2004.04.020

Barlow, J.F., Dobre, A., Smalley, R.J., Arnold, S.J., Tomlin, A.S., Belcher, S.E., 2009. Referencing of street-level flows measured during the DAPPLE 2004 campaign. Atmos. Environ. 43, 5536–5544. doi:10.1016/j.atmosenv.2009.05.021

De Gids, W., Phaff, H., 1982. Ventilation rates and energy consumption due to open windows: a brief overview of research in the Netherlands. Air infiltration Rev. 4, 4–5.

Dobre, A., Arnold, S., Smalley, R., Boddy, J., Barlow, J., Tomlin, A., Belcher, S., 2005. Flow field measurements in the proximity of an urban intersection in London, UK. Atmos. Environ. 39, 4647–4657. doi:10.1016/j.atmosenv.2005.04.015

Gough, H., 2017. Effects of meteorological conditions on building natural ventilation in idealised urban settings. PhD thesis. University of Reading, Department of Meteorology.
Gough, H., Sato, T., Halios, C., Grimmond, C.S.B., Luo, Z., Barlow, J.F., Robertson, A., Hoxey, A., Quinn, A., 2018. Effects of variability of local winds on cross ventilation for a simplified building within a full-scale asymmetric array: Overview of the Silsoe field campaign. J. Wind Eng. Ind. Aerodyn. 175C, 408–418.

Gough, H.L., King, M.-F., Nathan, P., Sue Grimmond, C.S., Robins, A.G., Noakes, C.J., Luo, Z., Barlow, J.F., n.d. Influence of neighbouring structures on building façade pressures: comparison between full-scale, wind-tunnel, CFD and practitioner guidelines. J. Wind Eng. Ind. Aerodyn.

Gough, H.L., Luo, Z., Halios, C.H., King, M.F., Noakes, C.J., Grimmond, C.S.B., Barlow, J.F., Hoxey, R., Quinn, A.D., 2018. Field measurement of natural ventilation rate in an idealised full-scale building located in a staggered urban array: Comparison between tracer gas and pressure-based methods. Build. Environ. 137, 246–256. doi:10.1016/j.buildenv.2018.03.055

King, M.F., Gough, H.L., Halios, C., Barlow, J.F., Robertson, A., Hoxey, R., Noakes, C.J., 2017a. Investigating the influence of neighbouring structures on natural ventilation potential of a full-scale cubical building using time-dependent CFD. J. Wind Eng. Ind. Aerodyn. 169, 265–279. doi:10.1016/j.jweia.2017.07.020

King, M.F., Khan, A., Delbosc, N., Gough, H.L., Halios, C., Barlow, J.F., Noakes, C.J., 2017b. Modelling urban airflow and natural ventilation using a GPU-based lattice-Boltzmann method. Build. Environ. 125, 273–284. doi:10.1016/j.buildenv.2017.08.048

Klepeis, N.E., Nelson, W.C., Ott, W.R., Robinson, J.P., Tsang, A.M., Switzer, P., Behar, J. V, Hern, S.C., Engelmann, W.H., 2001. The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants. J. Expo. Sci. Environ. Epidemiol. 11, 231.

Larsen, T.S., Plesner, C., Leprince, V., Carrié, F.R., Bejder, A.K., 2018. Calculation methods for single-sided natural ventilation: Now and ahead. Energy Build. 177, 279–289. doi:10.1016/j.enbuild.2018.06.047

Snow, S., Boyson, A., King, M.-F., Malik, O., Coutts, L., Noakes, C., Gough, H., Barlow, J., Schraefel, M. c., 2018. Using EEG to characterise drowsiness during short duration exposure to elevated indoor Carbon Dioxide concentrations. bioRxiv 483750. doi:10.1101/483750

Snow, S., Soska, A., Chatterjee, S.K., Schraefel, M. c., 2016. Keep Calm and Carry On: Exploring the Social Determinants of Indoor Environment Quality, in: Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems – CHI EA ’16. ACM Press, New York, New York, USA, pp. 1476–1482. doi:10.1145/2851581.2892490

United Nations, 2014. World Urbanization Prospects 2014 revision (highlights). New York.

Vardoulakis, S., Heaviside, C., 2012. Health Effects of Climate Change in the UK 2012.

Warren, P.R., Parkins, L.M., 1985. Single-sided ventilation through open windows, in: Conf. Proc. Thermal Performance of the Exterior Envelopes of Buildings, ASHRAE, Florida. p. 20.

 

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