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Indoor climate design for human comfort, health and wellbeing under a - - PowerPoint PPT Presentation

Jun 21, 2023 227 likes •455 views

IBPSA-England | Modelling Residential Buildings: Comfort, Energy and Wellbeing Thursday 6 th July 2017, Hoare Lea O ffi ces, Western Transit Shed, 12-13 Stable Street, London NC1 4AB Indoor climate design for human comfort, health and wellbeing

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Indoor climate design for human comfort, health and wellbeing under a climate of change

– Modelling approaches

IBPSA-England | Modelling Residential Buildings: Comfort, Energy and Wellbeing
 Thursday 6th July 2017, Hoare Lea Offices, Western Transit Shed, 12-13 Stable Street, London NC1 4AB Dr Anna Mavrogianni | Lecturer in Sustainable Building and Urban Design
 UCL Institute for Environmental Design and Engineering (IEDE), The Bartlett, University College London (UCL)

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

1 | IBPSA-England

IBPSA-England is an affiliate of International Building Performance Simulation Association (IBPSA), a non-profit international society of building performance simulation researchers, developers and practitioners, dedicated to improving the built environment. IBPSA-England is founded to advance and promote the science of building performance simulation in order to improve the design, construction, operation, and maintenance of new and existing buildings. Any individual with an interest in the field of building simulation can become an individual member of IBPSA-England. There will be no membership fee. To become a member (individual or corporate) and join our mailing list please use our new sign-up portal at: http://eepurl.com/85ljr

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

2 | A growing concern

Indoor overheating A nationwide, growing problem that can render homes uninhabitable in summer months. Indoor air pollution Long-term health risks are associated with indoor air pollutants from everyday

  • bjects and appliances as well as
  • utdoor sources.

They affect:

  • the construction industry,
  • social landlords,
  • the health care sector,
  • building owners, and
  • occupiers.
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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

3 | Causes of poor indoor environmental quality

Image source: IPCC 5th Assessment Report

A ‘perfect storm’ of interacting factors

  • climate change
  • urbanization and urban heat islands

Image source: UCL IEDE LUCID project

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

Image source: Hoare Lea

A ‘perfect storm’ of interacting factors

  • climate change
  • urbanization and urban heat islands
  • winter energy efficiency targets
  • drive to reduce construction costs
  • increasing land and housing prices
  • lack of technical skills
  • lack of building regulations
  • lack of transport emissions standards

4 | Causes of poor indoor environmental quality

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

Image source: bit.ly/2szUzys

A ‘perfect storm’ of interacting factors

  • climate change
  • urbanization and urban heat islands
  • winter energy efficiency targets
  • drive to reduce construction costs
  • increasing land and housing prices
  • lack of technical skills
  • lack of building regulations
  • lack of transport emissions standards
  • sociocultural lack of knowledge about

heat and indoor air quality

  • the invisibility of the problem

Image source: bit.ly/2siW67B

5 | Causes of poor indoor environmental quality

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

Indoor overheating and poor air quality impacts can be assessed with respect to: Thermal comfort and wellbeing Productivity Health Energy use and carbon emissions

6 | Causes of poor indoor environmental quality

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

7 | Research questions

What is the relative contribution of: background regional climate local urban climate building energy retrofit inhabitant behaviour space heating energy use summer thermal comfort indoor air quality health

  • n

…at the national or citywide level?

  • n
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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

8 | Housing stock modelling aims

The NIHR Health Protection Research Unit (HPRU) Theme 2 – Healthy Sustainable Cities aims to build on the EPSRC LUCID and NERC AWESOME modelling work in order to create a housing stock indoor environment model for Great Britain that is:


a

  • futurewise (including background global and regional climate change scenarios),
  • localised (factoring in the local climate, e.g. the Urban Heat Island effect),
  • adaptable (able to reflect changes due to land cover changes, e.g. urban greening),
  • scalable (able to model future building stock growth and retrofit),
  • detailed (including a range of inhabitant behaviour scenarios) and
  • validated (using monitored data from the English Housing Energy Follow-Up Survey).

local climate
 change building stock transformations inhabitant behaviour variation regional climate
 change land use
 change

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

9 | Housing stock modelling overview

Housing stock modelling Research questions London Great Britain Sample approach Archetype approach GIS BREDEM Housing surveys EnergyPlus Inferred inputs and assumptions Building fabric External climate Inhabitant behaviour Metamodelling Testing Multiple Linear Regression Artificial Neural Networks Support Vector Networks LUCID data EFUS data

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

10 | Housing stock modelling structure

A geographically-referenced housing stock database was generated using the Homes Energy Efficiency Database (HEED) and the English Housing Survey (EHS). This underpinned the development of individual- address level indoor overheating and air pollution risk modifiers for Great Britain, for use alongside historical weather, outdoor air pollution, population socio-economic data, and mortality data in a large-scale epidemiological investigation.

Image source:
 Taylor et al. 2016

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

11 | GIS-based modelling inputs

Building model inputs are derived using Geographic Information Systems (GIS) databases, such as the Ordnance Survey Topography Layer, and the Geo Information Group’s Building Class product.

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

A meta-modelling framework underpins the development of a national housing stock model that

  • utputs health-related building

performance metrics. Artificial Neural Networks (ANNs) were found to outperform Support Vector Regression (SVR) algorithms.

Image source:
 Symonds et al. 2016

12 | Meta-modelling

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

13 | The role of location

The Urban Heat Island was found to decrease the average annual household space heating load by 14% under the current climate. A further 16% reduction is predicted under a Medium-High emissions scenario in the 2050s.

Space heating demand averaged at Middle Layer Super Output Area level with and without the Urban Heat Island effect under the current and future (Medium- High emissions 2050s) climate Image source: Mavrogianni et al. 2012 (PhD thesis, UCL)

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

14 | The role of dwelling characteristics

  • Indoor overheating is

determined more by the characteristics of a dwelling than its location within a city.

  • Homes most prone to
  • verheating are top-floor flats,

buildings with only one external façade, no shading, very high or very low insulation levels.

  • Internal wall insulation may

increase indoor temperatures if the property is not sufficiently ventilated.

  • Detached and semi-detached

dwellings are the most vulnerable to high levels of infiltration of outdoor air pollution.

  • A. Mean Maximum Daytime living room Temperature (MMDT, oC),
  • B. Mean Maximum Night time bedroom Temperature (MMNT, oC), and
  • C. I/O ratios for PM2.5, for the pensioners’ occupancy assumption

aggregated at the Lower Super Output Area level. Image source: Taylor et al. 2014

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

15 | The role of inhabitant behaviour

Shading windows that receive direct sunlight during the day and ventilating the home when external temperatures are lower can significantly reduce the risk of overheating.

Living room operative temperature distribution for all window opening and lifestyle patterns for dwelling variants before and post full retrofit Image source:
 Mavrogianni et al. 2014

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

16 | Combined effects

Triple heat jeopardy mapping work carried out for the Greater London Authority found that the risk of death during hot weather is most likely in the

  • utskirts of London, where many homes are at

risk of overheating, rather than in the city centre, where outdoor temperatures are generally higher.

Estimated mortality per million population during a warm 55-day period in London Image source: Taylor et al. 2015 Urban
 heat island Population
 age Building
 characteristics

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

17 | Future research

For summary of our research findings please visit: http://www.arcc-network.org.uk/list/ so-what/

  • Use of new EPC database (~15 million

homes) instead of HEED

  • Expansion of the model to include analysis

for effect of environmental change on indoor air quality and moisture related variables

  • Addition of further adaptation options (e.g.

internal blinds, wall/roof albedo, window reflectance)

  • Changing the occupant behaviour to

recent CIBSE TM59 guidelines

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

New Master’s degree: MSc Health, Wellbeing and Sustainable Buildings Creating a new generation of experts who drive sustainable innovation for health and wellbeing in residential and non-domestic buildings Starting September 2017 For further information please contact the Course Director, Dr Marcella Ucci: m.ucci@ucl.ac.uk visit our website: www.ucl.ac.uk/bartlett/environmental-design/ programmes/postgraduate/

  • r follow us on Twitter: @MScHWSB

18 | Sustainable design for health and wellbeing

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

19 | References

  • 1. Symonds P., Taylor J., Shrubsole C., Mavrogianni A., Davies M., Chalabi Z. and Hamilton I., 2017. Overheating in English

dwellings: comparing modelled and monitored large-scale datasets. Building Research & Information, 45(1-2): 195-208. DOI: 10.1080/09613218.2016.1224675

  • 2. Mavrogianni A., Pathan A., Oikonomou E., Biddulph P., Symonds P. and Davies M., 2017. Inhabitant actions and summer
  • verheating risk in London dwellings. Building Research & Information, 45(1-2): 119-142. DOI: 10.1080/09613218.2016.1208431
  • 3. Symonds P., Taylor J., Chalabi Z., Mavrogianni A., Davies M., Hamilton I., Vardoulakis S., Heaviside C. and Macintyre H., 2016.

Development of an England-wide indoor overheating and air pollution model using artificial neural networks. Journal of Building Performance Simulation, 9(6): 606-619. DOI: 10.1080/19401493.2016.1166265

  • 4. Taylor J., Davies M., Mavrogianni A., Shrubsole C., Hamilton I., Das P., Jones B., Oikonomou E. and Biddulph P., 2016. Mapping

indoor overheating and air pollution risk modification across Great Britain: a modelling study. Building and Environment, 99: 1-12. DOI: 10.1016/j.buildenv.2016.01.010

  • 5. Makantasi A.-M. and Mavrogianni A., 2016. Adaptation of London's social housing to climate change through retrofit: a holistic

evaluation approach. Advances in Building Energy Research, 10(1): 99-124. DOI: 10.1080/17512549.2015.1040071

  • 6. Taylor J., Wilkinson P., Davies M., Armstrong B., Chalabi Z., Mavrogianni A., Symonds P., Oikonomou E. and Bohnenstengel S.I.,
  • 2015. Mapping the effects of urban heat island, housing, and age on excess heat-related mortality in London. Urban Climate,

14: 517-528. DOI: 10.1016/j.uclim.2015.08.001

  • 7. Mavrogianni A., Taylor J., Thoua C., Davies M. and Kolm-Murray J., 2015. Urban social housing resilience to excess summer
  • heat. Building Research & Information, 43(3): 316-333. DOI: 10.1080/09613218.2015.991515
  • 8. Taylor J., Mavrogianni A., Davies M., Das P. and Shrubsole C., 2015. Understanding and mitigating overheating and indoor

pollution risks using coupled temperature and indoor air quality models. Building Services Engineering Research & Technology, 36(2): 275-289. DOI: 10.1177/0143624414566474

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IBPSA-England - Modelling Residential Buildings: Comfort, Energy and Wellbeing


Anna Mavrogianni, UCL IEDE

20 | References

  • 9. Taylor J., Shrubsole C., Davies M., Vardoulakis S., Das P., Mavrogianni A. and Oikonomou E., 2014. The modifying effect of the

building envelope on population exposure to PM2.5 from outdoor sources. Indoor Air, 24(6): 639-651. DOI: 10.1111/ina.12116

  • 10. Mavrogianni A., Davies M., Taylor J., Chalabi Z., Biddulph P., Oikonomou E., Das P. and Jones B., 2014. The impact of occupancy

patterns, occupant-controlled ventilation and shading on indoor overheating risk in domestic environments. Building and Environment, 78: 183-198. DOI: 10.1016/j.buildenv.2014.04.008

  • 11. Das P., Shrubsole C., Jones B., Hamilton I., Chalabi Z., Davies M., Mavrogianni A. and Taylor J., 2014. Using probabilistic

sampling-based sensitivity analyses for indoor air quality modelling. Building and Environment, 78: 171-182. DOI: 10.1016/ j.buildenv.2014.04.017

  • 12. Taylor J., Davies M., Mavrogianni A., Chalabi Z., Biddulph P., Oikonomou E., Das P. and Jones B., 2014. The relative importance
  • f input weather data for indoor overheating risk assessment in London dwellings. Building and Environment, 76: 81-91. DOI:

10.1016/j.buildenv.2014.03.010

  • 13. Oikonomou E., Davies M., Mavrogianni A., Biddulph P. and Wilkinson P., 2012. Modelling the relative importance of the urban

heat island and the thermal quality of dwellings for overheating in London. Building and Environment, 57: 223-238. DOI: 10.1016/j.buildenv.2012.04.002

  • 14. Mavrogianni A., Wilkinson P., Davies M., Biddulph P. and Oikonomou E., 2012. Building characteristics as determinants of

propensity to high indoor summer temperatures in London dwellings. Building and Environment, 55: 117-130. DOI: 10.1016/ j.buildenv.2011.12.003

  • 15. Milojevic A., Wilkinson P., Armstrong B., Davies M., Mavrogianni A., Bohnenstengel S.I. and Belcher, S.E., 2011. Impact of

London's urban heat island on heat-related mortality. Epidemiology, 22(1): 182-183. DOI: 10.1097/01.ede.0000392239.91165.65

  • 16. Mavrogianni A., Davies M., Chalabi Z., Wilkinson P., Kolokotroni M. and Milner J., 2009. Space heating demand and heatwave

vulnerability: London domestic stock. Building Research & Information, 37(5): 583-597. DOI: 10.1080/09613210903162597

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Thank you

– Any questions?

a.mavrogianni@ucl.ac.uk @AnnaMvrg

Image source: bit.ly/2tvViNP