Thermal resilience in a renovated nearly zero-energy dwelling during intense heat waves

Figures & data

Figure 1. Heat wave-related mortalities around the globe during the past decades. Map generated using MapChart (2022).

Table 1. Summary of recent literature on heatwave impacts on building performance.

Location and Climate	Study type	Core focus	Operation	Key findings	Reference
Studies from mixed humid climates (4A)
London (4A), UK	Observational with field measurements and surveys	Overheating	Air-conditioned Free-running	Dwellings built after 1996, under higher energy efficiency standards, tend to have indoor temperatures that were significantly higher and remained above thresholds for a longer period than older homes.	Pathan et al. (2017)
Exeter (4A), UK	Observational with field measurements and surveys	Overheating	Free-running	Overheating happened frequently and disproportionately in dwellings with vulnerable occupants, even during summers without extreme or prolonged heat waves, which is a significant find.	Vellei et al. (2017)
Leeds (4A), UK	Observational with field measurements and surveys	Overheating	Free-running	Due to inadequate shading for excessively large windows and poor ventilation control, the study apartments were prone to overheating. However, overheating was significantly reduced through the efficient use of windows and continuous mechanical extract ventilation (MEV).	Baborska-Narożny et al. (2017)
London (4A), UK	Observational with field measurements and surveys Modeling with EnergyPlus	Overheating	Air-conditioned	The monitoring data showed that under the current climate, London homes, particularly bedrooms, are already at risk of overheating during hot spells. The occupant behaviour should align with model assumptions to obtain reliable modeling outputs for overheating analysis.	Mavrogianni et al. (2017)
London (4A), UK	Modeling with EnergyPlus	Overheating	Free-running	Controlling window openings during the hottest periods while keeping curtains closed during the day was the most cost-effective measure. Heating energy-saving measures poorly impact overheating by being ineffective or making it worse.	Porritt et al. (2012)
Perugia (4A), Italy	Modeling with EnergyPlus	Overheating	Air-conditioned	High thermal insulation levels in the envelope raised the risk of indoor overheating in study dwellings. Temperature values between 24 and 28°C were achieved due to active cooling systems.	Pyrgou et al. (2017)
Studies from other humid climate zones
Central England (4A) and (5A), UK	Observational with field measurements	Overheating	Free-running	Recently built dwellings showed much higher mean temperatures than those from earlier times. Temperatures above thresholds were more persistent in newer dwellings than in older ones.	Morey et al. (2020)
Athens (3A), Greece	Observational with field measurements	Overheating	Free-running	Thermal comfort evaluations from 50 low-income non-air-conditioned houses during the summer of 2007 indicated very high indoor temperatures up to 40°C and a rise of 4.2°C in mean temperature during July.	Sakka et al. (2012)
Rome (3A), Italy	Observational with field measurements Modeling with simulations	Overheating Energy use	Air-conditioned Free-running	The average operating temperature increased by more than 5°C due to the combined effects of the heat wave in an urban setting. Heat waves significantly worsen the thermal comfort conditions in free-floating buildings.	Zinzi et al. (2020)
Buenos Aires (3A), Argentina	Modeling with EnergyPlus	Overheating	Free-running	Relatively brief heat waves can also significantly impact the indoor environment, so they shouldn't be ignored when analyzing a building's resilience.	Flores-Larsen et al. (2022)
Zurich (5A), Switzerland	Observational with field measurements Modeling with simulations	Overheating	Air-conditioned Free-running	Thermal comfort in urban environments was moderately improved by precooling the building before the heat wave. The combination of precooling and moisture desorption was more energy-efficient than air-conditioning.	Zhou et al. (2020)
Toronto (5A), Ottawa (6A), Montreal (6A), Canada Houston (2A), Baltimore (4A), USA	Modeling with EnergyPlus	Overheating	Intermittent air-conditioning	The building operation with closed interior blinds and open windows was appropriate for cold climatic areas, and the building operation with closed external shades and open windows was suitable for hot climatic areas.	Ji et al. (2022)
Atlanta (3A), Detroit (5A), USA	Modeling with simulations	Heat exposure	Free-running	Heat exposure is more common for low-income and high-income households due to the lack of air conditioning. When air conditioning fails, extreme heat inside buildings can reach dangerously high levels.	Stone Jr. et al. (2021b)
Studies from dry climate zones
Phoenix (1B), USA	Modeling with EnergyPlus	Heat exposure	Free-running	The heat exposure in the reference buildings was high due to inadequate HVAC and/or power outages. The extreme heat impacts can be reduced by adaptation strategies like installing battery-operated cooling systems and onsite renewable energy for evaporative cooling.	Rajput et al. (2022)
Phoenix (1B), USA	Modeling with EnergyPlus	Heat exposure	Free-running	Homes with intermittent access to mechanical air conditioning will be exposed to a high heat exposure risk due to a rise in summer cooling needs in parallel with rising summer temperatures.	Stone Jr. et al. (2021a)

Figure 2. Proposed study workflow.

Figure 3. Heat wave detection thresholds (Ouzeau et al. 2016).

Figure 4. Belgian study locations and the weather stations used for data extraction used in the study.

Figure 5. The renovated nearly zero-energy dwelling simulation model and floor layout.

Figure 6. Heat waves identified and classified across the study locations in Belgium from 2001 to 2020.

Figure 7. The most intense heat waves with occurrence [year], global intensity [°C.days], maximum temperature [°C], and duration [days] geolocated on the study locations in Belgium from 2001 to 2020.

Figure 8. Characterization of thermal resilience of cooling strategies in reference dwelling before, during, and after the intense heat wave in Antwerp, Belgium, from July 16, 2018, to August 14, 2018.

Table 2. Thermal resilience quantification using degree-hours [°C-hours] for cooling strategies outside each temperature threshold before, during, and after the intense heat wave in Antwerp, Belgium, from July 16, 2018, to August 14, 2018.

	Above designed minimum value: 26°C			Above critical value: 30°C
Event	Strategy 01	Strategy 02	Decrease [%]	Strategy 01	Strategy 02	Decrease [%]
Before heat wave [16/07 – 22/07]	13.29	0	100	0	0	–
During heat wave [23/07 – 07/08]	333.34	4.96	98	2.75	0	100
After heat wave [08/07 – 14/08]	0.72	0	100	0	0	–

Figure 9. Indoor Overheating Degree [°C] in different occupied zones in the reference nearly zero-energy dwelling before, during, and after the most intense heat wave in Antwerp, Belgium, from July 16, 2018, to August 14, 2018.

Figure 10. Percentage of overheating exceedance hours [%] in the reference dwelling zones during the intense heat wave in Antwerp, Belgium, from July 23, 2018, to August 07, 2018.

Table A.1. The general description of the reference dwelling.

Building characteristics	Values
Number of floors [-]	3
Total area [m^2 ]	173
Occupants [-]	4
Total volume [m^3]	873
External wall area [m^2]	122
Roof area [m^2]	91
Floor area [m^2]	259
Window area [m^2]	41
Window U-value [W/m^2K]	1.20
Window G-value [-]	0.60
Wall surface absorptance (-)	0.90
Walls U-value [W/m^2K]	0.40
Roof U-value [W/m^2K]	0.30
Ground U-value [W/m^2K]	0.30
Attic floor U-value [W/m^2K]	0.80
Airtightness (at 50 Pa m^3/h.m^2) [ACH]	1.58

Table A.2. The DesignBuilder model inputs.

Active cooling	Strategy 02
Production	Reversible VRF unit (electric)
Distribution	DX cooling coils
Target zones	Bedrooms, Office room, Living + Kitchen
Cooling	Setpoint: 26°C, Setback: 50°C
Nominal COP	3.3 (Legal Information Institute 2022)
Fuel type	Electricity
Sizing factor	1
Schedule	On: 24/7
Mechanical ventilation	Strategy 01 and Strategy 02
Target zones	Bedrooms, Office room, Living + Kitchen
Ventilation rates	8.33 l/s/person (CEN 2019)
AHU type	Constant Air Volume
AHU fans	Constant volume fans
Nominal COP	0.7
Schedule	On: 24/7

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Data availability statement

The Python code used for heatwave identification, classification, and visualization is available at: doi.org/10.5281/zenodo.7326894 (Joshi et al. 2022).