Climate adaptive optimization of green roofs and natural night ventilation for lifespan energy performance improvement in office buildings

Green roofs and natural night ventilation are highly coupled and complementary techniques to improve building energy efficiency, but previous studies have not fully explored the synergetic benefits of combining two tech-nologies. Furthermore, the traditional method of design optimization using Typical Meteorological Year (TMY) weather data falls short of providing climate-adaptive designs for new buildings that react differently to weather changes, as well as capturing the applicability and uncertainty of yearly weather variations. Therefore, building long-term performance in practice often deviates significantly from its design expectation. To quantitatively assess the energy savings when integrating green roofs and night ventilation (GR-NV) while taking future long-term weather impacts into account, this study proposes a systematic approach that integrates field testing, sensitivity analysis, building energy simulation, and climate adaptive optimization. The proposed approach is validated and demonstrated in an office building in Chongqing, China. The results show that Chongqing's annual mean air temperature in 2050 would climb by 2.4 C in comparison to that of TMY. With the global warming effects, the annual night ventilation hours and the amount of sensible heat dissipated by NV increased by 78 h (13.2%) and 15.8 MJ/m2 (18.7%) from 1991 to 2050. The choice of plant species in the GR-NV system would also be impacted by global warming. The optimal design alternative based on FMY could reduce annual energy use by up to 5.07 kWh/m2 (12.2%) in new buildings.

Automated summary

Green roofs and natural night ventilation are two techniques that can improve building energy efficiency. This study proposes a systematic approach that combines field testing, sensitivity analysis, building energy simulation, and climate adaptive optimization to quantitatively assess the energy savings of integrating these two techniques. The results show that the choice of plant species in the system and the design based on future weather impacts can significantly reduce annual energy use in new buildings.