Buildings in China cover a total floor area of over 65 billion square metres and account for more than a fifth of the country’s total electricity consumption. Keeping indoor spaces at the right temperature throughout the year is therefore a significant economic challenge, with traditional heating and cooling systems requiring vast amounts of energy to operate.
Following a large-scale study involving 28,000 participants in 14 major cities across different climatic zones of China, a research team led by Professor Runming Yao at the University of Reading developed a model to promote thermal comfort while minimising energy consumption, ultimately reducing carbon emissions.
The Adaptive Predicted Mean Vote (aPMV) model, which combines data on climate and outdoor temperature with information about human behaviour and physiology, has been used to design climate-responsive, low-carbon buildings and new thermal technology.
The model has been adopted by the Chinese government as the basis for three national green building standards, to discourage developments with excessive heating and cooling demands. It has also changed industry practice by informing standards set by national professional bodies, and has influenced the design of air conditioning technology by promoting the use of seasonal control modes that significantly reduce energy consumption.
With the demand for improved indoor thermal environment control predicted to grow further as a result of the ongoing effects of climate change, this research by the University of Reading represents a vital step towards an environmentally sustainable future for China.
Find out more
View the full impact case study on the REF 2021 website: Energy Savings Through Adoption of Adaptive Thermal Comfort Models in Chinese Building Design Standards