Transition towards carbon neutrality : Forecasting Hong Kong's buildings carbon footprint by 2050 using a machine learning approach

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

25 Scopus Citations
View graph of relations

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)633-642
Journal / PublicationSustainable Production and Consumption
Volume35
Online published16 Dec 2022
Publication statusPublished - Jan 2023

Link(s)

Abstract

Hong Kong has planned to achieve zero-carbon emissions before 2050. Hong Kong's building sector is responsible for approximately 60 % of carbon emissions, while its evolutionary trajectories and neutrality pathway remain unclear. To this end, we adopt the STIRPAT model and machine learning approach to identify the most relevant factors and determine their historical correlation with building energy consumption. Then, the out-of-sample prediction is conducted to explore the energy pathway and carbon footprint towards 2050 in the Hong Kong building sector under various assumptions and scenarios. The predicted results suggest that electricity consumption and carbon emissions will continue to increase following current trends. In a moderate scenario, if 2.2 % and 1.6 % of residential and commercial buildings are replaced annually with 2.75 % better energy-performance construction, their electricity consumption is likely to reach 30 %–40 % and 20 %–30 % from the 2015 level as the HK2050 required. With lower electricity emission intensity, the Hong Kong building sector could achieve near zero emissions. Our projection is valuable for developing energy-saving and emission-mitigation strategies towards various carbon neutrality goals in the building sector.

Research Area(s)

  • Carbon footprint, Carbon neutrality, Energy consumption, Hong Kong building, Machine learning

Download Statistics

No data available