Understanding Household Carbon Emissions in Singapore

A Lianhe Zaobao article cites household emissions data from a study by FRS researchers.

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A recent external page Lianhe Zaobao article highlights research on Singapore’s residential carbon footprint, estimating that local households emit 3.5 million tonnes of carbon dioxide annually—an amount requiring 44.8 million trees to offset.

In 2023, household emissions from electricity use were projected to reach 3.57 million tonnes, with HDB flats and private homes contributing 2.1 million tonnes and 1.47 million tonnes respectively. In 2022, emissions totalled 3.61 million tonnes, with HDB flats at 2.11 million tonnes and private homes at 1.5 million tonnes.

These figures stem from the study by FRS researchers Pradeep Alva, Clayton Miller and Rudi Stouffs on “Mitigating operational greenhouse gas emissions in ageing residential buildings using an Urban Digital Twin dashboard”.

A Digital Twin Solution for Emission Reduction

This research introduces the Urban Digital Twin (UDT)GHG App, a decision-support tool designed to help Singapore mitigate greenhouse gas (GHG) emissions in its ageing residential buildings. Integrating advanced modelling techniques provides critical insights for policymakers and urban planners critical insights on household emission reduction and sustainable urban development.

Key features of the GHG App include:
• A Potential for Intervention (PFI) map, which helps decision-makers prioritise low-carbon building rejuvenation
• Emissions mapping data across Singapore's built environment, which supports targeted decarbonisation strategies.

GHG App showing PFI results
GHG App showing PFI results in a heat map for a sample case. Sliders at the bottom-left of the dashboard help users set each parameter weight, based on which PFI maps are automatically generated.

Bridging the Gap Between Research and Action

Singapore’s ageing infrastructure poses significant sustainability challenges, requiring long-term resilience planning, automated building inspection, and effective maintenance.

However, translating complex data into actionable insights remains a hurdle.

To bridge this gap, FRS researchers have integrated FRS BounceBack, an AI-powered chatbot built using Delphi AI. As an open-access tool, BounceBack informs users about emissions data, energy use, and policy strategies specific to Singapore. By making climate action more accessible, it empowers both policymakers and the public.

The study’s findings can contribute to setting GHG accounting standards, emission limits, and decarbonisation planning. Future iterations of the tool will enhance AI-driven insights, further expanding their role in Singapore’s urban sustainability initiatives.

Further Reading

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