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Online ISSN 2819-7046 SPECIAL ISSUE: AMBITION VS ACTIONS 2026

COMMENTARY

Singapore’s Economic Expansion and Relative Decoupling of CO₂ Emissions

JEREMY NYARUNDA MOMANYI

Thompson Rivers University

This commentary applies the IPAT framework to Singapore, a city-nation with one of the highest standards of living in the world (List of countries by GDP (PPP) per capita, 2025). Given such prosperity, Singapore should be leading in emission reduction—but is it? To answer this query, this short opinion piece decomposes the three main factors—population growth, affluence, and technology—that influence CO₂ emissions in Singapore’s economy.

Singapore has experienced sustained GDP growth, becoming one of the world’s most prosperous economies. However, this expansion scales up overall economic activity, thereby leading to higher CO₂ emissions (Ali et al., 2016). A higher standard of living, usually measured by GDP per capita, can also encourage stricter regulations, which redirect firms and consumers toward cleaner and more efficient technologies (Su & Ang, 2020). Such technological advancements tend to reduce the carbon intensity of GDP and can offset emissions arising from growth. Yet, as shown in Figure 1, the scale effect of economic growth has been stronger than technological improvements, driving emissions upward. Singapore’s rising population and affluence have not been sufficiently counterbalanced by improvements in energy and carbon intensity (Chen & Taylor, 2020).

Line graph showing Singapore’s greenhouse gas emissions and GDP per capita over time from 2000 to 2022. The left y-axis line represents greenhouse gas emissions in gigatonnes, which fluctuate in the early 2000s, then generally increase from around 50 to just over 70 by 2022. The right y-axis line represents GDP per capita (constant USD), which shows a steady upward trend overall, rising from approximately $50,000 to over $90,000, with a slight dip around 2020 before continuing to increase. The chart illustrates long-term economic growth alongside rising emissions, with some periods of divergence.

Figure 1: GDP Rises with CO2 Emissions Over Time (Julius AI, 2025).

Table 1 shows the average growth rates of population, GDP per capita, GDP, and carbon intensity across time periods and aligns these trends with their corresponding impacts on CO2 emissions.

Period Population Growth Rate GDP per Capita Growth Rate GDP Growth Rate Carbon Intensity CO2 Emissions Growth
2001-2022 1.53 3.05 4.58 -3.54 1.04
2001-2015 2.12 3.11 5.23 -4.30 0.93
2016-2022a 0.26 2.91 3.17 -1.9 1.27
2016-2022b 0.36 3.99 4.35 -2.5 1.85
2023-2030 0.50 3.50 4.0 -6.74 -2.74
Table 1. IPAT Over Different Intervals of Years

Note. Period 2016-2022a includes the 2020 COVID-19 year, whereas 2016-2022b excludes the 2020 COVID-19 year (World Bank Open Data, Singapore).

The data suggest that in Singapore, economic growth continues to outpace reductions in carbon intensity, leading to rising CO₂ emissions. Prior to the Paris Agreement, between 2001 and 2015, GDP grew by more than 5% annually, outstripping improvements in carbon intensity. The evidence indicates that sustainability mechanisms have not yet been sufficiently strong to offset the pressures of the rapid economy. While investments in clean technology and structural reforms are underway, the data show that Singapore has so far achieved only relative decoupling—emissions have risen more slowly than GDP but have not declined in absolute terms.

The projection to 2030 highlights the scale of Singapore’s decarbonization challenge: emissions must decline from 74.3 MtCO₂e in 2023 to 60 MtCO₂e by 2030, representing an annual reduction of approximately 2.7% and requiring a 6.7% yearly decrease in carbon intensity—almost double the historical rate of improvement (Raihan & Tuspekova, 2022). Achieving this trajectory is highly ambitious and will require accelerated energy transitions, substantial efficiency gains, and expanded regional cooperation on low-carbon energy imports. Without such transformative measures, Singapore risks remaining in a state of relative decoupling, falling short of its climate commitments and its potential to serve as a global leader in sustainable urban development (Katircioğlu, 2014).

A strong policy pathway for Singapore would be to accelerate its transition to renewable and low-carbon energy sources by expanding solar capacity, scaling up regional green electricity imports, and tightening carbon pricing under its existing carbon tax (Lau et al., 2021). Complementary measures, such as incentives for energy-efficient technologies in transport, industry, and buildings, alongside investments in carbon capture and waste-to-energy systems, would further reduce carbon intensity while sustaining economic growth (Alva et al., 2024). Singapore has already introduced several such initiatives, including Southeast Asia’s first carbon tax (scheduled to rise to S$50–80 per tonne by 2030), a shift in power generation from oil to natural gas, and plans for large-scale solar deployment and electricity imports (Loh & Bellam, 2024). Yet, despite these efforts, land constraints and reliance on imported energy mean that only relative decoupling has been achieved to date. To reach net-zero emissions by 2050, Singapore must accelerate its clean-energy transition at an unprecedented pace.


Acknowledgment

This commentary is a result of my independent analysis; however, I acknowledge the use of ChatGPT (version 5) and Julius AI artificial intelligence tools solely for the purpose of refining language and also coming up with the necessary graph to represent the analyzed data. All interpretations, arguments, and conclusions presented are entirely my own.


References

Alva, P., Mosteiro-Romero, M., Miller, C., & Stouffs, R. (2024). Mitigating operational greenhouse gas emissions in ageing residential buildings using an urban digital twin dashboard. Energy and Buildings, 302, Article 114681. https://doi.org/10.1016/j.enbuild.2024.114681

Ali, H., Abdul-Rahim, A., & Ribadu, M. (2016). Urbanization and carbon dioxide emissions in Singapore: Evidence from the ARDL approach. Environmental Science and Pollution Research, 24(2), 1967–1974. https://doi.org/10.1007/s11356-016-7935-z

Chen, Q., & Taylor, D. (2020). Economic development and pollution emissions in Singapore: Evidence in support of the environmental Kuznets curve hypothesis and its implications for regional sustainability. Journal of Cleaner Production, 243, Article 118637. https://doi.org/10.1016/j.jclepro.2019.11863

Julius AI. (2025). Julius AI [Large language model]. https://julius.ai/

Katircioğlu, S. (2014). Testing the tourism-induced EKC hypothesis: The case of Singapore. Economic Modelling, 41, 383–391. https://doi.org/10.1016/j.econmod.2014.05.028

Lau, H., Ramakrishna, S., Zhang, K., & Hameed, M. (2021). A decarbonization roadmap for Singapore and its energy policy implications. Energies, 14(20), Article 6455. https://doi.org/10.3390/en14206455

List of countries by GDP (PPP) per capita. (2025). In Wikipedia. Retrieved October 6, 2025, from https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(PPP)_per_capita

Loh, J., & Bellam, S. (2024). Towards net zero: Evaluating energy security in Singapore using system dynamics modelling. Applied Energy, 353, Article 122537. https://doi.org/10.1016/j.apenergy.2023.122537

OpenAI. (2025). ChatGPT (Oct 6 version) [Large language model]. https://chat.openai.com/

Raihan, A., & Tuspekova, A. (2022). The nexus between economic growth, energy use, urbanization, tourism, and carbon dioxide emissions: New insights from Singapore. Sustainability Analytics and Modeling, 2, Article 100009. https://doi.org/10.1016/j.samod.2022.100009

Su, B., & Ang, B. (2020). Demand contributors and driving factors of Singapore’s aggregate carbon intensities. Energy Policy, 146, 111817. https://doi.org/10.1016/j.enpol.2020.111817

World Bank Group. (2025). Singapore | Data. World Bank Open Data. https://www.worldbank.org/en/country/singapore


Author

Momanyi Jeremy Nyarunda is a graduate student in Economics at Thompson Rivers University, with academic interests in environmental and natural resource economics, climate policy, and sustainable development. His work focuses on the economic dimensions of climate change, carbon emissions, and growth–environment trade-offs in advanced and emerging economies. He is particularly interested in applying empirical economic frameworks, such as the IPAT model and the Environmental Kuznets Curve, to real-world policy challenges.


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