Singapore’s population has showed a general increasing trend. This is projected even in the future.

https://blog.euromonitor.com/2015/07/singaporean-consumers-in-2020-a-look-into-the-future.html
Population of people aged 15 – 65+ in Singapore. From: Euromonitor International from national statistics/UN

An effect of this huge population is higher amounts of greenhouse gas emissions. Note the similarity in trend for carbon dioxide emissions as well (below).

http://climateactiontracker.org/countries/singapore.html

Why is this so? According to Birdsall (1992), he proposed 2 mechanisms in which population growth could contribute to greenhouse gas emissions.

 1.  Increased energy demands for power, industry and transportation.

Larger energy demands usually lead to increased fossil fuel extraction and burning – leading to higher emissions.

Data extracted from the World Bank indeed shows that energy consumption has risen over the years in Singapore.

https://data.worldbank.org/indicator/EG.USE.PCAP.KG.OE?locations=SG-MY-HK

Also, we have been consuming more electricity that is generated from these energy sources.

https://data.worldbank.org/indicator/EG.USE.ELEC.KH.PC?locations=SG
Electric power consumption (kWh per capita)

However, interestingly, most of the emissions is projected to come from industries in the future. This seems to be indirectly linked to population growth, which we will usually think of household consumption instead. However, a larger population will lead to increased demand for goods – factories will have to produce more to meet our increased consumption (a more indirect link). Refer to the diagram below to see predicted percentages for 2020.

https://www.nccs.gov.sg/climate-change-and-singapore/national-circumstances/singapore%27s-emissions-profile

 2. Greater rate of deforestation e.g. in response to changes for land use.

Large scale deforestation has occured in Singapore since our Independence in 1959. We started moving towards urbanisation. By 1990, more than 99% of the original forest was cleared, more than half of Singapore had been urbanised and most of the plantations were abandoned (Corlett 1991, 1992).

Even after the 1990s, deforestation is still presently being carried out. Deforestation releases large amounts of carbon dioxide. This is as there will be less of their absorption by trees – Instead, it will be produced if the trees have been burnt or left to rot. Look at the diagram below to see Singapore’s deforestation effect on carbon dioxide emissions.

 

http://www.globalforestwatch.org/country/SGP

General findings

Our general findings between the positive correlation between population growth and emissions are supported by a study conducted by Shi (2001). He predicted that global emissions will be larger if a country has higher population growth – Greatest emissions under high population growth scenario (see below).

http://archive.iussp.org/Brazil2001/s00/S09_04_Shi.pdf

Population is positively correlated with carbon dioxide emissions (r = +0.51) – meaning: higher population leads to higher emissions.

Correlation of Variables Used in the Study: 1975-1996
Source: The World Bank (Table 2)
Variable (1) (2) (3) mean std.dev min max
(1)       42.72 148 0.01 1,447
(2) 0.21
(0.001)
    7,630 9,861 84.72 45,951
(3) 0.51
(0.001)
-0.10
(0.001)
  45.01 138 0.16 1,215
(4) 0.02
(0.296)
0.71
(0.001)
-0.14
(0.001)
3.05 2.53 0.200 25.67

P values are in the parentheses
(1) CO2 emissions in 1,000,000.
(2) GDP per capita.
(3) Population in 1,000,000.
(4) Energy efficiency.

Interestingly, he found out that the impact of population pressure on emission is more pronounced in developing than developed countries. In low income countries, for example, a one- percent increase in population raised the emissions by 1.85%, 1.66% in lower middle income countries and 0.64% in high income countries.

Unstandardised Regression Coefficients from the Fixed-Effects Regression of the CO2 Emissions: the Role of Population, Affluence, and Energy Efficiency for Low, Low Middle, Upper Middle, and High Income Countries: 1975-1996
Source: The World Bank (Table 4)
Variable Low
Income
Countries
Low
Middle
Income
Countries
Upper
Middle
Income
Countries
High
Income
Countries
  (absolute t value in parentheses)
Intercept  -24.47**
(2.34)
-20.52***
(5.73)
-4.13
(0.79)
-3.20
(0.82)
GDP per capita 1.55***
(9.21)
1.16***
(16.80)
0.66***
(5.94)
1.07***
(9.77)
Population 1.85***
(2.81)
1.66***
(7.96)
0.96***
(3.08)
0.64***
(2.97)
Energy Efficiency -0.93***
(4.71)
-0.55***
(8.60)
-0.25***
(3.17)
-0.21***
(5.24)
Rho -0.49***
(12.00)
-0.72***
(20.82)
-0.92***
(34.60)
-0.95***
(68.34)
fitness statistics
Durbin-Watson
AIC
Degree of freedom
Number of countries
2.13
213
490
26
2.164
-944
469
24
1.89
-488
263
14
1.84
-1005
584
29
All models include country and year fixed effects, and all variables are in ln forms.
The error terms are adjusted for first-order autocorrelation, using maximum likelihood methods. Its coefficients (AR1) are represented by rho.
***P<0.01
**P<0.05
*P<0.10

Based on these findings, the rise in emissions could at least be partially attributed to the increasing population. We are already ranked 26th among 142 countries per capita of emissions (see figure below). Multiplying this by a larger population will inevitably lead to a higher emission value.

https://www.nccs.gov.sg/climate-change-and-singapore/national-circumstances/singapore%27s-emissions-profile
Source: CO2 Emissions from Fuel Combustion – 2015 Highlights © OECD/International Energy Agency, 2015. From National Climate Change Secretariat (NCCS).