Sample Research Paper on Global Warming

Data Collection

To complete this research 30 countries were selected with indication of their Human
Development Index (HDI) and CO2 emissions per capita in three separate years. Of the 30 states;
10 (highest HDI), 10 (medium HDI) and 10 (lowest HDI). The independent variable of this
assessment is the year. The dependent variables are the CO2 emissions in metric tons per capita
and the HDI levels within the three separate years. It would help the assessment be as wide-
ranging, accurate and representative as possible.
One table was constructed and recorded the HDI values and CO2 emissions per capita in
a million metric tons per country in those years. States were arranged by their highest to lowest
HDI value in the third year. Also recorded were the significance values in which HDI
contributed to the amount of per capita CO2 emissions. Significance ranking ranged from 0-10;
0-3(not significant), 4-6 (quite significant), 7-9(very significant) and 10 and above (extremely
Results and observations were collated to understand whether the increase in HDI level is
necessarily relative to a rise in the amount of CO2 emissions per capita in a country. The
information was represented in the form of graphs to assess how and at what margin does HDI
affects the per capita CO2 emissions. The reasons given were analyzed according to the given
results. The results were also critically evaluated based on analysis of reliability and indication of
possible future improvements


The data collected accepted the hypothesis that the higher the HDI value of a country the
higher its per capita CO2 emissions while, the lower the HDI value, the more moderate per

capita emissions. It was evident for the fact that most countries with high HDI value such as
European Union and Japan recorded the highest amount of CO2 emissions per capita. Nations
with gradually increasing (medium) HDI value such as China recorded as well a significant
increase in their CO2 emissions per capita. Countries such as Burundi with low HDI recorded
close to zero CO2 emissions per capita. Probable cause is that where HDI value is increasing,
energy consumption is increasing whereby the largest energy-source is fossil fuels – a primary
source of CO2 release.
However, a country could be on the same HDI value with another but have significant
differences in the amount of CO2 emissions per capita. Switzerland and USA have hardly any
appreciable difference in their HDI value yet Switzerland’s per capita CO2 emissions were three
times less than that of the USA. The probable cause of difference could be population size of a
country to emissions per person. Some states, especially those with high HDI, while having high
per capita emissions were recording a sense of stability or decline in their per capita CO2
emissions such as Canada and Netherlands. The reason could be of the use of alternative
renewable sources of energy or high taxation on fossil fuel-based products.
Another notable deviation was of low or medium HDI value countries such as Trinidad &
Tobago recording high per capita emissions similar to high HDI countries such as Norway and
Luxembourg. The reason could be having lax environmental laws which lead to uncontrolled
pollutions and the high demand for cheap goods encourages low-cost productions.



The assessment utilized various sources and was able to reach a fair and justified
conclusion. However, some aspects would have been improved such as using data from more
than three years to widen the survey and collate more accurate results.


The data accepted the hypothesis, but I did not wholeheartedly agree with it. Few
countries showed that despite where their HDI level was, it did not correlate with per capita CO2
emissions as depicted by the hypothesis. On the whole, though, the data mainly proved that the
higher the HDI level of a country, the higher its energy consumption and resultantly the higher its per capita CO2 emissions.