Being a bit of a hippy I’m often drawn to those lists that rank the world’s nations according to their degradation of our environment. The USA, Russia, China and India most often occupy the seats as the planet’s worst CO2 emission offenders. The United Kingdom being a bit further down the lists (admittedly not much further down) allows me to remain smug in the knowledge that my fair island isn’t one of the top contributors to global warming. However, one thing that does snag as unfair about the environmental shame tallies is that countries that produce the most CO2, more often than not have some of the largest populations. This prompted me to attempt to construct a new list. Rather than the countries studied being ranked based on their total emissions I have compiled a ranking based on carbon and CO2 contribution relative to their population, namely per 10,000 people. The equation used is embarrassingly simple: Total CO2 from greenhouses gases/population from year of study x 10,000. Given than I am no statistician it’s safe to assume that the maths is far too basic to provide an accurate picture but I hope it does produce a rough guideline.
When I first embarked into this waste of my free time I intended to cover every nation. This proved unfeasible because countries that produced the least CO2 tended to have fairly undeveloped economies. In order to rectify this I placed a number of filters in place such as United Nations membership; whether the country was placed on the United Nations ‘Least Developed Nations’ listing; and whether they fit within the top 70World Bank and IMF GDP lists. The issue with these filters is that they often excluded larger economies from Asia such as India, whilst allowing very small countries such as Liechtenstein into the study.
Eventually, I concluded to start with a much smaller sample of countries: those within European Economic Area (henceforth EEA). My reasoning for this was that the countries are fairly close together but produce very different amounts of emissions. Furthermore, their are large differences in populations e.g. Iceland has a population of less than 500,000 compared to countries such as Germany and Italy with a population exceeding ten million. This will allow for future examination into population size and possible links to greenhouse gas emissions. Finally, seeing as all these countries are within the EEA they will have fairly similar capitalist based economies with varying GPD and social policy which will allow for study into finances, politics and taxation and their correlation with environmental degradation.
The following lists are taken from two studies.The first is from the World Bank (2012) which highlights the world’s nations by “Total greenhouse gas emissions (kt of CO2 equivalent)”. The second study is from the Carbon Dioxide Analysis Center (2013) which ranks countries by “total CO2 emissions from fossil fuel burning, cement production and gas flaring expressed in thousand metric tons of carbon”. I utilised the data from both investigations to examine contribution of each EEA nation for an average of 10,000 people. The total populations were taken from the World Bank website. Liechtenstein was removed from the rankings due to the countries exclusion from the World Bank 2012 study, possibly due to the low level of inhabitants (less than 45,000) and the negligible CO2 contribution. Links to the sources will follow the tables below.
|Country||Total Population (2012) to nearest 10,000||Total greenhouse gas emissions (kt of CO2 equivalent)2012 World Bank data||Greenhouse gas emissions per 10,000 people (kt of CO2 equivalent) approx|
|Country||Total Population (2013) to nearest 10,000||total CO2 emissions from fossil fuel burning, cement production and gas flaring expressed in thousand metric tons of carbon(2013)||total CO2 emissions from fossil fuel burning, cement production and gas flaring expressed in thousand metric tons of carbon(2013) per 10,000 persons approx|
Table 1:Greenhouse Gas Emissions Data-
Table 2: Carbon from fossil fuel burning etc Data-
Table 1 & 2: Population Data-