Iceland’s CO2 and CH4 Emissions Created Through Economy

I have decided to analyze the data on Iceland’s Economy and how it affects their environement through greenhouse gas emissions: Carbon Dioxide(CO2) and Methane(CH4).The values from environmental accounting for greenhouse gas (GHG) are according to the standards of the United Nations (UN) and are published in the National Inventory Report by The Environmental Agency of Iceland. This website was provided by professor Bharat Bhushan Verma as an example of Open Data. Their statistic data is offered open to the public as I was able to download the segment I wanted. Here is the link to Iceland’s Statistal Database Link

Anyone can choose between five data base sectors; Business Sectors, Economy, Population and Elections, Society, and Environment. I chose to do Environment, viewing two of the top greenhouse gas emissions responsible for air pollution, Carbon Dioxide and Methane. Based on ten economic sectors: Air Transport, Metal Production, Agriculture and Food Production, Households, Water Transport, Fishing and Aquaculture, Power, Water and Remediation services, Construction and Mining, Tourism Operations, Land Transport and Storage, and Commerce & Services.I chose to reserach the 15 year time period from 2002-2017. Below you can see a table showcasing example of some of the sectors Carbon Dioxide levels for years 2002-2012.

library(ggplot2)
## Warning: package 'ggplot2' was built under R version 3.6.3
library(tidyr)
library(dbplyr)
library(knitr)
## Warning: package 'knitr' was built under R version 3.6.3
library(gapminder)
## Warning: package 'gapminder' was built under R version 3.6.3
library(viridisLite)
library(RColorBrewer)
library(paletteer)
## Warning: package 'paletteer' was built under R version 3.6.3
library(ggthemes)

Ice <-read.csv("C:/Users/khend/Documents/R/Iceland(1).csv")
Ice_table <- knitr::kable(Ice[1:11,1:5])
Ice_table
Year Air.Transport..H51. Metal.Production Agriculture.and.food.production Water.Transport..H50.
2002 566.91 804.08 218.46 154.02
2003 811.17 823.06 104.60 202.28
2004 842.20 828.01 23.67 224.73
2005 908.88 807.50 26.07 103.23
2005 547.85 909.16 51.37 174.85
2007 799.59 1094.80 78.57 232.04
2008 788.55 1541.12 90.72 218.16
2009 586.05 1594.57 87.88 265.20
2010 763.96 1612.50 80.30 259.38
2011 729.45 1595.84 75.59 268.07
2012 854.14 1663.90 84.44 217.29

Co2 Comparison:

Throuhgout my research of the Iceland Greenhouse Gas Emissions from 2002-2017 I decided to compare the trends of several economic sectors and the amount of CO2 they are emitting each year. Below is the first comparison of the three industries that contribute the highest amounts of CO2 in Iceland; Air Transportation, Metal Production, and Fishing/Aquaculture. From 2002-2017 Air Transporation emitted an average of 1022 Tonnes of CO2, Metal Production with 1361 Tonnes of CO2, and Fishing/Aquaculture with 450 Tonnes of CO2 per year. As you can see below maintained an emission level well below 1000 Tonnes until 2013 when it began to skyrocket. Metal Production has shown a steady growth in CO2 emission since 2002, not realy showing any sign of declining but maybe a plateau is soon to come. On the other hand, during the 15 year time span the Fishing industry seemed to of reached it’s peak of CO2 emission level in 2009 but from there on has declined.

ggplot(Ice, aes(Year)) + geom_line(aes(y=Air.Transport..H51., colour="Air.Transport"),size=1)+
  geom_line(aes(y=Metal.Production, colour="Metal Production"))+
  geom_line(aes(y=Fishing.and.aquaculture..AO3.,colour="Fishing/Aquaculture"))+
  theme(axis.text=element_text(colour="red")) +
  labs(x="Year", y="CO2(Tonnes)", title="Comparison of Carbon Dioxide Emissions")+expand_limits(y=0)+ coord_cartesian(xlim= c(2002,2017), ylim= c(300,2000))+theme(axis.line=element_line(colour="black",size=1, linetype="solid"))

Methane and CO2 Comparison.

The final comparisons I have created are between; The CO2 growth of the Tourism industry to the CO2 decline of Agriculture, and the comparison of the growth of CH4(Methane) in the Agricultural industry to the decline of CH4 in the Power and Water industry. As visualized below, the practices of Agriculture changed immensley from 2002-2017, showcasing a major drop-off in CO2 emissions but a steady growth in Methane emissions. It also can be concluded that the Tourism Industry in Iceland had been expanding each year, hense the increase of CO2 levels, which may be great for the economy but not so much for the environment. Whatever Iceland environmental practices were in place in 2005 for the Power and Water Services sector that made the Methane level jump through the roof, were immediately altered the year after and it seemed stayed that way for the next eleven years.

ggplot(Ice, aes(Year))+
  geom_line(aes(y=Tourism.operators.and.road.transport.of.foreign.nationals, colour="Tourism"))+ geom_line(aes(y=Agriculture.and.food.production, colour="Agriculture"))+ggtitle("Comparison of Carbon Dioxide Emissions") + ylab("CO2(Tonnes)")+theme(axis.line=element_line(colour="black",size=1,linetype="solid"))+
  theme(axis.text=element_text(colour="red"))

ggplot(Ice, aes(Year))+
  geom_line(aes(y=Agriculture.Methane., group=1, colour="Agriculture"))+ geom_line(aes(y=Power.and.Water.Services.Methane.,group=1, colour="Power and Water"))+ggtitle("Comparison of Methane Emissions") + ylab("CH4(Tonnes)")+theme(axis.line=element_line(colour="black",size=1,linetype="solid"))+
  theme(axis.text=element_text(colour="red"))

Final Remark

Throughout my research of Iceland’s Economic Environmental practices I found the release of emission levels vital to understand, as the numbers do not lie. I find it fascinating that Iceland is well organized with their annual measurements. It was interesting to compare the growth and decline within various economic sectors, especially the fact that it seems many sectors focus on the delcine of one of the two Greenhouse gas emission, either CO2 or CH4, but both as I saw with Agricultural practices. I could really get behind the research of environmental measurements that are created through the economy, I was glad we were able to choose our own data set, made it much more interesting. I did however come into complications with the organization of my data, which made it difficult to create multiple ggplots. I had to play a lot with the tidying of the data before it finally made sense.