Click the Original, Code and Reconstruction tabs to read about the issues and how they were fixed.

Original


Source: AR4 Climate Change 2007: Mitigation of Climate Change — IPCC.


Objective

The target audience for this report were environmental scientists and journalists. The graph was to be used by Journalists to inform and motivate the general public as to sectors requiring attention to prevent environmental degradation.

The visualisation chosen had the following three main issues:

  • The pie chart data presentation requires consideration of too many factors driving CO2 emissions to be interpreted clearly in a pie chart as this made the chart too busy and the use of percentages reduces the impact of the size of the problem in this instance (10% of what?)
  • Three of the sectors were similar in size so interpreting the relative importance was difficult and the color scheme did not gain your attention
  • Red and green were placed side by side making it difficult for colour blind individuals to interpret

Reference

  • United Nations Intergovernmental Panel on Climate Change (IPCC) “Technical Report”. (2007). Retrieved 1/8/2021, 10.00 am from IPCC website: https://www.ipcc.ch/report/ar4/wg3

Code

The following code was used to fix the issues identified in the original-Reconstruction.

library(ggplot2)

Carbon<-data.frame(Sector=c("Energy Supply", "Transport", "Building (Res & Commcl)", "Agriculture", "Forestry", "Industry (Man)", "Waste & Sewage"), Gtused=c(12.95, 6.55, 3.95, 6.75, 8.7, 9.7, 1.4)) 
  
myplot<-ggplot(data=Carbon, aes(x = reorder(Sector, Gtused), y = Gtused, fill = Sector)) + geom_col(width=0.5) + labs(title = "Non Deforestation drivers of CO2  emmissions-2004", x= "Sector", y = "Generation in Gigatonnes")
 myplot<-myplot + geom_text(aes(label=Gtused),vjust=-0.5)
 myplot<-myplot + scale_fill_manual(values = c("Waste & Sewage" = "green",  "Building (Res & Commcl)" =  "green", "Transport"   =  "orange",  "Agriculture" = "orange", "Forestry" = "orange", "Industry (Man)" = "red",  "Energy Supply" = "red") )
 myplot<-myplot + scale_x_discrete(guide = guide_axis(n.dodge=2))

Data Reference

  • United Nations Intergovernmental Panel on Climate Change (IPCC) “Technical Report”. (2007). Retrieved 1/8/2021, 10.00 am from IPCC website: https://www.ipcc.ch/report/ar4/wg3

Reconstruction

The following plot fixes the main issues in the original.