Global CO2 Emissions

Author

Holly Monger

Begin Instructions:

The text below has all the promots for the exam with a link to the raw data itself. For each component, there is a point value indicated that I will use as a rubric. In addition to those points, this will also be evaluated on the following:

End Instructions

Question 1. { A single paragraph here about why CO2 emissions are of interest to us. [5 pts]}

Carbon dioxide (CO2) emissions represent a paramount area of interest for scholars, policymakers, and the global community at large due to their pivotal role in climate change dynamics. As a greenhouse gas, CO2 contributes significantly to the enhancement of Earth’s natural greenhouse effect, trapping heat and leading to a rise in global temperatures. This phenomenon, commonly referred to as anthropogenic global warming, is principally driven by human activities such as the combustion of fossil fuels, deforestation, and industrial processes. The consequences of heightened CO2 concentrations are multifaceted, encompassing rising sea levels, more frequent and severe weather events, disruptions in ecosystems, and threats to human health and socio-economic stability. Consequently, understanding, monitoring, and mitigating CO2 emissions have become imperative endeavors to address the complexities of climate change and to formulate effective strategies for sustainable environmental management and global resilience.

The Data

Question 2. { A narrative (e.g., not just a list of figures or R output) about the data, where it comes from, and what it contains. This is a complete paragraph just like you find in a normal research paper [5 pts].

The data under examination originates from the Global, Regional, and National Fossil-Fuel CO2 Emissions dataset compiled by Boden, Marland, and Andres in 2013 (Boden, Marland, & Andres, 2013). Accessible in the form of a ZIP archive named CSV-FILES, this dataset serves as a valuable resource for understanding carbon dioxide (CO2) emissions worldwide. The dataset encompasses a wide range of information spanning multiple years and is instrumental in analyzing emissions from various countries. The sources of emissions are categorized into solid fuels, liquid fuels, gas fuels, cement production, gas flaring, bunker fuels, while also providing data on per capita CO2 emissions and total CO2 emissions for 259 nations. This comprehensive compilation allows for a nuanced examination of global and regional trends in CO2 emissions, facilitating a detailed exploration of the contributing factors to climate change. The dataset, being rich in detail and scope, provides researchers and policymakers with a robust foundation for formulating strategies to address the complexities of carbon emissions on a global scale.

Question 3. As part of this description, make a table describing the \(CO_2\) data including columns for the minimum, mean, and maximum value for each of the emission variables. [10 pts]}

Emission Variables Minimum Mean Maximum
Total CO2 (thousand metric tons) Total CO2 (thousand metric tons) -1473.00 22687.119661 2806634.00
Solid Fuel Consumption Solid Fuel Consumption -103.00 11202.723867 2045156.00
Liquid Fuel Consumption Liquid Fuel Consumption -4663.00 7680.005109 680284.00
Gas Fuel Consumption Gas Fuel Consumption -40.00 3227.981971 390719.00
Cement Production Cement Production 0.00 638.453865 338912.00
Gas Flaring Gas Flaring 0.00 276.163457 20520.00
Per Capita CO2 (metric tons) Per Capita CO2 (metric tons) -0.68 1.268883 45.96
Bunker Fuels Bunker Fuels 0.00 560.330606 45630.00

Components of Emissions

Question 4. { The total emissions is composed of several types of data. For the data from the year 2010, analyze and present to the reader the relative contributions of CO2 by source for each of the G7 Countries. [5 pts]}

# A tibble: 6 × 3
  Country Source            Percentage
  <chr>   <chr>                  <dbl>
1 Canada  Gas Fuels             33.7  
2 Canada  Liquid Fuels          47.8  
3 Canada  Solid Fuels           16.8  
4 Canada  Gas Flaring            0.551
5 Canada  Cement Production      1.16 
6 Canada  Bunker Fuels           1.04

Question 5. { Divide the data into the G7 (e.g., Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) and non-G7 countries. Compare emission output amongst all G7 countries to those from the rest of the world combined. All plots must be labelled properly and have an appropriate caption.[10 pts] }

The graph shows that G7 countries are the primary emitters of fossil fuels globally. Possible interpretations could be that G7 countries are more developed and have higher energy demands, or that G7 countries have played a larger role in the development of industries that rely heavily on fossil fuels, such as transportation and manufacturing compared to Non-G7 countries. These may be the primary reasons for the higher fossil fuel emissions from G7 countries. This highlights the importance of G7 countries taking action to reduce their emissions and help to mitigate climate change.

The dots above Non-G7 in the graph are outliers. These are data points that are significantly different from the rest of the data set. In this case, the outliers are countries with non-G7 emissions that are much higher than the average for non-G7 countries.

There are a few possible explanations for the outliers:

The outliers may be countries that are rapidly industrializing and have a high demand for energy, or countries that have a large amount of natural resources, such as coal or oil, and produce these resources for export. They could also be countries that have not implemented policies to reduce their emissions. The outliers here are still part of the non-G7 group of countries which means that the overall trend for non-G7 countries is still lower emissions than for G7 countries. However, the outliers show that there is a great deal of variation within the non-G7 group of countries.

Question 6. { Perform a statistical analysis of G7 vs. non-G7 countries output by source. Provide textual description of your analyses and present output as tables or in-text. [10 pts] }

                            Source      p.value adjusted_p.value
1         Emissions.from.Gas.Fuels 1.752126e-14     1.051276e-13
2      Emissions.from.Liquid.Fuels 3.493838e-02     2.096303e-01
3       Emissions.from.Solid.Fuels 1.144837e-01     6.869025e-01
4       Emissions.from.Gas.Flaring 7.323487e-01     1.000000e+00
5 Emissions.from.Cement.Production 4.477030e-01     1.000000e+00
6      Emissions.from.Bunker.Fuels 5.535988e-02     3.321593e-01

Emissions from Gas Fuels: p-value: 1.75e-14 Adjusted p-value: 1.05e-13 Interpretation: The p-value is extremely low, indicating a significant difference in emissions from Gas Fuels between G7 and non-G7 countries. The adjusted p-value remains significant after correction. This means that, even after adjusting for multiple comparisons (using methods like Bonferroni correction, Holm’s method, or others), the result is still considered statistically significant. This suggests that the observed difference in emissions from Gas Fuels between G7 and non-G7 countries is unlikely to be due to random chance.

Emissions from Liquid Fuels: p-value: 0.035 Adjusted p-value: 0.21 Interpretation: The p-value is below the conventional threshold of 0.05, suggesting a significant difference. However, after adjusting for multiple comparisons, the result is no longer significant. This suggests that any observed differences in emissions from sources like Liquid Fuels between G7 and non-G7 countries could be due to random variability.

Emissions from Solid Fuels: p-value: 0.114 Adjusted p-value: 0.687 Interpretation: The p-value is not below 0.05, indicating no significant difference in emissions from Solid Fuels between the two groups. This result holds after adjusting for multiple comparisons. The differences observed in emissions from sources like Gas Fuels, Liquid Fuels, or others between G7 and non-G7 countries are unlikely to be due to random chance alone.

Emissions from Gas Flaring: p-value: 0.732 Adjusted p-value: 1.0 Interpretation: The p-value is high, suggesting no significant difference in emissions from Gas Flaring. This result holds even after adjustment.

Emissions from Cement Production: p-value: 0.448 Adjusted p-value: 1.0 Interpretation: The p-value is not below 0.05, indicating no significant difference in emissions from Cement Production between G7 and non-G7 countries. This result holds after adjusting for multiple comparisons.

Emissions from Bunker Fuels: p-value: 0.055 Adjusted p-value: 0.332 Interpretation: The p-value is slightly above 0.05, indicating a marginally significant difference. However, after adjusting for multiple comparisons, the result is no longer significant. This suggests that any observed differences in emissions from sources like Bunker Fuels between G7 and non-G7 countries could be due to random variability.

Reference

Boden, T.A., G. Marland, and R.J. Andres. 2013. Global, Regional, and National Fossil-Fuel CO2 Emissions. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A. doi.