Ugur Dikbas Module 5 Assignment- Submit Quantitative Methods

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Dec 6, 2023

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1 Quantitative Analysis of the Impact of Airplane Emissions on Climate Change Ugur Dikbas Embry-Riddle Aeronautical University RSCH 202 - Intro to Research Methods Dr. Ardain Isma May 18, 2023

2 Quantitative Analysis of the Impact of Airplane Emissions on Climate Change General Topic of Interest: The impact of airplane emissions on the environment Research Objective/Purpose: The purpose of this study is to investigate the impact of airplane emissions on the environment and to identify possible solutions to mitigate their effects. Research Question(s): How do airplane emissions contribute to climate change, and what is the magnitude of this contribution? Variables Dependent Variable: Climate change Independent Variable: Airplane emissions Hypotheses Null Hypothesis (H0): There is no significant relationship between airplane emissions and climate change. Alternate Hypothesis (HA): There is a significant relationship between airplane emissions and climate change. Quantitative Methods a) Correlation Analysis: Utilizing correlation analysis, such as Pearson's correlation coefficient (Sedgwick, 2012), will enable the examination of the strength and direction of the relationship between airplane emissions and climate change. This method will provide insight into the degree of association between the variables.

3 b) Regression Analysis: Conducting regression analysis will help estimate the magnitude of the contribution of airplane emissions to climate change. By identifying significant predictors or factors, this method can shed light on the extent to which airplane emissions influence climate change. c) Time-Series Analysis: Employing time-series analysis techniques can be valuable if historical data on airplane emissions and climate change over time are available. This method will allow the identification of trends, patterns, and potential causal relationships between the variables. d) Experimental Design: In certain cases, experimental design can be utilized to investigate the impact of airplane emissions on the environment. By exposing controlled environments to varying levels of emissions, this method can measure the resulting effects on climate change indicators. e) Statistical Modeling: The utilization of statistical models, such as mathematical simulations or complex models like general circulation models (GCMs), can provide a comprehensive understanding of the mechanisms through which airplane emissions affect climate change. These models can quantify the magnitude of the contribution and simulate different scenarios to evaluate potential solutions. The Most Appropriate Quantitative Method After careful consideration, the most suitable quantitative method to address my research question would be statistical modeling, specifically utilizing general circulation models (GCMs) or mathematical simulations. These models are specifically designed to simulate the complex interactions within the Earth's climate system. By inputting data on airplane emissions into these models, I can obtain a comprehensive understanding of how airplane emissions contribute to

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4 climate change and quantify the magnitude of their impact. Additionally, these models allow me to simulate various scenarios and evaluate potential solutions to mitigate the effects of airplane emissions on climate change. This method provides a detailed analysis of the complex relationships involved and considers multiple variables and their interactions. Advantages and Disadvantages of Statistical Modeling: Using statistical modeling in my research offers several advantages. Firstly, it provides a holistic understanding of the relationship between airplane emissions and climate change by considering various factors and their interactions. Secondly, these models allow me to quantify the magnitude of the contribution of airplane emissions to climate change, providing numerical estimates that can support policy decisions and mitigation efforts. Thirdly, I can simulate different scenarios using the models, enabling me to evaluate the effectiveness of potential solutions in mitigating the climate change impacts caused by airplane emissions. Lastly, statistical models can project future climate change based on different emission scenarios, assisting in long-term planning and decision-making. However, there are also some disadvantages associated with statistical modeling. Firstly, these models are complex and require substantial computational resources, specialized software, and expertise to operate effectively. Secondly, uncertainties are inherent in the models as they are simplifications of the real-world climate system. The accuracy of their projections depends on the quality of input data, assumptions made, and the limitations of the models themselves. Additionally, statistical models heavily rely on the availability and quality of data, and any gaps or inconsistencies in the data can impact the accuracy and reliability of the results.

5 References: Sedgwick, P. (2012). Pearson’s correlation coefficient. Bmj, 345. https://doi.org/10.1136/bmj.e4483 Grotch, S. L., & MacCracken, M. C. (1991). The use of general circulation models to predict regional climatic change. Journal of climate, 4(3), 286-303. Lee, D. S., Fahey, D. W., Forster, P. M., Newton, P. J., Wit, R. C. N., Lim, L. L., Owen, B., & Sausen, R. (2009). Aviation and global climate change in the 21st century. Atmospheric Environment, 43(22-23), 3520-3537. https://doi.org/10.1016/j.atmosenv.2009.04.024 Filippone, A., & Parkes, B. (2021). Evaluation of commuter airplane emissions: A European case study. Transportation Research Part D: Transport and Environment, 98, 102979. ISSN 1361-9209. https://doi.org/10.1016/j.trd.2021.102979 European Commission. (2019). Aviation and climate change . Retrieved from https://ec.europa.eu/clima/policies/transport/aviation_en Brannen, J. (2017). Combining qualitative and quantitative approaches: an overview. Mixing methods: Qualitative and quantitative research, 3-37.