Capstone Project for Advanced DSBME
Emission of greenhouse gasses such as CO2 by human activities is one of the leading causes of global warming and climate change. Following the industrial revolution, combined land and ocean temperature increased at an average of 0.08°C per decade. Further, average temperature trends have more than doubled to 0.18°C per decade since 1981. These trends have corresponded to an overall 2°C increase in global temperature since the pre-industrial era.
The process of climate change has been proposed to cause such environmental phenomena as rising sea levels, ocean acidification, and extreme weather events. These phenomena are expected to degrade Earth’s biodiversity as regions become uninhabitable for both human and nonhuman life. Also, according to a publication on the Lancet, global warming by excessive CO2 emission is closely related to public health, especially to heat-related morbidity and mortality. As a result, it is necessary to understand the contributions of individual countries to global emissions in order to enact effective climate change policy.
In this project, our objective is to develop a global environmental tracker tool. Our shiny app consists of three parts. In part I, the app offers a colorful scatterplot for displaying the user-selected environmental metric across all the countries. This gives the user an overview of the environmental trend globally. In the following two parts, we analyze emissions data for an array of over 60 countries who are the world’s leading CO2 emitters and provide emissions predictions for a desired user-input year. This tracker tool allows the user to select their desired countries, CO2 emission metric, and projected year and displays a map and projection of emissions trends for the selected year and metric. Emissions have been reported to be growing exponentially in recent decades, so time series data were presented on a logrithmic scale and fitted to a linear model for projected emissions predictions. In part II and III, we delivered our analysis using different display forms respectively. In part II, the app provides an interactive global map, paired with user-selected environmental metric analysis and prediction of a specific country. In part III, which is CO2 emission specific, the app displays CO2 emission analysis and predictions of two user-selected countries simultaneously for making comparison.
Yingnan Zhang – Data preprocessing; feature selection; created page "Global environmental data distribution"; displayed time series and implemented exponential fit prediction; project description drafting.
Brice Graham Hendrickson - Shiny app UI design, created shiny app code skeleton; created panel for user inputs; displayed interactive global map; project description drafting.
Shardul Rakshit – Implemented linear regression algorithm; helped debugging, participated in UI design;