Impact of Emission on Climate Change and Global Life Expectancy

Abstract

This research article explores the critical intersection of data science, global climate and public health, specifically investigating how escalating  emissions accelerate climate change and subsequently influence global life expectancy. Utilizing longitudinal data from the World Bank Open Data repository (spanning 1990 to the present), the study employs a combination of Data Mining as data Wrangling, Exploratory Data Analysis (EDA) and machine learning techniques, to identify patterns between environmental degradation and human health outcomes.

The analysis reveals a dual-threat mechanism: first, the direct impact of air pollution on respiratory and cardiovascular health; and second, the indirect consequences of climate instability—such as extreme weather events, food insecurity, and the spread of vector-borne diseases—which disproportionately lower life expectancy in developing regions. A significant portion of this study is dedicated to a comparative analysis of South Asia, evaluating how its unique industrial trajectory and population density make it more vulnerable to these shifts compared to global averages.

Preliminary findings indicate a strong negative correlation between high per-capita carbon output and the rate of longevity improvement in emerging economies. The project concludes with data-driven policy recommendations aimed at South Asian governance, emphasizing the need for decoupled economic growth from carbon intensity to safeguard future public health.