Fear in a Handful of Dust: The Epidemiological, Environmental, and Economic Drivers of Death by PM2.5 Pollution

Abstract

This study evaluates numerous epidemiological, environmental, and economic factors affecting morbidity and mortality from PM2.5 exposure in the 27 member states of the European Union. This form of air pollution inflicts considerable social and economic damage in addition to loss of life and well-being. This study creates and deploys a comprehensive data pipeline. The first step consists of conventional linear models and supervised machine learning alternatives. Those regression methods do more than predict health outcomes in the EU-27 and relate those predictions to independent variables. Linear regression and its machine learning equivalents also inform unsupervised machine learning methods such as clustering and manifold learning. Lower-dimension manifolds of this dataset’s feature space reveal the relationship among EU-27 countries and their success (or failure) in managing PM2.5 morbidity and mortality. Principal component analysis informs further interpretation of variables along economic and health-based lines. A nonlinear environmental Kuznets curve may describe the fuller relationship between economic activity and premature death from PM2.5 exposure. The European Union should bridge the historical, cultural, and economic gaps that impair these countries’ collective response to PM2.5 pollution.

Editorial on S.I. “Advances in Measuring Health and Wellbeing” in the International Journal of Environmental Research and Public Health

“…This Special Issue contains 11 contributions from diverse research lines, representing different geographies, such as America, Asia or Europe. Some of them are related to elderly or disabled populations ( [1][2][3][4]), while others present new financial or actuarial proposals ( [5][6][7]) or focus on specific diseases, specific factors of mortality or on general wellbeing ( [8][9][10][11]). All of them apply state-of-the-art tools or develop new methods to visualize and analyse data coming from multiple sources to produce reliable measurements on peoples' health and wellbeing.…”

“…Finally, James Ming Chen, Mira Zovko, Nika Šimurina and Vatroslav Zovko [11] focus their study on the effects of PM2.5 pollution on the mortality of the population of 27 countries of the European Union. They assess the success (or failure) of PM2.5 pollution management through a collection of statistical techniques ranging from linear regression models to machine learning.…”