Statistical analysis of global environmental impact patterns using a world multi-regional input–output database

Understanding how anthropogenic impacts are generated at a global scale is a major challenge to face. This work studies the environmental impact patterns of the wealthiest nations using environmentally extended multi-regional input–output tables. A multivariate statistical analysis is performed on data covering 69 environmental indicators (classified into 5 main categories: energy, emissions, material, water and land) and 41 countries. This analysis shows that damages in different categories (and also within the same one) are highly correlated and that the wealthiest countries display very similar environmental impact patterns. These findings might help to develop more effective environmental regulations that will focus on controlling a reduced number of key indicators. In addition, the analysis of pollution patterns at a global scale will help to establish unified environmental regulations in countries with similar patterns.