Abstract: <p>Climate change is a global challenge with profound environmental, health, andsocio-economic implications. Canada's diverse geography offers a unique lens to study
localized climate trends. This thesis models and clusters climate variables, focusing
on temperature trends, using Bayesian hierarchical models and clustering techniques
to uncover regional patterns and health impacts.… more
Abstract: <p>This thesis develops an Long Short-Term Memory (LSTM) neural network model to assess the relationship between ambient air pollutant exposure and public health risks, accommodating both linear and nonlinear associations with distributed lags.The research makes three key contributions. First, Maximal Information Coefficient (MIC) methods identify the most relevant air pollutants and their… more
