Statistical analysis
The Distributed Lag Linear and Non-Linear Model (DLNM) was used to view the direct and delayed effect of air pollution and environmental factors on CE. Considering the distribution of number of daily CE events, the Quasi-Poisson model is a more suitable model than the Poisson model. Quasi-Poisson is usually used when the variance is greater than the average, and this was the reason why we used this model. It was used in combination with a DLNM to investigate the lagged and non-linear effects. For all variables, the maximum lag day L was considered up to 10 days.
The multivariate DLNM model for the air pollutants is:
\begin{equation} \text{log\ E}\left(Y_{t}\right)=s\left({PM10}_{t};\eta_{\text{PM}10}\right)+s\left({NO2}_{t};\eta_{NO2}\right)+s\left({SO2}_{t};\eta_{SO2}\right)+s\left(\text{WS}_{t};\eta_{\text{WS}}\right)+s\left(\text{SS}_{t};\eta_{\text{SS}}\right)+ns\left(time,\left(4\times 6+4\right)\text{df}\right)+DOW+\sum_{k=1}^{6}{\gamma_{k}\mu_{\text{tk}}}\backslash n\nonumber \\ \end{equation}