## 3 Empirical Data and Technical Parameters
### Health Benefits: BenMAP Parameter Data  
To estimate the health benefits of each air pollution control measure, the following data were included in the BenMAP database: population data, geographic layers, pollution monitoring data, and mortality rate from the National Health Insurance Research Database [38; 39; 40; 41; 42; 43; 44]. A meta-analysis was then performed to calculate the coefficient of estimation of the health impact function.  
The VSL is a fatal risk monetization metric that has been used extensively in health benefit assessment studies [45; 46]. The basic concept of VSL suggests that people have a willingness to pay (WTP) for the reduction of a certain percentage of fatal risk; VSL represents the summation of the WTPs in the unit of risk [47].  
The estimation of health benefits owing to improvements in air pollution was performed using the value transfer method (VTM) on the VSL derived by [PERSON] [47] for Taiwan in 2014. In the VTM, the value transfers were based on two aspects, the differences in income and consumer prices between the two years. The adjustments for differences in income were performed by substituting the salary income elasticity of the VSL estimated by [PERSON] [47] into Equation (5):  
\[VSL_{2019}=VSL_{2014}\times\left\{1+\frac{\left[\epsilon_{w}\times\left(\frac{ W_{2019}-W_{2014}}{W_{2014}}\right)\right]}{100}\right\} \tag{5}\]  
In Equation (5), \(VSL_{2019}\) is the nominal VSL value for 2019, \(\epsilon_{w}\) is the salary income elasticity of the VSL estimated by [PERSON] [47], and \(W_{2019}\) and \(W_{2014}\) are the average monthly salary incomes of Taiwanese workers in 2014 and 2019.  
The differences in consumer prices were adjusted using Equation (6):  
\[RVSL_{2019}=VSL_{2014}\times\left(CPI_{2014}/CPI_{2019}\right) \tag{6}\]  
In this equation, \(RSVL_{2019}\) is the VSL value after consumer price adjustments, while \(CPI_{2019}\) and \(CPI_{2014}\) are the 2019 and 2014 consumer price indices (CPIs), respectively.  
The empirical data used in this study and their descriptions are shown in Table 2.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Type of Database** & **Data Description** \\ (Base Year = 2013, Target Year = 2019) & **Data** \\ \hline
**Pollutant Monitoring Data** & PM\({}_{2.5}\) monitoring data across Taiwan in 2013: 24.1 ug/m\({}^{3}\) \\  & (seasonal average) 1 [FOOTNOTE:1]Footnote 1: Taiwan EPA monitoring Data \({}^{2}\) National Health Insurance Research Database in Taiwan, the grid size is 3 km \(\times\) 3 km. \({}^{3}\) Death rates of all cause = number of deaths in 2013/total population. \({}^{4}\) Death rate of cardiovascular disease = Number of death due to cardiovascular disease in 2013/total population. \({}^{5}\) Deaths rate of Respiratory diseases = Number of death due to Respiratory diseases in 2013/total population. \({}^{6}\) SEGIS (Socio-Economic Geographic Information System), Department of Statistics, Ministry of the Interior \({}^{7}\) The papers that were included in this meta-analysis are [39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57; 58; 59; 60; 61; 62; 63; 64; 65; 66; 67; 68; 69; 70; 71; 72; 73; 74; 75; 76; 77; 78; 79; 80; 81; 82; 83; 84; 85; 86; 87; 88; 89; 90; 91;