## 2 Research Methodology: ABaCAS-Taiwan  
To conduct the analysis and planning of air pollution control strategies from a monetary perspective, the U.S. EPA began to develop the environmental benefit mapping and analysis program (BenMAP) in 2003. The ABaCAS was subsequently created by improving and integrating several cost-benefit assessment models. This system is based on the \"Impact Path Approach\" (IPA) [19; 20] which is a multidisciplinary assessment framework that links the outcomes of three stage-wise simulations and assessments. The three stages conducted when using the IPA framework to perform a monetized assessment of the effects of air pollutant emissions on human health are: (1) simulating the effects of air pollutant emissions on air pollution concentrations, (2) estimating the health impacts caused by changes in pollution concentration, and (3) monetizing these health impacts. One of the strengths of the IPA framework is its ability to clearly describe impact pathways through which air pollutants are emitted and eventually transferred to affected subjects. In addition, it enables quantitative modeling of the effects of pollutants at each key stage of an impact pathway. The IPA framework is, at present, the most commonly used assessment framework for the analysis of air quality policies. The ABaCAS-Taiwan was jointly developed by the Taiwan EPA, U.S. EPA, and the University of Tennessee. In addition to the intrinsic strengths of the ABaCAS system, the ABaCAS-Taiwan system also includes several technical parameters that have been adapted for local application in Taiwan. Therefore, this system is well-suited for air quality analyses in the Taiwanese context, but can also be adapted for use in other countries. For example, [PERSON] et al. [3] used Software for Model Attainment Test-Community Edition (SMAT-CE) to identify the pollutant concentrations that must be reduced to achieve the 2020 O\({}_{3}\) and PM\({}_{2.5}\) targets (75 ppb and 12 \(\mu\)g/m\({}^{3}\), respectively) of the U.S. They revealed that anthropogenic NO\({}_{\times}\) anthropogenic SO\({}_{\times}\) emissions, residential wood combustion PM\({}_{2.5}\), and direct PM\({}_{2.5}\) emissions from non-electric generating units must be reduced by 25%, 25%, 100%, and 50% over their corresponding 2007 levels, respectively, to meet the 2020 PM\({}_{2.5}\) target. [PERSON] et al. [4] combined the response surface model (RSM)-linear coupled fitting with SMAT-CE to reduce the dimensions required to establish air quality modeling, and used this approach to investigate the contributions of primary emissions to ambient PM\({}_{2.5}\) levels in the Yangtze River Delta in January and August 2010. In a study on power plants in the Yangtze River Delta, [PERSON] et al. [5] used a multi-pollutant control cost model to identify viable pollution control measures to achieve China's air quality targets, as well as their corresponding emission control costs. The ABaCAS-Taiwan assessment system is based on the standard ABaCAS framework, and it was created by incorporating Taiwanese data to localize the system. The database includes air quality monitoring data, Taiwan emission data, population, inflation data, incidence rates, prevalence rates, and mortality rates. ABaCAS-Taiwan consists of four modules: Taiwan emission control analysis system (TECAS), advance response surface model (RSM), software for model attainment test (SMAT), and environmental benefits mapping and analysis program-community edition (BenMAP-CE). The TECAS module can be used to estimate the technical cost of a pollution control strategy, while RSM can be used to quickly estimate both O\({}_{3}\) and PM\({}_{2.5}\) levels. Furthermore, RSM can be employed for the rapid calculation of precursor emissions with a minimum number of simulations [6; 7; 21]. SMAT is used to correct for errors between observed and simulated values, to ensure that the simulated values can be a better fit for the observed values.