Optimal evaluation of expansion alternatives for existing air quality monitoring network by grey compromise programming

This paper presents a new approach – grey compromise programming – for siting new air quality monitoring stations in a metropolitan region. In particular, cost, effectiveness and efficiency characteristics for expanding the existing air quality monitoring network are postulated in the multi-criteria decision-making process. In order to test the impacts of the growth of population and emission sources, a series of technical settings in the grey compromise programming model were examined and the uncertainties possibly embedded in the planning procedure were recognized for assessing the optimal expansion alternatives in the air quality monitoring network. The practical implementation was established by a case study for the city of Kaohsiung in Taiwan. It appears that such an approach is useful for screening the expansion alternatives in the air quality monitoring network under uncertain environments, that may further help planners and decision makers find more flexible solutions based on those multiobjective design principles.