Using a set of strategic indicator systems as a decision-making support implement for establishing a...

BACKGROUND, SCOPE AND AIMS: To realize the vision of sustainable development (SD) originating from the 'only one earth' philosophy, and to integrate the conceptions of ecology and sustainability into the planning and decision-making criteria of urban growth management, the establishment of a recycling-oriented society (ROS) is essential. However, before the above intention can be achieved, it is indispensable to develop a system of strategic indicators for supporting a radical reformation of the urban development plan. Therefore, this study, based on the conception of the new urban development pattern ROS, attempted to carefully choose a sample city in Taiwan for launching a preliminary case study, and furthermore designed and proposed a concise and strategy-oriented assessment indicator system termed ROSAIS. ROSAIS, on the one hand, can act as a compass for understanding resource using efficiency and recycling status during city development and, on the other hand, can serve as an implement supporting decision-making for ROS construction.

According to the definition and spirit of ROS, the structure of ROSAIS should clearly represent the relationship between resources and environment in human activities. The eco-efficiency indicator system (EEIS) and environmental symbiosis indicator system (ESIS) can be considered two key subindicator systems, and are the necessary components of ROSAIS. EEIS chooses the dominant production sectors in urban economic activities to calculate their eco-efficiency (EE). Separately, for obtaining a consensus regarding the framework of ESIS, the questionnaire approaches and expert consultation, together with the research experience and foundation of current relevant studies and indicator systems, are applied when crucial resource and environmental issues and respective indicators are selected.

The calculation results of EEIS in this case study indicated that among the three dominant production activities (agricultural, fishery, and animal husbandry sector) the fishery sector has the highest EE, which indicates that the fishery activities and resources significantly influence the sustainability of the economic-environmental system of the sample city. Furthermore, according to a consensus achieved in ESIS, local green spaces, resource recovery, energy consumption pattern change, freshwater conservation and greenhouse effect abatement were considered as the five crucial issues influencing how the case study city can develop into an ES-city. The rate of local green spaces, resource recycling, freshwater conservation and the rate of reduction of nonrenewable energy use as well as carbon dioxide (CO2) emissions were used to evaluate the above five issues.

This case study is unparalleled in Taiwan. Even in Japan, where ROS legislation has been implemented, this kind of study remains in the preliminary stages. Furthermore, when communicating the indicator results, it is essential to provide the context and countermeasures of the crucial issues that are faced. The two sub-indicator systems proposed in this case study could comply completely with the above-mentioned requirements. For example, the EEIS provides information for achieving a balance between environmental burden and economic benefits among dominant production sectors; the ESIS provides information for setting strategies for overcoming the crucial issues faced.

This study recommends that urban planers should consider the construction of the corresponding strategic indicator system to be indispensable, and makes further use of the indicator results related to the environmental education of residents for identifying and promoting participation with ROS, and turning them into implements for supporting urban SD decision-making. Furthermore, a successful indicator system depends on data availability and quality. This study recommends that urban planers should pay considerable attention to constructing relevant data collection channels, databases and the data quality.