Abstract
INTRODUCTION: PM(2.5) and climate change are two major public health concerns, with majority of the research on their interaction focused on the synergistic effect, particularly for extreme events such as hot or cold temperatures. The climate sustainability index (CLS) was introduced to comprehensively explore the impact of climate change and the interactive effect on human health with air pollution. METHODS: In this study, a county-level panel data in China was collected and used. The generalized additive model (GAM) and geographically and temporally weighted regression (GTWR) was used to explore the interactive and spatial effect on mortality between CLS and PM(2.5). RESULTS AND DISCUSSIONS: Individually, when CLS is higher than 150 or lower than 50, the mortality is higher. Moreover, when PM(2.5) is more than 35 μg/m(3), the influence on mortality is significantly increased as PM(2.5) concentration rises; when PM(2.5) is above 70 μg/m(3), the trend is sharp. A nonlinear antagonistic effect between CLS and PM(2.5) was found in this study, proving that the combined adverse health effects of climate change and air pollution, especially when CLS was lower (below 100) and PM(2.5) was higher (above 35 μg/m(3)), the antagonistic effect was much stronger. From a spatial perspective, the impact of CLS and PM(2.5) on mortality varies in different geographical regions. A negative and positive influence of CLS and PM(2.5) was found in east China, especially in the northeastern and northern regions, -which were heavily polluted. This study illustrated that climate sustainability, at certain level, could mitigate the adverse health influence of air pollution, and provided a new perspective on health risk mitigation from pollution reduction and climate adaptation.