Air pollution is one of the most pressing environmental issues,and prolonged exposure to air pollution,which is linked to several chronic diseases,represents a notable risk factor for public health. Green infrastructure (GI),through its ecosystem service of reducing air pollution,plays a crucial role in addressing this challenge. As a vital public resource and an integral component of urban infrastructure,properly planned GI can optimize its service efficiency,enhance urban environmental quality,and improve residents' health and quality of life. We carried out a study on the GI supply-demand relationship in Tianjin,focused on air pollution exposure. Using the Land Use Regression (LUR) method,we analyzed the high-resolution spatial distribution of PM_2.5 from November 2020 to October 2021. The demand for GI stems from residents' need to mitigate the risks associated with prolonged exposure to air pollution. It also reflects their expectations for GI to reduce air pollution and enhance their health and well-being. Population exposure risk (PER) was quantified as the GI demand,using data on PM_2.5 distribution and population density. GI's capacity to clean the air was evaluated as the GI supply,using land cover and NDVI datasets to calculate the supply indicators. Subsequently,we proposed a classification method to determine the types of GI supply-demand relationships,representing the degree to which GI supply fits demand. Utilizing Fragstats and ArcGIS,we calculated these indicators and mapped the spatial and temporal distribution to highlight critical imbalances in the GI supply-demand relationship. The results showed the following conclusions. (1) The distribution of air pollutants exhibited temporal variations and urban-rural spatial differences,with human activities significantly contributing to PM_2.5 levels. (2) Air pollution exposure was closely associated with high-intensity urban development,as GI resources in those areas were inadequate to address the health demands caused by high exposure risks. (3) The vegetation in farmlands and salt fields was monoculture or insufficiently covered,and the landscape pattern was fragmented which reduced GI supply. (4) The increase in pollutant concentrations during the heating season and the loss of surface vegetation exacerbated the mismatch between GI supply and demand,manifesting in different supply-demand conflicts in high-density built-up areas and rural villages. We suggested tailored optimization strategies based on varying supply-demand correlations and types of surface vegetation. This study identified the issue of spatial imbalances in the GI supply-demand relationship from the perspective of air pollution exposure,aiming to provide theoretical and practical insights for optimizing the allocation of GI resources and for healthy city governance.