Speaker
Description
Background
Amidst intensifying climate change, urban regions around the globe are experiencing more frequent and severe extreme weather events. In particular, the frequency and intensity of heatwaves have risen substantially, with the urban heat island effect further exacerbating extreme heat conditions. This escalation contributes to increasing mortality and morbidity, creating a major public health challenge worldwide. Furthermore, growing evidence indicates a strong correlation between heatwaves and elevated levels of air pollutants, notably particulate matter (PM2.5 and PM10) and surface ozone. These dual environmental pressures, extreme heat and air pollution, pose heightened health threats. Additionally, the global onset of population ageing is expected to intensify the susceptibility of individuals to environmental exposure risks, therefore increasing the overall disease burden. Although many studies have separately investigated the health consequences of extreme heat or air pollution, comparatively fewer have focused on their combined effects, especially in terms of spatial precision for assessing compound health risks.
Purpose
This study aims to clarify the synergistic health impacts of extreme heat and air pollution within a high-density urban environment under intensifying climate change. By integrating multi-source remote sensing and health outcome data at a 1 km² spatial resolution, we aim to pinpoint critical health threshold phenomena for both temperature and pollutant concentrations and discern the socio-spatial environmental health risk disparities that emerge. Through this citywide analysis in Shanghai, we endeavor to highlight key hotspots and at-risk groups, thereby informing evidence-based, region-specific public health strategies and environmental interventions for policy makers and urban planners.
Methods
Focusing on Shanghai—a prototypical high-density urban environment—we integrated a spatial resolution of 1 km×1 km multi-source remote sensing data with health outcome datasets. We then developed an interpretable spatial machine learning model to quantify the synergistic effects of extreme temperatures and air pollution on health. Additionally, by leveraging the IPCC’s Hazard-Exposure-Vulnerability assessment framework, we performed a citywide, grid-level (1 km²) health risk analysis covering multiple environmental stressors. Specifically, satellite-derived land surface temperature measurements and ground-based air quality monitoring provided spatially and temporally resolved exposure indices, while hospitalization and mortality records enabled detailed evaluations of adverse health events. This model architecture balanced predictive accuracy with interpretability, allowing us to probe complex nonlinear interactions between heat stress and pollution levels and to achieve a spatially refined health risk assessment.
Results
Our findings reveal significant nonlinear associations and threshold effects among environmental exposures and health outcomes, suggesting that the combined influence of extreme heat and air pollution cannot be seen as merely additive. Certain temperature thresholds and pollutant concentration levels were linked to disproportionately steep rises in cardiovascular and respiratory admissions, suggesting that both the intensity and duration of exposure are critical factors driving negative health outcomes. The spatially explicit risk assessment of the dual environmental exposures revealed substantial heterogeneity in exposure to both extreme temperatures and air pollution, pinpointing several high-risk zones that exhibit pronounced vulnerabilities due to demographic and socioeconomic profiles. Specifically, areas with higher concentrations of elderly populations in urban centers, as well as those adjacent to industrial sites, experienced notably elevated risk levels. These findings underscore the importance of adopting region-specific strategies and targeted interventions, particularly for populations most susceptible to environmental stressors.
Conclusion
Our research addresses a critical gap in understanding the synergistic health risks posed by extreme heat and air pollution in the context of climate change, offering a pioneering city-scale spatial precision assessment of these compound impacts. The findings accentuate the urgency of targeted urban planning and policy measures to mitigate such risks, enhance sustainability, and promote socio-spatial justice in rapidly evolving urban environments.
References
Arunab, K.S. and Mathew, A., 2024. Quantifying urban heat island and pollutant nexus: A novel geospatial approach. Sustainable Cities and Society, 101, p.105117.
O'Lenick, C.R., Wilhelmi, O.V., Michael, R., Hayden, M.H., Baniassadi, A., Wiedinmyer, C., Monaghan, A.J., Crank, P.J. and Sailor, D.J., 2019. Urban heat and air pollution: A framework for integrating population vulnerability and indoor exposure in health risk analyses. Science of the total environment, 660, pp.715-723.
Silva, R.A., West, J.J., Lamarque, J.F., Shindell, D.T., Collins, W.J., Faluvegi, G., Folberth, G.A., Horowitz, L.W., Nagashima, T., Naik, V. and Rumbold, S.T., 2017. Future global mortality from changes in air pollution attributable to climate change. Nature climate change, 7(9), pp.647-651.
Yang, J., Zhou, M., Ren, Z., Li, M., Wang, B., Liu, D.L., Ou, C.Q., Yin, P., Sun, J., Tong, S. and Wang, H., 2021. Projecting heat-related excess mortality under climate change scenarios in China. Nature communications, 12(1), p.1039.
He, Z., Wu, Z., Herzog, O., Hei, J., Li, L. and Li, X., 2024. Compound Health Effects and Risk Assessment of Extreme heat and Ozone Air Pollution under Climate Change: A Case Study of 731 Urban Areas in China. Sustainable Cities and Society, p.106084.
| Keywords | Climate change; Multi-environmental exposure; Synergistic health risk; Spatial assessment |
|---|---|
| Best Congress Paper Award | Yes |
