This study analyzed mortality change rate (MCR: daily change rate of mortality at a given temperature per average summer mortality) for 229 municipalities in Korea considering age, occupation, household type, chronic diseases, and regional temperature distribution. We found that the MCR for heat wave differs depending on socioeconomic factors and the temperature distribution in the region. The MCRs for the elderly (≥65 years of age), outdoor workers, one-person households, and chronic disease patients start to increase at lower temperatures and react more sensitively to temperature than others. For the socioeconomic factors considered in this study, occupation was found to be the most significant factor for the MCR differences (outdoor workers 1.17 and others 1.10 above 35 °C, p < 0.01). The MCRs of elderly outdoor workers increased consistently with temperature, while the MCRs of younger outdoor workers decreased at 33 °C, the heat wave warning level in Korea. The MCRs in lower temperature regions start to increase at 28 °C, whereas the MCRs start to increase at 30 °C in higher temperature regions. The results of this study suggest that heat wave policies should be based on contextualized impacts considering age, occupation, household type, chronic disease, and regional temperature distribution.
Climate action is goal 13 of UN’s 17 Sustainable Development Goals (SDG). Future impacts of climate change depend on climatic changes, the level of climate change policy, both mitigation and adaptation, and socio-economic status and development pathways. To investigate the climate change policy impact of socio-economic development pathways, we develop three pathways. Climate change affects socio-economic development in many ways. We interpret global storylines into South Korean contexts: Shared Socio-economic Pathway 1 (SSP1), SSP2, and SSP3 for population, economy, and land use. SSP elements and proxies were identified and elaborated through stakeholder participatory workshops, demand survey on potential users, past trends, and recent national projections of major proxies. Twenty-nine proxies were quantified using sector-specific models and downscaled where possible. Socio-economic and climate scenarios matrixes enable one to quantify the contribution of climate, population, economic development, and land-use change in future climate change impacts. Economic damage between climate scenarios is different in SSPs, and it highlights that SSPs are one of the key components for future climate change impacts. Achieving SDGs generates additional incentives for local and national governments as it can reduce mitigation and adaptation policy burden.
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