Social vulnerability emphasizes the different burdens of disaster losses within and between places. Although China continuously experiences devastating natural disasters, there is a paucity of research specifically addressing the multidimensional nature of social vulnerability. This article presents an initial study on the social vulnerability of the Yangtze River Delta region in China. The goal is to replicate and test the applicability of the place-based Social Vulnerability Index (SoVI®) developed for the United States in a Chinese cultural context. Twenty-nine variables adapted from SoVI® were collected for each of the 134 analysis units in the study area. Using principal components analysis, six factors were identified from the variable set: employment and poverty, education, poor housing quality, minorities, family size, and housing size—factors similar to those identified for the United States. Factor scores were summed to get the final SoVI® scores and the most and least vulnerable study units were identified and mapped. The highest social vulnerability is concentrated in the southern portions of the study area—Jingning, Suichang, Yunhe, Lanxi, Pan’an, and Shengsi. The least socially vulnerable areas are concentrated southwest, west, and northwest of Shanghai. Limitations of replication are discussed along with policy-relevant suggestions for vulnerability reduction and risk mitigation in China.

In this article, we recall the United Nations’ 30-year journey in disaster risk reduction strategy and framework, review the latest progress and key scientific and technological questions related to the United Nations disaster risk reduction initiatives, and summarize the framework and contents of disaster risk science research. The object of disaster risk science research is the “disaster system” consisting of hazard, the geographical environment, and exposed units, with features of regionality, interconnectedness, coupling, and complexity. Environmental stability, hazard threat, and socioeconomic vulnerability together determine the way that disasters are formed, establish the spatial extent of disaster impact, and generate the scale of losses. In the formation of a disaster, a conducive environment is the prerequisite, a hazard is the necessary condition, and socioeconomic exposure is the sufficient condition. The geographical environment affects local hazard intensity and therefore can change the pattern of loss distribution. Regional multi-hazard, disaster chain, and disaster compound could induce complex impacts, amplifying or attenuating hazard intensity and changing the scope of affected areas. In the light of research progress, particularly in the context of China, we propose a three-layer disaster risk science disciplinary structure, which contains three pillars (disaster science, disaster technology, and disaster governance), nine core areas, and 27 research fields. Based on these elements, we discuss the frontiers in disaster risk science research.

The frequency and intensity of extreme heat wave events have increased in the past several decades and are likely to continue to increase in the future under the influence of human-induced climate change. Exposure refers to people, property, systems, or other elements present in hazard zones that are thereby subject to potential losses. Exposure to extreme heat and changes therein are not just determined by climate changes but also population changes. Here we analyze output for three scenarios of greenhouse gas emissions and socio-economic growth to estimate future exposure change taking account of both climate and population factors. We find that for the higher emission scenario (RCP8.5-SSP3), the global exposure increases nearly 30-fold by 2100. The average exposure for Africa is over 118 times greater than it has been historically, while the exposure for Europe increases by only a factor of four. Importantly, in the absence of climate change, exposure is reduced by 75–95% globally and across all geographic regions, as compared with exposure under the high emission scenario. Under lower emission scenarios RCP4.5-SSP2 and RCP2.6-SSP1, the global exposure is reduced by 65% and 85% respectively, highlighting the efficacy of mitigation efforts in reducing exposure to extreme heat.