This research offers a new framework for assessing social vulnerability to climate change. A social vulnerability assessment trial was carried out for Chinese coastal cities at the county level. First, the 10 factors having the most influence on social vulnerability were identified. They are “House with no lavatory”, “House with no bath facilities”, “Employees in primary industry”, “Houses with no tap water”, “GDP in primary sector”, “Children”, “House with no kitchen”, “Rate of natural increase (RNI), “Employees in management sector”, and “Highly educated”. Second, indexes of social vulnerability, exposure, sensitivity, and adaptability were evaluated and mapped to examine their spatial pattern. The results demonstrate that the distribution of exposure index (EI) is similar to that of social vulnerability index (SVI): many counties are categorized at the medium level while a few counties belong to the high or low categories. The distribution of adaptability proves that it should be paid more attention, as 30.14% of its counties belong to the lowest level. After calculating the Getis-Ord Gi* statistic of SVI, two cold spots and two hot spots are identified. Third, the relationship between urban development and social vulnerability are discussed. During urbanization, there are evident differences of SVI between urban and rural areas. Urbanization can help city districts reduce social vulnerability, while creating more social vulnerability in the coastal counties. For the districts, more adjustment strategies and work should be applied in the dimension of exposure during urbanization. For the counties, the prominent problem to be faced is an increase in sensitivity.

Many frequent and severe air pollution incidents have emerged across the vast parts of China recently. The identification of factors and mapping social vulnerability has become extremely necessary for environmental management and sustainable development. However, studies associating social vulnerability with air pollution remain sparse. With reference to research achievements of social vulnerability, this study made a new trial regarding social vulnerability assessment to air pollution. With the projection pursuit cluster (PPC) model, the top three factors contributing to social vulnerability index (SVI) were discovered and SVI and SVI dimensions (susceptibility, exposure, and adaptability) were evaluated. Results revealed that adaptability values are higher than susceptibility and exposure values. SVI is in a poor condition as, for the whole region, most values belong to the high-medium level. High SVI values mainly appear in the northern and the southern ends of study area. SVI in Shanghai is lower than in Jiangsu and Zhejiang provinces. On the scale of prefecture-level city, it can be found that the low-value centers of SVI always occurred in urban core areas. The spatial variation and inequality in social vulnerability provide policy-makers a scientific basis for air pollution prevention and sustainable management.