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To cope with climate change, it is of great importance to describe the temporal and spatial evolution of climate change vulnerability and its driving factors. Therefore, this paper establishes a comprehensive index of vulnerability to climate change based on the vulnerability scoring diagram (VSD) framework. Moran's I index is used to study the spatial evolution characteristics of vulnerability, and spatial regression analysis is used to explore the factors influencing the spatial distribution of vulnerability. The results show that (1) the climate change vulnerability of China has decreased over time, and the sensitivity state is relatively stable; however, the annual change in exposure and adaptive capacity is significant. (2) The western region of China is more vulnerable than the eastern region, and the most vulnerable provinces are Guizhou and Gansu. (3) The regional vulnerability is generally in a significant spatial agglomeration state. (4) Finally, the driving factors of the spatial distribution of climate change vulnerability include forest coverage, the urban-rural income gap and information technology. These recommendations provide detailed discussions and scientific information for mitigating global warming and formulating long-term emission reduction targets, thereby optimizing resource allocation and providing spatial governance directions for the formulation of adaptation policies. [ABSTRACT FROM AUTHOR]

China's urban environments are particularly vulnerable to flooding due to climate change and rapid urbanization. Study of the urban flood risk analysis has significantly increased over the past decade, and this paper therefore reviews the main results (i.e. theoretical basis, methods, techniques, case studies) obtained in the literature from China. We focus on the following topics: (1) urban flood hazard analysis, (2) exposure and vulnerability analysis, and (3) urban flood risk assessment. Recent advances made in the research area are presented with suggestions for further research to improve the availability and reliability of urban flood risk analysis. [ABSTRACT FROM AUTHOR]

This paper applies climate change scenarios in China based on the SRES assumptions with the help of RCMs projections by PRECIS (providing regional climates for impacts studies) system introduced to China from the Hadley Centre for Climate Prediction and Research at a high-resolution (50 km×50 km) over China. This research focuses on B2 scenario of SRES. A biogeochemical model "Atmosphere Vegetation Integrated Model (AVIM2)" was applied to simulating ecosystem status in the 21st century. Then vulnerability of ecosystems was assessed based on a set of index of mainly net primary production (NPP) of vegetation. Results show that climate change would affect ecosystem of China severely and there would be a worse trend with the lapse of time. The regions where having vulnerable ecological background would have heavier impacts while some regions with better ecological background would also receive serious impacts. Extreme climate even would bring about worse impact on the ecosystems. Open shrub and desert steppe would be the two most affected types. When the extreme events happen, vulnerable ecosystem would extend to part of defoliate broad-leaved forest, woody grassland and evergreen conifer forest. Climate change would not always be negative. It could be of some benefit to cold region during the near-term. However, in view of mid-term to long-term negative impact on ecosystem vulnerability would be enormously. [ABSTRACT FROM AUTHOR]

A persistent concern about the social consequences of climate change is that large, vulnerable populations will be involuntarily displaced. Existing evidence suggests that changes in precipitation and temperature can increase migration in particular contexts, but the potential for this relationship to evolve over time alongside processes of adaptation and development has not been widely explored. To address this issue, we link longitudinal data from 20 thousand Chinese adults from 1989 to 2011 to external data on climate anomalies and use this linked dataset to explore how climatic effects on internal migration have changed over time while controlling for potential spatial and temporal confounders. We find that temperature anomalies initially displaced permanent migrants at the beginning of our study period, but that this effect had reversed by the end of the study period. A parallel analysis of income shares suggests that the explanation might lie in climate vulnerability shifting from agricultural to non-agricultural livelihood activities. Taken together with evidence from previous case studies, our results open the door to a potential future in which development and in situ adaptation allow climate-induced migration to decline over time, even as climate change unfolds. [ABSTRACT FROM AUTHOR]

Extreme heat events have occurred more frequently in China in recent years, leading to serious impacts on human life and the health care system. To identify the characteristics of individuals with heat-related illnesses in China during the summer of 2013, we collected the data from the Heat-related Illness Surveillance System in Chinese Center for Disease Control and Prevention (China CDC). A total of 5758 cases were reported in the summer of 2013, mostly concentrated in urban areas around the middle and lower reaches of the Yangtze River. We found a difference in age distribution of percentage of deaths from heat-related illness between males and females. Severe cases in males mostly occurred in the age group 45-74 years but in females mostly in the age group over 75. A distributed lag non-linear model had been used to identify population vulnerabilities in Ningbo and Chongqing. The results show that there was a clear positive relationship between maximum temperature and heat-related illness, and the heat effect was nonlinear and could last for 3 days. The elderly and males in the range of 45-64 years old might be the most vulnerable people of heat-related illness in China. We also highlighted some deficiencies of the surveillance system, such that the reported data were not accurate, comprehensive, or timely enough at this stage. [ABSTRACT FROM AUTHOR]

Extreme climatic events are likely to adversely affect many countries throughout the world, but the degrees among countries may be different. China and Japan are the countries with high incidences of extreme weather/disaster, both facing with the urgent task of addressing climate change. This study seeks to quantitatively compare the impacts of extreme climatic events on socioeconomic systems (defined as vulnerability) of the two countries by simulating the consequences of hypothetical same degree of electricity disruption along with extreme events. To do that, two computable general equilibrium models are constructed, by using which three-stage scenarios are simulated for China and Japan, respectively. The results reveal that China and Japan have unequal socioeconomic vulnerabilities to extreme events. (1) Negative impact of the same degree of power outages is bigger on China's socioeconomic system than on that of Japan, and this difference is more obvious in the very short-run scenario. (2) The decline of China's GDP, total output, and employment levels is 2-3 times higher than that of Japan, while the difference of the resident welfare levels is sharper, which of China drops 3-5 times of Japan. (3) Structural factors are the main reason for vulnerability differences between China and Japan, including the differences of expenditure structure, factor input structure for production of life requirement sectors, material and energy dependence for the production of industrial sectors, and usage structure of services outputs. Based on these findings, some policy implications and recommendations for fairness issues on climate change adaptation are proposed. [ABSTRACT FROM AUTHOR]

We assessed the vulnerability of 208 endemic or endangered species in China to the effects of climate change, as a part of the project 'Research on China's National Biodiversity and Climate Change Strategy and Action Plans'. Based on the China Species Information System, we selected comprehensive species as analysis targets, covering taxa including mammals, birds, reptiles, amphibians and plants. We applied nine species distribution models in BIOMOD (a package of R software) to estimate the current (1991-2010) ranges and predicted future (2081-2100) ranges of these species, using six climate variables based on Regional Climate Model version 3 (RegCM3) and A1B emission scenario. The model results showed that different taxa might show diverse potential range shifts over time. The range sizes of half of the species (104 species) would decrease, and those of another half would increase. We predicted that the future remaining ranges (intersection of current and future ranges/current ranges) of 135 species would be less than 50 % of their current range sizes. Species that are both endemic and critically endangered would lose more of their range than others. In summary, the most vulnerable species are currently found on the Qinghai-Tibetan Plateau, in the Hengduan Mountain Range, and southern China. Future action plans dealing with climate change in China should be prepared with consideration for vulnerable species and their habitats. [ABSTRACT FROM AUTHOR]

Water scarcity is a common problem in many countries, especially those located in arid zones. The vulnerability of water resources due to climate change is an imperative research focus in the field of water resources management. In this study, a System Dynamics (SD) model was developed to simulate the water supply-and-demand process in Bayingolin, a prefecture in China, and to evaluate water resources vulnerability currently as well as in the future. The model was calibrated and validated using historical data. Three alternative scenarios were designed by changing parameters to test the vulnerability of water resources: i) increase the Wastewater Treatment Rate by 50 %; ii) decrease the Irrigation Water Demand per Hectare by 20 %; iii) increase Total Water Supply by 5 %. Results show that the baseline vulnerability of study region is high. The agricultural irrigation is the largest water use, and the water demand structure will change in future. Decreasing the irrigation water demand is the most suitable intervention to relatively reduce the vulnerability. Results also demonstrated that SD is a suitable method to explore management options for a complex water supply and demand system. [ABSTRACT FROM AUTHOR]