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The gale disaster brought by the typhoon has affected the eastern coastal area of China greatly. That being so, the research on the distribution character of the on-shore gale caused by the typhoon is of great significance to guard against typhoon disasters. This article, based on 233 wind observation stations' wind speed data in eastern coastal area of China, extracted each station's annual maximum wind speed sequence, selected the Weibull and Pearson-III extreme value distribution models to fit the sequence, and used the Kolmogorov test method and the residual sum of squares to test the fitting effect. The Weibull distribution model was selected as the better distribution model when reflecting the disaster risk character of typhoon gales in eastern coastal area of China, then the extreme risk scenarios under 20, 50, and 100 year return periods were built to analyze the spatial distribution characteristics of the typhoon gale disaster risk. The results show that the southeastern coastal area totally has a comparatively high risk, and the coastal area of Zhejiang and Hainan, Leizhou Peninsula belong to the extreme risk regions in the study area, with the overall risk of the northern region being lower than the south in the study area, only part of Shandong Province has a slightly higher risk than the northern region. The typhoon gale risk scenario analysis method is based on extreme value distribution model established by this study has a certain significance to study the gale risk in eastern coastal area of China.

Oceanic disasters, especially the storm surge hazard, occur with increasing frequency and intensity in coastal areas. Yang Shan Deep-water Port, the most important gateway of China to the world, is exposed to a high disaster risk. The analysis of its hazard-formative environment is the basic work to find appropriate measures to reduce the risk. In this work, the evolution of the hazard-formative environment of storm surge hazard in Yang Shan Deep-water Port is studied systematically by Geographic Information System (GIS) spatial analysis techniques. The results indicate that the hazard-formative environment in Yang Shan Port has changed a lot due to human disturbance in recent years, and the evolution of this environment will lead to a higher potential risk of disaster with global climate change.

Differences in spatial scale appear in expression of natural disaster risk. The large-scale region spans up to global level, regional (continental) level, watershed level of major rivers, the natural regional and national level. Grasping the principle of “good order, reasonable distribution”, the expression of disaster risk map focuses on regional risk general trends and macroeconomic situation. The meso-scale regions contain natural areas, sub-districts, the provinces, cities, regions of administrative division. Risk zoning services are for the regional long-term disaster prevention and mitigation planning. It also provides accurate background parameters for small-scale disaster risk assessment. The small-scale regions include natural state, the district, county, town, village, streets and communities of the administrative divisions. The risk characterization of affected areas is to improve the accuracy of vulnerability assessment. It is also provide technical methods for disaster risk assessment.

Urban natural disaster risk research is one of the effective ways on urban regional implementation of risk reduction and mitigation strategies. Disaster risk assessment and zoning is the frontier and hot issue in international disaster risk field. Geographic Information System (GIS) technology is an important aiding tool for natural disaster risk researches. Over the past five years, we studied the integrated toolkit for urban natural disaster risk research supported by Shanghai Youth Science and Technology Venus Program (09QA1401800) ‘Natural disaster risk assessment and zoning in Shanghai based on the scenarios simulation technology’ and National Science Key Foundation in China (40730526) ‘Study on natural disaster contingency planning for China's coastal cities based on risk scenario analysis’. The integrated toolkit system was designed and developed based on ArcEngine 9.3 components technology, NET Framework development environment, and C# language, it includes five functional modules: (1) evolution analysis of hazard-formative environments, (2) hazard analysis of disaster-making factors, (3) vulnerability assessment of hazard-affected bodies, (4) disaster loss assessment and risk zoning, and (5) simulation of disaster emergency shelter. The integrated toolkit can be used by the government to establish urban natural disaster mitigation strategies.

China's coastal region is physically and socio-economically vulnerable to accelerated sea-level rise and associated coastal flooding because of its low topography, highly developed economy and highly-dense population. In this study, we present a scenario of sea level rise and storm surge flooding along the China's coastal region over the next century and apply them to a digital elevation model (DEM) which acquired by the shuttle radar topography mission (SRTM) to illustrate the extent and spatial distribution to which coastal areas are susceptible to permanent inundation and episodic flooding due to storm events. To perform flood scenario analysis and vulnerability assessment, a method for producing several sets of data was implemented by combining remote sensing processing, the use of grid-based socio-economic data, and subsequent analysis using Geographical Information Systems (GIS). This analysis shows that inundation and coastal flooding will mainly occur in the major delta without the protection of dike systems. However, due to the concentration of population and economic activities in China's coastal region, societal and economic consequences of continued sea-level rise would be substantial. Finally, some suggestions are presented for decision-makers, and other concerned stakeholders to develop appropriate public policies and mitigation measures.

Atmospheric deposition samples were collected and analyzed from 50 sampling sites in Baoshan district, Shanghai. The results show that the average concentration of Pb, Cr, Cd, Zn and Cu is 281.88, 254.45, 7.06, 2433.92 and 331.08mg•kg-1 respectively, which are much higher than background values of soil in Shanghai. The spatial distribution features of five heavy metals illustrate higher concentrations in industrial and heavy traffic areas. The order of potential ecological risk is Cd> Cu> Pb> Zn> Cr. Baoshan is suffering a considerable risk, and metal contamination in this district is serious.