Lake eutrophication and algal bloom is one of the most important environmental problems facing China's lakes, and it is also the focus of lake eutrophication control of the world's attention. The monitoring data on chlorophyll concentration was analyzed every one month, combined with corresponding weather conditions from 2004 to 2006. According to the degree of eutrophication in Taihu Lake, it is divided into five Lakes: heavy eutrophication region V, eutrophication region IV, middle-level eutrophication region III, light eutrophication region II and nutrition region I. Based on fuzzy factor optimization method, the average wind speed, average pressure, average temperature and sunshine hours was selected to discuss the influence mechanism of meteorological factors on the algae bloom in Taihu Lake. Considered the four meteorological factors as the input layer nodes, BP neural network model was applied to build the zoning monitoring and early warning model of blue algae in Taihu Lake.

Based on the latest national carbon dioxide emissions data released from the International Energy Agency (IEA), the carbon dioxide emissions trends of BRICS were analyzed in three aspects: the total carbon dioxide emissions, the emission intensity calculated using purchasing power parties (PPP) and per capita carbon dioxide emissions. The results show that the total carbon dioxide emissions among BRICS presented an increasing trend in different extent. On the other hand, the emission intensity calculated using PPP of BRICS showed a decreasing trend. The per capita carbon dioxide emissions of BRICS also presented an increasing trend in different extent. The Russian Federation and South Africa’s per capita carbon dioxide emissions were higher than the World’s average level, whilst those of India, Brazil and China were lower than the World’s average level, which is far less than the level of the OECD countries.

This paper analyzed the excess mortality change in nine districts of Nanjing city, based on mortality data and meteorological data from 2004 to 2010. Taken a typical heat waves process in summer of 2006 as an example, it was discussed of the effect of the heat process on different gender, different age groups , and various disease death toll and excess mortality changes. The excess mortality was associated with the average maximum temperature and average minimum temperature during the heat waves. Excess mortality occurred in the middle of June heat wave when excess mortality was much higher than in other time periods. In late June, early July to early August, the excess mortality is relatively small. The average daily deaths are increasing with increasing age for male and female, and every age death numbers is higher than that with no heat waves during the heat wave period. In addition to the respiratory system diseases, diseases of the genitourinary system, other diseases, residual disease in the heat waves has increased, and diseases of the nervous system and the endocrine system diseases of excess mortality rate reached a staggering 342.93% and 119.63%, accounting for almost half of the total heat excess mortality. The heat waves effect is very obvious. The conclusion is of great significance for prevention of high temperature heat harm.

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