The paper defined the concept of dual water carrying capacity based on water balance of different water quality and addressed a new method of determining forewarning classification according to timing of water shortage. A forewarning model of dual water carrying capacity was established based on system dynamics model. Taking the upstream of Niulanjiang watershed as a case study, the dual water carrying capacity was assessed and predicted by the model. Results show that under business as usual scenario, water resources of high quality will reach blue early warning and that of ordinary quality will reach yellow early warning. To meet the requirement of water diversion in the area, only low rate of socioeconomic development can be sustained in the area while environment protection measures has to be made at medium or above level.

Taking Lake Dianchi Watershed as study area, the dynamics change degree of land use types in the watershed was analyzed based on interpretation data from TM image in 1990 and 1999. The direction of land use conversion was quantitatively analyzed by land use transfer matrix based on the Markov model. Meanwhile, land use change tendency of 2008 was simulated and forecasted based on land use conversion rules using multi-criteria evaluation method from GIS and combining with CA-Markov model. Compared with the interpretation data of 2008, Kappa coefficient of the simulated results was 0.7338, indicating that the simulated results were credible. The spatial patterns of land use change in 2017 and 2026 were simulated by using CA-Markov model. The results show that land use change is also active in this watershed and ecological restoration and reconstruction is still confronted with pressure. Farmland, forest, water and unused land will reduce from 2008 to 2026, while the grassland and construction land will continue to increase. Compared with the trend of land use from 1990 to 2008, the simulated result indicate that farmland, forest and construction land from 2008 to 2026 will keep the same change trend while grassland, water and unused land show the opposite change trend. Construction land will expand on the basis of the present and the change of water is little. Although forest resources will decrease in future, it is still the main land use types in watershed. Construction land expansion significantly increases the load of non-point source pollution in Dianchi. Unreasonable land use is one of the major causes of the water quality degradation in Dianchi Lake currently, and it is going to increase the pressure on the water environment and ecology of water basin in the future. Therefore, to maintain enough arable land per capita, lower fertilization strength, improve land utilization levels, keep a sufficient amount of ecological land, use construction land frugally and intensively, are some important measures to reduce the potential of non-point source pollution in the area. The research can provide scientific support for rational planning and management of land use, the policies formulating of ecological restoration and economic development.

Based on NANI calculator, statistic data and parameter from 358 cities of China (Hong Kong, Macao and Taiwan are not included) are applied to assess net anthropogenic nitrogen input (NANI) at China’s city scale. On average, NANI of Mainland China has reached to 45.15 Tg in 2010, and on a per area basis the value is 4716 kg/km², which is 3 times than world average level. Nitrogen fertilizer input dominates NANI budget items, which accounts for 65.0% of the total, net food and feed input (21.4%), oxide N deposition (7.3%) and crop fixation (6.5%) follow. On geographical basis, NANI of the 358 cities has an obvious characteristic of regionalization, and high value areas appear in cropland and population concentrated places. Compared to province scale data, data on city scale is more effective to assist in discerning key regions, which is able to control more nitrogen input with smaller control area.

The observations of ozone sounding at Shanghai Baoshan National Climate Stations during May 2007 and December 2009 are analyzed. The results show that ozone vertical distribution is mainly influenced by photochemistry and dynamic transport. Ozone distribution in the boundary layer and the middle and upper stratosphere is apparently influenced by photochemistry. In the boundary layer, ozone concentration gradient varies positively. Influencing factors such as temperature, radiation and vapor, lead to a seasonal variation of highest ozone in the summer and lowest ozone in the winter. Above 26 km, photochemical processes lead to the highest ozone concentrations in the middle and upper stratosphere in the summer, vice versa in the winter. Dynamic transport significantly influences ozone level in upper troposphere and lower stratosphere, about 10-17 km. Ozone concentration is highest in spring due to the process of stratosphere-troposphere exchange.